Quantitative Source Apportionment Research Articles

Impacts of Chemical Degradation on the Global Budget of Atmospheric Levoglucosan and Its Use As a Biomass Burning Tracer.

Levoglucosan has been widely used to quantitatively assess biomass burning's contribution to ambient aerosols, but previous such assessments have not accounted for levoglucosan's degradation in the atmosphere. We develop the first global simulation of atmospheric levoglucosan, explicitly accounting for its chemical degradation, to evaluate the impacts on levoglucosan's use in quantitative aerosol source apportionment. Levoglucosan is emitted into the atmosphere from the burning of plant matter in open fires (1.7 Tg yr-1) and as biofuels (2.1 Tg yr-1). Sinks of atmospheric levoglucosan include aqueous-phase oxidation (2.9 Tg yr-1), heterogeneous oxidation (0.16 Tg yr-1), gas-phase oxidation (1.4 × 10-4 Tg yr-1), and dry and wet deposition (0.27 and 0.43 Tg yr -1). The global atmospheric burden of levoglucosan is 19 Gg with a lifetime of 1.8 days. Observations show a sharp decline in levoglucosan's concentrations and its relative abundance to organic carbon aerosol (OC) and particulate K+ from near-source to remote sites. We show that such features can only be reproduced when levoglucosan's chemical degradation is included in the model. Using model results, we develop statistical parametrizations to account for the atmospheric degradation in levoglucosan measurements, improving their use for quantitative aerosol source apportionment.

Quantitative source apportionment of heavy metals in cultivated soil and associated model uncertainty

To estimate spatial distribution, source analysis and uncertainty of heavy metals (Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni) based on geographic information system (GIS), positive matrix factorization model (PMF) and bootstrap (BS) using 382 soil samples collected from cultivated soils in Lanzhou. The mean contents of Cd, Hg, Cu, Zn and Ni were high as 1.7,1.7, 2.1, 1.5 and 1.3 times local background values, mean contents of Pb, Cr and As were lower than local background values. However, the mean contents of eight heavy metals were lower environmental quality risk control standard for soil contamination of agricultural soil. Proportions of four sources were identified: Cr was predominantly contributed by natural sources (29.14%), Cu, Zn and Ni was primarily from industrial sources (25.26%), Hg and As were mainly of agricultural sources (27.49%), Pb and Cd mainly came from traffic source and smelting-related activities (18.09%). Uncertainties analysis contained three aspects: bootstrap runs, factor contributions in the PMF solution, and coefficient of variation (CV) values. By combining the four pollution source factors with bootstrap runs, the accuracy of the four pollution source factors were reliable based on PMF model. The median values in the BS runs was considered the most true factor contribution, and the 5th–95th quartile interval represents the variability of each factor, Factor 4 (traffic source) R2 was 0.70 and lower variability. The highest CV value usually means a significantly deviation degree. In this study, the CV values of Cr in Factor 1, Cu, Zn, and Ni in Factor 2, Hg, and As in Factor 3, Pb, and Cd in Factor 4 were lower, indicates a lower deviation degree. and with the lowest content among heavy metals usually was also with the greatest uncertainties. In this study improves understanding of the reduction of heavy metal pollution in cultivated soil, and also serves as reference for pollution source apportionment in other regions.

Microplastic pollution and quantitative source apportionment in the Jiangsu coastal area, China

We investigated the pollution characteristics, the spatial distributions of microplastics, and the source compositions in the Jiangsu Coastal Area, China. The average abundance of microplastics in the surface water and sediment were 0.0998 ± 0.0720 items/m3 (using a trawl with 333-μm mesh)and 0.1858 ± 0.0927items/g, respectively. The concentration of microplastics showed a distribution trend of high near shore and low far shore in the east-west direction, and were the highest in the southernmost part. According to microplastics found in the surface water, the results of a quantitative source apportionment indicate that the most common source in the northernmost and southernmost regions were clothing fibers, accounting for 38.40% and 40.44% of the total source, respectively. While the major source type in the middle region was the decomposition of hard, large plastic waste. Finally, we suggested some control measures for the main types of microplastics observed in the different regions.

