Dust Storm Identification via Satellite Remote Sensing [1 ed.] 9781616688899, 9781608769063

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Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved. Dust Storm Identification via Satellite Remote Sensing, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved. Dust Storm Identification via Satellite Remote Sensing, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

NATURAL DISASTER RESEARCH, PREDICTION AND MITIGATION SERIES

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DUST STORM IDENTIFICATION VIA SATELLITE REMOTE SENSING

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Solar Activity and Forest Fires Milan Rodovanovic and Joao Fernando Pereira Gomes 2009. ISBN: 978-1-60741-002-7 Indigenous Knowledge and Disaster Risk Reduction: From Practice to Policy Rajib Shaw, Anshu Sharma and Yukiko Takeuchi (Editors) 2009. ISBN: 978-1-60741-574-9 Indigenous Knowledge and Disaster Risk Reduction: From Practice to Policy Rajib Shaw, Anshu Sharma and Yukiko Takeuchi (Editors) 2009. ISBN: 978-1-60876-674-1 (Online Book)

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Forest Fires: Detection, Suppression and Prevention Eduards Gomez and Kristina Alvarez (Editors) 2009. ISBN: 978-1-60741-716-3 Meltdown: Climate Change, Natural Disasters and other Catastrophes – Fears and Concerns of the Future Kathryn Gow 2009. ISBN: 978-1-60876-153-1 Landslides: Causes, Types and Effects Ernest D. Werner and Hugh P. Friedman (Editors) 2010. ISBN: 978-1-60741-258-8 Dust Storms: Elemental Composition, Causes and Environmental Impacts Siniša Brstilo and Quentin Madunic (Editors) 2010. ISBN: 978-1-60876-456-3

Dust Storm Identification via Satellite Remote Sensing D.G. Kaskaoutis, H.D. Kambezidis; K.V.S. Badarinath and Shailesh Kumar Kharol 2010. ISBN: 978-1-60876-906-3

Dust Storm Identification via Satellite Remote Sensing, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved. Dust Storm Identification via Satellite Remote Sensing, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

NATURAL DISASTER RESEARCH, PREDICTION AND MITIGATION SERIES

Copyright © 2010. Nova Science Publishers, Incorporated. All rights reserved.

DUST STORM IDENTIFICATION VIA SATELLITE REMOTE SENSING

D.G. KASKAOUTIS H.D. KAMBEZIDIS K.V.S. BADARINATH AND

SHAILESH KUMAR KHAROL

Nova Science Publishers, Inc. New York

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NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Dust storm identification via satellite remote sensing / D.G. Kaskaoutis ... [et al.]. p. cm. Includes index. ISBN 978-1-61668-889-9 (eBook) 1. Dust storms--Sahara--Remote sensing. I. Kaskaoutis, D. G. QC959.S34D87 2009 551.55'9--dc22 2009047848

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CONTENTS Preface

ix

About the Authors

ix

Chapter 1

Introduction

1

Chapter 2

Major Dust Source Regions

3

Chapter 3

Dust Characteristics and Effects

9

Chapter 4

Techniques for Dust Identification and Monitoring

17

Chapter 5

Dust Transport Model (DREAM)

27

Chapter 6

Identification of the SD Events Over Athens in the Period 2000-2005

29

Analysis of the SD Events Over Athens in the Period 2000-2005

37

Source Regions and Pathways of the SD Transport Over Athens in the Period 2000-2005

41

Seasonal Variations of the SD Occurrences and Optical Properties

45

Analysis of the Dust-Transport Mechanisms Over Athens

51

Chapter 11

The Use of AI for the Dust Detection

57

Chapter 12

Combination of Satellite Retrievals and Model Applications for the Dust Monitoring

63

Chapter 7 Chapter 8 Chapter 9 Chapter 10

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Contents

Chapter 13

Application of the Method

77

Chapter 14

Conclusions

85

Acknowledgments

87

References

89

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Index

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PREFACE Dust storms are considered natural hazards, which affect ecosystems for a short-time interval ranging from a few hours to a few days. Due to the significant impact of dust outbreaks on climate, human health and ecosystems, numerous studies have been conducted throughout the world with differing instrumentation and techniques focusing on the investigation about such events. The identification of the dust aerosol sources is a difficult process due to the complex natural and anthropogenic processes, which are involved in entraining soil particles into the atmosphere during a dust transport. Monitoring of these particles is only possible from satellites because ground-based measurements are very limited in space and time. Focusing mainly on the Sahara desert, this chapter provides a short review on the recent knowledge about the dust aerosol optical and physico-chemical properties, the seasonal variability of dust outbreaks, the dust source regions, the main pathways towards Southern Europe, which is mostly influenced, and the main results of similar studies. Furthermore, this chapter is looking forward to providing a new methodology to the scientific community for the dust transport monitoring using a combination of satellite data and back-trajectory analysis for the identification of coarse-mode aerosols, Sahara dust (SD) events and the analysis of the dust-transport mechanisms. The analysis covers a 6-year (20002005) period of daily aerosol optical depth at 550 nm (AOD550) and fine-mode (FM) fraction values, derived from Terra-MODIS observations. Based on the AOD550-FM relation, the cases satisfying the criterion AOD550>0.3 and FM1.0). The mean and the standard deviations of AOD550, FM and AI values are also given for the SD events over Athens in the period 2000-2005. Year

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Season 2000 2001 2002 2003 2004 2005 Winter Spring Summer Autumn 2000-2005

Number ofNumber ofSahara dustIntense SDAOD550 data coarse-mode (SD) events events (SD events) particles 266 51 (19%) 16 (31%) 5 (31%) 0.47±0.15 298 84 (28%) 12 (14%) 6 (50%) 0.64±0.26 313 56 (18%) 20 (36%) 9 (45%) 0.68±0.24 307 63 (20%) 7 (11%) 1 (14%) 0.51±0.17 311 45 (14%) 12 (27%) 3 (25%) 0.51±0.18 309 38 (12%) 12 (32%) 8 (67%) 0.53±0.21 376 13 (4%) 7 (54%) 4 (57%) 0.57±0.24 466 40 (9%) 27 (68%) 16 (59%) 0.62±0.27 510 182 (35%) 30 (16%) 8 (27%) 0.54±0.19 452 102 (22%) 15 (15%) 4 (27%) 0.47±0.12 1804 337 (18.7%) 79 (23.4%) 32 (40.5%) 0.54±0.21

FM AI (SD events) (SD events) 0.45±0.09 0.48±0.13 0.44±0.11 0.41±0.14 0.47±0.14 0.49±0.15 0.43±0.03 0.52±0.13 0.45±0.13 0.44±0.12 0.46±0.13

1.03±0.62 1.26±0.77 1.54±0.86 0.63±0.70 1.12±0.65 0.51±0.58 0.63±0.48 1.13±0.73 1.32±0.87 0.59±0.61 1.11±0.77

The standard deviations of AOD550 were found to be largest during winter and spring, when AOD550 is maximum, thus indicating stronger variability in aerosol load over GAA associated with the dust events. Large standard deviations of AOD550 can also be related to the variability of the dry deposition processes, associated with local meteorological conditions especially in winter and, also, to some intense dust events in spring. In contrast, during the summer and autumn the dust events are not so intense and the atmospheric conditions seem to be more stable, indicative of the lower standard deviations of the AOD550 values. Moreover, there is a significant year-to-year variability in dust outbreaks. Thus, there were slightly lower AOD550 magnitudes and variability in 2003, associated

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Analysis of the SD Events Over Athens in the Period 2000-2005

