Environmental chemistry : undergraduate and graduate classroom, laboratory, and local community learning experiences 9780841232853, 0841232857, 9780841232860

Table of contents :
Content: Introduction to Environmental Chemistry of the Arctic: An Introductory, Lab-Based Course Offered Both Face-to-Face and by Distance / Guerard, Jennifer J., Department of Chemistry and Biochemistry, University of Alaska Fairbanks, 900 Yukon Dr., Fairbanks, Alaska 99775, United States
Hayes, Sarah M., Department of Chemistry and Biochemistry, University of Alaska Fairbanks, 900 Yukon Dr., Fairbanks, Alaska 99775, United States, Present address: Eastern Mineral and Environmental Resources Science Center, U.S. Geological Survey, 954 National Center, Reston, Virginia 20192, United States / Community-Based Undergraduate Research: Measurement of Hazardous Air Pollutants with Regard to Environmental Justice / Zimmermann, Kathryn, School of Science and Technology, Georgia Gwinnett College, 1000 University Center Lane, Lawrenceville, Georgia 30043, United States
Young, Laura, School of Liberal Arts, Georgia Gwinnett College, 1000 University Center Lane, Lawrenceville, Georgia 30043, United States
Woodard, Kelsey, Center for Teaching Excellence, Georgia Gwinnet College, 1000 University Center Lane, Lawrenceville, Georgia 30043, United States / Undergraduate Research Experience in Remote Sensing / Kahl, A. / Trends in Atmospheric Ammonia: An Environmental Chemistry Class Project / Ezeh, Vivian C. / Using DNA Barcoding To Identify Duckweed Species as Part of an Undergraduate Ecology Course / Baker, Stokes S. / Synthesis of a Novel Series of Nitrogen-Containing Ligands for Use as Water Remediators, All Incorporating Long-Chain Aliphatic Moieties / Pothoof, Justin
Bhagwagar, Michele
Nguyen, Grace
Tinawi, Sara
Makki, Sara
Benvenuto, Mark A. / Analysis of Cosmetic Mineral Eyeshadows and Foundations with a Handheld X-ray Fluorescence Analyzer / Ngo, Tiffany Tieu
Thomas, Sara
Stokes, Diamond
Benvenuto, Mark A.
Roberts-Kirchhoff, Elizabeth S. / Arctic Communities as Sites of Local Field Work in Environmental Chemistry / Hermanson, Mark H., Hermanson & Associates, LLC, 2000 53rd St. W., Minneapolis, Minnesota 55419, United States
Le Cras, Sydney, Department of Natural Resources Management & Environmental Sciences, California State Polytechnic University, 180 North Poly View Drive, San Luis Obispo, California 93407, United States / Mapping of Brownfield Properties in the Detroit Community Using GIS / Rihana-Abdallah, Alexa
Pang, Yuncong / Editors' Biographies /

Citation preview

Environmental Chemistry: Undergraduate and Graduate Classroom, Laboratory, and Local Community Learning Experiences

ACS SYMPOSIUM SERIES 1276

Environmental Chemistry: Undergraduate and Graduate Classroom, Laboratory, and Local Community Learning Experiences Elizabeth S. Roberts-Kirchhoff, Editor University of Detroit Mercy Detroit, Michigan

Mark A. Benvenuto, Editor University of Detroit Mercy Detroit, Michigan

Sponsored by the ACS Division of Environmental Chemistry, Inc.

American Chemical Society, Washington, DC Distributed in print by Oxford University Press

Library of Congress Cataloging-in-Publication Data Names: Roberts-Kirchhoff, Elizabeth S., editor. | Benvenuto, Mark A. (Mark Anthony), editor. | American Chemical Society. Division of Environmental Chemistry. Title: Environmental chemistry : undergraduate and graduate classroom, laboratory, and local community learning experiences / Elizabeth S. Roberts-Kirchhoff, editor (University of Detroit Mercy, Detroit, Michigan), Mark A. Benvenuto, editor (University of Detroit Mercy, Detroit, Michigan) ; sponsored by the ACS Division of Environmental Chemistry, Inc. Description: Washington DC : American Chemical Society, [2018] | Series: ACS symposium series ; 1276 | Includes bibliographical references and index. Identifiers: LCCN 2018018539 (print) | LCCN 2018020709 (ebook) | ISBN 9780841232853 (ebook) | ISBN 9780841232860 Subjects: LCSH: Environmental chemistry. | Air--Pollution--Research. | Cosmetics--Analysis. Classification: LCC TD193 (ebook) | LCC TD193 .E57 2018 (print) | DDC 577.27--dc23 LC record available at https://lccn.loc.gov/2018018539

The paper used in this publication meets the minimum requirements of American National Standard for Information Sciences—Permanence of Paper for Printed Library Materials, ANSI Z39.48n1984. Copyright © 2018 American Chemical Society Distributed in print by Oxford University Press All Rights Reserved. Reprographic copying beyond that permitted by Sections 107 or 108 of the U.S. Copyright Act is allowed for internal use only, provided that a per-chapter fee of $40.25 plus $0.75 per page is paid to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. Republication or reproduction for sale of pages in this book is permitted only under license from ACS. Direct these and other permission requests to ACS Copyright Office, Publications Division, 1155 16th Street, N.W., Washington, DC 20036. The citation of trade names and/or names of manufacturers in this publication is not to be construed as an endorsement or as approval by ACS of the commercial products or services referenced herein; nor should the mere reference herein to any drawing, specification, chemical process, or other data be regarded as a license or as a conveyance of any right or permission to the holder, reader, or any other person or corporation, to manufacture, reproduce, use, or sell any patented invention or copyrighted work that may in any way be related thereto. Registered names, trademarks, etc., used in this publication, even without specific indication thereof, are not to be considered unprotected by law. PRINTED IN THE UNITED STATES OF AMERICA

Foreword The ACS Symposium Series was first published in 1974 to provide a mechanism for publishing symposia quickly in book form. The purpose of the series is to publish timely, comprehensive books developed from the ACS sponsored symposia based on current scientific research. Occasionally, books are developed from symposia sponsored by other organizations when the topic is of keen interest to the chemistry audience. Before agreeing to publish a book, the proposed table of contents is reviewed for appropriate and comprehensive coverage and for interest to the audience. Some papers may be excluded to better focus the book; others may be added to provide comprehensiveness. When appropriate, overview or introductory chapters are added. Drafts of chapters are peer-reviewed prior to final acceptance or rejection, and manuscripts are prepared in camera-ready format. As a rule, only original research papers and original review papers are included in the volumes. Verbatim reproductions of previous published papers are not accepted.

ACS Books Department

Contents Preface .............................................................................................................................. ix 1.

Introduction to Environmental Chemistry of the Arctic: An Introductory, Lab-Based Course Offered Both Face-to-Face and by Distance ......................... 1 Jennifer J. Guerard and Sarah M. Hayes

2.

Community-Based Undergraduate Research: Measurement of Hazardous Air Pollutants with Regard to Environmental Justice ....................................... 21 Kathryn Zimmermann, Laura Young, and Kelsey Woodard

3.

Undergraduate Research Experience in Remote Sensing .................................. 49 A. Kahl

4.

Trends in Atmospheric Ammonia: An Environmental Chemistry Class Project ..................................................................................................................... 57 Vivian C. Ezeh

5.

Using DNA Barcoding To Identify Duckweed Species as Part of an Undergraduate Ecology Course ............................................................................ 67 Stokes S. Baker

6.

Synthesis of a Novel Series of Nitrogen-Containing Ligands for Use as Water Remediators, All Incorporating Long-Chain Aliphatic Moieties .......... 81 Justin Pothoof, Michele Bhagwagar, Grace Nguyen, Sara Tinawi, Sara Makki, and Mark A. Benvenuto

7.

Analysis of Cosmetic Mineral Eyeshadows and Foundations with a Handheld X-ray Fluorescence Analyzer .............................................................. 89 Tiffany Tieu Ngo, Sara Thomas, Diamond Stokes, Mark A. Benvenuto, and Elizabeth S. Roberts-Kirchhoff

8.

Arctic Communities as Sites of Local Field Work in Environmental Chemistry .............................................................................................................. 105 Mark H. Hermanson and Sydney Le Cras

9.

Mapping of Brownfield Properties in the Detroit Community Using GIS ..... 125 Alexa Rihana-Abdallah and Yuncong Pang

Editors’ Biographies .................................................................................................... 135

vii

Indexes Author Index ................................................................................................................ 139 Subject Index ................................................................................................................ 141

viii

Preface “We do not inherit this land from our parents. We borrow it from our children.” - Amish saying, or Native American Proverb, or Chief Seattle There is probably no more direct connection between the science of chemistry and our modern society than that encompassed in the field we now call environmental chemistry. As populations have grown, and population density in certain areas has increased dramatically, the impact of all human presence on our air, water, and soil has become pronounced. In many cases, the impact has been negative, yet every human being must leave some footprint of their time on Earth, no matter how small. This makes it important that we examine our surroundings in some detail. This book has its roots in the symposium: “Environmental Chemistry: Undergraduate and Graduate Classroom, Laboratory, and Local Community Learning Experiences” held in 2017 at the 253rd National Meeting of the American Chemical Society in San Francisco, CA. There were several excellent presentations there, which we wished to capture. There are also some authors in this volume who were unable to attend, but who are doing good work in the field today. We have an impressive collection of ways that environmental chemistry is explored by both undergraduate and graduate students in independent research projects and course-based undergraduate research experiences. Students are exploring these topics in interdisciplinary groups both within their institution and the greater community. For example, Guerard and Hayes (Chapter 1) describes a novel entry-level environmental chemistry course with students onsite working collaboratively with students at distant sites focused on the chemistry of the Arctic. In a community-focused project, Zimmerman et al. (Chapter 2) reports on the passive sampling of air pollutants in local communities as an interdisciplinary project by students from political science and basic science working with professionals from a local environmental law firm. Kahl (Chapter 3) details a collaboration between faculty and students from several campuses to support a network of data loggers to collect information on water quality across western Pennsylvania, while Ezeh (Chapter 4) reports on a course-based research experience where data on atmospheric ammonia was collected. An interesting use of DNA barcoding to catalog the varieties of duckweed in Michigan waters as part of an undergraduate ecology course is described by Baker (Chapter 5). Benvenuto and his students (Chapter 6) report on the synthesis of a novel set of ligands designed to chelate metal ions in aqueous systems. Roberts-Kirchhoff, Benvenuto and their students (Chapter 7) describe the results from the elemental analysis of consumer products. Hermanson and LeCras (Chapter 8) describe ix

a second example of students involved in collecting data on environmental chemistry in the Arctic with their report of the analysis of atmospheric mercury and flame retardants. We conclude the volume with Rihana-Abdallah and Pang’s summary (Chapter 9) of brownfields in both Michigan and Detroit, a city that has played a major role in the industrialization of America. We believe this book has the potential to become an important piece of the greater mosaic that is an understanding of the factors which make up the chemistry of our local, regional, and global environment, and to make the current ideas and this discussion available to a much wider audience. We hope that the chapters herein inspire our readers to execute further projects and deeper study of our local and greater environment. It is indeed worth remembering that we only borrow what we use today from our children’s generation.

Elizabeth S. Roberts-Kirchhoff, Ph.D. Assistant Dean for Academics College of Engineering & Science University of Detroit Mercy Detroit, Michigan, United States [email protected] (e-mail)

Mark A. Benvenuto, Ph.D. Fellow, American Chemical Society Professor and Department Chair University of Detroit Mercy Detroit, Michigan, United States [email protected] (e-mail)

x

Chapter 1

Introduction to Environmental Chemistry of the Arctic: An Introductory, Lab-Based Course Offered Both Face-to-Face and by Distance Jennifer J. Guerard1 and Sarah M. Hayes*,1,2 1Department of Chemistry and Biochemistry, University of Alaska Fairbanks, 900 Yukon Dr., Fairbanks, Alaska 99775, United States 2Present address: Eastern Mineral and Environmental Resources Science Center, U.S. Geological Survey, 954 National Center, Reston, Virginia 20192, United States *E-mail: [email protected]. Phone: 703-648-6461.

In this chapter, we present a model for an entry-level lab-based undergraduate environmental chemistry course delivered simultaneously by face-to-face and distance modalities. This course frames conceptual chemistry using the theme of Alaskan Arctic environmental issues in order to increase engagement and perceived relevance of chemical principles. Synchronously delivered lectures and guided discussions along with the incorporation of peer-mentored research projects encourage the development of a learning community among students in the course. Distance students participate in the same virtual and “kitchen” lab experiments as on-campus students, thus providing an educationally equivalent curriculum to all. In mixed teams of on-campus and distance students, all students participate in research projects to allow entry-level students to explore their interests in STEM fields. Students thereby begin to build an identity as a scientist and hopefully this course will serve as a mechanism to improve recruitment and retention of students, especially from traditionally underrepresented groups, in the chemical sciences and other STEM fields of study. Responses from the first course offering communicated positive attitudes toward the course content and methods.

© 2018 American Chemical Society

Introduction Alaska and the Arctic: A Contextually Relevant Framework for Environmental Chemistry Environmental chemistry has been increasingly introduced into undergraduate curricula in recent decades (e.g., (1–4)). Contextually driven activities improve both understanding and engagement in undergraduate courses by highlighting the relevance of chemistry and its application to the real world (4). Environmental chemistry is an especially useful context in which to present chemical concepts, especially for non-majors (3). Incorporating environmental and climate-change issues into chemistry courses has been shown to improve scientific literacy and conceptual understanding (5, 6). High-latitude systems are especially sensitive to changes in climate. The Arctic has continued to see air temperatures increasing at double the global average rate, bringing with them a host of environmental changes from decreases in sea-ice extent to thawing permafrost (7). Alaska represents a diverse set of ecosystems from coastal Western hemlock-Sitka spruce forests to the treeless Arctic plains (8). Wetlands cover an extraordinarily high proportion of Alaska, occupying 43% of Alaska’s surface area compared to only around 5% of land surface area in the lower 48 states (9). The fate and transport of contaminants in the Arctic is also of concern, as organic contaminants have been observed to undergo long-range transport to high latitudes (10). Thus, assessing surface water quality is critically important for understanding Alaska’s environmental health. This is especially true in rural communities, where residents live in close connection to and rely upon their environment. Environmental stresses affect subsistence practices, food availability, water quality, and infrastructure, among many other aspects of life (11–15). Many Alaskans connect with the One Health paradigm, i.e. the idea that the health of humans, animals, and the environment are inextricably linked (13, 16, 17). As such, Alaska and the Arctic are an ideal backdrop against which to highlight environmental chemical processes in atmospheric, aquatic, terrestrial, and biological spheres, in addition to being directly relevant to communities within the state. Course-Based Undergraduate Research and Peer Mentoring The demonstrated benefits of incorporating research into course curricula are well known (e.g., (18)), suggesting that research not only affects attitudes toward the relevance of chemistry (5), but also improves confidence, understanding, and success in later courses (19–22). Undergraduate involvement in research has also been linked to improved critical thinking, intellectual independence, and increased retention in fields related to STEM (23). Mentoring has specifically been observed to improve the student research experiences and retention of students from traditionally underrepresented groups (24, 25). Mentored research early in the undergraduate experience, particularly that which blends both faculty and near-peer mentoring, can be an effective method for integrating students into the research process (e.g., (26, 27)). Effective mentoring has been linked to increased independence and competency (28–31), as 2

well as improved retention (24, 32, 33). Peer mentoring in research contexts, when undergraduates mentor each other, is viewed positively by undergraduates and have benefits including becoming part of a community, growth of self-confidence, and a sense of accomplishment (34). These factors are important for persistence within STEM (35). Further, studies have shown that peer instruction can lead to improved conceptual understanding (36, 37). While traditional undergraduate research provides many benefits such as those listed above, course-based research is also beneficial to students. Participation in a classroom-based research experience at the introductory level has been linked to positive changes in student interest toward pursuing science careers and attitudes toward science in general (38). Course-based research experiences are also attractive to students because of the finite time commitment required (39). Course-based research experiences have been shown to provide several benefits that promote inclusion, that may be especially important for traditionally underrepresented students, including: improving awareness of research opportunities, learning of the benefits of research, and providing interactions with faculty (40). Together, these benefits may serve as a gateway to future more traditional undergraduate research experiences. Engagement Challenges with Distance Learning Course-based research is an example of integrating active learning techniques in the classroom, and has been shown to statistically improve student grades, long term comprehension (41, 42), and reduce the achievement gap between disadvantaged students and their peers (43). These techniques are supported by pedagogical studies that have concluded that classroom lecture learning accounts for less than 10% of the lifetime learning (44). The effectiveness of a variety of active learning techniques has been demonstrated, including: case studies, student discussions, lecture pauses, and involving students as creators. However, incorporating active learning techniques in distance courses can be especially challenging. This Study The authors developed a blended face-to-face and distance lecture and lab-based course that interweaves Alaska and Arctic-relevant issues throughout the curriculum, emphasizing chemical principles and their roles in the environment. This course incorporates active learning in several forms as well as faculty-directed and peer-mentored research projects. In keeping with best practices (45), the curriculum deliberately integrates the face-to-face and distance courses by mixing student teams to facilitate the development of learning relationships between students. We have intentionally designed an environmental chemistry course that involves students as both researchers and peer mentors to strengthen the sense of a learning community among participants. This course engages students in all aspects of the research cycle, including: developing laboratory techniques, applying the scientific method, making and recording careful observations, interpreting numerical data, and sharing their results. 3

Thus, entry-level students learn introductory chemical concepts by engaging in faculty-directed research and exploring the status of environmental health in Arctic ecosystems and communities.

Rationale In this chapter, we describe a model for a lab-based course offered simultaneously by on-campus and distance modalities in which chemistry is taught in the context of Arctic environmental health. The target demographics are early career or nontraditional undergraduate students regardless of their physical location within Alaska or declared major of study. As a core-designated course, this course is accessible and attractive to students from diverse majors of study and will hopefully serve as a mechanism to build science literacy across the state. Distance learning is a particularly important method of instruction for Alaska because, being the largest state in the United States, it has many rural communities that are separated by large distances and not connected by roads (Figure 1). In 2000, Alaska had less than 13,000 miles of public road (46). In fact, several unique factors can impact the student experience at distance campuses or in rural communities in Alaska compared to most locations in the rest of the U.S. These include: limited bandwidth for internet connectivity, below freezing temperatures for most of the academic year, and most outlying communities are not connected to the road system, meaning materials have to be transported either by water during the summer or by air. All of these factors must be taken into account when planning a successful lab and field-based distance course like the one described here. The University of Alaska system has a high proportion of non-traditional and rural students. It is common for students to take courses online, though there are currently few offerings in chemistry or that incorporate research, and few undergraduate environmental chemistry courses (distance or face-to-face), especially targeting early undergraduates. This was seen as a great opportunity to make chemistry relevant for our students by applying it to the Arctic environment where they live and capitalizing on faculty research expertise. This course was designed to attract students early in their post-secondary education in order to provide a course-based lab and peer-mentored research experience by distance, in hopes of improving STEM recruitment and retention. Students are expected to come to this course with no previous research experience. They are guided through small but highly relevant research projects examining surface waters from their home communities. The project portion is intentionally designed to involve students as both researchers and peer mentors (Figure 2). In cooperation with other members of their research teams (which are ideally mixed between face-to-face and distance students), students examine water quality indicators within the context of human, animal, and ecosystem health. In this way, we are directly incorporating One Health relevant research into the curriculum in a way that is accessible to students with little prior science knowledge.

4

Figure 1. This course is offered in both distance and on-campus modalities to allow students in rural communities across Alaska to participate and build relationships with students on-campus. Alaska has unique challenges, including a very limited road system.

We hope to recruit or retain nontraditional STEM majors, who might not be as successful starting off in a more traditional, calculation-based general chemistry setting. Applying conceptual chemistry in the context of Arctic environmental health is aimed to frame the content in an especially relevant and accessible format for rural Alaskans. Engaging students in research empowers them to assess the health of their home communities. Further, building personal relationships between rural students and the main University of Alaska Fairbanks (UAF) campus could support rural students interested in finishing their degree program at UAF. Degree requirements include core courses, which are designed to provide “students with a shared foundation of skills and knowledge that, when combined with specialized study in the major and other specific degree requirements, prepares students to better meet the demands of life in the 21st century” (47). These core requirements include eight credits of natural science, which are fulfilled by taking two specially designated lab-based courses selected from the 100 and 200-level science classes. 5

Enrollments were capped such that there was a limit of twice as many face-to-face students as distance students, to best facilitate the integrated group research projects with mixed teams of distance and on-campus students. The ratio of distance to face-to-face students with regards to this course and student success has not yet been thoroughly tested, and are open to adjustment in the future depending on the composition of the research groups in future deliveries.

Figure 2. Theoretical framework for faculty-guided research projects and mentoring of research teams made up of on-campus and distance students.

Student Learning Outcomes This course was intentionally designed to require less advanced math prerequisites compared to that required by most STEM core courses at UAF, in order to reach students early in their post-secondary experience and remove barriers for exposure to the chemical sciences. Taken directly from the syllabus (48), after successful completion of this course, students will be able to: 1. 2. 3. 4.

Understand the basic chemical concepts as they relate to the function of ecosystems and the existence/transformation of contaminants. Outline basic metrics for assessing air, water, and soil quality and explain their importance as indicators of environmental health. Identify examples of anthropogenic influences of natural cycles and explain how that impacts ecosystem health. Evaluate student-generated water quality data from across the state and interpret data to assess anthropogenic perturbation of ecosystems.

Each of these student learning outcomes were integrated throughout the entire course, through synchronous lecture, discussion, laboratory, and peer-mentored research activities as described below.

6

Implementation Successful execution depends on developing strong integration between lab and lecture topics (Table 1), creating lab kits with clear instructions, integrating tablet technologies to create a seamless interface between on-campus and distance students, and supporting teams in forming strong collaborations. The course syllabus is available from the UAF Department of Chemistry and Biochemistry website and a course schedule is shown in Table 1 (48).

Integration of Face-to-Face and Distance Course Delivery This course was set up for enrollment in either a face-to-face or distance format, each worth the same number of credits and providing equivalent experiences. The lecture was held synchronously with both face-to-face and distance participants, in order to foster productive real-time discussion on course topics, and facilitate the development of a learning community during each class period. While distance courses are often perceived to be less engaging than face-to-face courses, specific strategies were implemented to enhance engagement and facilitate active learning. Both peer-to-peer and instructor-to-peer communication have been reported by students to be the most important factors in facilitating engagement in online courses (49). This is also reflected in the fact that student completion rates in online courses tend to be higher when students perceive a sense of community (50, 51). We chose to enhance this through peer-discussion online, peer-mentored research, and faculty facilitated discussion during synchronous class time, along with regular directed feedback between instructor and student relating to coursework. Lectures were delivered through the university learning management system (LMS), where non-animated slides and audio were transmitted so as to lower the bandwidth requirement for distance students. The software allowed for distance students to raise hands, type questions, and/or speak by audio during the class session, as needed, in order to be fully interactive during the session. In addition to lecture, all of the other facets of the course were delivered online as much as possible. Reading questions and exams were conducted through the LMS, and all lectures were recorded and posted on the LMS. Lab report forms were filled out either in person for face-to-face students, or scanned/photographed and uploaded into the LMS for distance students. A discussion forum hosted on the LMS was required for all students in order to foster interaction between faceto-face and distance students, which was actively monitored by the instructors. To ensure distance students had tools necessary for full and engaged participation, android tablets were sent out with the distance laboratory kits on loan. Distance students were responsible for their own internet access, but otherwise the tablets contained all the necessary apps to participate fully in the course pre-loaded onto the device, which then became their portal for the course.

7

Table 1. Tentative Course Schedule. Lecture topics, case studies and laboratory experiments are tightly coupled to facilitate student learning. Wk.

Topic

Case Study

Laboratory

0

Course Introduction

1

Labor Day Intro. to Env. Chem.

The Obligation to Endure

1: Safety and Scientific Method

2

Air Quality

Bear Trouble

2: Air Quality Models and Intro. to pH

3

Introduction to Water Quality

Regulating Triclosan

3: Water Quality and Contamination

4

Water Quality and Treatment

PCB Transport in the Arctic

4: Sampling Surface Water

5

Water Quality of Groundwater

Sulfolane

5: Surface Water Analysis

6

Marine Water Quality

Ocean Acidification

6: Marine Water and Ocean Acidification

7

Contaminant Transformations EXAM 1

none

7: Contaminant Partitioning

8

Weathering and Soil Formation

Permanent Permafrost

9: Weathering and Soil Formation

9

Metals and Inorganic Contaminants

Pebble Mine

10: Soil Quality and Contamination

10

Environmental Microbiology I

Coliforms in Antarctica

8: Microbial World

11

Environmental Microbiology II

Biodegradation of Oil

11: Biodiversity and Biomagnification

12

Ecological Interactions Thanksgiving

Bioaccumulation in the Arctic

No lab

13

Forrest Fires and Ecological Succession

Glacier Bay Succession

Group work on presentations

14

Climate Change in the Arctic

Climate Change Data

14: Energy Sources and Climate Change

15

EXAM 2 3:15-5:15 pm Final Exam- Student Presentations

Context-Driven Chemistry In addition to incorporating Alaska and Arctic specific issues into lectures, several lecture periods included guest lecturers from various departments within the university who offered extpertise in different areas. Guest lecturers were researchers who shared their research and how it related to environmental 8

chemistry, thereby giving students the opportunity to see how scientists were actively using environmental chemistry to solve real-world problems. Weekly case studies from poplar news or science articles or National Center for Case Study Teaching in Science (NCCSTS; (52)) were chosen for their environmental and/or Arctic themed relevance. These formed the basis for discussion board topics, in which a few discussion prompts were posted each week to facilitate student sharing. Some of the prompts focused on comprehension of the issues, while others focused on student reactions and the impacts students had observed in their home communities. Participating in discussion forums (both posting and replies) was a required part of the course for all students. Distance and On-Campus Laboratory Experiences There are several established ways to approach distance laboratory experiences, including: lab intensives, kitchen labs, and virtual labs. Lab intensives are when students travel to a campus for a few days to perform experiments with their classmates, and are most similar to a traditional lab course experience, except with a compressed time frame. This option has been used successfully in rural Alaska because most students enrolled can readily travel to a central location at one of the university’s satellite campuses, but lab intensives can lack flexibility. Kitchen labs are experiments designed to be performed in a student’s home without significant hazards, and often without sophisticated equipment. Kitchen labs are attractive because they provide a flexible, authentic lab experience with minimal safety hazards. Virtual labs allow students to explore concepts through a computer-based simulation and are useful to visualize molecular-scale or other phenomena that cannot be observed, when resources are not available or experiments are too hazardous to perform an experiment at home. For this course, we chose to do a combination of kitchen and virtual lab exercises because of the opportunity to directly link lab and lecture content on a weekly basis and allow flexibility for students. Distance Laboratory Kits Mail-delivered lab kits were developed in partnership with eScience Labs (53). We collaborated with eScience Labs to create completely self-contained laboratories with complete step-by-step instructions (Figure 3). We were able to modify several existing experiments from eScience Lab material, but rewrote a substantial portion of the lab manual to refocus on environmental chemistry and Arctic-related issues. We worked closely with eScience Labs, meeting regularly in a combination of remote and in-person meetings during the six months prior to the first course offering. The result was a set of customized lab kits specifically for our course, several newly developed laboratory activities, and a 167-page laboratory manual. Completed lab kits were shipped to the instructors in Fairbanks so a few remaining supplies could be added prior to shipment to distance students. Added materials included: loaned instructional tablets pre-loaded with a complete lab manual and all applications needed to successfully complete the course, 9

printed packets with copies of the lab manual pages for students to write on, and acid-washed sampling containers used in the research project, and pre-postage-paid thermosafe containers and ice packs for shipping aliquots of research project samples back to UAF during the term.