Pollution characteristics, spatial distributions, and source apportionment of heavy metals in cultivated soil in Lanzhou, China

For the purpose of pollution assessment, human health risk assessment and quantitative source apportionment of heavy metals in cultivated soils, a total of 382 cultivated soil samples were collected from cultivated of Lanzhou in September 2019. Various indices, including pollution index (PI), Nemerow integrated pollution index (NIPI) and potential ecological risk index (RI) were used to analyze the pollution levels caused by heavy metals. Human health risk assessment, geographic information system (GIS) and positive matrix factorization (PMF) receptor modeling were employed to analyze the human health risk and source of heavy metals. The results showed that mean concentrations of Hg exceeded the national soil pollution risk screening value (GB 15618–2018). Spatially, except Cr in the study area, Pb, Cd, As, Cu, Zn and Ni have high value in Chengguan and Qilihe. Hg has high values in study areas outside Chengguan, Anning and Qilihe. The Nemerow integrated pollution index showed that the moderate and severe samples sites were 37.70% and 3.66%, respectively. The potential ecological risk indicates that most of the sampling sites are moderate risks. According to the health risk assessment results, the carcinogenic and non-carcinogenic risks of heavy metals to the human body are insignificant. Based on positive matrix factorization, there are four main sources of eight heavy metals. Pb, Cd, Zn and Ni were attributed to traffic sources; Hg were closely related to agricultural activities and medical treatment; Cr, Cu and Ni originated from natural source, As was derived from industrial activity. In this study enhance understanding of the pollution levers of heavy metals in Lanzhou cultivated soils, and also serves as reference for pollution source apportionment in other regions.

Insights into particulate matter pollution in the North China Plain during wintertime: local contribution or regional transport?

Abstract. Accurate identification and quantitative source apportionment of fine particulate matter (PM2.5) provide an important prerequisite for design and implementation of emission control strategies to reduce PM pollution. Therefore, a source-oriented version of the WRF-Chem model is developed in the study to conduct source apportionment of PM2.5 in the North China Plain (NCP). A persistent and heavy haze event that occurred in the NCP from 5 December 2015 to 4 January 2016 is simulated using the model as a case study to quantify PM2.5 contributions of local emissions and regional transport. Results show that local and nonlocal emissions contribute 36.3 % and 63.7 % of the PM2.5 mass in Beijing during the haze event on average. When Beijing's air quality is excellent or good in terms of hourly PM2.5 concentrations, local emissions dominate the PM2.5 mass, with contributions exceeding 50 %. However, when the air quality is severely polluted, the PM2.5 contribution of nonlocal emissions is around 75 %. Nonlocal emissions also dominate Tianjin's air quality, with average PM2.5 contributions exceeding 65 %. The PM2.5 level in Hebei and Shandong is generally controlled by local emissions, but in Henan, local and nonlocal emissions play an almost equivalent role in the PM2.5 level, except when the air quality is severely polluted, with nonlocal PM2.5 contributions of over 60 %. Additionally, the primary aerosol species are generally dominated by local emissions, with the average contribution exceeding 50 %. However, the source apportionment of secondary aerosols shows more evident regional characteristics. Therefore, except for cooperation with neighboring provinces to carry out strict emission mitigation measures, reducing primary aerosols is a priority to alleviate PM pollution in the NCP, especially in Beijing and Tianjin.

