Search

Long-term changes in dry deposition fluxes (DDF) and health risks for toxic elements (TE) in total suspended particles (TSP) in the Bohai Rim region are important for assessing control effects of pollution sources. Thus, we investigated the trends in DDF and concentrations for TSP and TE and health risks of TE in eight cities in the region from 2011-2020. TSP concentration and DDF showed general downward trends. Compared to the before Clear Air Action Plan (BCAAP, 2011-2012) period, concentration and DDF of TE over the Clear Air Action Plan (CAAP, 2013-2017) period substantially decreased, with the highest decrease rates in Zn, Cd, and Cr. During the study period, non-carcinogenic (HI) and total carcinogenic (TCR) risks for children and adults were 0.09 and 0.04, and 1.54 × 10 -5 and 2.65 × 10 -5 , respectively, with Cr 6+ and As being dominant contributors. Compared to the BCAAP period, HI and TCR over the CAAP period decreased by 36.8 % and 32.4 %, respectively. However, their risks increased over the Blue Sky Protection Campaign (BSPC, 2018-2020) period. Potential source contribution function suggested substantial changes in potential risk areas over different control periods, with the BSPC primarily being on land and the Yellow Sea., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

PM 2.5 in Shijiazhuang was collected from October 15, 2018 to January 31, 2019, and selected toxic elements were measured. Five typical haze episodes were chosen to analyze the health risks and critical risk sources. Toxic elements during the haze episodes accounted for 0.33% of PM 2.5 mass. Non-cancer risk of toxic elements for children was 1.8 times higher than that for adults during the haze episodes, while cancer risk for adults was 2.5 times higher than that for children; cancer and non-cancer risks were primarily attributable to As and Mn, respectively. Health risks of toxic elements increased during the growth and stable periods of haze episodes. Non-cancer and cancer risks of toxic elements during the haze stable periods were higher than other haze stages, and higher for children than for adults during the stable period. Mn was the largest contributor to non-cancer risk during different haze stages, while As was the largest contributor to cancer risk. Crustal dust, vehicle emissions, and industrial emissions were critical sources of cancer risk during the clean-air periods; while vehicle emissions, coal combustion, and crustal dust were key sources of cancer risk during the haze episodes. Cancer risks of crustal dust and vehicle emissions during the haze episodes were 2.0 and 1.7 times higher than those in the clean-air periods. Non-cancer risks from emission sources were not found during different periods. Cancer risks of biomass burning and coal combustion increased rapidly during the haze growth period, while that of coal combustion decreased sharply during the dissipation period. Vehicle emissions, crustal dust, and coal combustion were significant cancer risk sources during different haze stages, cancer risk of each source was the highest during the stable period. Southern Hebei, Northern and central Shaanxi were potential risk regions that affected the health of both adults and children in Shijiazhuang., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Samples of ambient PM 2.5 were collected in the Qingdao harbor area between 21 March and May 25, 2016, and analyzed to investigate the compositions and sources of PM 2.5 and to assess source-specific selected toxic element health risks to workers via a combination of positive matrix factorization (PMF) and health risk (HR) assessment models. The mean concentration of PM 2.5 in harbor area was 48 μg m -3 with organic matter (OM) dominating its mass. Zn and V concentrations were significantly higher than the other selected toxic elements. The hazard index (HI) and cancer risk (R i ) of all selected toxic elements were lower than the United States Environmental Protection Agency (USEPA) limits. There were no non-cancer and cancer risks for workers in harbor area. The contributions from industrial emissions (IE), ship emissions (SE), vehicle emissions (VE), and crustal dust and coal combustion (CDCC) to selected toxic elements were 39.0%, 12.8%, 24.0%, and 23.0%, respectively. The HI values of selected toxic elements from IE, CDCC, SE, and VE were 1.85 × 10 -1 , 7.08 × 10 -2 , 6.36 × 10 -2 , and 3.37 × 10 -2 , respectively; these are lower than the USEPA limits. The total cancer risk (R t ) value from selected toxic elements in CDCC was 2.04 × 10 -7 , followed by IE (6.40 × 10 -8 ), SE (2.26 × 10 -8 ), and VE (2.18 × 10 -8 ). CDCC and IE were the likely sources of cancer risk in harbor area. The Bo Sea and coast were identified as the likely source areas for health risks from IE via potential source contribution function (PSCF) analysis based on the results of PMF-HR modelling. Although the source-specific health risks were below the recommended limit values, this work illustrates how toxic species in PM 2.5 health risks can be associated with sources such that control measures could be undertaken if the risks warranted it., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Factor analysis utilizes the covariance of compositional variables to separate sources of ambient pollutants like particulate matter (PM). However, meteorology causes concentration variations in addition to emission rate changes. Conventional positive matrix factorization (PMF) loses information from the data because of these dilution variations. By incorporating the ventilation coefficient, dispersion normalized PMF (DN-PMF) reduces the dilution effects. DN-PMF was applied to hourly speciated particulate composition data from a field campaign that included the start of the COVID-19 outbreak. DN-PMF sharpened the morning coal combustion and rush hour traffic peaks and lowered the daytime soil, aged sea salt, and waste incinerator contributions that better reflect the actual emissions. These results identified significant changes in source contributions after the COVID-19 outbreak in China. During this pandemic, secondary inorganic aerosol became the predominant PM 2.5 source representing 50.5% of the mean mass. Fireworks and residential burning (32.0%), primary coal combustion emissions (13.3%), primary traffic emissions (2.1%), soil and aged sea salt (1.2%), and incinerator (0.9%) represent the other contributors. Traffic decreased dramatically (70%) compared to other sources. Soil and aged sea salt also decreased by 68%, likely from decreased traffic.

