ArticlePDF Available

Identification and Apportionment of Sources from Air Particulate Matter at Urban Environments in Bangladesh

Authors:

Figures

Content may be subject to copyright.
A preview of the PDF is not available
... The abundance and composition of particulate matter in the urban environment are widely studied in Bangladesh (Begum et al., 2014a;Islam et al., 2015;Rana and Khan, 2020;Rouf et al., 2011). In Dhaka city, brick kilns, motor vehicles, fugitive lead, road dust, soil dust and sea salt have been found to be mostly responsible for the high concentration of PM (Begum et al., 2014a). ...
... The abundance and composition of particulate matter in the urban environment are widely studied in Bangladesh (Begum et al., 2014a;Islam et al., 2015;Rana and Khan, 2020;Rouf et al., 2011). In Dhaka city, brick kilns, motor vehicles, fugitive lead, road dust, soil dust and sea salt have been found to be mostly responsible for the high concentration of PM (Begum et al., 2014a). Transboundary impacts on PM was also investigated (Begum, 2016). ...
... A few studies have been conducted regarding PM variation in Bangladesh. A study reported that brick kiln, motor vehicle, fugitive lead, road dust, soil dust, sea salt are the major sources for PM dispersion (Begum et al., 2014a). Rajshahi, Dhaka, Khulna and Chattogram are observed as the most polluted areas in Bangladesh. ...
Thesis
As the cities in Bangladesh get more industrialized, more development projects are undertaken, making the surrounding air more polluted. The air pollution in major cities of Bangladesh has become quite acute in recent years. Among all components, PM2.5 is considered to be one of the major harmful elements. Due to its tiny particle size, it can enter the bloodstreams of respiratory tracts and even can cause death.Therefore, it is crucially needed to understand the particulate matter characteristics, to bring it down to a moderate level. Since, studies showed that, meteorology has significant influence on PM variation, approach has been taken in this study to understand the influence of meteorology on PM variation over the region of Bangladesh. Air quality and meteorological data from Department of Environment (DoE) for the period of 2013-2018 for eleven stations (CAMSs) of Bangladesh are collected. Among eleven existing stations, we perform analysis on eight available stations and the remaining three are discarded due to theirpoor-quality data. We perform annual and seasonal cross correlation analysis to identify major influential parameters on PM variation at different times of the year. We also perform multiple linear regression analysis (MLR) using interaction terms to understand the combined effect of meteorological parameters on PM. Annual cross correlation analysis shows that, wind speed, temperature,solar radiation and relative humidity are effective parameters for PM2.5 and wind speed, relative humidity,rainfall duration andrainfall are effective parameters for PM10variation. Wind speed, relative humidity,temperature, rainfall duration and rainfall amount show negative correlation with PM and solar radiationshow positive correlation with PM. Seasonal analysis shows that, low wind speed causes PM accumulation in winter and post-monsoon, whereas, high wind speed causesPM dilution in pre-monsoon and monsoon. Change in temperature can change boundary layer height and subsequently alter ambient PM. This effect of temperature is found to be effective throughout the year. However, bioaerosol formation in presence of temperature is observed during monsoon. Relative humidity is inversely correlated with PM and the correlation is highest in monsoon for majority of thestations. However, due to its location in coastal area and intrusion of sea aerosol,Chattogram shows weak correlation between relative humidity and PM in monsoon. Solar radiationshows positive correlation with PM throughout the year. The duration of rainfallis found to be more effective in PM removal compared to amount of rainfall. Highest negative correlation between precipitation and PM is observed inSylhet, since it is the region of highest consistent rainfall in Bangladesh. MLR analysis showed that local meteorology could explain up to 17% to 78% PM variation in major cities of Bangladesh. The interaction between temperature, relative humidity and wind speed and their combined effect are found to have major influence on PM for most of the stations. This study gives a comprehensive idea on how much influence meteorological parameters can have on PM variation in different cities in Bangladesh for different seasons. Findings of this study are expected to be helpful in decision making for adoption of pollution control measures and evaluating different climate change mitigation and adaptation approaches.
... Intensity and sources of air pollutants vary from place to place and season to season. Therefore, identification of sources of air pollutants is very much needed to control the pollution [1]. ...