39

with smaller daily peaks in AOD550, which are probably attributed to the less frequent dust cases (7) in this year. Note also that mean values of AOD550 and FM are slightly lower in 2003 (0.51 and 0.41, respectively) than in 2002 (0.68 and 0.44, respectively). The computed analysis has shown a mean number of ~13 SD events per year in the period February 2000-December 2005. Papayannis et al. (2005) reported a larger mean number of 18 SD events per year in the period 2000-2002. However, limiting the results to this common period, Papayannis et al. (2005) found 50 SD events, a number too close to ours (48). Both results compare well to a mean value of 16 SD events per year, during an 11-year period (19831994), reported by Moulin et al. (1997) for the western Mediterranean and the Ligurian Sea, while Meloni et al. (2007) reported about 19 SD events per year in the period 1999-2005, corresponding to 26% of the cloud-free days in Lampedusa. The seasonal variation of the SD events can be partly explained by the prevailing synoptic weather conditions. During spring, strong aerosol activity takes place in the eastern Mediterranean, where dust is transported by thermal lows (Sharav cyclones) formed over North Africa, which then moves along the African coast from west to east (Alpert and Ziv, 1999; Barkan et al., 2005; Fotiadi et al., 2006). Nevertheless, the dust transported over any part of the Mediterranean basin exhibits a clear seasonal pattern in each region (Barnaba and Gobbi, 2004; Antoine and Nobileau, 2006). The most temporally extended investigations regarding the seasonal dust transport over the Mediterranean Sea have been conducted by Moulin et al. (1998) using Meteosat visible channel images in the period 1983-1994, and Antoine and Nobileau (2006) using SeaWiFS images in the period 1998-2004. The time series of AOD550 and FM in the present analysis, in conjunction with the air-mass trajectories, have shown that dust outbreaks can also take place in winter, but they are rare. This is normal given the less favorable conditions for dust transport in this season. In addition, it is worth mentioning another factor playing a major role in determining the SD seasonal pattern. This factor is precipitation, which is the most efficient removal process of suspended particles. Note that during summer the aerosol wet removal processes are practically absent over GAA. In contrast, the higher precipitation rate in the autumn-winter period tends to reduce the residence time of aerosol particles in the atmosphere. In case of non-local aerosols (dust or long-range pollution transport), the precipitation effect is expected to be even more evident (Barnaba and Gobbi, 2004). According to the literature, the high spring AOD550 values in the eastern Mediterranean are associated with strong dust events taking place in this season (Moulin et al., 1998; Karyampudi et al., 1999; Prospero et al., 2002; Barnaba and Gobbi, 2004; Antoine and Nobilaeu 2006; Pace et al., 2006; Fotiadi et al., 2006;

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Kalivitis et al., 2007; Meloni et al., 2007), when dust particles are transported from the North African deserts. This is also indicated by lower values of the Ångström exponent during spring. Nevertheless, these seasonal features are not depicted clearly over Athens using the MODIS AOD550 and FM dataset, since it was found (Kaskaoutis et al., 2007b) that the AOD550 shows a plateau of high values from April to August, while the FM presents a remarked decrease during the summer months. However, it is worth noticing that all the above studies include either all the Mediterranean Sea, or coastal areas close to the African continent, but in no case urban environments like the present analysis. The columnar aerosol optical properties over Athens are determined, not only from the SD outbreaks and the weather patterns over the Mediterranean, but also from the local emissions and the industrial activities in the urban environment. On Mediterranean islands, like Crete and Lampedusa, the identification of the dust events is easily identified due to their remote location from pollution sources. Also, at these locations, more dust events have been registered (Pace et al., 2006; Kalivitis et al., 2007) due to their proximity to the North African coast. Similarly, the PM exceedances caused by the SD transport over Rome are better associated with the dust events when they are considered at a rural rather than an urban site (Gobbi et al., 2007). Synoptically, we can establish that the aerosol properties in the vertical can be strongly modified within an urban environment with enhanced anthropogenic aerosols in the boundary layer. Thus, a relative thin dust plume in an elevated layer into the atmosphere might not be detectable using the aerosol properties in the whole atmospheric column. Therefore, the lidar system, which provides the vertical profile of the extinction coefficient, is more accurate and reliable for the detection of the thin dust plumes. On the other hand, the intense and thick dust plumes, which are transported vertically, has a clear signal in both satellite images and the retrieval aerosol properties as well as in the PM concentrations in the ground.

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Chapter 8

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SOURCE REGIONS AND PATHWAYS OF THE SD TRANSPORT OVER ATHENS IN THE PERIOD 2000-2005 The present chapter focuses on the identification of SD events from both satellite data and back-trajectory analysis; hence, it is necessary to investigate the pathways of dust transport over Athens. The use of back trajectories for the identification of dust events can help to evaluate the observations from remotesensing techniques or ground-based measurements, since their spatio-temporal resolution is limited by the presence of clouds (Meloni et al., 2007). To this respect Fig. 13 shows the main pathways of the air masses at 4000 m corresponding to the 79 SD events. The choice of this altitude is based on the fact that the Saharan outflow above the Mediterranean and Europe occurs mainly in the upper troposphere (Alpert et al., 2004; Papayannis et al., 2005). From Fig. 13 it is concluded that the western and southwestern sectors are the most preferable for the air masses transported in the free troposphere (4-km) during SD events. The back-trajectory analysis has shown that during dust events, the air masses are either coming from the Atlantic Ocean and traveling over North Africa and western Mediterranean or from north African arid regions across the central Mediterranean or the Libyan Sea before arriving over GAA. Both pathways suggest active mixing processes of aerosols in the vertical column. Nevertheless, various transport pathways can lead to the formation and transport of Saharan dust plumes towards Europe (Nickovic and Dobricic, 1996; Barkan et al., 2005). Similar pathways reaching Lampedusa are presented by Pace et al. (2006). For each case of a SD event, a potential source was identified if the criteria set in Section 4 were satisfied over the source areas. According to Fig. 13 the most

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important source regions of SD outbreaks are Algeria, Libya, Mauritania, Tunisia and Morocco, situated in the northern and northwestern parts of the Saharan desert. Also, there are some cases when the air masses come from south directions (Libya). It was found that in these cases, the SD are more intense carrying significant amounts of dust over Greece. Moreover, it was found (not presented here) that the air masses coming from Africa in the lower atmospheric levels (1000 and/or 500 m) exhibit a shift towards east, mainly originating form the eastern Algeria, Tunisia, Libya and Egypt. This shift is mainly depended on the prevailing meteorological conditions and the synoptic pressure systems that carry Saharan air masses over Greece following a cyclonic or anticyclonic pathway. This is another factor that controls the transport pathways, the source regions and the transportation of dust in the lower or the upper atmospheric levels and will be discussed in the following. It should be noted here that similar findings have been published by Papayannis et al. (2005) for Athens, by Coen et al. (2004) for Jungfraujoch (Swiss Alps), by Pace et al. (2006) and Meloni et al. (2007, 2008) for Lampedusa. Furthermore, Alpert et al. (2004) reported the North Chad area as the most active region for giving SD outbreaks. Prospero et al. (2002) found that the most active dust regions are situated in North Africa during summer and move southwest during the September-January period. Using the TOMS-AI dataset several studies (Middleton and Goudie, 2001; Israelevich et al., 2002; Prospero et al., 2002; Washington et al., 2003) have highlighted the Bodélé depression in Chad as the most important dust source region not only in Sahara but also in the world. A persistently active source of dust emissions is located south of Atlas Mountains (Morocco) with peak emissions occurring between June and August. Another active dust source region is the eastern Libyan desert extending into Egypt. Similar study by Brooks and Legrand (2000) specify several areas in the Sahel region, which is also significant to winter dust mobilization. It should be noted that all these regions have mean annual rainfall as low as between 100 and 200 mm. The interannual variability in dust is a result of changes in dust mobilization controlling parameters within the Sahel region (e.g., anthropogenic activities, rainfall and vegetation cover) as established by Moulin and Chiapello (2004) and Chiapello et al. (2005). The differences in dust sources between seasons are attributed to the prevailing meteorological transport conditions. Unfortunately, the limited number of SD events in each season does not allow a proper statistical analysis for the Athens case.

