American Journal of Remote Sensing 2014; 2(4): 20-29 Published online October 20, 2014 (http://www.sciencepublishinggroup.com/j/ajrs) doi: 10.11648/j.ajrs.20140204.11 ISSN: 2328-5788 (Print); ISSN: 2328-580X (Online) The seasonal variability of aerosol optical depth over Bangladesh based on satellite data and HYSPLIT model Mainul Islam Mamun*, Monirul Islam, Pallab Kumar Mondol Department of Applied Physics and Electronic Engineering, University of Rajshahi, Rajshahi 6205, Bangladesh Email address: mainul_apee@yahoo.com (M. I. Mamun), rajib_apee@yahoo.com (M. Islam), pallabapee_ru@yahoo.com (P. K. Mondol) To cite this article: Mainul Islam Mamun, Monirul Islam, Pallab Kumar Mondol. The Seasonal Variability of Aerosol Optical Depth over Bangladesh Based on Satellite Data and HYSPLIT Model. American Journal of Remote Sensing. Vol. 2, No. 4, 2014, pp. 20-29. doi: 10.11648/j.ajrs.20140204.11 Abstract: Atmospheric aerosols have constituted a crucial environmental and climate issue. There is lack of studies dealing with monitoring of aerosol patterns over Bangladesh. This review attempts to analyze the seasonal variations in AOD over Bangladesh during the period 2002-2011, using MODerate resolution Imaging Spectroradiometer (MODIS) Level 3 remote sensing data. A Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to generate a backward trajectory in order to identify the origins of air masses, with the aim of understanding the spatio-temporal variability in aerosol concentration. Seasonal variations during the last decade show maximum AOD values during pre-monsoon season; while minimum AOD during post-monsoon. An evidence of decadal decreasing trend in AOD is found during monsoon season while all other seasons show increasing trends. High spatio-temporal variations of AOD are observed during different seasons in 2010. Back trajectory analysis indicates that Bangladesh is mainly affected by the pollutants and desert dust of India combining with sea salt particles blown from the Arabian Sea. The air masses are arriving at lower altitudes (500m, 1500m) mainly from western India and Indian subcontinent but at higher altitude (2500m) especially in winter season it comes from far western regions, such as Europe and various sub-Saharan regions of Africa. Different flow patterns of air masses during postmonsoon are observed that the air masses are arriving from southeast in the direction; in case of Sylhet division the sources of air masses are in the coastal regions of Thailand, border regions of Myanmar and China. These studies become helpful to understand the nature and influence of aerosols on seasonal dynamics over Bangladesh. Keywords: Aerosol Optical Depth, MODIS, Seasonal Variations, HYSPLIT, Bangladesh 1. Introduction Atmospheric aerosols have many impacts on global climatic system. Aerosols attenuate the solar radiation to reach in earth surface by scattering and absorbing the radiation, altering the solar spectrum, affecting the earth’s energy budget, influencing the cloud properties, hydrological cycle and also human health [9]. Earth’s atmosphere is changing due to the variations of atmospheric aerosol load, greenhouse gases, solar radiation, and land surface properties [18]. Aerosols are suspended liquid or solid particles in air. They exhibit a wide range of compositions and shapes depending on the origins and associated atmospheric processes. Aerosol processes are very complex and highly inhomogeneous in their distributions. As a result accurately modeling of anthropogenic aerosols and their effects remains a challenge till to present. Mass concentration quantification by an optical measure known aerosol optical depth (AOD) is usually used to estimate the aerosol loading or amount in the atmosphere [27]. Various scientific researchers have been recognized that atmospheric aerosol is a key parameter in climate change studies especially over South Asia. Atmospheric temperature fluctuations [15], [8] radiative forcing (e.g. [22]), rainfall pattern changes (e.g. [19], [25]), intensive tropical cyclone (e.g. [4]) and desertification (e.g. [20]) are examined by aerosol studies. Aerosols exhibit high spatio-temporal variations which influence the cloud properties and precipitation processes. These indirect effects are recognized by several literatures on regional and global scale [16], [17]. Satellite data is important and useful for the study about air quality research [6], [12]. Satellite retrievals of column aerosol optical depth (AOD) are a cost effective way to monitor and study aerosols distribution and effects on climate [3]. [15] reported that for mapping the distribution and properties of aerosols satellite data has tremendous potential. Due to sparse of ground measurements in many regions of the world satellite data is the only way to monitoring aerosol loads and aerosol properties in a regional 21 Mainul Islam et al.: The Seasonal Variability of Aerosol Optical Depth over Bangladesh Based on Satellite Data and HYSPLIT Model and global scale. The USA’s National Oceanic and Atmospheric Administration (NOAA) HYSPLIT model can indirectly describe and map the spatio-temporal temporal variations of aerosols. Aerosol