... By using HYSPLIT-4, the theory of drawing backward trajectories is based on the integration of the air mass location with respect to time. Using the wind, air mass is transported, its passive transport can be measured according to Begum et al. [1] by evaluating the three-dimensional means of velocity vector when the particles are in the primary position P(t) and the first estimated position P' (t + dt). ...
... Begum et al. [1] indicated the vehicular emission as one of the major sources of pollution in Bangladesh. The increasing number of vehicle movement in Khulna city may cause the dominancy of vehicle emissions among different monitoring locations. ...
Article
Full-text available
Air pollution is a great concern in urban areas of Bangladesh because of the emissions from various anthropogenic sources. Identification of sources of respective air pollutants is needed to control the affluence of pollution. The aim of this study was to ascertain the possible sources which are polluting the airshed of Khulna city. This study performed qualitative source apportionment and investigated the long-range transport of air pollutants at different locations of the city. Nine locations were selected to investigate the sources of pollutants through the observation-identification method. Vehicle emission was found as a dominant source of air pollutants at almost all the observed locations. The average ratio of PM 2.5 /PM 10 was found as 0.66 which varied from 0.38 to 0.88 and average PM 1.0 /PM 10 was found as 0.35 varied from 0.16 to 0.44. These ratios revealed the dominancy of fine particles as on average 66% of PM 2.5 and 35% of PM 1.0 contributed to the total concentration of PM 10. The extensive aspect of fine particles revealed the greater contribution of anthropogenic sources to the air of Khulna city as around 66% of fine particles were found to be contributed to the concentration of PM 10. This study also investigated the long-range transport of air pollutants for nine monitoring locations in the city. From the backward trajectory analysis, it was concluded that trajectories followed two paths; one is the west Bengal path and another is the Bay of Bengal path. The higher concentration of all air pollutants was found when the trajectories followed the west Bengal path which indicated the contribution of industrial activities in neighboring India, China, and Bhutan to the concentrations of air pollutants behind the perimeter of Bangladesh.
... Ambient PM 10 denotes the particleswith an aerodynamic diameter of ≤10 µm and PM 2.5 denotes ≤2.5 µm. These fine and coarse particles originate from biomass and fossil fuel burning, brick kilns, motorized vehicles, soil dust, pollen, sea spray etc. [5]. These particles are inhaled by living being and suffered from acute and chronic diseases [6]. ...
... The previous studies focused on characterization of average annual atmospheric pollutants for different locations whereas some were conducted during the dry season or only one season and specific source oriented (e.g., baby taxy ban, condensed natural gas introduction) spatiotemporal and diurnal variations with different time in Dhaka city [5,[20][21][22][23]. This study has analyzed the updated data of both PM 2.5 and PM 10 concentration in Dhaka city from 2013-2018 in relation to meteorological parameters. ...
Article
Full-text available
The capital Dhaka of Bangladesh is one of the most densely populated and air polluted cities in the world. This study is aimed to assess the trend of Particulate Matter (PM2.5 and PM10) from 2013 to 2018 in relation to meteorological parameters. PM data were collected from the Continuous Air Monitoring Station (CAMS) at Darus Salam point in Dhaka city. CAMS gather air samples through beta gauge instrument which measures the volume of gas extracted through the stack/duct and calculates mass concentration. In the present study, PM2.5 was 54 % of that of PM10 which is fine particulate matter. PM2.5 and PM10 had the lowest concentration in the month of July due to the highest rainfall rate whereas it was highest in the months of January and December. In addition, annual average concentration of PM2.5 and PM10 is observed to be 5-6 times higher than Bangladesh National Ambient Air Quality Standard (BNAAQS) while higher PM concentrations were observed in winter seasons. This study found significantly inverse association between ground-level PM and meteorological parameters in Dhaka city. Air pollution is deteriorating rapidly in Dhaka city and it is high time to implement the Clean Air Act urgently to reduce such destruction.
... Al, Ca and Fe are elements linked with crustal sources ( Begum et al., 2004 ) probably unpaved roads at rural traffic sites which is the main source of these tracer comparisons to other sites. Al, Ca is also emitted from Brick Klin (Begum et al., 2014 ) which is situated 9 km far away from the rural site (Iradatnagar) and is the key contributor for metal sources. Results revealed a similar trend for size fraction PM 1.0-0.5 excepting Ba and Mn which were higher at Iradatnagar. ...
