This study studied the characteristics and source apportionment of heavy metal pollution in the agricultural soil surrounding a gangue coal heap in Chongqing,China by using absolute principal component scores-multiple...This study studied the characteristics and source apportionment of heavy metal pollution in the agricultural soil surrounding a gangue coal heap in Chongqing,China by using absolute principal component scores-multiple linear regression(APCSMLR)model and positive matrix factorization(PMF)model.The applicability of the models was compared in the assessment of source apportionment.The results showed that the average contents of Cd,Hg,As,Pb,Cr,Cu,Ni,and Zn in the surface soil were 0.46,0.14,9.66,31.2,127,95.6,76.0,and 158 mg/kg,respectively.Combined with the spatial distribution and correlation analyses,the results of source apportionment were consistent for both the APCSMLR and PMF models.Cd,Hg,As,and Pb were mainly affected by the gangue heap accumulation,with respective contributions of 74.6%,79.4%,69.1%,and 67.2%based on the APCS-MLR model and respective contributions of 69.7%,60.7%,57.4%,and 41.9%based on the PMF model.Ni and Zn were mainly affected by industrial and agricultural activities,while Cr and Cu were mainly affected by natural factors.The results of the source apportionment were approximately consistent between the APCS-MLR and PMF models.The combined application of the two receptor models can make the results of source apportionment more comprehensive,accurate,and reliable.展开更多
The deterioration of the surface water environment has become a serious challenge for water resources management due to increasing anthropogenic disturbance. Water resources protection requires control of potential po...The deterioration of the surface water environment has become a serious challenge for water resources management due to increasing anthropogenic disturbance. Water resources protection requires control of potential pollution sources. In this study, 99 water samples were collected from a river in a typical agricultural city of Anhui Province in eastern China, and these samples were analyzed in terms of pH, electrical conductivity, and the concentrations of F-, Cl-, SO42-, Na+, K+, Mg2+, Ca2+, As, Cr, Cu, Zn, and Pb. Cluster analysis, co-occurrence network analysis, and principal component analysis/factor analysis were conducted to qualitatively identify the potential sources of river water pollution in the study area. An absolute principal component score-multiple linear regression receptor model was used to quantitatively evaluate the contribution of each source to water quality parameters. The results showed that all observed water quality indices met the quality criteria specified in the Chinese drinking water standards, except for pH, ρ(F-), ρ(SO42-), and ρ(As). The heat map showed that the frequent recharge of pollutants from the tributaries during the wet season was the main reason for the deterioration of water quality. Five sources of river water pollution were identified, and their contribution ratios in a descending order were as follows: the geogenic process (24%) > agricultural activities (21%) > poultry farming sources (17%) > domestic pollution (9%) > transportation pollution (5%). Therefore, controlling pollution from agricultural activities, strengthening the regulation of livestock farming, and improving the sewage network are the recommended strategies for improving the quality of surface water resources in this area.展开更多
Summer and winter campaigns for the chemical compositions and sources of nonmethane hydrocarbons(NMHCs)and oxygenated volatile organic compounds(OVOCs)were conducted in Xi’an.Data from 57 photochemical assessment mon...Summer and winter campaigns for the chemical compositions and sources of nonmethane hydrocarbons(NMHCs)and oxygenated volatile organic compounds(OVOCs)were conducted in Xi’an.Data from 57 photochemical assessment monitoring stations for NMHCs and 20 OVOC species were analyzed.Significant seasonal differences were noted for total VOC(TVOC,NMHCs and OVOCs)concentrations and compositions.The campaign-average TVOC concentrations in winter(85.3±60.6 ppbv)were almost twice those in summer(47.2±31.6 ppbv).Alkanes and OVOCs were the most abundant category in winter and summer,respectively.NMHCs,but not OVOCs,had significantly higher levels on weekends than on weekdays.Total ozone formation potential was higher in summer than in winter(by 50%)because of the high concentrations of alkenes(particularly isoprene),high temperature,and high solar