Receptor modeling application framework for particle source apportionment

The effects of fine particulate matter on the blood-testis barrier and its potential mechanisms

With the rapid expansion of industrial scale, an increasing number of fine particulate matter (PM2.5) has bringing health concerns. Although exposure to PM2.5 has been clearly associated with male reproductive toxicity, the exact mechanisms are still unclear. Recent studies demonstrated that exposure to PM2.5 can disturb spermatogenesis through destroying the blood-testis barrier (BTB), consisting of different junction types, containing tight junctions (TJs), gap junctions (GJs), ectoplasmic specialization (ES) and desmosomes. The BTB is one of the tightest blood-tissue barriers among mammals, which isolating germ cells from hazardous substances and immune cell infiltration during spermatogenesis. Therefore, once the BTB is destroyed, hazardous substances and immune cells will enter seminiferous tubule and cause adversely reproductive effects. In addition, PM2.5 also has shown to cause cells and tissues injury via inducing autophagy, inflammation, sex hormones disorder, and oxidative stress. However, the exact mechanisms of the disruption of the BTB, induced by PM2.5, are still unclear. It is suggested that more research is required to identify the potential mechanisms. In this review, we aim to understand the adverse effects on the BTB after exposure to PM2.5 and explore its potential mechanisms, which provides novel insight into accounting for PM2.5-induced BTB injury.

Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements

Based on the data of the State of Global Air (2020), air quality deterioration in Thailand has caused ~32,000 premature deaths, while the World Health Organization evaluated that air pollutants can decrease the life expectancy in the country by two years. PM2.5 was collected at three air quality observatory sites in Chiang-Mai, Bangkok, and Phuket, Thailand, from July 2020 to June 2021. The concentrations of 25 elements (Na, Mg, Al, Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Br, Sr, Ba, and Pb) were quantitatively characterised using energy-dispersive X-ray fluorescence spectrometry. Potential adverse health impacts of some element exposures from inhaling PM2.5 were estimated by employing the hazard quotient and excess lifetime cancer risk. Higher cancer risks were detected in PM2.5 samples collected at the sampling site in Bangkok, indicating that vehicle exhaust adversely impacts human health. Principal component analysis suggests that traffic emissions, crustal inputs coupled with maritime aerosols, and construction dust were the three main potential sources of PM2.5. Artificial neural networks underlined agricultural waste burning and relative humidity as two major factors controlling the air quality of Thailand.

Trace elements and microbial community composition associated with airborne PM2.5 in wetlands: A case study in Tablas de Daimiel National Park

Tablas de Daimiel National Park (TDNP) is one of the most important wetlands in the Iberian Peninsula. Due to its location near various cities and new industries focused on agricultural waste revalorization, we investigated concurrently the concentrations of particulate matter 2.5 (PM2.5) mass, trace element composition, and associated microbial communities (bacteria and fungi) during a year-long study. The goal of this study was to explore the dependencies among these physicochemical and microbiological parameters on a seasonal time scale. Additionally, we assessed meteorological conditions and back trajectories to shed light on atmospheric mechanisms and sources related to these elements. We found the variability of PM2.5 to be influenced by local meteorological parameters. Through the analysis of crustal enrichment factors (EFs), bivariate correlations, and air mass patterns, we determined that soil resuspension was the primary contributor to elevated metal concentrations in PM2.5 within the park, followed by other minor sources, such as traffic emissions and Sahara dust intrusions. The measured metal levels were used to calculate the ecological risk in the area, resulting in a low ecological risk index (RI) of 52. Shifts in microbial community structure were observed to be mainly driven by changes in air temperature and Cu concentration. The results from this study contribute to a better understanding of the environmental dynamics in TDNP. Taken together, our findings will aid in the development of effective strategies for its conservation and management.

Evaluating the effectiveness of low-sulphur marine fuel regulations at improving urban ambient PM2.5 air quality: Source apportionment of PM2.5 at Canadian Atlantic and Pacific coast cities with implementation of the North American Emissions Control Area

Ambient fine size fraction particulate matter (PM2.5) sources were resolved by positive matrix factorization at two Canadian cities on the Atlantic and Pacific coast over the 2010-2016 period, corresponding to implementation of the North American Emissions Control Area (NA ECA) low-sulphur marine fuel regulations. Source types contributing to local PM2.5 concentrations were: ECA regulation-related (residual oil, anthropogenic sulphate), urban transportation and residential (gasoline, diesel, secondary nitrate, biomass burning, road dust/soil), industry (refinery, Pb-enriched), and largely natural (biogenic sulphate, sea salt). Anthropogenic sources accounted for approximately 80 % of PM2.5 mass over 2010-2016. Anthropogenic and biogenic sources of PM2.5-sulphate were separated and apportioned. Anthropogenic PM2.5-sulphate was approximately 2-3 times higher than biogenic PM2.5-sulphate prior to implementation of the NA ECA low-S marine fuel regulations, decreasing to 1-2 times higher after regulation implementation. Non-marine anthropogenic sources (gasoline, road dust, local industry factors) were shown to together contribute 38 % - 45 % of urban PM2.5. At both coastal cities, the residual oil and anthropogenic sulphate factors clearly reflected the effects of the low-S fuel regulations at reducing primary and secondary sulphur-related PM2.5 emissions. Comparing a pre-regulation and post-regulation period, residual oil combustion PM2.5 decreased by 0.24-0.25 μg/m3 (94%-95 % decrease) in both cities and anthropogenic sulphate PM2.5 decreased by 0.78 μg/m3 in Halifax (47 % decrease) and 0.71 μg/m3 in Burnaby (58 % decrease). Regulation-related PM2.5 across these factors decreased by approximately 1 μg/m3 after regulation implementation, providing a quantified lower estimate of the beneficial influence of the regulations on urban ambient PM2.5 concentrations. Further reductions in coastal city ambient PM2.5 may best consider air quality strategies that include multiple sources, including marine shipping and non-marine anthropogenic source types given this analysis found that marine vessel emissions remain an important source of urban ambient PM2.5.

Impact of COVID-19 restrictions on the dry deposition fraction of settleable particulate matter at three industrial urban/suburban locations in northern Spain

Ninety 24-h samples of the dry deposition fraction of settleable particulate matter (DSPM) were collected at one suburban industrial site ('EMA') and two urban industrial sites ('Lauredal' and 'Laboratory') in the western area of Gijón (North of Spain) from December 2019 to June 2020. The levels registered point to an environmental issue that should receive close attention from environmental authorities. Before lockdown restrictions due to COVID-19 were established, all samples collected at the EMA site exceeded 300 mg·m^-2·d^-1 (the Spanish limit value until 2002). Large amounts of DSPM were also registered at the Lauredal and Laboratory sites, maximum levels reaching 1039.2 and 672.7 mg·m^-2·d^-1, respectively. Seven metals were analysed in DSPM samples: Al, Ca, Fe, K, Mg, Mn and Na. Fe reached the highest values: 2473.4, 463.4 and 293.3 mg·m^-2·d^-1 (EMA, Lauredal and Laboratory sites, respectively). This study quantifies the reductions in the DSPM levels registered (on average, 97.2, 73.5 and 90.5% at the EMA, Lauredal and Laboratory sites, respectively) during the lockdown, which involved the restriction of population mobility and industrial activity. The influence of wind speed and its direction were also assessed to better understand the role of these restrictions in the observed reductions. The concentrations of all the metals in the DSPM were reduced by more than 75%, on average, except for K at the Laboratory and Lauredal sites. These decreases were much higher than those found by other authors for smaller fractions of the atmospheric particulate matter (PM10, PM2.5). The findings of the present study highlight the importance of DSPM in highly industrialized urban/suburban locations and indicate the direction that legal measures might take, given the influence of anthropogenic emissions.

Apportionment of Vehicle Fleet Emissions by Linear Regression, Positive Matrix Factorization, and Emission Modeling

Real-world emission factors for different vehicle types and their contributions to roadside air pollution are needed for air-quality management. Tunnel measurements have been used to estimate emission factors for several vehicle types using linear regression or receptor-based source apportionment. However, the accuracy and uncertainties of these methods have not been sufficiently discussed. This study applies four methods to derive emission factors for different vehicle types from tunnel measurements in Hong Kong, China: (1) simple linear regressions (SLR); (2) multiple linear regressions (MLR); (3) positive matrix factorization (PMF); and (4) EMission FACtors for Hong Kong (EMFAC-HK). Separable vehicle types include those fueled by liquefied petroleum gas (LPG), gasoline, and diesel. PMF was the most useful, as it simultaneously seeks source profiles and source contributions. Diesel-, gasoline-, and LPG-fueled vehicle emissions accounted for 52%, 10%, and 5% of PM2.5 mass, respectively, while ammonium sulfate (~20%), ammonium nitrate (6%), and road dust (7%) were also large contributors. MLR exhibited the highest relative uncertainties, typically over twice those determined by SLR. EMFAC-HK has the lowest relative uncertainties due to its assumption of a single average emission factor for each pollutant and each vehicle category under specific conditions. The relative uncertainties of SLR and PMF are comparable.