Figure 3. Lab manual and lab kit developed for the course through a collaboration with eScience Labs.

During the first offering of the course, the instructors held regular office hours both in person for face-to-face students and online through LMS to answer any questions that students might have regarding performing lab experiments. However, there were very few procedural questions, a testament to the excellent lab kit we produced. During the first course offering, the instructional team also met weekly to create videos demonstrating how to perform each laboratory experiment. In future offerings, these videos will be pre-loaded on the lab kit tablets and hosted online to offer maximum support for students while minimizing the required bandwidth. Several virtual labs were used when the content was either not available or too hazardous to be delivered by air mail. For example, a virtual lab exploring aquatic macroinvertebrates was used instead of a real pond dip because by the 10th week of the semester most surface water in Alaska is frozen (Table 1). We also endeavored to find virtual labs that would be self-supporting or require minimal bandwidth. On-campus labs relied on the same laboratory manual and experiments as distance students received in mailed the lab kits. This provides an educationally equivalent opportunity for all students enrolled in the course. On-campus labs have the advantage of being less expensive to run and the lab fees are lower for the on-campus students relative to the distance students because supplies can be purchased in bulk, do not have to be packed into an individual lab kit, and supplies can be used by several courses to minimize costs.

10

Lab Safety Laboratory safety, regardless of physical venue is always of the utmost importance. The instructional team worked extensively with eScience Labs, UAF Environmental Health and Safety, and our departmental safety specialist to ensure that we were doing everything possible to promote a culture of safe practices for both our face-to-face and distance students. Lab kits sent to distance students included standard personal protective equipment, including: safety glasses, gloves, apron, and bench paper. For the field sampling component of the research project personal safety was stressed in the lab manual and in class several times prior to the activity. To manage risk, the instructional team required that each student select a site a week prior to sampling and submit it for approval, which was then considered in conjunction with safety specialists. Life jackets were required (although not provided) when working in and around water. It is imperative to work with university safety experts when designing specific protocols for sampling and all aspects therein. Peer-Mentored Research Projects One of our motivations in developing the course was to empower rural students to contribute to meaningful research within their home communities. Alaska has a paucity of data on surface water and drinking water quality in many areas (54). Thus, we could contribute to the state of knowledge in a meaningful way by engaging students in measuring water quality across the state. Because most surface waters are frozen September to April, this course had to be run in the fall semester with sampling occurring as early as possible to be sure that students had liquid-phase natural surface waters to sample and minimize ice-related risks. Students began preparing in week 2 of the semester by identifying a sampling site and submitting it for instructor approval (Table 1). In week 3, students perform a practice analysis with all the equipment used in the field on tap and distilled water, so that students will feel comfortable with the tablets and bluetooth pH, temperature, and redox probes (ORP), as well as the test strips provided. Instructor videos help students select good sampling sites, use proper sampling techniques, and calibrate and use their bluetooth probes properly (55). In week 4, rural students collect water samples, filter and split their 1 L sample into four 250-ml splits, reserving one for themselves and prepare the remaining three splits for shipment to UAF in coolers provided. On their split they analyze some of the water quality parameters (pH, temperature, ORP). Meanwhile on-campus students prepare for arrival of mailed samples and prepare materials needed for the more sophisticated analyses performed at UAF, including: flame atomic absorption (FAA) to measure cations, ion chromatography (IC) to measure anions, and characterization of dissolved organic matter (DOM) by UV-Visible spectroscopy and fluorescence. In week 5, all students analyze water quality indicators with on-campus team members duplicating rural student results. Measured parameters include: pH, chloride, alkalinity, hardness, phosphate, ammonia, and total iron. Some of these parameters may be altered by the time delay between sampling and measurement 11

which was discussed, but was coordinated in this way for time distribution between labs. On-campus students also make UV-Vis measurements and prepare samples for the more advanced instrumentation, which faculty demonstrate for all students. In this project, research team members develop different, but equivalently valuable, expertise with the rural students becoming site experts and the on-campus student becoming more knowledgeable about the advanced instrumentation used to analyze waters. While the on-campus students get to experience the site through videos and observations collected by the rural student, they will never have the same understanding as the student embedded in the community where it was collected. Similarly, while videos and explanations of sample preparation are available to rural students, it is not the same as physically preparing samples for the other analysis techniques. However, both experiences are essential to successful completion of the research project. The distance student becomes the site expert, and the on-campus students then also perform Hach test strip kits just like the distance students, but then work together to assess the overall health of the water body. For the rest of the semester, especially week 13 lab (Table 1), students work in their teams to research more about the water body they sampled and interpret their water quality data. They consider what the water is used for and how human activity might affect the water quality upstream and downstream. Teams examine their measured water quality parameters versus the Alaska State Water Quality Standards to see if they are within legal limits and evaluate the overall health of the water. Students chat by video on the tablets, and then jointly work to develop a presentation about the water quality of that site.

Results First Offering Successes The technical aspects of the distance delivery of the course worked very smoothly. There were very few questions relating to performing the lab, despite all students being distance students. Distance delivery of lectures via the LMS was quite smooth and in the rare cases that students were not able to attend class synchronously they could still watch the lecture videos. Both instructors attended and participated in all lectures during the term, which brought diverse perspectives and energy to the presentation of material, and guest lecturers provided additional expertise in specific topics and brought new perspectives into the classroom. One of the most successful parts of the course was the weekly asynchronous discussions, where students interacted above and beyond the requirements by continuing to discuss in a thoughtful way with each other. The self-perpetuating nature of student interactions and depth of student contributions was one of the main successes and joys of the course for the instructional team.

12

First Offering Challenges The first offering of this course did not conform exactly to the model we proposed above. The course attracted only three students, all juniors or seniors, and all enrolled in the distance course. Students all lived in locations connected to the road system served by the USPS and did not have problems with bandwidth. This was largely attributed to the course first being offered as a trial course that did not fulfill a graduation requirement. However, the course has since gained core designation, which will hopefully help in recruiting our target demographic in the future. We would also like to build relationships with rural campuses to help with future recruitment.

Assessment of Student Attitudes Formative and summative evaluation of the course was built in from the beginning using an external evaluator who performed pre- and post-assessment of student attitudes and learning, which were anonymized and withheld from the instructional team until after grades were assigned. With the small class size, it is impossible to generate statistically relevant results. However, both of the two students who participated in both the pre and post surveys reported increased likelihood in response to the question, “How likely is it that your eventual career will directly pertain to the environmental field?” Students also reported a strong integration between lab and lecture. Below are representative student quotes received in the semester-end evaluations: “Chem 194 has been a rewarding experience that provided important information on problems in the local environments, as well as larger problems we are facing worldwide. The combination of interesting lectures with practical labs has made the class engaging and fun.” “I’m really glad I took Chem 194, as it provided me with a wealth of information on environmental problems, and potential solutions to help evaluate and preserve the quality of different ecosystems.” “The labs were straight forward, and the action of sampling from a field site was a very enriching experience that really tied the class to local issues.” “Introduction into Environmental Chemistry in the Arctic really peaked my interest and introduced me to many concepts that I had not encountered before.” “The water project was very unique, and helpful to seeing the connections of water parameters and the topics of many lectures, and how they connect to the environment.” 13

“I liked the amount of communication with the other class members throughout the semester. I liked having to read and respond to discussion board posts, but not being required to communicate any more often or seriously than that. I was glad I could work independently on the labs and weren’t required to collaborate with others for those.” “I liked the amount of communication from the instructors to the class about assignments, exams, problems, etc.” “I’m not sure that the lab was super useful to me. I definitely felt as if it was intended for people that had not worked at all in science before. I liked the overall course content, but the lab felt very simplistic.” The tone of most of these comments suggest that, although there are some things the instructional team can improve upon, students valued the course’s Arctic focus and it would be appropriate for our target demographic.

Future Work This course was fully developed in summer and first offered in Fall 2015 as a trial course and has since been approved for a core designation, which also involved moving from a 3-credit to a 4-credit course. This corresponds to an extra hour of lecture per week from the 2015 offering, which will be used to incorporate more active learning strategies, facilitate more in-class discussion, and increase collaboration between on-campus and distance students. It is important for faculty to not just deliverer content and facilitate discussion during synchronous lecture, but also to actively engage with students in all facets of the course, including discussion forums, laboratory activities, etc. Additional data from future offerings will allow for long-term data collection on enrollments, recruitment, and STEM retention. Unfortunately, subsequent offerings of the course have not yet occurred due to other unrelated constraints. Future offerings will also grow the water quality data sets generated by students within the course. Specifically, we are looking to collect data on basic water quality across the state, a property that is lacking (54) and to present this accumulated data in an online venue for public access. The next phase of this project will involve developing an interactive map to display student-collected data from the class in a publically available venue (Figure 4). In this way, students can contribute to publically available data on Alaska’s surface water. This could eventually serve as a resource for policy makers and scientists in identifying surface water quality concerns and faciliate resource managment decision making. Potential extensions for the course could include community engagement activities to discuss water quality and/or environmental issues, and to contribute to our knowledge of natural Arctic waters. Partnerships with satellite campuses may also bring mutual benefits of increased enrollments and additional pathways for students to pursue their educational dreams. 14

Figure 4. Collection of student-generated data in an interactive map describing status of surface water quality in the state of Alaska.

Conclusions This course model describes translatable models for the implementation of an integrated face-to-face and distance laboratory, and a course-based peer-mentored research component. The contextually driven laboratory and research activities may especially serve rural/nontraditional students by identifying issues relevant to their local community and environment. Part of this course’s success is improving students’ self-identity within science and capitalizing on issues students care about as a mechanism to increase engagement. Our model is specific to Alaska and the Arctic, but the course content can be tailored through case studies, peer-mentored research projects, and exploration of location-relevant environmental issues to other ecosystems. We welcome interest in translating this course model to other ecosystems through collaborative projects.

Acknowledgments The authors wish to gratefully acknowledge Chris Iceman, Annie Chartrand, and the Department of Chemistry and Biochemistry for their participation and support of the class. Also, the invaluable contributions of several UAF Biomedical Learning and Student Training (BLaST) Learning, Research, and Training Technicians (LRTTs): Lori Gildehaus, Johanna Green, and Theresa Vertigan for their guest lectures and contributions to the lab. The UAF eLearning staff, especially Madara Mason and Christin Bouffard for their support in course development through the UAF Chancellor’s Innovation in Technology and eLearning (CITE) Fellows Program. Our collaborators at eScience Labs, 15

especially Scott Higgins, Ellen Thompson, and Valarie Houghton for taking on this course as a labor of love. Our external evaluator, Lori Sowa, nd the UAF Alaska Summer Research Academy (ASRA) program for supporting the translation of this work to middle and high school audiences. Support for this project was provided by the UAF Office of Undergraduate Research and Scholarly Activities through a 2015 Mentor Award, and the UAF BLaST program through a Curriculum Development Project. Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Numbers UL1GM118991, TL4GM118992, or RL5GM118990. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Chapter 2

Community-Based Undergraduate Research: Measurement of Hazardous Air Pollutants with Regard to Environmental Justice Kathryn Zimmermann,*,1 Laura Young,2 and Kelsey Woodard3 1School of Science and Technology, Georgia Gwinnett College, 1000 University Center Lane, Lawrenceville, Georgia 30043, United States 2School of Liberal Arts, Georgia Gwinnett College, 1000 University Center Lane, Lawrenceville, Georgia 30043, United States 3Center for Teaching Excellence, Georgia Gwinnet College, 1000 University Center Lane, Lawrenceville, Georgia 30043, United States *E-mail: [email protected].

Environmental justice focuses on disparate exposures of communities to pollution based on race, national origin, or income level. This collaborative study, which paired faculty and undergraduate students from political science and chemistry disciplines with an external community advisor, collected data to help bring environmental justice issues to the forefront of discussions in their community. Interdisciplinary, undergraduate researchers from Georgia Gwinnett College measured gas-phase polycyclic aromatic hydrocarbons (PAHs), using passive sampling methods, in communities with differing demographic indicators. This undergraduate research project leveraged student interest and motivation in social justice themes to address a community-based question that combines physical (environmental chemistry) and social science (political science).

© 2018 American Chemical Society

Introduction Georgia Gwinnett College Georgia Gwinnett College (GGC), a public, open-access, four-year, liberal arts college in the University System of Georgia, opened in 2005. In the last twelve years, GGC has grown exponentially from 120 students to over 12,000 students, with 67.7% enrolled as full-time undergraduates (1). GGC was recently ranked as the most ethnically diverse college in the South (2), and has the distinction as an emerging Hispanic Serving Institution. Many of GGC’s students are self-supported, first generation college students, and, as of Fall 2016, 52% of GGC students were Pell Grant Eligible (1). GGC offers an unique opportunity to gain higher education, often admitting at least 80% of applicants. The student demographics as of Fall 2015 are listed below in Table 1, exemplifying the diversity of the college as a whole, the school of science and technology (SST), the school of liberal arts (SLA), and the student demographics in the Environmental Justice Community Innovations Project (EJ-CIP) conducted during the 2016-2017 academic year.

Table 1. Demographic distribution of student population of the entire college (GGC), the SST, the SLA (1), and the undergraduate project described in this chapter (EJ-CIP) Demographic

% Black

% Hispanic

% First Generation College Studenta

% Female

% Above the age of 23

GGC

32.6

16.9

41.7

56.2

24.6

SST

33.3

16.3

38.8

44.4

25.2

SLA

37.2

17.6

40.5

63.6

27.0

EJ-CIP Projectb

57.1

0

N/S

85.7

28.6

a For the Fall 2015 semester, 2,469 students who did not provide first-generation information

are excluded from the sample (1). b Demographic information for the EJ-CIP Project was collected using self-reported data from a student survey of the project. N/S corresponds to data that was “not surveyed” in this questionnaire.

The EJ-CIP undergraduate research project brought together an interdisciplinary team of two GGC faculty members (Political Science and Chemistry) and seven undergraduate students. GreenLaw, a non-profit environmental law firm based in downtown Atlanta, served as the community-based external advisor to the project. The environmental justice focus of the project served to leverage student interest and motivation in the application of both social and physical scientific practices to a community-based issue. The outcome goals of this undergraduate research project were multifaceted and listed as follows: 22

• • • •

Motivate and engage students in applied research and experiential learning through a community-based, interdisciplinary project; Integrate students with an external advisor, as well as other members, in their regional community; Improve student knowledge of environmental justice history, policies, and research; and Improve interdisciplinary communication and understanding at an undergraduate level.

Experiential Learning at an Open Access Institution GGC, and other public, four-year universities of its kind, are met with various challenges and opportunities to meet the demands and needs of their diverse and open access student population (3). To address some of these challenges at GGC and other institutions, the University System of Georgia (USG) Board of Regents became an official partner of the Liberal Education and America’s Promise (LEAP) Initiative under the Association of American Colleges and Universities (AACU), forming a consortium called LEAP State Georgia Consortium. In 2005, the AACU’s LEAP Initiative was launched with a call to national public advocacy and campus action, responding to contemporary demands for an increase in college-educated workers and more engaged and informed citizens. Termed as high-impact educational practices, LEAP activities are a parasol of experiential education, widely tested and shown to engage and challenge students. They are also proven to increase rates of student retention and be beneficial for college students of various backgrounds (4, 5). The Association for Experiential Education defines this practice as “a philosophy and methodology in which educators purposefully engage with students in direct experiences and focused reflection in order to increase knowledge, develop skills, clarify values, and develop one’s capacity to contribute to their communities (6).” In other words, the process through which a learner constructs knowledge, skill, and value from direct experience is called experiential learning (EL). These direct experiences take on various forms, including first-year seminars and experiences, community service, fieldwork, sensitivity training groups, internships, cooperative education with community partners, participation in faculty-led research, service-learning, and community-based learning and research, the latter of which will be explored in the next section. Renowned philosophers, educators, and trailblazers of the EL approach, Aristotle, John Dewey, David Kolb, Kurt Lewin, and Jean Piaget, all believe that true learning takes place when the experience allows the student to 1) harness their own learning, both in and outside the classroom; 2) bridge prior and current knowledge; 3) serve a societal and individual learner purpose; and 4) realize-life/world application. Speaking to the harnessing, bridging, purpose, and application, Dewey (7) believed that educators (faculty) must understand and take into account human experience, stating that “Education is not preparation for life; education is life itself.” By doing so, faculty serve as facilitators of learning and become better reflective practitioners, bridging the traditional and progressive sides of education. 23

GGC’s Community Innovations Project Program In 2015, a survey by Hart Research Associates on behalf of the AACU demonstrated that employers place a high priority on collaborative team work and application of skills to real world issues when hiring recent graduates (Figure 1) (8). However, this survey also showed a disconnect between the skill sets desired for employment and employers’ ratings of these skills in newly hired graduates (8). In an effort to address this incongruity in expectations and observations of employers, to align with LEAP’s charge, and to support GGC’s vison and mission, GGC’s Center for Teaching Excellence (CTE) supported the creation of the Community Innovations Project (CIP) program. The goal of this program is to encourage engaged, public scholarship, giving students an opportunity to work alongside faculty on interdisciplinary projects which are considered important to (and defined by) members of the community. Such an opportunity integrates faculty roles of teaching, research, and service, allows students to gain hands-on experience putting their knowledge into practice, and cultivates genuine, intentional relationships with the community.

Figure 1. Top: Percentage of employers that rated the described skills as very important for recent graduates to have. Bottom: Percent of “much” greater likelihood of hire if recent college graduates have had the following experiences. Reprinted with permission from Falling Short: College Learning and Career Success. Copyright 2015 by the Association of American Colleges and Universities (8). With its underpinnings in service learning, the pilot CIP program is a form of community-based research (CBR), where expertise is derived from community members themselves. Community members are the content experts and voice of expression for the community’s need for interaction with the academic institution. This interaction allows for reciprocity and supports a mutually beneficial relationship between key players (students, faculty, community members/external advisors, and institutions). This also allows for a true intergenerational partnership 24

of learning to occur, thereby fostering learning communities to meet the call of nurturing civic minded students and future leaders. Principles of CBR are (9): •

• •

To create a collaborative relationship between members of the community and researchers (professors and/or students). It engages university faculty, students and staff with diverse partners and community members; To validate multiple sources of knowledge and encourage the use of many methods of discovery and of distribution of the knowledge produced; and To create a form that is also participative (among other reasons, change is usually easier to achieve when those affected by the change are involved) and qualitative.

The CIP program was inspired by a similar program currently employed at Harvey Mudd College. The Clinic Program, a hallmark of the Harvey Mudd College for over 50 years, focuses on small groups of undergraduate students working for corporate and government sponsors to design, develop, or conduct research according to the needs of the sponsor (10, 11). The CIP program takes a similar approach, but implements this community-based EL at an open-access, liberal arts, institution. In Spring 2016, the pilot program successfully launched a request for proposals for interdisciplinary faculty/student teams to work on a one-year project addressing real-world problems, identified as important by a local external community partner organization, such as a for-profit company, not-for-profit organization, governmental agency, or non-academic unit of GGC. Project teams consisted of two or more GGC faculty Principal Investigators (PIs), three or more students (junior standing), and an advisor from an external organization. Grant awards were in the amount of $7,000 for each one-year team project, with $3,000 allocated to faculty for summer stipends during project planning. Using the PARE (Prepare, Action, Reflection, and Evaluation) Model as a guide, the CTE held a pre-planning summer orientation to curate a supportive environment and explore topics including types of EL pedagogy, student learning outcomes and expectations, importance of reflection, community partner relationship and expectations, logistics and risk management, and mandatory project reporting dates. The CTE also communicated with external advisors regarding the CIP process, expectations, and memorandums of understanding (MOUs). At the end of the academic year, all projects were expected to result in a deliverable, such as a formal report, presentation, or prototype/work of design, etc. All project teams were also required to make a formal presentation at the end of the academic year. During the pilot year, two projects were funded, including the EJ-CIP project focused on environmental justice with regard to hazardous air pollutants. With evaluation feedback from 2016 – 17 pilot CIP teams, the program has continued for another academic year, providing Grantmanship Informational sessions for interested faculty teams, focusing on professional development in proposal writing and discussion of opportunities and challenges presented by previous awardees. 25

Environmental Justice and Air Pollution The United States Environmental Protection Agency (U.S. EPA) defines environmental justice as the “fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income with respect to development, implementation, and enforcement of environmental laws (12).” Although environmental justice is not universally defined, it usually refers to the belief that citizens of a certain ethnicity or socioeconomic class should not disproportionately face the burden of the externalities related to pollution and other environmental health hazards. Though there are different interpretations of this term, most definitions share the common theme of justice in distribution, procedures, and process (13). Air quality, which can negatively influence human health (such as rates of asthma and negative effects on the cardiopulmonary system) (14, 15), has been previously studied with respect to environmental justice. Several studies, focusing on atmospheric particulate matter (PM), have shown that minority and low income communities have higher exposure to environmental contaminants via air pollution (16–20). Apelberg et al. (21) found that on-road sources of air toxics might be an area to focus policy changes with respect to reducing the disproportionate health burden of air pollution based on socioeconomic status or race. This is important because, while the National Ambient Air Quality Standards (NAAQS) monitoring provides data for exposure differences between communities for air quality parameters such as CO, lead, NO2, O3, PM and SO2, less is known about the distribution of exposure to toxic hazardous air pollutants (HAPs). This is due to the diverse chemical properties and the number of molecules categorized as HAPs (22, 23). Two previous studies (24, 25) have shown that, due to mobile sources (such as high traffic density), exposure to air toxics and the associated risks are disproportionately shouldered by minority and low-income communities. As a result, the EJ-CIP project investigated environmental justice with respect to HAPs, focusing on polycyclic aromatic hydrocarbons (PAHs). The topic of environmental justice is of particular importance in the state of Georgia, since, as of 2010, it is one of only five states that has not addressed environmental justice in the form of any initiatives, task forces, programs, or employees working at the state level (26). Thus, one aim of this study was to analyze the spatial variability in concentrations of gas-phase PAHs and possible correlations of PAH concentrations with demographic indicators such as percent minority population, percent linguistic isolation, or percent below poverty level. A second goal for this study was to provide preliminary data and proof of concept for using passive air sampling as a method to build a database of spatial HAPs concentrations that can be used to support community discussions and policies regarding environmental justice and air quality. Interdisciplinary Undergraduate Research: Importance of Combining Political Science and Environmental Chemistry Higher education is increasingly looking for ways to facilitate interdisciplinary communication. In fact, interdisciplinary curriculum was 26

found to be the “number-one issue in American education (27).” This focus is because of the many benefits due to increased conversations amongst disciplines. Specifically, interdisciplinary education encourages critical thinking within one’s own discipline and leads to more holistic approaches to solving some of the world’s more complex, pressing issues, while improving self-discipline. Interdisciplinary education also prepares students for modern working conditions that call for increasing amounts of multi-professional teamwork, giving future generations further ability to consciously approach complex problems in group settings with colleagues of different skill sets (28). Increasing communication and collaboration in non-traditional academic groups also typically leads to an increase in creativity (27). Embarking on interdisciplinary research or teaching requires focus on thematic integration, which becomes the organizer and a driver for the curriculum. Knowledge integration is also important. This “is achieved when interactive and connective relationships…are established between the knowledge and skills in the two or more disciplines (27).” Special attention must therefore be placed on finding a common link between the disciplines and focusing on the skills needed to understand those links. This means learner-initiated integration is also key because it helps lead students to discover connections. This is done by placing a value on independent thinking which can help the student ask questions and find connections between the disciplines; “to develop sequential understandings in separate areas of knowledge and skill; and to establish thought patterns or mindsets that lead them to look for” the necessary links and “connective relationships across all areas of learning (27).” The topic of environmental justice (the subject of the EJ-CIP research project) provides thematic integration to engage multiple disciplines because of the interdisciplinary nature of the topic itself. Specific to the issue of environmental justice, physical scientists must gather data and quantify exposures of different populations to HAPs, and policy specialists must analyze demographics of different communities, examine policies currently in place that address this issue, and generate ideas for moving forward with evidence-based policies. Thus, environmental justice combines a mixture of scientific expertise, socio-economic analysis, and a knowledge of legal and historical requirements. For example, public policy experts are interested in why certain groups are targeted with externalities related to pollution, why the targeted groups are unable to fight against policies that affect them negatively, and why regulatory efforts by policymakers may fail to protect vulnerable populations. Those interested in health policy use the level and type of exposure to understand what policies should be adopted to combat health related issues in differing regions or communities. Public administrators focus on issues related to urban planning, including the regulations and laws dictating the placement of polluting facilities. Alternatively, political economists aim to understand the impact of pollution on the economy. Political economists can also combine their work with health policy experts to determine the number of sick days missed from work due to environmental justice issues and the impact these absences have on the economy as a whole. 27

The environmental justice work of public policy experts would not be possible without the data provided by physical scientists such as chemists, biologists, and epidemiologists. The work of physical scientists is essential for collecting the data analyzed by policy experts to answer the questions they pose and to implement evidence-based policies (29). Specifically, chemists are able to analyze complex mixtures to quantify HAPs in communities, giving an estimation of exposure rates to different toxic compounds. Biologists can use mouse-model studies or cellular assays to assess the toxicity of different compounds or the possible synergistic effects of mixtures. This work combines with that of epidemiologists using crosssectional or longitudinal studies to assess human health effects of exposure. One of the challenges faced by the teaching and learning of both political science and chemistry (the two disciplines most heavily combined in this project) is to maintain relevance in the eyes of students. During the EJ-CIP project, the thematic integration of the two fields to investigate social justice issues in the form of exposure to toxic air pollutants was used to demonstrate the relevant nature of both fields in the lives of students and their communities. One goal of such project-based research within the community is to give students the opportunity to link expertise gained from coursework with application to a real-life challenge and the ability to drive or direct positive change. For example, students who study public policy (SLA students) may encounter challenges interpreting the source or meaning of chemical exposure data. SST students, on the other hand, may not see the relevance of their work or how it can possibly impact policy decisions. This deficiency in interdisciplinary understanding from both fields can result in the impediment of sound future policy analyses and implementation. In sum, from an environmental justice perspective, there is an intimate link between science and public policy. This relationship also exists between policy and other scientific endeavors, since funding for a variety of scientific investigations is often influenced by public policy and it is imperative that public policy is evidenced-based and data-driven. Since this mutualism between policy-makers and scientists makes it necessary that communication between the two fields flows efficiently (29–32), it is important to introduce undergraduate students to the role of science in public policy and vice versa. Thus, the EJ-CIP project integrated students on an interdisciplinary level, early in their career development, aiming to strengthen communication across the policy and physical science disciplines. Previous approaches to this challenge have included curriculum development for upper level chemistry courses that include problem- and project-based learning with an environmental focus (31, 33–37). However, teaching chemistry with public policy implications and themes only confronts one-half of the communication challenge. Interdisciplinary communication must be encouraged in both directions. Not only must physical science students understand policy implications, but political science students must also be proficient in the scientific method and data interpretation. As a result of the above challenges, effort in the EJ-CIP study was directed to require students to work outside of their field of expertise. SLA students worked alongside SST students in the field and laboratory, while SST students worked with SLA students on demographic and policy analysis (Figure 2). This encouraged students to ask questions of one 28

another, communicate openly, and discover important relationships between the social and physical sciences, resulting in facilitated dialogue between future policy makers and scientists from an early stage in their careers.