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Figure 13. Four-day back trajectories ending over GAA at 4000 m during all SD events in the period February 2000-December 2005.

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Chapter 9

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SEASONAL VARIATIONS OF THE SD OCCURRENCES AND OPTICAL PROPERTIES The monthly variation of the coarse-mode particles, corresponding to all SD events, is given in Fig. 14.It is obvious that during the winter and spring most of the coarse-mode cases correspond to SD outbreaks, while in the summer the inverse situation occurs. It was found (not presented here) that in the summer months, and especially in August, the majority of the cases is dominated by coarse-mode aerosols that correspond to air masses from northern directions enriched with marine aerosols during their passage above the Aegean Sea. These coarse-mode particles from northern directions (mainly soil materials and sea spray) were found to travel within the boundary layer. The uplift of soil coarsemode particles due to convection from the dry landscapes neighboring Athens in summer, the stagnation of the air masses and the absence of precipitation constitute a favorable combination for the presence of coarse-mode aerosols, or their formation through coagulation, condensation and gas-to-particle conversion. In winter almost all cases dominated by coarse-mode particles correspond to SD events. However, this season is the less favorable period for SD outbreaks, not only due to precipitation that favors the wet deposition and scavenging processes, but also due to the prevailing synoptic weather patterns; Greece is mostly influenced by air masses coming from the north and northwestern sectors. To the contrary, spring (especially April-May) is the most favorable period for intense SD events over Athens. This is driven by the synoptic meteorological conditions when Greece is influenced by air masses coming from southwest. According to other studies conducted in Crete (Fotiadi et al., 2006; Kalivitis et al., 2007), springtime is the period of most dust occurrences. Bearing in mind the differences between the locations, instrumentation, methodology and experimental periods,

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D.G. Kaskaoutis, H.D. Kambezidis, K.V.S. Badarinath et al.

the small differences in the seasonal distribution of dust between Athens and Crete can be assumed negligible. Early autumn can also be considered as a period with significant dust transport, which is in agreement with Papayannis et al.’s (2005) results. Moreover, Israelevich et al. (2003) identified three periods of increased dust events in the eastern Mediterranean, (a) spring (March-May), (b) summer (July-August) and, (c) autumn (September-November). They also found remarkable differences in the size distribution (larger particles in summer and autumn) as well as in the real and imaginary parts of the refractive index. These changes in the dust physical and optical properties suggest variations in the chemical composition of dust that may be attributed to changes in the source regions and transport mechanisms.

80

Frequency of occurence

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Coarse particles SD events Intense SD events

60 50 40 30 20 10 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month Figure 14. Monthly variation of the occurrence of coarse-mode particles (white), SD events (cyan), and intense SD events (blue) over GAA in the period 2000-2005. The intense SD events are identified as having values of AOD550>0.6 and AI>1.0.

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Seasonal Variations of the SD Occurrences and Optical Properties

47

F requency of occurrences

W in t e r

A u tu m n

Sum m er

S p r in g

12 11 10 9 8 7 6 5 4 3 2 1 0

W in t e r 2000

2001

2002

2003

2004

2005

Y ears

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Figure 15. Seasonal fluctuation of SD events over GAA in the period 2000-2005.

Figure 15 shows the seasonal fluctuation of the SD events in the period 20002005. It is obvious that significant variations in the number of such events also pointed out by Antoine and Nobileau, 2006, for the whole Mediterranean. Thus, in the period 2000-2002 the majority of the SD events occurred in the summer as shown by Papayannis et al. (2005). On the other hand, the springtime SD events clearly dominate in 2005. More specifically, on 16-17 April 2005 the most intense Sahara dust transport took place over Athens, limiting the visibility to only a few meters and increasing dramatically the PM10 concentrations (~200 μg m-3) at the surface, while the MODIS AOD550 value was larger than 2.0 over Greece. The annual dust deposition rate over Greece is significant due to its proximity to North Africa. Nihlen and Olsson (1995) estimated the annual dust deposition over the Aegean Sea to be 11.2-36.5 g m-2, while even larger deposition (10-100 g m-2) was estimated over Crete (Pye, 1992). On the other hand, a quite interesting remark is the small number of SD events in 2003 and especially during springtime. Nevertheless, there is an evidence for increasing SD transport over eastern Mediterranean in recent years (Ganor, 1994; Ganor and Foner, 1996). However, the limited number of years for dust monitoring does not allow for drawing statistically significant conclusions over Athens. The seasonal as well as the year-to-year variability of the occurrence of the SD events over Athens is

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D.G. Kaskaoutis, H.D. Kambezidis, K.V.S. Badarinath et al.

mainly attributed to the variability in dust emissions and transport pathways, the local and regional meteorology and the removal (wet and dry) processes along the dust trip. Since the discrimination of the coarse-mode particles is achieved through their columnar optical properties, the boundary layer aerosols mainly attributed to local anthropogenic emissions, play a significant role for the identification of the coarse-mode aerosols and then of the SD events. W in te r 0 .8 5 0 .8

A u tu m n

A O D at 550nm

0 .7 5

Sum m er

0 .7 0 .6 5 0 .6 0 .5 5 0 .5 0 .4 5

S p r in g

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0 .4 0 .3 5 0 .3

W in te r 2000

2001

2002

2003 Y ears

2004

2005

Figure 16. Seasonal variability of the AOD550 values during the SD events over GAA in the period 2000-2005.

Significant seasonal and annual variabilities are also obvious regarding the AOD550 values of the 79 SD events (Fig. 16). The mean seasonal AOD550 values range from 0.32 (autumn 2004) to 0.85 (summer 2001). Spring exhibits high AOD550 values, while autumn moderate-to-low values. On the other hand, winter exhibits a wide range of AOD550 values. It is worth observing the low values in 2003 and the very high ones in 2004. This large variability in AOD550 values is attributed to many factors, such as the intensity of the dust outbreak, the source region, the local and regional meteorology, the stagnation of the air masses, the removal processes and the dust-transport mechanisms. Similarly, Chiapello and Moulin (2002) found a high year-to-year variability in winter AODs. Moreover, in the Athens urban environment the emission of aerosols play significant role in the

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Seasonal Variations of the SD Occurrences and Optical Properties

49

columnar AOD550 values, a factor that cannot be ignored in such studies. Kosmopoulos et al. (2008) found that the temporal variability in the optical properties of the coarse-mode aerosols over Athens is larger that those of the urban/industrial ones or of the clean maritime conditions. Their interpretation was based on the greater variability of the natural processes that produce coarse-mode aerosols rather than the local emissions, which are responsible for the fine-mode particles. Furthermore, there is a considerable evidence that the North African dust emissions are highly variable over the last decades (Goudie and Middleton, 1992; N’tchayi Mbourou et al., 1997; Prospero and Lamb, 2003). A detailed analysis of the 79 SD events over GAA in the period 2000-2005 classifies them into 56 events of varying duration (1 to 4 consecutive days, Fig. 17). The average duration of the SD events is 1.4 days. The duration of individual dust episodes changes with season, being 1.23 in spring, 1.52 in summer and 1.01 in autumn-winter. The most frequent duration is 1 day (60%), followed by 2 days (13%). Longer durations (3 or 4 days) are very rare and are present in 4 cases only. The most persistent dust episode over Athens in the examined period, took place from 8 to 11 July 2002, with average AOD550 and FM values of 0.52±0.11 and 0.44±0.06, respectively. The respective AI was 1.2±0.4. During those dates an anticyclone was formed over the central part of North Sahara (Tunisia and west Libya), and facilitated the transport of air masses from Algeria to Athens at the altitude of 4000 m. As regards the dust transport within the boundary layer in the same period, the air masses came from the Atlantic Ocean exhibiting a descending path when approaching Athens. In the cold period, the synoptic meteorological conditions do not favor a stable atmosphere over the area and, as a consequence, the SD events over GAA do not last longer than one day. Nevertheless, the majority of these cases correspond to intense SD events also exhibiting high AOD550 values (0.55-0.6). Meloni et al. (2007) reported that the average duration of the SD events at Lampedusa was about 2.0±0.2 days, with a maximum length in summer (2.9±0.5) and a minimum in autumn-winter (1.6±0.2). The most frequent duration was 1 day (59%), followed by 2, 3, 4 and 5 days, while the longest duration of 13 consecutive days occurred in two episodes. The first of these episodes was from 6 to 18 August 1999 and, therefore, cannot be verified in the present analysis. The second lasted from 6 to 18 July 2002 (Fig. 9) and was persistent over a large part of the Mediterranean, and also over Athens (8-11 July 2002).