radiation levels in summer.The Hybrid Environmental Receptor Model(HERM)was used to conduct source apportionment for atmospheric TVOCs in winter and summer,with excellent accuracy.HERM demonstrated its suitability in a situation where only partial source profile data were available.The HERM results indicated significantly different seasonal source contributions to TVOCs in Xi’an.In particular,coal and biomass burning had contributions greater than half in winter(53.4%),whereas traffic sources were prevalent in summer(53.1%).This study’s results highlight the need for targeted and adjustable VOC control measures that account for seasonal differences in Xi’an;such measures should target not only the severe problem with VOC pollution but also the problem of consequent secondary pollution(e.g.,from ozone and secondary organic aerosols).展开更多
Long-lasting expansion of haze pollution in China has already presented a stern challenge to regional joint prevention and control. There is an urgent need to enlarge and reconstruct the coverage of joint prevention a...Long-lasting expansion of haze pollution in China has already presented a stern challenge to regional joint prevention and control. There is an urgent need to enlarge and reconstruct the coverage of joint prevention and control of air pollution in key area. Air quality models can identify and quantify the regional contribution of haze pollution and its key components with the help of numerical simulation, but it is difficult to be applied to larger spatial scale due to the complexity of model parameters. The time series analysis can recognize the existence of spatial interaction of haze pollution between cities, but it has not yet been used to further identify the spatial sources of haze pollution in large scale. Using econometric framework of time series analysis, this paper developed a new approach to perform spatial source apportionment. We applied this approach to calculate the contribution from spatial sources of haze pollution in China, using the monitoring data of particulate matter(PM_(2.5)) across 161 Chinese cities. This approach overcame the limitation of numerical simulation that the model complexity increases at excess with the expansion of sample range, and could effectively deal with severe large-scale haze episodes.展开更多
The formation of heavy metal pollution in soil is closely related to human production and life. In order to effectively control heavy metal pollution and repair damaged soil,the pollution source should be known and ju...The formation of heavy metal pollution in soil is closely related to human production and life. In order to effectively control heavy metal pollution and repair damaged soil,the pollution source should be known and judged first. Based on the preliminary analysis of major sources of soil heavy metal pollution in soil,combined with relevant literatures on heavy metal pollution source of soil or sediment at home and abroad in recent years,application progress of isotope tracer technique,especially lead isotope tracer technique,in the study of heavy metal pollution sources in soils and sediments were reviewed. The key points of future isotope tracer technology in the field of heavy metal pollution source apportionment were prospected.展开更多
Fireworks(FW)could significantly worsen air quality in short term during celebrations.Due to similar tracers with biomass burning(BB),the fast and precise qualification of FW and BB is still challenging.In this study,...Fireworks(FW)could significantly worsen air quality in short term during celebrations.Due to similar tracers with biomass burning(BB),the fast and precise qualification of FW and BB is still challenging.In this study,online bulk and single-particle measurements were combined to investigate the contributions of FW and BB to the overall mass concentrations of PM_(2.5)and specific chemical species by positive matrix factorization(PMF)during the Chinese New Year in Hong Kong in February 2013.With combined information,fresh/aged FW(abundant ^(140)K_(2)NO_(3)^(+)and ^(213)K_(3)SO_(4)^(+)formed from ^(113)K_(2)Cl^(+)discharged by fresh FW)can be extracted from the fresh/aged BB sources,in addition to the Second Aerosol,Vehicles+Road Dust,and Sea Salt factors.The contributions of FW and BB were investigated during three high particle matter episodes influenced by the pollution transported from the Pearl River Delta region.The fresh BB/FW contributed 39.2%and 19.6%to PM_(2.5)during the Lunar Chinese New Year case.However,the contributions of aged FW/BB enhanced in the last two episodes due to the aging process,evidenced by high contributions from secondary aerosols.Generally,the fresh BB/FW showed more significant contributions to nitrate(35.1%and15.0%,respectively)compared with sulfate(25.1%and 5.9%,respectively)and OC(14.8%and11.1%,respectively)on average.In comparison,the aged FW contributed more to sulfate(13.4%).Overall,combining online bulk and single-particle measurement data can combine both instruments’advantages and provide a new perspective for applying source apportionment of aerosols using PMF.展开更多