Hazardous heavy metals in the pristine lacustrine systems of Antarctica: Insights from PMF model and ERA techniques

A comprehensive study was presented on the ecological risk, distribution, and quantitative source apportionment of heavy metals in the selected lacustrine systems of Schirmacher Hills using various environmental indices and methods. A total of 25 sediment samples from 16 lakes were collected around scientific research stations and analyzed for metals. Geochemical approaches and ecological risk assessment methods were implemented to characterize and evaluate the contamination level and associated risk in the lacustrine systems. Moreover, statistical techniques and a positive matrix factorization (PMF) model were indorsed to understand metals' association and apportion their probable sources. Results revealed that most of the heavy metals (mean concentration in ppm) such as Al (77,504.09), Cd (1.36), Co (29.52), Cr (102.75), Cu (65.19), Fe (57,632.87), Mn (679.05), Ni (49.13), Pb (10.11), and Zn (253.78) are originated from natural weathering of source rocks (78.53%) followed by human-induced actions/ station activities coupled with atmospheric deposition (21.47%). Environmental risk assessment (ERA) techniques suggest that the lakes in the study area are under minimal to moderate enrichment/ contamination category and experienced minimal to adverse biological effects where metal toxicity risk is minimal.

Quantitative source apportionment, risk assessment and distribution of heavy metals in agricultural soils from southern Shandong Peninsula of China

The heavy metals, including cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), zinc (Zn), and the metalloid arsenic (As) were detected in surface and core soil samples collected from a tobacco growing region in Shandong Peninsula on the east coast of China to evaluate their pollution levels, ecological and health risks, and to analyze their spatial and vertical distributions. The heavy metal sources were identified quantitatively using the positive matrix factorization (PMF) receptor model. In accordance, most of the soils did not have accumulations and were not contaminated by As, Cr, Cu, Ni, Pb, and Zn. High accumulations of Cd and Hg occurred in the soils, posing an ecological risk to the local agricultural environment, while Cr and Ni levels presented a carcinogenic health risk to humans. Four main sources of heavy metals in the soils were identified. Correspondingly Ni and Cr were mainly originated from natural sources, Hg from coal combustion, Cd from agricultural practices, Cu, Pb, and Zn from agricultural practices and industrial activities, and As from industrial activities.

Heavy metal pollution of road dust in a city and its highly polluted suburb; quantitative source apportionment and source-specific ecological and health risk assessment

Sources of heavy metals (As, Cd, Co, Cr, Cu, Mn, Ni, Pb and Zn) in the road dust of Bandar Abbas city, Iran, and its west suburb were apportioned and the related source-specific ecological and health risks were assessed. The level of heavy metal pollution and the related ecological risk for suburban road dust (suburban RD) were far higher than those of urban RD. Accordingly, probabilistic health risk assessment showed no significant health risk in urban region but significant health risk in the suburb, especially for As with cancer risk above 10−4. Source apportionment using positive matrix factorization (PMF) identified lithogenic source (45.9%) and traffic emission (47.6%) as the main sources of heavy metals in urban and suburban regions, respectively. However, the industrial/construction activities showed the main contribution in ecological risk in both regions. On the other hand, the health risks in urban and suburban regions were mainly attributed to lithogenic source (49.7% for non-cancer risk and 36.8% of cancer risk) and traffic emission (69.4% of non-cancer risk and 46.6% of cancer risk), respectively. The sensitivity analysis showed that the Pb and As originated from traffic emission had the most impact on the non-cancer and cancer risks, respectively, in the suburb. Therefore, this study highlighted the concern about traffic emission as a critical heavy metal source in the road dust of Bandar Abbas suburb.

