Recent work has identified the presence of humic-like substances (HULIS) in ambient fine particulate matter (PM
) in Beijing, China and that residential coal combustion as well as biomass burning are ...significant contributors to its presence. These results were based on the characterization of emissions from representative stoves and modeling of the aerosol with the Community Multiscale Air Quality (CMAQ) chemical transport model. The CMAQ source apportionment estimated that residential coal and biofuel burning and secondary aerosol formation were important annual sources of ambient HULIS, contributing 47.1%, 15.1%, and 38.9%, respectively. In this study, chemical composition data including concentrations of water-soluble organic carbon and HULIS across four seasons during 2012-2013 were analyzed with positive matrix factorization (PMF) to provide a complementary source apportionment. The PMF results indicate that the identified sources were Traffic, Biomass Burning, Nitrate/Sulfate, Incineration, Sulfate, Coal Combustion/Ammonium Chloride, Residential Coal/Biofuel Combustion, and Road Dust/Soil with mass contributions (fractions) to PM
of 12.35 (10.4%), 8.70 (8.9%), 24.51 (22.4%), 5.64 (7.2%), 25.14 (24.5%), 7.10 (6.2%), 14.18 (15.4%), and 5.33 μg/m
(5.0%), respectively. The contributions to the observed HULIS concentrations were 0.63 (10.9%), 0.38 (6.4%), 0.07 (1.7%), 0.00 (0%), 1.12 (28.8%), 0.00 (0%), 1.50 (52.2%), and 0.01 μg/m
(0.3%), respectively. These PMF modeling results were in reasonable agreement with the CMAQ values supporting the attribution of significant amounts of primary HULIS to residential coal and biofuel combustion. Currently, efforts are underway in China to replace solid fuel combustion for heating and cooking with natural gas and electricity by 2020. Thus, future studies should be able to see substantial reductions in both PM
and HULIS in the near term future.
PM2.5 pollution events are often happened in urban agglomeration locates in mountain-basin regions due to the complex terra and intensive emissions. Source apportionment is essential for identifying ...the pollution sources and important for developing local mitigation strategies, however, it is influenced by regional transport. To understand how the regional transport influences the atmospheric environment of a basin, we connected the PM2.5 source contributions estimated by observation-based receptor source apportionment and the regional contributions estimated by a tagging technology in the comprehensive air quality model with extensions (CAMx) via an artificial neural network (ANNs). The result shows that the PM2.5 in Xi'an was from biomass burning, coal combustion, traffic related emissions, mineral dust, industrial emissions, secondary nitrate and sulfate. 48.8 % of the PM2.5 in study period was from Xi'an, then followed by the outside area of Guanzhong basin (28.2 %), Xianyang (14.6 %) and Weinan (5.8 %). Baoji and Tongchuan contributed trivial amount. The sensitivity analysis showed that the transported PM2.5 would lead to divergent results of source contributions at Xi'an. The transported PM2.5 from the outside has great a potential to alter the source contributions implying a large uncertainty of the source apportionment introduced when long-range transported pollutants arrived. It suggests that a full comprehension on the impacts of regional transport can lower the uncertainty of the local PM2.5 source apportionment and reginal collaborative actions can be of great use for pollution mitigation.
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•Local emission and the pollutants from the outside of GB were the major contribution regions to the PM2.5 in Xi’an.•Transported PM2.5 from different regions would change the results of source contributions in a basin city at different degree.•Source apportionment in Xi’an was more sensitive to the quantity of PM2.5 transported from the outside of the basin.
Delhi is one of the most polluted cities worldwide and a comprehensive understanding and deeper insight into the air pollution and its sources is of high importance. We report 5 months of highly ...time-resolved measurements of non-refractory PM2.5 and black carbon (BC). Additionally, source apportionment based on positive matrix factorization (PMF) of the organic aerosol (OA) fraction is presented. The highest pollution levels are observed during winter in December/January. During that time, also uniquely high chloride concentrations are measured, which are sometimes even the most dominant NR-species in the morning hours. With increasing temperature, the total PM2.5 concentration decreases steadily, whereas the chloride concentrations decrease sharply. The concentrations measured in May are roughly 6 times lower than in December/January. PMF analysis resolves two primary factors, namely hydrocarbon-like (traffic-related) OA (HOA) and solid fuel combustion OA (SFC-OA), and one or two secondary factors depending on the season. The uncertainties of the PMF analysis are assessed by combining the random a-value approach and the bootstrap resampling technique of the PMF input. The uncertainties for the resolved factors range from ±18% to ±19% for HOA, ±7% to ±19% for SFC-OA and ±6 % to ±11% for the OOAs. The average correlation of HOA with equivalent black carbon from traffic (eBCtr) is R2 = 0.40, while SFC-OA has a correlation of R2 = 0.78 with equivalent black carbon from solid fuel combustion (eBCsf). Anthracene (m/z 178) and pyrene (m/z 202) (PAHs) are mostly explained by SFC-OA and follow its diurnal trend (R2 = 0.98 and R2 = 0.97). The secondary oxygenated aerosols are dominant during daytime. The average contribution during the afternoon hours (1 pm–5 pm) is 59% to the total OA mass, with contributions up to 96% in May. In contrast, the primary sources are more important during nighttime: the mean nightly contribution (22 pm–3 am) to the total OA mass is 48%, with contributions up to 88% during some episodes in April.