Figure 2. A Venn diagram which shows the interdisciplinary nature of the project, in which students from both fields of expertise were required to conduct methods and work in the field of their collaborators.

Experimental Methods Interdisciplinary Nature of the Research Team This project integrated students into a field of study that was beyond their current realm of expertise, aiming to improve dialogue and understanding between science and policy. Students worked collaboratively within this team to reach a goal (obtaining and disseminating results), which encouraged the growth of beneficial hard and soft skills, including, but not limited to, conducting research in an experiential and quantitative fashion, communicating technical information both orally and in writing, and working in real world, modern conditions in their respective fields. Via their external advisor, GreenLaw, students interacted with professionals outside of the college, to see the operation of environmental law and advocacy groups first-hand, as well as to make contacts with professionals having similar interests and goals. Although it is possible for the SST and SLA aspects of this program to stand alone, the interdisciplinary nature of the program allowed students and faculty to gain experience with environmental chemistry analyses while simultaneously engaging in an upper level policy analysis. Collaboration with outside groups also added an additional component of community engagement that encouraged the development of professional soft skills outside of the typical college setting. Importantly, students with different academic backgrounds worked together to solve a complex problem relating to their community. The team consisted of seven students from three different disciplinary backgrounds. Two students were 29

majoring in biochemistry, one in environmental science, and four were political science majors concentrating in legal studies. The political science majors had very limited knowledge regarding the science needed to inform policymakers nor were they experienced with lab work. The biochemistry students, however, were unaware of the policy implications related to the work they often performed in the lab. For the environmental studies student, the interdisciplinary nature of the project helped to consolidate the knowledge learned inside the classroom with actual fieldwork and lab experience. EJSCREEN Seven sites were chosen for analysis, with each student choosing a site to research. This format gave students “ownership” over the data collection and analysis specific to their site. Students used the EJSCREEN tool, a publically available database provided through the U.S. EPA (38). EJSCREEN “allows users to access high-resolution environmental and demographic information for locations in the United States, and compare their selected locations to the rest of the state, EPA region, or the nation (38).” It should be noted that screening-level tools, such as EJSCREEN, are limited in scope and data, and therefore, do not determine the existence or absence of environmental justice concerns in a specific geographic location (38). Thus, this project used EJSCREEN to select possible sites of inquiry and then followed with subsequent chemical measurements and demographic analyses. Students investigated the demographic distributions of several possible sites, but also investigated the predicted air pollution environmental indicators provided by EJSCREEN such as, particulate matter less than 2.5 microns in aerodynamic diameter (PM2.5), the national air toxics assessment (NATA) diesel PM, and NATA air toxics cancer risk. These are described as follows: • • •

PM2.5 (annual average concentration, µg/m3, calculated from a combination of air quality monitoring sources); NATA Diesel PM (concentration of diesel PM estimated in µg/m3); and NATA Air Toxics Cancer Risk (estimated lifetime inhalation cancer risk using emissions estimated from the National Emission Inventory (NEI));

Sampling sites in the Atlanta metropolitan region were chosen based on these environmental indicators, as well as, several demographic parameters listed below (38): •

•

•

Percent low income: The percent of people in a location living in households where the income is less than or equal to twice the indicated federal poverty level; Percent minority population: The percent of people in a location who have listed their racial status as something other than white and/or list their ethnicity as Hispanic or Latino; and Percent linguistic isolation: The percent of individuals in a location living in a household in which all household members older than 13 speak a 30

non-English language and also speak English less than what is considered very well. Data for these demographic parameters for each site are listed below in Table 2.

Table 2. Demographic data obtained for each site from EJSCREEN (38) Site ID

% Low income

% Minority

%Linguistically Isolated

A

15

19

0

B

24

90

0

C

49

63

6

D

54

87

11

E

77

66

9

F

27

38

12

G

36

16

0

Students were required to contact sites to gain permissions to hang samplers. This included providing a description of the proposed project, details of samplers, timelines, etc. The calls also allowed students to practice discussing the importance of the reasons behind their work, thus increasing the awareness of environmental justice issues in the state of Georgia. Selected sites for hanging samplers included several elementary schools, a science nature reserve, several Georgia Environmental Protect Division sampling sites, and a private residence.

Passive Air Samplers and Laboratory Techniques For this pilot study, students’ initial focus included atmospheric PAHs. The study aimed to quantify gas-phase concentrations of the 16 PAHs listed on the U.S. EPA Priority Pollutant List (39). PAH sources include incomplete combustion processes such as vehicle (diesel) emissions, residential activity and industrial heating (40). PAHs have shown mutagenic properties in bacterial and mammalian assays, and are classified by the International Agency for Research on Cancer (IARC) as probable human carcinogens (41–43). Combined with their tendency to bioaccumulate, PAHs pose risks to both environmental organisms and humans (44). Table 3 lists the analyte PAHs measured in this study, their associated abbreviations, molecular structures and internal standards of quantitation.

31

Table 3. List of analyte PAHs (including abbreviations and molecular structures) measured in this study

32

Passive air samplers (PAS) were used in this study to measure the concentration of PAHs at each site. These samplers, characterized and used in many previous studies of ambient concentrations of gas-phase persistent organic pollutants, are low cost and require no power during sampling, and have not yet been deployed in the Atlanta metropolitan region. The PAS (Tisch Environmental; Cleves, OH) have been thoroughly characterized and their method of operations previously described (45, 46). In brief, the PAS includes a polyurethane foam disk (PUF, ½” height x 5 ½” diameter; part number TE-0114) held inside of a stainless steel dome used for protection against precipitation, deposition of particulate matter, UV light, and the influence of wind speed (47). They operate based on the air-side mass transfer coefficient and the PUF-air partitioning coefficient of each analyte (45), and thus, require no outside power source for a pump, are quiet and non-invasive, and are a relatively inexpensive way to increase spatial resolution of gas-phase PAH concentrations. PAS are ideal for this type of study, in which spatial resolution of samples is important, compared to traditional samples methods (such as high volume air samplers), because PAS allows for simultaneous measurements at several different sites at a time, generally prohibited with tradition sampling methods due to high cost and person-hours needed to change sampling media. Similar PAS systems have been used in several large-scale studies to measure atmospheric PAH concentrations (46–52).

Figure 3. PAS deployed at Site C using non-invasive measures (zip ties and hose clamps). Prior to deployment, sample domes (Figure 3) were cleaned with acetone and PUFs were pre-cleaned via Soxhlet extraction in a 50/50 acetone and hexane mixture (Fisher Scientific, Optima) for 24 hours. Samplers were deployed at sites selected by students starting in January 2017, and hung at heights ranging from 166 cm – 182 cm to represent a ‘human height’ exposure concentration. Dates of deployment ranged from January 10, 2017 to March 17, 2017. Preliminary analyses estimated the average sampling rate of these samples to be 5.0 m3d-1 (46, 47, 51, 52). Table 4 shows deployment characteristics for each site. 33

Table 4. Deployment characteristics for each site Site

Latitude

Longitude

Site Type

Date Deployed

Total # Sample Days

A

34.075402°

-83.87047°

School

1/17/2017

37.0

B

33.571235°

-84.61902°

School

1/10/2017

51.9

C

33.828622°

-84.11447°

Residential

2/4/2017

31.0

D

33.963097°

-84.06922°

GA EPD

1/11/2017

54.0

E

34.299359°

-83.8134°

GA EPD

1/13/2017

41.9

F1, F2

34.257762°

-83.84541°

Forested

1/13/2017

42.0

G

33.729485°

-84.37091°

Residential

2/4/2017

40.8

Method blank extracts were collected by subjecting clean PUFs to the same laboratory and analytical procedures as sample PUFs. Two field blanks were collected by packaging clean PUFs in aluminum foil, plastic bags and mason jars, transporting them to the sampling site in the same manner as the sample PUFs, placing the field blank PUFs in the stainless domes for approximately one minute, and then storing under similar conditions as sample PUFs until extraction and analysis. It should be noted that the only site where replicates were measured was Site F (samples F1/F2). All PUFs were stored in aluminum foil, plastic bags, and mason jars at 30°C until extractions were performed. PUFs were spiked with a mix of deuterated internal standards (NAP-d8, ANT-d10, FLA-d10, and BaA-d12, Supelco, TraceCERT) for quantitative purposes and Soxhlet extracted in 50/50 hexane/acetone (Fisher Scientific, Optima) mix for 24 hours. Samples were then concentrated under rotary evaporation and eluted through silica solid phase extraction (SPE) columns (Discovery DSC-Si, Sigma Aldrich) using a 50/50 mixture of hexane and dichloromethane (DCM, Fisher Scientific, Optima) mix. Extracts were brought to a final volume of ~ 200 µL using nitrogen flow (53). All PUF extracts were analyzed with gas chromatography- mass spectrometry (GC-MS) using a Shimadzu QP2010S, operated with EI ionization and SIM mode. Samples were injected at 280° C in splitless mode, and separations were completed on a 30 m x 250 µm i.d. (film thickness 0.25 µm) SHRXI-5 MS column (Shimadzu). The initial temperature of the column was held at 70°C for three minutes, and then increased at 20° min-1 to 315°C and held for 30 minutes. Retention times confirmed with a PAH mix standard solution (EPA 610 PAH mix, Supelco) and concentrations were calculated relative to the added deuterated internal standards.

Student Deliverables Blog Student reflection helps facilitate learning and keeps students fully engaged (54). It is therefore important to find ways that help students reflect on the material they learn. Blogs are a great tool for classroom use since they require students to 34

reflect on their work in a digital environment familiar to today’s student. Blogging also allows students to create an online portfolio that highlights their work that they can share with family, friends, potential graduate schools, and employers. As a result, this project required students keep a weekly blog updating the progress of the project and the specific work they performed. Students began their blog by summarizing the goals of the project and discussing the importance of investigating issues related to environmental justice. After the initial post, students shared their experience selecting site locations, the new skills they learned in the laboratory, the knowledge they gained related to environmental policy, their experience visiting site locations and placing the air samplers, as well as meeting with members of the community. In addition to reflections on their work, students also posted photographs and supplemental information to enhance the substance of their reflections. The result was a professional online portfolio useable to display skills and accomplishments when applying for graduate school or employment. Students also reflected on the experiences they had at their meeting with the external advisor, GreenLaw. Students not only discussed the substance of the meeting, but also reflected on how the classroom and laboratory work transferred to real world professional endeavors to solve issues of environmental justice. The connection with what they learned and how it applied to future career possibilities is particularly useful since it helps students see beyond the classroom experience to how these skills can transfer to their future career goals. Site Reports Students’ site reports made it easy to record and organize data for later analysis to determine what, if any, factors may contribute to the amount of pollution in an area where samplers were placed. The reports included basic geographic information, demographic statistics, and identification of polluting businesses and industry located in the area of sample placement. For this project, each student was assigned a particular location for which they generated the site report. The reports were divided into several sections. The first section covered basic location and geographic information about the sampler location. Demographic information, such as population levels, percentage of individuals in different minority groups, income levels, and education levels were included. In addition to basic demographic information, the report included a section to record health statistics of individuals living in the area. The third section of the report included information about area pollution. The percentile of PM2.5, NATA Diesel PM, and NATA RHI were estimated using the EJSCREEN information (38). Information about current and past industries that may contribute to pollution surrounding the sampler placement was also included. Details about these industries included the name and address of the business, the type of industry, and a summary of possible pollutants created by that particular industry. The final section of the report included the actual data collected from the air samplers placed in the field by the students. To gather information for the report, students conducted on-site visits to survey the geography of the area and determined present conditions where 35

samplers were placed. USGS and Google Maps were also used to learn more about the topography of the sampler location. An examination of municipal and county planning files as well as searches with local public agencies were checked for prior and current land usage and permits in the area. This information helped students locate current and past polluting industries. The Health Department provided statistics about the health of individuals within a county, though this information proved to be more difficult to find for most students, and was not spatially resolved to the level of our chemical measurements. Demographic information was primarily collected using statistics provided by the EJSCREEN, but also compared to census data when available. In some cases, students gained information on history of a location through informal interactions with community members. For example, through interaction with community members in Gainesville, GA, students learned of the Newtown story and the Newtown Florist Club (55). The predominantly African American residents living in the Newtown neighborhood exist alongside 14 polluting industries within a 1-mile radius of their community. Members of this community have suffered from high incidences of lupus, and specific types of mouth, throat, and lung cancers. The Newton Florist Club is a grassroots organization that has organized to bring awareness to their fight for environmental justice. This is a community who has historically struggled with issues of environmental (in) justice and brings light to the complex nature of proving and solving these types of issues. These sources provided information for the environmental justice struggles of a community less than 30 miles from GGC, giving the students a local context with respect to the need of sound measurements and policies regarding environmental justice. When site reports were completed, students met to discuss their findings and analyze the results. They also shared their reports on their individual blogs. Not only were the reports useful for helping students organize the data they needed to collect for analyzing the sampler results and drawing conclusions about the sources of pollution and its impacts, but they also provided a deliverable that students can share with potential employers and graduate schools. Presentations and Outreach Students took part in multiple presentations during the project. The first was given to the community-based external advisor, GreenLaw. At this meeting, students were hosted for the morning at the non-profit environmental law firm in downtown Atlanta. Students met with several attorneys and interns to discuss the project and relevant environmental justice case law, history, and current policies existing in Georgia. Students provided a formal presentation to the attorneys, sharing the overall goal, project plan, and the research design they developed for this study. When completed, students received advice for improving their research design and discussed how collaboration would take place during the remainder of the project. Students were also invited to present at the 2016 Energy Symposium held at Georgia Gwinnett College. Although the focus of this event was energy security, the hosts felt the work the students were doing not only related to the importance 36

of finding clean energy alternatives, but also wanted to highlight alternative means by which the topic of energy security can be taught. Specifically, students discussed the relationship of fossil fuels and air pollution and its impact on the health of individuals. They shared demographic data related to areas affected by air pollution, and argued that certain communities were disproportionately disadvantaged compared to others because of the current reliance on fossil fuels. After discussing their experimental design and hypotheses (since, at the time, data collection was not complete), the students discussed the benefits of clean renewable energy solutions and the greater impact it would have on those communities more likely to suffer from the externalities of fossil fuels. Not only was this experience beneficial because it helped students relate their project to larger environmental issues, but several prominent scholars, including a member from the United Nations, were present. Thus, students were able to network with professionals in academia as well as in high-level government positions, an experience not typically granted students in a traditional classroom setting. Two senior biochemistry students traveled to present preliminary results at the annual Spring American Chemical Society (ACS) meeting in San Francisco, CA. This was the first national meeting at which either student had either attended or presented. One of these students is currently pursuing a Ph.D. in Chemistry at University of Georgia, and the other is in the process of applying for graduate school. In addition, the entire group of students presented at the annual Georgia Gwinnett College CREATE Symposium. The CREATE Symposium gave students an opportunity to share their work on the project with their fellow students as well as other faculty members on campus. During this presentation, students explained the purpose and goals of the EJ-CIP project. Most of the presentation, however, shared the results of the research and discussed the importance of the project to the Atlanta metropolitan region. The students also had the opportunity to communicate the goals and results of their project to middle-school age campers at the Elachee Nature Science Center during the summer of 2017. Two students from the project attended an afternoon of summer camp to lead a group of 12-14 campers in the activity of making Schoenbein paper. This relatively inexpensive activity allows participants to create their own colorimetric measurement of tropospheric ozone (considered a criteria pollutant by the EPA) using the oxidation of iodine (clear to purple/brown color change). This outreach activity allows for the discussion of the importance of air quality, the effects of air quality on the health of sensitive populations (children and elderly populations), and well as the introduction of environmental justice pertaining to air quality. In the future, the goal of such projects will be to hang PAS at elementary and middle schools, and have the students at such schools participate in ozone data collection using Schoenbein paper during the time that the PAS is hung on their property. This type of outreach collaboration will include K-12 students helping to collect semi-quantitative data in an active research project. Each of these presentations gave students an opportunity to not only share the project goals and results, but also their experience working on an interdisciplinary project and the benefits this type of collaborative approach had on their overall educational experience. In addition, students gained exposure presenting in a 37

professional setting and were able to network with business professionals as well as community and global leaders.

Preliminary Data Generated by Undergraduates PAHs quantified included NAP, ACY, ACE, FLU, PHEN, ANT, FLA, PYR, BaA, CHR, B(b+k)F, B(a)P, I123P + DBA, and BgP. Separation of 14 out of 16 analyzed PAHs were achieved with the method, with B(b)- and B(k)F reported as a sum of the two isomers, as well as I123P and DBA. Retention times of analytes in sample extracts were confirmed by retention times of standards (see Figure 4).

Figure 4. Chromatograms of standard PAH mixture (top), and site A extract (bottom). Peaks are labeled according to Table 3 with (-dx) representing a peak of a deuterated internal standard.

38

Preliminary results from the analysis of six sites in the Atlanta metropolitan region regarding total PAH concentrations using PAS techniques are shown in Figure 5. While statistical analysis of variance could not be performed on single samples (replicates were only measured at one site), upon initial analysis, concentrations of PAHs at site A were two times greater than the average concentration of all other sites. This sampler was hung on a fence bordering the parking lot of an elementary school, where it was thought that buses idled prior to loading students for transport at the end of each school day. Although a height of 166 cm was used to approximate exposure for an average adult, it may not havee allowed for complete mixing of an air parcel prior to sampling. As a result, the data for this site was considered as an outlier and was not used in the combined chemical concentration and demographic analysis (shown in Figure 7).

Figure 5. Total PAH concentrations (pg m-3) for six sites in the Atlanta metropolitan region. Samples F1 and F2 represent replicate samplers hung at site F. These were the only replicate samples taken during this pilot project. Replicate samples at F1 and F2 demonstrated a small amount of variability, showing the importance for providing replicates at each sampling site. Upon analysis of the distribution of PAHs at each site, preliminary analysis shows differing compositions of the samples for different sites (Figure 6). The most prominent PAH in each sample was PHEN, followed by varying contributions from FLU, FLA, PY, and ACE. Preliminary analysis notes that Site F, our most forested site (Elachee Nature Science Center) contained more ACE than other sites, and Sites B and C have similar PAH profiles, despite being located over 40 miles from one another. It should also be noted that several semi-volatile and non-volatile PAHs were measured with the PAS. Although these sampling devices operate based on partitioning of analytes between the gas- and PUFphases, it has been shown previously that particulate matter can be collected (46, 56). The difference in distributions of PAHs amongst sites suggests that further investigation is needed into source differences or distances from sources (photodegradation during atmospheric transport). 39

Figure 6. Distribution of PAHs for Site A (top left), Site F (top right), Site B (bottom left) and Site C (bottom right). PAHs that appear in over five percent are represented structurally, according to pie chart color. Students compared total sum of PAHs (pg m-3) to the demographic information collected at each site for a preliminary environmental (in)justice analysis. Preliminary regression analysis gives the respective coefficients of determination shown in Figure 7. However, possibly due to our small number of samples (n = 6 in this analysis) and the lack of replicate measurements, the data shown in Figure 7 are inconclusive to the presence or absence of environmental (in)justices regarding PAHs (p > 0.05). Therefore, these correlations can be considered insignificant with respect to this study. However, this preliminary analysis is meant to demonstrate a proof of concept that these PAS could be used to increase spatial resolution of HAP concentrations on a large scale, thus increasing the strength of the dataset for exposure to the chemicals for different communities. For future studies containing a higher number of sampling sites (n > 50), sample sites should not only vary in demographic parameters, but also in distance from freeways and point-source contributions. Higher resolution GIS measurements should also be used for more conclusive interpretation of results.

Influence of Interdisciplinary Community-Based Research on Student Outcomes Students (n = 7) were presented with a survey of attitudinal opinions using an experience gains scale with question styles modeled after the survey of undergraduate research experiences (SURE) (57). The students were presented with the survey approximately six months after the conclusion of the project and all seven students responded to the survey. Of these students, 71.4% had not previously participated in an undergraduate research project at GGC, 42.9% 40

were from the SST and 57.1% were from the SLA. Students were asked to rate different parameters based on their experience during the EJ-CIP project as either a negative change, no change, small positive change, moderate positive change, or large positive change. The results from this survey are displayed in Table 5.

Figure 7. Correlation plots showing relationships between total sum of PAH concentration for each site as a function of % minority population (top), % low income (middle), and % linguistic isolation (bottom).

41

Table 5. Results of student survey after EJ-CIP participation % Participant Response

Parameter assessed Perception that scientific inquiry can be applied in everyday life

71.4% Large change 28.6% Moderate change

Understanding of how scientists work on real issues/problems

57.2% Large change 28.5% Moderate change 14.3% Small change

Perception that research questions can be successfully applied to address community issues

85.7% Large change 14.3% Moderate change

Confidence in your laboratory techniques

71.4% Large change 14.3% Moderate change 14.3% Small change

Confidence in communicating with researchers outside of your major

85.7% Large change 14.3% Moderate change

Confidence in working on a project in which some areas are outside of your expertise

71.4% Large change 28.6% Moderate change

Ability to work as part of a collaborative group

85.7% Large change 14.3% Moderate change

Understanding of the history of environmental justice and current policies in place

85.7% Large change 14.3% Moderate change

The parameters that saw the greatest percent of students reporting a “large positive change” included: • • • •

Perception that research questions can be successfully applied to address community issues; Confidence in communicating with researchers outside of your major; Ability to work as part of a collaborative group; and Understanding of the history of environmental justice and current policies in place.

Thus, the survey suggests that goals were met with respect to increasing the knowledge of undergraduates that academic research can be applied to community issues, the confidence and ability of students to communicate and work outside of their areas of expertise, and increasing awareness of environmental justice history and issues in the state of Georgia. Students generally reported an increase change for all parameters given, with the exception of “understanding that scientific assertions require supporting evidence.” Several students, when asked to express additional comments on the project offered: •

“It gave me (a social science major) the ability to understand that in leadership positions where legislation is being implemented, it is very important to merge with other disciplines and majors to gain as much information as possible to make the best decisions;” 42

•

• •

“The CIP made me realize the depth of work that can be done within the legal profession to help society at large. As a result, I am better able to focus more specifically on the type of legal career I wish to pursue”; “Working with other students with different majors, striving for the same goal was inspiring as well as educational;” and “So grateful to have been able to work with a team from varying degree programs.”

These comments suggest that the interdisciplinary nature of the project was well received by students, and encouraged them to persist throughout the term of the project. Based on these results, this project could be considered for implementation at other institutions interested in leveraging student interest in environmental and social issues to develop interdisciplinary research projects.

Future Goals Several students have suggested that this research project be offered as an official course, instead of just a faculty advised research project. The interdisciplinary nature of the project lends itself to the newly developed Environmental Science major here at GGC, which includes both a social science, and a natural science track. Political science students have also expressed an interest in participating in an official course such as this. They argue the active learning approach as well as the integration with other fields like chemistry help provide real world experiences that better connect the theories they study with their application. In continuing this project, it is expected to increase the sample number, number of replicates, and extend analyte analysis to include specific polychlorinated biphenyl (PCB) congeners. This theme will be used as a full semester long course integrated research project for the Environmental Science Capstone Course (ESNS 4900) offered at GGC in Spring 2018.

Acknowledgments We would like to thank our seven student researchers for their participation and energy put forth into this project. We would also like to thank Mr. Lee Irminger (Elachee Nature Science Center), Mr. Ken Buckley (GA Environmental Protection Division), Evoline C. West Elementary, and Duncan Creek Elementary School for their cooperation with hanging sampling devices. Special thanks to our external advisor, GreenLaw, for hosting our students and providing valuable feedback on their project plan. Faculty and support who were influential in discussing and promoting this project include Dr. Charles Pibel, Dr. Brian Etheridge, Dr. Aldolfo Santos, and Dr. Thomas Mundie. We thank the Georgia Gwinnett College Community Innovations Project program and the School of Science and Technology for funding. The results and contents of this publication do not necessarily reflect the views and opinions of the external advisors or collaborating partners. 43

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Chapter 3

Undergraduate Research Experience in Remote Sensing A. Kahl* Environmental Engineering, Penn State Greater Allegheny, 4000 University Dr., McKeesport, Pennsylvania 15132, United States *E-mail: [email protected].

The Multi-Campus Research Experience for Undergraduates (MC REU) is an initiative to increase undergraduate research at the Pennsylvania State University (Penn State), Greater Allegheny. The MC REU program supports Penn State undergraduate engineering students to conduct research with Penn State faculty. Students participating in the program complete a proposed engineering research project in conjunction with two Penn State faculty members; one from the student’s home campus and one faculty member based at University Park. The objectives of the MC REU are: (1) to promote undergraduate students participating in research early in their academic program to broaden their education and increase their chances of entering graduate studies; and (2) to promote mutual awareness and collaboration among faculty across the Commonwealth. This chapter details the results of two sessions of undergraduate research in remote sensing, with special emphasis on student engagement outside of the classroom and collaboration with faculty.

© 2018 American Chemical Society

Introduction The purpose of the research is to build and establish a network of data loggers across Western Pennsylvania to monitor water quality and observe salinization trends. Data loggers are simple sensors that collect and store information over time for a particular location. The problem with current water quality research is the lack of data across a focus area. If a large network can be easily and inexpensively built along streams and rivers in a focus area (in this case Western Pennsylvania), more insight can be found on the causes of poor water quality in drinking water sources. To do so, salinization measurements will give insight on overall water quality. Salinization can be found with a measure of conductivity, directly related to the concentration of total dissolved solids in the water (1). The problem with recent brand name data loggers is that they are too intricate and expensive for simple research purposes. What is needed to advance the current state of knowledge is a simple yet robust sensor that is cheap to build and easy to operate. Results from deploying this sensor will give an understanding on the behaviors of the dissolved solids present in surface water such as salt. Over time, the inexpensive data loggers have the potential to lead to a network of sensors blanketing Western Pennsylvania, therefore increasing awareness of water contamination issues. As the project is in its early stages, mapping the area where these sensors will be deployed has not yet occurred. Water quality data coupled with the emerging field of data science has the potential to expedite scientific research and inform decisions about resource allocation. One of the areas with the most potential for growth and innovation is that of the water sensing. Current water sensors are large, cumbersome to use and require specialized maintenance in order to gain reliable data sources. This limits the number of sensors citizen groups can deploy as well as the duration that they can be maintained. Smart systems, such as the internet of things (IOT) sensor network in this work can help track contaminants at the backyard level and act as first line avenues for data collection. The niche that citizen groups fill within the water quality data nexus is currently small due to the limited availability and accessibility of water quality sensors. Increasing data yields in a measurable way through inclusion of IOT sensors and optimization can build out the footprint of those community groups in a sustainable way. This in turn will build capacity within the network and provide a jumping off point for community revitalization efforts. Sensors for the IOT are growing in prevalence and availability. A Wall Street Journal article last year estimated that the IOT market could reach $1.7 trillion by 2020 (2). IOT technology has moved beyond indoor space and into the outdoors recently with a number of products and services such as the Edyn watering sensor. The Edyn garden sensor has 5 sensors. It measures temperature, humidity, light levels, soil moisture and soil nutrition (3). The Edyn probe functions by sending an electrical pulse into the soil and detecting how that pulse is affected by fertilizer and water using a technique that is identical to that used in commercial farming. It also includes extensive digital dictionaries indexing the compatibility, preferred conditions, and seasonal watering needs for thousands of plants. The current version of the Edyn is produced commercially and costs $99 50

per sensor, which is still a substantial amount of money, particularly for a large network of sensors. There are currently open hardware low-cost data loggers for turbidity, but not other water-quality parameters such as salinity. An NSF-sponsored critical zone observatory (CZO) also includes multiple data loggers built with open-sourced hardware (Arduino) and monitoring equipment, but to our knowledge no conductivity measurements are recorded regularly and no sensor design was included in the design. The MC REU project is in its third year of existence. The REU program connects faculty and students early in their careers to help build a foundation of undergraduate research. Students spend most their time at their home commonwealth campus, with two weeks out of the ten-week experience in workshops with the entire cohort at University Park. Having two faculty mentors (one from each campus) allows students to make bridging connections and extend their research networks early in their undergraduate careers. It has been shown that students that participate in undergraduate research show increased interest in graduate study (4). A survey of researchers participating in NSF REUs showed a 29% increase in interest of students in pursuing a PhD after graduation following their undergraduate research experience (4). An emphasis of the MC REU program is for students to participate in the culture of research by experiencing faculty mentorship, presenting at the end of experience conference and writing about their research work. In this way, students broaden their education and increase their awareness of pathways to graduate education. Another emphasis of the MC REU program is to connect faculty from Commonwealth campuses to other faculty within Penn State. Faculty mentors collaborating on shared research goals with shared student workers promote awareness of Penn State resources and avenues for collaboration. A goal of the program is to spawn new research collaborations as well as to promote the use of shared resources for research.