concentration in Asia is increasing over the industrial and urban both areas due to growing populations, increasing urbanization and industrialization, demands for energy, changes in land use, increasing motorized traffic, increasing temperature and increasing other kinds of pollution. Different studies in India show increasing trend of aerosol optical depth which reflects its polluted environment as increasing anthropogenic aerosols. [14] reported that spatial and temporal variations of aerosol load, optical properties and their climate implications due to large diversity in population density, regional emissions, land use and seasonally-changed air masses. [23] analyzed the seasonal AOD variability over Rajkot, in India, found lower values in winter and higher values in summer. [19] also found the maximum AOD in the summer season than in the winter season over Indo-Gangetic plain. Similarly, [1] found higher AOD values in summer and lower values in winter for various cities in Pakistan. But a detailed analysis of distribution of AOD over South Asia basically on monthly and seasonally basis are rather sparer. To understand the properties and impacts of aerosols monthly and diurnal studies are needed. The objective of this study is to investigate the seasonal variability of AOD over Bangladesh during the period 20022011 using MODIS level-3 data. A detailed observation in each season is done in the year of 2010. HYSPLIT model is also used to understand the spatial and temporal variability in aerosol load for seven divisions in Bangladesh of different seasons. 2. Methodology 2.1. Study Area Bangladesh is a low-lying, riverine country located in South Asia with 710 km coastline largely marshy jungle on the northern littoral of the Bay of Bengal. Geographically Bangladesh is formed by the Ganges delta which is constructed by the confluence of the Ganges (Padma), Meghna and Brahmaputra (Jamuna) rivers and their tributaries. The west, north, and east of Bangladesh are bordered with India by a 4,095-kilometer land frontier and the southeast is bordered with Myanmar by a short land and water frontier (193 km) (Fig. 1). Four distinct seasons are considered in the study area from climatic point of view. Firstly the dry winter season from December to February, secondly the pre monsoon hot summer from March to April, thirdly the monsoon or rainy season from June to September and fourthly the post monsoon season which lasts from October to November [24]. Wind velocity is higher in summer than in winter. The average temperature everywhere is about 25°C. Mean monthly temperatures range between 18°C in January and 30°C in April-May. Maximum summer temperature ranges between 38 °C and 41 °C. April is the hottest month in most parts of the country and January is the coolest month. Significant differences in seasonal temperatures occur across the country. Heavy rainfall is characteristic of Bangladesh as a result flood occurred every year. The rainy season is characterized by southerly or southwesterly winds, very high humidity, and heavy rainfall and long consecutive days of rainfall. About 80 % of total rainfall occurs during the monsoon season. Fig 1. Geographical location of Bangladesh. 2.2. Dataset and Analyses Aerosol optical depth (AOD) can be measured by both in situ and remote sensing measurement systems. Here the satellite remote sensing measurement is used. To study the large spatial and temporal heterogeneities of aerosol distributions satellite remote sensing is essential. The MODerate resolution Imaging Spectroradiometer (MODIS) AOD datasets are used. The MODIS instruments onboard NASA’s Terra and Aqua satellites which launched in December 1999 and in May 2002 respectively. It has 36 spectral channels to provide information about atmosphere, land and oceanic conditions. MODIS provides a continuous data collection which is important for understanding both long- and short-term change in the global environment. Aerosol retrieval is different over land [11] from over oceans [26]. The MODIS provides observations at moderate spatial (250m to1 km) and temporal (1 to 2 days) resolutions using different portions of the electromagnetic spectrum. For this investigation MODIS Terra Level-3 Level data is used. A 7-day air-mass back trajectory is made using the Hybrid Single Particle Lagrangian Intregrated Trajectory (HYSPLIT) model to reveal the sources of aerosols over Bangladesh of seven different divisions with four representative seasons. The FNL dataset which is reprocessed from the National Oceanic and Atmospheric Administration (NOAA) is used as the meteorological input for the trajectory model. The user can calculate up to 40 forward or backward trajectories at different altitudes with a horizontal grid of 1.5° × 1.5° and a resolution of 500 × 500m using the HYSPLIT model. In this study, the backward trajectories are calculated at 500m, 1500m, and 2500m heights above ground level to investigate the origin of air masses bringing particular matters (such as desert dust, sea salt) into the various divisions of Bangladesh during different seasons. American Journal of Remote Sensing 2014; 2(4): 20-29 3. Result and Discussions 