Hourly concentrations of non-methane hydrocarbons (NMHCs) were collected at a background monitoring site between April of 2004 and March of 2005 and at suburban and urban sites between March and ...December of 2006. The sources of NMHCs were identified and associated health risks through the inhalation pathway were evaluated. Positive matrix factorization (PMF) results showed that solvent sources account for the largest portion of the total NMHCs at suburban and urban areas in South Korea, and the risk assessment combined with the PMF results indicated that risk-weighted contributions of solvent sources were enhanced compared to the absolute contribution (from 52% to 68% in suburban areas and from 47% to 80% in urban areas). Carcinogenic risk due to benzene exposure exceeded the one-in-a-million (i.e., 10
−6) cancer benchmark at all three study sites, and the fractions of the population with greater than the benchmark level were 87%, 99%, and 98% in the background, suburban, and urban sites, respectively. Common benzene sources of three study sites were predicted to be Shandong in China based on the 120 h potential source contribution function (PSCF) analysis.
To prioritize management options for NMHC sources, risk term may give more meaningful information than amount term. This study suggests that controlling solvent sources would be better option for the mitigation of non-carcinogenic health risk from airborne NMHCs. In addition, the identification of benzene sources using PSCF can be used to assist policymakers in developing regional measures to reduce benzene.
► Solvent use was the largest source of ambient NMHCs at suburban and urban areas. ► Risk-weighted portion of solvent source was greater than their absolute portion. ► Carcinogenic risk due to benzene exceeded 10
−6 benchmark at all three study sites. ► Common benzene sources were predicted to be Shandong in China based on 120 h PSCF
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Daily PM2.5 samples were obtained at the site of East China University of Science and Technology (ECUST) in urban Shanghai during 2009–2010 and 2011–2012. The temporal variations of PM2.5 and its ...chemical compositions including secondary inorganic aerosol (SIA) and carbonaceous components were studied. The concentrations of PM2.5 were (94.04±52.17) μg/m3 and (68.44±41.57) μg/m3 in 2009 and 2012, respectively. The concentrations and contributions of SIA to PM2.5 were significantly higher in 2012 than those in 2009. Sulfate took up above 50% of SIA in 2009 and the corresponding value decreased to 41% in 2012. The increasing trend of NO3−/SO42− mass ratio implied that the contributions of mobile sources were more and more important. The molar ratios of NH4+/(2SO42−+NO3−) were 0.57 and 0.70, lower than 1, which demonstrated that most aerosol samples were ammonium-poor. But the neutralization process of ammonium might affect the formation of sulfate and nitrate, which was indicated by the strong correlation between NH4+–SO42− and NH4+–NO3−. The average molar ratio of ammonium to sulfate was 1.74 in 2009, so there was not enough ammonium to neutralize sulfate sufficiently. The higher value of 2.30 in 2012 indicated that sulfate was sufficiently neutralized by ammonium and the predominant production was (NH4)2SO4. Aerosol samples had higher char-EC/soot-EC ratios and lower OC/EC ratios in 2009 than those of samples in 2012. The higher K+/OC values demonstrated that biomass burning made important contributions to carbonaceous components in both 2009 and 2012.
All backward trajectories were grouped into four clusters, mainly from the Northwest, the Circum-Bohai-Sea Region (CBSR), the Southwest and the Southeast. The cluster from the Northwest was the most polluted pathway in 2009, while the cluster from the CBSR had more effects in 2012. PSCF model for PM2.5 and carbonaceous components except soot-EC suggested that the Yangtze River Delta Region (YRDR) made significant contributions by short-range transportation in 2009 and 2012. The Northwest, the CBSR and the Pearl River Delta Region (PRDR) were also the potential source areas. However, the source pattern of soot-EC was significantly different from those of other carbonaceous components.
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•The significant increasing trend of nitrate is obtained.•Most aerosol samples were ammonium-poor in both 2009 and 2012.•Mobile sources and the secondary aerosol reactions are more and more important.•The dominant transportation pathways are identified by backward trajectory cluster.•PSCF model demonstrated that the YRDR are the main potential source areas.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
In this study, we investigated the transport pathways and potential sources of PM10 in Shanghai based on PM10 monitoring data recorded from 2006 to 2009 using three methods: backward trajectory ...cluster analysis, trajectory sector analysis (TSA) and potential source contribution function (PSCF). Seven clusters were generated from the backward trajectory cluster, and two potential sources were identified from the PSCF method. Among the seven clusters, three northerly clusters corresponded to the winter monsoon. The northerly air flow transported high-concentration PM10 that had been emitted from northwestern sources, including Hebei, Shandong, Anhui and Jiangsu to Shanghai in winter and spring. The other three southerly clusters were associated with the summer monsoon caused by the Indian low and the Subtropical high over the western Pacific Ocean controlling the weather patterns of the eastern coastal area in summer. Corresponding to the southerly path, the PSCF method also identified a southwestern source including Zhejiang, Jiangxi and Fujian. The remaining eastern cluster, which represented the transition of monsoons, did not contribute much to the PM10 concentration in Shanghai. According to the results of TSA, the relative PM10 contribution to Shanghai of the northwestern source was approximately twice that of the southwestern source.