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Duration of SD events (days)

10 9 8

1 day 2 days 3 days 4 days

Average duration=1.4 days 56 events

7 6 5 4 3 2 1 0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Month

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Figure 17. Monthly variation of the duration of the SD events over GAA in the period 2000-2005.

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Chapter 10

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ANALYSIS OF THE DUST-TRANSPORT MECHANISMS OVER ATHENS This section conducts an analysis of the SD events over Athens and the related air-mass pathways that carry dust aerosols over the area both in the boundary layer and the free troposphere. To this respect, a further discrimination is made: a) trajectories at 4000, 1000 and/or 500 m indicate dust transport, implying a vertical transport (VT), b) trajectories at only 500 and 1000 m have African origin, meaning a boundary-layer transport (BLT), and c) cases with trajectories at 4000 m, are characterized as upper atmosphere transport (UAT) ones. The seasonal variation of the occurrences for the three dust-transport mechanisms over Athens is presented in Fig. 18. In Table 2 the frequency of occurrence, mean AOD550, FM and AI values are given for the 79 SD events. In general, the interaction of the air masses reaching Athens at 4000 m with the Saharan boundary layer is the most common mechanism for the dust transport over GAA, thus giving place to the VT or UAT types. This can be explained by taking into account that in the summer the mixed layer over the desert is higher than in other seasons because of the strong convective processes induced by radiative heating. In the spring, the VT mechanism is usually dominant within the boundary layer. In contrast, in the autumn and especially in the winter, the Saharan mixed layer is rather low and, therefore, the 4000-m air masses seldom interact with the mixing layer. Nevertheless, besides its low frequency, the VT type clearly dominates. The above situation is reversed in the summer, when the Sahara dust is transported above Athens at high altitudes thus enhancing the UAT mechanism. It is worth noticing that in all seasons the BLT mechanism is rather rare over Athens. This fact underlines that the presence of Saharan dust over Greece is either vertically

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distributed or transported in the free troposphere. On annual basis, the VT mechanism dominates since it corresponds to 53% of the cases, while the BLT is rather rare corresponding to only 16% (Table 2). The results presented by Meloni et al. (2007) give support to our explanation regarding the dust transport mechanisms. The same researchers found that the interaction of the 4000 m trajectory with the Saharan boundary layer in summer is the prevalent mechanism determining the air-mass loading, which can be explained from the higher (3945 m, on average) mixed layer. In spring and autumn the average altitude of the mixed layer is 2903 m and 2528 m, respectively, while in winter it reduces to 1321 m (Meloni et al., 2007). As expected, the AOD550 and AI values are higher for the VT mechanism, while the BLT is usually associated with lower values, since the dust particles interact with other aerosols near the surface and their deposition is enhanced. On the other hand, the FM values are lower for the BLT mechanism since the coarse-mode aerosols dominate not only in the vertical, but also near the surface, where the local emissions play a crucial role in the columnar aerosol properties.

18

A u tu m n

F requency of occurrences

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W in t e r

Sum m er

S p r in g

16 14 12 10 8 6 4 2 0

W in t e r BLT

VT

UAT

Figure 18. Seasonal variation of the frequency of occurrences for the three mechanisms of dust transport over GAA: vertical transport (VT), upper atmosphere transport (UAT) and boundary-layer transport (BLT). Dust Storm Identification via Satellite Remote Sensing, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

Analysis of the Dust-Transport Mechanisms Over Athens

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Table 2. Frequency of occurrence and aerosol properties (AOD550, FM and AI) for the three dust transport mechanisms over GAA in the period 20002005. Season Winter Occurrences 1 (8%) Boundary 0.37±0.00 AOD550 Layer 0.70±0.00 Transport AI (BLT) 0.56±0.00 FM Occurrences 5 (12%) Vertical 0.59±0.24 AOD550 Transport 1.00±0.69 AI (VT) 0.41±0.04 FM Occurrences 1 (4%) Upper 0.49±0.00 Atmosphere AOD550 1.30±0.00 Transport AI (UAT) 0.03±0.00 FM

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Mechanism

Parameter

Spring 2 (15%) 0.44±0.32 1.55±0.77 0.58±0.01 18 (43%) 0.79±0.28 1.47±0.79 0.530.12 7 (29%) 0.63±0.19 1.37±1.15 0.45±0.13

Summer 6 (46%) 0.54±0.16 1.55±0.57 0.28±0.15 10 (24%) 0.56±0.18 2.11±0.87 0.48±0.13 14 (58%) 0.62±0.22 1.53±0.43 0.42±0.15

Autumn 4 (31%) 0.41±0.11 1.15±0.73 0.34±0.14 9 (21%) 0.51±0.18 1.21±0.66 0.47±0.11 2 (8%) 0.48±0.09 0.80±0.56 0.37±0.09

Year 13 (16%) 0.47±0.14 1.33±0.63 0.37±0.18 42 (53%) 0.65±0.26 1.51±0.83 0.49±0.12 24 (30%) 0.60±0.19 1.41±0.72 0.41±0.15

Recently, Kalivitis et al. (2007), using multiyear PM10 measurements in conjunction with TOMS and AERONET aerosol data, showed that aerosols arrive over Crete, either simultaneously in the lower-free troposphere and inside the boundary layer, or initially into the free troposphere with the heavier particles gradually being scavenged inside the boundary layer. They found that 57% of the autumn dust cases are associated with VT and about 37% with UAT, whilst during the winter a similar situation was encountered with a VT dominance. The results of the present chapter are in close agreement with those findings, since VT corresponds to 60% and 71% of the cases in autumn and winter, respectively. On the other hand, in the summer the inverse situation was observed over Crete with UAT dominating (60%) over VT (25%) and BLT (15%), a conclusion too close to our results. The respective percentages in the present analysis are 47%, 33% and 20% for UAT, VET and BLT, respectively. Both pathways (VT and UAT) contribute almost equally to the dust transport over Crete in spring, while in Athens the VT mechanism clearly dominates in this season. Kalivitis et al. (2007) ascribed those results to the stability of the atmosphere during the summer, which blocks the vertical distribution of the dust layers. The similarity of the results in Fig. 18 with those presented by Kalivitis et al. (2007) allows the consideration of the same reasons for the dust transport mechanisms over Athens. On the other hand, a summer maximum of UAT has also been observed in the Canary islands,

