Coal Combustion Sources Research Articles

Characteristics and Source Apportionment of Volatile Organic Compounds in August in the Chang-Zhu-Tan Urban Area

Continuous sampling using the tank sampling method were conducted in Changsha, Zhuzhou, and Xiangtan cities from August 18 to 27, 2020, and 106 VOCs species were analyzed using GC-MS analysis. Then, the regional VOCs concentrations, generation potential, and source of VOCs were studied. The results showed that the average φ(VOCs) was (20.5±10.5)×10-9 in the Changsha-Zhuzhou-Xiangtan area, in which OVOCs (33.5%) and alkanes (28.2%) accounted for the highest proportion. The ozone formation potential (OFP) of VOCs was 118.5 μg·m-3, and the contributions of aromatic hydrocarbons, olefin, and OVOCs to OFP were 37.4%, 24.2%, and 23.6%, respectively. The average secondary organic aerosol formation potential (SOAp) of the VOCs was 0.5 μg·m-3, and the contribution of aromatic hydrocarbons to SOAp was 97.0%, among which C8 aromatic hydrocarbons contributed 41.7%. Toluene, m/p-xylene, and o-xylene were the common dominant species that contributed significantly to OFP and SOAp. The characteristic ratio results showed that VOCs in Changsha were relatively influenced by industrial processes and solvent use, whereas Zhuzhou and Xiangtan were more affected by coal and biomass combustion. The PMF results showed that the VOCs mainly came from vehicle exhaust and oil and gas volatilization (27.2%), coal and biomass combustion (23.7%), industrial processes (20.4%), solvent use (17.2%), and natural sources (11.5%) in the Changsha-Zhuzhou-Xiangtan area.

Urban and suburban variations in emission sources and quality-adjusted life year loss of PM2.5-bound PAHs in Beijing, China

Urban and suburban variations in PM2.5-bound PAH compositions, sources and their potential health risk in terms of quality-adjusted life year (QALY) loss were explored, taking Haidian and Fangshan as urban and suburban representatives in Beijing. The annual mean total concentration of 16 priority PAHs in Fangshan (26.95 ng/m3) was higher than that in Haidian (12.59 ng/m3). The concentration of PAHs was much higher during the heating season, with four-ring PAHs as the dominant species. The PMF-PSCF-CPF integrated source apportionment method identified the same three sources in both areas; however, the mass contribution of traffic emissions in Haidian (64.2%) was larger than that in Fangshan (54.7%), while the source of coal and natural gas combustion and the source of biomass combustion, petroleum volatilization and coke oven contributed less (26.4% and 9.3%) than those in Fangshan (32.1% and 13.2%). Potential risk contribution of vehicle emissions (Haidian: 2943.39 QALYs, 91.36%; Fangshan: 6360.58 QALYs, 83.25%) was much greater than its mass contribution because its emission contained more PAH species with high toxicity, such as BaP. QALY loss covers the content of mental health, integrates noncarcinogenic and carcinogenic effects, and can more comprehensively reflect the health loss of affected people, thus being a suitable indicator for determining priority control sources.

Measurement report: The importance of biomass burning in light extinction and direct radiative effect of urban aerosol during the COVID-19 lockdown in Xi'an, China

Abstract. Due to the complexity of emission sources, a better understanding of aerosol optical properties is required to mitigate climate change in China. Here, an intensive real-time measurement campaign was conducted in an urban area of China before and during the COVID-19 lockdown in order to explore the impacts of anthropogenic activities on aerosol light extinction and the direct radiative effect (DRE). The mean light extinction coefficient (bext) decreased from 774.7 ± 298.1 Mm−1 during the normal period to 544.3 ± 179.4 Mm−1 during the lockdown period. A generalised additive model analysis indicated that the large decline in bext (29.7 %) was due to sharp reductions in anthropogenic emissions. Chemical calculation of bext based on a ridge regression analysis showed that organic aerosol (OA) was the largest contributor to bext in both periods (45.1 %–61.4 %), and the contributions of two oxygenated OAs to bext increased by 3.0 %–14.6 % during the lockdown. A hybrid environmental receptor model combined with chemical and optical variables identified six sources of bext. It was found that bext from traffic-related emissions, coal combustion, fugitive dust, the nitrate and secondary OA (SOA) source, and the sulfate and SOA source decreased by 21.4 %–97.9 % in the lockdown, whereas bext from biomass burning increased by 27.1 %, mainly driven by the undiminished need for residential cooking and heating. An atmospheric radiative transfer model was further used to illustrate that biomass burning, rather than traffic-related emissions, became the largest positive effect (10.0 ± 10.9 W m−2) on aerosol DRE in the atmosphere during the lockdown. Our study provides insights into aerosol bext and DRE from anthropogenic sources, and the results imply the importance of controlling biomass burning for tackling climate change in China in the future.

