Fine particulates over South Asia: Review and meta-analysis of PM2.5 source apportionment through receptor model

Singh, N. P.; Murari, Vishnu; Kumar, Manish; Barman, S. C.; Banerjee, Tirthankar

doi:10.1016/j.envpol.2016.12.071

Cited by 186 publications

(63 citation statements)

References 90 publications

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“…BC and O 3 are two key short-lived climate pollutants. Similarly, species like fine particles and carbon monoxide (CO) are potent to health damages by posing impacts upon the respiratory and cardiovascular system and even also to the climate system (Singh et al, 2017, and references therein). Because of the IGP's close proximity to the Himalaya-Tibetan plateau region, this once relatively clean region is now subjected to increasing air pollution transported from regions such as the IGP, which can exert additional risks to sensitive ecosystems in the mountain region (e.g., Lüthi et al, 2015;Marinoni et al, 2013;Duchi et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

et al. 2017

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Abstract. Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O 3 ) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of 3 months (April-June 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley -Atmospheric Brown Clouds). The main objective of this work is to understand and document the level of air pollution, diurnal characteristics and influence of open burning on air quality in Lumbini. The hourly average concentrations during the entire measurement campaign ranged as follows: BC was 0.3-30.0 µg m −3 , PM 1 was 3.6-197.6 µg m −3 , PM 2.5 was 6.1-272.2 µg m −3 , PM 10 was 10.5-604.0 µg m −3 , O 3 was 1.0-118.1 ppbv and CO was 125.0-1430.0 ppbv. These levels are comparable to other very heavily polluted sites in South Asia. Higher fraction of coarsemode PM was found as compared to other nearby sites in the Indo-Gangetic Plain region. The BC / CO ratio obtained in Lumbini indicated considerable contributions of emissions from both residential and transportation sectors. The 24 h average PM 2.5 and PM 10 concentrations exceeded the WHO guideline very frequently (94 and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants to understand the pollutant transport pathways. The model estimated values were ∼ 1.5 to 5 times lower than the observed concentrations for CO and PM 10 , respectively. Model-simulated regionally tagged CO tracers showed that the majority of CO came from the upwind region of Ganges Valley. Model performance needs significant improvement Published by Copernicus Publications on behalf of the European Geosciences Union.

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Section: Introductionmentioning

confidence: 99%

Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

et al. 2017

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“…Several methods have been introduced to identify and quantify OC emission sources, such as the use of organic molecular tracers (Simoneit et al, 1999), receptor models (positive matrix factorization, PMF; chemical mass balance, CMB) (Singh et al, 2017;Bove et al, 2014;Marcazzan et al, 2003), and dispersion models (Colvile et al, 2003); however, their reliability is limited by their low atmospheric lifetimes, in turn due to chemical reactivity and highly variable emission factors (Fine et al, 2001(Fine et al, , 2002(Fine et al, , 2004Gao et al, 2003;Hedberg et al, 2006;Robinson et al, 2006). Recently, radiocarbon ( 14 C) analysis has been used as a powerful tool for facilitating the direct differentiation of non-fossilfuel (NF) carbon sources from fossil fuel (FF) sources, because 14 C is completely absent from FF carbon (e.g., diesel and gasoline exhaust, coal combustion), whereas NF carbon (e.g., biomass burning, cooking and biogenic emissions) shows a high contemporary 14 C level (Szidat et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Sources of non-fossil-fuel emissions in carbonaceous aerosols during early winter in Chinese cities

Liu

Cheng

et al. 2017

Atmos. Chem. Phys.

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Abstract. China experiences frequent and severe haze outbreaks from the beginning of winter. Carbonaceous aerosols are regarded as an essential factor in controlling the formation and evolution of haze episodes. To elucidate the carbon sources of air pollution, source apportionment was conducted using radiocarbon ( 14 C) and unique molecular organic tracers. Daily 24 h PM 2.5 samples were collected continuously from October 2013 to November 2013 in 10 Chinese cities. The 14 C results indicated that non-fossil-fuel (NF) emissions were predominant in total carbon (TC; average = 65 ± 7 %). Approximately half of the EC was derived primarily from biomass burning (BB) (average = 46±11 %), while over half of the organic carbon (OC) fraction comprised NF (average = 68 ± 7 %). On average, the largest contributor to TC was NF-derived secondary OC (SOC nf ), which accounted for 46 ± 7 % of TC, followed by SOC derived from fossil fuels (FF) (SOC f ; 16 ± 3 %), BB-derived primary OC (POC bb ; 13 ± 5 %), POC derived from FF (POC f ; 12 ± 3 %), EC derived from FF (EC f ; 7±2 %) and EC derived from BB (EC bb ; 6 ± 2 %). The regional background carbonaceous aerosol composition was characterized by NF sources; POCs played a major role in northern China, while SOCs contributed more in other regions. However, during haze episodes, there were no dramatic changes in the carbon source or composition in the cities under study, but the contribution of POC from both FF and NF increased significantly.