Seasonal variations in characteristics, sources and diurnal patterns of carbonaceous and water-soluble constituents in urban aerosols from the east coast of tropical India

Environmental context The export of various man-made pollutants from northern India has a large impact on aerosol formation processes, their transformations and regional environmental chemistry over tropical peninsular India. The quantitative source apportionment of organic aerosols performed in this study provides a better understanding of their sources and implications for climate and air-quality management policies in South Asia. Abstract This study highlights seasonal characteristics, sources, daytime (sea-breeze) and night-time (land-breeze) variations of carbonaceous and water-soluble ionic components in PM10 (<10 µm particulate matter) aerosols from the east coast (Chennai city) of tropical India. Elemental and organic carbon (EC and OC) were found to be higher in winter when air masses were delivered from the northern part of India covered by the Indo-Gangetic-Plains whereas lower concentrations were observed during summer and monsoon associated with marine air masses. Sea salts (Na+ and Cl–), dust (Ca2+ and Mg2+) and nitrates (NO3–) were found to be highest in monsoon, suggesting these species may be co-transported over the sampling site with marine air masses. Using air mass back-trajectory analysis, linear relationships between chemical species and specific mass ratios, we demonstrate that east coast urban aerosols are strongly influenced by aged anthropogenic sources including biomass burning in winter and post monsoon while aged marine emissions mixed with local pollutants (dust and vehicular) are important in monsoon and summer. Further, the mesoscale phenomenon was reflected in measured chemical constituents during the study period. Positive-matrix-factorisation (PMF) analysis confirmed that OC aerosols are largely attributable to chemically aged anthropogenic (53 % in the day and 39 % in the night) and combustion-derived (17 % and 39 %) sources in winter and sea salts mixed with dust and vehicular emissions (61 % and 52 %) during monsoon. These important insights about the sources and formation processes of organic aerosols will help in understanding the formation of atmospheric brown clouds over south Asia.

The quantitative source apportionment of heavy metals in peri-urban agricultural soils with UNMIX and input fluxes analysis

The intensive human activities are the major cause of heavy metals pollution in suburban farmland, which poses threats to soil environment and safety of agricultural products. The combination of spatial analysis (SA), principal component analysis (PCA), input fluxes analysis (IFA) and UNMIX model have precisely analyzed the sources and relative contribution of heavy metals from each source. The results revealed that average contents of Cr, Ni, Cu, Zn, Pb and Cd were 37.82, 13.65, 17.93, 93.78, 48.84 and 0.24 mg kg −1 , respectively. The spatial distribution indicated that parent materials, industrial activities and traffic emissions had significant effects on contents of heavy metals in topsoil. According to UNMIX model, the contribution rates of soil parent material, industrial/ traffic emissions, and agricultural activities to heavy metals in soil were 49.15%, 35.00% and 15.85% respectively. Which indicated largest contribution of natural sources, but input of human activities including industry, transportation and agriculture could not be ignored. The input fluxes analysis (IFA) reveals that atmospheric deposition was main source of heavy metals in soil, followed by fertilizer and irrigation. This study has presented reliable methods for analysis of sources of heavy metals in suburban farmland soil. The combination of UNMIX and IFA can accurately identify and quantify pollution sources. • UNMIX and input fluxes analysis were combined for source apportionment of heavy metals. • Heavy metals in soil mainly come from natural sources, industrial and traffic emissions, and agricultural activities. • UNMIX can be successfully applied for sources apportionment of heavy metals in soil.

Non-methane hydrocarbon (NMHC) fingerprints of major urban and agricultural emission sources for use in source apportionment studies