Sources and Formation of Atmospheric Nitrate Over China–Indochina Peninsula in Spring: A Perspective From Oxygen and Nitrogen Isotopic Compositions Based on Passive Air Samplers

The formation processes and potential sources of particulate nitrate can be revealed by nitrogen (δ15N-NO3−) and oxygen (δ18O-NO3−) isotopes; however, the linkage and comparative information over a large scale is limited. In this work, the feasibility of using quartz wool disk passive air samplers (Pas-QW) to identify and quantify the nitrate concentrations and their isotopic compositions was demonstrated. The results of a simultaneous sampling campaign from March to June showed that the NO3− concentration was largely attributed to the development of the regional economies. The regional distribution of δ15N-NO3− values was due to the source changes. The decreasing trend of δ18O-NO3− values with latitude from south to north was mainly a combination of oxygen isotopic fractionation of the oxidant induced by natural factors and anthropogenic changes in O3 concentrations. Coal combustion (CC) and mobile sources (MS) have a significant contribution to NOx in the typical urban agglomerations, while the high contribution from biomass burning (BB) and biogenic soil emission (BS) was mainly in areas with high natural productivity and intensive agricultural activities. By allowing simultaneous monitoring at multiple sites and over extended periods, passive sampling complements existing techniques for studying nitrate aerosol, and the results can provide a reference for the spatial distribution of its sources and formation in the China–Indochina Peninsula (CICP).

Effect of indoor coarse particulate matter on blood pressure and lung function of male patients with chronic obstructive pulmonary disease: Perspectives of constituent, source and season

BackgroundEvidence regarding the cardiopulmonary effects of indoor coarse particulate matter (PM2.5-10) and its chemical constituents and sources remains limited. MethodsFive consecutive daily visits (200 person-visits in total) were completed among 40 male patients with chronic obstructive pulmonary disease (COPD) in this panel study from November 2015 to May 2016 in Beijing, China. Daily indoor PM2.5-10 was collected and twenty-one elements were measured using inductively coupled plasma mass spectrometry. Lung function and blood pressure were measured at daily visit. Principal component analysis (PCA) was used for source appointment. Bayesian kernel machine regression (BKMR) and linear mixed-effect models were used to establish the exposure-response relationships. ResultsAn interquartile range (IQR, 23.12μg/m3) increase in 1-day average concentration of indoor PM2.5-10 was associated with changes of 0.88 (95CI: -0.25, 2.01) mmHg in systolic blood pressure (SBP), 1.15 (95CI: 0.25, 2.06) mmHg in diastolic blood pressure (DBP), -2.29% (95CI: -4.07%, -0.51%) in forced expiratory volume in the first second (FEV1) and -1.68% (95CI: -3.41%, 0.06%) in peak expiratory flow (PEF). According to the results of PCA, soil/dust, coal combustion, and natural Ni/Cr sources were identified as three main sources of indoor PM2.5-10 inorganic elements. BKMR analysis revealed a significant association of all measured constituents with elevated SBP and a negative trend of FEV1. Coal combustion-related constituents posed a stronger joint effect on blood pressure than the other two sources. Stronger associations of indoor PM2.5-10 constituents with elevated blood pressure and decreased PEF were observed during the heating period than during the non-heating period. And the adverse effects of coal combustion-related constituents on blood pressure and lung function were also stronger in the heating season. ConclusionsIndoor PM2.5-10 constituents were associated with impaired cardiopulmonary health of COPD patients, and those from coal combustion source may play a dominant role, especially during the heating period.