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“…Observed CO concentrations ranged between 124.9 and 1429.7 ppbv with an average value of 344.1 ± 160.3 ppbv. CO concentration observed in Lumbini is lower than that of Mohali, western India, where the average concentration was 566.7 ppbv during pre-monsoon season due to intense biomass and agro-residue burning over the region (Sinha et al, 2014). Temporal variation of CO concentrations is similar to that of BC, exhibiting very strong correlation (r = 0.9).…”

Section: Meteorologymentioning

confidence: 69%

“…Different sites located at urban, semi-urban and remote locations were used for comparison to get a clear comparative picture of the situation at Lumbini amongst other locations in the region. Pre-monsoon seasonal average PM 2.5 concentration in Lumbini has been found to be lower than in the megacity Delhi and northwestern IGP (Sinha et al, 2014), possibly due to higher levels of emissions (from traffic and biomass burning, respectively) over those regions. In addition, average BC and CO concentrations in Lumbini fell between concentrations observed at rural sites (up to 6 times higher) and cities in the region (see Table 2), indicating that Lumbini, in a way, can still be considered a semi-urban location.…”

Section: Meteorologymentioning

confidence: 89%

“…The correlation of WS (> 1 m s −1 ) with concentration of air pollutants indicates that air pollution over Lumbini is not only of local origin but also from other nearby regions. Past studies near this site have been focused on cities like Kathmandu (Sharma et al, 2012;Panday and Prinn, 2009;Putero et al, 2015) and Kanpur (Ram et al, 2010) and regions of IGP dominated by agro-residue burning (Rastogi et al, 2016;Sinha et al, 2014;Sarkar et al, 2013), all of which reported very high levels of pollution. Our study adds to the growing list of scientific observations in the IGP by providing data from the foothills of the central Himalayas.…”

Section: Meteorologymentioning

confidence: 99%

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Compiled Response to the reviewers comments

Rupakheti¹

2017

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Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O 3 ) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of 3 months (April-June 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley -Atmospheric Brown Clouds). The main objective of this work is to understand and document the level of air pollution, diurnal characteristics and influence of open burning on air quality in Lumbini. The hourly average concentrations during the entire measurement campaign ranged as follows: BC was 0.3-30.0 µg m −3 , PM 1 was 3.6-197.6 µg m −3 , PM 2.5 was 6.1-272.2 µg m −3 , PM 10 was 10.5-604.0 µg m −3 , O 3 was 1.0-118.1 ppbv and CO was 125.0-1430.0 ppbv. These levels are comparable to other very heavily polluted sites in South Asia. Higher fraction of coarsemode PM was found as compared to other nearby sites in the Indo-Gangetic Plain region. The BC / CO ratio obtained in Lumbini indicated considerable contributions of emissions from both residential and transportation sectors. The 24 h average PM 2.5 and PM 10 concentrations exceeded the WHO guideline very frequently (94 and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants to understand the pollutant transport pathways. The model estimated values were ∼ 1.5 to 5 times lower than the observed concentrations for CO and PM 10 , respectively. Model-simulated regionally tagged CO tracers showed that the majority of CO came from the upwind region of Ganges Valley. Model performance needs significant improvementPublished by Copernicus Publications on behalf of the European Geosciences Union. 11042 D. Rupakheti et al.: Pre-monsoon air quality over Lumbini in simulating aerosols in the region. Given the high air pollution level, there is a clear and urgent need for setting up a network of long-term air quality monitoring stations in the greater Lumbini region.

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Fine particulates over South Asia: Review and meta-analysis of PM2.5 source apportionment through receptor model

Cited by 186 publications

References 90 publications

Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

Sources of non-fossil-fuel emissions in carbonaceous aerosols during early winter in Chinese cities

Compiled Response to the reviewers comments

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