Abstract. In complex atmospheric emission environments such as urban agglomerates, multiple sources control the ambient chemical composition driving air quality and regional climate. In contrast to pristine sites, where reliance on single or a few chemical tracers is often adequate for resolving pollution plumes and source influences, the comprehensive chemical fingerprinting of sources using non-methane hydrocarbons (NMHCs) and the identification of suitable tracer molecules and emission ratios becomes necessary. Here, we characterise and present chemical fingerprints of some major urban and agricultural emission sources active in South Asia, such as paddy stubble burning, garbage burning, idling vehicular exhaust and evaporative fuel emissions. A total of 121 whole air samples were actively collected from the different emission sources in passivated air sampling steel canisters and then analysed for 49 NMHCs (22 alkanes, 16 aromatics, 10 alkenes and one alkyne) using thermal desorption gas chromatography flame ionisation detection. Several new insights were obtained. Propane was found to be present in paddy stubble fire emissions (8 %), and therefore, for an environment impacted by crop residue fires, the use of propane as a fugitive liquefied petroleum gas (LPG) emission tracer must be done with caution. Propene was found to be ∼ 1.6 times greater (by weight) than ethene in smouldering paddy fires. Compositional differences were observed between evaporative emissions of domestic LPG and commercial LPG, which are used in South Asia. While the domestic LPG vapours had more propane (40 ± 6 %) than n-butane (19 ± 2 %), the converse was true for commercial LPG vapours (7 ± 6 % and 37 ± 4 %, respectively). Isoprene was identified as a new tracer for distinguishing paddy stubble and garbage burning in the absence of isoprene emissions at night from biogenic sources. Analyses of source-specific inter-NMHC molar ratios revealed that toluene/benzene ratios can be used to distinguish among paddy stubble fire emissions in the flaming (0.38 ± 0.11) and smouldering stages (1.40 ± 0.10), garbage burning flaming (0.26 ± 0.07) and smouldering emissions (0.59 ± 0.16), and traffic emissions (3.54 ± 0.21), whereas i-pentane ∕ n-pentane can be used to distinguish biomass burning emissions (0.06–1.46) from the petrol-dominated traffic and fossil fuel emissions (2.83–4.13). i-butane ∕ n-butane ratios were similar (0.20–0.30) for many sources and could be used as a tracer for photochemical ageing. In agreement with previous studies, i-pentane, propane and acetylene were identified as suitable chemical tracers for petrol vehicular and evaporative emissions, LPG evaporative and vehicular emissions and flaming-stage biomass fires, respectively. The secondary pollutant formation potential and human health impact of the sources was also assessed in terms of their hydroxyl radical (OH) reactivity (s−1), ozone formation potential (OFP; gO3/gNMHC) and fractional benzene, toluene, ethylbenzene and xylenes (BTEX) content. Petrol vehicular emissions, paddy stubble fires and garbage fires were found to have a higher pollution potential (at ≥95 % confidence interval) relative to the other sources studied in this work. Thus, many results of this study provide a new foundational framework for quantitative source apportionment studies in complex emission environments.

Fingerprinting characterization of sedimentary PAHs and black carbon in the East China Sea using carbon and hydrogen isotopes

In this study, we present the application of a dual-isotope approach for the source apportionment of polycyclic aromatic hydrocarbons (PAHs) and black carbon (BC) in the East China Sea (ECS). The δ13C and δ2H isotope signatures of the PAHs were determined from surface sediments collected from the ECS. A Bayesian Markov chain Monte Carlo (MCMC) model was used to the environmental source identifications with dual-isotope PAHs data. The results indicate that the coal combustion source is predominant (with average of 41%) in the ECS. Liquid fossil fuels combustion, biomass combustion, and petrogenic sources account for 23%, 20%, and 12% of the total PAH burden, respectively. Additionally, we also determine the stable and radio carbon isotopes (δ13C and Δ14C) of total BC in sediment samples of the ECS. The results demonstrate the quantitative source apportionments for different sources, reflecting the contributions of fossil fuels (coal combustion and petroleum-related emissions), biomass (C3 and C4 plants) combustion, and rock-weathering sources. The fossil combustion in BC accounts for 67%, with 23% for biomass sources, meanwhile the rock weathering source in BC is an average of 10%. These results show a remarkable similarity and extensive homologies at source apportionment of PAHs and BC in the ECS, even though some differences in source mechanisms and processes. These findings on the environmental source apportionment will provide a reference for improved emission inventories, and will help to provide guidance for the efforts to mitigate environmental pollution in the coastal areas and marginal sea.

Quantitative source identification and apportionment of heavy metals under two different land use types: comparison of two receptor models APCS-MLR and PMF.