Pollution Characteristics and Source Apportionment of Atmospheric Volatile Organic Compounds in Summer in Yuncheng City

Based on the online monitoring data of VOCs, O3, and NO2 in Yuncheng City from June to August 2020, the pollution characteristics of VOCs in Yuncheng City in summer were analyzed. At the same time, the main emission sources were determined using a PMF model, and the chemical reactivity of VOCs was evaluated using the maximum incremental reactivity (MIR) method and fractional aerosol coefficients (FAC). The results showed that the urban area of Yuncheng was seriously polluted by VOCs and NO2 in the early morning and evening during summer, the peak value of VOCs daily variation occurred at 08:00 and 20:00, respectively, and was mainly affected by the morning and evening peaks in traffic. The ρ(VOCs) from June to August was 50.52 μg·m-3, and the species with the highest proportion were alkanes (39.39%) and oxygenated volatile organic compounds (OVOCs, 34.63%). Five VOCs emission sources were determined by the PMF model, of which the largest contribution was from motor vehicle exhaust emission sources (33.10%), followed by industrial emission sources (29.46%), natural gas and coal combustion sources (17.31%), solvent use sources (11.94%), and plant emission sources (8.19%). Controlling motor vehicle exhaust emission sources is the key to alleviate VOCs pollution in summer in Yuncheng City. The average ozone formation potential (OFP) of VOCs was 162.88 μg·m-3, in which OVOCs had the highest contribution rate (45.37%); acetaldehyde, propionaldehyde, ethylene, isoprene, and toluene were the key active components; and industrial emission sources were the emission sources with the highest contribution rate. The average value of secondary organic aerosol formation potential (SOAp) of VOCs was 0.40 μg·m-3, in which the contribution rate of aromatic hydrocarbons was the highest (88.00%), and the solvent use source was the emission source with the highest contribution rate.

Concentration Variation and Source Analysis of Metal Elements in PM2.5 During COVID-19 Control in Suzhou

To study the variation in concentration and source analysis of metal elements during COVID-19 control in Suzhou, a multi-metal online monitor was used to determine hourly online data of 14 metal elements from December 1, 2019 to March 31, 2020. This study analyzed variation in concentration and source analysis of metal elements using a PMF model before, during, and after shutdown during COVID-19 control. The results showed that the concentrations of Cr, Mn, Zn, and Fe during shutdown decreased the most, by 87.6%, 85.6%, 78.3%, and 72.2%, respectively, compared with those before shutdown. The concentrations of Mn, Cr, Zn, and Fe after shutdown increased the most, by 227.0%, 215.4%, 147.4%, and 113.4%, respectively, compared with those of the previous stage. The diurnal variation in K differed at three stages. Zn showed a single peak shape at three stages, but the peak width and peak time were different. Unlike the concentrations, the diurnal variations in Fe, Mn, Pb, Se, and Hg were not significantly changed. The daily variation characteristics of Ca, Ba, Cu, As, Cr, and Ni during and after shutdown were significantly different from those before shutdown. The results of source analysis by the PMF model showed that metal elements mainly came from dust, motor vehicle, coal burning, industrial smelting, and mixed-combustion sources. Among them, the concentration of industrial smelting sources changed greatly, with the concentration decreasing by 89.0% during shutdown and increasing by 358.0% after shutdown.

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.

Investigating the relationship between mass concentration of particulate matter and reactive oxygen species based on residential coal combustion source tests