3.1. Seasonal variations in AOD Fig. 2 shows the spatial distribution of seasonal mean AOD over Bangladesh in 2010, for four representative seasons namely pre-monsoon (March-May), monsoon (JuneSeptember), post-monsoon (October-November) and winter (December-February) which reveals high spatial variability. The seasonality of AOD exhibits the patterns of higher values during pre-monsoon & monsoon seasons whereas lower values during post-monsoon & winter seasons. Fig. 3 shows the temporal variations of seasonal AOD by time series plots over Bangladesh during 2010. The results show that at the beginning of pre-monsoon season the AOD is increasing then from July AOD is rapidly decreasing and this decreasing trend remains constant throughout the whole monsoon season. Again from starting of post-monsoon season the AOD is increasing rapidly and this increasing trend follows the winter season. 3.1.1. Variations in AOD During Pre–Monsoon Season In pre-monsoon (March-May) the spatial distribution of AOD is presenting deviations from region to region as shown in Fig. 2a. The northern, southern and eastern parts show higher AOD distributions during pre-monsoon season. It is found that the AOD starts to increase rapidly from the beginning of pre-monsoon (March), reaching its maximum in June as shown in Fig. 3a. The summer increase could be due to high temperature and high wind velocities producing larger quantities of wind-driven dust particles [1]. During pre-monsoon season also the water soluble aerosols grow hygroscopically in the presence of water vapor causes higher AOD values [1]. A higher concentration of water vapor in pre-monsoon season leads to a higher AOD because water vapor and AOD are directly related to each other’s [1], [23]. The increasing AOD also indicate to increased emissions of aerosols from biomass burning in Bangladesh, as the other source of aerosols which must be examined [10]. Dust activity is maximum during May-July. Dust frequency and intensity during pre-monsoon depend on various meteorological phenomenons such as rainfall amount, soil moisture, wind speed and wind direction etc. [8]. 3.1.2. Variations in AOD During Monsoon Season The strong gradient in AOD distribution is shown during monsoon season over Bangladesh in 2010 (Fig. 2b). The AOD concentration is increasing from very low to very high from northeastern part to southwestern part of the country. Khulna, Barisal and the coastal areas are shown highest AOD distribution in monsoon period; this may be due to a high concentration of water vapors and sea salt spray. From monsoonal time series plot it is shown that the high AOD value is decreased rapidly from July and reached its minimum value (~0.1) in October. This decrease just before the winter season could be due to cloud scavenging and rain washout process [23]. Bangladesh and northeast India is affected by monsoon at the end of June, and as a consequence, the MODIS retrievals in July and August are limited due to extensive cloudiness. So, there are possibilities of lack of data over some times over specific 22 pixels in this area leading to the observed complicated pattern as regards the AOD variations [10]. 3.1.3. Variations in AOD During Post- Monsoon Season In post-monsoon, spatial distribution shows comparatively lower values of AOD distribution than other seasons over Bangladesh while the south-western region (Khulna and Barisal) shows higher AOD distribution than other regions. As this area are affected by sea salt and marine aerosols. The eastern regions especially Chittagong and Sylhet divisions show very lower AOD distribution. From the AOD time series graph (Fig. 3c) it is shown that AOD is rapidly increasing from September, reaching a maximum AOD value of ~1.00 in November. This increasing manner may be due to local activities which are started from October [10]. 3.1.4. Variations of AOD During Winter Season Winter season shows high aerosol loading over Bangladesh in 2010 except the Chittagong and Sylhet divisions, as shown in Fig. 2d. The spatial distribution shows a strong gradient in AOD from very high to low from west to east. From Fig. 3d the winter period clearly reveals the lowest variability of AOD in 2010 over Bangladesh among all seasons. Note that some area in northwestern Rajshahi division shows extremely high AOD distributions in winter. Dense fog is a common activity in Bangladesh during winter which may be the reason for this peak AOD. Dense fog causes enormous economic loss and also the daily life become stand still. [10] also found a pronounced eastwards increasing AOD over Eastern IGP during winter season. [5] reported that “the Bihar pollution pool” strongly influencing the aerosol load & properties over the northern Bay of Bengal. Again dryer weather and lower humidity causes a lower AOD values in winter season than summer season [1]. 