At present, many researchers are increasingly aware of the importance of using models to identify heavy metal (HM) pollution sources. However, on the performance and application of different source identification models to HMs under different land use types had been studied little. In this study, comparison of absolute principal component scores-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models and their application characteristics in identifying pollution sources were carried out by using 11 HMs in Zhongwei City farmland and Shizuishan industrial park, Ningxia. The results indicated that HM pollution in farmland mainly came from pesticides, fertilizers, and deposition of the Yellow River, while the pollution in industrial park mainly originated from atmospheric deposition and various industrial productions. The APCS-MLR model had the problem of less identification sources and the difficulty to explain the complex pollution, while the PMF model not only identified more pollution sources, but also distinguished heavy metal-related sources for two different land use types and different industrial production conditions. It is of great significance the formulation of agricultural-related pesticides' and chemical fertilizers' rational use and various industrial production-related raw materials put in and emission control strategies.

Quantitative source apportionment of heavy metal(loid)s in the agricultural soils of an industrializing region and associated model uncertainty

Heavy metal(loid)s are natural constituents of the Earth’s crust, and apportionment of their sources in surface soils is a challenging task. This study evaluated the application of positive matrix factorization (PMF) model, assisted with regression modeling and geospatial mapping, in the quantitative source apportionment of heavy metal(loid)s in the agricultural soils of Handan, a region covering >12,000 km2. Obvious enrichment of As, Cd, Cu, Pb, and Zn was found in the surface soils, with Cd alone accounted for 73 % of the overall potential ecological risk. PMF model revealed that Cd (56.9 %) and Pb (47.8 %) in the region’s agricultural soils were predominantly contributed by industrial sources, Fe (71.8 %), Cr (60.0 %), V (52.9 %), Cu (50.7 %), Ni (42.2 %), and Mn (41.4 %) were primarily of lithogenic origin, while Co (54.1 %), As (42.9 %), and Zn (40.0 %) mainly came from the mixed sources of natural background, agricultural sources, and vehicle emissions. Uncertainty analysis showed that the contributions of pollution sources to the soil heavy metal(loid)s estimated by PMF model had considerable variations. While quantitative source apportionment of heavy metal(loid)s in soils could be achieved with PMF based on their spatial distributions, combination with emission inventory and reactive transport are probably necessary to obtain more accurate results.

Geostatistical mapping and quantitative source apportionment of potentially toxic elements in top- and sub-soils: A case of suburban area in Beijing, China

Abstract The risk assessment and source identification for potentially toxic elements (PTEs) in soils, particularly agricultural soils from megacities, are significant for environmental protection and pollution control. In this study, an intensive sampling (4127 topsoil samples and 994 subsoil samples) was conducted in the Shunyi District, Beijing, which is a suburban area with extensive cropland cover and has been impacted by the megacity over several decades. Concentrations and distributions of 8 PTEs, including V, Cr, Ni, As, Cd, Zn, Pb and Hg, were determined, and their possible sources were quantitatively assessed by principal component analysis (PCA), redundancy analysis (RDA), positive matrix factorization (PMF) analysis, and anthropogenic contribution ratio method. Among 8 PTEs, Zn, V and Cr exhibited significantly high concentrations in soils, with means of 68.29, 68.19 and 52.13 mg/kg, respectively, followed by Pb (23.84 mg/kg), Ni (22.91 mg/kg), As (8.30 mg/kg), Cd (0.15 mg/kg) and Hg (0.05 mg/kg). RDA and PCA demonstrated that the rock weathering was a significant source of V, Cr, Ni and As, and the local emissions and atmospheric deposition respectively contributed most of Cd, Zn and Pb, and of Hg in soils. This source category was confirmed the spatial variations of anthropogenic contribution ratios to individual PTEs. PMF results showed that the local emissions contributed 96.3% of Cd, 44.4% of Zn and 32.0% of Pb in soils, and the atmospheric source carrying urban pollutants amounted to 78.7–80.2% of Hg. In this case, several effective analysis methods have been successfully applied to quantify the impact of a megacity to PTEs in suburban soils. These results improve understanding of the contamination status of PTEs in suburban soils from Beijing megacity, and provide basis for policymaker regarding environmental protection and pollution control.