The chemical species in PM 2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM 2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM 2.5 was 124 μg/m 3 during the heating period, and NO 3 - and organic carbon (OC) were the dominant species. The concentrations and percentages of NO 3 - , SO 4 2- , and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM 2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

To identify the critical factors impacting the number concentration of particles with the aerodynamic diameters less than 2.5μm (PNC 2.5 ), the continuous measurement of PNC 2.5 , chemical components in PM 2.5 , gaseous pollutants and meteorological conditions were conducted at an urban site in Tianjin in June 2015. Results indicated that the average PNC 2.5 was 2839±2430 dN/dlogDp 1/cm 3 during the campaign. Compared to other meteorological parameters, the relative humidity (RH) had the strongest relationship with PNC 2.5 , with a Pearson's correlation coefficient of 0.53, and RH larger than 30% influenced strongly PNC 2.5 . The important influence of secondary reactions on PNC 2.5 was inferred due to higher correlation coefficients between PNC 2.5 and SO 4 2- , NO 3 - and ratios that represent the conversion of nitrogen and sulfur oxides to particulate matter (r=0.42-0.49; p<0.01). Under specific RH conditions, there were even stronger correlations between PNC 4 + (r=0.78-0.89; p<0.01) and between PNC 2.5 and ratios that represent the conversion of nitrogen and sulfur oxides to particulate matter (r=0.42-0.49; p<0.01). Under specific RH conditions, there were even stronger correlations between PNC 2.5 and NO 3 - , SO 4 2- , NH 4 + , while those between PNC 2.5 and EC, OC were relatively weak, especially when RH exceeded 50%. Principal component analysis (PCA) and Pearson's correlation analysis indicated that secondary sources, vehicle emission and coal combustion might be major contributors to PNC 2.5 . Backward trajectory and potential source contribution function (PSCF) analysis suggested that the transport of air masses originated from these regions around Tianjin (Liaoning, Hebei, Shandong and Jiangsu) influenced critically PNC 2.5 . The north of Jiangsu, the west of Shandong, and the east of Hebei were distinguished as major potential source-areas of PNC 2.5 by PSCF model., (Copyright © 2018. Published by Elsevier B.V.)