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while in the winter the BLT mechanism was most common (Viana et al., 2002), contrary to our results. This fact partly differentiates the dust transport patterns from northern Africa towards eastern Mediterranean and Atlantic Ocean as has been also established by Alpert et al. (2004). The back-trajectory analysis performed in the period 2000-2005 for all SD events indicates the main pathways followed by the dust-laden air masses at each altitude. It was found that the western and southwestern sectors are the most preferable for the air-mass transport in the free troposphere during SD events. On the other hand, the dust-laden air masses ending over Athens in the boundary layer (BLT) are shifted easterly (Libya) and, as a consequence, the southern sector holds a larger fraction. This is linked to the synoptic meteorological situation when Greece is influenced by air masses coming from southwest in the warm period of the year. Under intense dust events and in conjunction with the local pollution, the AOD550 values over GAA can be up to 0.9, causing a significant reduction in visibility, degradation of the air quality and deleterious effects on human health. Long-range transport of desert dust mainly takes place in the free troposphere (Alpert et al., 2004), where the aerosol residence time is of the order of two weeks. On the other hand, Sahara air masses within the boundary layer travel over shorter distances and they mainly originate from Libya or Tunisia. In cases that the air masses traveled over longer distances (e.g. from western Algeria or Mauritania) they get weakened and mixed with other aerosols before reaching over Athens. As a consequence, ground-based and space-borne passive remote sensing, which provides columnar estimates of the aerosol load, cannot be used to quantify the radiative effects of mineral dust particles accurately. In addition, when the visible wavelengths are used, thin dust plumes often remain undetected over continents because of poor knowledge of the surface reflectance characteristics, which vary with season. In addition, dust often remains unresolved when the outbreaks are associated with cloud (cirrus) formation (Balis et al., 2006). These problems can be overcome with a lidar system. Its benefit in detection the vertical distribution and dust-transport mechanisms can be highlighted; Papayannis et al. (2005) showed that multiple distinct dust layers of variable thickness (200-300 m) were systematically observed in the altitude region between 1.5 and 6.5 km over Athens during various SD events. Also, Amiridis et al. (2005) found that the free tropospheric particles contributed between 30% and 54% to the total tropospheric AOD during some SD events over Thessaloniki. As mentioned in section 6, and also shown from other studies (e.g. Meloni et al., 2007; Ogunjobi et al., 2008), the use of back trajectories at different altitudes and their correlation with the source regions or columnar aerosol properties at a specific location may be problematic especially in cases that the air masses come

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from different sources and travel at different altitudes. As a consequence, in the 79 SD events not all the air masses were of a Saharan origin according to the criteria considered. This fact differentiates the dust transport mechanisms. Figure 19 shows the seasonal evolution of the air-mass occurrences at the three altitudes during the 79 SD events. It should be noted that only the air masses of Saharan origin have been taken into account. It is obvious that as the altitude increases so does the frequency of occurrence of the Saharan air masses, clearly indicating the dominant mechanism of UAT or VT over Athens. In winter, no differences in the frequency of occurrences at the three altitudes are presented thus favoring the VT mechanism. This situation significantly changes in the warm period of the year, when the African air masses at 4000 m clearly dominate over those at 1000 m and 500 m, while in autumn the differences are minimized. The gradient of the number of cases among all three altitudes is more intense in the summer thus favoring the UAT mechanism.

F requency of occurrence

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4000m

1000m

500m

A ll W in te r

S p r in g

Sum m er

A u tu m n

S p r in g

Figure 19. Seasonal variation of the air-mass trajectories at three altitudes in the atmosphere over GAA during the 79 SD events in the period 2000-2005.

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24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4

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Chapter 11

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THE USE OF AI FOR THE DUST DETECTION The presence of dust over Athens is mainly related to its long-range transport with a vertical development up to 4 km, easily identified by satellites. The availability of remote-sensing data such as TOMS-AI and IDDI can allow for a global view of dust. To investigate this, the AI obtained by TOMS is presented in a common diagram with the MODIS-AOD550 (Fig. 20) for the period 2000-2005. In general, the AI is adequate for the characterization of the dust load over the eastern Mediterranean on climatological basis (Kalivitis et al., 2007). Both AOD550 and AI varied widely in the experimental period from 0.1 to 1.2 and from 0.0 to ~3.5, respectively. In Fig. 20 periods with concurrent peaks of both AOD550 and AI values are pointed with dotted lines. AI peaks are more frequent in spring and summer than in winter and autumn indicating that the presence of dust can be detected to a certain extent by TOMS. The high AOD550 values in late spring and summer, in conjunction with relative high values of AI, indicate the predominance of coarse particles, probably dust transported from African deserts. A significant annual variation is obvious in both AI and AOD550 values, with the higher AI values to be present in the April-July period (0.81±0.73), while the AOD550 exhibits a broader maximum (March to September) of high values (~0.4). The median AI value for the whole period is 0.2, while the 60% of the values lie between 0.1 and 0.8 (upper left and upper right quartiles, respectively). The average AI value of 0.47±0.58 is considerably higher than its median, indicative of the spiky behavior of the values reaching 2.5-3.0 under intense SD events.

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AI

2.5 2.0 1.5 1.0 0.5 0.0 1.4

4/11/00 12/7/01 19/3/02 24/11/02 1/8/03

7/4/04 13/12/04 20/8/05

4/11/00 12/7/01 19/3/02 24/11/02 1/8/03

7/4/04 13/12/04 20/8/05

1.2

AOD 550

1.0 0.8 0.6 0.4 0.2 0.0

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Date

Figure 20. Variability of the AOD550 and AI values over GAA in the period 2000-2005. The continuous line refers to a 5-day running average. Some intense SD events are underlined with the dotted lines.

The coincidence of the spikes in AI and AOD550 is further investigated on a seasonal basis in order to obtain information on the ways in which the aerosol loading takes place over GAA. To this purpose, Fig. 21 correlates the AI values with AOD550 on a seasonal basis. AOD550 values above 0.3 are representative of turbid atmospheres in an urban environment, while high AI values indicate the presence of dust aerosols. Therefore, the fact of simultaneous high AI and AOD550 values is indicative of a dust event. In each season the threshold values of AI=1.0 and AOD550=0.3 have been considered; any values above these indicate the presence of SD events (shaded areas). The threshold of 1.0 in AI values is the same with that proposed by Prospero et al. (2002) for the identification of dust source regions in northern Africa. In winter, 35% of the AI spikes (above 1.0) occur simultaneously with AOD550 peaks (above 0.3), while the majority of the high AI values is associated with low AOD550. In this season, the AOD550 is low,

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while 4 cases with AI>1.0 were characterized as clear conditions. It was found that on those dates precipitation took place over Athens favoring wet deposition and ventilation of the air. In spring and summer the situation is reversed and the majority of the AI spikes corresponds to high AOD550 values. In spring the 90% of the AI spikes (AI>1.0) are associated with simultaneous high AOD550 values, while the respective fraction in the summer is about 80%. Simultaneous presence of high AI and AOD550 values is not high in the autumn, indicative of the clearer atmospheric conditions in this season. Nevertheless, the 65% of the AI>1.0 values correspond to AOD550>0.3. On the other hand, it is observed that the high AOD550 values in an urban environment do not correspond to high AI values in the majority of the cases, thus indicating that AI is not an appropriate tool for the identification of dust aerosols in the boundary layer.

3.5

3.5

Winter TOMS-AI

2.0 1.5

2.5 2.0 1.5

1.0

1.0

0.5

0.5 0.2

0.4

0.6

Spring

3.0

2.5

0.0 0.0

0.8

1.0

0.0 0.0

1.2

0.2

MODIS AOD550

0.6

0.8

1.0

1.2

3.5

Summer

2.5 2.0 1.5

2.5 2.0 1.5

1.0

1.0

0.5

0.5

0.2

0.4

0.6

0.8

MODIS AOD550

1.0

1.2

Autumn

3.0

TOMS-AI

3.0

0.0 0.0

0.4

MODIS AOD550

3.5

TOMS-AI

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TOMS-AI

3.0

0.0 0.0

0.2

0.4

0.6

0.8

1.0

1.2

MODIS AOD550

Figure 21. Seasonal correlation of AOD550 and AI values over GAA for the period 20002005. The AOD550>0.3 and AI>1.0 values are indicative of dust particles in the columnar aerosol load.