An Advanced PMF Model Based on Degradation Process for Pollutant Apportionment in Coastal Areas

With increasing stress posed to the marine ecosystem and coastal communities, prevention and control of coastal pollution becomes urgent and important, in which the identification of pollution sources is essential. Currently, the pollutant source apportionment in coastal areas is mainly based on receptor models, such as the positive matrix factorization (PMF) model. Nevertheless, these models still lack consideration of the changes of pollutant behaviors (e.g., the degradation of pollutants) which cause the differences in pollutant compositions. Subsequently, the source apportionment via receptor models only based on the monitoring data may not be consistent with the one in pollution sources. To fill this gap, a pollutant degradation model was firstly developed in this study. Accordingly, the degradation model was inversed to estimate the pollutant concentrations at their emitting sources, based on the monitoring concentration in the coastal area. Finally, the estimated concentrations were fed to the PMF model for pollutant source apportionment, advancing the PMF model with degradation process. To demonstrate the feasibility and accuracy of the developed model, a case study of source appointment was carried out based on the polycyclic aromatic hydrocarbons (PAHs) in the sediments of the Pearl River Estuary. The results indicated the same types of emission source identified by the original and advanced PMF models, which were oil spill, biomass and coal combustion, and traffic emission. Nevertheless, the contributions of sources were significantly varied between the two models. According to the analyses based on emission inventory, the offsets of the results from the original PMF model were −55.4%, 22.7%, and 42.2% for the emission sources of oil spill, biomass and coal combustion, and traffic emission, respectively. Comparatively, the offsets for the advanced PMF model narrowed down to −27.5%, 18.4%, and −4.4%. Therefore, the advanced PMF model is able to provide satisfactory source apportionment for organic pollutants in coastal areas, and thus further provide a scientific basis for marine pollution prevention and control.

Chemometric approach in environmental pollution analysis: A critical review

With the ever-increasing global population and industrialization, it has become a call of the hour to start taking care of the environment to balance the ecosystem. For this, effective monitoring and assessment are required, which involves collecting and measuring environmental details, temporal and spatial readings of environmental data, and parameters. However, assessment of the environment is very tedious as it includes monitoring target analytes, identifying their sources, and reporting, which invariably implies that detailed environmental monitoring would be an intricate and expensive process. The traditional protocols in environmental measures are often manual and time demanding, which makes it further difficult. Moreover, several changes also occur within the environment, which could be chemical, physical, or biological, and since these environmental impacts are often cumulative, it becomes difficult to measure an isolated system. Furthermore, the chances of skipping significant results and trends become high. Also, experimental data obtained from the environmental analysis are usually non-linear and multi-variant due to different associations among various contributing variables. Therefore, it is implied that accurate measurements and environment monitoring are not using traditional analytical protocols. Thus, the need for a chemometric approach in environmental pollution analysis becomes paramount due to the inherent limitations associated with the conventional approach of analyzing environmental datasets. Chemometrics has appeared as a potential technique, which enhances the particulars of the chemical datasets by using statistical and mathematical analysis methods to analyze chemical data beyond univariate analysis. Utilizing chemometrics to study the environmental data is a revolutionary idea as it helps identify the relationship between sources of contaminations, environmental drivers, and their impact on the environment. Hence, this review critically explores the concept of chemometrics and its application in environmental pollution analysis by briefly highlighting the idea of chemometrics, its types, applications, advantages, and limitations in the environmental domain. An attempt is also made to present future trends in applications of chemometrics in environmental pollution analysis.

Particulate Matter in Swine Barns: A Comprehensive Review

Particulate matter (PM) represents an air quality management challenge for confined swine production systems. Due to the limited space and ventilation rate, PM can reach relatively high concentrations in swine barns. PM in swine barns possesses different physical, chemical, and biological characteristics than that in the atmosphere and other indoor environments. As a result, it exerts different environmental and health effects and creates some unique challenges regarding PM measurement and mitigation. Numerous research efforts have been made, generating massive data and information. However, relevant review reports are sporadic. This study aims to provide an updated comprehensive review of swine barn PM, focusing on publications since 1990. It covers various topics including PM characteristics, sources, measurement methods, and in-barn mitigation technologies. As PM in swine barns is primarily of biological origins, bioaerosols are reviewed in great detail. Relevant topics include bacterial/fungal counts, viruses, microbial community composition, antibiotic-resistant bacteria, antibiotic resistance genes, endotoxins, and (1→3)-β-D-glucans. For each topic, existing knowledge is summarized and discussed and knowledge gaps are identified. Overall, PM in swine barns is complicated in chemical and biological composition and highly variable in mass concentrations, size, and microbial abundance. Feed, feces, and skins constitute the major PM sources. Regarding in-barn PM mitigation, four technologies (oil/water sprinkling, ionization, alternation of feed and feeders, and recirculating air filtration) are dominant. However, none of them have been widely used in commercial barns. A collective discussion of major knowledge gaps and future research needs is offered at the end of the report.

Size-segregated chemical source profiles and potential health impacts of multiple sources of fugitive dust in and around Bhopal, central India

PM_2.5 and PM₁₀ fugitive dust samples from multiple sources (construction, demolition, industrial, agricultural fields, and bare ground) were collected in triplicate for each size bin, from 18 distinct locations in and around Bhopal, central India. The dust samples were dried, sieved, and re-suspended in a chamber fitted with a suitable sampling system, to collect PM_2.5 and PM₁₀ samples onto Teflon and Quartz filters. The filters were subjected to gravimetric and chemical analyses. Trace elements, water-soluble ions, and thermal-optical carbon fractions were quantified using a variety of analyses. These species were then used to develop PM₁₀ and PM_2.5 chemical source profiles of the fugitive dust sources. As expected, crustal species were abundant in all source categories. For industrial dust, Fe contribution to mass in both size fractions was about 11.4% and above the upper continental crustal abundance. Further, the source profiles generated for each source were different from their counterparts in the US EPA SPECIATE database and profiles reported in literature. Thus, it will be useful to utilize profiles generated in this study to enhance receptor model performance for the study region. However, collinearity analysis of the profiles revealed that PM₁₀ agricultural and bare ground dust; and PM_2.5 construction and demolition dust profile pairs may not be separated by receptor models. Finally, a human health risk assessment revealed that construction and industrial dust may pose significant risk to the population. The Incremental Lifetime Cancer Risk (ILCR) metric revealed that adults (2 × 10^-5) and children (1 × 10^-5) were susceptible to cancer risk from exposure to metals in PM_2.5 fugitive dust. Further, children were more vulnerable than adults. This finding merits further investigation of oxidation state and solubility/bioavailability of Cr and Ni in fugitive dusts.

Assessment of surface water of Gulf of Kachchh, west coast of India: A chemometric approach

The present study is aimed at investigation of surface water quality of Gulf of Kachchh (GoK), Gujarat. The main objective of this study was to convert complex dataset of water quality parameters from GoK into comprehensive, simple and interpretable observations. Hence, physico-chemical parameters and nutrients of surface water from GoK were analyzed. Chemometric results indicated that oxygen, salinity, dissolved solids, nutrient and natural conditions were the factors that affected surface water quality. The water quality index was calculated to identify water quality classes to evaluate the spatio-seasonal trend in the study area. The results revealed that water quality was moderate in summer, worst in pre-monsoon and best in post-monsoon. The study also highlighted that Marine National Park (Central GoK) was observed to be comparatively in good condition with abundant marine biodiversity. Thus, the results of chemometric study of water quality parameters can be a valuable tool for government authorities for sustainable development of GoK.

A review of the main strategies used in the interpretation of similar chemical profiles yielded by receptor models in the source apportionment of particulate matter

Receptor models have been widely used for the source apportionment of airborne particulate matter. However, in the last 10 years, the use of factor analysis-based models, such as PMF and UNMIX, has increased significantly. The results yielded by these models must be interpreted by users who must know all variables influencing the modeling, and without this knowledge, the probability of incorrect interpretation of the source profiles may increase, especially when two or more sources have similar chemical profiles. Concerning the quality of data, this work shows that a broad characterization of PM composition, including inorganic, organic, and mineralogical species can improve this process, avoiding misinterpretation and the attribution of mixed or unidentified sources. This work aims to provide readers with some answers for a question often risen during source apportionment studies: Which source markers should be used for better separation and interpretation of source profiles? This review shows there is no right answer for this because different strategies can be used for this purpose. Therefore, this review aims to compile and highlight qualitatively the key strategies already used by several experienced receptor models users, combining the use of inorganic, organic, and mineralogical markers of PM for better separation and interpretation of the profiles yielded by receptor models. Also, this work presents a compilation in tables of the main chemical species reported in the literature as markers for interpreting the source profiles.