Article
Full-text available
Air quality at two traffic junctions representing GLA indicating pollution at highway and Iradatnagar indicating rural pollution was evaluated in Uttar Pradesh, India. The present study aimed to determine the concentration of size-segregated PM with the characterization of metals at different traffic junctions i.e. (Agra and Mathura). In the study, PM2.5-1.0 and PM1.0-0.5 were measured with the help of Cascade Sioutas Impactor during the study period December to January 2018. The size fraction of PM2.5-1.0 was found to be higher at GLA (350.92µg/m³) followed by Iradatnagar (329.12µg/m³), whereas the average value of size fraction of PM1.0-0.5 was found higher at Iradatnagar (341.01µg/m³) in comparison with GLA (313.47µg/m³) respectively. The average PM2.5 concentration in all the sampling sites was found to be 7-8 times higher when compared with the National Ambient Air Quality Standards (60µg/m³) (NAAQS, India). Twelve metals viz. (Al, Ba, Ca, Cd, Cr, Cu, Fe, Mg, Mn, Ni, Pb, and Zn) were subsequently determined by ICP-OES. Al, Ba, Ca, and Mg, were found in higher concentrations in comparison with other metals. Source apportionment of metals was done by PCA (Principal Component Analysis) which shows that metal loading of Al, Ca, Cr, Cu, Fe, and Ni was influenced by vehicular emission with 33.6 % constitutes of the total variance. Higher bioavaiablity was observed for PM2.5-1.0 (5.12-6.46%) and least was found for PM1.0-0.5 (4.56-7.055%). For health risk estimation, the average value of HQs was found higher for PM1.0-0.5 size fraction. HQ values were recorded higher for GLA (7.95) for PM2.5-1.0 and (9.50) for PM1.0-0.5 fraction. Overall, the observed HQs values far exceeded the acceptable level. Average value (1×10–⁶) of carcinogenic risk factor was found higher for an adult and child respectively.
... The largest source in Rajshahi is brick kilns (40.2%) with a substantial contribution from biomass burning (Begum et al. 2014) including transboundary pollution from across the IGP (Ommi et al. 2017). Lockdown resulted in the reduction of automobile operation, local brick making, and some other industries producing an expected reduction in PM. ...
Article
An integrated approach was used to estimate the number of COVID-19 patients related to air quality and meteorological phenomena. Additionally, the air quality during pre-lockdown, lockdown, and post-lockdown stages of the COVID-19 pandemic was assessed to determine the effect of the infection containment measures taken in Bangladesh during the pandemic. The air quality was assessed based on measurements of nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), carbon monoxide (CO), black carbon, particulate matter (PM2.5 and PM10), and aerosol optical depth. Time-averaged maps of these parameters have been generated from NASA’s (National Aeronautics and Space Administration) website. Values of these parameters have also been collected from a continuous air monitoring station (CAMS) located in Bangladesh’s north-western city Rajshahi. The comparison shows that lockdown during the pandemic has brought significant improvements in air quality. However, the improvement was not sustained, since rapid increases in the air pollutant concentrations were observed in the post-lockdown period. Furthermore, Pearson correlation coefficients between each air quality variable and the daily new COVID-19 case rates were calculated. Different meteorological variables during the same time periods were determined to observe the variation in Rajshahi city. Relationships of these variables with the case rates were also established. Additionally, statistical analyses of the obtained data have been conducted for the measured variables using the Kruskal–Wallis test to assess the differences in the observed data among the pre-lockdown, lockdown, and post-lockdown periods. Dunn’s “Q” test was employed to test if the variables showed significance statistical difference during the Kruskal–Wallis test for pairwise comparisons. From the study, it has been observed that both meteorological variables and air quality parameters have significant relationship with daily new COVID-19 case rates. Both positive and negative associations of these parameters with the COVID-19 case rates have been observed. Very high air pollution has been observed in the post-lockdown period. Thus, it is recommended that appropriate authorities undertake corrective measures to protect the environment in cities with large populations. This study provides guidance for decision makers and health officials for future research and potentially reducing the spread of COVID-19.