In Xi'an, a city that frequently experiences serious PM pollution in northern China, 1476 PM 10 and 1464 PM 2.5 valid daily filter samples were collected at six sites from December 2014 to November 2015 and analyzed for 29 species. The annual mean PM 10 and PM 2.5 concentrations were 149.4 ± 93.1, 108.0 ± 70.9 μg/m 3 , respectively. Organic carbon (OC) is the predominant PM 2.5 component while crustal material predominated in PM 10 . Sulfate concentrations, which was the largest component in Xi'an PM in previous studies, were lower than nitrate. Winter sulfate, OC, and elemental carbon (EC) have decreased since 2003, while nitrate remained constant in recent years and the ratio of NO 3 - /SO 4 2- increased from 0.4 in 2006 to 1.3 in 2014. This result suggests that the motor vehicle contribution to PM has increased relative to coal-fired power plant emissions over the past decade. The mass fractions of crustal material, sulfate, and EC in PM 2.5 decreased as the PM 2.5 concentrations increased from "clean" days (<50 μg/m 3 ) to the highest values, while nitrate significantly increased. Despite forming through secondary reactions, the high concentrations of SOC and SO 4 2- in winter are attributed to primary emissions and particularly to residential heating and cooking with coal. Primary SOC and SO 4 2- accounted for 33% and 42% of their total PM 2.5 concentrations in winter, respectively. Therefore, control measures applied to these primary sources can substantially improve air quality., (Copyright © 2018. Published by Elsevier Ltd.)

A novel approach was developed to estimate regional contributions to ambient PM 2.5 in Haikou, China. In this paper, the investigation was divided into two main steps. The first step: analysing the characteristics of the chemical compositions of ambient PM 2.5 , as well as the source profiles, and then conducting source apportionments by using the CMB and CMB-Iteration models. The second step: the development of estimation approaches for regional contributions in terms of local features of Haikou and the results of source apportionment, and estimating regional contributions to ambient PM 2.5 in Haikou by this new approach. The results indicate that secondary sulphate, resuspended dust and vehicle exhaust were the major sources of ambient PM 2.5 in Haikou, contributing 9.9-21.4%, 10.1-19.0% and 10.5-20.2%, respectively. Regional contributions to ambient PM 2.5 in Haikou in spring, autumn and winter were 22.5%, 11.6% and 32.5%, respectively. The regional contribution in summer was assumed to be zero according to the better atmospheric quality and assumptions of this new estimation approach. The higher regional contribution in winter might be mainly attributable to the transport of polluted air originating in mainland China, especially from the north, where coal is burned for heating in winter., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Heze city, a medium-size city in Shandong province, Eastern China. Ambient PM 2.5 samples were collected in urban area of Heze from August 2015 to April 2016, and chemical species and sources of PM 2.5 were investigated in this paper. The results indicated that the average concentration of PM 2.5 was 100.9 μg/m 3 during the sampling period, and the water-soluble ions, carbonaceous species included elemental carbon (EC) and organic carbon (OC), as well as elements contributed 32.7-51.7%, 16.3% and 12.5%, respectively, to PM 2.5 . Pearson's correlation analysis showed that the existing form of NH 4 + was more complex and diverse in spring/summer, and ammonium nitrate, ammonium sulfate and ammonium hydrogen sulfate might be major form of NH 4 + in autumn/winter. Correlation analysis between PM 2.5 and SO 4 2- /NO 3 - , PM 2.5 and OC/EC during different seasons suggested that mobile sources might make an important impact on the increase of PM 2.5 concentrations in spring/summer, and stationary sources might play a critical role on the increase of PM 2.5 concentrations in autumn/winter. Seven factors were selected in Positive Matrix Factorization (PMF) models analysis based on the Error Estimation (EE) diagnostics during different seasons. Secondary source had the highest contribution to PM 2.5 in Heze for the whole year, and followed by coal combustion, vehicle exhaust, soil dust, construction dust, biomass burning and metal manufacturing, and their annual contributions to PM 2.5 were 26.5%, 17.2%, 16.5%, 11.5%, 7.7%, 7.0% and 3.8%, respectively. The air masses that were originated from Mongolia reflected the features of large-scale and long-distance air transport; while the air masses that began in Jiangsu, Shandong and Henan showed the features of small-scale and short-distance. Shandong, Henan and Jiangsu were identified as the major potential sources-areas of PM 2.5 by using potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Improved understanding of the fractionation and geochemical characteristic of rare earth elements (REEs) from steel plant emissions is important due to the unclear atmospheric signature of these elements and their adverse impact on human health and the environment. In this study, ambient particulate matter of different sizes was collected from one site in an integrated iron and steelmaking industrial zone (HG) and one urban background site with no direct industrial emissions (ZWY) during a 1-year sampling campaign in China. The total concentrations of REEs for TSP, PM10, and PM2.5 were 27.248, 14.989, 3.542 ng/m(3) in HG and 6.326, 5.274, 1.731 ng/m(3), respectively, in ZWY, which revealed the local influence of the steelmaking activities to the air quality. With respect to ZWY, the REEs in HG site are obviously fractionated in the coarser fraction, and LREEs account for more than 80 % of the total REE burden in all of the samples. Additionally, the REEs in HG and ZWY show a homogeneous trend with successively increased LREE/HREE ratios from the coarse particles to the fine particles. In our samples, La, Ce, Nd, and Sm are the most enriched rare earth elements, especially in the HG site. Moreover, ternary diagrams of LaCeSm indicate that the REEs in HG are potentially contributed by steelworks, carrier vehicles, coal combustion, and road dust re-suspension.