Particulate matter (PM) has been considered to be closely related to human health, especially fine particulate matter. However, whether PM mass concentration alone is a good indicator for health impact remains a challenging question. In this study, emissions from residential coal combustion (RCC), one of the important PM sources in northern China, were tested to examine the relationship between the emission factors of particle-generated reactive oxygen species (ROS) (EFROS) and PM (EFPM). A total of 24 combinations of source tests were conducted, including eight types of coal with different geological maturities (two anthracites and six bituminous) burned in three types of stoves (one honeycomb coal stove, one old chunk stove, and one new chunk stove). Here, ROS was defined as generated hydroxyl radical (·OH) by PM, and results showed EFROS from 24 residential coal combustion varied greatly by nearly 20 times. EFROS ranged 0.78–14.85 and 2.99–12.91 mg kg−1 for the emissions from honeycomb and chunk coals, respectively. Moreover, the correlation between EFROS and EFPM was significantly positive in honeycomb coal emissions (r = 0.82, p < 0.05), but it was insignificant in chunk coal emissions (r = 0.07, p > 0.05). For honeycomb coal emissions, organic carbon (OC) was quite abundant in PM and it might be the predominant contributor to both EFPM and EFROS, resulting in a strong and positive correlation. For chunk coal emissions, high EFROS was mainly related to relatively high metal emissions in AN and LVB, while the metals were not major components in PM, leading to a poor correlation between EFPM and EFROS. Therefore, this study revealed that PM was not always positively correlated with ROS from residential coal burning, and the relationship was mainly determined by the compositions of PM, suggesting PM mass concentration alone may not be the best indicator for assessing health impacts.

Impacts of Household Coal Combustion on Indoor Ultrafine Particles-A Preliminary Case Study and Implication on Exposure Reduction.

Ultrafine particles (UFPs) significantly affect human health and climate. UFPs can be produced largely from the incomplete burning of solid fuels in stoves; however, indoor UFPs are less studied compared to outdoor UFPs, especially in coal-combustion homes. In this study, indoor and outdoor UFP concentrations were measured simultaneously by using a portable instrument, and internal and outdoor source contributions to indoor UFPs were estimated using a statistical approach based on highly temporally resolved data. The total concentrations of indoor UFPs in a rural household with the presence of coal burning were as high as 1.64 × 105 (1.32 × 105–2.09 × 105 as interquartile range) #/cm3, which was nearly one order of magnitude higher than that of outdoor UFPs. Indoor UFPs were unimodal, with the greatest abundance of particles in the size range of 31.6–100 nm. The indoor-to-outdoor ratio of UFPs in a rural household was about 6.4 (2.7–16.0), while it was 0.89 (0.88–0.91) in a home without strong internal sources. A dynamic process illustrated that the particle number concentration increased by ~5 times during the coal ignition period. Indoor coal combustion made up to over 80% of indoor UFPs, while in an urban home without coal combustion sources indoors, the outdoor sources may contribute to nearly 90% of indoor UFPs. A high number concentration and a greater number of finer particles in homes with the presence of coal combustion indicated serious health hazards associated with UFP exposure and the necessity for future controls on indoor UFPs.

Historical trends in atmospheric metal(loid) contamination in North China over the past half-millennium reconstructed from subalpine lake sediment

Trace metal (loid) contamination in the atmosphere is widely monitored, but there is a gap in understanding its long-term patterns, especially in North China, which is currently a global contamination hotspot mainly caused by heavy industry emissions and coal combustion. Herein, historical trends of atmospheric As, Cd, Cr, Cu, Hg, Ni, Pb and Zn contamination in North China over the past ∼500 years are comparatively studied with sediment cores from two subalpine lakes (Gonghai and Muhai). Arsenic, Pb, Cd and Hg were main pollutants according to Pb isotopes and enrichment factors. Mercury contamination has increased continuously since the late 1800s and increasing As, Pb and Cd contamination started in the 1950s in Gonghai. In contrast, the contamination in Muhai lagged two decades for As, Cd and Pb and a half-century for Hg behind that in Gonghai, although the trends were similar. This contamination lag was attributed to the low sensitivity of Muhai sediment to early weak atmospheric metal contamination under 2.1-fold higher detrital sedimentation. As, Pb and Cd contamination has intensified since the 1980s, and the metals showed similar sedimentary fluxes in the cores. However, sedimentary fluxes of Hg contamination were 3.4-fold higher in Gonghai than in Muhai due to combination with organic matter. No obvious Cr, Cu and Ni contamination in the cores was mainly because of the low atmospheric deposition from anthropogenic sources relative to detrital input, although some of their atmospheric emissions were higher than those of As, Cd and Hg. Atmospheric As, Pb and Cd contamination was mainly from domestic sources of coal combustion and nonferrous smelting. Mercury contamination was mainly from global and Asian sources in the first half of the 20th century, and domestic emissions gradually dominated Hg contamination after the mid-1900s.