Industrial coking facilities are an important emission source for volatile organic compounds(VOCs).This study analyzed the atmospheric VOC characteristics within an industrial coking facility and its surrounding envir...Industrial coking facilities are an important emission source for volatile organic compounds(VOCs).This study analyzed the atmospheric VOC characteristics within an industrial coking facility and its surrounding environment.Average concentrations of total VOCs(TVOCs)in the surrounding residential activity areas(R1 and R2),the coking facility(CF)and the control area(CA)were determined to be 138.5,47.8,550.0,and 15.0μg/m^(3),respectively.The cold drum process and coking and quenching areas within the coking facility were identified as the main polluting processes.The spatial variation in VOCs composition was analyzed,showing that VOCs in the coking facility and surrounding areas were mainly dominated by aromatic compounds such as BTX(benzene,toluene,and xylenes)and naphthalene,with concentrations being negatively correlated with the distance from the coking facility(p<0.01).The sources of VOCs in different functional areas across the monitoring area were analyzed,finding that coking emissions accounted for 73.5%,33.3% and 27.7% of TVOCs in CF,R1 and R2,respectively.These results demonstrated that coking emissions had a significant impact on VOC concentrations in the areas surrounding coking facility.This study evaluates the spatial variation in exposure to VOCs,providing important information for the influence of VOCs concentration posed by coking facility to surrounding residents and the development of strategies for VOC abatement.展开更多
Metal smelting have brought severe metal(loid)s contamination to the soil.Spatial distribution and pollution source analysis for soil metal(loid)s in an abandoned lead/zinc smelter were studied.The results showed that...Metal smelting have brought severe metal(loid)s contamination to the soil.Spatial distribution and pollution source analysis for soil metal(loid)s in an abandoned lead/zinc smelter were studied.The results showed that soil was contaminated heavily withmetal(loid)s.The mean of lead(Pb),arsenic(As),cadmium(Cd),mercury(Hg)and antimony(Sb)content in topsoil is 9.7,8.2,5.0,2.3,and 1.2 times higher than the risk screening value for soil contamination of development land of China(GB36600-2018),respectively.Cd ismainly enriched in the 0–6mdepth of site soil while As and Pbmainly deposited in the 0–4mlayer.The spatial distribution of soil metal(loid)s is significantly correlated with the pollution source in the different functional areas of smelter.As,Hg,Sb,Pb and copper(Cu)were mainly distributed in pyrometallurgical area,while Cd,thallium(Tl)and zinc(Zn)was mainly existed in both hydrometallurgical area and raw material storage area.Soil metal(loid)s pollution sources in the abandoned smelter are mainly contributed to the anthropogenic sources,accounting for 84.5%.Specifically,Pb,Tl,As,Hg,Sb and Cumainly from atmospheric deposition(55.9%),Cd and Zn mainly from surface runoff(28.6%),While nickel(Ni)mainly comes from parent material(15.5%).The results clarified the spatial distribution and their sources in different functional areas of the smelter,providing a new thought for the risk prevention and control of metal(loid)s in polluted site soil.展开更多