3.1.5. Seasonal Mean Variations of AOD Seasonal mean variations and trends of AOD are also analyzed over Bangladesh for a period of ten years (20022011) as shown in Fig. 4. The highest AOD level is observed in pre-monsoon and the lowest AOD level in post-monsoon. The annual mean AOD in summer is 0.61 and in post monsoon it is 0.33. Where winter season and monsoon season show medium to high AOD levels. It is also evident that pre-monsoon AODs are higher than those for all other seasons in the year, followed in order by winter, monsoon and post-monsoon. Our analysis shows that the AOD trends since 2002 are increasing in pre-monsoon, post-monsoon and winter seasons but decreasing in monsoon season. It is also shows that the AOD trend is rapidly increasing in winter than all other seasons, ordered by post-monsoon and pre-monsoon. The rapid increase of AOD in winter may be due to increase in fog and local activities with conjunction of anthropogenic aerosols. The decreasing trend of AOD in monsoon during the last decade indicates that the rainfall amounts and patterns may be changing as the rainy season shifts backward. It is also found that AOD values varied between low values in post-monsoon and high values in pre-monsoon, where the pattern values in winter and monsoon are quite similar to each other. During pre-monsoon high temperature plays a vital role in heating lifting loose material from soil and also due to higher wind speed consequently higher AOD 23 Mainul Islam et al.: The Seasonal Variability of Aerosol Optical Depth over Bangladesh Based on Satellite Data and HYSPLIT Model values observed. Rain washout processes reduce the AOD values in post-monsoon season [1]. Anthropogenic aerosols are the major type over south Asia as they contribute about 70 – 80% to the total AOD [7]. They also the dominant type both over urban areas and downwind Oceanic areas [21]. In rural and agricultural areas the fine mode aerosols mainly originate from burning of bio-fuels, while in urban areas they are originating from fossil-fuel combustions [10]. (d) Winter Fig 2. AOD distribution images of Terra-MODIS over Bangladesh during (a) pre-monsoon, (b) monsoon (c) post-monsoon and (d) winter seasons in 2010. (a) Pre-monsoon (b) Monsoon (c) Post-monsoon American Journal of Remote Sensing 2014; 2(4): 20-29 24 4. Influence of Air Masses on AOD, Using Back Trajectory Analysis Fig 3. Seasonal time series plots of AOD during (a) pre-monsoon, (b) monsoon (c) post-monsoon and (d) winter seasons over Bangladesh for the year 2010. Seven day back trajectory analyses based on the NOAA HYSPLIT model are studied in order to understand the sources of the air masses in the study regions. The study regions are the seven divisions of Bangladesh, for winter, pre-monsoon, monsoon and post-monsoon post seasons. These trajectories are computed at several altitudes (2500m, 1500m, and 500m). The trajectories for 08 December 2009, 29 May 2010, 22 July 2010 and 15 October 2010 are shown in Fig. 5. These trajectories are only included here as a representative because similar trajectories found for other time period. Fig. 5 reveals that most of the back trajectories identified air masses flow originating either from Arabian Sea (extremely), Bay of Bengal, the great Thar Desert of India, Pakistani Desert (Cholistan), the Sahara and sub-Saharan regions, Libya, various western regions of India towards north-south, Africa & Europe also from Atlantic Ocean and sometimes from south-eastern regions such as China, Myanmar, Luzon Sea and that consequently a significant increase in AOD over this areas could be observed. In general the air masses from the western land mass and from the Arabian Sea are responsible for the increase in AOD values over Bangladesh. Fig 4. Annual-mean seasonal variations and trends of AOD over Bangladesh for the period 2002-2011. Barisal 25 Mainul Islam et al.: The Seasonal Variability of Aerosol Optical Depth over Bangladesh Based on Satellite Data and HYSPLIT Model During winter (08 December 2009) back trajectories at several areas reveal that the trajectories are from the west and north-west in the direction. For 500m and 1500m altitudes the sources of air mass loading mainly are west Indian and east Pakistani deserts and the middle & western regions of India, all over the seven divisions. But in Khulna and Sylhet divisions at 1500m altitude a different air mass loading are observed. The sources are Red Sea for Khulna and Bay of Bengal for Sylhet. Where in 2500m altitude the air masses are loading from far western regions, such as Europe and various sub-Saharan region of Africa such as Poland, Estonia, Libya, Sahara desert etc. In Sylhet this source is Saudi Arab and in Rangpur this source is Persian Gulf. Fig. 5 shows that, in pre-monsoon and monsoon seasons the highest AOD values in Bangladesh occurred due to Sea salt bringing from the Arabian Sea via Bay of Bengal through southwest direction. This highest AOD value is observed in Bangladesh in most of the divisions. Only in northern divisions Rajshahi and Rangpur at 2500m altitude in summer other type of air masses are loading with conjunction of Arabian Sea salt. Such as north Atlantic Ocean salt and air masses from Nepal (close to Indian border) are loading in Rajshahi and Rangpur respectively. Again in Chittagong division at 1500m altitude the air masses are loading from Goa of India (coastal region). During post-monsoon (15 October 2010) verities are observed on air masses loading. Fig. 5 reveals