► We combined three methods to investigate the transport pathways and potential sources of PM10 in Shanghai. ► Seven clusters were generated corresponding to the effect of East Asian monsoons. ► The northwestern and southwestern areas were two sources influencing Shanghai. ► The northwestern source was the dominant one affecting Shanghai in winter and spring.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Nonmethane hydrocarbons (NMHCs) have an important influence on the formation of photochemical smog and secondary organic aerosols in the atmosphere. We investigated 55 NMHCs in Chengdu from 27 ...October 2016 to 30 September 2017 to identify their sources, pollution levels, and secondary transformation potential. The average concentration of NMHCs in Chengdu was 41.8 ± 20.8 ppbv. Meteorological conditions play a vital role in the formation and dispersion of NMHCs, PM2.5, and O3. The photochemical conversion of NMHCs was inhibited by lower solar radiation, leading to low O3 concentrations and high NMHC concentrations. Aromatics and alkenes played a leading role in the secondary transformation, accounting for 60 ± 16% and 29 ± 11% of the total secondary formation potential, respectively. The southwest air mass trajectory was the most significant transportation path affecting the NMHC concentration in Chengdu. The results of the positive matrix factorization model indicated that there were seasonal differences in the sources of NMHCs in Chengdu. Four major emission sources were identified, namely, vehicle exhaust, industrial, paint solvents, and biogenic sources. Vehicle exhaust emissions were the greatest contributor to NMHCs in Chengdu, accounting for approximately 45% of the NMHCs. Overall, toluene, m/p‐xylene and ethylbenzene constitute a large fraction of the calculated ozone and secondary aerosol formation potential. Future studies should consider targeting these compounds when evaluating ozone and aerosol reduction strategies. However, in terms of total control of NMHC pollution, Chengdu should focus on effective control measures for traffic emissions.
Plain Language Summary
Nonmethane hydrocarbons (NMHCs) can enhance atmospheric oxidation, promote the formation of secondary pollutants, and affect air quality and human health in urban areas, as well as have an indirect effect on global climate change. The unique topographical factors, adverse meteorological conditions, and high pollution emissions make the levels, sources, and secondary transformation of NMHC pollution in Chengdu a vital and meaningful research topic. In this study, gas chromatography was used to conduct field observations of NMHCs in Chengdu from 27 October 2016 to 30 September 2017 with a 30‐min time interval to establish a detailed analysis system for NMHCs. The analysis results showed that (1) aromatics and alkenes played a leading role in secondary transformation, (2) the trajectories from the southwest were the most important transport pathways influencing the concentrations of NMHCs in Chengdu, and (3) vehicle exhaust was the primary source of NMHCs in the Chengdu urban area. Through the above conclusions, we can formulate suitable pollution control measures in Chengdu. This work is of great significance to the improvement of air quality in Chengdu.
Key Points
Based on the multieffect assessment method, aromatics and alkenes played a leading role in secondary transformation
Western and southern Chengdu are the potential source regions of strong pollutant discharge of nonmethane hydrocarbons in Chengdu
The sources show seasonal differences, and vehicle exhaust is the primary source of nonmethane hydrocarbons in the Chengdu urban area
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Air pollution poses a serious threat to human health. The implementation of air pollution prevention and control policies has gradually reduced the level of atmospheric fine particles in Beijing. ...Exploring the latest characteristics of PM
2.5
has become the key to further improving pollution reduction measures. In the current study, outdoor PM
2.5
samples were collected in the spring and summer of Beijing, and the chemical species, oxidative potential (OP), and sources of PM
2.5
were characterized. The mean PM
2.5
concentration during the entire study period was 41.6 ± 30.9 μg m
−3
. Although the PM
2.5
level in summer was lower, its OP level was significantly higher than that in spring. SO
4
2–
, NH
4
+
, EC, NO
3–
, and OC correlated well with volume-normalized OP (OP
v
). Strong positive correlations were found between OP
v
and the following elements: Cu, Pb, Zn, Ni, As, Cr, Sn, Cd, Al, and Mn. Seven sources of PM
2.5
were identified, including traffic, soil dust, secondary sulfate, coal and biomass burning, oil combustion, secondary nitrate, and industry. Multiple regression analysis indicated that coal and biomass combustion, industry, and traffic were the main contributors to the OP
v
in spring, while secondary sulfate, oil combustion, and industry played a leading role in summer. The source region analysis revealed that different pollution sources were related to specific geographic distributions. In addition to local emission reduction policies, multi-provincial cooperation is necessary to further improve Beijing's air quality and reduce the adverse health effects of PM
2.5
.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