Source Analysis of Ambient PM2.5 in Wuhan City Based on Random Forest Model

Based on the online monitoring data of fine particle(PM2.5) mass concentration, carbonaceous components, ionic constituents, and elemental components in an urban site of Wuhan from December 2019 to November 2020, the chemical characteristics of PM2.5 were analyzed. In addition, seasonal source apportionment of PM2.5 was conducted using the principal component analysis(PCA) method and random forest(RF) algorithm model. The results indicated that ρ(PM2.5) was the highest in winter[(61.33±35.32) μg·m-3] and the lowest in summer[(17.87±10.06) μg·m-3]. Furthermore, organic carbon(OC), with a concentration of(7.27±3.51) μg·m-3, accounted for the major proportion compared with that of elemental carbon(EC) in the carbonaceous component of PM2.5. NO3-, SO42-, and NH4+ had the highest proportion in ionic components, with concentrations of (11.55±3.86),(7.55±1.53), and (7.34±1.99) μg·m-3, respectively. K, Fe, and Ca were the main elements in elemental components, with concentrations of (752.80±183.98),(542.34±142.55), and (459.70±141.99) ng·m-3, respectively. Relying on main factor extraction by PCA and quantitative analysis by RF, five emission sources were ultimately confirmed. The seasonal concentration distribution of these emission sources was as follows:coal burning and secondary sources(46%, 39%, 41%, and 52% for spring, summer, autumn, and winter, respectively) made the highest contribution to PM2.5, followed by vehicle emission sources(22%, 28%, 27%, and 21%), industrial emission sources (14%, 18%, 17%, and 13%), dust sources (10%, 8%, 6%, and 6%), and biomass burning sources (8%, 7%, 9%, and 8%). The valuation of the RF model was evaluated using multiple indicators, including RMSE, MSE, and R2. The evaluation results showed that the model for winter had the best performance (R2=0.974, RMSE=3.795 μg·m-3, MAE=2.801 μg·m-3), the models for spring (R2=0.936, RMSE=3.512 μg·m-3, MAE=2.503 μg·m-3) and autumn (R2=0.937, RMSE=4.114 μg·m-3, MAE=3.034 μg·m-3) performed with moderate-fitting goodness, and the summer model showed a relatively weak-fitting performance (R2=0.866, RMSE=5.665 μg·m-3, MAE=3.889 μg·m-3). The RF model had a satisfactory performance in PM2.5 source apportionment and had excellent prospects in analyzing massive historical data of air pollutants.

Sources and Seasonal Variance of Ambient Volatile Organic Compounds in the Typical Industrial City of Changzhi, Northern China

Volatile organic compounds (VOCs) emitted from industrial processes, which are major emission sources of air pollutants, could cause significant impacts on air quality. However, studies on the comprehensive analysis from sources contributing to the health risk perspective regarding ambient VOCs in industrial cities are limited. In this study, VOC samples were collected from 15 April 2018 to 19 October 2018 in Changzhi, a typical industrial city in northern China, and a total of 57 VOCs were measured for analysis. The average VOC concentrations were 54.4 µg·m−3, with the highest concentrations in autumn (58.4 µg·m−3). Ambient VOCs in spring, summer and autumn were all dominated by alkanes (66.8%), with contributions of 70.3%, 66.3% and 63.8%, respectively. The top five concentrations of total VOCs were isopentane (19.0%), ethane (9.5%), n-butane (8.1%), benzene (7.9%) and propane (5.2%), indicating that vehicle exhaust and coal combustion are the main sources of VOCs. Source apportionment by principal component analysis showed that vehicle exhaust (27.5%) and coal combustion (23.5%) were the main sources of VOCs in Changzhi, followed by industrial production (17.4%), solvent evaporation (13.5%), liquefied petroleum gas/natural gas leaking (9.5%), and biogenic emissions (8.7%). Sources of coal combustion and vehicle exhaust contributed more VOCs than industrial production. The carcinogenic risks of benzene (3.4 × 10−5) and ethylbenzene (2.2 × 10−6) were higher than the limit levels (1 × 10−6). Coal combustion contributed most (25.3%) to the carcinogenic risks because of its high VOC emissions. In an industrial city such as Changzhi, vehicle exhaust and coal combustion have become major sources of ambient air VOCs owing to the increasingly stringent industrial standards. Therefore, VOCs from vehicle exhaust and coal combustion also need to take into account mitigation measures for VOCs from the perspective of source contribution to health risk.