Methods This project is based on the Arduino platform and uses Arduino Unos as its basis due to their wide availability and ease of use at an entry level. Arduino is an open source platform for building electronics. The Arduino system consists of a microcontroller or small circuit board, and software that is used to write and upload code to the microcontroller. Arduino code is based on C++, and is simple to learn and use, making it an ideal choice for an undergraduate research project. Two student teams worked over the course of two summer term periods to refine and test a basic sensor design. For the purpose of this exercise, each design was focused on sensing conductivity as the main goal. The first iteration of the sensor is a simple Arduino Uno that has three power sources, built in temperature sensor diodes, and a customizable protoboard. This sensor, called the Riffle, was originally produced by PublicLab as part of the Open Water Project. The Riffle can also be attached to a protoboard to increase 51

its sensing capability. Both the Riffle and associated protoboard are shown in Figure 1. The Riffle can be powered with a lithium-ion battery, a button-cell battery, or a USB/microUSB port. The temperature is automatically logged on a microSD card for the Riffle. In order for the Riffle to measure conductivity, a circuit design capable of doing so was soldered onto the protoboard attachment. In order to make the Riffle compatible with a conductivity probe, the protoboard was adapted to include a sensor array called the Coqui. The Coquí (Figure 2) is designed with a probe that acts as a variable resistor.

Figure 1. Riffle Arduino board (top) and associated proto board (bottom).

Figure 2. Coqui sensor on protoboard. 52

When the electrodes are placed into a solution, the solution has a specific conductance; therefore, acting as a resistor. Depending upon the voltage going through the circuit, the pitch of the piezo speaker varies. For example, if the probe is placed into water with high conductance, the pitch of the sound released from the piezo speaker increases. The speaker can be replaced with an LED light that will act similarly to the speaker. The light shines brighter the more conductive the sample is. The LED that is already in the circuit diagram in Figure 2 acts as an ‘on/off’ power indicator. To adapt the Coquí to the Riffle attachment, the piezo speaker is replaced with the analog read pin. The protoboard is designed where the top two rows are labeled connections that run to the data logger. The rest of the pins on the protoboard are connected vertically down the board. A diagram of the Coquí design for the protoboard can be seen in Figure 2. The LED is still used as a power indicator in the protoboard design. The protoboard is then connected to a simple nichrome wire probe which can be used to test the water sample. This simple device was then tested by the student to determine how well it performed compared to a traditional conductivity probe. The students then used these tools to evaluate prepared water samples. The prepared water sample consisted of tap water that had varying levels of salt present. During this challenge, students were required to answer the following questions: Does the new conductivity probe give good data compared to a traditional probe? Is the new conductivity probe easy to use? Could the design of the probe be improved? In what way? What are potential community uses for the conductivity probe? Questions were posed in oral form, following project discussion with faculty mentors in the eighth week of the REU experience. Students responded to these questions both orally and in the written form of a report. It was found that the Arduino based probe did not perform as well as the traditional probes within a reasonable margin of error (10-15%), likely due to interferences on the nichrome wire probe which lead to variation in the cell constant. As the comparison test was only performed one time, data is not included here. Students in future undergraduate research experiences will perform the comparison test multiple times to generate a larger data set for analysis, including statistics. Anecdotally, collecting and analyzing data helped to stimulate and sustain student interest in research, as students involved in the project were able to see their efforts manifest. Students made several suggestions regarding the design of the probe, the most common response being to make the probe more robust. This response was a valuable insight as the project continues to develop. For future work, undergraduate researchers will fabricate a housing to better protect the probe and reduce interferences. Regarding potential community uses for the probe, 53

monitoring water quality downstream of industrial discharges and within local water bodies for fishermen were two popular responses. Students involved in the MC REU program were asked to produce weekly reports about their research experience, blog about topics related to undergraduate research and present a final poster at the closing research forum.

Discussion Close collaboration with faculty is one of the main goals of the program, which is fostered by the structure of the REU. As part of student engagement within the MC REU program, each student spends 8 weeks at their home campus and 2 weeks at the University Park Penn State campus. During this time, students visit laboratories on campus, attend sessions about career development and teambuilding, and meet with additional faculty and graduate students. Although working independently on a research project, students receive faculty support and instruction for several hours each week to help achieve their goals. This close collaboration is cited by students as the most valued asset of the program. Both sessions that have engaged with this program cite the close collaboration with faculty as well as the hands-on nature of the research activity as stimulating their interest in research. More specifically, the students were surveyed if they would continue doing undergraduate research. All responses were either agree or strongly agree. One commented that participating in the project “…helped me to see research as an avenue for a possible career that I had not considered before.” It was also noted in the comments portion of the poll that presenting their research in the closing forum helped them to better understand not only the material but to stimulate the interest of others in the audience in the growing field of remote sensing.

Conclusions This research experience has resulted in an engaged student experience that provides in-depth topic exploration and familiarity with complex material as well as providing greater engagement between faculty and students. Students benefited from the interaction with real world research problems as well as their own discoveries to provide enhanced understanding of the research process. Students responded overwhelmingly positively to this activity, and it is planned to continue to offer this research experience for students. For future work, students will map the area of Western Pennsylvania for sensor placement, and collect and interpret relevant water quality data using the sensors.

Acknowledgments The author would like to acknowledge the support of the Penn State Greater Allegheny community during preparation of this submission. 54

References 1. 2. 3. 4.

Thomas, A. G. Specific Conductance as an Indicator of Total Dissolved Solids in Cold, Dilute Waters. Hydrol. Sci. J. 1986, 31 (1), 81–92. Norton, S. Internet of Things Market to Reach $1.7 Trillion by 2020. The Wall Street Journal, June 2, 2015. Flatow, I. The Blossoming Internet of Things for Your Garden. Science Friday, April 29, 2016. Russell, S. H.; Hancock, M. P.; McCullough, J. Benefits of Undergraduate Research Experiences. Science (Washington) 2007, 316 (5824), 548–549.

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Chapter 4

Trends in Atmospheric Ammonia: An Environmental Chemistry Class Project Vivian C. Ezeh* Department of Chemistry, Kenyon College, 200 N. College St., Gambier, Ohio 43022, United States *E-mail: [email protected].

An environmental chemistry class managed an ammonia monitoring station as a class project. The ammonia station was part of the National Atmospheric Deposition Program. The pedagogy goal for the project was to improve quantitative reasoning skills, such as data management and visualization. The data obtained during the fall 2017 semester was used to teach data management, graph making and mapping with a GIS program. Evaluation of submitted project assignments and students’ response to an end-of-semester survey support an improvement in quantitative reasoning skills.

Introduction How do we know if an environmental policy to reduce pollution is effective? Answers can be obtained from environmental data collected by a network of monitoring stations. There are several environmental networks dedicated to measuring, collating, and archiving various environmental data. An example is the “Ammonia Monitoring Network (AMoN)” which as part of the National Atmospheric Deposition Program (NADP) monitors ammonia gas concentration in the atmosphere (1). This and other networks are very important to our understanding of the trends in various environmental data. Ammonia (NH3) is a compound that exists as a gas in the atmosphere at atmospheric pressure and temperature. Agriculture practices such as farming and animal husbandry are primary sources of NH3 to the atmosphere (2). Acting as a basic gas in the atmosphere, NH3 reacts with acidic species to form ammonium salts which contribute to aerosol formation as particulate matter (PM) (3, 4). © 2018 American Chemical Society

When the ammonium salts fall back to land and water, they contribute to acidification and nitrogen eutrophication (3). NH3 in the atmosphere also reacts with secondary organic aerosols contributing to photochemical smog (5). The concentration of NH3 in the atmosphere is increasing and there is currently no policy to regulate the gas (Figure 1) (6, 7). Some gases regulated by the United States Clean Air Act show decreasing concentration trend. For example, sulfur dioxide (SO2) and nitrogen dioxide (NO2) levels in the atmosphere are declining (Figure 1) (7). Tracking atmospheric NH3 is important to understanding trends and effects of the gas in the environment. The data can also inform policies to regulate atmospheric NH3. With Kenyon College located in an agricultural community, the atmospheric ammonia monitoring station is an important data point in obtaining a better picture of the ammonia pollution problem. There are six AMoN sites in the state of Ohio, the Kenyon College site (labeled OH32) is the only one on a college campus.

Figure 1. National Emission Inventory (NEI, 2015), SO2 (reported as S), NOx and NH3 (both reported as N) emissions from 2001 to 2014. NOx is assumed to be in the form of NO2 (7). Reproduced with permission from reference (7). Copyright 2016 Elsevier. The AMoN project was incorporated as a course-based research experience in an environmental chemistry class to improve the quantitative reasoning course goal (8, 9). The hypothesis for the ammonia class project is that the process of answering the research questions will improve problem-solving and quantitative skills. This book chapter is a description of involving a class in a network data collecting experiment. The success, challenges, and feedback of beginning a course-based research experience will be discussed. Also discussed will be a personal reflection of an early career faculty on course design. 58

Course and Project Description Environmental Chemistry, CHEM 110, is a chemistry class designed for students to fulfill the requirement to take a science-based course if they major in humanities, arts and languages. The majority of the students are political science, international studies, or economics majors. The course is also designated as a quantitative reasoning (QR) course. A QR course focuses on the organization, analysis, and implementation of numerical and graphical data. To enhance the QR aspect of the course, the 2017 fall semester CHEM110 class (20 students) managed an ammonia monitoring station on campus. The project was supported by a grant from the Kenyon College faculty affairs committee. The project goals were: 1) Write and execute a data management plan, 2) Collate and graph ammonia concentration and weather data (temperature, pressure, humidity, wind speed, visibility), and 3) Plot ammonia data on a geographic information system. The secondary goals were: 1) to expose students to a field-based project and 2) use data to make observations. Several activities and assignments were incorporated into the course schedule to support the project goals. A workshop on data management was facilitated by the Social Science and Data Librarian and then each team wrote a data management plan. For project goal 2, each team designed a Google sheet to collate project data. Also a workshop on plotting graphs with Google sheets was facilitated by the Social Science and Data Librarian. At the end of the semester, each student made graphs (line graph, scatter plot with trend line and 2D plots) with their collated project data. The third project goal was achieved by plotting data from the six sites in Ohio onto the Ohio state map by using Google MyMaps. Finally, a project survey was carried out to gauge the success of the project goals. The National Atmospheric Deposition Program (NADP) - National Trends Network (NTN) was established in 1977 with a mission to study atmospheric deposition and its effects on the environment.1 The network has been collecting data (amount, trends, and geographic distribution) on various atmospheric pollutants such as acidic precipitation, mercury, and ammonia. Although initially funded by the United States Department of Agricultural, NADP is now supported by a network of researchers. Measurement of ammonia started in 2010, and the network consist of approximately 100 monitoring stations (1). The data collected are the only consistent record of atmospheric ammonia concentration in the United States. Participating in the network consist of hosting a sampling site, changing samplers according to protocol and mailing the samplers to the NADP central analytical lab (CAL) for analysis. AMoN uses a Radiello (radial diffusive or passive) sampler for the ammonia project. The Radiello sampler is made of microporous polyethylene impregnated with phosphoric acid, NH3 is selectively adsorbed from the atmosphere and is trapped as ammonium salts (10). The sampler deployment is on a two-week cycle; which means a sampler is installed on a Tuesday, removed on a Tuesday two weeks later and mailed to the CAL for chemical analysis. Preliminary ammonia concentration (measured as µg/m3) results are received about two weeks after the sampler is received at the CAL.

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Project Implementation In preparation for siting the ammonia sampler on campus, several locations on campus were evaluated during the summer of 2017. The chosen location was in an open field, with low vehicle & human traffic, and greater than 1 km (0.62 miles) from agricultural activities. Geographical information such as latitude (40.370055 N), longitude (82.395539 W) and altitude (312 m) was recorded. A shelter to house the sampler was installed at the beginning of the fall 2017 semester, and the first sampler was deployed on Aug 22nd 2017. After introductions on the first day of class (Aug 24th 2017), the class visited the sampler location to observe the setup. An article “Nitrogen from the Environment” was assigned to the class to acquaint students with the class project (11). Students then completed a brief survey designed to get the class invested in the project (Survey 1, Table 1). Based on responses from the survey, 6 teams of 3-4 students were formed. Also, the class wanted to explore how the following variables would affect ammonia concentration trends: 1) weather (temperature, pressure, wind speed & direction, humidity, and visibility), 2) vegetation change, and 3) location of samplers around Ohio. In summary, the class decided to track weather conditions by checking weather websites and record vegetation changes by taking pictures of vegetation around the sampler. The bulk of the semester was spent changing the sampler according to schedule and collating project data. Each team sent a representative for the sampler change.

Table 1. Survey 1: Questions at the beginning of project #

Survey Questions

1

What are reactive nitrogen species

2

How will participating in this project benefit your college, personal or career goals

3

How would you organize this project to ensure that everyone benefits and contributes to its success

4

Give one example of another environmental data (apart for concentration of ammonia) that we could collect to enrich the project

Within the semester, two 30 min workshops were included in the class schedule to teach data management and graphing skills. The concepts covered in the data management workshop included: file naming strategies, options for preserving data, and categories of data. Each team wrote a data management plan and submitted via Google Docs. Students were able to articulate the class project goals and plan with the data management plan assignment. Graphing with Google sheets, classification of variables, and interpretation of R2 values were taught at the second workshop. 60

After 13 weeks of the monitoring project, the class project was completed in an 80 min workshop. Using the collated data, students made several graphs during the workshop to answer the project research questions. Examples of graphs completed included; line graphs, scatter plots (with Trendline & R2 value), 2D plot (line graph with 2 y-axes) and a matrix plot (graphical comparison of several variables). Each graph was copied to a Google slide with a figure number and short description. A mapping exercise with data from other sites in the state of Ohio was also completed. Average ammonia concentration for the 6 sites in Ohio was obtained from the AMoN website and mapped with the Google MyMaps GIS. Finally, each student wrote a summary which included their observations and discussion of the team’s results.

Project Results By the project wrap date, we had five ammonia concentration data points. The class decided that the best representation of ammonia data was to match it to the Tuesday dates between the 2 weeks sampling period. For example, one ammonia concentration value represented the two weeks from Aug 22nd to Sept 5th. However, for the plotting assignment, that ammonia concentration was matched to Aug 29th and the corresponding weather data for Aug 29th. A plot of ammonia concentration and Tuesday dates showed a general increase in ammonia concentration during Aug to Oct 2017 (Figure 2). Each student made a plot of ammonia concentration as a dependent variable with their weather data as an independent variable. Figure 3 is an example of a scatter plot of ammonia concentration and temperature. Following a discussion of outlier data points, linear regression analysis was performed with 4 data points, and R2 values were obtained. On the question of weather conditions effect on ammonia trends, we observed no correlation between ammonia concentration and pressure or visibility. A positive correlation with temperature (Figure 4) and a negative correlation with humidity or wind speed. Ammonia concentration data for the other sites in Ohio was obtained from AMoN website. A geographical information system plot was made with average ammonia data for Aug – Oct 2017 (Figure 5). We observed that Cincinnati (OH27) site had the highest average ammonia concentration, while the lowest was at the Deer Creek State Park (OH54) site. Finally, the highest ammonia concentration (2.21 µg/m3) during the Aug – Oct sampling period for Kenyon site (OH32) corresponded with a complete loss of leaves on trees close to the sampler.

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Figure 2. Scatter plot of ammonia concentration (µg/m3) vs date for Aug 22nd – Oct 31st 2017.

Figure 3. Scatter plot of ammonia concentration (µg/m3) vs temperature (°F) for fall 2017.

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Figure 4. Scatter plot of ammonia concentration (µg/m3) vs temperature (°F) for fall 2017 after removing the possible outlier data point.

Figure 5. GIS plot of average ammonia concentration (µg/m3) for sites within the state of Ohio for fall 2017 (Aug 22nd – Oct 31st).

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Assessment The class project was classified as a formative exercise in the class design and accounted for 10% of the class grade. Students were allowed to make corrections after feedback for the full possible point per activity. A survey (Survey 2, Table 2) was used to evaluate the quantitative reasoning skills gained from the project. Student response (15 students) showed a significant number learned or gained the QR skills taught by the project.

Table 2. Survey 2: Questions at the end of project #

The ammonia project was included to enhance the quantitative reasoning designation of CHEM110. Rate the following QR skills as 1 (I didn’t learn this skill); 2 (I learned or improved on this skill); 3 (I knew this before) or N/A (didn’t participate in this activity)

1

Designing and executing a data management plan

2

Organizing data on a spreadsheet and preserving the data

3

Plotting data on graphs

4

Plotting data on a map

Figure 6. Response to survey 2.

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Discussion The project was successfully implemented and having the class project enhanced the communal feel of the class. Use of passive samplers and chemical analysis conducted at CAL made the project easier to incorporate into the course schedule without significant change to course content. Students practiced asking research questions and agreeing on which inquires to pursue. As they were searching for answers, they learned data management, graphing and visualization skills. Although we had a small data set, some observations on ammonia concentration trends were made. The effect of nearby agricultural activities, leaves loss and decomposition, and urban heat were discussed in summary submitted by students. In summary, the class project provided a great platform to enhance the QR designation of the environmental chemistry class. The time commitment to manage the project was low. After the time required for initial planning, the bi-weekly sampler change takes about 10 min to complete. The small time commitment made it easier to juggle with the busy schedule of academic life. Implementing the project provided an opportunity to collaborate with colleagues outside of my department in designing pedagogy activities. Most of the schedule went as planned; we just required an extra half class time to complete the graph and mapping assignment. In all, it was a successful class project.

Conclusion and Future Directions Data from ammonia monitoring on campus was used to teach graph and visualization skills. Observation from our limited data was similar to trends reported from analysis of larger data sets tested with rigorous statistics tools (7). The monitoring project will continue and by the next class there will be more data points to work with. With a larger data set, more statistics skills will be included in the class project.

Acknowledgments I thank the faculty affairs committee of Kenyon College for awarding the teaching grant that provided funding for this class project. Nathan Wolfe, Social Science and Data Librarian at Kenyon College, was valuable to the successful implementation of the class project. He provided expertise in data management and visualization. I am grateful to colleagues that provided support for the smooth running of the class project. Steven Vaden, constructed the shelter for the sampler. Emily Wise managed the finances for the project. Mrs. Shannon Hashman assisted by making sure that the samplers are mailed back to CAL. Mrs. Carolyn Waggoner helped by receiving the sampler. Prof. Simon Garcia provided support as the alternate site manager.

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References NADP National Atmospheric Deposition Program, Ammonia Monitoring Network (AMoN). http://nadp.isws.illinois.edu/AMoN/ (accessed January 14, 2018). 2. Warner, J. X.; Dickerson, R. R.; Wei, Z.; Strow, L. L.; Wang, Y.; Liang, Q. Increased atmospheric ammonia over the world’s major agricultural areas detected from space. Geophys. Res. Lett. 2017, 44 (6), 2875–2884. 3. Sutton, M. A.; Tang, Y. S.; Dragosits, U.; Fournier, N.; Dore, A. J.; Smith, R. I.; Weston, K. J.; Fowler, D. A spatial analysis of atmospheric ammonia and ammonium in the U.K. Sci. World J. 2001, 1, 275–286. 4. Meng, Z.; Lin, W.; Zhang, R.; Han, Z.; Jia, X. Summertime ambient ammonia and its effects on ammonium aerosol in urban Beijing, China. Sci. Total Environ. 2017, 579, 1521–1530. 5. Liu, Y.; Liggio, J.; Staebler, R.; Li, S.-M. Reactive uptake of ammonia to secondary organic aerosols: kinetics of organonitrogen formation. Atmospheric. Chem. Phys. 2015, 15 (23), 13569–13584. 6. Walker, J.; Nelson, D.; Aneja, V. P. Trends in Ammonium Concentration in Precipitation and Atmospheric Ammonia Emissions at a Coastal Plain Site in North Carolina, U.S.A. Environ. Sci. Technol. 2000, 34 (17), 3527–3534. 7. Butler, T.; Vermeylen, F.; Lehmann, C. M.; Likens, G. E.; Puchalski, M. Increasing ammonia concentration trends in large regions of the USA derived from the NADP/AMoN network. Atmos. Environ. 2016, 146 (Supplement C), 132–140. 8. Russell, J. E.; D’Costa, A. R.; Runck, C.; Barnes, D. W.; Barrera, A. L.; Hurst-Kennedy, J.; Sudduth, E. B.; Quinlan, E. L.; Schlueter, M. Bridging the Undergraduate Curriculum Using an Integrated Course-Embedded Undergraduate Research Experience (ICURE). CBE Life Sci. Educ. 2015, 14 (ar4), 1–10. 9. Brownell, S. E.; Hekmat-Scafe, D. S.; Singla, V.; Seawall, P. C.; Conklin Iman, J. F.; Eddy, S. L.; Stearns, T.; Cyert, M. S. A High-Enrollment CourseBased Undergraduate Research Experience Improves Student Conceptions of Scientific Thinking and Ability to Interpret Data. CBE Life Sci. Educ. 2015, 14 (ar21), 1–14. 10. Radiello - The Radial Diffusive Sampler. http://www.radiello.com/english/ nh3_en.htm (accessed October 25, 2017). 11. NADP Nitrogen from the Atmosphere. http://nadp.isws.illinois.edu/lib/ brochures/nitrogenAtmos.pdf (accessed January 14, 2018). 1.

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Chapter 5

Using DNA Barcoding To Identify Duckweed Species as Part of an Undergraduate Ecology Course Stokes S. Baker* Biology Department, University of Detroit Mercy, 4001 West McNichols Road, Detroit, Michigan 48221, United States *E-mail: [email protected].

DNA barcoding identifies species by sequencing polymerase chain reaction (PCR) amplicons and comparing the amplicon sequence to sequences found in databases. There are many applications of this technology that support environmental investigations. As part of an inquiry ecology laboratory course, undergraduate students at the University of Detroit Mercy conducted nutrient response experiments with duckweed, floating aquatic plants. The students used DNA barcoding to identify their wild collected plants because duckweed are extremely small and do not possess distinctive morphological features. The results of barcoding with the chloroplast atpF-atpH intergenic region showed that a cove in Lake Saint Clair, Michigan, USA, hosted a duckweed community that contained at least four species. One of the species, Lemna obscura, has never been reported in Michigan waters. This paper describes how primer design, a robust DNA extraction procedure, software use, and database utilization can be incorporated into laboratory instruction.

© 2018 American Chemical Society

Introduction For over two decades, national organizations (1–4) have called for reform of undergraduate science, technology, engineering and mathematics (STEM) education by replacing content driven curriculum with curricula that focuses on teaching core concepts and developing skills that support modern scientific research. Recently, the American Association for the Advancement of Science has called for revisions of biology curriculum to teach scientific skills by integrating major principles, such as information flow, with activities that develop competency in mathematics and provide undergraduate students experiences in accessing large data sets (5). Ecology, a subject that has always been interdisciplinary, has placed growing reliance on the use of molecular tools (6) and the utilization of large databases (7). Unfortunately, most ecology laboratory teaching manuals do not contain exercises that provide students experience with molecular ecology, nor exposure to database utilization. [For example, see Vodopich (8)] DNA barcoding is a technique well suited to ecological investigations. Species are identified by homology searches of DNA databases like GenBank (9). Thus, student investigations that utilize DNA barcoding provide them an introduction to molecular ecology and exposure to publicly available supercomputing resources. An inquiry investigation was implemented in the Ecology Laboratory (BIO4490) course taught at the University of Detroit Mercy (Detroit, MI, USA), where undergraduates conducted nutrient response experiments with wild duckweed. DNA barcoding is a technique that is used to identify species by sequencing short (400 to 800 bp) regions of genomes (10). This strategy involves using polymerase chain reaction (PCR) primers that are homologous to evolutionarily conserved regions that flank a variable region. The resulting amplicon sequence is determined by combining Sanger sequencing with capillary electrophoresis (11). The resulting sequence is used to search nucleotide databases such as GenBank (9, 12). Ecologists use DNA barcoding in several applications such as identifing species from small fragments collected from environmental samples, identifying microorganisms, and identify species from individuals that do not contain definitive morphological features (10). Though there is no single primer pair that can be used to barcode all of life, a limited collection of primer pairs have emerged that can be used to identify broad collections of taxonomic groups (10, 13). For plants, primers that hybridize to the plastid genome are widely used because each plant cell contains several copies of its plastid genome (14). Two commonly used primer pairs are rbcL which amplifies a 654 bp portion of the gene encoding the large subunit of ribulose bisphosphate carboxylase/oxygenase (RuBisCO) and atpF-atpH which amplifies 578 to 707 bp intergenic region of the ATP synthase locus (15, 16). Duckweed plants were used in the Ecology Laboratory course because it is becoming an excellent model system. They are small free-floating plants that proliferate in the 48 contiguous states, Hawaii, and southern Canada (17). Duckweed plants grow easily in the laboratory (18), have rapid clonal reproduction (19) and are extensively used in toxicology testing (20). Duckweed 68

are monocots in the clade Lemnoideae (21). Unfortunately, because of its small size and infrequent flowering, it is a difficult plant to identify at the species level (22). In the past, biochemical assays, such as chromatography, were used to confirm species identification (22). DNA barcoding is now the tool of choice for duckweed identification. For example, the Rutgers Duckweed Stock Cooperative only accepts germplasm donation that has been identified by DNA barcoding (23). A standard practice in field ecology is to identify species found in field collections. Typically, this is done with the aid of dichotomous keys and field guides. Unfortunately, reliable identification of duckweed based solely on morphology is not possible. Thus, a modified version of the DNA Learning Center’s Barcoding 101 curriculum was used to identify duckweed species (13).

Materials and Methods Plant Material During the month of September (2014, 2015 and 2016), duckweed populations (Figure 1, Panel A) were field-collected from an abandoned marina in Lake Saint Clair, Michigan, USA (Latitude 42.56141, Longitude -82.84313). To assess the species diversity of the population, students were asked to choose plants that had different morphological features. The plants were photographed with an SLR digital camera with a 100 mm macro lens or with a dissecting microscope with a built-in digital camera (Figure 1, Panels B - D). A DNA sample was also isolated from a coleus plant (Plectranthus amboinicus). The plant was obtained from a retail outlet. The resulting coleus DNA sequence was used as an outgroup for making dendrograms.

