Impact of Unleaded Gasoline Introduction on the Concentration of Lead in the Air of Dhaka, Bangladesh

Biswas, Swapan Kumar; Tarafdar, S. A.; Islam, Ashraful; Khaliquzzaman, M.; Tervahattu, Heikki; Kupiainen, Kaarle

doi:10.1080/10473289.2003.10466299

Cited by 88 publications

(54 citation statements)

References 29 publications

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“…The method is based on the absorption of light, in which the amount of light absorption is proportional to the black carbon concentration on the filter. The black carbon concentration values were obtained according to the method described by other workers (Edwards et al, 1983;Cohen et al, 2000;Biswas et al, 2003).…”

Section: Mass and Black Carbon Measurementmentioning

confidence: 99%

A Long Term Study on Characterization and Source Apportionment of Particulate Pollution in Klang Valley, Kuala Lumpur

Rahman

Hamzah

Elias

et al. 2015

Aerosol Air Qual. Res.

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Samples of airborne particulate matter, PM 2.5 and PM 10-2.5 were collected using a Gent stacked filter sampler at an urban site, Klang Valley, Kuala Lumpur between January 2002-December 2011. The samples were analyzed for their elemental composition and black carbon content by Particle Induced X-ray Emission (PIXE) and light absorption, respectively. The annual average for PM 2.5 , PM 10-2.5 and PM 10 ranged from 21 to 35, 18 to 26 and 44 to 56 µg m -3 , respectively. Factor analysis method and the Positive Matrix Factorisation (EPA PMF3) technique were also applied to the fine fraction data set in order to identify the possible sources of particulate matter and their contributions to the ambient particulate matter concentrations in the Klang Valley. A five factor PMF solution was found for PM 2.5 particulate matter. The sources identified were; motor vehicles, industry, smoke/biomass burning, secondary sulphate and soil. It was found that the primary source of haze air particulate matter was locally generated mostly from vehicular emissions which contribute about 35% of the PM 2.5 mass. The Hybrid Single Particle Lagrangian Intergrated Trajectory (HYSPLT) model was also used to explore possible long range transport of pollution. Smoke trans-boundary events were identified based on fine potassium from the data base in 2004, 2006 and 2008.

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Section: Mass and Black Carbon Measurementmentioning

confidence: 99%

A Long Term Study on Characterization and Source Apportionment of Particulate Pollution in Klang Valley, Kuala Lumpur

Rahman

Hamzah

Elias

et al. 2015

Aerosol Air Qual. Res.

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“…EC is often determined using thermal-optical protocols, such as National Institute of Occupational Safety and Health Method 5040 with correction by thermal-optical transmission (NIOSH/TOT) (Birch 1998(Birch , 2002Birch and Cary 1996;Stone et al 2010;Kaul et al 2011) or the Interagency Monitoring of Protected Visual Environments with correction by thermal-optical reflectance (IMPROVE/TOR) (Chow et al 1993(Chow et al , 2007Pavuluri et al 2011). BC cannot be measured directly but must be inferred from the particle light absorption (b ap ) through a conversion factor that is used to translate b ap to the BC mass concentration (Chow et al 2009;Biswas et al 2003). According to the literature, both EC and BC are considered to assume a graphitic structure and are therefore thermally refractory and light-absorbing in nature (Bond and Bergstrom 2006;Salako et al 2012;Conny et al 2003;Turpin et al 1990).…”

Section: Introductionmentioning

confidence: 99%

Comparison of elemental and black carbon measurements during normal and heavy haze periods: implications for research