A chemical transport model (CTM) is an essential tool for air quality prediction and management, widely used in air pollution control and health risk assessment. However, the current models do not perform very well in reproducing the observations of some major chemical components, for example, sulfate, nitrate, ammonium and organic carbon. Studies have suggested that the uncertainties in the model chemical mechanism, source emission inventory and meteorological field can cause inaccurate simulation results. Still, the emission source profile (used to create speciated emission inventories for CTMs) of PM 2.5 has not been fully taken into account in current numerical simulation. Based on the characteristics and variation rules of chemical components in typical PM 2.5 sources, different simulation scenarios were designed and the sensitivity of simulated PM 2.5 components to the source chemical profile was explored. Our findings showed that the influence of source profile changes on simulated PM 2.5 components' concentrations cannot be ignored. Simulation results of some components were sensitive to the adopted source profile in CTMs. Moreover, there was a linkage effect: the variation in some components in the source profile would bring changes to the simulated results of other components. These influences are connected to chemical mechanisms of the model since the variation in species allocations in emission sources can affect the potential composition and phase state of aerosols, chemical reaction priority, and multicomponent chemical balance in thermodynamic equilibrium systems. We also found that the perturbation of the PM 2.5 source profile caused variation in simulated gaseous pollutants, which indirectly indicated that the perturbation of source profile would affect the simulation of secondary PM 2.5 components. Our paper highlights the necessity of paying enough attention to the representativeness and timeliness of the source profile when using CTMs for simulation. [ABSTRACT FROM AUTHOR]