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•Over 65% of the daily PM2.5 concentrations exceed the national air quality standard.•Exceptionally high chloride contribution during early mornings in the cold period•Significant solid fuel combustion contribution throughout the full campaign•PMF uncertainty assessment
Identifying PM2.5 sources is crucial for effective air quality management and public health. This research used the Multilinear Engine (ME-2) model to analyze PM2.5 from 515 EPA Chemical Speciation ...Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites across the U.S. from 2000 to 2019. The U.S. was divided into nine regions for detailed analysis. A total of seven source types (tracers) were resolved across the country: (1) Soil/Dust (Si, Al, Ca and Fe); (2) Vehicle emissions (EC, OC, Cu and Zn); (3) Biomass/wood burning (K); (4) Heavy oil/coal combustion (Ni, V, Cl and As); (5) Secondary sulfate (SO42-); (6) Secondary nitrate (NO3-) and (7) Sea salt (Mg, Na, Cl and SO42-). Furthermore, we extracted and calculated secondary organic aerosols (SOA) based on the secondary sulfate and nitrate factors. Notably, significant reductions in secondary sulfate, nitrate, and heavy oil/coal combustion emissions reflect recent cuts in fossil-fueled power sector emissions. A decline in SOA suggests effective mitigation of their formation conditions or precursors. Despite these improvements, vehicle emissions and biomass burning show no significant decrease, highlighting the need for focused control on these persistent pollution sources for future air quality management.
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•A 20-year study identifies key PM2.5 pollution sources across the U.S. using an advanced Multilinear Engine (ME-2) model.•Substantial emission reductions achieved in the fossil fuel sector indicate the effectiveness of pollution control measures.•No significant decrease in vehicle emissions and biomass burning highlights the need for focused pollution management.•Future efforts aim to link emission sources with health outcomes, enhancing air quality management policies.
Regional transport plays an important role in the serious PM
pollutions in the Beijing-Tianjin-Hebei (BTH) region, China. Practical regional joint emission control strategies require quantitative ...assessments of the transport contribution among cities and regions. The Community Multiscale Air Quality model equipped with the Integrated Source Apportionment Model is used to simulate the contributions from 5 major emission sectors in 13 cities of the BTH region, and 4 surrounding provinces outside BTH for the year 2014. Annual averaged local contribution ranges from 32% to 63% for the 13 cities in the BTH region, where secondary components contributing more than primary components. Regional contribution ratio becomes larger and the transport distance longer in July and October than in January and March. For Beijing, local contributions are 62% and 69% in January and March respectively, and the regional transports are mainly from nearby cities such as Zhangjiakou, Baoding and Langfang. In July and October, local contributions in Beijing are only 33% and 38% respectively, and a large range of regions in the south have substantial contributions, where Shandong Province and Henan Province contribute 3.6-5.3 μg/m
. Analysis of daily contributions suggests that regional transport is stronger under higher PM
concentrations. During heavy pollution, local emissions in Beijing contribute 61%, 49%, 23% and 25% in January, march, July and October respectively, while during the clean days, the ratios are 88%, 88%, 76% and 57% respectively. Southerly regional transport during the rising phase of "saw tooth" pattern might be enhanced by weak cold high pressure and its easterly, northerly moving path. Among the major emission sectors, in winter, local domestic combustion is the most important source for Beijing, Tianjin and Shijiazhuang. In summer, transportation and domestic combustion are two important local sources for Beijing, while joint control in other cities should focus on industry.
PM2.5 have been related to various adverse health effects, mainly due to their ability to penetrate deeply and to convey harmful chemical components, such as metals inside the body. In this work, ...PM2.5 were sampled at Saint-Omer, a medium-sized city located in northern France, in March–April 2011 and analyzed for their total carbon, water-soluble ions, major and trace elements. More specifically, the origin of 15 selected elements was examined using different tools including enrichment factors, conditional bivariate probability function (CBPF) representations, diagnostic ratios and receptor modelling. The results indicated that PM2.5 metal composition is affected by both emissions of a local glassmaking factory and an integrated steelworks located at a distance of 35 km from the sampling site. For the first time, diagnostic ratios were proposed for the glassmaking activity. Therefore, metals in PM2.5 could be attributed to the following anthropogenic sources: (i) local glassmaking industry for Sn, As, Cu and Cr, (ii) distant integrated steelworks for Ag, Fe, Cd, Mn, Rb and Pb, (iii) heavy fuel oil combustion for Ni, V and Co and (iv) non-exhaust traffic for Zn, Pb, Mn, Sb, and Cu. The impact of such sources on metal concentrations in PM2.5 was assessed using a constrained receptor model. Despite their low participation to PM2.5 concentration (2.7%), the latter sources were found as the main contributors (80%) to the overall concentration levels of the 15 selected elements in PM2.5.