Refined source apportionment of residential and industrial fuel combustion in the Beijing based on real-world source profiles

Residential and industrial emissions are considered as dominant contributors to ambient fine particulate matter (PM2.5) in China. However, the contributions of residential and industrial fuel combustion are difficult to distinguish because specific source indicators are lacking. In this study, real-world source testing was performed on residential coal, biomass and industrial combustion, industrial processes, and diesel and gasoline vehicle source emissions in the Beijing-Tianjin-Hebei region, China. PM2.5 emission factors and chemical profiles, including 97 compositions (e.g., carbonaceous matter, water-soluble ions, elements, EPA priority polycyclic aromatic hydrocarbons (EPAHs), methyl PAHs (MPAHs), and n-alkanes) were obtained for the aforementioned sources. The results showed high OC1, OC2, fluoranthene, methyl fluoranthene, and retene in emissions from residential coal combustion, high OC3, sulfate, Ca, and iron abundance in emissions from industrial combustion, and high Pb and Zn loadings in emissions from industrial processes. Furthermore, specific diagnostic ratios were determined to distinguish between residential and industrial fuel combustion. For example, the ratios of MPAHs/EPAHs (>1) and Mfluo/Fluo (>5) can be used as fingerprinting ratios to distinguish residential coal combustion from other sources. Finally, 1-h resolution refined source apportionments of PM2.5 were conducted in Beijing during two haze events (EP1 and EP2) with a chemical mass balance (CMB) model based on the localized real-world source profiles established in this study. Source apportionment results of CMB showed that the contributions of industrial and residential fuel combustion were 19.4% and 30.8% in EP1 and 26.8% and 18.1% in EP2, respectively, which were comparable to the results of the positive matrix factorization model (R2 = 0.82). This study provides valuable information for the successful and accurate determination of the contributions of residential and industrial fuel combustion to ambient PM2.5.

Source apportionment of polycyclic aromatic hydrocarbons (PAHs) in a sediment core from Lake Dagze Co, Tibetan Plateau, China: Comparison of three receptor models

Receptor models are a useful tool for identifying sources of polycyclic aromatic hydrocarbons (PAHs) in multiple environmental media. In this study, three different receptor models (including the principal component analysis-multiple linear regression (PCA-MLR), positive matrix factorization (PMF), and Unmix models) were used to apportion the sources of 16 priority PAHs in a sediment core of Lake Dagze Co. The ∑PAHs (sum of all 16 measured PAHs) concentrations ranged from 51.89 to 132.82 ng/g with an average of 80.39 ng/g. The ∑PAHs were dominated by 2-3 ring PAHs, accounting for 80.12% on average, thereby indicating that they mainly originated from biomass and coal combustion and/or from long-range atmospheric transportation. The three models produced consistent source apportionment results. The greatest contributor to ∑PAHs was biomass combustion, followed by coal combustion, vehicle emissions, and petrogenic sources. Moreover, the temporal variation of the common sources was well-correlated among models. The multi-method comparison and evaluation results showed that all three models were useful tools for source apportionment of PAHs, with the PMF model providing better results than the PCA-MLR and Unmix models. The temporal trends of factor contributions were verified by PAHs with different ring numbers. Significant correlations were found between the simulated concentrations of each source factor and the PAHs with different ring numbers (P<0.01), except for the petrogenic source identified by the Unmix model (P>0.05). This study can provide useful information for further investigation of source apportionment of PAHs in the sediment cores.