PM2.5 and Trace Elements in Underground Shopping Districts in the Seoul Metropolitan Area, Korea

We measured PM_2.5 in 41 underground shopping districts (USDs) in the Seoul metropolitan area from June to November 2017, and associated 18 trace elements to determine the sources and assess the respiratory risks. The PM_2.5 concentrations were 18.0 ± 8.0 μg/m³ inside USDs, which were lower than 25.2 ± 10.6 μg/m³ outside. We identified five sources such as indoor miscellanea, soil dust, vehicle exhaust/cooking, coal combustion, and road/subway dust, using factor analysis. Almost 67% of the total trace element concentration resulted from soil dust. Soil dust contribution increased with the number of stores because of fugitive dust emissions due to an increase in passers-by. Vehicle exhaust/cooking contribution was higher when the entrances of the USDs were closed, whereas coal combustion contribution was higher when the entrances of the USDs were open. Although miscellanea and coal combustion contributions were 3.4% and 0.7%, respectively, among five elements with cancer risk, Cr and Ni were included in miscellanea, and Pb, Cd, and As were included in coal combustion. The excess cancer risk (ECR) was the highest at 67 × 10^-6 for Cr, and the ECR for Pb was lower than 10^-6, a goal of the United States Environmental Protection Agency for hazardous air pollutants.

Connecting land use-land cover and precipitation with organic matter biogeochemistry in a tropical river-estuary system of western peninsular India

Organic matter (OM) composition changed due to land use ─ land cover (LULC) and hydrology modification, has distinctive linkage towards sustainable environment management in tropical river systems. It is crucial in small river systems, which experience delay of freshwater flow to the estuaries due to headwater damming, also LULC alteration along the entire basin. In order to understand this fundamental linkage in tropical Zuari river-estuary (ZRE), we analyzed multi-proxy data of organic carbon to total nitrogen ratio (C_org/N), stable organic carbon isotope (δ¹³C_org) and lignin phenols measured in seasonally collected suspended particulate matter (SPM) and sediment samples. Results highlighted about moderate seasonality of OM tracers, with a significant effect of LULC alteration, which nevertheless a striking feature in monsoon-fed river-estuaries of peninsular India. Particulate C_org export from ZRE estimated to be 20 × 10³ kg yr^-1, was much lower as compared to tropical river-estuary systems elsewhere. OM fraction from vascular plant (mangroves) contributed to SPM and sediment was 15% and 40%, respectively, calculated using a Bayesian mixing calculation through Stable isotope analysis in R (SIAR). Presence of mudflat LULC in the estuarine region notably caused 20% decrease in C_org and 60% increase in lignin phenol (Λ8) as compared to their limits in upstream. This is although mudflat accounts only 3% of ZRE catchment. The degree of shifts in OM tracers highlights towards efficient entrapment, transformation and/or utilization of riverine OM in the mudflats of ZRE. Accelerated human induced LULC dampens the seasonality of OM characteristics and flow is highlighted through this study, which is essential towards sustainable environmental management practice in small rivers of India and World.

Chemical characteristics of road dust PM2.5 fraction in oasis cities at the margin of Tarim Basin

In order to understand the compositions characteristics of particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) fraction in road dust (RD_2.5) of oasis cities on the edge of Tarim Basin, 30 road dust (RD) samples were collected in Kashi, Cele, and Yutian in the spring, 2018, and RD_2.5 was collected using the resuspension approach. Eight water-soluble ions, 39 trace elements and 8 fractions of carbon-containing species in PM_2.5 were analyzed. Ca²⁺ and Ca were the most abundant ions and elements in RD_2.5 (7.1% and 9.5%). Cl^- in RD_2.5 was affected not only by attributed to saline-alkali soils in oasis cities of the Tarim Basin and dust from Taklimakan Desert but also by human activities. Moreover, the organic carbon/elemental carbon (OC/EC) ratio indicated that carbon components in RD_2.5 in Cele town mainly come from fossil fuel combustion, while those in Yutian and Kashi mainly come from biomass combustion. It is noteworthy that high Ca in RD_2.5 was seriously affected by anthropogenic emissions, and high Na and K contents in RD_2.5 could be derived from soil and desert dust. It was estimated that Cd, Tl, Sn and Cr were emitted from anthropogenic emissions using the enrichment factor. The coefficients of divergence (COD) result indicated that the influence of local emission on road dust emission is greater than that of long-distance transmission. This study is the first time to comprehensively analyze the chemical characteristics of road dust in oasis cities, and the results provides the sources of road dust at the margin of Tarim Basin.

Organic Molecular Marker from Regional Biomass Burning—Direct Application to Source Apportionment Model

To reduce fine particulate matter (PM2.5) level, the sources of PM2.5 in terms of the composition thereof needs to be identified. In this study, the experimental burning of ten types of biomass that are typically used in Republic of Korea, collected at the regional area were to investigate the indicated organic speciation and the results obtained therefrom were applied to the chemical mass balance (CMB) model for the study area. As a result, the organic molecular markers for the biomass burning were identified as they were varying according to chemical speciation of woods and herbaceous plants and depending upon the hard- and soft characteristics of specimens. Based on the source profile from biomass burning, major sources of PM2.5 in the study area of the present study appeared as sources of biomass burning, the secondary ions, secondary particulate matters, which is including long-distance transport, wherein the three sources occupied most over 84% of entire PM2.5. In regard to the subject area distinguished into residential area and on roads, the portion of the biomass burning appeared higher in residential area than on roads, whereas the generation from vehicles of gasoline engine and burning of meats in restaurants, etc. appeared higher on roads comparing to the residential area.

Sub-type source profiles of fine particles for fugitive dust and accumulative health risks of heavy metals: a case study in a fast-developing city of China

Sub-type source profiles for atmospheric fine particle (PM_2.5) were still scare in China, which limited the accurate source identification of it. Fugitive dust (including road dust, soil dust, resuspended dust, and construction dust, etc.) was one type of the most important contributors to PM_2.5 and its associated toxic metals held potential threaten to human health. The chemical compositions, sources, and health risks of sub-type fugitive dust deserved an investigation for further accurate control of particles and alleviating human health risks. A total of sixty-five fugitive dust samples were collected in Suzhou, a fast-developing city in southern China, including eleven sub-types of road dust (overpass, main street, collector street, and ordinary street), soil dust (farmland and tree lawn), resuspended dust (site types were corresponding to those of road dust), and construction dust (large construction sites). Chemical analysis of water-soluble ions, elements, and carbonaceous components was carried out to establish the sub-type source profiles of PM_2.5 for fugitive dust. Results showed that crustal elements were the most abundant components of fugitive dust, and soil dust was less polluted by anthropogenic activities. High contents of OC and low contents of EC were found in all the eleven types of dust. Equivalent ratios of anions and cations indicated that the fugitive dust was obviously alkaline. The contents of OC and EC in the four types of road dust were higher than those in other types of dust, while there existed differences among the sub-types of road dust. The NO₃^-/SO₄^2- ratios (0.03-0.09) implied that coal-burning and motor vehicle emission co-existed in Suzhou. Coefficient divergence (CD) values of eleven sub-type source profiles showed that there were certain differences among them, which suggested the possibility of sub-type source identification. Cluster analysis indicated the heavy metals in fugitive dust were mainly from crustal materials, metallurgical manufacturing, vehicle emissions, and industrial activities. The enrichment degree of heavy metals for the four types of road dust was also inconsistent. Heavy metals in road dust and soil dust posed a non-carcinogenic risk to children through direct ingestion, and the non-carcinogenic risk of direct intake of heavy metals was much higher than that of respiratory and skin contact. It was found that the accumulative health risks of heavy metals were higher in densely populated areas, traffic intensive areas, and industrial areas through the spatial analysis. This study firstly discussed the chemical compositions of PM_2.5 for eleven sub-types of fugitive dust in a Chinese city and assessed the accumulative health risks of heavy metals, which could be a demonstration for further related researches.