Extreme weather events are on the rise against the backdrop of climate change. Impact of tropical cyclone (TC) system, one of the extreme weather events, on air pollution remain poorly understood. A total of 103 recorded TCs (tropical storms and stronger) together with the surface air quality data collected from over 2000 observational sites in mainland China in 2014–2020 were utilized to examine the co‐occurrence of TC with continental ozone (O3) and fine particulate matters (PM2.5) pollution. TCs exhibit cleaning effects on PM2.5 within its coverage (typically ∼650 km), but enhance the co‐occurrence of O3 and PM2.5 in an extended region. The co‐occurrence frequencies are greater than 30% for any two co‐occurring events, and ∼8% for TC + PM2.5 + O3. We observed superregional trans‐boundary transportation of air pollutants driven by TC, led to ubiquitous spatial offsets and temporal lags of O3, PM2.5 pollution and TC, which are often inconsistent with traditional mechanisms such as accelerated chemical reactions for O3 formation. O3 pollution tends to occur 1∼2 days after PM2.5 pollution moved west. In contrast, PM2.5 pollution usually occur 4–12 hr following O3 pollution within a day over most regions except the southeast of China. Such spatial and temporal offsets vary with the paths of TCs. Composite analysis shows that temperature, wind field and large pressure systems are the key factors for air pollution formation and transportation over TC periphery. Our results have implications for understanding the interactions between TCs and air pollution, particularly for coastal areas where there are recurring TCs. Key Points: Tropical cyclones driving superregional trans‐boundary transportation of air pollutantsTropical cyclone (e.g., super typhoon In‐Fa) structure could induce unique distribution of O3 in both horizontal and vertical directionsComposite analysis shows that tropical cyclone associated temperature, wind field and large pressure systems are the key factors forming air pollution [ABSTRACT FROM AUTHOR]

Fine particle (PM2.5) mass concentration and relative humidity (RH) are the primary factors influencing atmospheric visibility. There are some studies focused on the complex, nonlinear relationships among visibility, PM2.5 concentration, and RH. However, the relative contribution of the two factors to visibility degradation, especially for different aerosol types, is difficult to quantify. In this study, the normalized forward sensitivity index method for identifying the dominant factors of visibility was used on the basis of the sensitivity of visibility to PM2.5 and RH changes. The visibility variation per unit of PM2.5 or RH was parameterized by derivation of the visibility multivariate function. The method was verified and evaluated based on 4453 valid hour data records in Tianjin, and visibility was identified as being in the RH-sensitive regime when RH was above 75%. In addition, the influence of aerosol chemical compositions on sensitivity of visibility to PM2.5 and RH changes was discussed by analyzing the characteristics of extinction components ((NH4)2SO4, NH4NO3, organic matter, and elemental carbon) measured in Tianjin, 2015. The result showed that the fitting equation of visibility, PM2.5, and RH, separately for different aerosol types, further improved the accuracy of the parameterization scheme for visibility in most cases. [ABSTRACT FROM AUTHOR]

In recent years, China has experienced severe and persistent air pollution associated with rapid urbanization and climate change. Three years' time series (January 2014 to December 2016) concentrations data of air pollutants including particulate matter (PM 2.5 and PM 10 ) and gaseous pollutants (SO 2 , NO 2 , CO, and O 3 ) from over 1300 national air quality monitoring sites were studied to understand the severity of China's air pollution. In 2014 (2015, 2016), annual population-weighted-average (PWA) values in China were 65.8 (55.0, 50.7) μg m −3 for PM 2.5 , 107.8 (91.1, 85.7) μg m −3 for PM 10 , 54.8 (56.2, 57.2) μg m −3 for O 3 _8 h, 39.6 (33.3, 33.4) μg m −3 for NO 2 , 34.1 (26, 21.9) μg m −3 for SO 2 , 1.2 (1.1, 1.1) mg m −3 for CO, and 0.60 (0.59, 0.58) for PM 2.5 /PM 10 , respectively. In 2014 (2015, 2016), 7% (14%, 19%), 17% (27%, 34%), 51% (67%, 70%) and 88% (97%, 98%) of the population in China lived in areas that meet the level of annual PM 2.5 , PM 10 , NO 2 , and SO 2 standard metrics from Chinese Ambient Air Quality Standards-Grade II. The annual PWA concentrations of PM 2.5 , PM 10 , O 3 _8 h, NO 2 , SO 2 , CO in the Northern China are about 40.4%, 58.9%, 5.9%, 24.6%, 96.7%, and 38.1% higher than those in Southern China, respectively. Though the air quality has been improving recent years, PM 2.5 pollution in wintertime is worsening, especially in the Northern China. The complex air pollution caused by PM and O 3 (the third frequent major pollutant) is an emerging problem that threatens the public health, especially in Chinese mega-city clusters. NO x controls were more beneficial than SO 2 controls for improvement of annual PM air quality in the northern China, central, and southwest regions. Future epidemiologic studies are urgently required to estimate the health impacts associated with multi-pollutants exposure, and revise more scientific air quality index standards. [ABSTRACT FROM AUTHOR]