Regional heterogeneities in the emission of airborne primary sugar compounds and biogenic secondary organic aerosols in the East Asian outflow: evidence for coal combustion as a source of levoglucosan

Abstract. Biomass burning (BB) significantly influences the chemical composition of organic aerosols (OAs) in the East Asian outflow. The source apportionment of BB-derived OA is an influential factor for understanding their regional emissions, which is crucial for reducing uncertainties in their projected climate and health effects. We analyzed here three different classes of atmospheric sugar compounds (anhydrosugars, primary sugars, and sugar alcohols) and two types of biogenic secondary organic aerosol (BSOA) tracers (isoprene- and monoterpene-derived SOA products) from a year-long study that collected total suspended particulate matter (TSP) from an island-based receptor site in Gosan, South Korea. We investigate the seasonal variations in the source emissions of BB-derived OA using mass concentrations of anhydrosugars and radiocarbon (14C-) isotopic composition of organic carbon (OC) and elemental carbon (EC) in ambient aerosols. Levoglucosan (Lev) is the most abundant anhydrosugar, followed by galactosan (Gal), and mannosan (Man). Strong correlations of Lev with Gal and Man, along with their ratios (Lev/Gal is 6.65±2.26; Lev/Man is 15.1±6.76) indicate the contribution from hardwood burning emissions. The seasonal trends revealed that the BB impact is more pronounced in winter and fall, as evidenced by the high concentrations of anhydrosugars. Likewise, significant correlations among three primary sugars (i.e., glucose, fructose, and sucrose) emphasized the contribution of airborne pollen. The primary sugars showed higher concentrations in spring/summer than winter/fall. The fungal spore tracer compounds (i.e., arabitol, mannitol, and erythritol) correlated well with trehalose (i.e., a proxy for soil organic carbon), suggesting the origin from airborne fungal spores and soil microbes in the East Asian outflow. These sugar alcohols peaked in summer, followed by spring/fall and winter. Monoterpene-derived SOA tracers were most abundant compared to isoprene SOA tracers. Both BSOA tracers were dominant in summer, followed by fall, spring, and winter. The source apportionment based on multiple linear regressions and diagnostic mass ratios together revealed that BB emissions mostly contributed from hardwood and crop residue burning. We also found significant positive linear relationships of 14C-based nonfossil- and fossil-derived organic carbon fractions with Lev C, along with the comparable regression slopes, suggesting the importance of BB and coal combustion sources in the East Asian outflow.

Pollution Characteristics and Health Risk of Heavy Metals in Fugitive Dust Around Zhaotong City

In order to explore the pollution characteristics and health risks of heavy metals in fugitive dust around the urban areas of Zhaotong City, road dust and soil dust samples were collected in the Zhaoyang District of Zhaotong City in May 2019. The dust samples were suspended using a particle resuspension system to obtain PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm). The concentrations of Ca, Al, Fe, Mg, Ti, V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd, and Pb in PM2.5 were quantified by ICP-MS and ICP-OES. By analyzing 10 types of heavy metals in PM2.5, the results showed that the average concentration of Mn was the highest in the soil fugitive dust, followed by Cr, Ni, Zn, Cu, Co, Pb, V, As, and Cd. The average concentration of Zn in the road fugitive dust was the highest, followed by Mn, Cu, Cr, Pb, Ni, As, Co, V, and Cd. The enrichment factor (EF) indicated that Cd was strongly enriched in the two types of fugitive dust. The EFs of Cu, Zn, and Pb in road fugitive dust showed a moderate enrichment, and they were higher than those in soil fugitive dust. Correlation and principal component analysis showed that heavy metals in the two types of fugitive dust were affected by coal burning sources. At the same time, heavy metals in soil fugitive dust were affected by agricultural activity sources, and heavy metals in road fugitive dust were affected by traffic sources. The results of the health risk assessment indicated that the carcinogenic risks of Cr, Co, Ni, As, and Cd in soil fugitive dust were higher than those in road fugitive dust. The non-carcinogenic risks of heavy metals in the two types of fugitive dust for children were higher than those for adults, and the non-carcinogenic risks of Cu, Zn, and Pb in road fugitive dust were higher than those in soil fugitive dust.