Compositional Characteristics of Atmospheric Aerosols during a Consecutive High Concentration Episode in Seoul, Korea

This study focuses on the temporal variation in the compositional characteristics of atmospheric aerosols in Seoul, South Korea, during the consecutive high aerosol concentration episode from 30 December 2013 to 2 January 2014. The temporal variations in the observed physical, optical, and chemical properties show that there were three distinct episodes during the period: haze, mixed haze/Asian dust, and Asian dust episodes. For the haze period, the concentration of secondary inorganic aerosols increased and both secondary inorganic aerosols and calcium species exhibited simultaneously high concentrations during the mixed haze/Asian dust period. The neutralization factors by ammonia in the haze periods were higher as 1.03 than the other periods, meanwhile the neutralization contribution by calcium carbonate was relatively higher as 1.39 during the Asian dust episode. The backward trajectory analysis showed that concentrations of SO42−, NO3−, and NH4+ were relatively high when air masses moved over East China. Principal component analysis showed that water-soluble components originated from soil dust/incineration, secondary aerosols/biomass burning, and road dust from the haze aerosol. For the mixed haze/Asian dust episode, the major source of aerosols was estimated to have originated from soil dust, pollutants from fossil fuel combustion, biomass burning, and sea-salt emissions. Furthermore, the main sources of ionic species in the Asian dust aerosols were estimated to be sea-salt/soil dust, secondary aerosols/coal combustion, and road dust.

Chemical source profiles of urban fugitive dust PM2.5 samples from 21 cities across China

Urban fugitive (road and construction) dust PM_2.5 samples were collected in 21 cities of seven regions in China. Seven water-soluble ions, eight sub-fractions of carbonaceous components, and 19 elements were determined to investigate the chemical profiles of urban fugitive dust. Among the analyzed chemical compositions and on regional average, the elemental compositions showed the highest proportion (12.5-28.9% in road dust (RD) and 13.1-38.0% in construction dust (CD)), followed by water-soluble ions (5.1-19.0% in RD and 4.2-16.4% in CD) and carbonaceous fractions (5.4-9.6% in RD and 4.9-9.3% in CD). Chemical compositions measured in CD were all slightly lower than those in RD although statistically insignificant (p > 0.05). Soil dust, which was estimated from Fe concentration, was proved to be the biggest contributor to urban fugitive dust PM_2.5 mass. While, it showed a higher contribution in Northern China (71.5%) than in Southern China (52.1%). Higher enrichment factors were found for elemental S, Zn and Pb in RD than CD, reflecting stronger anthropogenic sources (i.e. vehicle exhaust) in RD. Low NO₃^-/SO₄^2- and high SO₄^2-/K⁺ ratios both indicated that fugitive dust was strongly influenced by stationary sources (e.g. coal combustion), and this influence was especially strong in Northern China. Coefficients of divergence proved that dust profiles within the same region were more similar than across regions, reflecting that urban fugitive dust was influenced more by local sources than long-range transport.

Resonant Synchrotron X-ray Diffraction determines markers for iron-rich atmospheric particulate matter in urban region

Particulate matter driven health problems are strongly associated with its chemical composition. Despite the benefits of using source apportionment models for air quality management, limitations such as collinearity effects, restrict their application or compromise the accurate separation of sources, particularly for particulate matter with similar chemical profiles. Receptors models also depend on the operator expertise to appropriately classified sources, a subjective process that can lead to biased results. For highly correlated sources, the identification of specific markers is still the best way to achieve proper source apportionment. In this study, Resonant Synchrotron X-ray Diffraction has been applied to the analysis of atmospheric particles to determine markers for industrial and vehicular sources in the Region of Greater Vitória, Brazil. Total suspended particulate matter, PM_10, and PM_2.5 samples were analyzed by Resonant Synchrotron X-ray Diffraction showing high levels of iron-based crystalline phases. In comparison to the use of chemical elemental species, the identification of the crystalline phases provided an enhanced approach to classify specific iron-based source markers. For this study, α-Fe₂O₃ was identified with iron-based sources such as iron ore, pelletizing, and sintering; metallic Fe was inferred with blast furnaces and steelmaking; FeS₂ was correlated with coal deposits; and K₂Fe₂O₄ was associated to sintering emissions. Elemental carbon with different X-ray diffraction patterns enabled the differentiation of industrial and vehicular sources. The attribution of crystal rather than elemental composition in the identification of sources improves the accuracy of source apportionment studies.

Differential toxicities of fine particulate matters from various sources

Fine particulate matters less than 2.5 µm (PM2.5) in the ambient atmosphere are strongly associated with adverse health effects. However, it is unlikely that all fine particles are equally toxic in view of their different sizes and chemical components. Toxicity of fine particles produced from various combustion sources (diesel engine, gasoline engine, biomass burning (rice straw and pine stem burning), and coal combustion) and non-combustion sources (road dust including sea spray aerosols, ammonium sulfate, ammonium nitrate, and secondary organic aerosols (SOA)), which are known major sources of PM2.5, was determined. Multiple biological and chemical endpoints were integrated for various source-specific aerosols to derive toxicity scores for particles originating from different sources. The highest toxicity score was obtained for diesel engine exhaust particles, followed by gasoline engine exhaust particles, biomass burning particles, coal combustion particles, and road dust, suggesting that traffic plays the most critical role in enhancing the toxic effects of fine particles. The toxicity ranking of fine particles produced from various sources can be used to better understand the adverse health effects caused by different fine particle types in the ambient atmosphere, and to provide practical management of fine particles beyond what can be achieved only using PM mass which is the current regulation standard.

Comparison of Measurement-Based Methodologies to Apportion Secondary Organic Carbon (SOC) in PM2.5: A Review of Recent Studies

Secondary organic aerosol (SOA) is known to account for a major fraction of airborne particulate matter, with significant impacts on air quality and climate at the global scale. Despite the substantial amount of research studies achieved during these last decades, the source apportionment of the SOA fraction remains difficult due to the complexity of the physicochemical processes involved. The selection and use of appropriate approaches are a major challenge for the atmospheric science community. Several methodologies are nowadays available to perform quantitative and/or predictive assessments of the SOA amount and composition. This review summarizes the current knowledge on the most commonly used approaches to evaluate secondary organic carbon (SOC) contents: elemental carbon (EC) tracer method, chemical mass balance (CMB), SOA tracer method, radiocarbon (14C) measurement and positive matrix factorization (PMF). The principles, limitations, challenges and good practices of each of these methodologies are discussed in the present article. Based on a comprehensive—although not exhaustive—review of research papers published during the last decade (2006–2016), SOC estimates obtained using these methodologies are also summarized for different regions across the world. Conclusions of some studies which are directly comparing the performances of different methodologies are then specifically discussed. An overall picture of SOC contributions and concentrations obtained worldwide for urban sites under similar conditions (i.e., geographical and seasonal ones) is also proposed here. Finally, further needs to improve SOC apportionment methodologies are also identified and discussed.

A causation-based method developed for an integrated risk assessment of heavy metals in soil

A comprehensive and fact-based risk assessment of heavy metals in soils is paramount for defining strategies for environmental management. However, the risk assessment approaches of heavy metals in soils are often incomplete, in particular, causation-based pollution source apportionment is absent at present. Here, we developed a causation-based method framework of an integrated risk assessment of soil heavy metals. This method framework involves risk identification, causation-based source apportionment and an environmental sensitivity assessment. Dongtang Township in Guangdong Province, China was used as a case study. We found that air Cd, the background value and metallurgical industries (Danxia and Fankou plants) were identified as the major causes of soil Cd, and air and soil Cd as well as water Cd interacted causally. Danxia and Fankou plants, the mining area and background value were the major causes of soil Pb. The risk level and environmental sensitivity of the Danxia and Fankou plants were assessed. This is the first study to establish a causation-based method framework of an integrated risk assessment of soil heavy metals. This framework promotes systematic integration of risk assessment of soil heavy metals and expands traditional research on pollution source apportionment from a correlation-based approach to crucial insights into causation.

Speciation of organic fractions does matter for aerosol source apportionment. Part 2: Intensive short-term campaign in the Paris area (France)

The present study aimed at performing PM₁₀ source apportionment, using positive matrix factorization (PMF), based on filter samples collected every 4h at a sub-urban station in the Paris region (France) during a PM pollution event in March 2015 (PM₁₀>50μgm^-3 for several consecutive days). The PMF model allowed to deconvolve 11 source factors. The use of specific primary and secondary organic molecular markers favoured the determination of common sources such as biomass burning and primary traffic emissions, as well as 2 specific biogenic SOA (marine+isoprene) and 3 anthropogenic SOA (nitro-PAHs+oxy-PAHs+phenolic compounds oxidation) factors. This study is probably the first one to report the use of methylnitrocatechol isomers as well as 1-nitropyrene to apportion secondary OA linked to biomass burning emissions and primary traffic emissions, respectively. Secondary organic carbon (SOC) fractions were found to account for 47% of the total OC. The use of organic molecular markers allowed the identification of 41% of the total SOC composed of anthropogenic SOA (namely, oxy-PAHs, nitro-PAHs and phenolic compounds oxidation, representing 15%, 9%, 11% of the total OC, respectively) and biogenic SOA (marine+isoprene) (6% in total). Results obtained also showed that 35% of the total SOC originated from anthropogenic sources and especially PAH SOA (oxy-PAHs+nitro-PAHs), accounting for 24% of the total SOC, highlighting its significant contribution in urban influenced environments. Anthropogenic SOA related to nitro-PAHs and phenolic compounds exhibited a clear diurnal pattern with high concentrations during the night indicating the prominent role of night-time chemistry but with different chemical processes involved.