DNA Isolation Total DNA was isolated using the Wizard Genomic DNA Purification Kit (Promega Corporation, Madison, Wisconsin, USA). Splash goggles and plastic gloves were worn during the procedure because some of the reagents in the kit contain chaotropic agents. The work-flow is illustrated in Figure 2. Forceps were used to transfer clonal duckweed clusters into 1.5 mL microcentrifuge tubes. Up to 40 mg (fresh weight) of plant materials was homogenized in 100 μL of Nuclei Lysis Solution using plastic pestles design to fit inside the microcentrifuge tubes. The material was ground by hand until the plant materials were well macerated. An additional 500 μL of Nuclei Lysis Solution was added to each tube and mixed by inverting. The manufacturer’s protocol was followed for the remainder of the DNA isolation process.

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Figure 1. Wild population of duckweed. Panel A: A mixed species community growing in Lake Saint Clair, Michigan. The arrow points at a water lily, a member of the Nymphaeaceae. Close-up photographs of Spirodela polyrhiza (Panel B), Lemma minor (Panel C), and Wolffia columbiana (Panel D). The bars are 2-mm size standards. (see color insert)

Figure 2. Workflow of DNA extraction protocol. 70

Barcoding Primers For this study, oligonucleotides that could hybridize to plastid DNA were used as PCR primers. For most applications, the rbcL primer pair are suitable (15, 16). However, for the identification of duckweed species, the atpF-atpH primer pair should be used (24). More details will be presented in the Instructional Prospective section. For the rbcL locus (13) the primer sequences are 5′-ATGTCACCACAAACAGAGACTAAAGC-3′ (forward primer, tm = 59.6 °C) and 5′-GTAAAATCAAGTCCACCRCG-3′ (reverse primer, tm = 52.8 °C). For the atpF-atpH locus (24) the primer sequences are 5′-ACTCGCACACACTCCCTTTCC-3′ (forward primer, tm = 59.6 °C) and 5′-GCTTTTATGGAAGCTTTAACAAT-3′ (reverse primer, tm = 50.1 °C). To facilitate automated DNA sequences, oligonucleotides that fused plastid DNA primer sequences with M13 universal sequencing primer sequences were synthesized. The M13 forward (-21) universal sequencing primer sequence is 5′-TGTAAAACGACGGCCAGT-3′ and the M13 reverse (-27) universal sequencing primer is 5′-CAGGAAACAGCTATGAC-3′(25). The M13 universal primer/rbcL fusion primers (13) used were 5′-TGTAAAACGACGGCCAGT/ ATGTCACCACAAACAGAGACTAAAGC-3′ (forward fusion primer), and 5′-CAGGAAACAGCTATGAC/GTAAAATCAAGTCCACCRCG-3′ (reverse fusion primer). The M13 universal primer/atpF-atpH locus fusion primers used were 5′-TGTAAAACGACGGCCAGT/ACTCGCACACACT CCCTTTCC-3′ (forward fusion primer) and 5′-CAGGAAACAGCTATGAC/ GCTTTTATGGAAGCTTTAACAAT-3′ (reverse fusion primer). The oligonucleotides were purified by high-performance liquid chromatography (HPLC) by the manufacturer (Bio Basic, Markham, Ontario, Canada). They were diluted and combined to make primer mixtures containing 0.5 pmoles/μL forward primer and 0.5 pmoles/μL reverse primer.

PCR Conditions Illustra PuReTaq Ready-To-Go PCR Beads (GE Healthcare Life Sciences, Pittsburgh, Pennsylvania, USA) were used for all sequencing reactions. This system uses freeze-dried pellets that contain a hot-start Taq DNA polymerase, deoxynucleotides, buffers, and co-factors. Only DNA template and primers are needed to complete the mixture. To perform the PCR reaction, the following was added to each 200 μL Ready-To-Go PCR Beads tube: 6.63 pmoles of each primer, ~50 ng plant DNA, and enough PCR grade water to bring the final volume up to 25 µL. The thermocycling conditions used are described below. For tubes containing the M13 universal/rbcL gene fusion primer, initial template melting was at 94 °C for 180 s, followed by 35 cycles of template melting at 94 °C for 15 s, template priming at 54 °C for 15 s, and polymerization at 72 °C for 30 s. The final polymerase extension was performed at 72 °C for 300 s (13). The PCR product was stored overnight at 4 °C. For tubes containing the M13 universal/atpF-atpH locus fusion primer, initial template melting was at 94 °C for 120 s, followed by 35 cycles of template melting 71

at 94 °C for 15 s, template priming at 50 °C for 15 s, and polymerization at 72 °C for 45 s. The final polymerase extension was performed at 72 °C for 300 s (26). The PCR products were stored overnight at 4 °C. If there were poor PCR product yields with either primer set, the following PCR protocol was attempted. Genomic DNA and primers were combined as described previously. Initial template denaturation was at 95 °C for 180 s, followed by 40 cycles of denaturation at 95 °C for 60 s, annealing at 55 °C for 45 s, and primer extension at 72 °C for 45 s. The final polymerase extension was performed at 72 ○C for 300 s.

Analysis of PCR Products and Sequencing To determine if appropriate PCR amplicons were produced, 5 μL of the PCR reactions were fractionated by 2% agarose 1X TBE gel electrophoresis (25). After electrophoresis, gels were stained with 1X GelGreen Nucleic Acid Stain (Phenix Research, Candler, North Carolina, USA) and illuminated with a blue light emitting diode transilluminator (Figure 3). The remaining 20 μL of PCR products were held in reserve for DNA sequencing.

Figure 3. Example results of a 2% agarose showing PCR products from the atpF-atpH locus and the rbcL locus. The numbers identify DNA samples extracted from individual plants. The PCR reaction that produced appropriate amplicons were sent to a commercial sequencing faculty (GENWIZ, South Plainfield, New Jersey, USA). The core facility performed amplicon purification and Sanger sequenced the amplicon using M13 universal primers. Both the forward and reverse strands were sequenced. 72

Sequence Quality Control Students evaluated the quality of their DNA sequences by visual inspection of the capillary electrophoresis chromatograph traces. To do so, the students downloaded Chromas 2.6.4 (27) (Technelysium Proprietary Limited, South Brisbane, Australia), free software that shows the four color channel traces and deduced DNA sequence (Figure 4). Ambiguous sequences from the 3’-end and 5’-end were trimmed, and internal sequences that were called “N” were changed to the correct base when the peaks could be reliably evaluated by inspection. The corrected sequences were exported as FASTA files.

Figure 4. Four channel chromatograph of Sanger sequencing product visualized with Chromas 2.6.4. If the DNA sequences were correctly identified, the nucleotide sequence of the forward strand and the reverse-complement sequence of the reverse strand should be identical. To evaluate their sequence reliability, the students used web-based software (28) that uses a Needleman-Wunsch alignment algorithm (29) to align their forward and reverse sequences. The chromatograph peaks corresponding to the non-complementary nucleotides were re-evaluated and corrected with Chromas 2.6.4.

Species Identification Species were identified by their homology to atpF-atpH or rbcL sequences posted in the GenBank (12) database. To help students handle the bioinformatic workflow, the DNA Subway pipeline (30) created by CyVerse (31) was utilized. DNA Subway provides a collection of web-based bioinformatics tools that allow students to utilize resources hosted on the eXtreme Science and Engineering Discovery Environment (XSEDE) supercomputer cluster (32). The students uploaded their sequences onto the DNA Subway Blue Line (13). On the Blue Line, the sequences were processed through quality control tools, which trimmed ambiguous sequences and paired the sense and antisense strand of the barcode sequences. After quality control, the GenBank database was queried by BLASTn (33). An example output is shown in Figure 5. 73

Figure 5. Example BLASTn output from homology search with an atpH-atpF amplicon sequence. An additional feature of the DNA Subway Blue Line is it provides tools to create dendrograms. Students created alignments of multiple DNA sequences using the MUSCLE computer program (34). From the resulting matrix, the students created maximum likelihood dendrograms and neighbor-joining dendrograms using PHYLIP (35). Results and Discussion Both the rbcL and the atpF-atpH fusion primers (Figure 3) were able to produce amplicons of the correct sizes (15, 24). Unfortunately, the rbcL sequencing data did not meet the class’ needs because there was not enough sequence divergence to identify the plants to the species level (Personal observation and (24)). The results from the BLASTn searches of the atpF-atpH barcodes indicated that there were at least four species of duckweed (Figure 6) growing in the anthropogenic cove. According to range maps produced by US Department of Agriculture (17) and the Flora of North America (36), Lemna minor, Spirodela polyrhiza, and Wolffia columbiana are all native plants to Michigan. In contrast, one student isolated DNA that produced a barcode for L. obscura (Figure 5). The 587 nucleotides sequenced showed 99.8% homology to GenBank sequence GU454235.1 (24). This plant is listed as “absent” from Michigan (17, 36) though native to Ohio. Both natural and anthropogenic mechanisms could explain the migration of L. obscura to Lake Saint Clair. The lake is part of a major migratory flyway (37). Therefore, L. obscura may have been deposited by waterfowl. Alternately, the lake is part of the Great Lakes Waterway (37). Thus, boat traffic may have facilitated movement. When the barcode sequences were arranged into a maximum likelihood dendrogram (Figure 6) or a neighbor-joining dendrogram (not shown), the resulting trees produce monophyletic clades. Members of the same species share terminal nodes. Members of the same genus were found in common clades. The organization of the genera (Lemna, Spirodela, and Wolffia) were consistent with the taxonomy published in the NCBI Lifemap (38), Encyclopedia of Life database (21), the Tree of Life database (39), and Wang et al. (24). These three genera are in the clade Lemnoideae. 74

Figure 6. Maximum likelihood dendrogram from atpF-atpH barcode sequences. The numbers are arbitrary plant identification numbers. The photographs of the plants are inserted. Plants 9, 10, 13, and 18 are top views. Plants 5, 11, 12, and 14 are underside views. Images are not to scale. (see color insert) The dendrograms were rooted by setting a dicot (P. amboinicus) atpF-atpH barcode sequence as the outgroup. Monocots and dicots represent two distinct clades of angiosperms (40). There is a growing collection of evidence indicating that monocots evolved before dicots (40). If the goal of the dendrogram is to perform cladistical analysis, then the outgroup should be basal to all other taxons in the analysis (41). In future student investigations, a basal angiosperm, water lilies (Nymphaeaceae) (42), will be sampled and used as the outgroup. Fortunately, water lilies often grow alongside the studied duckweed community, as shown in Figure 1 (Panel A).

Instructional Perspective and Conclusions The described undergraduate investigation supports STEM curriculum reform. The barcoding activity was part of an inquiry curriculum where students conducted nutrient pollution experiments on wild collected aquatic plants. Students learned a state-of-the-art technology to identify their experimental organism. Species identification is part of the community of practice (4) in ecology. By using DNA barcoding, the students focused on the key concept of information flow, a learning outcome identified in the Vision and Change recommendations (5). The students apply another key concept, organic evolution (5) when they used their sequence data to create dendrograms. One of the revolutions in ecology is the growing importance of big data (i.e., data sets larger than 1 terabyte (7)). Because of the size of the datasets and the complexity of the data, big data analysis is an interdisciplinary process involving statistics and computer science to elucidate biological information. Since specialized skills are needed to perform these analyses, several web-based resources have been developed that allow non-specialists to access and process 75

big data sets. In this investigation, the students accessed several large databases and used algorithms to process their sequence information. Specifically, the supercomputing resources of NCBI were used to perform BLASTn queries (33) of the GenBank database (9) to identify plant species. Additional large databases were used to enrich the students learning experience. The USDA Plants Database (17) was accessed to obtain species range maps, and phylogenetic databases (21, 38, 39) were utilized to help the students interpret their dendrograms. The barcoding exercise can be modified to support many classroom investigations. For example, students can use similar procedures to identify difficult to classify organisms like green filamentous algae or identify small non-distinct plant fragments, like roots found in soil samples. Because of the diversity of material that can be used (10), DNA barcoding can be integrated into many inquiry settings. Unfortunately, there is no single universal sequence for barcoding (10, 15, 16). In this study, the atpF-atpH intergenic spacer locus was used because it could identify members of the Lemnoideae down to the species level (24). However, the number of barcode entries in GenBank for this locus is relatively small as compared to rbcL barcode. As of December 2017, there were 244,837 nucleotide records labeled as rbcL in GenBank while only 3998 nucleotide records labeled as atpF-atpH intergenic spacer. As a result, the rbcL barcode may be better suited in many investigations. Using DNA sequencing in species identification is a strategy that is likely to be utilized for many years to come. The technology behind DNA sequencing is rapidly advancing, especially with next-generation sequencing (NGS). This has led to metagenomics, an investigative approach where whole microbial communities are barcoded (43–45). In the past, NGS was limited to relatively short reads (46). For example, an Illumina MiSeq produced reads of only 350 base pairs. Recently, an inexpensive long-read technology has become available (47). By sequencing longer stretches of DNA, long-read NGS may lead us closer to the goal of having a small set of “universal” barcodes. Our instructional approaches will need to evolve to take advantage of this rapidly changing science.

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17. USDA Natural Resources Conservation Service. The Plants Database Home Page. http://plants.usda.gov/ (accessed December 31, 2017). 18. Cross, J. W. The Charms of Duckweed Home Page. http://www.mobot.org/ jwcross/duckweed/duckweed.htm (accessed December 31, 2017). 19. Ziegler, P.; Adelmann, K.; Zimmer, S.; Schmidt, C.; Appenroth, K. J. Relative in vitro growth rates of duckweeds (Lemnaceae) – the most rapidly growing higher plants. Plant Biol. 2015, 17 (Suppl 1), 33–41. 20. Wang, W. Literature review on duckweed toxicity testing. Environ. Res. 1990, 52, 7–22. 21. Encyclopedia of Life. Lemnoideae Web site. http://eol.org/pages/10553303/ overview (accessed November 18, 2017). 22. Les, D. H.; Landolt, E.; Crawford, D. J. Systematics of the Lemnaceae (duckweeds): inferences from micromolecular and morphological data. Plant Syst. Evol. 1997, 204, 161–177. 23. Rutgers University. Rutgers Duckweed Stock Cooperative Home Page. http://www.ruduckweed.org/ (accessed September 21, 2017). 24. Wang, W.; Wu, Y.; Yan, Y.; Ermakova, M.; Kerstetter, R.; Messing, J. DNA barcoding of the Lemnaceae, a family of aquatic monocots. BMC Plant Biol 2010, 10, 205. https://doi.org/10.1186/1471-2229-10-20. 25. Sambrook, J.; Fritsch, E. F.; Maniatis, T. Molecular Cloning: A Laboratory Manual. 2 ed.; Cold Spring Harbor Laboratory: Cold Spring Harbor, NY, 1989; Vol. 3. 26. Waksman Institute of Microbiology. Protocol of DNA barcode duckweeds by atpF-atpH marker, 2013. Spirodela Database Web site. https:/ /www.waksman.rutgers.edu/spirodela/pages/protocol-dna-barcodeduckweeds-atpf-atph-marker (accessed December 30, 2017). 27. Chromas, version 2.6.4; Technelsium LLC: South Brisbane, Queenland, Australia, 2017. 28. European Molecular Biology Laboratory. Pairwise Sequence Alignment Web site. https://www.ebi.ac.uk/Tools/psa/ (accessed November 12, 2017). 29. Li, W.; Cowley, A.; Uludag, M.; Gur, T.; McWilliam, H.; Squizzato, S.; Park, Y. M.; Buso, N.; Lopez, R. The EMBL-EBI bioinformatics web and programmatic tools framework. Nucleic Acids Res 2015, 43, W580−W584. https://doi.org/10.1093/nar/gkv279 (accessed December 31, 2017). 30. Cold Spring Harbor Laboratory. DNA Subway: Fast Track to Gene Annotation and Genome Analysis Home Page. https://dnasubway.cyverse.org/ (accessed November 11, 2017). 31. Antin, P.; Lyons, E.; Merchant, N.; Micklos, D.; Vaughn, M.; Ware, D. Cyverse Home Page. http://www.cyverse.org/ (accessed November 11, 2017). 32. Extreme Science and Engineering Discovery Environment. XSEDE Home Page. https://www.xsede.org/ (accessed November 11, 2017). 33. Altschul, S. F.; Gish, W.; Miller, W.; Myers, E. W.; Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410. 34. Edgar, R. C. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinf. 2004, 5, 113. https://doi.org/ 10.1186/1471-2105-5-113 (accessed November 30, 2017). 78

35. Felsenstein, J. PHYLIP: Phylogeny Inference Package Home Page. http:// evolution.genetics.washington.edu/phylip/ (accessed November 13, 2017). 36. Landolt, E., Lemnaceae, Flora of North America North of Mexico; Flora of North America Association: New York, 2000; p 200. http://www.efloras.org/ florataxon.aspx?flora_id=1&taxon_id=10488 (accessed December 31, 2017). 37. Hartig, J. H.; Zarull, M. A.; Corkum, L. D.; Green, N.; Ellison, R.; Cook, A.; Green, E.; Norwood, G. Habitat management lessons from the environs of the Detroit River International Wildlife Refuge. J. Great Lakes Res. 2014, 40 (Suppl 2), 31–36. 38. de Vienne, D. M. Lifemap: Exploring the Entire Tree of Life PLOS Biol 2016, 14, e2001624. https://doi.org/10.1371/journal.pbio.2001624 (accessed December 31, 2017). 39. Maddison, D. R.; Schulz, K.-S.; Maddison, W. P. The Tree of Life Web Project. Zootaxa 2007, 1668, 19–40. 40. Soltis, P. S.; Soltis, D. E. Ancient WGD events as drivers of key innovations in angiosperms. Curr. Opin. Plant Biol. 2016, 30 (Suppl. C), 159–165. 41. Hall, B. G. Phylogenetic Trees Made Easy : How-to Manual, 4th ed.; Sinauer Associates: Sunderland, MA, 2011. 42. Angiosperm Phylogeny Group. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG III. Bot. J. Linean. Soc. 2009, 161, 105–121. 43. Schloss, P. D.; Handelsman, J. Metagenomics for studying unculturable microorganisms: Cutting the Gordian knot. Genome Biol. 2005, 6, 229. http://dx.doi.org/10.1186/gb-2005-6-8-229. 44. Thomas, T.; Gilbert, J.; Meyer, F. Metagenomics - A guide from sampling to data analysis. Microb. Inform. Exp. 2012, 2, 1−12. https://doi.org/10.1186/ 2042-5783-2-3 (accessed December 31, 2017). 45. Langille, M. G. I.; Zaneveld, J.; Caporaso, J. G.; McDonald, D.; Knights, D.; Reyes, J. A.; Clemente, J. C.; Burkepile, D. E.; Vega Thurber, R. L.; Knight, R.; Beiko, R. G.; Huttenhower, C. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat. Biotechnol. 2013, 31, 814–821. 46. Quail, M.; Smith, M.; Coupland, P.; Otto, T.; Harris, S.; Connor, T.; Bertoni, A.; Swerdlow, H.; Gu, Y. A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers. BMC Genomics 2012, 13, 341. https://doi.org/10.1186/1471-2164-13-341 (accessed December 31, 2017). 47. Menegon, M.; Cantaloni, C.; Rodriguez-Prieto, A.; Centomo, C.; Abdelfattah, A.; Rossato, M.; Bernardi, M.; Xumerle, L.; Loader, S.; Delledonne, M. On site DNA barcoding by nanopore sequencing. PLoS ONE 2017, 12, e0184741. https://doi.org/10.1371/journal.pone.0184741.

79

Chapter 6

Synthesis of a Novel Series of Nitrogen-Containing Ligands for Use as Water Remediators, All Incorporating Long-Chain Aliphatic Moieties Justin Pothoof, Michele Bhagwagar, Grace Nguyen, Sara Tinawi, Sara Makki, and Mark A. Benvenuto* Department of Chemistry & Biochemistry, University of Detroit Mercy, 4001 W. McNichols Rd., Detroit, Michigan 48221-3038, United States *E-mail: [email protected].

A series of symmetrical, highly multi-dentate podand ligands, all incorporating terminal, long-chain aliphatic moieties and a centrally-positioned series of nitrogen atoms, have been synthesized and characterized. These ligands were produced in a continuing effort to find effective, useful, inexpensive water remediators that are able to function as chelates and remove metal ions indiscriminantly from aqueous solutions. The ligands were complexed with a variety of metal ions, to determine the solubility of the resulting complexes in water. They were also examined to determine if they could retain metal cations in non-aqueous solvent.

Introduction Throughout the history of civilization, humankind has almost always lived near water. Even desert dwellers knew exactly where water was to be found, precisely because the presence of water meant life. Yet for as long, brackish water, saline water, and water that has in any other way been contaminated with some foreign matter has been of concern to people, precisely because it is either difficult or impossible to use (1–12). Saline water is certainly still useful for fishing and for waterborne traffic, but is routinely far too salty to drink.

© 2018 American Chemical Society

What can be called this degradation of water has become a more acute problem in the last 75 years than it has for almost all of the recorded history prior to that time, because of the explosion in human population worldwide (13–16). For example, the loss of the Aral Sea is one of the largest man-made catastrophes dealing with a freshwater source that has ever been recorded (17, 18). The pollution of the Gulf of Mexico near the mouth of the Mississippi River with agricultural waste and farm run-off is another large-scale degradation of a significant part of the world’s water that has become a major regional concern (4, 19). And the recently enhanced salinity of the aptly named Dead Sea, as its waters are used by companies in Israel and Jordan for mineral extraction, is a further issue of concern for peoples of the region who have used the sea for centuries (20). In these three cases and several more, the presence of larger numbers of people near water sources, and depending on water, stresses those water sources more than at any previous time in history. Clearly, the need for materials to clean polluted or degraded water is important. Numerous different chealting molecules have been used in some way to extract unwanted ions or organic matter from water, with ethylene diamine tetraacetic acid (EDTA) being arguably the widest known chemical used for this purpose, at least on a small scale (21–26). But the existence of a class of chelators does not prevent further, similar molecules from being produced and examined in the hope that they too may function as inexpensive, efficient remediators of environmentally degraded waters. This paper is the result of a research project utilizing undergraduate researchers, in which a novel series of ligands have been produced, under ambient temperature and pressure conditions, resulting in organic molecules having three or five nitrogen atoms in their central portion. These nitrogen atoms act to form a dative bond non-specifically with a variety of metal ions, forming coordination complexes. They function much as molecules such as EDTA and other established chelators, and should prove useful in remediating water containing a wide variety of cations.

Results and Discussion Synthesis and Characterization of Ligands The amines diethylene triamine (N3) and tetraethylene pentaamine (N5), as well as the two aldehydes: octanal and dodecanal, were all purchased from Aldrich and used as received. A single 1H NMR was run of each starting material to ensure purity of the material. Solvents, monoglyme and toluene, were purchased commercially and used without further purification. To synthesize the target ligands, two molar equivalents of an aldehyde were reacted with one molar equivalent of an amine at room temperature (25°C), with either monoglyme or toluene as a solvent, with mechanical stirring, for approximately 16 hours. Starting solutions were uniformaly clear, with the resulting solutions after stirring being very slightly yellow. Figure 1 shows the basic reaction chemistry for the production of the target ligands. 82

Figure 1. General route for ligand synthesis. The reaction schmeme illustrated in Figure 1 was used to produce Ligands 1 and 2, and represents a wider scheme that can be used to produce numerous other long-chain ligands. Figure 2 shows both ligands that were produced in this study, and Table 1 indicates the sample sizes and molar ratios of materials used in the syntheses.

Figure 2. Shortest (Ligand 1) and longest ligand (Ligand 2). The ligands were examined by 1H NMR, and as expected, displayed a very cluttered, crowded aliphatic region. The reaction though, a Schiff’s base condensation, produces molecules that in these cases contain two imine sites. These double bonds are the only functionality the target ligands have besides the nitrogen atoms, and importantly, the imine proton appears as a singlet in the region δ 8.2 – 8.8. This is definitely different from the aldehydic proton of the starting material, which appears slightly above δ 11.0. It is also several ppm away from the -CH2- saturated methylene signals from those protons two bonds away from each nitrogen atom. In short, the imine singlet of each target ligand serves as a diagnostic that the ligand has been produced. The presence of the imine singlet, and the complete loss of the aldehyde singlet, were used as indicators that the ligands formed quantitatively. Evaluation of Ligand Complexing Abilities In a traditional manner, for each trial, a solution of Ligand 1 or 2 was added to a separatory funnel, then an aqueous solution of a metal salt was added (results are summarized in Table 2). Precipitation of material essentially occurred upon contact, with only a few seconds of shaking of the separatory funnel. Simply adding a sample of a dry salt to the non-aqueous solution of either Ligand 1 or 2 produced some unexpected results. This experimental approach was chosen because it was felt that it would be straightforward to separate any precipitate, dry it, and determine the overall conversion to the target coordination complex. But it can be seen in Table 2 that four of the five metal salts added directly to the non-aqueous ligand solution of Ligand 2 stayed in solution. While such 83

behavior is not unheard of, it is not common. Reported examples of organic ligands that solvate ionic materials in non-aqueous solutions always involve more complex ligands than those produced here (27–29). It appears then that in the case of Ligand 2 – a molecule that can be termed α,ω-bis-dodecyl-tetraethylene-pentaamine – a very simply chelator has been found that will hold hundredth molar concentrations of several cations in non-aquoeous solution.

Experimental Section Diethylene triamine and tetraethyelene pentaamine were purchased from Aldrich and used with no further purification, as were octanal and dodecanal. Solvents were purchased and used without distillation. The formation of all ligands was performed in monoglyme, and in toluene, with the amine first measured out and dissolved in the solvent. The aldehyde was added only after the amine was completely solvated. All solutions were stirred for a minimum of 16 hours, during which time minimal color changes occurred from clear to a very pale yellow. Samples of each ligand were dried by rotary evaporation, followed by a minimum of 16 hours on a Schlenk line, and solvated in CDCl3 for characterization via NMR. Both ligands were examined by 1H NMR using a Jeol 300 MHz instrument, at 25°C. Table 1 lists the amounts of amine and aldehyde used in production of Ligands 1 and 2.

Table 1. Ligand Synthetic Data Amine

Amine mass, g (mole)

Aldehyde, g (mole)

Molar mass of amine (g/mol)

Product – Ligand Number

Diethylenetriamine (N3)

1.104 (0.011)

2.533 (0.021), octanal

103.0

1

Tetraethylenepentaamine (N5)

2.031 (0.011)

3.962 (0.022), dodecanal

184.32

2

Two different techniques were used to form metal-ligand coordination complexes. The first technique involves dissolving in distilled water a stoichiometric equivance of a metal salt to the ligand solution, then adding this to a separatory funnel containing the stoichiometric equivalence of the ligand in non-aqueous solvent. In all such trials, a precipitate formed immediately. The second technique involved measuring out the proper amount of a dry metal salt, routinely a molar equivalence to the ligand solution in non-aqueous solvent. The dry salt was then added to the ligand solution directly. In several cases, the coordination complex that formed remained in solution. Results are summarized in Table 2. 84

For both techniques, 0.044 M solutions of Ligand 1 were used, and 0.033 M solutions of Ligand 2 were used. This allowed for an easy-to-measure, highly reproducible set of starting samples and experimental size.