Positive matrix factorization on source apportionment for typical pollutants in different environmental media: a review.

A bibliometric analysis of published papers with the key words "positive matrix factorization" and "source apportionment" in 'Web of Science', reveals that more than 1000 papers are associated with this research and that approximately 50% of these were produced in Asia. As a receptor-based model, positive matrix factorization (PMF) has been widely used for source apportionment of various environmental pollutants, such as persistent organic pollutants (POPs), heavy metals, volatile organic compounds (VOCs) as well as inorganic cations and anions in the last decade. In this review, based on the papers mainly from 2008 to 2018 that focused on source apportionment of pollutants in different environmental media, we provide a comparison and summary of the source categories of typical environmental pollutants, with a special focus on polycyclic aromatic hydrocarbons (PAHs), apportioned using PMF. Based on the statistical average, coal combustion and vehicular emission, are shown to be the two most common sources of PAHs, and contribute much more to emissions than other sources, such as biomass burning, biogenic sources and waste incineration. Heavy metals were mainly from agricultural activities, industrial and vehicular emissions and mining activities. Quantitative source apportionment on pollutants such as VOCs and particulate matter were also apportioned, showing a prominent contribution from fossil-fuel combustion. We conclude that, aside from natural sources, abatement strategies should be focused on changes in energy structure and industrial activities, especially in China. Source apportionment of typical POPs including polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs), polychlorinated biphenyls (PCBs), halogenated flame retardants (HFRs) and perfluorinated compounds (PFCs) is less comprehensive and further study is required.

Source apportionment of volatile organic compounds in the northwest Indo-Gangetic Plain using a positive matrix factorization model

Abstract. In this study we undertook quantitative source apportionment for 32 volatile organic compounds (VOCs) measured at a suburban site in the densely populated northwest Indo-Gangetic Plain using the US EPA PMF 5.0 model. Six sources were resolved by the PMF model. In descending order of their contribution to the total VOC burden these are “biofuel use and waste disposal” (23.2 %), “wheat-residue burning”(22.4 %), “cars” (16.2 %), “mixed daytime sources”(15.7 %) “industrial emissions and solvent use”(11.8 %), and “two-wheelers” (8.6 %). Wheat-residue burning is the largest contributor to the total ozone formation potential (32.4 %). For the emerging contaminant isocyanic acid, photochemical formation from precursors (37 %) and wheat-residue burning (25 %) were the largest contributors to human exposure. Wheat-residue burning was also the single largest source of the photochemical precursors of isocyanic acid, namely, formamide, acetamide and propanamide, indicating that this source must be most urgently targeted to reduce human concentration exposure to isocyanic acid in the month of May. Our results highlight that for accurate air quality forecasting and modeling it is essential that emissions are attributed only to the months in which the activity actually occurs. This is important for emissions from crop residue burning, which occur in May and from mid-October to the end of November. The SOA formation potential is dominated by cars (36.9 %) and two-wheelers (21.1 %), which also jointly account for 47% of the human class I carcinogen benzene in the PMF model. This stands in stark contrast to various emission inventories which estimate only a minor contribution of the transport sector to the benzene exposure (∼10 %) and consider residential biofuel use, agricultural residue burning and industry to be more important benzene sources. Overall it appears that none of the emission inventories represent the regional emissions in an ideal manner. Our PMF solution suggests that transport sector emissions may be underestimated by GAINSv5.0 and EDGARv4.3.2 and overestimated by REASv2.1, while the combined effect of residential biofuel use and waste disposal emissions as well as the VOC burden associated with solvent use and industrial sources may be overestimated by all emission inventories. The agricultural waste burning emissions of some of the detected compound groups (ketones, aldehydes and acids) appear to be missing in the EDGARv4.3.2 inventory.