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VT

2.0

UAT 1.5

AI=0.92(0.30)AOD500- 0.89(0.17)

BLT

1.0

2

Aerosol Index

R =0.95 0.5

4.0

0.3

0.4

0.5

0.6

0.7

0.8

0.9

3.5

1.0

1.1

VT UAT BLT

3.0 2.5 2.0 1.5 1.0 0.5 0.0

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

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AOD550 Figure 22. Correlation between AOD550 and AI during SD events over GAA in the period 2000-2005 for the three transport mechanisms. The mean values for each transport mechanism are also shown.

The AOD550 and AI values are categorized according to the three transport mechanisms for the 79 SD events. Fig. 22 shows that there is no clear trend between the AOD550 and AI values since the scatter of the data is significant (lower panel). Thus, high AI values can be present for both high and low AOD550 and vice-versa. Nevertheless, higher AI values are associated with VT (1.51±0.83), while in cases when BLT is dominant AI takes its lowest value (1.33±0.63). Therefore, the uncertainty of AI to detect dust plumes in the boundary layer is obvious as also reported in other studies (Torres et al., 1998; Kalivitis et al., 2007). As expected, the columnar aerosol load is enhanced in cases of vertical transport. From this analysis it is clear that the air masses of Saharan origin at the lower levels (500 m or 1000 m) either interact with the marine boundary layer or are enriched with anthropogenic aerosols in the urban environment. This fact enhances AOD550, while it does not strongly affect the AI values over GAA. The correlation between the mean AOD550 and AI values (upper panel) provides useful information. The AI values increase significantly

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when the dust plume is observed at higher atmospheric levels (VT or UAT). These two transport mechanisms present no significant differences in AI values, but they have obvious differences in the AOD550 values, since the columnar aerosol load increases significantly in cases of vertical dust transport. A linear correlation holds between the mean AOD550 and AI values, associated with the 95% of the variance. Figure 23 shows the seasonal variation of both AOD550 and AI values for the three dust transport mechanisms over Athens. Both AOD500 and AI values exhibit their higher values in the VT mechanism, as expected, since the dust aerosols are dominant in the whole vertical column with this transport mechanism. Higher AOD550 is observed in spring due to more intense SD events, while in summer UAT presents higher AOD550 values since this transport mechanism dominates. In the winter, when VT is dominant, the AOD500 values for this transport mechanism are quite higher than those for the other two, while in the autumn no significant differences seem to occur. On the other hand, the BLT mechanism presents low AOD550, since these cases usually correspond to small-scale dust outbreaks, while the lower air masses are mixed with sea-salt aerosols before reaching over GAA. Also, the dust transport in the lower boundary layer strongly interacts with the surface thus enhancing the dry deposition. Regarding AI, the summer exhibits the highest values due to the longer duration of dust travel time in the upper atmospheric layers, while this parameter is enhanced for VT and UAT. This further confirms the assertions by Torres et al. (1998); they considered that the AI is significantly enhanced in dust plumes at an elevated layer in the atmosphere. To our knowledge there is a lack of similar studies examining the aerosol optical properties for different dust transport mechanisms and, therefore, a direct comparison or verification of our results cannot be achieved. All the above are in remarkable agreement with the transport mechanisms deduced from the trajectory analysis and reveal the usefulness of AI for the characterization of the dust load over the eastern Mediterranean on climatological basis. However, there are dust episodes, as they have been identified through the back-trajectories criteria, without peak in AI values (AI2.0) and large PM10 concentrations in Athens (>200 μgm-3). In addition, the presence of a well-defined low west of Lampedusa and a high pressure above Sahara led to the transport of intense Sahara dust over central Mediterranean, especially in spring (Meloni et al. 2008). On 29/6/2002 the pattern of 850-hPa geopotential height (Fig. 24c) was a northwestern air flow (a trough existed over Scandinavia), which in combination with a high-pressure system over northern Africa, mainly over Tunisia and Algeria, transferred continental air masses from central Europe to Balkans within the boundary layer. The wind speed (5 ms-1) over Greece was of breeze type. On the other hand, regarding the 500-hPa geopotential height distribution (Fig. 24d), the air flow was from the southwestern sector transferring air masses from the western parts of Africa towards Greece. The winds (20-24 ms-1) over the northwestern coasts of Africa towards western Balkans reached the type of strong gale. Therefore, in the middle troposhere Greece was influenced by southwestern air masses from northwestern arid regions of Africa with winds (9-14 ms-1) of strong breeze type. The warm region in Algeria indicates the occurrence of surface heating and uplift of warm air, which is associated with a strong convection and consequent uplift of dust particles driven by the surface heating. The uplift of air masses from the Sahara desert through convection towards Southern Europe and Greece can be verified from the 4000-m trajectory on that day (see Fig. 25b). This pattern determines a strong south-western/northeastern flow of dust-loaded air in the middle and upper atmosphere. Furthermore, this is a

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typical synoptic configuration allowing for the transport of Saharan dust to central Mediterranean and southern Italy (Barkan et al. 2005, Meloni et al. 2008). Barkan et al. (2005) identified the low in the Iberian Peninsula and west African coast, and the subtropical high as the two main features that influence the transport of dust from Africa to Europe. Moreover, Escudero et al. (2005) identified a similar pattern as the most frequent and effective in cause of dust outbreaks over the western Mediterranean and Iberia. Meloni et al. (2008) found that the abovedescribed meteorological situation produced the most favorable conditions for intense Saharan dust outbreaks at Lampedusa.

(a)

(b)

(c)

(d)

Figure 24. Atmospheric circulation in the lower (850-hPa geopotential height) and the middle (500-hPa geopotential height) troposphere, on 26/2/2001 (a, b), 29/6/2002 (c, d) and 13/10/2000 (e, f) over Europe. Dust Storm Identification via Satellite Remote Sensing, Nova Science Publishers, Incorporated, 2010. ProQuest Ebook Central,

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A completely different pattern with respect to the 850-hPa geopotential height appeared on 13/10/2000 (Fig. 24e). The presence of a ridge covering all Greece was responsible for the very low winds; namely the observed winds (4.5) above Libya and in the Eastern Mediterranean where the dust was transported vertically and the DREAM showed high aerosol load and concentration (Fig. 26a). As has been shown by DREAM (Fig. 26b), on 29/6/2002 the dust covered an extended area over Central and Eastern Mediterranean. This was also shown by the higher AOD550 values in Central Mediterranean (Fig. 27b). This feature is very pronounced in the AI values, since high values covered most part of Central Mediterranean (Fig. 29b). On the other hand, in the case of dust transport within the boundary layer (Fig. 29c), the AI values were quite low and the dust presence is not sensitive from the AI values. Furthermore, on that day (13/10/2000) the DREAM and AOD550 values were the lowest ones in close agreement with the low AI values. Moderate-to-low AI values were depicted in the Central part of the Mediterranean, since the AI values are not sensitive to cases of dust transport within the boundary layer. The same results were obtained by Kalivitis et al. (2007) analyzing the dust transport mechanisms over Crete. Furthermore, Kubilay et al. (2005) found that in the North-Eastern Mediterranean 30% of the dust events occur below the level of 850 hPa and cannot be detected effectively by TOMS. Moreover, the mineral dust particles may be coated with sulfate or other soluble materials reducing the UV-absorption and, therefore, the AI values (Levin et al., 1996). All the above demonstrate the temporal limitations of AI, since its use as an indicator of the dust amount is dictated by its dependence on the aerosol optical depth, the elevation of the aerosol layer, the cloud occurrence, the absorption properties and the particle-size distribution (Torres et al., 1998). Examining the dust transport mechanisms in the period 2000-2005 it was found that in the cases of VT both AOD550 and AI values were larger than those of the other two mechanisms. The mean AOD550 and AI values for the VT were found to be 0.57 and 1.07, while those for the UAT 0.55 and 1.0 and those for BLT 0.43 and 0.67. This was expected since the AOD550 is representative of the aerosol load in the vertical, so the VT exhibits the highest values and also, as mentioned above, the AI values are sensitive for the presence of absorbing aerosols in an elevated layer in the atmosphere, thus exhibiting higher values for VT and UAT. This fact also highlights the satellite use for the monitoring of the dust transport and the analysis of the dust optical characteristics.