Zhi

Chen

Xue

et al. 2014

Environ Monit Assess

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Studies specifically addressing the elemental carbon (EC)/black carbon (BC) relationship during the transition from clean-normal (CN) air quality to heavy haze (HH) are rare but have important health and climate implications. The present study, in which EC levels are measured using a thermal-optical method and BC levels are measured using an optical method (aethalometer), provides a preliminary insight into this issue. The average daily EC concentration was 3.08±1.10 μg/m 3 during the CN stage but climbed to 11.77±2.01 μg/m 3 during the HH stage. More importantly, the BC/EC ratio averaged 0.92±0.14 during the CN state and increased to 1.88± 0.30 during the HH state. This significant increase in BC/ EC ratio has been confirmed to result partially from an increase in the in situ light absorption efficiency (σ ap ) due to an enhanced internal mixing of the EC with other species. However, the exact enhancement of σ ap was unavailable because our monitoring scheme could not acquire the in situ absorption (b ap ) essential for σ ap calculation. This reveals a need to perform simultaneous measurement of EC and b ap over a time period that includes both the CN and HH stages. In addition, the sensitivity of EC to both anthropogenic emissions and HH conditions implies a need to systematically study how to include EC complex (EC concentration, OC/EC ratio, and σ ap ) as an indicator in air quality observations, in alert systems that assess air quality, and in the governance of emissions and human behaviors.

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“…A Po-210 (alpha emitter) electrostatic charge eliminator (STATICMASTER) was used to eliminate any charge accumulated on the filters before each weighing. Black carbon (BC) was measured at the AECD laboratory in Dhaka using an EEL (Evans Electroselenium Limited) Smoke Stain Reflectometer (Biswas et al 2003). Secondary standards of known black carbon concentrations are used to calibrate the reflectometer.…”

Section: Methodsmentioning

confidence: 99%

“…Factor 5 explained 2.7% of the variance and was labeled as fugitive or resuspended Pb source. Although, Pb was eliminated from the gasoline in Bangladesh in July 1999 (Biswas et al 2003), there may be substantial accumulated lead in the dust near roadways. Examining the fine particle results in Table 8, factor 1 explained 52.8% of the variance with high factor loadings for crustal elements including Si, Ti, Ca, K, Mn, Cu, Pb and Fe mixed with OMH, BC and Zn.…”

Section: Source Apportionmentmentioning

confidence: 99%

Characterization of Chittagong Aerosol by PCA Modeling

Begum

Biswas

Nasiruddin

2012

J Bangladesh Acad Sci

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Black carbon and other selected trace elements concentrations in aerosol samples collected at the Continuous Air Monitoring Station (CAMS) in Chittagong, the second largest city in Bangladesh, were investigated for possible source contributions. The particulate matter (PM) sampling was done from end of winter to middle of rainy season (February and July, 2007) using dichotomous sampler. The samples collected in two fractions of <2.5 m (fine) and 2.5 to 10 m (coarse) were analyzed for elemental concentrations by proton induced X-ray emission (PIXE), hydrogen by proton elastic scattering analysis (PESA), and black carbon by reflectance measurement. The elemental data sets together with black carbon were analyzed by principal component analysis method to identify the possible sources contributing to the mass concentration of coarse and fine particulate matter (FPM) fractions. The best solutions were found to be six and seven factors for coarse and fine fractions respectively, which could explain more than 90% of the variance in the data set. The sources were identified as biomass burning/brick kiln, soil dust, road dust, Zn source, Pb source, motor vehicle, CNG (compressed natural gas) vehicle and sea salt. It was found that in coarse fraction, the sea salt is mixed with Zn source and in fine fraction, the road dust factor is mixed with CNG vehicle source.

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Impact of Unleaded Gasoline Introduction on the Concentration of Lead in the Air of Dhaka, Bangladesh

Abstract: ABSTRACT

Cited by 88 publications

References 29 publications

A Long Term Study on Characterization and Source Apportionment of Particulate Pollution in Klang Valley, Kuala Lumpur

A Long Term Study on Characterization and Source Apportionment of Particulate Pollution in Klang Valley, Kuala Lumpur

Comparison of elemental and black carbon measurements during normal and heavy haze periods: implications for research

Characterization of Chittagong Aerosol by PCA Modeling

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