... Our source apportioned analysis indicated that the air pollution during monsoon season in Dhaka is dominated by fossil fuel combustion-related sources (e.g., traffic), whereas the nonmonsoon period PM 2.5 air pollution was more dominated by biomass burning (e.g., crop burning) and other sources (which include soil dust, road dust, construction dust, industrial emissions, and incinerators emissions) (9,31). We also found that PM 2.5 emitted from traffic was associated with the largest and statistically strongest observed association during the monsoon season. ...
Article
Full-text available
Rationale: To date, there is no published local epidemiological evidence documenting the respiratory health effects of source specific air pollution in South Asia, where PM2.5 composition is different from past studies. Differences include more biomass and residue crop-burning emissions, which may have differing health implications. Objectives: We assessed PM2.5 associations with respiratory emergency department (ED) visits in a biomass-burning dominated high pollution region, and evaluated their variability by pollution source and composition. Methods: Time-series regression modeling was applied to daily ED visits from January 2014 through December 2017. Air pollutant effect sizes were estimated after addressing long-term trends and seasonality, day-of-week, holidays, relative humidity, ambient temperature, and the effect modification by season, age, and sex. Results: PM2.5 yielded a significant association with increased respiratory ED visits [0.84% (95% CI: 0.33%, 1.35%)] per 10 μg/m3 increase. The PM2.5 health effect size varied with season, the highest being during monsoon season, when fossil-fuel combustion sources dominated exposures. Results from a source-specific health effect analysis was also consistent with fossil-fuel PM2.5 having a larger effect size per 10 μg/m3 than PM2.5 from other sources [fossil-fuel PM2.5: 2.79% (0.33% to 5.31%), biomass-burning PM2.5: 1.27% (0% to 2.54%), and other-PM2.5: 0.95% (0.06% to 1.85%)]. Age-specific associations varied, with children and older adults being disproportionately affected by the air pollution, especially by the combustion-related particles. Conclusions: This study provided novel and important evidence that respiratory health in Dhaka is significantly affected by particle air pollution, with a greater health impact by fossil-fuel combustion derived PM2.5.
... Cause of upsurge in pollution level in Dhaka is due to unplanned urbanization, industrialization, and motorization. Brick kiln operations in and around Dhaka are also liable for a large share of Dhaka's polluted air, which accounts for 58% of total fine particulate matter PM 2.5 pollution, followed by motor vehicles (10.4%), road dust (7.70%), fugitive Pb (7.63%), soil dust (7.57%), biomass burning (7.37%) and sea salt (1.33%) [20]. DoE [12] observed, concentration level of PM 2.5 and PM 10 at different locations of Bangladesh were 56.22-210.45μg/m 3 and 163.41-316.31μg/m 3 respectively; AQI impression was unhealthy to extremely unhealthy along with few good, moderate and caution; most frequent responsible pollutant was PM 2.5 . ...
Article
Full-text available
Air is an essential element of the earth’s atmosphere. Modern civilization and industrialization have rapidly changed the world and also uplifted the rate of different environmental pollutions. The serious consequences of air pollution cannot be ignored as it is related to maintain all sorts of life on earth. This article reviews the possible threat of air pollution on environment, health and crop production. During 2020, out of top 50 air polluted cities around the globe, 49 were from Bangladesh, China, India, and Pakistan. Intensity of PM2.5 and PM10 at various region of Bangladesh were 56.22-210.45μg/m3 and 163.41-316.31μg/m3 respectively. PM2.5 was superiorly (58%) responsible for air pollution in Dhaka city. Level of different air pollutants (PM, NOx, SO2, CO, O3) relied on activity, time and seasonal variation. COVID-19 pandemic significantly decreased PM emissions nearly 28% in Malaysia, 75% in Morocco and around 21% in China. Numerous serious health risk of air pollution was observed; among them death from cardio vascular (32.77%), cancers (10.49%) and respiratory diseases (10.21%) was main. SO2, NOx, fluorides and O3 were noted to be the key pollutants to hamper crop adaptation to stress and also reduce the production. Yield reduction of rice (about 15%), corn (nearly 20%) and wheat (almost 40%) was significant in an increased concentration of O3. Some prime remedy to control and minimize air pollutions were remarked as- improvement of public transportation system, shifting industries and brick kilns away from urban areas, setting and using waste treatment plant in industries, using ecofriendly green technologies, raising public awareness on air pollution through mass and social medias, enforcing environment pollution law by the government. Air pollution control and reduction requires a combination of many approaches; it is high time to take necessary action to stop and prevent air pollution now; else our future generation will suffer endlessly.