Based on the online and membrane sampling data of Yuncheng from January 1st to February 12th,2020,the formation mechanism of haze under the dual influence of Spring Festival and COVID-19 (Corona Virus Disease) was ana...Based on the online and membrane sampling data of Yuncheng from January 1st to February 12th,2020,the formation mechanism of haze under the dual influence of Spring Festival and COVID-19 (Corona Virus Disease) was analyzed.Atmospheric capacity,chemical composition,secondary transformation,source apportionment,backward trajectory,pollution space and enterprise distribution were studied.Low wind speed,high humidity and small atmospheric capacity inhibited the diffusion of air pollutants.Four severe pollution processes occurred during the period,and the pollution degree was the highest around the Spring Festival.In light,medium and heavy pollution periods,the proportion of SNA (SO_(4)^(2-),NO_(3)-and NH_(4)^(+)) was 59.6%,56.0%and 54.9%,respectively,which was the largest components of PM_(2.5);the[NO_(3)-]/[SO_(4)^(2-)]ratio was 2.1,1.5 and 1.7,respectively,indicating that coal source had a great influence;the changes of NOR (nitrogen oxidation ratio,0.44,0.45,0.61)and SOR (sulphur oxidation ratio,0.40,0.49,0.65) indicated the accumulation of secondary aerosols with increasing pollution.The coal combustion,motor vehicle,secondary inorganic sources and industrial sources contributed 36.8%,26.59%,11.84%and 8.02%to PM_(2.5)masses,respectively.Backward trajectory showed that the influence from the east was greater during the Spring Festival,and the pollutants from the eastern air mass were higher,which would aggravate the pollution.Meteorological and Spring Festival had a great impact on heavy pollution weather.Although some work could not operate due to the impact of the COVID-19 epidemic,the emission of pollutants did not reduce much.展开更多
Volatile organic compounds(VOCs)are important precursors of secondary organic compounds and ozone,which raise major environmental concerns.To investigate the VOC emission characteristics,measurements of VOCs based on ...Volatile organic compounds(VOCs)are important precursors of secondary organic compounds and ozone,which raise major environmental concerns.To investigate the VOC emission characteristics,measurements of VOCs based on proton transfer reaction-mass spectrometry during 2017 were conducted in a coastal industrial area in Ningbo,Zhejiang Province,China.Based on seasonal variation in species concentration,the positive matrix factorization(PMF)receptor model was applied to apportion the sources of VOCs in each season.The PMF results revealed that unknown acetonitrile source,paint solvent,electronics industry,biomass burning,secondary formation and biogenic emission were mainly attributed to VOC pollution.Biomass burning and secondary formation were the major sources of VOCs and contributed more than 70%of VOC emissions in spring and autumn.Industry-related sources contributed 8.65%–31.2%of the VOCs throughout the year.The unknown acetonitrile source occurred in winter and spring,and contributed 7.6%–43.73%of the VOC emissions in the two seasons.Conditional probability function(CPF)analysis illustrated that the industry sources came from local emission,while biomass burning and biogenic emission mainly came from the northwest direction.The potential source contribution function(PSCF)model showed that secondary formation-related source was mainly from Jiangsu Province,northeastern China and the surrounding ocean.The potential source areas of unknown acetonitrile source were northern Zhejiang Province,southern Jiangsu Province and the northeastern coastal marine environments.展开更多
Monocyclic aromatic hydrocarbons(MAHs)and polycyclic aromatic hydrocarbons(PAHs)are both well known as hazardous air pollutants and also important anthropogenic precursors of tropospheric ozone(O3)and secondary organi...Monocyclic aromatic hydrocarbons(MAHs)and polycyclic aromatic hydrocarbons(PAHs)are both well known as hazardous air pollutants and also important anthropogenic precursors of tropospheric ozone(O3)and secondary organic aerosols(SOA).In recent years,there have been intensive studies covering MAHs emission from various sources and their behavior under stimulated photochemical conditions.Yet in-situ measurements of PAHs presence and variations in ambient air are sparse.Herein we conducted large geometrical scale mobile measurements for 16 aromatic hydrocarbons(AHs,including 7 MAHs and 9 PAHs)in eastern China between October 27 and November 8,2019.This unique dataset has allowed for some insights in terms of AHs concentration variations,accompanying chemical composition,source contributions and spatial distributions in eastern China.In general,AHs showed a clear concentration variability between the south and the north of the Yangtze River Delta(YRD).The concentrations of PAHs were approximately 9%of AHs,but contributed 23%of SOA formation potential.Source apportionment via positive matrix factorization(PMF)model revealed that industrial processes as the largest source(44%)of observed AHs,followed by solvent usage(21%),vehicle exhaust(19%),coal combustion(11%)and coking processes(6%).In the perspective of PAHs sources,coal combustion emissions were identified as the dominating factor of a share of 41%–52%in eastern China.Our findings complemented the simultaneously monitoring information of PAHs and MAHs in eastern China,revealed the importance of PAHs to SOA formation and highlighted the necessity of formulating strategies to reduce emissions from anthropogenic sources and reduce risks to human health.展开更多