•Influence of steelworks emissions on metal concentrations in PM2.5 35 km away.•4 sources explained 2.7% of the PM2.5 but also 80% of the metal concentration.•Diagnostic ratios for the glassmaking activity were determined for the first time.•Influence of glassmaking factory on Sn, As, Cr and Cu atmospheric concentrations.
Contributions to 15 trace elements in airborne particulate matter with aerodynamic diameters <2.5μm (PM
) in China from five major source sectors (industrial sources, residential sources, ...transportation, power generation and windblown dust) were determined using a source-oriented Community Multiscale Air Quality (CMAQ) model. Using emission factors in the composite speciation profiles from US EPA's SPECIATE database for the five sources leads to relatively poor model performance at an urban site in Beijing. Improved predictions of the trace elements are obtained by using adjusted emission factors derived from a robust multilinear regression of the CMAQ predicted primary source contributions and observation at the urban site. Good correlations between predictions and observations are obtained for most elements studied with R>0.5, except for crustal elements Al, Si and Ca, particularly in spring. Predicted annual and seasonal average concentrations of Mn, Fe, Zn and Pb in Nanjing and Chengdu are also consistently improved using the adjusted emission factors. Annual average concentration of Fe is as high as 2.0μgm
with large contributions from power generation and transportation. Annual average concentration of Pb reaches 300-500ngm
in vast areas, mainly from residential activities, transportation and power generation. The impact of high concentrations of Fe on secondary sulfate formation and Pb on human health should be evaluated carefully in future studies.
In view of upcoming more stringent air quality limits and the ambition to align with the WHO guidelines, nitrogen dioxide (NO2) pollution from traffic and other sources will remain a problem in the ...EU. To assess the impact of traffic measures and emission reductions in other sectors on NO2-concentrations, an EU-wide high-resolution NO2 source apportionment web-application was developed. The application allows users to define scenarios in a user-friendly way and quickly visualize the NO2-concentrations at measurement stations and in cities. The user can configure a new Euro 7/VII emission standard and additionally define urban access regulations scenarios in cities. To capture the spatial scales of NO2 pollution, the SHERPA source-receptor model was used in combination with the QUARK kernel dispersion model. The first model considers long-distance impacts, the latter considers the strong concentration gradients close to roads. This paper focuses on the methodology, a follow-up paper describes the web-application.
•We present a method for fast sectoral and spatial NO2 source apportionment.•The road transport sector is considered in high detail and at 100-m resolution.•The impact of a new vehicle emission standard for NOx can be simulated.•The effect of urban access regulations can be simulated in 948 European cities.•NO2 concentration effects are visualized at measurement stations and over cities.
Nowadays, micropollutants such as pharmaceuticals, pesticides and personal care products can be found ubiquitously in the anthropogenically influenced water cycle. As micropollutants have virtually ...no natural background concentrations they are significantly more sensitive in detecting processes and flow paths than classic inorganic tracers and indicators and at the same time they are often highly source specific. Therefore, using micropollutants as environmental indicators for anthropogenic activities is a common and frequently applied method today. As they interact in many ways with environmental matrices they can be used for source apportionment as well as to estimate flow paths and residence times in waterbodies. This review gives a systematic overview over the large variety of micropollutants used as indicators in the aquatic environment over the last decades together with the prerequisites on their use. Their application is subdivided into their qualitative (compound presence or absence) and quantitative (volume flows) use and shows the numerous possibilities from gaining basic information on the water regime up to advanced applications such as wastewater-based epidemiology.
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•Anthropogenic micropollutants (MPs) are ubiquitously distributed in water bodies.•MPs are highly selective and sensitive indicators for numerous sources and processes.•MPs can be a vital tool for the evolving field of environmental forensics.•A systematic overview on qualitative and quantitative use of MPs is presented.
Urban Parks are important places for residents to engage in outdoor activities, and whether heavy metal(loid)s (HMs) in park soils are harmful to human health has aroused people's concern. A total of ...204 topsoil samples containing nine HMs were collected from 78 urban parks of Shanghai in China, and used to assess the health risks caused by HMs in soils. The results revealed that the Hg, Cd and Pb were the main enriched pollutants and posed higher ecological risks than the other HMs. Four HM sources (including natural sources, agricultural activities, industrial production and traffic emissions) were identified by combining the Positive matrix factorization model and Correlation analysis, with the contribution rate of 48.24%, 7.03%, 13.04% and 31.69%, respectively. The assessment of Probabilistic health risks indicated that the Non-carcinogenic risks for all populations were negligible. However, the Total carcinogenic risk cannot be negligible and children were more susceptible than adults. The assessment results of source-oriented health risks showed that industrial production and traffic emissions were estimated to be the most important anthropogenic sources of health risks for all populations. Our results provide scientific support needed for the prevention and control of HM pollution in urban parks.
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•Hg, Cd and Pb were identified as the most polluted HMs in the study area.•Four HM sources were identified by combining PMF model and correlation analysis.•The PMF-HRA model was developed to assess the source-oriented health risks.•The NCR for all populations was negligible, while the TCR cannot be negligible.