Source apportionment studies on particulate matter (PM10 and PM2.5) in ambient air of urban Mangalore, India

Particulate matter (PM₁₀ and PM_2.5) samples were collected from six sites in urban Mangalore and the mass concentrations for PM₁₀ and PM_2.5 were measured using gravimetric technique. The measurements were found to exceed the national ambient air quality standards (NAAQS) limits, with the highest concentration of 231.5 μg/m³ for PM₁₀ particles at Town hall and 120.3 μg/m³ for PM_2.5 particles at KMC Attavar. The elemental analysis using inductively coupled plasma optical emission spectrophotometer (ICPOES) revealed twelve different elements (As, Ba, Cd, Cr, Cu, Fe, Mg, Mn, Mo, Ni, Sr and Zn) for PM₁₀ particles and nine different elements (Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Sr and Zn) for PM_2.5 particles. Similarly, ionic composition of these samples measured by ion chromatography (IC) divulged nine different ions (F^-, Cl^-, NO₃^-, PO₄^3-, SO₄^2-, Na⁺, K⁺, Mg²⁺ and Ca²⁺) for PM₁₀ particles and ten different ions (F^-, Cl^-, NO₃^-, PO₄^3-, SO₄^2-, Na⁺, NH₄⁺, K⁺, Mg²⁺ and Ca²⁺) for PM_2.5 particles. The source apportionment study of PM₁₀ and PM_2.5 for urban Mangalore in accordance with these six sample sites using chemical mass balance model (CMBv8.2) revealed nine and twelve predominant contributors for both PM₁₀ and PM_2.5, respectively. The highest contributor of PM₁₀ was found to be paved road dust followed by diesel and gasoline vehicle emissions. Correspondingly, PM_2.5 was found to be contributed mainly from two-wheeler vehicle emissions followed by four-wheeler and heavy vehicle emissions (diesel vehicles). The current study depicts that the PM₁₀ and PM_2.5 in ambient air of Mangalore region has 70% of its contribution from vehicular emissions (both exhaust and non-exhaust).

Coarse particle (PM10-2.5) source profiles for emissions from domestic cooking and industrial process in Central India

To develop coarse particle (PM_10-2.5, 2.5 to 10μm) chemical source profiles, real-world source sampling from four domestic cooking and seven industrial processing facilities were carried out in "Raipur-Bhilai" of Central India. Collected samples were analysed for 32 chemical species including 21 elements (Al, As, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Mo, Na, Ni, Pb, S, Sb, Se, V, and Zn) by atomic absorption spectrophotometry (AAS), 8 water-soluble ions (Na⁺, K⁺, Mg²⁺, Ca²⁺, Cl^-, F^-, NO₃^-, and SO₄^2-) by ion chromatography, ammonium (NH₄⁺) by spectrophotometry, and carbonaceous fractions (OC and EC) by thermal/optical transmittance. The carbonaceous fractions were most abundant fraction in household fuel and municipal solid waste combustion emissions while elemental species were more abundant in industrial emissions. Most of the elemental species were enriched in PM_2.5 (<2.5μm) size fraction as compared to the PM_10-2.5 fraction. Abundant Ca (13-28%) was found in steel-rolling mill (SRM) and cement production industry (CPI) emissions, with abundant Fe (14-32%) in ferro-manganese (FEMNI), steel production industry (SPI), and electric-arc welding emissions. High coefficients of divergence (COD) values (0.46 to 0.88) among the profiles indicate their differences. These region-specific source profiles are more relevant to source apportionment studies in India than profiles measured elsewhere.

PM2.5 Source Apportionment Using a Hybrid Environmental Receptor Model

A hybrid environmental receptor model (HERM) that unifies the theory of effective-variance chemical mass balance (EV-CMB) and positive matrix factorization (PMF) models was developed to support the weight-of-evidence approach of air pollution source apportionment. The HERM software is capable of (1) conducting EV-CMB analysis for multiple samples in a single model run; (2) calculating EV-CMB and PMF source contributions, as well as middle grounds between the two (i.e., hybrid mode), using partial source information available for the study region; (3) reporting source contribution uncertainties and sample-/species-specific fitting performance measures; and (4) interfacing with MS Excel for convenient data inputs/outputs and analysis. Initial testing with simulated and real-world PM_2.5 (fine particulate air pollutants with aerodynamic diameter <2.5 μm) data sets show that HERM reproduces EV-CMB results from existing software but with more tolerance to collinearity and better uncertainty estimates. It also shows that partial source information helps reduce rotational ambiguity in PMF, thus producing more accurate partitioning between highly correlated sources. Moreover, source profiles generated from the hybrid mode can be more representative of the study region than those acquired from other locales or calculated by PMF with no source information. Strategies to use HERM for source apportionment are recommended.

Source apportionment for fine particulate matter in a Chinese city using an improved gas-constrained method and comparison with multiple receptor models

PM_2.5 is one of the most studied atmospheric pollutants due to its adverse impacts on human health and welfare and the environment. An improved model (the chemical mass balance gas constraint-Iteration: CMBGC-Iteration) is proposed and applied to identify source categories and estimate source contributions of PM_2.5. The CMBGC-Iteration model uses the ratio of gases to PM as constraints and considers the uncertainties of source profiles and receptor datasets, which is crucial information for source apportionment. To apply this model, samples of PM_2.5 were collected at Tianjin, a megacity in northern China. The ambient PM_2.5 dataset, source information, and gas-to-particle ratios (such as SO₂/PM_2.5, CO/PM_2.5, and NOx/PM_2.5 ratios) were introduced into the CMBGC-Iteration to identify the potential sources and their contributions. Six source categories were identified by this model and the order based on their contributions to PM_2.5 was as follows: secondary sources (30%), crustal dust (25%), vehicle exhaust (16%), coal combustion (13%), SOC (7.6%), and cement dust (0.40%). In addition, the same dataset was also calculated by other receptor models (CMB, CMB-Iteration, CMB-GC, PMF, WALSPMF, and NCAPCA), and the results obtained were compared. Ensemble-average source impacts were calculated based on the seven source apportionment results: contributions of secondary sources (28%), crustal dust (20%), coal combustion (18%), vehicle exhaust (17%), SOC (11%), and cement dust (1.3%). The similar results of CMBGC-Iteration and ensemble method indicated that CMBGC-Iteration can produce relatively appropriate results.

Seasonal variability of PM2.5 and PM10 composition and sources in an urban background site in Southern Italy

Comparison of fine and coarse fractions in terms of sources and dynamics is scarce in southeast Mediterranean countries; differences are relevant because of the importance of natural sources like sea spray and Saharan dust advection, because most of the monitoring networks are limited to PM₁₀. In this work, the main seasonal variabilities of sources and processes involving fine and coarse PM (particulate matter) were studied at the Environmental-Climate Observatory of Lecce (Southern Italy). Simultaneous PM_2.5 and PM₁₀ samples were collected between July 2013 and July 2014 and chemically analysed to determine concentrations of several species: OC (organic carbon) and EC (elemental carbon) via thermo-optical analysis, 9 major ions via IC, and 23 metals via ICP-MS. Data was processed through mass closure analysis and Positive Matrix Factorization (PMF) receptor model characterizing seasonal variabilities of nine sources contributions. Organic and inorganic secondary aerosol accounts for 43% of PM_2.5 and 12% of PM_2.5-10 with small seasonal changes. SIA (secondary inorganic aerosol) seasonal pattern is opposite to that of SOC (secondary organic carbon). SOC is larger during the cold period, sulphate (the major contributor to SIA) is larger during summer. Two forms of nitrate were identified: NaNO₃, correlated with chloride depletion and aging of sea-spray, mainly present in PM_2.5-10; NH₄NO₃ more abundant in PM_2.5. Biomass burning is a relevant source with larger contribution during autumn and winter because of the influence of domestic heating, however, is not negligible in spring and summer, because of the contributions of fires and agricultural practices. Mass closure analysis and PMF results identify two soil sources: crustal associated to long range transport and carbonates associated to local resuspended dust. Both sources contributes to the coarse fraction and have different dynamics with crustal source contributing mainly in high winds from SE conditions and carbonates during high winds from North direction.