Table 2. Metal – Ligand Complex Formation Ligand

Ligand mass, g (mole x10-3)

Salt mass, g (mole x 10-3)

Visible Result, technique 1

Visible Result, technique 2

1

0.118 (1.144)

0.198 (0.726) Fe(ClO4)2·H2O

Brown precipitate

Dark precipitate

1

0.118 (1.144)

0.279 (1.02) ZnClO4·6H2O

Grey precipitate

Grey precipitate

1

0.118 (1.144)

0.283 (0.870) Pb(C2H3O2)2

Grey precipitate

Grey precipitate

1

0.118 (1.144)

0.187 (0.511) Blue-brown Co(ClO4)2·6H2O precipitate

Brown precipitate

1

0.118 (1.144)

0.058 (0.142) Grey precipitate Nd(NO3)3·6H2O

Grey precipitate

2

0.103 (0.198)

0.0504 (0.198) Fe(ClO4)2·H2O

Brown precipitate

Dark brown solution

2

0.103 (0.198)

0.073 (0.198) ZnClO4·6H2O

Grey precipitate

Yellowish solution

2

0.103 (0.198)

0.072 (0.198) Brown precipitate Co(ClO4)2·6H2O

2

0.103 (0.198)

0.075 (0.198) Pb(C2H3O2)2

2

0.103 (0.198)

0.088 (0.198) Whitish Nd(NO3)3·6H2O precipitate

Grey precipitate

Brown solution Whitish-grey precipitate White solution

Conclusions This duo of multi-dentate ligands is both very easy and straightforward to synthesize, requiring no specialized reaction apparatus. Because of a single, diagnostic imine peak in an otherwise cluttered 1H NMR, the ligands can be characterized without ambiguity, and without having to resolve the aliphatic region of the 1H NMR spectrum. The ligands produced here all have minimal functionality, yet possess enough that they have proven to be excellent chelators. Their syntheses have been accomplished by multiple undergraduate researchers. The formation of metal-ligand complexes that precipitate readily from water indicate that these ligands may find use as an inexpensive form of water remediator. The fact that one of these ligands is capable of solvating metal salts into non-aqueous media when dry metal salts were added directly to non-aqueous solutions of the ligands was unexpected. It is an intriguing phenomenon however, 85

one that may hold promise for the use of these ligands in previously unexpected applications.

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Chapter 7

Analysis of Cosmetic Mineral Eyeshadows and Foundations with a Handheld X-ray Fluorescence Analyzer Tiffany Tieu Ngo, Sara Thomas, Diamond Stokes, Mark A. Benvenuto, and Elizabeth S. Roberts-Kirchhoff* Department of Chemistry and Biochemistry, University of Detroit Mercy, 4001 W. McNichols Rd., Detroit, Michigan 48221, United States *E-mail: [email protected].

Twenty-five consumer cosmetic mineral makeups purchased from local stores and three soil standard reference materials (SRMs) obtained from the National Institute of Standards and Technology (NIST) were analyzed using a handheld X-Ray fluorescence (XRF) analyzer. The soil standards were used to access the accuracy of the XRF analyzer. The XRF analysis allowed for efficient analysis of the elemental composition of several samples in a short amount of time. The results from the analysis with the handheld XRF were within 15% or less of the reported values for all three of the SRMs for aluminum, potassium, iron, zinc, and strontium; and for two of the SRMs for titanium, manganese, copper, rubidium, and lead. Common elements in all makeup samples included potassium, aluminum, iron, titanium, and rubidium. Lead was not detected in any of the samples. In conclusion, XRF provides a fast, efficient, and accurate method for elemental analysis of cosmetics.

© 2018 American Chemical Society

Introduction The first use of cosmetics dates to the ancient Egyptians in 4000 BC (1). According to the Federal Food, Drug, and Cosmetic Act, cosmetics are defined as “articles intended to be rubbed, poured, sprinkled, or sprayed on, introduced into, or otherwise applied to the human body or any part thereof for cleansing, beautifying, promoting attractiveness, or altering the appearance” (2). Cosmetic products are used by many people of different races and ages, and new products are continually introduced into the market. For this reason, ongoing studies on the composition and effects of cosmetics are of importance. Mineral foundations, specifically, have become increasingly popular and offer an alternative to traditional powder foundations. These mineral foundations are assumed to be natural-based cosmetics, formulated using natural, finely ground minerals. However, there is little and confusing information on what formulates a “true” mineral foundation since manufacturers have different ideas (3). Although the skin is a barrier and thus beneficial for preventing exposure to harmful substances, there are some trace elements or ingredients in cosmetics that can penetrate the skin and produce systemic exposure (4–6). These trace elements could include heavy metals such as lead. Long term exposure to lead has been known to be toxic to children and pregnant women (7). Contact dermatitis can result from exposure to metals such as nickel through cosmetics or jewelry (5, 6). In cosmetics, the FDA has established limits of less than 20 ppm for lead, less than 3 ppm for arsenic and less than 1 ppm for mercury in ingredients and colors, and less than 65 ppm mercury in cosmetics intended for use only in the area of the eye (2). Because of the harmful effects of certain trace elements and popularity of using cosmetics, the contents of cosmetics should be investigated on a regular basis. Studies have been reported that used methods such as XRay fluorescence (XRF), ICP-MS, and instrumental neutron activation to perform elemental analysis of cosmetics (8–11). Neutron activation and X-Ray methods are advantageous since they are nondestructive and do not require the sample to be in solution. In addition, McIntosh, et al. recently reported that the results from two XRF analyzers using the soil fundamental parameter method reliably detected many elements and gave semi-quantitative estimates of the elements present at higher levels in spices, herbal medicines and cosmetics as compared to Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) (11). XRF is a powerful, non-destructive technique with a wide range of applications including geological, chemical, environmental, industrial, forensic, biological, and others (12–18). XRF has been used to study a variety of substances including consumer products, food products, and dietary supplements (19–35). XRF offers analysis on multiple elements, low cost, little to no sample preparation, and high throughput. In X-ray spectroscopy, primary gamma rays or X-rays expose a sample to radiation. This radiation ejects electrons from an atom’s first (K) and second (L) inner shells. Electrons from higher shells fill the vacancy to stabilize the atom. When the electrons fill the vacancy, a characteristic fluorescence is emitted. The L to K transition is designated Kα, the M to K transition is named Kβ, and the M to L transition is designated Lα. In each case, a characteristic photon is released. The Kα and Kβ photons correlate to the Kα and 90

Kβ lines seen on the spectrum. (36–38). In this study, three standard reference materials and twenty-five makeup samples were analyzed with a Bruker S1 Titan handheld XRF analyzer to compare their elemental compositions.

Experimental Methods Standard reference materials (SRMs) were obtained from the National Institute of Standards and Technology (NIST). SRM 2586 is the Trace Elements in Soil standard containing lead from paint (Nominal 500 mg lead/kg). This soil standard has reported certified mass fractions for arsenic, cadmium, chromium, and lead. It also has reported reference mass fractions for other elements including aluminum, copper, iron, manganese, potassium, titanium, strontium, and zinc (39). SRM 2709a, a San Joaquin Soil standard, has certified mass fractions reported for several elements including iron, aluminum, potassium, manganese, and strontium, and has reported reference mass fractions for many elements including zinc and rubidium (40). SRM 2711a is a Montana II Soil standard. It has reported certified mass fractions for many elements including aluminum, potassium, titanium, iron, strontium, lead, copper and zinc (41). It also has reported reference mass fractions for other elements including rubidium. A Bruker S1 TITAN 600-800 handheld XRF analyzer was used to analyze the samples and SRMs. For each SRM, five separate samples (3.0 g per sample) were analyzed five times each for 120 s. The instrument was mounted on the TITAN bench-top stand. Each sample was placed on the safety platform to ensure the samples were analyzed from an equal distance. Before each analysis, each sample cup was removed from the safety platform and rotated. The instrument used a voltage of 45 kV and a current of 10 µA, with an Al/Ti filter. A Dell laptop computer with Bruker S1sync software was used to control the instrument, and data were collected and analyzed with the soil calibration fundamental parameters (FP) method. The soil calibration method provided a basic set of excitation conditions that could target most of the elements of interest. This calibration has been optimized for a SiO2 matrix. The reported elements with this method include Mg, Al, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Y, Zr, Nb, Mo, Rh, Pd, Ag, Cd, Sn, Sb, Ba, La, Ce, Hf, Ta, W, Pt, Au, Hg, Tl, Pb, Bi, Th, and U (42). Characteristic peaks for each element were identified using S1PXRF software from Bruker. The SRMs, used as provided, were placed into Chemplex Spectrocertified® Quality XRF sample cups (31.0 mm × 22.4 mm) and were covered with Chemplex Spectromembrane® perforated thin film mylar polyester sample support carrier films (3.6 µm) with a sealing ring. For each of the standards, the concentrations (averages and standard deviations) of various elements were determined and compared to the NIST standard values. The Limit of Detection (LOD) and Limit of Quantitation (LOQ) for each the analyzed elements using the soil calibration method were provided by Bruker (42). Those reported in this study are shown in Table 1. Twenty-five mineral eyeshadow and foundations were analyzed with a Bruker S1 TITAN 600-800 handheld XRF instrument as described for the SRMs. Each of the eyeshadow samples were measured out to one sample (6.0 g per sample) and analyzed five times for 120 91

s. Each of the foundation samples were measured out to five samples (7.0 g per sample) and analyzed for five times each for 120 s. Results are reported in ppm as average concentration ± standard deviation.

Table 1. Detection limits for selected elements with the S1 TITAN handheld XRF analyzer using the soil calibration method (42) K

Ti

Mn

Fe

Cu

Zn

Rb

Sr

Pb

LODa 960 (ppm)

41

20

18

13

5

3

3

4

11

LOQb 4800 (ppm)

205

100

90

65

25

15

15

20

55

Al

a

LOD, Limit of Detection.

b

LOQ, Limit of Quantitation.

Results and Discussion All NIST standards and cosmetic samples were analyzed with the soil calibration method with the handheld XRF analyzer. Since it is difficult to calibrate the XRF analyzer for a variety of cosmetic matrices, the soil calibration mode and its employment of Compton Normalization helps to correct for some matrix effects. SRM 2586 is the Trace Elements in Soil standard containing lead from paint (Nominal 500 mg lead/kg). SRM 2709a is the San Joaquin Soil Standard, and SRM 2711a is the Montana II Soil standard. The concentrations of each element are expressed in ppm (averages ± standard deviation), and the percent relative standard deviations (%RSD) are also given. The averages of each XRF analysis were compared to the reference or certified values for SRMs 2586, 2709a, and 2711a and expressed as percent error. Results from elements of interest where all three standards had reported certified or reference values above the LOQ for the instrument and the XRF results showed less than 15% error are shown in Table 2. The concentrations obtained by XRF analysis are compared to the reported values of the NIST standards for strontium, zinc, iron, aluminum, and potassium. The percent error for strontium was less than 2% for all standards, while for iron, aluminum, and potassium, the percent error was less than or equal to 10.0%. For zinc, the percent error was between 11.5 and 13.7%. The values of the %RSDs for almost all the elements are less than 10% and for most are less than 5% showing that there is not a large spread of data points around the mean. Shown in Table 3 are elements of interest where at least two of the soil standards reported certified or reference values above the LOQ of the instrument and the XRF results showed less than 15% error. The concentrations obtained by XRF analysis are compared to the reported values of the NIST standards for lead, manganese, titanium, copper, and rubidium. The percent error for lead was less than 7% with SRMs 2586 and 2711a. The concentration was not reported for SRM 2709a since the reported value was below the LOQ for the instrument of 55 ppm Pb. For manganese, the percent error was 10% or less with two of the standards and at 15.8 % with 2711a. For titanium, the percent error was 10% or 92

less with two of the standards and at 17.0 % with 2709a. For copper, the percent error ranged from 5-13% for the standards that had copper levels well above the LOQ of 25 ppm for the instrument. With SRM 2709a, the error was 26%, but the value of 33.9 ppm is very close to the instrument’s reported LOQ of 25 ppm which is determined with single element calibration standards. The percent errors for rubidium were determined to be 6.8 and 10.2 %. Twenty-five consumer cosmetic mineral makeups were purchased from various stores. All were analyzed with the soil calibration method with the XRF analyzer. The method was selected because of the similarities between the two matrixes (soil and powdered makeup) and it reports results from 44 elements. Each mineral makeup was assigned a sample identification designation (Table 4). Makeup samples varied between color and shine. For example, the eyeshadow M41 was lime green and M3 was an ocean blue. All foundations differed in the shade of brown. The results for the strontium and rubidium concentrations in the makeup samples are shown in Figure 1. Two foundation makeups, M4 and M50, had the highest strontium concentrations, while M28, M35, and M40 contain between 40 and 100 ppm of strontium. Results for rubidium are also shown in Figure 1, and all the samples had some measurable concentrations of this element. Samples M43 and M50 showed the highest amounts. Rubidium does occur naturally in several potassium ores/salts as well as some alumino-silicate ores/salts (43), and thus, may be contained in these samples due to the presence of potassium and/or aluminum. None of the samples showed concentrations of lead above the LOD. The results for the zinc concentration in the samples are shown in Figure 2. The two samples with the highest concentrations of zinc are the foundation samples M4 and M50. Zinc oxide and titanium oxide are used as protection from UV light in some cosmetics (44). These two foundations which supply UV protection apparently use zinc oxide for the advertised sun protection factor (SPF) since they show high zinc concentrations and as shown later, lower titanium concentrations. Results for aluminum, potassium, and iron are shown in Figure 3. All samples showed the presence of aluminum and potassium. There was a greater difference in the amount of iron in the samples with M6, M20 and M49 showing the highest concentrations. The results for the titanium analysis are shown in Figure 4. Many of the samples contained titanium which is not unexpected since titanium dioxide is used in various personal care products including sunscreens and loose face powders for protection from UV light and as a whitening agent (44). This makes sense since three of the samples with the highest values, M47, M48, and M49, are foundations with lighter shades of brown or tan. The results for manganese are shown in Figure 5. Samples M5 and M9 had high levels of manganese. These are both eyeshadows with a purple color and manganese violet is often used as a purple color in cosmetics (45). One cosmetic sample M17, a green eyeshadow, showed a high concentration of copper at 92,600 ppm. Two other samples, M5 and M43, had 93 and 161 ppm of copper, respectively. Several others M6, M7, M8, M16, M17, M20, M28, M35, M39-42 and M44-46, had measurable levels of copper under 50 ppm. 93

Table 2. Concentrations of strontium, zinc, iron, aluminum, and potassium from analysis with the handheld XRF compared to the NIST reported values for the SRMs where the analysis of three soil standards reported less than 15% errora Sr (ppm)

94

2586 XRFc

83 ± 2 (2.3)d

2586 SRM

84 ± 8 (9.5)

2709a XRF

243 ± 4 (1.5)

2709a SRM

239 ± 6 (2.5)

2711a XRF

245 ± 4 (1.8)

2711a SRM

242 ± 10 (4.1)

% Errorb

1.2

1.7

1.4

Zn (ppm) 311 ± 8 (2.7) 352 ± 16 (4.5) 88 ± 2 (6.2) 103 ± 4 (3.9) 358 ± 8 (2.2) 414 ± 11 (2.7)

% Error

11.5

13.7

13.6

Fe (ppm) 46410 ± 280 (0.6) 51610 ± 890 (1.7) 31676 ± 281 (0.9) 33600 ± 700 (2.1) 24083 ± 295 (1.2) 28200 ± 400 (1.4)

% Error

10.0

5.7

1.3

Al (ppm) 71648 ± 1557 (2.2) 66520 ± 760 (1.1) 71379 ± 16000 (22) 73700 ± 16000 (22) 75168 ± 2268 (3.0) 67200 ± 1000 (1.5)

% Error

7.7

3.1

1.3

K (ppm) 10627 ± 154 (1.5) 9760 ± 180 (1.8) 20607 ± 810 (6.6) 21100 ± 600 (2.8) 24971 ± 668 (2.7) 25300 ± 1000 (4.0)

% Error

8.8

2.3

1.3

a SRM values are certified or reference values as reported in Experimental Methods. b Percent error between measured XRF value and NIST reported value. c Values (average ± standard deviation) for XRF analysis with handheld instrument. d Percent relative standard deviation.

Table 3. Concentrations of lead, manganese, titanium, copper, and rubidium from analysis with the handheld XRF compared to the NIST reported values for the SRMs where the analysis of two soil standards reported less than 15% errora Pb (ppm)

% Errorb

Mn (ppm)

95

2586 XRFc

450 ± 9 (2.1)d

2586 SRM

432 ± 17 (3.9)

2709a XRF

Below LOQe

484 ± 20 (4.2)

2709a SRM

17.3 ± 0.1 (1.0)

529 ± 18 (3.4)

2711a XRF

1492 ± 28 (1.9)

568 ± 38 (6.7)

2711a SRM

1400 ± 10 (0.4)

4.1

6.5

901 ± 18 (1.7) 17070 ± 840 (4.9)

675 ± 18 (2.7)

% Error

9.8

8.4

15.8

Ti (ppm)

% Error

6763 ± 117 (1.7)

10.0

6050 ± 660 (11) 3930 ± 220 (5.6)

17.0

3360 ± 70 (2.1) 3161 ± 61 (1.9)

0.3

3170 ± 80 (2.5)

a SRM values are certified or reference values as reported in Experimental Methods

Values (average ± standard deviation) for XRF analysis with handheld instrument. 55 ppm. f Near LOQ of 25 ppm for Cu. g N.D., not detected.

Cu (ppm) 77 ± 2 (2.6) 81 (0) 43 ± 3 (7.0)f 33.9 ±0.5 (1.5) 122 ± 4 (3.0) 140 ± 2 (1.4)

% Error

Rb (ppm)

% Error

N.D.g 5.0 N.D. 89 ± 2 (2.1)

27

99 ± 3 (3.0) 112 ± 2 (1.5)

12.9

120 ± 3 (2.5)

10.2

6.8

b Percent error between measured XRF value and NIST reported value. d

Percent relative standard deviation.

e

c

LOQ, level of quantitation of

Table 4. Consumer mineral makeup analyzed by XRF Designation

Makeup Identifier

Type

M2

Danzig

Eye Shadow

M3

Paranoid

Eye Shadow

M4

Tan

Foundation

M5

Water Lily

Eye Shadow

M6

Sex Kitten

Eye Shadow

M7

Wild Flower

Eye Shadow

M8

Soiree

Eye Shadow

M9

Berry Flambe

Eye Shadow

M16

Pink

Eye Shadow

M17

Green

Eye Shadow

M20

Red

Eye Shadow

M28

Gray

Eye Shadow

M 35

Beige

Eye Shadow

M39

Raw Power

Eye Shadow

M40

Black No.1

Eye Shadow

M41

Electric Warrior

Eye Shadow

M42

Synergy

Eye Shadow

M43

Liberty

Eye Shadow

M44

True Gold

Eye Shadow

M45

Bare Skin

Eye Shadow

M46

Queen Tiffany

Eye Shadow

M47

Fairly Medium

Foundation

M48

Golden Tan

Foundation

M49

Medium Deep

Foundation

M50

Deep

Foundation

96

Figure 1. Concentration of strontium and rubidium in the makeup samples as determined by XRF analysis.

Figure 2. Concentration of zinc in the makeup samples as determined by XRF analysis.

97

Figure 3. Concentrations of aluminum, potassium and iron in the makeup samples as determined by XRF analysis.

98

Figure 4. Concentration of titanium in the makeup samples as determined by XRF analysis.

Figure 5. Concentration of manganese in the makeup samples as determined by XRF analysis.

99

Conclusions A soil calibration method with a handheld XRF was used to analyze three soil standard reference materials and twenty-five consumer mineral makeup samples. The results from the soil method can be used to quickly compare the elemental composition of the different makeup samples Comparing the reported results with the certified and reference values of the standard reference materials was used to verify that an element was present and the XRF’s precision and accuracy. There were five elements identified in some or all the makeup samples which were strontium, zinc, iron, aluminum, and potassium. These elements were verified with all three soil standard reference materials. In contrast, there were five other elements that were verified with two soil standard reference materials. These five elements were lead, manganese, titanium, copper, and rubidium. Of these five, all but lead were found in some or all the samples. None of the cosmetic samples analyzed contained levels above the FDA allowable levels of toxic metals (Pb, As, or Hg) (2). The XRF method is a quick way to analyze several samples. An instrument-supplied calibration method such as the soil calibration allows quick analysis of multiple elements to compare between samples. If more labor, time, and cost-intensive investigations are to be performed, this method provides an efficient way to quickly and accurately screen candidates before further analysis.

Acknowledgments Work reported in this publication was supported by the National Institutes of Health Common Fund and Office of Scientific Workforce Diversity under three linked awards RL5GM1189XX, TL4GM1189XX, 1UL1GM1189XX administered by the National Institute of General Medical Sciences, the University of Detroit Mercy’s McNichols Faculty Assembly Internal Research Fund, and the College of Engineering & Science at the University of Detroit Mercy.

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33. Chan, J. C.; Palmer, P. T. Determination of Calcium in Powdered Milk via X-ray Fluorescence Using External Standard and Standard Addition Based Methods. J. Chem. Educ. 2013, 90 (9), 1218–1221. 34. Barakat, A.; Maurice, S.; Roberts, C.; Benvenuto, M. A.; Roberts-Kirchhoff, E. S. Analysis of Salts and Salt Substitutes with a Handheld X-Ray Fluorescence Analyzer. In Trace Materials in Air, Soil, and Water; Evans, K. R.; Benvenuto, M. A.; Lanigan, K. C.; Rihana, A.; Roberts-Kirchhoff, E. S., Eds.; ACS Symposium Series 1210; American Chemical Society: Washington, DC, 2015, pp 101−114. 35. Shroeder, A. E., Smith, Z. R., Benvenuto, M. A., Roberts-Kirchhoff, E. S. Analysis of Dietary Supplements with a Handheld XRF Analyzer. In Food, Energy, and Water: The Chemistry Connection; Ahuja, S., Ed.; Elsevier, Inc: Amsterdam, Netherlands, 2015; pp 383−390. 36. XRF Research. X-ray Fluorescence. https://www.xrfresearch.com/ technology/x-ray-fluorescence (accessed April 2015). 37. Geochemical Instrumentation and Analysis. X-ray Fluorescence Instrumentation. http://serc.carleton.edu/research_education/ geochemsheets/techniques/XRF.html (accessed April 2017). 38. X-Ray Fluorescence: Qualitative and Quantitative Analysis. http:// oxford-labs.com/x-ray-fluorescence/qualitative-and-quantitative-analysis/ (accessed July 2017). 39. Wise, S. A.; Watters, R. L. Certificate of Analysis SRM® 2586 Trace Elements in Soil Containing Lead from Paint (Nominal 3000 mg/kg Lead); National Institute of Standards & Technology: Gaithersburg, MD, 2008. 40. Wise, S. A.; Watters, R. L. Certificate of Analysis SRM® 2709a San Joaquin Soil; National Institute of Standards & Technology: Gaithersburg, MD, 2009. 41. Wise, S. A.; Watters, R. L. Certificate of Analysis SRM® 2711a Montana II Soil; National Institute of Standards & Technology: Gaithersburg, MD, 2009. 42. S1 TITAN 600-800 Soil Calibration; Bruker Elemental: Kennewick, WA, February 2014. 43. Benvenuto, M. A. Industrial Chemistry; DeGruyter: Berlin, 2014. 44. Lewicka, Z. A.; Benedetto, A. F.; Benoit, D. N.; William, W. Y.; Fortner, J. D.; Colvin, V. L. The structure, composition, and dimensions of TiO2 and ZnO nanomaterials in commercial sunscreens. J. Nanopart. Res. 2011, 13 (9), 3607–3617. 45. Code of Federal Regulations Title 21. Manganese Violet. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/ CFRSearch.cfm?fr=73.2775 (accessed December 2017).

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Chapter 8

Arctic Communities as Sites of Local Field Work in Environmental Chemistry Mark H. Hermanson*,1 and Sydney Le Cras2 1Hermanson

& Associates, LLC, 2000 53rd St. W., Minneapolis, Minnesota 55419, United States 2Department of Natural Resources Management & Environmental Sciences, California State Polytechnic University, 180 North Poly View Drive, San Luis Obispo, California 93407, United States *E-mail:[email protected].

The Arctic is remote from major population centers and industrial or agricultural activities and is often assumed to be “pristine”. Considering that it is cold, dry and seasonally dark, the usual environmental processes affecting distribution or accumulation of contaminants is clearly different. However, since the late 1980s, various investigators have found that contamination levels of industrial and agricultural chemicals are sometimes very high in the Arctic. In some cases, the contaminants have traveled to the Arctic through the atmosphere as gasses or associated with particles in a process known as long-range atmospheric transport, or LRAT. These contaminants may be deposited on glaciers or ocean surfaces and in the case of the latter, will enter the food chain, including humans who rely on wild sources of food from the marine environment. In other cases, contaminants may arrive in the Arctic through imported construction or other materials. In the case of energy production, the emissions are the same as in any populated place. Here we discuss the early history of contamination in the Arctic and the more recent sampling, analysis and results of different environmental chemistry campaigns in the Arctic. Resident university students have been involved in sampling and data gathering for the analysis of atmospheric mercury released from coal combustion, and the apparent emissions of various flame retardants into the atmosphere from local © 2018 American Chemical Society

building materials or LRAT. The site is in Longyearbyen, on Svalbard, which was organized as a coal-mining town in 1906, and continues to operate today as a tourist site with a small university offering courses relevant to the Arctic. Electricity has been generated in Longyeaarbyen by coal combustion for about 100 years, and the effect during sampling in 2016 showed a daily atmospheric mercury cycle, with an average concentration similar to “European polluted air”, and average air in Detroit, USA. Our investigation of flame retardants showed that the organophosphorus flame retardants (OPFRs), considered to be replacements for now-banned brominated flame retardants (BFRs), have a concentration similar to non-urban areas in the U. S. Great Lakes region. The average content of the OPFRs was at least one order of magnitude greater than the BFRs. Using an Arctic community for investigations of environmental chemistry leaves students with a strong background about the impacts of urban and industrial pollution on the Arctic environment, demonstrating that the Arctic is part of the global contaminant distribution system, and is not “pristine”.