The OC/EC online monitoring campaign was carried out in Tianjin of China from 8th February to 15th March 2015 during the Chinese Spring Festival period (CSFP). The concentrations of OC, EC, BC and other ambient pollutants (e.g. SO 2 , NO 2 and PM 2.5 , etc.) in high time resolution were measured with related online-monitoring instruments. During the CSFP, according to the peaks of PM 2.5 concentrations and number concentrations (NC) of aerosol particles with aerodynamic diameters between 0.3 and 2.5 μm, five pollution-events were generally identified and displayed. These pollution-events were closely associated with large-scale fireworks displaying, combustion activities such as heating for winter, and the stable meteorological conditions, etc. During the CSFP, EC and OC concentrations showed variations up to one order of magnitude. The uncertainty of instrument itself and the difference for measured methods, further caused the differences between thermal OC (measured OC by thermal method) and optical OC (measured OC by optical method) concentrations, as well as between thermal EC (measured EC by thermal method) and optical EC (measured EC by optical method) concentrations. The high-concentration carbonaceous aerosols could enlarge the uncertainty of measuring instrument, reducing the correlations between OC and EC, and enhance the differences among thermal EC, optical BC and optical EC. The OC/EC ratios and the percentages of SOC/OC would be declined, when the pollution-events formed during the CSFP. Due to the different sources for thermal POC and thermal SOC, the correlation of the two was relatively lower (R 2 = 0.39). Thermal POC dominated over thermal OC during the CSFP. [ABSTRACT FROM AUTHOR]

Ambient PM 2.5 samples were collected in the urban area of Taian in China in August–September and November, 2014. The chemical compositions and emission sources of PM 2.5 were analyzed. The results indicated that the mean concentration of PM 2.5 reached 70.8 μg/m 3 during the non-heating period, and water soluble inorganic ions (WSIIs), carbonaceous materials, including elemental carbon (EC) and organic carbon (OC); and elements contributed 43.80%, 10.34% and 17.36%, respectively, to PM 2.5 . The mean concentrations of WSIIs at three sampling sites decreased in the same order: SO 4 2 − > NH 4 + > NO 3 − > Cl − during the non-heating period. NO 3 − and NH 4 + , SO 4 2 − and NH 4 + , showed extremely significant positive-correlations ( r = 0.79, 0.54; P < 0.01). The variability of OC was larger than the variability of EC during the non-heating period. The high concentration of secondary organic carbon (SOC) could reduce correlation-level between the OC and EC. Moreover, the percentages and concentrations of the total detected elements (TDE) increased significantly, ranging from August–September to November ( P < 0.01). Major sources of PM 2.5 identified from positive matrix factorization (PMF) model and enrichment factors (EFs) included secondary aerosol, coal combustion, metal manufacturing, soil dust/resuspended dust/construction dust and vehicle exhaust/biomass burning, which contributed 27.47%, 17.94%, 19.06%, 9.41% and 16.65%, respectively, to PM 2.5 . The backward trajectory analysis identified three transport pathways that originated from Mongolia (12% of the total trajectories), Inner Mongolia (2%), and southeast of Shandong Province (86%), and the potential source contribution function (PSCF) model identified southeast of Shandong Province was mainly a potential source-area that affected air quality in Taian. [ABSTRACT FROM AUTHOR]