Contribution of ship emissions to the concentration of PM2.5: A comprehensive study using AIS data and WRF/Chem model in Bohai Rim Region, China

Compared with on-road vehicles, emission from ships is one of the least-regulated anthropogenic emission sources and non-negligible source of primary aerosols and gas-phase precursors of PM_2.5. The Bohai Rim Region in China hosts dozens of large ports, two of which ranked among the top ten ports in the world. To determine the impact of ship emissions on the PM_2.5 concentrations over this region, two parts of works have been conducted in this study. First, a detailed ship emission inventory with high spatiotemporal resolution was developed based on Automatic Identification System (AIS) data. Then the WRF/Chem model was applied to modeling the impact of ship emissions by comparing two scenarios: with and without ship emissions. The results indicate that the total estimated ship emissions of SO₂, NO_X, PM₁₀, PM_2.5, CO, HC, and CO₂ from Bohai Rim Region in 2014 are 1.9×10⁵, 2.9×10⁵, 2.6×10⁴, 2.4×10⁴, 2.5×10⁴, 1.2×10⁴, and 1.3×10⁷tonnes, respectively. The modeling results indicate that the annual PM_2.5 concentrations increased by 5.9% on land areas of Bohai Rim Region (the continent within 115.2°E-124.3°E and 36.1°N-41.6°N) due to ship emissions. The contributions show distinctive seasonal variations of contributions, presenting highest in summer (12.5%) followed by spring (6.9%) and autumn (3.3%), and lowest in winter (0.9%). The contribution reaches up to 10.7% along the shoreline and down to 1.0% 200km inland. After examining the statistics of the modeling results during heavy and non-heavy haze days in July, it was found that 6 out of 9 cities around the Bohai Rim Region were observed with higher contributions from ship emissions during heavy haze days compared with non-heavy haze days. These results indicate that the impacts of ship emissions on the ambient PM_2.5 are non-negligible, especially for heavy haze days for most coastal cities in the Bohai Rim Region.

Public health costs accounting of inorganic PM2.5 pollution in metropolitan areas of the United States using a risk-based source-receptor model

In order to design effective strategies to reduce the public health burden of ambient fine particulate matter (PM_2.5) imposed in an area, it is necessary to identify the emissions sources affecting that location and quantify their contributions. However, it is challenging because PM_2.5 travels long distances and most constituents are the result of complex chemical processes. We developed a reduced-form source-receptor model for estimating locations and magnitudes of downwind health costs from a source or, conversely, the upwind sources that contribute to health costs at a receptor location. Built upon outputs from a state-of-the-art air quality model, our model produces comprehensive risk-based source apportionment results with trivial computational costs. Using the model, we analyzed all the sources contributing to the inorganic PM_2.5 health burden in 14 metropolitan statistical areas (MSAs) in the United States. Our analysis for 12 source categories shows that 80-90% of the burden borne by these areas originates from emissions sources outside of the area and that emissions sources up to 800 km away need to be included to account for 80% of the burden. Conversely, 60-80% of the impacts of an MSA's emissions occurs outside of that MSA. The results demonstrate the importance of regionally coordinated measures to improve air quality in metropolitan areas.

Particulate pollution in urban Chongqing of southwest China: Historical trends of variation, chemical characteristics and source apportionment

Chongqing, the largest megacity in southwest China, faces serious aerosol pollution but lacks information on particle characteristics and its sources. Official data released by Chongqing Environmental Protection Bureau demonstrated that urban PM₁₀ concentrations decreased remarkably from 150μgm^-3 in 2000 to 90μgm^-3 in 2012. However, only several peer-reviewed studies paid attention to local fine particle (PM_2.5) pollution. In the study, PM_2.5 samples were obtained and subjected to chemical analysis in an urban site of the city during 2012 to 2013. The annual mean PM₁₀ and PM_2.5 concentrations in urban Chongqing were 103.9±52.5 and 75.4±42.2μgm^-3, respectively. PM_2.5 showed a distinct seasonality of high concentration in winter and similar levels in other seasons. The average OC/EC (organic carbon/element carbon) ratio was 3.7 with more high-OC/EC ratio sources contribution in autumn and winter. The varying sources and formation mechanisms resulted in SO₄^2- and NH₄⁺ peaks in both summer and winter, whereas high nitrate concentration was only observed in winter. In the average mass closure, PM_2.5 was composed of 23.0% SO₄^2-, 11.7% NO₃^-, 10.9% NH₄⁺, 30.8% OM (organic matter), 5.2% EC, 8.2% mineral dust, 0.6% TEO (trace elements), 1.0% Cl^- and 1.1% K⁺, while exhibiting large seasonal variability. Using positive matrix factorization (PMF), six sources were apportioned in PM_2.5: secondary inorganic aerosols, coal combustion, other industrial pollution, soil dust, vehicular emission, and metallurgical industry. The annual mean contribution of above sources to PM_2.5 was 37.5, 22.0, 17.5, 11.0, 9.8 and 2.2%, respectively. Coal combustion was identified by As tracer and dominated the primary sources of PM_2.5, while the two different industrial sources were characterized by Cr and Mo, Co, Ni, and Se, respectively. The study is of great importance in characterizing the historical trends, current chemical characteristics and sources of fine particles in urban Chongqing.

Fine particulate speciation profile and emission factor of municipal solid waste incinerator established by dilution sampling method

In this study, fine particulate matter (PM2.5) emitted from a municipal solid waste incinerator (MSWI) was collected using dilution sampling method. Chemical compositions of the collected PM2.5 samples, including carbon content, metal elements, and water-soluble ions, were analyzed. Traditional in-stack hot sampling was simultaneously conducted to compare the influences of dilution on PM2.5 emissions and the characteristics of the bonded chemical species. The results, established by a dilution sampling method, show that PM2.5 and total particulate matter (TPM) emission factors were 61.6 ± 4.52 and 66.1 ± 5.27 g ton-waste(-1), respectively. The average ratio of PM2.5/TPM is 0.93, indicating that more than 90% of PM emission from the MSWI was fine particulate. The major chemical species in PM2.5 included organic carbon (OC), Cl(-), NH4(+), elemental carbon (EC) and Si, which account for 69.7% of PM2.5 mass. OC was from the unburned carbon in the exhaust, which adsorbed onto the particulate during the cooling process. High Cl(-) emission is primarily attributable to wastes containing plastic bags made of polyvinyl chloride, salt in kitchen refuse and waste biomass, and so on. Minor species that account for 0.01-1% of PM2.5 mass included SO4(2-), K(+), Na, K, NO3(-), Al, Ca(2+), Zn, Ca, Cu, Fe, Pb, and Mg. The mean ratio of dilution method/in-stack hot method was 0.454. The contents of water-soluble ions (Cl(-), SO4(2-), NO3(-)) were significantly enriched in PM2.5 via gas-to-particle conversion in the dilution process. Results indicate that in-stack hot sampling would underestimate levels of these species in PM2.5.

IMPLICATIONS

PM2.5 samples from a municipal solid waste incinerator (MSWI) were collected simultaneously by a dilution sampling technique and a traditional in-stack method. PM2.5 emission factors and chemical speciation profiles were established. Dilution sampling provides more reliable data than in-stack hot sampling. The results can be applied to estimate the PM2.5 emission inventories of MSWI, and the source profile can be used for contribution estimate of chemical mass balance modeling.

Short-term exposure to traffic-related air pollution and daily mortality in London, UK

Epidemiological studies have linked daily concentrations of urban air pollution to mortality, but few have investigated specific traffic sources that can inform abatement policies. We assembled a database of >100 daily, measured and modelled pollutant concentrations characterizing air pollution in London between 2011 and 2012. Based on the analyses of temporal patterns and correlations between the metrics, knowledge of local emission sources and reference to the existing literature, we selected, a priori, markers of traffic pollution: oxides of nitrogen (general traffic); elemental and black carbon (EC/BC) (diesel exhaust); carbon monoxide (petrol exhaust); copper (tyre), zinc (brake) and aluminium (mineral dust). Poisson regression accounting for seasonality and meteorology was used to estimate the percentage change in risk of death associated with an interquartile increment of each pollutant. Associations were generally small with confidence intervals that spanned 0% and tended to be negative for cardiovascular mortality and positive for respiratory mortality. The strongest positive associations were for EC and BC adjusted for particle mass and respiratory mortality, 2.66% (95% confidence interval: 0.11, 5.28) and 2.72% (0.09, 5.42) per 0.8 and 1.0 μg/m(3), respectively. These associations were robust to adjustment for other traffic metrics and regional pollutants, suggesting a degree of specificity with respiratory mortality and diesel exhaust containing EC/BC.