In this paper, a cluster analysis of backward air mass trajectories, arriving in Avignon (Southern France), was combined with a Potential Source Contribution Function (PSCF) model on a 0.5°×0.5° ...resolution grid, in order to indicate possible aerosol intrusions. A strict triple criterion was constructed from Aerosol Optical Thickness (AOT), Angstrom Exponent (AE), and PM (PM10 and PM2.5) concentration measurements, aiming to distinguish more effectively Episodes of Fine, Coarse and Overall Aerosols (FAE, CAE and OAE respectively). Large fractions of FAE (60.0%) and CAE (40.6%) were strongly attributed to the prevalence of Eastern and South–Southwest (S–SW) airflows respectively, whereas these distinct trajectory clusters also gathered large fractions of OAE (90.2% cumulatively). According to PSCF results, FAE events were strongly associated with the influence of air masses traveling over North Italy and Southern Germany, hence the impact of urban and industrial combustion was emerged. Main sources of coarse aerosols were principally isolated over the Mediterranean, thus the import of sea spray and dust from the Sahara desert is presumed. Satellite AOT observations were used for a more detailed identification of an intense 5-day intrusion of coarse aerosols. Short range slow moving air mass trajectories, were proven to be a clear marker of atmospheric stagnation, based on a wind speed analysis, triggering the accumulation of locally emitted anthropogenic aerosols (mainly PM2.5) and lack of city ventilation.
•Eastern atmospheric circulation transfers fine particles in Avignon (France).•The conveyance of coarse aerosols was attributed to S–SW airflows.•Saharan dust and Mediterranean sea salt intrusions provoked coarse aerosol episodes.•Local combustion emissions of fine particles in Avignon were indicated.•Short range trajectories are a clear marker of recirculation of polluted air.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The concentration of black carbon was measured in four sites of the industrial and high-traffic metropolis of Tehran with different land uses. Then, the contribution of biomass and fossil fuels in ...the emission of this pollutant was modeled using the Aethalometer model. The possible locations of important sources of black carbon dissemination were projected using PSCF and CWT models, and the results were compared in the two periods before and after the Covid-19 outbreak. Temporal variations of black carbon illustrated that BC concentration decreased in the period after the onset of the pandemic in all studied areas, and this decline was more explicit in the traffic intersection of the city. Diurnal changes of BC concentration indicated the significant impact of the application of the law banning night traffic of motor vehicles in reducing the BC concentration in this period, and probably the reduction of HDDV traffic has played the most important role in this reduction. The results related to the share of BC sources indicated that black carbon emissions are affected by an average of about 80% of fossil fuel combustion and wood combustion interferes with about 20% of BC emissions. Finally, speculations were made about the possible sources of BC emission and its urban scale transport using PSCF and CWT models, which indicated the superiority of the CWT model in terms of source segregation. The results of this analysis were further utilized to surmise black carbon emission sources based on the land use of receptor points.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Air pollution has attracted increasing attention in recent years. Cluster analysis, scene analysis, and the potential source contribution function (PSCF), based on the backward trajectory model, were ...used to identify the transport pathways and potential source regions of PM2.5 and PM10 (particulate matter with an aerodynamic diameter of not more than 2.5 µm and 10 µm) in Changchun in 2018. In addition, the PSCF was slightly improved. The highest average monthly concentrations of PM2.5 and PM10 appeared in March and April, when they reached 53.9μg/m3 and 120.0 μg/m3, respectively. The main potential source regions of PM2.5 and PM10 were generally similar: western Jilin Province, northwestern Inner Mongolia, northeastern Liaoning Province, and the Yellow Sea region. The secondary potential source regions were southern Russia, central Mongolia, western Shandong Province, eastern Hebei Province, and eastern Jiangsu Province. The northwest and southwest directions were found to be the two pathways that mainly affect the air quality of Changchun City. Moreover, the northwestern pathway had a larger potential contribution source area than the southwestern pathway. The airflow in the southwest direction came from Liaoning Province, Shandong Province, and the Yellow Sea region. This mainly occurred in summer; its transmission distance was short; it had a relatively higher weight potential source contribution function (WPSCF) value; it can be regarded as a local source; and its representative pollutants were SO2 (sulfur dioxide), CO (carbon monoxide), and O3 (ozone). The northwestern pathway passed through Russia, Mongolia, and Inner Mongolia. The transmission distance of this pathway was longer; it had a relatively lower WPSCF value; it can be considered as a natural source to a certain extent; it mainly occurred in autumn and, especially, in winter; and the representative pollutants of this pathway were NO (nitric oxide), NOx (nitrogen oxide), PM2.5, and PM10.
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