that air masses loading are observed from both southeast and southwest direction in Bangladesh. Such as Arabian Sea salt, anthropogenic air masses of different regions in India, China, Myanmar, Thailand, Luzon Sea etc. Dhaka and Sylhet divisions are shown highest differences of air mass loading among all of the divisions. The sources in Dhaka are Myanmar, coastal regions of Thailand and Arabian Sea and the sources in Sylhet are southwestern border region of China and Myanmar, costal region of Thailand, Bay of Bengal and Luzon Sea. Therefore the air mass back trajectories indicate that in pre-monsoon, monsoon, post-monsoon post and winter the sources of air masses loading are different. For example, winters air masses are reaching in Bangladesh have traveled long distances from northwest, while the other seasonal air masses have traveled shorter distances. Therefore it seems likely that the air masses spent more time over land during the summer than during the winter. During the summer months it would explain because in this time the higher levels of AOD are observed. This is also due to the uneven distribution of solar flax reaching the earth’s surface. The higher latitudes air is warmer than at lower latitudes. The tropical air which rises vertically moves towards the poles at high altitudes while the cooler polar air moves towards the equator at lower levels. The air presser consequently increases at equatorial latitudes due to the outflow of air mass and most equatorial air moves towards the poles under this pressure gradient. Since over the region of Bangladesh the air moves away from the equator in northerly direction at high altitudes and the coriolis force has a significant effect, south and south-westerly winds dominate [1]. These variations of sources, directions and distances of air mass loading may be due to various metrological parameters such as wind speed, wind direction, temperature, pressure etc. It is clear from the back trajectories that the air masses have been influenced by the combine effects effect of land, industries and the Ocean and that this has resulted in increased AOD values over Bangladesh. Chittagong American Journal of Remote Sensing 2014; 2(4): 20-29 Dhaka Khulna 26 27 Mainul Islam et al.: The Seasonal Variability of Aerosol Optical Depth over Bangladesh Based on Satellite Data and HYSPLIT Model Rajshahi Rangpur American Journal of Remote Sensing 2014; 2(4): 20-29 28 Sylhet Fig 5. Seven-day back trajectories for 7 divisions in Bangladesh for 8 Dec 2009, 29 May 2010, 22 Jul 2010 and 15 Oct 2010. 5. Conclusion The aim of this study is to analysis the seasonal AOD variations over Bangladesh based on Terra-MODIS Terra remote sensing data during the last decade (2002-2011) (2002 and to develop an understanding of the impact of aerosols on climate system. Aerosol air masses loading are identified by a backward trajectory with the help of a Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The seasonal mean AOD variations and trends are estimated for a period of 10 years (2002-2011), also the seasonal AOD variations and trends for one specific year of 2010 are examined over Bangladesh. Seasonal analyses report that the highest AODs are found in pre-monsoon monsoon season and minimum AODs are found in post-monsoon. monsoon. These high AODs in pre-monsoon are interpreted as being a result of higher temperature, higher humidity and lots of sea salt particles blown from Arabian Sea and Bay of Bengal, where low AODs in post-monsoon due to a result of clean and cool environment after rainy season by rain washout processes. Seasonal variations in 2010 present high spatial variations in each season over Bangladesh. Examination of these variations using back trajectory analysis reveal that air masses from Indian deserts and sub-Sahara Saharan regions, sea particles from Arabian Sea along with Indian pollutants (industrial emissions, locally derived dust and biomass burning) are the main sources of aerosol loading in Bangladesh. These air masses cause different AOD loading in various divisions, and overall influence in Bangladesh. This study has some limitations as there is no ground-based data and it is a newer study in Bangladesh. The comments of this research over Bangladesh may be less accurate as this satellite AOD retrievals don’t compare with ground based data also with other research projects. It is therefore recommends that further much more researches are needed about aerosols to achieve a better understanding of spatiotemporal variations in aerosols and their various atmospheric impacts. On the whole, this study in Bangladesh will prove useful in the assessments of spatio-temporal variations in aerosols on regional and global climate impact due to aerosols. Acknowledgements MODIS data used in this study were developed and maintained by the GES-DISC DISC of NASA is gratefully acknowledged with thanks. NOAA Air Resources Laboratory (ARL) is also gratefully acknowledged for providing the HYSPLIT model to analyze the Back Trajectories. Research Highlights Seasonal variations of AOD are examined using MODIS data and the HYSPLIT model. 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