... In Dhaka, fossilfuel sources include brick kilns, traffic and diesel electric generators; biomass sources include household biomass cooking and agricultural crop burning; and other sources include soil dust, road dust, construction dust, industrial and incinerators. 17,24 Health data Unlike in the developing world, digitized records of daily deaths or visits/admissions to hospitals were not available for hospital records in Bangladesh. We therefore directly procured and then digitized daily written records from the National Institute of Cardiovascular Diseases (NICVD). ...
Article
Background: Fine-particulate-matter (i.e. with an aerodynamic diameter of ≤2.5 µm, PM2.5) air pollution is commonly treated as if it had 'equivalent toxicity', irrespective of the source and composition. We investigate the respective roles of fossil-fuel- and biomass-combustion particles in the PM2.5 relationship with cardiovascular morbidity and mortality using tracers of sources in Dhaka, Bangladesh. Results provide insight into the often observed levelling of the PM2.5 exposure-response curve at high-pollution levels. Methods: A time-series regression model, adjusted for potentially confounding influences, was applied to 340 758 cardiovascular disease (CVD) emergency-department visits (EDVs) during January 2014 to December 2017, 253 407 hospital admissions during September 2013 to December 2017 and 16 858 CVD deaths during January 2014 to October 2017. Results: Significant associations were confirmed between PM2.5-mass exposures and increased risk of cardiovascular EDV [0.27%, (0.07% to 0.47%)] at lag-0, hospitalizations [0.32% (0.08% to 0.55%)] at lag-0 and deaths [0.87%, (0.27% to 1.47%)] at lag-1 per 10-μg/m3 increase in PM2.5. However, the relationship of PM2.5 with morbidity and mortality effect slopes was less steep and non-significant at higher PM2.5 concentrations (during crop-burning-dominated exposures) and varied with PM2.5 source. Fossil-fuel-combustion PM2.5 had roughly a four times greater effect on CVD mortality and double the effect on CVD hospital admissions on a per-µg/m3 basis than did biomass-combustion PM2.5. Conclusion: Biomass burning was responsible for most PM2.5 air pollution in Dhaka, but fossil-fuel-combustion PM2.5 dominated the CVD adverse health impacts. Such by-source variations in the health impacts of PM2.5 should be considered in conducting ambient particulate-matter risk assessments, as well as in prioritizing air-pollution-mitigation measures and clinical advice.
Article
Full-text available
Particulate matter (PM2.5) is one of the major threats to public health, particularly Dhaka City in Bangladesh, frequently cited as one of the worst cities in the World in terms of air quality. This study examines the effects of six environmental (land surface temperature (LST), digital elevation model (DEM), water vapor concentration, wind speed, rainfall, and normalized difference vegetation index (NDVI)) and six economic factors (population density, road density, gross domestic product (GDP), poverty rate level, and percentage of low-income groups in rural and urban setting) on PM2.5 concentration in five industrial cities of Bangladesh using geographically weighted regression modelling (GWR) and machine learning (ML) tools. The mean annual rate of PM2.5 concentration increased by > 42% during 2002–2020 in all cities. Dhaka and Narayanganj districts were affected the most. Goodness-of-fit (R2) was 93% (environmental factors) and 73% (economic factors). Environmental factors: LST (100%) and water vapor concentration (100%) were correlated positively with PM2.5, while DEM (100%), rainfall (83%), NDVI (81%), and wind speed (84%) had a negative relationship at 95% confidence level. β-coefficients of DEM (p < 0.02), LST (p < 0.01), water vapor concentration (p < 0.01), NDVI (p < 0.02), and poverty rate (p < 0.01) were correlated negatively. Moreover, machine learning has extracted a good prediction of PM2.5, ranging the R2 between 0.79 and 0.86%. This study can be replicated in other cities by incorporating socio-economical, local geo-environmental, and meteorological with other air pollutants.