Source apportionment and health risk assessment of PM10 in a naturally ventilated school in a tropical environment

This study aimed to investigate the chemical composition and potential sources of PM10 as well as assess the potential health hazards it posed to school children. PM10 samples were taken from classrooms at a school in Kuala Lumpur's city centre (S1) and one in the suburban city of Putrajaya (S2) over a period of eight hours using a low volume sampler (LVS). The composition of the major ions and trace metals in PM10 were then analysed using ion chromatography (IC) and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. The results showed that the average PM10 concentration inside the classroom at the city centre school (82µg/m(3)) was higher than that from the suburban school (77µg/m(3)). Principal component analysis-absolute principal component scores (PCA-APCS) revealed that road dust was the major source of indoor PM10 at both school in the city centre (36%) and the suburban location (55%). The total hazard quotient (HQ) calculated, based on the formula suggested by the United States Environmental Protection Agency (USEPA), was found to be slightly higher than the acceptable level of 1, indicating that inhalation exposure to particle-bound non-carcinogenic metals of PM10, particularly Cr exposure by children and adults occupying the school environment, was far from negligible.

Source Contributions to Wintertime Elemental and Organic Carbon in the Western Arctic Based on Radiocarbon and Tracer Apportionment

To quantify the contributions of fossil and biomass sources to the wintertime Arctic aerosol burden source apportionment is reported for elemental (EC) and organic carbon (OC) fractions of six PM10 samples collected during a wintertime (2012-2013) campaign in Barrow, AK. Radiocarbon apportionment of EC indicates that fossil sources contribute an average of 68 ± 9% (0.01-0.07 μg m(-3)) in midwinter decreasing to 49 ± 6% (0.02 μg m(-3)) in late winter. The mean contribution of fossil sources to OC for the campaign was stable at 38 ± 8% (0.04-0.32 μg m(-3)). Samples were also analyzed for organic tracers, including levoglucosan, for use in a chemical mass balance (CMB) source apportionment model. The CMB model was able to apportion 24-53% and 99% of the OC and EC burdens, respectively, during the campaign, with fossil OC contributions ranging from 25 to 74% (0.02-0.09 μg m(-3)) and fossil EC contributions ranging from 73 to 94% (0.03-0.07 μg m(-3)). Back trajectories identified two major wintertime source regions to Barrow: the Russian and North American Arctic. Atmospheric lifetimes of levoglucosan, ranging from 50 to 320 h, revealed variability in wintertime atmospheric processing of this biomass burning tracer. This study allows for unambiguous apportionment of EC to fossil fuel and biomass combustion sources and intercomparison with CMB modeling.

Emission and profile characteristic of volatile organic compounds emitted from coke production, iron smelt, heating station and power plant in Liaoning Province, China

107 kinds of C₂-C₁₂ volatile organic compound (VOC) mass concentrations and profiles for four types of coal-fired stationary sources in Liaoning Province were studied by a dilution sampling system and GC-MS analysis method, which are of significant importance with regard to VOC emissions in northeast of China. The results showed that there were some differences among these VOC source profiles. The total mass concentrations of analyzed 107 VOC species varied from 10,917 to 19,652 μg m(-3). Halogenated hydrocarbons exhibited higher mass percentages for the VOC source profiles of iron smelt (48.8%) and coke production plant (37.7%). Aromatic hydrocarbons were the most abundant in heating station plant (69.1%). Ketones, alcohols and acetates held 45.0% of total VOCs in thermal power plant. For non-methane hydrocarbons (NMHCs), which are demanded for photochemical assessment in the USA, toluene and n-hexane were the most abundant species in the iron smelt, coke production and thermal power plant, with the mass percentages of 64.8%, 52.7% and 38.6%, respectively. Trimethylbenzene, n-propylbenzene and o,m-ethyltoluene approximately accounted for 70.0% in heating station plant. NMHCs emitted from coke production, iron smelt, heating station and power plant listed above presented different chemical reactivities. The average OH loss rate of NMHCs from heating station, was 4 to 5.6 times higher than that of NMHCs from iron smelt, coke production and power plant, which implies that VOCs emitted from heating station in northeast of China should be controlled firstly to avoid photochemical ozone pollution and protect human health. There are significant variations in the ratios of benzene/toluene and m, p-xylene/ethylbenzene of these coal-fired source profiles. The representativeness of the coal-fired sources studied and the VOC samples collected should be more closely examined. The accuracy of VOC source profiles related to coal-fired processes is highly dependent on location and sampling method.

Source apportionment of size resolved particulate matter at a European air pollution hot spot

Positive Matrix Factorization-PMF was applied to hourly resolved elemental composition of fine (PM0.15-1.15) and coarse (PM1.15-10) aerosol particles to apportion their sources in the airshed of residential district, Ostrava-Radvanice and Bartovice in winter 2012. Multiple-site measurement by PM2.5 monitors complements the source apportionment. As there were no statistical significant differences amongst the monitors, the source apportionment derived for the central site data is expected to apply to whole residential district. The apportioned sources of the fine aerosol particles were coal combustion (58.6%), sinter production-hot phase (22.9%), traffic (15%), raw iron production (3.5%), and desulfurization slag processing (<0.5%) whilst road dust (47.3%), sinter production-cold phase (27.7%), coal combustion (16.8%), and raw iron production (8.2%) were resolved being sources of the coarse aerosol particles. The shape and elemental composition of size-segregated aerosol airborne-sampled by an airship aloft presumed air pollution sources helped to interpret the PMF solution.

Using an improved Source Directional Apportionment method to quantify the PM(2.5) source contributions from various directions in a megacity in China

The transport of particulate matter (PM) and chemical species is an essential mechanism for determining the fate of PM pollutants and their effects. To determine source transport quantitatively, an ambient PM2.5 dataset from a megacity in China was analysed using a novel method called "Source Directional Apportionment" (SDA). The SDA method is developed in this work to quantify contributions of each source category from various directions. The three steps of SDA are (1) to estimate source categories and time series of source contributions to PM with a factor analysis model, (2) to identify directions by trajectory cluster analysis and (3) to quantify source directional contributions for each source category by combining the time series of source contributions to the back trajectories in each direction. For PM2.5 in Chengdu, crustal dust, vehicular exhaust, coal combustion and secondary sulphate are all important contributors to PM; secondary nitrate and cement dust are relatively less influential. Four potential source directions were identified in Chengdu during the sampling period from 2009 to 2011. The percentages of source directional contributions from Directions 1-4 (northeast, southwest to south, southwest and west) were estimated as follows: crustal dust (7.9%, 9.1%, 6.4% and 6.2%, respectively), cement dust (1.0%, 1.2%, 1.3% and 1.1%, respectively), vehicular exhaust (6.4%, 6.0%, 5.6% and 7.0%, respectively), secondary sulphate (5.1%, 5.2%, 5.6% and 8.6%, respectively) and secondary nitrate (2.0%, 2.4%, 2.5% and 2.3%, respectively). Finally, the source directional contributions to important chemical species were quantified to determine their transport from sources to receptor.

Identification of the sources of PM10 in a subway tunnel using positive matrix factorization

The level of particulate matter of less than 10 μm diameter (PM10) at subway platforms can be significantly reduced by installing a platform screen-door system. However, both workers and passengers might be exposed to higher PM10 levels while the cars are within the tunnel because it is a more confined environment. This study determined the PM10 levels in a subway tunnel, and identified the sources of PM10 using elemental analysis and receptor modeling. Forty-four PM10 samples were collected in the tunnel between the Gireum and Mia stations on Line 4 in metropolitan Seoul and analyzed using inductively coupled plasma-atomic emission spectrometry and ion chromatography. The major PM10 sources were identified using positive matrix factorization (PMF). The average PM10 concentration in the tunnels was 200.8 ± 22.0 μg/m3. Elemental analysis indicated that the PM10 consisted of 40.4% inorganic species, 9.1% anions, 4.9% cations, and 45.6% other materials. Iron was the most abundant element, with an average concentration of 72.5 ± 10.4 μg/m3. The PM10 sources characterized by PMF included rail, wheel, and brake wear (59.6%), soil combustion (17.0%), secondary aerosols (10.0%), electric cable wear (8.1%), and soil and road dust (5.4%). Internal sources comprising rail, wheel, brake, and electric cable wear made the greatest contribution to the PM10 (67.7%) in tunnel air. Implications: With installation of a platform screen door, PM10 levels in subway tunnels were higher than those on platforms. Tunnel PM10 levels exceeded 150 µg/m3 of the Korean standard for subway platform. Elemental analysis of PM10 in a tunnel showed that Fe was the most abundant element. Five PM10 sources in tunnel were identified by positive matrix factorization. Railroad-related sources contributed 68% of PM10 in the subway tunnel.