Refined source apportionment plays an important role in precise control of atmospheric particulate matter sources. PM 2.5 samples were collected and analysed in Tian'jin from February to October 2016, and directional contribution of individual source category was apportioned by applying a new approach. Results indicated that the mean concentration of PM 2.5 was 64 μg/m3 during the studying period. NO 3 − and OC were dominated species in PM 2.5 mass. The concentrations of OC and Cl−, and OC/EC were higher in winter than other seasons. Secondary sources (SS), coal and biomass burning (CBB), vehicle exhaust (VE), crustal dust (CD), and industrial emission (IE), were identified as major sources using the PMF model, their contributions to PM 2.5 were 28.6–38.1%, 17.3–20.1%, 21.1–23.5%, 10.9–14.2%, and 4.0–10.3%, respectively. The contributions of dust source and coal combustion in Tian'jin are decreasing, while that of motor vehicles is gradually highlighted. The contribution of secondary sources is maintained at a high level in recent years. Source contributions from the directions 1–3 (SW, NW, NE) for SS (16.8%, 8.5%, 4.0%), CBB (10.1%, 8.5%, 2.0%), VE (8.7%, 7.9%, 3.2%), CD (7.3%, 7.0%, 0.9%), and IE (4.2%, 3.8%, 1.4%), were observed at TG site. Source contributions from the directions1–4 (SW, WNW, NNW, NE) for SS (16.5%, 9.7%, 5.9%, 6.3%), CBB (8.0%, 5.0%, 2.5%, 1.9%), VE (8.5%, 6.8%, 3.5%, 3.3%), CD (5.9%, 3.2%, 2.0%, 1.0%), IE (2.0%, 0.9%, 0.6%, 0.6%), were observed at FK site. The contributions of major sources from SW direction were higher than other directions. • Sources contributions of ambient PM 2.5 from directional directions was apportioned. • Contributions of dust source and coal combustion in Tian'jin are decreasing, while that of vehicles is gradually highlighted. • Contributions of major sources from south-west direction are high at two studying sites. [ABSTRACT FROM AUTHOR]

Abstract Sulfate is a major component of atmospheric fine particulate matter in the troposphere. Globally, observed sulfate concentrations are generally high in summer and low in winter. Current air quality models fail to reproduce high winter sulfate concentrations observed during substantial pollution episodes in northern China. From ambient measurement data, it was reported that contrary to current belief, sulfate, that is normally considered as a secondary species, was actually largely primary. The present study presents direct evidence of primary sulfate emissions from residential coal combustion (RCC) by testing particulate matter (PM) emissions from briquettes and chunk coal burned in a household stove. Sulfate accounted for 16.6 ± 7.7% and 29.2 ± 8.7% of PM 2.5 mass emissions from this stove burning coal briquettes and chunk coal, respectively. Using the 2014 emissions inventory, 1215 tons of PM 10 sulfate were estimated to have been emitted from RCC in Xi'an, a megacity that continually experiences severe PM pollution in northern China. The RCC contribution was also estimated using a constrained positive matrix factorization in which RCC accounted for averages of 26% and 32% of ambient PM 2.5 mass during the heating season at urban and rural sites in Xi'an, respectively. The winter contributions were higher than that during non-heating season. PM 2.5 emissions from RCC during heating season were 1.5–4.0 times those during non-heating season for the urban sites, and 2.5 to 6.8 times those for the rural sites. Thus, severe PM pollution in rural areas resulted from intense household coal combustion for space heating. Primary sulfate from RCC was responsible for a large fraction of ambient sulfate during heating season, on average contributing 38.9% and 49.2% of ambient sulfate mass in PM 2.5 at urban sites and rural sites, respectively. These results highlight the fact that RCC is an important primary source of atmospheric sulfate during the heating season, and provides information that will improve air quality models and support development of more effective abatement strategies for atmospheric particles. Graphical abstract Image 1 Highlights • Particles emissions from residential coal burned in a household stove were measured. • Sulfate constituted 29.2% of PM 2.5 mass from chunk coal combustion. • PMF was constrained with RCC source profile to estimate its emission. • Primary sulfate from RCC contributed 49.2% of wintertime sulfate in rural area. [ABSTRACT FROM AUTHOR]