Article
Long-term trends in air quality by studying the criteria pollutants (PM2.5, PM10, CO, O3, NO2, and SO2) and climate variables (temperature, surface pressure, and relative humidity) were depicted in this study. The seventeen years (2003-2019) average values of PM2.5, PM10, CO, O3, NO2, and SO2 were 88.69 ± 9.76 µg/m 3 , 124.57 ± 12.75 µg/m 3 , 0.69 ± 0.06 ppm, 51.42 ± 1.82 ppb, 14.87 ± 2.45 ppb, and 8.76 ± 2.07 ppb, respectively. The trends among the ambient pollutants were increasingly significant (p < 0.05) except for O3 with slopes of 1.83 ± 0.15 µg/m 3 /year, 2.35 ± 0.24 µg/m 3 /year, 0.01 ± 0.002 ppm/year, 0.47 ± 0.03 ppb/year, and 0.40 ± 0.02 ppb/year for PM2.5, PM10, CO, NO2, and SO2, respectively. Pearson correlations revealed a significant association among the pollutants while a noteworthy correlation was observed between ambient pollutants and surface temperature. Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) have been employed collectively to examine the main sources of the pollutants. PCA revealed similar trends for PMs and CO, as well as NO2 and SO2 being equally distributed variables. PMF receptor modeling resulted in attributing four sources to the pollutants. The factors inferred from the PMF modeling were signified as vehicular emissions, road/soil dust, biomass burning, and industrial emissions. The hazard quotient (HQ) values were not antagonistic (HQ <1) in acute exposure levels for three age groups (infants, children, and adults) while showing significant health risk (HQ >1) in chronic exposure for infants and children. Children are identified as the worst sufferers among the age groups which points to low breathing levels and high exposure to traffic pollution in Dhaka, Bangladesh. Highlights • Long-term trends of criteria air pollutants and climate variables were analyzed • Significant positive trends were observed for all the pollutants except ozone • Four factors were characterized as estimated sources from PMF modeling • HQ exceeded the acceptable limit (>1) for chronic exposure to children and infants Graphical Abstract 4
Article
Full-text available
In Dhaka, Bangladesh, particular matter (PM) is the air pollutant that is most harmful to public health and the environment when compared to other measured criteria pollutants. During recent years, the Government of Bangladesh has tried to control PM emissions coming from anthropogenic sources. About 30-50% of the PM10 mass in Dhaka (depending on location) is in fine particles with aerodynamic diameter less than 2.2 mu m. These particles are mainly of anthropogenic origin and predominately from transport-related sources. However, the combination of meteorological conditions, long-range transport during the winter and local sources results in PM concentrations remaining much higher than the Bangladesh National Ambient Air Quality Standard (BNAAQS). It has been found that black carbon accounted for about 50% of the total fine PM mass before the adoption of control policies. As a result, the PM emission as well as BC has not increased in proportion to the increase in the number of combustion sources like motor vehicles, diesel power generator or brick kiln. Positive Matrix Factorization (PMF) was applied to fine particle composition data from January 2007 to February 2009. It was found that motor vehicles contribute less BC with respect to brick kiln industry. This result demonstrates the effectiveness of the government's policy interventions since previously vehicles represented the major contributors of BC. BC is also transported over long distances, mixing with other particles along the way as demonstrated by a potential source contribution function analysis. Transboundary transport of air pollution in the South Asian region has become an issue of increasing importance over the past several decades. The relative amounts of local and long-range transported pollutants are currently unknown.