Introduction: Why Environmental Chemistry in the Arctic? The study of environmental chemistry involves the reactions, movements or accumulations of chemicals in various environmental compartments. Rarely do investigators know in advance what they are looking for because chemicals observed are seen only by using analytical instruments. The analyte list is often developed from policy agreements about chemicals in the environment, such as the Stockholm Convention (www.pops.int). And the result is often identification of pollutant chemicals with unknown sources except at sites of well-known contamination. The typical image of the Arctic is of bright white, clean snow, clear, uncontaminated skies, very few people, and no trace of any known contamination. Why is there a need to investigate environmental chemistry in a pristine environment? Especially considering that it is too cold, too dry, and in the winter, too dark to support many common chemical reactions or movements. The concept of the Arctic as a pristine place, cut off from the rest of the world, and particularly from the contaminating effects of human activity because of its remote (and usually unknown) location, has persisted for decades. Some opinions about this began to change as early as the 1950s when spring-time weather flights in Alaska (the Ptarmigan flights) observed what was characterized as the Arctic haze, an optical effect of high-altitude “smoke” observed from aircraft. The origin of the “smoke” was unknown, and the reason for its appearance only at high altitude was also unknown (1). One assumption was that the material in the “haze” may have originated with forest fires, not considering that urban or industrial particles could move to the Arctic. That view began to change when Murozumi et al. (2) measured a 200-times greater Pb concentration in surface ice and snow over pre-industrial background levels from an ice core collected near Camp Century, a remote glacier106

covered site in Greenland. The increase in glacial Pb concentrations was attributed to growth of Pb smelting before World War II and use of tetra-ethyl Pb in motor fuel, which began in 1924, and had rapid growth after World War II. A transport mechanism of atmospheric dust, contaminated with industrial and urban Pb from urban/industrial areas to Greenland, was proposed. Even though the Pb results from Murozumi et al. (2) were generally well received, the magnitude of movement and accumulation of contaminants to the Arctic was not appreciated for nearly 20 years. The observations of Arctic Haze and Pb in Greenland ice led to emphasis on effects of long-range atmospheric transport (LRAT) to the Arctic from urban/industrial and agricultural areas. This approach has dominated investigations of environmental chemistry in the Arctic for decades. Studies have shown accumulated polychlorinated biphenyls (PCBs), pesticides, and brominated flame retardants (BFRs) in glaciers where these compounds were obviously never manufactured or used. The attraction for LRAT studies arises from the low human populations in the Arctic and the general lack of industrial or agricultural activity meaning that the contaminants must travel long-distances through the atmosphere. And long travel means that the contaminants must be persistent and undergo transformation from gas to condensed phases under the influence of cold Arctic air temperatures. Persistence is often associated with the reaction rate of a substance with hydroxyl radicals (OH.) produced by photolytic reactions and which are considered to be the most important atmospheric substance to oxidize many different contaminant gases. But it is also known that contaminants can travel to the Arctic associated with particles and in that form are less likely to be oxidized by OH., intensifying their persistence. The earliest observation of direct human effect by contaminants in the Arctic appeared in 1989 when Dewailly et al. (3) published the results of a survey of organic industrial contaminants in breast milk in an Inuit community in northern Quebec. The intent of the study was to use the Inuit community as a “background” amount for comparison to samples from Quebec City which were assumed to show the effects of typical urban/industrial living. It turned out that the Inuit concentrations were several times higher than the Quebec City samples, and after confirmation with further samples, it was discovered that the difference was attributable to the Inuit diet which was largely comprised of community-harvested sea food, particularly seal and fish. This should have been no surprise because it was earlier noted that seals and fish in the Arctic were affected by bioaccumulation of contaminants that condensed into the marine environment from the atmosphere, showing that LRAT of semi-volatile industrial chemicals was having a significant effect on contamination of marine ecosystems in the Arctic (4). The biomagnification of contaminants from fish to seals was significant, and in hindsight, it should have been clear that biomagnification from seals to humans would be large as well. In the Dewailly et al. study, the contaminant class was polychlorinated biphenyls (PCBs) which were not manufactured anywhere in North America after 1977 and Europe after 1983. Immediately, the issues of environmental persistence and bioaccumulation/biomagnification were considered to be important, and have been ever since. 107

The difficulty with a study like Dewailly et al. (3) was how to address the contamination issue with the local community where it was found. How does one report a high level of PCB contamination in human breast milk to a population which has no industry, may not have any PCB sources in the community, and not know – or even not care – what PCBs are? After all, nobody can see environmental chemical contaminants in most cases, so how does one convince anybody that they really are present?

Atmospheric Mercury from a Coal-Fired Power Plant on Svalbard Longyearbyen, on Svalbard, is the location of the only operating coal power plant in a Norwegian territory and has depended on this form of energy throughout its history (Figure 1). Unilike the community where Dewailly et al. conducted research on organic contaminants in breast milk, Svalbard has no indigenous population. Everyone there, including environmental chemistry students and scientists working in the community, is from elsewhere. As a result, students and researchers have a direct role in understanding the environmental impacts that they and others in the community create simply by living and working there and consuming energy or constructing buildings in the process. One outstanding feature in Longyearbyen is the coal plant, one of only two that we know of in the Arctic. This plant creates an opportunity to measure the impact of energy production on the environment in a way that people living in a larger community elsewhere in the world would not consider. The interest in investigating a coal plant in this situation arises from the image of the Arctic as “pristine”, and therefore a place where, with no coal plant, the residues of energy production would not expect to be found, unless delivered by LRAT. While combustion chemistry is not often related to investigations in environmental chemistry, one learns that researching the effects of living in such close proximity to a coal plant that expanding into new areas of chemical investigation becomes a necessity if one is to comprehend the real environment. Energy production in Arctic towns involves use of fossil fuels, usually transported there from elsewhere. In most towns, diesel fuel is used. The residues of combustion will always leave a chemical imprint on the community, and the magnitude of that imprint depends on the fuel and how it is managed. Since mercury is a significant neurotoxin to humans, and can move easily between environmental compartments, we decided that it would be useful to learn more about it for our courses at the University Center on Svalbard. Unlike the Inuit community where Dewailly et al. (3) worked, having a resident student population in the Arctic creates the opportunity to make local contaminant issues part of the curriculum. Mercury analysis in the Arctic atmosphere has focused on long-term measurements of elemental mercury (Hg0(g)) at Alert, on Ellesmere Island in Canada (5), at Zeppelin Observatory on Svalbard (6) and at Station Nord in northeast Greenland (5). Studies at these sites are characteristic of many contaminant investigations in the Arctic, including Svalbard, that focus on 108

the effects of LRAT and deposition with few, if any, observations of local contaminant sources. Some investigators have concluded that there are no anthropogenic mercury emissions in the Arctic (7). However, Svalbard has two potential emissions sources, both coal-burning power plants in Longyearbyen and Barentsburg (Figure 1), which need to be considered.

Figure 1. Svalbard map highlighting Longyearbyen (78.22°N 15.65°E). From the Norwegian Polar Institute. Hg0(g) has an estimated atmospheric lifetime of about 1 year6 so it is well mixed in the atmosphere and distributed globally in concentrations that average between 1.5 – 1.7 ng m-3 (6, 8, 9). Anthropogenic emissions are dominated by coal combustion and these emissions are highly correlated to the amounts of mercury in the coal that is burned, suggesting that the process will convert mercury to the gas phase (9). Mercury in coal and combustion systems can be found in three different forms, as HgS found in pyrite (see below), as Hg2+(aq) after oxidation, and as Hg0(g), the latter being the most common form of atmospheric emissions. Mercury in coal is normally HgS and is a contaminant in pyrite (FeS2) commonly found in bituminous coal (10–12). Modern coal plants wash bituminous coal before combustion in order to remove pyrite because it does not support combustion (13). Washing removes variable amounts of mercury ranging from 10 – 50%, depending 109

on the coal (11, 13). For unwashed coal, sulfur from both iron and mercury will oxidize to SO2, the discharge of which is regulated in some countries. After HgS is oxidized, mercury will be released in some form, perhaps as an HgCl2 or as Hg2+(aq) in the presence of water in contact with combustion gases. Mercury may remain as Hg2+(aq), but in the presence of SO32-(aq), a strong Hg2+(aq) ligand, it will accept unshared electrons from SO32-(aq) to form Hg0(g) and move in to the atmosphere following a series of intermediate reactions (14, 15). In 2016, a guest lecturer in one of our university courses on Svalbard deployed a portable mercury analyzer at our site during her visit in early May. The intent was to measure the concentrations of Hg0(g) at a site where it has not been measured before but where the concentration might be influenced by the local coal-burning power plant. This research during our course is the first that we are aware of to measure Hg0(g) concentrations generated from an anthropogenic source in the Arctic. Atmospheric contamination in Longyearbyen by substances other than mercury has been documented, showing that the community is affected by some typical urban contaminants (see section about flame retardants, below). In Longyearbyen we collected continuous air samples, with 5-second interval sampling and 10-minute reporting interval, from 2 to 10 May 2016 (Monday to Monday) using a Lumex 915+ atomic fluorescence spectrophotometer. The sampling site was 725 m upwind (to the east) from the coal-burning power plant. The device, which was on loan to us during this time, was located inside the Svalbard Research Park (Svalbardforskningsparken) with a sampling tube extending outside. It was calibrated against a mercury saturated cell before being put into operation. It was reset to zero by drawing air through a dedicated inlet with a black carbon absorbant at the beginning of alternate sample reports (every 20 minutes). As a spectrometer packaged in a small field-ready case, it was typical of several modern instruments available for measurement of trace gases in the atmosphere. Movement of Hg0(g) could be affected by meterological variables, so the class collected air temperature data (hourly averages) from the Adventdalen weather station, located 1.02 km ESE from the Svalbard Research Park. Wind direction and speed data (hourly averages) were from Svalbard Lufthavn (airport), located 2.36 km northwest. The variability of these meteorological data over time were associated with Hg0(g) variability in an effort to determine if weather conditions had an effect on our observations. Three notable results are apparent in the Hg0(g) data set from Longyearbyen. First is a large daily cycle of Hg0(g) with the highest daily concentrations, 5.7 ng m-3, occurring around midday and the lowest values, about 1.0 – 1.5 ng m-3, within three hours of midnight (Figure 2). The low end of the range is consistent with the lowest average concentration, 1.23 ng m-3, observed during a cruise in the Arctic Ocean (16). This range is a factor of about 5.7 every day showing the effect of a large, active source, which we assume is the coal-burning power plant. All Hg0(g) investigations that we have found in the literature show ranges, but not on a daily basis: At the Arctic sampling site at Alert, the average annual range of Hg0(g) was a factor of 2 between 1995 and 2007 (17), less than half the daily range at Longyearbyen. The second result is the extreme event on 9 May, with a jump in concentration up to 42 ng m-3 lasting 20 minutes during a series of obserations 110

over about 90 minutes from beginning to end (not shown). Following this, the daily cycle was once again observed. The cause of this event is unknown but assumed to be associated with power plant emissions. Including the extreme event, the range of values in Longyearbyen is 1.0 to 42 ng m-3. Without including the extreme values on 9 May, the third major result is the average value of 2.7 ng m-3 (+/- 0.87, n = 1131), between 70% and greater than 100% more than the average Arctic background amounts that range from 1.23 to 1.56 ng m-3 (5–8, 16).

Figure 2. Daily Hg0(g) concentration cycles from Longyearbyen 2 to 10 May 2016 without peak values on 9 May. Dates are at 00:00 each day. The Longyearbyen average is greater than the “European polluted air” average concentration of 2.5 ng m-3 from Mace Head, Ireland (18, 19), where the maximum did not exceed 3.5 ng m-3, well below the Longyearbyen daily maximum. Mace Head was among the longest active atmospheric Hg0(g) sensors, and is near the western-most part of Europe (excluding Iceland), away from European pollution sources unless easterly winds prevail (18). The Mace Head average for “European polluted air” is about the same as the average observed in Detroit, USA (2.47 ng m-3) during 2004, a site known to be affected by many industrial/urban sources (20). The Detroit values range from 0.36 – 25.6 ng m-3, the maximum about 60% of the peak concentration observed in Longyearbyen. The peak value in Longyearbyen is similar to the lower concentrations of highly contaminated air events observed in East St. Louis USA from October to December 2002, which ranged from 50 – 220 ng m-3 Hg0(g) (21), 111

the latter value approaching the no-effect reference concentration of 300 ng m-3. These comparisons show that Longyearbyen is affected by a strong, continuous anthropogenic source of Hg0(g). A comparison of the daily Hg0(g) cycle with air temperature, wind direction and speed did not show an association with any of these variables. Air temperature variation (Figure 3) and wind direction or speed variation (not shown) did not show daily variability consistent with Hg0(g) trends. In fact, our Hg0(g) sampling location was upwind from the power plant during almost the entire sampling period with wind speed greater than 5 m s-1 most of the time.

Figure 3. Hourly average air temperature at Longyearbyen during Hg0(g) sampling, 2 – 10 May 2016.

The Longyearbyen power plant, which we assume is the source of the high average and daily cycle of Hg0(g), began operating in 1983. It is a 10 MW plant that burns about 25 000 MT of bituminous coal per year (2015) taken from Mine 7, about 12 km east from the plant. This coal has a high pyrite (FeS2) content, which is known to be contaminated with HgS (11, 12), noted above. As far as we know, FeS2 is not washed from Mine 7 bituminous coal, so associated Hg becomes part of the combustion residue. In general, older coal combustion systems, like the one in Longyearbyen, cannot be adapted to operate with washed coal (13). 112

High values of Hg0(g) have been observed in the emissions of bituminous coal plants in China, and those emissions have been highly correlated with the amounts of mercury found in the coal that is burned (9). In December 2015, the Longyearbyen plant was required to install air pollution control devices (APCD) to reduce emissions of NOx, particles, and SO2. Other monitored emissions included CO2, O2, temperature, and airflow (m3 per hour) (22). The first step in the APCD process treats NOx using urea. This is followed by an electrostatic precipitator to remove particles. The third step is wet flue gas desulfurization (FGD) using sea water. Most wet FGD processes in coal combustion systems employ a limestone-gypsum system (13, 23, 24), but the cost of this would likely be prohibitive in Longyearbyen because there is no local limestone source, while sea water is plentiful and free. In the FGD step using sea water, reaction of dissolved SO2 with H2O will first produce SO32-(aq) because the S in both SO2 and SO32-(aq) has the same oxidation state (4+). Protons resulting from this reaction are neutralized by natural seawater alkalinity (23). The SO32-(aq) will react readily with Hg2+(aq) either from the flue gas (including pyrite residues) or seawater itself, with S contributing unshared electrons to form Hg0(g) which will move to the atmosphere after a series of intermediate reactions (14, 15). The process of chemical reduction of Hg2+(aq) by SO32-(aq) has been observed at coal-fired power plants using sea water FGD in China (10, 25). The result is high Hg0(g) concentrations ranging up to 13.5 ng m-3, approximately 8 times greater than the global average, above the aeration ponds where FGD takes place or at discharge points of FGD water back in to the ocean. Combustion literature also suggests that Hg0(g) emissions from coal combustion may result from SO32-(aq) added for deoxygenation to prevent corrosion in the combustion system (26). Again, SO32-(aq) will reduce Hg2+(aq) to Hg0(g), especially at high temperatures (14, 15). This short Hg0(g) sampling campaign from Longyearbyen clearly shows the presence of both high emissions and daily trends of Hg0(g) in an Arctic settlement relying on coal combustion for local energy. The local and regional impacts of these emissions have not been studied. However, Dastoor and Durnford (27) noted that Hg0(g) concentrations at the Zeppelin Observatory in Ny-Ålesund (Figure 1) in 2007-2008 were 1.6 – 1.7 ng m-3, and significantly higher than at Alert, in the far northern Canadian Arctic, from 2005 – 2009 (1.4 - 1.6 ng m-3). They attributed this higher concentration to seawater emissions from the West Spitsbergen Current near Svalbard that originated near North America (and possible industrial mercury sources) with the Gulf Stream. The higher concentrations at Zeppelin than at both Station Nord and Alert were also noted by Angot et al. (5) and were attributed to the fact that Zeppelin during summer is surrounded by open water – presumably emitting Hg0(g), while Station Nord and Alert are surrounded by multi-year sea ice during most years, preventing emissions from surface water. Hirdman et al. (28) attribute peak Hg0(g) concentrations at Zeppelin during winter to transport of comparatively contaminated air masses from Europe. An additional consideration, based on our results, is that the source in Longyearbyen may contribute to higher Hg0(g) at Zeppelin which is 114 km NW (downwind) from Longyearbyen (29). 113

Documentation of the effects of this Arctic coal-burning site on Hg0(g) concentrations and distribution in the eastern Arctic is needed, along with on-going measurements to observe seasonal and long-term concentration changes.

Particle-Associated Flame Retardants in Air in an Arctic Town Beginning in 2010, we made an exercise of having students collect air samples on the roof of the Svalbard research park in our environmental chemistry courses. For both courses, it was necessary for students to understand how sampling air differs from sampling other environmental matrices. Collecting environmental samples for chemical analysis involves removing the substrate, whether it is ice, snow, water, soil or organisms, from the native system and putting it into a lower density matrix, the atmosphere, to measure the volume or mass. This is followed by measurement of chemical analytes of interest found in that volume or mass. An exception is collecting samples of the atmosphere itself because there is no lower density system to accept the sample in order to measure its volume. Air sampling requires a device to remove the analytes of interest from the air. The issue then becomes a question of how to collect and measure the volume of air from which the analytes have been removed. This issue first appeared in the scientific literature in the 1930s when Drinker et al. (30) performed toxicology experiments with rats to approximate the gas phase chlorinated biphenyl concentrations in factory air which were thought to affect workers at a manufacturing site. A major challenge became measuring the mass of contaminant that would have toxic effects, requiring controlling the amount of toxin released into the air but more importantly, calculation of the volume of air to which the test organisms were being exposed in the experiments. The description of the experiment refers to an orifice calibrator used to identify air flow (and thus volume over a unit of time), and is the earliest mention of this that we have found in the literature. The need for high volume air sampling – and the need for calibration of flow rate and volume using an orifice calibrator - became even more important in the USA with founding of the American Conference of Governmental Industrial Hygienists (ACGHI) which developed recommended concentration limits of a variety of contaminants in air that in 1966 resulted in a list of 78 mostly organic compounds (31). This list, along with limits proposed by Drinker et al. (30) introduced an added complication with air sampling, which was that the volume collected needed to be very large (typically greater than 500 m3) because of the toxic effect of a small mass of contaminant in air. High-volume (Hi-Vol) air sampler development soon followed the ACGHI limits with early designs in the 1960s that included use of vacuum pumps that could move large volumes of air (32). Later development in the 1980s included systems that have proven to be reliable in extreme weather conditions (33). Once students were able to quantify the volume of air collected over a period of time, we were able to analyze the samples for a series of particle-associated flame retardants, including some BFRs and organophosphorus flame retardants (OPFRs) that are often considered to be replacements for BFRs that are no longer 114

used or produced because of restrictions or bans by government agencies or treaties such as the Stockholm Convention. While we were able to conduct the sample collection as a course exercise, the samples had to be sent elsewhere for analysis by gas chromatography / mass spectrometry. Although the students were not able to experience the analytical part of the work, they were able to understand the meaning of the results. Earlier results on investigation of BFRs in an ice core from Svalbard suggested that concentrations of some of them were high, particularly those that were high production (34), leading us to realize that particles, with their associated contaminants, were subject to LRAT to glacier surfaces in the European Arctic. In this exercise, since the samples were collected on the roof of our building, we had to assume that the presence of these contaminants could be from either LRAT or from local emissions or from our building. Since this was the first investigation of this type, we were comfortable with this assumption. Organophosphate esters (OPEs) and BFRs are used in a large variety of consumer and industrial products to delay ignition and slow the spread of fire in order to comply with flammability regulations. Polybrominated diphenyl ethers (PBDEs) have historically been the most widely used BFRs, but these compounds now are off the market globally due to their persistence, bioaccumulation, and toxicity. Several PBDE compounds were added to the Stockholm Convention and are targeted for elimination of production and use. To compensate for the restrictions placed on PBDEs, the production and use of OPEs have increased. Halogenated (mainly chlorinated) OPEs, such as tris(2-chloroethyl) phosphate (TCEP), tris(1-chloro-2-propyl) phosphate (TCPP) and tris(1,3-dichloropropyl) phosphate (TDCPP), as well as non-halogenated aryl OPEs, such as triphenyl phosphate (TPP) and tricresyl phosphate (TCP), are used as flame retardants in building materials, electronics, plastics, and furniture and textiles. Some of the non-halogenated alkyl OPEs are also used as plasticizers and anti-foaming agents in hydraulic fluids, lacquers, and floor polishes. OPEs have been in use for several decades, and their global consumption as flame retardants was 270,000 tons in 2005. However, their production increased after the PBDE phase out; for example, production volumes for TDCPP, TPP, and TCPP in the United States increased from 450-4500 metric tons in 1990 to 4500-22500 metric tons in 2006. In Western Europe, the OPE production increased at about 10% between 2001 and 2006. Now OPEs constitute about 20% of the world’s flame retardant consumption. Despite these rapid increases in the use of OPEs, data on their environmental concentrations in the Arctic are rare, making new samples and data especially valuable. Like BFRs, OPEs are additive flame retardants and not covalently bound to the material in which they are used; hence, they can leach into the environment. Because of low vapor pressures, they are associated with particles in the atmosphere, indicating that if influenced by LRAT, it will be different from gas-phase compounds. Figure 4A shows the concentrations of the individual OPEs in Longyearbyen. The data are put in summary form as a class exercise showing, among other things, how statistical interpretations can be made. The sum of the eight OPE concentrations shown (ΣOPEs) ranged from 33 to 1450 pg/m3, with the mean 115

ΣOPE concentration of 426 ± 57 pg/m3. The non-chlorinated tri-n-butyl phosphate (TnBP) and 2-ethylhexyl-diphenyl phosphate (EHDPP) were the most abundant OPE congeners measured and were detected in all the samples at concentrations ranging from 5.6 to 1000 pg/m3 for TnBP and 6 to 300 pg/m3 for EHDPP. Mean tris(butoxyethyl) phosphate (TBEP) concentrations were statistically indistinguishable from the TnBP and EHDPP concentrations, but TBEP was detected only in ~25% of the samples with the concentrations ranging from 47 to 210 pg /m3. In addition, triphenyl phosphate (TPP) and tris(2-ethylhexyl) phosphate (TEHP) were detected in all samples, but at lower concentrations ranging from 1 to 52 pg/m3 and 1 to 42 pg m-3, respectively. Overall, the sum of all non-chlorinated OPE concentrations was ~75% of the ΣOPE concentrations. The sum of the three chlorinated OPEs, TCEP, TCPP, and TDCPP, was only ~25 % of the ΣOPE concentrations. The most abundant chlorinated OPE was TCPP, which was detected in all samples with the concentrations ranging from 10 to 190 pg m-3. Average TDCPP concentrations were statistically not distinguishable from the average TCPP concentrations, but this OPE was detected only in ~20% of the samples at concentrations ranging from 2 to 290 pg/m3. Finally, TCEP concentrations were the lowest among the levels of the chlorinated OPEs and ranged from 4 to 63 pg/m3. There are only two studies that have measured atmospheric OPE concentrations in the Arctic environment: ΣOPE concentrations of ~120–1100 pg/m3 were reported in three particle phase samples collected at Ny-Ålesund, and over the Arctic Ocean the reported ΣOPE concentrations ranged from 237 to 1270 pg/m3 in particle samples. Interestingly, both of these studies reported that chlorinated OPEs dominated the ΣOPE concentration, which is different from our findings. The OPE profile found in our samples agrees with the ΣOPEs profiles measured at North American remote sites, where the non-chlorinated OPEs, TnBP, TBEP and TPP, were found to comprise up to 85% of the ΣOPE concentrations. Overall, our data, like that in the literature, clearly show that OPEs are widely present in the atmosphere at remote regions throughout the world, including polar regions. It has been shown that particle-bound OPEs are persistent in the atmosphere with regard to OH. oxidation, with estimated atmospheric lifetimes ranging from ~6 days for non-chlorinated OPEs to ~14 days for TDCPP. Longer atmospheric lifetimes suggest that OPEs can undergo LRAT. Along with the OPEs, we measured many BFRs and Dechlorane Plus (DP) to compare to the OPE concentrations. Figure 4B shows the concentrations of total BFRs (ΣBFRs, the sum of 34 PBDE congeners, tetrabromo-p-xylene (pTBX), pentabromo-benzene (PBBz), pentabromoethylbenzene (PBEB), hexabromo-benzene (HBB), 2-ethylhexyl-2,3,4,5-tetra-bromobenzoate (TBB), bis(2-ethylhexyl)-tetrabromophthalate (TBPH), 1,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE), and decabromodiphenyl-ethane (DBDPE)), total PBDEs (ΣPBDEs, the sum of 34 PBDE), BDE-47, 99, 209, pTBX, PBBz, HBB, PBEB, and DP (the sum of the syn- and anti-DP). ΣBFR concentrations were in the range of 3–77 pg/m3, with the average concentration of 16 ± 2.7 pg/m3. TBB and TBPH were the dominant non-PBDE BFRs measured in these samples and comprised ~46% and 17% of ΣBFR concentrations, respectively. TBB and TBPH concentrations varied from 0.2 to 58 pg/m3 and 0.3 to 14 pg/m3, respectively and 116

were higher than concentrations previously reported for atmospheric vapor-phase samples collected in the Canadian and European Arctic and over the Arctic Ocean in 2006–2010. TBB and TBPH are major components of Firemaster 550, and the presence of relatively higher concentrations in our Longyearbyen samples could be related to a recent increase in the use of Firemaster 550. One way to identify Firemaster as a parent product from observed concentrations is a ratio of TBB to TBB+TBPH concentrations. We know that this ratio in the commercial Firemaster 550 mixture was 0.77 ± 0.03. In this study, the ratio averaged 0.65 ± 0.02, which is close enough to the Firemaster value to suggest that TBB and TBPH measured in Longyearbyen may be related Firemaster 550 emissions to the atmosphere.

Figure 4. (A) Concentrations (pg/m3) of OPEs and (B) BFRs and ΣDP in the atmospheric particle phase at Longyearbyen, Svalbard. The black horizontal line inside each box represents the median. The boxes represent the 25th and 75th percentiles. Error bars represent 5th and 95th percentiles. Note that the concentrations scale is 10 times greater for panel A than for panel B. Reprinted with permission from Salamova et al. (33) Copyright 2014, American Chemical Society.

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ΣPBDE concentrations were ~37% of ΣBFR on average, and ranged from 1.0 to 31 pg/m3. The most abundant PBDE congener was BDE-209, which contributed 24% to ΣPBDE concentrations and was in the 0.1-6.7 pg/m3 concentration range. The common penta-congeners, BDE-47 and BDE-99, were the second and third most abundant PBDEs and contributed on average ~15% and ~12% to the ΣPBDE concentrations. These PBDE concentrations generally agree with those previously measured at Ny-Ålesund on Svalbard. DBDPE and BTBPE were detected in most of these samples,but at lower concentrations (0.04-2.2 pg/m3 and 0.01-0.09 pg/m3, respectively). Among the bromobenzenes, HBB was detected in all samples with the concentrations ranging from 0.01 to 1.7 pg/m3. PBEB, pTBX, and PBBz were detected in ~70% of the samples with average concentrations lower than the HBB concentrations. Finally, DP was also detected in all of the samples, and ΣDP concentrations ranged from 0.05 to 5.0 pg/m3. The fractional abundance of anti-DP defined as a fraction of anti-DP in ΣDP varied from 43-90%, with the mean value of 75 ± 2%, which is consistent with the previously reported composition of the commercial DP mixture. Since OPEs are potential replacements for the discontinued PBDEs, we compared ΣOPE, total chlorinated OPE (ΣCl-OPEs), and total non-chlorinated OPE (Σnon-Cl-OPEs) concentrations with ΣBFR concentrations, as well as with the most abundant BFRs (TBB, TBPH, and ΣPBDEs) measured in the same samples (see Figure 5A). Overall, ΣOPE, ΣCl-OPE, Σnon-Cl-OPE concentrations are ~150, 100, and 35 times higher (on average) than the BFR concentrations, respectively (see Figure 5B). In other words, atmospheric OPE concentrations measured are 1-2 orders of magnitude higher than corresponding BFR concentrations, which is consistent with the OPE-BFR ratios found for the North American Great Lakes basin and oceanic air over the Northern Pacific. In fact, OPE concentrations measured in this study are 1-2 orders of magnitude higher than any BFR (specifically, PBDE) concentrations historically measured in the Arctic atmosphere, even those measured during the active PBDE production period. Figure 6 shows literature data on PBDE concentrations measured at various Arctic sites since the 1990s. With the exception of two high values found at Alert and Tagish in 1994/1995, which were attributed to local waste incineration sources and here assumed to be outliers, all of the previously measured ΣPBDE concentrations are within 1-10 pg/m3, while OPE concentrations measured in this study are generally between 10-1000 pg/m3.