Sources of airborne particulate matter-bound metals and spatial-seasonal variability of health risk potentials in four large cities, South Korea

Fifteen airborne particulate matter-bound metals were analyzed at 14 sites in four large cities (Seoul, Incheon, Busan, Daegu) in South Korea, between August 2013 and June 2017. Among the seven sources resolved by positive matrix factorization, soil dust and marine aerosol accounted for the largest and second largest portions in the three cities; however, in Seoul, soil dust and traffic occupied the largest and the second largest, respectively. Non-carcinogenic risk assessed by inhalation of eight metals (Cd, Co, Ni, Pb, As, Al, Mn, and V) was greater than the hazard index (HI) of 1 at four sites located at or near the industrial complexes. Cumulative incremental lifetime cancer risk (ILCR) due to exposure to five metals (Cd, Co, Ni, Pb, and As) exceeded the 10−6 cancer benchmark at 14 sites and 10−5 at six sites, which includes four sites with HI greater than 1. The largest contributor to ILCR was coal combustion in Seoul, Incheon, and Daegu, and industry sources in Busan. Moreover, industry sources were the largest contributors to non-carcinogenic risk in Seoul, Busan, and Daegu, and soil dust was in Incheon. Incheon had the highest HI in spring because of the higher contribution of soil dust sources than in other seasons. The higher ILCR in Incheon in spring and winter and higher ILCR and HI in Daegu in autumn were mainly due to the influence of industry or coal combustion sources. Statistically significant differences in the ILCR and HI values among the sampling sites in Busan and Daegu resulted from the higher contribution of industry sources at a certain site in the respective city.

Associations between Source-Specific Fine Particulate Matter and Mortality and Hospital Admissions in Beijing, China.

The health effects of PM2.5 exposure have become a major public concern in developing countries. Identifying major PM2.5 sources and quantifying the health effects at the population level are essential for controlling PM2.5 pollution and formulating targeted emissions reduction policies. In the current study, we have obtained PM2.5 mass data and used positive matrix factorization to identify the major sources of PM2.5. We evaluated the relationship between short-term exposure to PM2.5 sources and mortality or hospital admissions in Beijing, China, using 441 742 deaths and 9 420 305 hospital admissions from 2013 to 2018. We found positive associations for coal combustion and road dust sources with mortality. Increased hospital admission risks were significantly associated with sources of vehicle exhaust, coal combustion, secondary sulfates, and secondary nitrates. Compared to the cool season, excess mortality risk estimates of coal combustion source were significantly higher in the warm season. Our findings show that reducing more toxic sources of PM2.5, especially coal emissions, and developing clean energy alternatives can have critical implications for improving air quality and protecting public health.

Characteristics and sources of environmentally persistent free radicals in PM2.5 in Dalian, Northeast China: correlation with polycyclic aromatic hydrocarbons.

Environmentally persistent free radicals (EPFRs) are an emerging class of environmental hazardous contaminants that extensively, stably exist in airborne particulate matter and pose harmful effects on human health. However, there was little research about the sources of EPFRs in actual atmospheric conditions. This study reported the occurrence, characteristics, and sources of EPFRs and polycyclic aromatic hydrocarbons (PAHs) in PM2.5 collected in Dalian, China. The concentrations of PM2.5-bound EPFRs ranged from 1.13 × 1013 to 8.97 × 1015 spins/m3 (mean value: 1.14 × 1015 spins/m3). Carbon-centered radicals and carbon-centered radicals with adjacent oxygen atoms were detected. The concentration of ∑PAHs ranged from 1.09 to 76.24ng/m3, and PAHs with high molecular weight (HMW) were predominant species in PM2.5. Correlation of EPFRs with SO2, NO2, O3, and 12 kinds of PAHs indicated that both fuel (coal and biomass) combustion and photoreaction in atmosphere influenced the concentrations of EPFR. The positive matrix factorization (PMF) model results have shown that the primary sources contributed most of the EPFRs and those of secondary sources had a little proportion. Coal combustion (52.4%) was the primary contributor of EPFRs, followed by traffic emission (22.6%), industrial sources (9.6%), and secondary sources (9.2%) during the heating period, whereas industrial emission (39.2%) was the primary contributor, followed by coal combustion (38.1%), vehicular exhaust (23.5%), and secondary sources (9.6%) during the non-heating period. The finding of the present study provides an important evidence for further study on the formation mechanism of EPFRs in actual atmospheric to control the air pollution.