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(a)

(b)

(c)

Figure 29. Contour maps of the AI values derived from the TOMS sensor on board the Earth Probe satellite on 26/2/2001 for vertical transport (a), 29/6/2002, upper atmosphere transport (b) and 13/10/2000, boundary layer transport (c). The AI values over Athens are 0.8, 1.8, and 0.1 for 26/2/2001, 29/6/1002 and 13/10/2000, respectively.

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In Southern Europe, several studies investigated the respective contributions of various aerosol sources to the PM10 levels. The aerosols in the Mediterranean have been a major concern due to the variety of sources, natural and anthropogenic (Pace et al., 2006, Zerefos et al., 2006), and the vicinity to the Sahara desert. Furthermore, it has been shown that the total aerosol optical depth was higher in this area compared to Northern Europe (Matthias et al. 2004). Therefore, there have been several studies on the impact of Saharan dust on air quality in Spain (Rodriguez et al., 2001, Escudero et al., 2007), in Italy (Kishcha et al., 2005, Gobbi et al., 2007) or Greece (Grivas et al., 2007). These studies examined the impact of Saharan dust on surface PM concentrations and the subsequent exceedance of the EU air-quality limits. Suggestively, it is referred, that the contribution of African dust flows to PM10 levels exceeding the EU threshold values has been estimated to be from 44 to 100% in Spain, with larger intensities for Southern stations in the summer (Escudero et al., 2007). Similarly, the SD events in 2001 corresponded to 63-68% of the days exceeding the PM10 limits in Rome (Gobbi et al., 2007). This issue constitutes a real challenge for further research in Athens combining the surface concentrations with the dusttransport mechanisms over a period of several years.

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Chapter 13

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APPLICATION OF THE METHOD In this section, a detailed discussion highlighting the main difficulties in SD monitoring via satellites and back trajectories in an urban environment is given. Furthermore, the main results of previous studies conducted over Mediterranean are underlined and compared with the present ones. The direct comparison of our results with those of other relevant studies conducted in the Mediterranean Sea does not constitute an easy task. Differences in instrumentation (ground-based sun-photometers, satellites, lidar), data collection, period of measurements, methodology for the classification of air masses, consideration of wind-direction sectors and air-mass altitudes are among the main difficulties. However, satellite and ground-based data are now available over extended periods. The main conclusions of the studies focusing on the Saharan dust transport towards Mediterranean and South Europe can be summarized as: i) the Saharan dust outbreaks occur mainly during spring in the eastern Mediterranean with a shift towards west in the summer and early autumn, ii) the summer maximum and winter minimum of aerosol optical depth are clearly identified in all studies, while the aerosol size and its seasonal evolution are strongly affected by the location, and iii) a clear south-to-north gradient is obvious regarding the desert-dust particles, optical depths and characteristics. León et al. (1999) used a combination of data from sunphotometrs and satellites (POLDER and METEOSAT) at Thessaloniki, Greece from April 1996 to June 1997. They found that the contribution of the aerosol load due to African dust is about 15%, while the majority of the dust events occurred in the period March to July. The smaller effect of the dust events in the Thessaloniki area compared to that in GAA is attributed to the longer distance traveled by aerosols and the additional mixing processes in the atmosphere. The occurrence of SD

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events exhibited a maximum in different months in the different regions of the Mediterranean Basin; the SD events are more frequent in April in the eastern, in June in the central, and in July in the western Mediterranean (Barnaba and Gobbi, 2004; Antoine and Nobileau, 2006; Meloni et al., 2007). According to Barkan et al. (2005), the average number of SD cases in July (period 1996-2000) over Italy was 3.7, which is comparable to our findings in the same month, i.e., 3.2. Escudero et al. (2005) analyzing aerosol data in Spain in the period 1996-2002 found that the SD events reach Spain in 15% of the days, which correspond to about 16 SD episodes per year, with absolute maximum in May and secondary in June, July and August. The average duration of the SD events over Spain was found to be 3.3 days. Antoine and Nobileau (2006) used 7-year (1998-2004) SeaWiFS data to investigate the seasonal evolution of the Saharan dust in the Mediterranean Basin and derived the spatial and temporal distribution of AOD and Ångström exponent. The winter minimum as well as the maximum values of AOD in spring and summer was captured. Focusing on the eastern Mediterranean and Aegean Sea, the most frequent occurrence of SD events can be found in spring and summer, even if the maximum dust load appears from May to August. Nevertheless, apart from the distinct annual trend, the Saharan dust load over the eastern part of the Mediterranean Basin in terms of AOD and Ångström exponent values exhibits a significant year-to-year variability. Meloni et al. (2007) reported that the SD events in Lampedusa correspond to 24% of the whole data set, during a long period (1999 and 2001-2005). Moreover, Pace et al. (2006), using data in the 2001-2003 period at the same location found that SD events were present in 30% of the cases. In contrast, in Athens the number of clear SD events (79 cases) seems to be too low in comparison to the 1804 events from observations of MODIS. The major dust sources in North Africa that influence the Eastern Mediterranean have been previously identified with the use of back trajectories (Pace et al., 2006; Meloni et al., 2007, 2008), TOMS (Prospero et al., 2002; Engelstaedter et al., 2006) and DREAM data (Alpert et al., 2004). Also, the seasonal dynamics of dust transport towards the Mediterranean Basin have been described by several authors (Alpert and Ziv, 1989; Moulin et al., 1998; Fotiadi et al., 2006; Meloni et al., 2007). Satellite or ground-based techniques give a global picture of the aerosols and can provide information on the columnar distribution of their properties. However, the accuracy of the remote-sensing measurements still has to be checked against ground-based instruments and lidars. Despite the satellite uncertainties and biases compared to ground-based instruments, the methodology for the identification of SD events leads to satisfactory results in the majority of the cases. On the other hand, there are some cases of Saharan dust outbreaks over