Summary The results from the Arctic studies and experiences we have discussed demonstrate how small towns have been used as environmental chemistry laboratories, where contaminant levels of mercury and organic contaminants, from combustion, diffuse local emissions, or LRAT, are significantly affecting environmental quality at the local level. In the case of mercury emissions from coal combustion, the results show not only the importance of environmental chemistry, but a significant bit of combustion and pollution control chemistry, 118

which will impress upon students the need to use a very broad approach when attempting to understand the sources and processes involved in environmental chemistry. Not all of the experiences, results or processes we have presented are unique to the Arctic, but the fact that they are found there shows that the Arctic, while far away in the experiences or even imaginations of most environmental chemists, is part of the integrated world. The benefit to students is that the outcomes of these research investigations can be taken anywhere in the world with a broader understanding of the different processes affecting environmental chemistry, and that even the remote parts of the world are not off-limits to the effects of human processes.

Figure 5. (A) Concentrations (pg/m3) of ΣOPEs, Σnon-Cl-OPEs, ΣCl-OPEs, ΣBFRs, ΣPBDEs, TBB, and TBPH in the atmospheric particle phase at Longyearbyen, Svalbard. The red line represents the arithmetic mean, and the black horizontal line inside each box represents the median. The boxes represent the 25th and 75th percentiles. Error bars represent 5th and 95th percentiles. (B) Ratios of ΣOPE, Σnon-Cl-OPE, ΣCl-OPE concentrations to ΣBFR, ΣPBDE, TBB and TBPH concentrations. Reprinted with permission from Salamova et al. (33) Copyright 2014, American Chemical Society.

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Figure 6. Atmospheric concentrations (pg/m3) of ΣOPEs (purple, rightmost bar) in Longyearbyen, Svalbard and historic ΣPBDEs (blue bars; gas phase, the sum of di- to hepta-PBDE congener concentrations) measured at various Arctic sites worldwide. See reference (33) for information on literature references of data shown. Reprinted with permission from Salamova et al. (33) Copyright 2014, American Chemical Society.

The results that we have presented, while showing examples of the effects of human activity in the Arctic, are not known to be harmful to organisms in the environment. The Hg0(g) concentrations are below the no-effect reference concentrations, and the FRs do not have established reference concentrations in air. While there are mechanisms producing or moving these toxic substances in and to Longyearbyen, the immediate risk to the environment is low. However, for a region with very few if any sources of these contaminants, the need to understand the fates and effects, and in some cases the sources of these pollutants remains a challenge for the environmental chemist.

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Acknowledgments The research results reported here include experiences by both authors as professor (MHH) and student (SLC) at the University Center on Svalbard. The access to sampling opportunities resulting from courses AT-210 (Arctic Environmental Pollution) and AT-331 (Arctic Environmental Pollution: Atmospheric Distribution and Processes) are gratefully acknowledged. The sampling instrument producing mercury data was supplied by Michelle Nerentorp Mastromonaco, Chalmers Technical Univeristy, Götborg, Sweden. The section of this chapter on flame retardants is adapted from Salamova et al. (33)

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25. Sun, L.; Feng, L.; Yuan, D.; Lin, S.; Huang, S.; Gao, L.; Zhu, Y. The extent of the influence and flux estimation of volatile mercury from the aeration pool in a typical coal-fired power plant equipped with a seawater glue gas desulfurization system. Sci. Total Environ. 2013, 444, 559–564, DOI: 10.1016/j.scitotenv.2012.11.101. 26. Cotton, I. J. Oxygen scavengers – the chemistry of sulfite under hydrothermal conditions. Mater. Perf. 1987, 26, 41–48. 27. Dastoor, A. P.; Durnford, D. A. Arctic ocean: Is it sink or a source of atmospheric mercury? Environ. Sci. Technol. 2013, 48, 1707–1717, DOI: 10.1021/es404473e. 28. Hirdman, D.; Aspmo, K.; Burkhart, J. F.; Eckhardt, S.; Sodermann, H.; Stohl, A. Transport of mercury in the Arctic atmosphere: Evidence for a spring-time net sink and summer-time source. Geophys. Res. Lett. 2009, 36, L12814, DOI: 10.1029/2009GL038345. 29. Windfinder, 2017. https://www.windfinder.com/windstatistics/ longyearbyen_spitsbergen (accessed September 2, 2017). 30. Drinker, C.; Warren, M. F.; Bennett, G. A. The problem of possible systemic effects from certain chlorinated hydrocarbons. J. Ind. Hyg. Toxicol. 1937, 19, 283–311. 31. Danielson, J. A. Air Pollution Control Manual. U.S. Public Health Service, National Center for Air Pollution Control, 1967. 32. Jutze, G. A.; Foster, K. E. Recommended method for atmospheric sampling of fine particulate matter by filter media-high-volume sampler. J. Air Pollut. Control Assoc. 1967, 17, 17–25. 33. Salamova, A.; Hermanson, M. H.; Hites, R. A. Organophosphate and halogenated flame retardants in atmospheric particles from a European Arctic site. Environ. Sci. Technol. 2014, 48, 6133–6140, DOI: 10.1021/es500911d. 34. Hermanson, M. H.; Isaksson, E.; Forström, S.; Teixeira, C.; Muir, D. C. G.; Pohjola, V.; van de Wal, R. Deposition history of brominated flame retardant compounds to an ice core from Holtedahlfonna, Svalbard, Norway. Environ. Sci. Technol. 2010, 44, 7405–7410, DOI: 10.1021/es1016608.

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Chapter 9

Mapping of Brownfield Properties in the Detroit Community Using GIS Alexa Rihana-Abdallah* and Yuncong Pang Department of Civil &Environmental Engineering, University of Detroit Mercy, 4001 W. McNichols Road, Detroit, Michigan 48221, United States *E-mail: [email protected].

Brownfields are properties left abandoned or underused because of a perceived contamination problem. They contribute to urban sprawl, limit economic growth and reduce tax revenue. They also contribute to environmental degradation and pose potential risk to public health. For these reasons, brownfields are of interest as prospective sites for redevelopment. In Detroit, the motor city of Michigan, decades of industry and manufacturing plants have left a number of properties contaminated with organic and inorganic chemicals, heavy metals, and debris from dilapidated buildings. This work describes a classroom project in which brownfield sites were identified according to pollutant types or industrial activities and then mapped using the Geographic Information System software (GIS). Focusing primarily on communities in Detroit, students were able to use GIS to visually locate and map brownfield sites contaminated with either lead, asbestos, or petroleum products. This work further motivated them to research remediation teachniques for potential redevelopment of these sites in their communities.

Introduction The federal Environmental Protection Agency (EPA) defines brownfields as “abandoned, idled, or underused industrial and commercial facilities where expansion or redevelopment is complicated by a real or perceived environmental contamination” (1). Brownfields differ in many aspects, such as location, size, © 2018 American Chemical Society

age, past use, and degree of environmental contamination. These factors can pose obstructions to redevelopment. There are many types of properties classified as potential brownfields, including abandoned gas stations, landfills, old dry cleaning operations, and vacant industrial plants. Old and vacuous office buildings, vacant residential housing, warehouses, and commercial operations also can be classified as brownfields. Most of these properties may have contaminants such as asbestos, lead paint, or hazardous chemicals that must be cleaned up when redeveloping the properties. The EPA estimates that the number of brownfield sites in the United States exceeds 400,000 (2). This stagrant number stems from several factors including the decline of the manufacturing industry sector, the passing of more stringent environmental policies to protect public health and the environment, and the continued struggle to balance public safety and economic growth. The tension between motivations to ensure environmental quality and to promote economic development is mostly noticeable in urban areas hit by the loss of industrial jobs (3). During the 1970s and 1980s, in order to protect the public from brownfield contamination, the US Congress passed several acts and the US EPA initiated its Superfund program designed to list contaminated sites on the National Priority List (NPL) and fund their cleanup process. This program sparked an interest in brownfield redevelopment and helped revive economic life in urban communities.

Brownfields in Michigan Brownfield classification encompasses a wide variety of pollutants and various degrees of contamination. Students were asked to list industries and manufacturing operations in Michigan that can be sources of accidental spills and thus have the potential to produce contaminated sites. A list of industrial activities was compiled. Then, using the EPA and Department of Environmental Quality (DEQ) websites, brownfield sites by county were tabulated according to the different activities and operations conducted on these sites (4–6). Students then generated a list of typical pollutants expected to arise from the identified activities. Table 1 displays the number of brownfields per county classified according to the category of activities. This table is by no means an exhaustive list of brownfields in Michigan. To better visualize the extent of contaminated sites in the state, GIS was used to map the brownfields by county. GIS software is designed to store, display, and analyze geographic and spatial data. GIS stores data on geographical features and characteristics and allows the user to produce maps and layer the statistical data on its geographical location. The software used in this study is ArcGIS 9.3, a tool that helps visualize the data and enhance users’ understanding of the data for further analysis. Figure 1 shows the number of brownfields in each county. The colors on the map each are associated with a range of numbers, with red representing the highest range. As seen in Figure 1, most of the brownfields in Michigan are concentrated in Wayne County, which contains the city of Detroit.

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Figure 1. Brownfields in Michigan. (see color insert)

Table 1. Brownfields in Michigan by contaminants (4–6) Typical Activity

Automotive refinishing and repair

Typical Contaminants Found

Some metals and metal dust; various organic compounds; solvents; paint and paint sludge; scrap metal; waste oil

County

Number of Brownfields

Oakland

8

Jackson

4

Macomb

3

Wayne

2

Ionia

2

Allegan

1

Hillsdale

1

Continued on next page.

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Table 1. (Continued). Brownfields in Michigan by contaminants (4–6) Typical Activity

Typical Contaminants Found

Coal gasification

Polynuclear aromatic hydrocarbons (PAH)

Dry cleaning

Volatile organic compounds (VOCs) such as chloroform and tetrachloroethane; various solvents; spot removers; fluorocarbon 113

Incinerators

Dioxin; various municipal and industrial waste

Landfills

Machine shops/metal fabrication

Metals; VOCs; polychlorinated biphenyl (PCB); ammonia; methane; household products and cleaners; pesticides; various wastes

Metals; VOCs; dioxin; beryllium; degreasing agents; solvents; waste oils

County

Number of Brownfields

Monroe

1

Wayne

1

Ionia

1

Wayne

2

Oakland

4

Monroe

2

Newaygo

1

Macomb

1

Wayne

1

Lenawee

1

Macomb

5

Wayne

2

Oakland

2

Shiawassee

1

Jackson

1

Bay

1

Ionia

1

Kent

1

Hillsdale

1

Lenawee

1

Clinton

1

Polymers; phthalates; cadmium; solvents; resins; chemical additives; VOCs

Kalamazoo

1

Shiawassee

1

Jackson

1

Pharmaceutical manufacturing

Lead; various organic chemicals; organic solvents

Wayne

1

Silver; solvents; acids; waste oils; inks; and dyes; photographic chemicals

Oakland

1

Printing industry

Monroe

1

Plastics manufacturing

Continued on next page.

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Table 1. (Continued). Brownfields in Michigan by contaminants (4–6) Typical Activity

Typical Contaminants Found

Scrap metal operations

Various metals (such as lead and nickel); PCBs; dioxin

Petroleum refining and reuse

Electroplating operations

Petroleum hydrocarbons; benzene, toluene, ethylbenzene, xylene (BTEX); solvents; fuels; oil and grease

Various metals such as cadmium, chromium, cyanide, copper, nickel

County

Number of Brownfields

Oakland

1

Wayne

8

Oakland

3

Kalamazoo

2

Shiawassee

1

Kent

1

Jackson

1

Wayne

1

Brownfields in Detroit The city of Detroit is steeped in history. Its industrial boom erupted in the early part of the twentieth century with the advent of the automobile. The automotive industry allowed the city to grow exponentially in a very short period of time. Production boomed, jobs were abundant, thousands of homes were built for workers, and the city grew and flourished (7). However, with better technology, the industry began to replace and refine the workforce. Jobs once numerous began to wane. Socioeconomic issues came to a head in 1967 when the great race riots of Detroit raged for five days. Half-burned houses, empty factories, and vacant land soon peppered the city’s landscape. About 30% of Detroit is now vacant land, which accounts for about 40 square miles of the city’s total 138.77 square mile area. The city’s population has shrunken from a peak of 2 million in the early 1950s to 900,000 today (8). With all of these dilapidated buildings and decaying factories come several environmental problems. When most of these buildings were erected, environmental regulations, building codes, acceptable building materials and storage regulations were different from today’s standards. Before codes, buildings might have been structurally unsafe and unsanitary and emergency exits might have been inadequate. Building codes were developed following disastrous situations to address societal concerns about public health and safety by setting minimum requirements for building design, construction and operation to protect the public and natural resources. For example, current constructions must meet seismic design standards, flood-protection and wind-bracing requirements (9). In earlier construction projects, builders used asbestos for insulation due to its resistance to heat and fire. Before 1978, paint and gasoline contained lead. Leaking underground storage tanks (LUST) threatened to pollute groundwater with lead and gasoline. When improperly 129

utilized or disposed of, asbestos, lead and petroleum compounds present many environmental challenges that contribute to the formation of browfields. Primarily used for its natural fire-retardant properties, asbestos was used in many applications, including insulation for pipes and furnaces, floor and ceiling tiles, and textured paints. However, anytime asbestos is disturbed by sanding, remodeling, or demolition, asbestos particles if inhaled can cause asbestosis and eventually lead to lung cancer and mesothelioma (10). Lead contamination also poses serious problems, particularly in Detroit. It can be found in houses built before lead-based paint was banned in 1978, which includes almost 90% of all low-income Detroit housing (11), and in soil contaminated by air deposition of lead particles emitted before leaded gasoline was phased out. Digestion of lead paint chips and inhalation of lead dust can cause lead poisoning (12). Finally, petroleum contaminantion can arise from modern gasoline stations that use underground storage tanks (UST) to store fuel products. When gasoline stations are abandoned due to financial failure, these UST remain buried underneath the stations and can begin leaking over time. Leakage can be caused by malfunction or corrosion of the tanks, UST fill manholes, supply pipes, or dispensing pumps (13). The release of a fuel product can contaminate surrounding soil, groundwater and even surface water (14). Determining the source, extent and nature of the release is crucial in containing and cleaning the spill.

Figure 2. Brownfield sites in Detroit. (see color insert) 130

Since Detroit has the most brownfield sites of all cities in Michigan, the focus was on locating brownfields contaminated with these three chemicals within the city limits. From old gas stations to abandoned factories to vacant commercial properties, these buildings are not only eyesores to the community but also health hazards to those living near them. A total of 27 properties contaminated with either lead, asbestos or petroleum chemicals were identified through the help of the Department of Environmental Affairs for the city of Detroit (15). This department, in collaboration with the US EPA and Michigan DEQ, formed the Redevelopment of Urban Sites (REUS) committee to address current and future issues related to brownfield sites as well as initiatives associated with environmental and economic redevelopment. The 27 properties then were mapped using GIS; the result is shown in Figure 2. Finally, students researched EPA recommendations for site cleanup.

Brownfield Remediation The process of remediating a site contaminated by hazardous substances can be complicated. Depending on the extent and nature of the contamination, the remediation process can be costly and time-consuming. The EPA, in conjunction with the State Response and Brownfield Program Operations Task Force, provides a 3-step approach to brownfield remediation (16). Step 1 is a basic assessment of the site, which is a two-phase process. The first phase is establishing the probability of contamination. The second phase is determining the planned future use of the site. Step 2, which establishes which contaminants are actually present, also is a two-phase process. The first phase requires a survey of the site and a review of all historical records regarding past use and operations of the site. The second phase involves collecting and analyzing soil, air and water samples, and estimating the amount of contaminant and potential effects on public health. Step 3 is cleaning up the site. The type of clean-up varies widely based on the type and amount of contamination. Removal and treatment of contaminated soil and groundwater are the most common approaches.

Conclusions This paper describes a classroom project that aims to identify certain industrial operations that cause site contamination in the state of Michigan. These sites are known as brownfields. Once tabulated by county, these sites then were mapped using the GIS software. Wayne county, home to the city of Detroit, had the largest number of brownfields. Students then selected three contaminants—asbestos, lead and petroleum—that are among the top three most common contaminants found in Detroit brownfields. Twenty-seven properties in Detroit were identified as contaminated by asbestos, lead and/or petroleum. The mapping of the properties by the GIS software was reported in the paper. Locating brownfields in their communities motivated students to research solutions for site cleanup. The three steps of brownfield remediation recommended by the EPA were identified. Overall, brownfield redevelopment poses challenges to major 131

cities like Detroit. Although it carries financial burden, it has enormous potential to bring environmental, economic, and social benefits to the city.

Acknowledgments The authors would like to acknowledge the help of the students who put forth effort and energy into this work. The authors would like to thank Yan J., McCutcheon K., and Hancock C. for their contribution and assistance with the data for this research project.

References U.S. Environmental Protection Agency. Brownfields. https://www.epa.gov/ brownfields (accessed on November 19, 2016) 2. Fischer, T.; Rosenberg, B.; Kchao, V.; Sheahan, J. Detroit Hosts EPA Brownfields 2008 Conference. http://www.usmayors.org/ usmayornewspaper/documents/05_19_08 (accessed October 11, 2016) 3. Brachman, L. Turning brownfields into community assets: Barriers to redevelopment. In Recycling the city: The use and reuse of urban land. Greenstein, R., Sungu-Eryilmaz. Y. Eds; Lincoln Institute of Land Policy: Cambridge, MA, 2004, 67-88. 4. Michigan Department of Environmental Quality. A MDEQ Report on the: Environmental Protection Bond Fund Cleanup and Redevelopment Fund Clean Michigan Initiative Bond Fund. https://www.nrc.gov/docs/ML1126/ ML112620577.pdf (accessed October 1, 2016) 5. Michigan Department of Environmental Quality. Inventory on Facilites. https://secure1.state.mi.us/facilitiesinventoryqueries/ (accessed October 5, 2016) 6. Contaminated Site Clean-Up Information (CLU-IN). Brownfields. https:// clu-in.org/cihandbook/CIOCpage/brown.htm (accessed on October 8, 2016) 7. Hyde, C. K. Detroit the Dynamic: The Industrial History of Detroit from Cigars to Cars. https://www.jstor.org/stable/20173894? seq=1#page_scan_tab_contents (accessed December 10, 2017) 8. Gallagher, J. Acres of Barren Blocks Offer Chance to Reinvent Detroit. Detroit Free Press. http://www.cityfarmer.info/2008/12/23/acres-of-barrenblocks-offer-chance-to-reinvent-detroit/ (accessed December 19, 2017) 9. Environmental Energy and Study Institute (EESI): The Value and Impact of Building Codes http://www.eesi.org/papers/view/the-value-and-impact-ofbuilding-codes (accessed March 24, 2018) 10. U.S. Environmental Protection Agency. Asbestos. http://www.epa.gov/iaq/ asbestos.html#Sources%20of%20Asbestos (accessed December 21, 2017) 11. Detroit Environmental Agenda. https://detroitenvironmentaljustice.org/wpcontent/uploads/2017/07/DETROIT-ENVIRONMENTAL-AGENDA.pdf (accessed March 21, 2018) 12. U.S. Environmental Protection Agency. Lead. http://www.epa.gov/lead (accessed December 21, 2017) 1.

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13. U.S. Environmental Protection Agency. Underground Storage Tank. https://www.epa.gov/ust/leaking-underground-storage-tanks-correctiveaction-resources (accessed March 21, 2018) 14. U.S. Environmental Protection Agency. Basic Information on Petroleum Brownfields. http://www.epa.gov/OUST/petroleumbrownfields/pbbasic.htm (accessed December 21, 2017) 15. Brownfield Listings: The Redevelopment Marketplace. https:// brownfieldlistings.com/ 16. Davis, T. S. Brownfields: A Comprehensive Guide to Redeveloping Contaminated Property; American Bar Association, 2002; pp 354−356.

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Editors’ Biographies Elizabeth S. Roberts-Kirchhoff Elizabeth Roberts-Kirchhoff received a B.S. in Chemistry from Texas A & M University and a Ph.D. in Biological Chemistry from the University of Michigan. After postdoctoral research at Wayne State University and The University of Michigan, she joined the faculty at the University of Detroit Mercy in 1997. Presently, Liz serves as Assistant Dean of Science in the College of Engineering & Science at the University of Detroit Mercy. Liz has taught courses in biochemistry, medicinal chemistry, and environmental toxicology to science majors and general, organic, and biochemistry to allied health majors. Liz has continued to develop and implement innovative and evidenced-based teaching pedagogies in the classroom and laboratory. This has included the development of modules in Process-oriented Guided Inquiry Learning, the innovative use of technologies in the classroom, and the implementation of project-based laboratories and course-based undergraduate research experiences. Her research focus on the analysis of metals and xenobiotics in food, consumer products, and the waters of Southeastern Michigan contributes to the growing body of knowledge about how we impact our environment and how our environment impacts our health. Liz has interest in the analysis of metals and xenobiotics including the X-ray fluorescence analysis of metals in food, dietary supplements, and cosmetics, and the GC-MS and LC-MS analysis of pesticides and pharmaceutical compounds in southeastern Michigan waterways.

Mark A. Benvenuto Mark Benvenuto received his education at the Virginia Military Institute and the University of Virginia (B.S. and Ph.D., respectively) and did a post-doctoral fellowship at the Pennsylvania State University. He also served a four-year term of service between his undergraduate and graduate education as a lieutenant in the United States Army, spent mostly in Mannheim, West Germany. He joined the University of Detroit Mercy as a faculty member in inorganic chemistry in 1993 and has been department chair since 2001. Mark has taught freshman-level chemistry to science and engineering students virtually every semester since he has been at the University of Detroit Mercy and has been voted the UDM Science Teacher of the Year by the students five times. He was also awarded the Michigan College Science Teacher of the Year in 2003 by the Michigan Science Teachers Association. He has been active in local and national ACS activities for two decades and is a Class of 2015 ACS Fellow. © 2018 American Chemical Society

Mark maintains research interests in two broad areas: coordination chemistry, specifically the development of multi-dentate ligands with unusual coordinating abilities, and in the analysis of trace materials in archaeological objects as well as food supplements and personal care products via energy dispersive X-ray fluorescence spectrometry.

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Indexes

Author Index Baker, S., 67 Benvenuto, M., ix, 81, 89 Bhagwagar, M., 81 Ezeh, V., 57 Guerard, J., 1 Hayes, S., 1 Hermanson, M., 105 Kahl, A., 49 Le Cras, S., 105 Makki, S., 81 Ngo, T., 89

Nguyen, G., 81 Pang, Y., 125 Pothoof, J., 81 Rihana-Abdallah, A., 125 Roberts-Kirchhoff, E., ix, 89 Stokes, D., 89 Thomas, S., 89 Tinawi, S., 81 Woodard, K., 21 Young, L., 21 Zimmermann, K., 21

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Subject Index A Arctic, environmental chemistry conclusions, 15 future work, 14 implementation distance laboratory experiences, 9 face-to-face or distance format, 7 lab manual and lab kit developed, 10f surface water and drinking water quality, paucity of data, 11 tentative course schedule, 8t introduction course-based undergraduate research, 2 distance learning, engagement challenges, 3 environmental chemistry, contextually relevant framework, 2 rationale, 4 distance and on-campus modalities, course, 5f faculty-guided research projects, theoretical framework, 6f UAF, STEM core courses, 6 results, 12 course, formative and summative evaluation, 13 USPS, students, 13 Arctic communities, 105 air in an arctic town, particle-associated flame retardants, 114 OPEs, concentrations, 117f atmospheric mercury, 108 chemical reduction, process, 113 Longyearbyen, Daily Hg0(g) concentration cycles, 111f Longyearbyen, hourly average air temperature, 112f meterological variables, 110 svalbard map highlighting longyearbyen, 109f introduction, 106 summary, 118 atmospheric concentrations, 120f atmospheric particle phase, concentrations, 119f Atmospheric ammonia, trends assessment response to survey 2, 64f survey 2, 64t conclusion and future directions, 65

course and project description, 59 discussion, 65 introduction, 57 National Emission Inventory, 58f project implementation, 60 questions at the beginning of project, 60t project results, 61 ammonia concentration, scatter plot after removing the possible outlier data point, 63f ammonia concentration, scatter plot for Aug 22nd-Oct 31st 2017, 62f ammonia concentration, scatter plot for fall 2017, 62f average ammonia concentration, GIS plot, 63f

C Community-based undergraduate research experimental methods, 29 analyte PAHs, list, 32t deployment characteristics for each site, 34t each site, demographic data, 31t EJSCREEN, 30 non-invasive measures, PAS deployed at site C, 33f future goals, 43 interdisciplinary community-based research, influence, 40 EJ-CIP participation, results of student survey, 42t PAH concentration, correlation plots, 41f introduction, 22 CIP program, 25 employers that rated the described skills, percentage, 24f interdisciplinary nature of the project, Venn diagram, 29f interdisciplinary undergraduate research, 26 open access institution, experiential learning, 23 student population, demographic distribution, 22t student deliverables, 34

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annual Georgia Gwinnett College CREATE Symposium, 37 basic demographic information, 35 presentations and outreach, 36 undergraduates, preliminary data generated, 38 PAHs, distribution, 40f standard PAH mixture, chromatograms, 38f total PAH concentrations, 39f Cosmetic mineral eyeshadows, analysis, 89 conclusions, 100 experimental methods, 91 selected elements, detection limits, 92t introduction, 90 results and discussion, 92 aluminum, potassium and iron, concentration, 98f lead, concentrations, 95t manganese, concentration, 99f strontium, concentrations, 94t strontium and rubidium, concentration, 97f strontium and rubidium concentrations, 93 titanium in the makeup samples, concentration, 99f XRF, consumer mineral makeup analyzed, 96t zinc in the makeup samples, concentration, 97f

D Detroit community using GIS, mapping of brownfield properties brownfield remediation, 131 conclusions, 131 Detroit, brownfields, 129 brownfield sites, 130f introduction, 125 Michigan, brownfields, 126 brownfields, 127f brownfields, contaminants, 127t

Duckweed species, using DNA barcoding, 67 instructional perspective and conclusions, 75 DNA sequencing, technology, 76 introduction, 68 atpF-atpH barcode sequences, maximum likelihood dendrogram, 75f DNA extraction protocol, workflow, 70f duckweed, wild population, 70f homology search, example BLASTn output, 74f PCR conditions, 71 2% agarose, example results, 72f Sanger sequencing product, four channel chromatograph, 73f

N Nitrogen-containing ligands, synthesis of a novel series conclusions, 85 experimental section, 84 ligand synthetic data, 84t metal-ligand complex formation, 85t introduction, 81 results and discussion, 82 ligand synthesis, general route, 83f shortest and longest ligand, 83f

R Remote sensing, undergraduate research experience, 49 conclusions, 54 discussion, 54 introduction, 50 methods, 51 Coqui sensor on protoboard, 52f REU experience, 53 Riffle Arduino board, 52f

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