Aerosol and ozone observations during six cruise campaigns across the Mediterranean basin: temporal, spatial, and seasonal variability

The Mediterranean basin, because of its semi-enclosed configuration, is one of the areas heavily affected by air pollutants. Despite implications on both human health and radiative budget involving an increasing interest, monitoring databases measuring air pollution directly over this area are yet relatively limited. Owing to this context, concentrations of fine (PM2.5) and coarse (PM2.5-10) particles along with other ancillary data, such as ozone levels and meteorological parameters, were measured during six cruise campaigns covering almost the whole Mediterranean basin. Elemental composition of both PM2.5 and PM2.5-10 was also determined to identify specific tracers for different classes of particles that can be found in the Mediterranean atmosphere. Outcomes resulting from the integration of a preliminary qualitative examination with a more quantitative analysis, based on receptor modelling, suggested that European continental influence, Saharan dust outbreaks, wildfire events, sea spray and fossil fuel combustion were the leading causes of the aerosol-ozone variations within the Mediterranean basin. Shipping emissions, consisting in both local harbours and maritime traffic across the basin, were also tested using the marker ratio of V/Ni. Peak values observed for coarse fraction have shown to be driven by the occurrence of African dust events. Considering the major influence of Continental pollution and wildfire events, the spatial variability resulted in larger fine particle concentrations and higher ozone levels over the Eastern Mediterranean side in comparison to the Western one.

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1-10 microm (PM1-10) sources in a village, Brezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM1-10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM10 and PM1-10 within 2008-2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM1-10 data across the multiple sites. PMF resolved seven sources of PM1-10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM1-10. The conditional probability function (CPF) helped to identified local sources of PM1-10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Field study and source attribution for PM2.5 and PM10 with resulting reduction in concentrations in the neighborhood north of the Houston Ship Channel based on voluntary efforts

When annual average PM2.5 (fine particulate matter sized 2.5 microns and less) data for 2005 became available in April 2006 and the 3-yr average PM2.5 concentration in an area just north of the Houston Ship Channel reached 15.0 microg/m3, the Texas Commission on Environmental Quality (TCEQ) initiated daily collection of quartz fiber as well as Teflon PM2.5 filter samples for chemical speciation analysis. The purpose of the chemical speciation analysis was to use the speciation data, together with meteorological data and hourly TEOM (tapered element oscillating microbalance) PM2.5 mass data, to identify the causes of the high PM2.5 concentrations affecting the monitoring site and the neighborhood. The ultimate purpose was to target emission reduction efforts to sources contributing to the high measured PM2.5 concentrations. After a year of data collection, it was recognized that a specific source, unpaved driveways and loading areas along the Ship Channel and dirt tracked onto Clinton Drive, the main artery running east-west north of the Ship Channel, were the primary cause for the Clinton Drive site's measuring PM2.5 concentrations significantly higher than other sites in Houston. The source characterization and remediation steps that have led to sustained reduced concentrations are described in this paper.

Characterization of particulate matter and its related metal toxicity in an urban location in South West India

This study reports the quantification of the toxicity of particulate matter (PM)-bound metals and their possible associated risks to human health. For assessment of PM, 24-h samples of PM(10) and PM2.5 were collected by Mini Vol-TAS sampler at an urban site of Pune. Samples were sequentially extracted with ultrapure water and concentrated HNO3 and analyzed for "soluble" and "total" metals. Factor analysis identified the resuspension of road dust due to traffic, biomass burning, construction activities, and wind-blown dust as possible sources that played an important role for overall pollution throughout the year. Water-soluble proportion was found to be ≤ 20 % for Cr, Co, Fe, and Al; ≥ 50 % for Sr, Cd, Ca, and Zn; and a substantial proportion (~25-45 %) for Mn, Ba, K, Na, Ni, Mg, Cu, and Pb metals in PM(10). For PM2.5, the water-soluble proportion was ≤ 20 % for Fe, Co, Ni, Cr, and Al, while Sr, K, and Cd were mostly soluble (> 50 %) and Cu, Ba, Mn, Ca, Zn, Pb, Na, and Mg were substantially soluble (~25-45 %). In the present study, among the toxic metals, Cd and Pb show higher concentration in the soluble fraction and thus represent the higher bioavailability index and especially are harmful to the environment and exposed person. Risk calculations with a simple exposure assessment method showed that the cancer risks of the bioavailable fractions of Cr, Cd and Ni were greater than the standard goal.

Black carbon emissions in gasoline vehicle exhaust: a measurement and instrument comparison

A pilot study was conducted to evaluate the performance and agreement of several commercially available black carbon (BC) measurement instruments, when applied to the quantification of BC in light-duty vehicle (LDV) exhaust. Samples from six vehicles, three fuels, and three driving cycles were used. The pilot study included determinations of the method detection limit (MDL) and repeatability. With respect to the MDL, the real-time instruments outperformed the time-integrated instruments, with MDL = 0.12 mg/mi for the AE51 Aethalometer, and 0.15 mg/mi for the Micro Soot Sensor (MSS), versus 0.38 mg/mi for the IMPROVE_A thermal/ optical method, and 0.35 mg/mi for the OT21_T Optical Transmissometer. The real-time instruments had repeatability values ranging from 30% to 35%, which are somewhat better than those of the time-integrated instruments (40-41%). These results suggest that, despite being less resource intensive, real-time methods can be equivalent or superior to time-integrated methods in terms of sensitivity and repeatability. BC mass data, from the photoacoustic and light attenuation instruments, were compared against same-test EC data, determined using the IMPROVE_A method. The MSS BC data was well correlated with EC, with R2 = 0.85 for the composite results and R2 = 0.86 for the phase-by-phase (PBP) results. The correlation of BC, by the AE51, AE22, and OT21_T with EC was moderate to weak. The weaker correlation was driven by the inclusion of US06 test data in the linear regression analysis. We hypothesize that test-cycle-dependent BC:EC ratios are due to the different physicochemical properties of particulate matter (PM) in US06 and Federal Test Procedure (FTP) tests. Correlation amongst the real-time MSS, PASS-1, AE51, and AE22 instruments was excellent (R2 = 0.83-0.95), below 1 mg/mi levels. In the process of investigating these BC instruments, we learned that BC emissions at sub-1 mg/mi levels can be measured and are achievable by current-generation gasoline engines.

IMPLICATIONS

Most comparison studies of black carbon (BC) measurement methods were carried out in the ambient air. This study assesses the agreement among various BC measurement instrument in emissions from light-duty gasoline vehicles (LDGVs) on standard test cycles, and evaluates applicability of these methods under various fuel types, driving cycles, and engine combustion technologies. This research helps to fill in the knowledge gap of BC method standardization as stated in the U.S. Environmental Protection Agency (EPA) 2011 Report to Congress on Black Carbon, and these results demonstrate the feasibility of quantification of BC at the 1 mg/mi PM standard in California Low Emission Vehicle III regulations.

Temporal trends of elements in Turin (Italy) atmospheric particulate matter from 1976 to 2001

The temporal trends of major, minor and trace elements in the total atmospheric particulate sampled in the urban area of Turin (Italy) were determined for the following years: 1976, 1986, 1996 and 2001. The wavelength dispersive X-ray fluorescence (WD-XRF) technique was adopted to determine the concentrations of Ba, Br, Ca, Cl, Cr, Cu, Fe, K, Mg, Mn, Ni, Pb, S, Ti and Zn. A smaller number of samples was also analysed by ICP atomic emission spectroscopy (ICP-AES) and the results were compared with those obtained by WD-XRF to confirm their validity. A clear seasonal pattern with higher concentrations of the aforementioned elements in the cold periods was observed. Moreover, a change in the chemical composition of atmospheric particulate matter was evidenced, particularly between the first (1976 and 1986) and the last (1996 and 2001) years. This change can be attributed both to the greater contribution of Pb and Br to atmospheric pollution in the past and, in recent years, to the higher level of pollutants associated with increased vehicular traffic and industrial activities. The application of chemometric techniques (Principal Component Analysis and Cluster Analysis) allowed us to speculate about the main emitting sources influencing the total atmospheric particulate in these years.

Levels and sources of polychlorinated biphenyls in Ankara creek sediments, Turkey

The spatial distribution, degree of pollution and major sources of polychlorinated biphenyls (PCBs) were evaluated in surficial sediments of Ankara Creek, located in the capital of Turkey and serving as one of the tributaries in the third largest watershed in Turkey. Sediment ΣPCB concentrations analyzed on Aroclor and congener basis (seven indicator congeners) range from 5.5 to 777.6 ng g(-1) and 3.7 to 743.3 ng g(-1) dw as Aroclor and congener based concentrations, respectively. High concentrations of ΣPCBs were observed in the samples located at the downstream sections of the Creek, after discharge from Ankara municipal wastewater treatment plant. Using a chemical mass balance receptor model (CMB), major sources of PCBs affecting the sediments were investigated. The CMB model identified Aroclor 1254 and 1260 to be the major PCB sources affecting sediments. The potential sources for the PCBs were briefly discussed in terms of their use in various industrial applications.