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Athens, which the proposed instrumentation and method cannot detect. A characteristic example for failing to detect the dust event over Athens via the methodology described in the present chapter is the 28-31 August 2000 case. This case was selected because that Saharan dust over Athens has extensively been analyzed by Papayannis et al. (2005) and, therefore, a direct comparison between the results can be made. For that dust event these researchers used satellite images, model (DREAM) predictions, back trajectories and lidar vertical profiles over Athens. From their analysis the dust event of 28-31 August 2000 can easily be detected as an elevated dust load causing a significant increase in extinction and backscatter coefficients as well as in lidar ratio between 2.5 and 4.5 km. The air masses at these altitudes showed a clear African origin. In addition, the DREAM model and the MODIS images strongly verified these results. Unfortunately, based on our aerosol discrimination (section 2), this dust event does not belong to coarse-mode aerosols. Obviously, the MODIS AOD550 values were high in the period 28-31 August 2000, exhibiting an average of 0.68±0.11. However, the FM values on these days were high (0.81±0.12) corresponding to urban/industrial aerosols. It should be noted that these FM values could be partly verified by the lidar profiles (Papayannis et al., 2005), which clearly showed a significant aerosol load in the boundary layer caused by anthropogenic activities. Also, the air masses at lower altitudes (975 and 850 hPa) came from Northern directions carrying pollution or biomass-smoke aerosols from the Balkan countries. To this respect, the MODIS data (AOD550 and FM) could not detect that dust event. In addition, Balis et al. (2004) showed that the mixing of the pollution layer with maritime aerosols obstructs the separation or even detection of dust in the lidar measurements, since the estimated optical properties are not representative for desert dust. From the whole experimental period, the back trajectories in 14 cases at both 1000 m and 4000 m come from Sahara, without satisfying the initial criteria (AOD550>0.3 and FM0.88. This depicts that the identification of the SD events is easier in rural environments with proximity to North Africa, such as Lampedusa (Pace et al., 2006; Meloni et al., 2007) and Crete (Kalivitis et al., 2007). Nevertheless, satellites provide a long-term dataset covering an extended area and, therefore, constitute a powerful tool for the atmospheric monitoring. It is become obvious that the combined use of different techniques and instrumentation is needed for the better and unbiased aerosol monitoring. Therefore, long-term satellite data, in conjunction with available lidar and AOD data from groundbased instruments, constitute a perfect combination to better evaluate the dust presence and aerosol optical properties. Taking into account the aforementioned difficulties, the present method for the identification of the SD events can derive reasonable results highlighting the wide use of satellites for aerosol monitoring. In the last two decades numerical models were developed for prognostic purposes, including simulations of emission, transport and deposition of Saharan dust aerosols in order to quantify their export to the North Atlantic and Mediterranean, as well as to study their effects on global climate. To this respect, the DREAM model is now capable of reproducing more realistic patterns of dust distributions due to an improved parameterization of land-surface conditions. In Southern Europe, several studies have investigated the respective contributions of various aerosol sources on PM10 levels. Aerosols in the Mediterranean have been a major concern, because of the vicinity of the Sahara desert. Furthermore, it has been shown that the total aerosol optical depth was higher in this area compared to that in Northern Europe (Matthias et al., 2004). Therefore, there have been conducted several studies on the impact of Saharan dust on air quality in Spain (Rodriguez, et al., 2001; Escudero et al., 2007), in Italy (Kishcha et al., 2005; Gobbi et al., 2007) or Greece (Grivas et al., 2008). These studies examined the impact of Saharan dust on surface PM concentrations and the violation of the European Community limits for air quality. It is mentioned, that the contribution of African dust flows to PM10 levels exceeding the EU threshold values has been estimated to be from 44% to 100% in Spain, with larger intensities for the Southern stations and the summer (Escudero et al., 2007). Similarly, the SD events in 2001 corresponded to 63-68% of the days exceeding of the PM10 limits in Rome (Gobbi et al., 2007). This issue will be a real challenge for further research in Athens combining the surface concentrations with the dust transport mechanisms over a period of several years.

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Figure 30. The dust plume over central Mediterranean during the dust event in the period 6-18 July 2002. This dust plume affects Athens during the period 8-11 July. It is transported from the northeast Sahara (Algeria) and is transported over central and eastern Mediterranean following an anticyclonic pathway.

The dust storms affecting Greece can be divided in two great categories, mainly depending on their source regions, regional meteorology, transport mechanisms, intensity, influence on the ground-level PM concentrations and association with clouds. More3 specifically, dust storms originated from Libya are transported northward throughout the atmospheric column, from near the surface to the middle of troposphere. Analyzing the satellite images for a long-time period (~6 years) we observed that these dust storms are more intense than those originated from the northwestern Africa (mainly Algeria, Mauritania and Mali), which are the most frequent in the central/eastern Mediterranean and south Europe, as several studies found (Coen et al., 2004; Papayannis et al., 2005; Meloni et al., 2007; 2008). Except of their intensity, other significant differences between the dust events coming over Greece from Libya and those from northwestern Sahara are 1) the regional and synoptic meteorology favoring their transport, 2) the seasonality, 3) their vertical extend, and 4) their association with clouds. More specifically, the dust events affecting Greece from southwestern directions, with a source in the desert regions of northwestern Africa, also cover a great part of the central Mediterranean, before reaching Greece; as a consequence, their intensity is decreased since the larger particles were deposited near the source. These events are more common in summer and are mainly driven by an

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anticyclone over northwestern Africa, which transport desert particles over central and eastern Mediterranean with air masses following an anticyclonic pathway. The duration of these dust events is rather large, especially in the central part of the Mediterranean, where Meloni et al. (2007) found durations of 13 consecutive days occurred in two episodes, in August 1999 and from 6 to 18 July 2002 (Fig. 30).

Figure 31. True-color image obtained from Aqua-MODIS sensor during the intense dust event on 17 April 2005 (11:40 UTC). The thick dust plume (as a yellow veil) is well depicted, being transported from Libya over the Eastern Mediterranean and specifically Greece, covering an extended area. The dust layer also traveled over the Balkan countries (not shown in the Figure). This yellow veil is evident in between the North African coast and Crete; then it becomes more vague as being diluted by the removal processes (mainly dry deposition).

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The latest was persistent over a large part of the Mediterranean also affecting Greece. These dust events, are mainly detected at an elevated layer into the atmosphere (Gobbi et al., 2001; Papayannis et al., 2005) having a clear signal in AI values (Alpert et al., 2004; Kaskaoutis et al., 2009). For this reason the deposition of the smaller and lighter dust particles still suspended on the air is not favored, enhancing the duration of the thin dust plumes. The stable weather and the nearly absence of precipitation over Mediterranean in the summer also favor the dust-aerosol residence time. However, these dust plumes are not as thick and visible from satellites as those coming from Libya. Since the dust particles within the boundary layer are easily deposited, while those at middle and upper atmosphere are not due to the reasons mentioned above, these dust events are mainly detected in the upper atmosphere. Similarly, Kalivitis et al. (2007) found that the dust events over Crete in summer are mainly transported in the upper atmosphere. Finally, dust events originated from northwestern Africa in summer are associated with sunny and cloudless conditions over the largest part of the Mediterranean and Greece. In contrast, the dust events originated from Libya affect only the eastern Mediterranean, as in the case on 17 April 2005 (Fig. 31). Furthermore, a different meteorological pattern is responsible for their exposure, mainly driven by a cyclone centered on Adriatic Sea and Italy and an extent trough reaching the Libyan coast. The result of this atmospheric circulation is a northward flow associated with strong surface and middle-troposphere winds carrying significant amount of dust over eastern Mediterranean and Greece (Kaskaoutis et al., 2008). The dust plume in these cases is transported throughout the atmospheric column, resulting in both large AOD in the vertical and increased surface PM concentrations. These dust events are more frequent in late winter (although rare) and early spring, since this period favors the depressions above Mediterranean. To this respect, Kalivitis et al. (2007) found that the vertical dust transport is more frequent in winter and spring over Crete, while a similar dust transport mechanism took place on 26 February 2001, as reported by Kaskaoutis et al. (2009). The duration of these dust events is 1-2 days, since the depressions favoring them are quickly moved and attenuated. They are associated with extent cloud cover over eastern Mediterranean and Greece, which is generated by the presence of the depression and the uplift of water vapor from the sea. The cloud cover usually obscures satellite and ground-based (e.g. sunphotometer) observations during these events, as was also the case of 17 April 2005. The dust plume is mainly transported below the clouds, at altitudes lower than 4 km, as also presented in Kaskaoutis et al. (2009). From all the above, the two different cases for the dust transport over Greece have become clearly established.

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Chapter 14

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CONCLUSIONS The need for a more complete understanding of the role of atmospheric dust and its impact on the environment has led to research of the causes for dust emission, variability, transport mechanisms and removal processes in space and time in the recent decades. North Africa is the largest dust-producing region in the world with dust emissions being highly variable on time scales from diurnal to multiannual. The development of satellite-derived products of global dust distributions has improved our understanding of dust-source regions and transport pathways in the recent years. This chapter focused on the SD events affecting the Eastern Mediterranean and coastal Greece. The analysis was performed for the urban Athens area in the period of February 2000 to December 2005, using MODIS (AOD550 and FM) products, TOMS-AI values and model (HYSPLIT and DREAM) results. From the experimental period the cases corresponding to coarse-mode (possibly desert-dust) particles were discriminated using appropriate threshold values (AOD550>0.3 and FM