Abstract Soil fugitive dust (SFD) contributes significantly to ambient particulate matter (PM) in Northern China. In this study, an improved method is developed to establish a high spatial resolution SFD emission inventory through the use of remote sensing (RS) -geographical information system (GIS) technology based on the wind erosion equation (WEQ). The purpose of the application of RS is to obtain vegetation coverage data, which can be achieved through the supervised classification of land use and retrieval of vegetation coverage. Vegetation coverage was then converted to vegetative cover factor by adopting the approach given in this study. Given that the excellent spatial data analysis and the calculation function of the GIS, the high-spatial-resolution vegetative cover factor, soil texture, control efficiency, and other parameters could be multilayer nested and calculated. The SFD emission inventory is eventually obtained, with the highest spatial resolution of 30 m. As an application case, the SFD emission inventory of Tianjin city in 2013 was established with an activity level of 6383 sq. km. bare land, and 27.14 kt, 14.39 kt, 6.240 kt emitted TSP, PM 10 , PM 2.5 , respectively. Moreover, the Calpuff model was used to simulate the contributions of SFD to ambient springtime PM 10 and compare the predicted PM 10 to observation data to explore the feasibility of this method. This study could be a reference for the establishment of a high spatial resolution SFD emission inventory in dust dominated regions, providing information that will meet the requirement of air quality models and support the efforts of government to reduce particulate matter pollution. Graphical abstract Image 1 Highlights • An improved method was developed to establish bottom-up soil fugitive dust emission inventory. • RS-GIS technologies were applied as indispensable tools. • Landsat 8 satellite data was used for interpreting vegetation coverage. • High spatial resolution dust emission inventory of Tianjin was established. [ABSTRACT FROM AUTHOR]

Cooking is a major source of indoor air pollution. Existing studies suggest that organic material is the most abundant component by mass in cooking emissions, while the detailed organic species that result from cooking remains poorly understood. This work provides a comprehensive foundational knowledge of emission arising from typical Chinese residential cooking based on a field-work measurement of polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and the routinely measured fine particulate matter (PM 2.5) composition. Exposure to the Chinese cooking procedures will likely pose a significant health risk, with grilling producing the highest PM 2.5 concentration (28.79 ± 9.36 mg m−3) and the most distinctive composition among the cooking patterns. The PAHs with 3 rings dominated the total PAHs by mass (48.08%), with the major organic species Phenanthrene (Phe), Anthracene (Ant), Benzo [a] pyrene (BaP), and Fluorene (Flu), accounting for 0.0399–0.5966, 0.0091–0.6710, 0.0046–0.4531, and 0.0086–0.3102 ng per μg of PM 2.5 , respectively. Oxygenated VOCs (OVOCs) accounted for 37.98% of the total VOCs. The ratios of Fla/(Fla + Pyr) and IcdP/(IcdP + BghiP) helped in distinguishing residential cooking emissions from other sources. The incremental lifetime cancer risk (ILCR) values of PAHs and VOCs were 6.9 × 10−6–1.8 × 10−5 and 2.7 × 10−6–1.8 × 10−3, respectively, which were substantially higher than the acceptable levels (1.0 × 10−6) established by the U.S. EPA. The considerable health risks posed by Chinese cooking emissions necessitate additional study and control measures to lessen indoor air pollution and protect human health. [Display omitted] • The characterization of PM 2.5 and VOCs from residential cooking were obtained. • Grilling produced the highest PM 2.5 concentration among all the cooking methods. • Phe, Ant, BaP, and Flu could be used as tracers of cooking emissions. • "Fla/(Fla + Pyr)" and "IcdP/(IcdP + BghiP)" have potential of disentangling sources. • The ILCR values of PAHs and VOCs were much higher than the acceptable levels. [ABSTRACT FROM AUTHOR]