Article
Full-text available
The fine particle (<2.5 μm) composition data from seven National Park Service locations in Alaska for the period from 1986 to 1995 was performed using a new type of factor analysis, positive matrix factorization (PMF). This method uses the estimates of the error in the data to provide optimum data point scaling and permits a better treatment of missing and below detection limit values. Eight source components were obtained for data sets from the Northwest Alaska Areas and the Bering Land Bridge sites. Five to seven components were obtained for the other Alaskan sites. The solutions were normalized by using aerosol fine mass concentration data. Squared correlation coefficients between the reconstructed mass obtained from aerosol composition data for the sites and the measured mass were in the range of 0.74-0.95. Two factors identified as soils were obtained for all of the sites. Concentrations for these factors for most of the sites have maxima in the summer and minima in the winter. A sea-salt component was found at five locations. A factor with the highest concentrations of black carbon (BC), H+, and K identified as forest fire smoke was obtained for all data sets except at Katmai. Factors with high concentrations of S, BC-Na-S, and Zn-Cu were obtained at all sites. At three sites, the solutions also contained a factor with high Pb and Br values. The factors with the high S, Pb, and BC-Na-S values at most sites show an annual cycle with maxima during the winter-spring season and minima in the summer. The seasonal variations and elemental compositions of these factors suggest anthropogenic origins with the spatial pattern suggesting that the sources are distant from the receptor sites. The seasonal maxima/minima ratios of these factors were higher for more northerly locations. Four main sources contribute to the observed concentrations at these locations: long-range transported anthropogenic aerosol (Arctic haze aerosol), sea-salt aerosol, local soil dust, and aerosol with high BC concentrations from regional forest fires or local wood smoke. A northwest to southeast negative gradient suggesting long-range transport of air masses from regions north or northwest of Alaska dominated the spatial distribution of the high S factor concentrations.
Article
Full-text available
Fine particulate matter (PM2.5) samples were simultaneously collected on Teflon and quartz filters between February 2010 and February 2011 at an urban monitoring site (CAMS2) in Dhaka, Bangladesh. The samples were collected using AirMetrics MiniVol samplers. The samples on Teflon filters were analyzed for their elemental composition by PIXE and PESA. Particulate carbon on quartz filters was analyzed using the IMPROVE thermal optical reflectance (TOR) method that divides carbon into four organic carbons (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. The data were analyzed by positive matrix factorization using the PMF2 program. Initially, only total OC and total EC were included in the analysis and five sources, including road dust, sea salt and Zn, soil dust, motor vehicles, and brick kilns, were obtained. In the second analysis, the eight carbon fractions (OC1, OC2, OC3, OC4, OP, EC1, EC2, EC3) were included in order to ascertain whether additional source information could be extracted from the data. In this case, it is possible to identify more sources than with only total OC and EC. The motor vehicle source was separated into gasoline and diesel emissions and a fugitive Pb source was identified. Brick kilns contribute 7.9 microg/m3 and 6.0 microg/m3 of OC and EC, respectively, to the fine particulate matter based on the two results. From the estimated mass extinction coefficients and the apportioned source contributions, soil dust, brick kiln, diesel, gasoline, and the Pb sources were found to contribute most strongly to visibility degradation, particularly in the winter.
Article
Full-text available
Samples of fine and coarse airborne particulate matter (PM) were collected between February and July 2007 at the Continuous Air Monitoring Station (CAMS) in Chittagong, the second largest city in Bangladesh. Samples were collected using a dichotomous sampler in two fractions of < 2.5 mu m (fine) and 2.5 to 10 mu m (coarse). Samples were analyzed for elemental concentrations by proton induced X-ray emission (PIXE), hydrogen by proton elastic scattering analysis (PESA), and black carbon by reflectometry. Elemental data sets together with black carbon were analyzed by positive matrix factorization to identify the possible sources of mass for the coarse and fine PM fractions. Best solutions were found to be six and seven factors for elemental compositions for coarse and fine fractions at the CAMS at Chittagong, respectively. Sources were identified as biomass burning/brick kiln, soil dust, road dust, Zn source (including two-stroke motorcycles), motor vehicle, CNG vehicle, and sea salt. The PMF results show that about 35.5% of PM(2.5) mass at this site comes from biomass burning. The second largest contribution of fine PM comes from motor vehicle including CNG vehicles. The third one is a Zn source that includes emissions from two-stroke vehicles and galvanizing factories with vehicles, probably the larger contributor of the two source types. In case of coarse PM, about 40% of PM(2.5-10) mass comes from soil dust including road dust.
Article
Full-text available
Transboundary transport of air pollution in the South Asian region has been an issue of increasing importance over the past several decades. Long-range transport of anthropogenic pollution is contrasted with that of pollution produced by natural processes such as dust storms or natural forest fires. Airborne particulate matter datasets covering the period from 2002 to 2007 from the neighboring countries like Bangladesh, India, Pakistan and Sri Lanka were used to find the source areas that are primarily responsible for long range transported pollutants. All four countries collected samples with the same type of sampler and follow the same technique for mass and BC measurements. It was found that high fine soil contributions were from dust storms. On the other hand, smoke in this region mainly comes from northern India where agricultural waste is often burned. (C) Author(s) 2011. This work is distributed under the Creative Commons Attribution 3.0 License.