Atmospheric particulate matters in an Indian urban area: Health implications from potentially hazardous elements, cytotoxicity, and genotoxicity studies

The nature of the atmospheric particulate matters (PMs) varies depending on their sizes and their origin from different activities in the background environment. These PMs are associated with potentially hazardous elements (PHEs) such as organic compounds (e.g. Polyaromatic Hydrocarbons) that can be harmful to health. The main objective of this work is the identification and investigation of the toxicological aspects of PHEs in PMs during pre-monsoon and post-monsoon season in an urban area of Northeast region (NER) of India. In the course of the study, the 24 -hs average concentrations of PMs were detected to be more than two-times higher than the Indian standard limit (NAAQ, category) which indicates poor air quality in both the seasons around the sampling sites. This study demonstrates that the concentrations of PM-bound PAHs are mutagenic and that the Excess Cancer Risks exceed the USEPA standard limits. PMs cause cytotoxicity and can also induce genotoxicity to human health analyzed by cell culture and gel electrophoresis. This study helps to promote research to evaluate the PMs bound PHEs toxicity in diverse human cell lines and also their relationship with climatic factors as well as quantitative source apportionment for mitigation purposes.

Geochemical characteristics, partitioning, quantitative source apportionment, and ecological and health risk of heavy metals in sediments and water: A case study in Shadegan Wetland, Iran

Heavy metal concentrations were investigated in water and sediments of Shadegan Wetland southwest of Iran to assess the fate, partitioning, and risk assessment and also to quantify the sources of heavy metals using MLR-APCS (multiple linear regression of absolute principal component scores) receptor model. The relatively high values of Kd (partition coefficient) for Pb, Zn, Ni, As, and V revealed their affinity for being enriched in sediments while Sb, Mo, and Se exhibited greater partitioning towards water. Enrichment factors of Se, Cd, Pb, Mo, Co, Zn, and Cu revealed significant to moderate contamination and should be of some concern. Application of the modified ecological risk index (MRI) revealed sediments moderate to high risk. Hazard index values for Hg were found less than the safe level. MLR-APCS model indicated that anthropogenic sources in sediments were responsible for 80.9%, 73.2%, 73.1%, 88.6% and 74.2% of Se, Mo, Hg, Pb, and Zn, respectively.

Quantitative source apportionment of water solutes and CO2 consumption of the whole Yarlung Tsangpo River basin in Tibet, China.

The Tibetan Plateau is known as the "Asian water tower," and the Yarlung Tsangpo (YT) River is the largest river that originates in and flows across the southern Tibetan Plateau. Although the solute source of YT River has been extensively and qualitatively analyzed, there is a lack of the quantitative analysis for the whole basin and seasonal variation of hydrochemical characteristics. Here, 212 samples obtained in the mainstream and tributary of YT River in different (wet, normal, and dry) periods were used for the solute apportionment using the mass balance model. The results showed that the solutes in YT River water were mainly derived from the carbonate and silicate rock weathering that accounts 42.2% and 26.9% in the total solute source, respectively, as the complex geological conditions in the basin. A part of the ions (7.5%) was also originated from the atmospheric precipitation as the abundant rainfall in the wet period. Meanwhile, the contribution of solute sources had no significantly seasonal variation in the upstream, whereas it had significantly seasonal variation in the downstream with the tropical climate and heavy rainfall. Importantly, the rock weathering of the basin could consume so much atmospheric CO2 (0.54% of the consumption at global with the only 0.16% of the global surface area) that could mitigate the global warming, which followed an increasing trend from upstream to downstream. The quantitative analysis of the solute source for YT River fills in the gaps in the chemically characteristic cognition of the basin. It is beneficial for the water resource management for the Asian. The proportion of solute sources in the YT River and its tributaries for wet (W), normal (N), and dry (D) periods.