Article
Full-text available
Particulate matter (PM) sampling for both coarse and fine fractions was conducted in a semi-residential site (AECD) in Dhaka from February 2005 to December 2006. The samples were analyzed for mass, black carbon (BC), and elemental compositions. The resulting data set were analyzed for sources by Positive Matrix Factorization (EPA-PMF). From previous studies, it is found that, the air quality became worse in the dry winter period compared to the rainy season because of higher particulate matter concentration in the ambient air.. Therefore, seasonal source contributions were determined from seasonally segregated data using EPA-PMF modeling so that further policy interventions can be undertaken to improve air quality. From the source apportionment results, it is observed that vehicular emissions and emission from brick kiln are the major contributors to air pollution in Dhaka especially in the dry seasons, while contribution from emissions from metal smelters increases during rainy seasons. The Government of Bangladesh is considering different interventions to reduce the emissions from those sources by adopting conversion of diesel/petrol vehicles to CNG, increasing traffic speed in the city and by introducing green technologies for brick production. However, in order to reduce the transboundary effect it is necessary to take action regionally. (C) 2010 Elsevier Ltd. All rights reserved.
Article
A total of 1,000 kilns producing 3.5 billion bricks and consuming 0.85 million tons of coal per year resulted in an estimated 2,200 to 4,000 premature deaths and 0.2 to 0.5 million asthma attacks per year in the Greater Dhaka region. In this paper, the emission reductions and health cost savings are presented for moving to cleaner brick manufacturing technologies for the districts of Gazipur, Savar, Dhamrai, Rupganj, Manikganj, Kaliganj, and Narayanganj. A summary of various technologies and feasibility of these technologies based on lessons learnt from the pilots is discussed. We explored three “what-if” scenarios through 2020 for better energy efficiency, lower coal consumption, and lower emission rates, under which the total health cost savings are estimated to range between USD12 million annually for short-term implementation and up to 55 million annually for long-term implementation. Between 2015 and 2020, the cumulative health cost savings could range between USD126 and 234 million, which clearly outweigh any cost of capital investment necessary for the technology change. An improvement in energy efficiency will result in USD1.8 to 3.0 million per year in coal savings, which will accrue to the kiln owners collectively, and these savings will pay back the capital investment within 3–4 years, in addition to the health cost savings for the city inhabitants. Hence, the entrepreneurs have all the social, environmental, and economic incentives to adopt cleaner technologies. A major gap at the regulatory level is in building awareness for the entrepreneurs and setting up an incentive structure to implement this transition, which is being addressed by an advisory committee by the Government of Bangladesh responsible for the revision of the Brick Burning Act of 1989 and related legislations.
Article
A new variant ‘PMF’ of factor analysis is described. It is assumed that X is a matrix of observed data and σ is the known matrix of standard deviations of elements of X. Both X and σ are of dimensions n × m. The method solves the bilinear matrix problem X = GF + E where G is the unknown left hand factor matrix (scores) of dimensions n × p, F is the unknown right hand factor matrix (loadings) of dimensions p × m, and E is the matrix of residuals. The problem is solved in the weighted least squares sense: G and F are determined so that the Frobenius norm of E divided (element-by-element) by σ is minimized. Furthermore, the solution is constrained so that all the elements of G and F are required to be non-negative. It is shown that the solutions by PMF are usually different from any solutions produced by the customary factor analysis (FA, i.e. principal component analysis (PCA) followed by rotations). Usually PMF produces a better fit to the data than FA. Also, the result of PF is guaranteed to be non-negative, while the result of FA often cannot be rotated so that all negative entries would be eliminated. Different possible application areas of the new method are briefly discussed. In environmental data, the error estimates of data can be widely varying and non-negativity is often an essential feature of the underlying models. Thus it is concluded that PMF is better suited than FA or PCA in many environmental applications. Examples of successful applications of PMF are shown in companion papers.