The source apportionment of PM2.5 is essential for pollution prevention.In view of the weaknesses of individual models,we proposed an integrated chemical mass balancesource emission inventory(CMB-SEI)model to acquire ...The source apportionment of PM2.5 is essential for pollution prevention.In view of the weaknesses of individual models,we proposed an integrated chemical mass balancesource emission inventory(CMB-SEI)model to acquire more accurate results.First,the SEI of secondary component precursors(SO2,NOx,NH3,and VOCs)was compiled to acquire the emission ratios of these sources for the precursors.Then,a regular CMB simulation was executed to obtain the contributions of primary particle sources and secondary components(SO4^2-,NO3^-3,NH4^+,and SOC).Afterwards,the contributions of secondary components were apportioned into primary sources according to the source emission ratios.The final source apportionment results combined the contributions of primary sources by CMB and SEI.This integrated approach was carried out via a case study of three coastal cities(Zhoushan,Taizhou,and Wenzhou;abbreviated WZ,TZ,and ZS)in Zhejiang Province,China.The regular CMB simulation results showed that PM2.5 pollution was mainly affected by secondary components and mobile sources.The SEI results indicated that electricity,industrial production and mobile sources were the largest contributors to the emission of PM2.5 gaseous precursors.The simulation results of the CMB-SEI model showed that PM2.5 pollution in the coastal areas of Zhejiang Province presented complex pollution characteristics dominated by mobile sources,electricity production sources and industrial production sources.Compared to the results of the CMB and SEI models alone,the CMB-SEI model completely apportioned PM2.5 to primary sources and simultaneously made the results more accurate and reliable in accordance with local industrial characteristics.展开更多
Characteristics of atmospheric VOCs(volatile organic compounds) have been extensively studied in megacities in China, however, they are scarcely investigated in medium/smallsized cities in North China Plain(NCP).A com...Characteristics of atmospheric VOCs(volatile organic compounds) have been extensively studied in megacities in China, however, they are scarcely investigated in medium/smallsized cities in North China Plain(NCP).A comprehensive research on possible sources of VOCs was conducted in a medium-sized city of NCP, from May to September 2019.A total of 143 canister samples of 8 sites in Xuchang city were collected, and 57 VOC species were detected.The average VOC concentrations were 42.6 ± 31.6 μg/m3, with 53.7 ± 31.0 μg/m3 and 32.1 ± 27.8 μg/m^(3), in the morning and afternoon, respectively.Alkenes and aromatics contributed 80% of the total ozone formation potential(OFP).Aromatics accounted for more than 95% of secondary organic aerosol potential(SOAP).VOCs were dominated by the local emission with significant transport from the southeast direction.PMF analysis extracted 6 sources, which were combustion(33.1%), LPG usage(19.3%), vehicular exhaust & fuel evaporation(15.8%), solvent usage(15.2%), industrial(9.11%) and biogenic(7.51%), respectively and they contributed 33.4%, 17.6%, 12.9%, 18.6%, 9.28% and 8.22% to the OFP, respectively.Combustion and LPG usage were the dominant VOC sources;and combustion, solvent usage and LPG usage were the main sources of OFP in Xuchang city, which were different to megacities in China with a high contribution from vehicular exhaust, solvent usage and industry,suggesting specific control strategies on VOCs need to be implemented in medium-sized city such as Xuchang city.展开更多
Atmospheric extinction is impacted by the chemical composition of particles.To better understand the chemical composition of PM_(2.5)(particles with diameters of less than 2.5μm)and its relationship with extinction,o...Atmospheric extinction is impacted by the chemical composition of particles.To better understand the chemical composition of PM_(2.5)(particles with diameters of less than 2.5μm)and its relationship with extinction,one-month sampling campaigns were carried out in four different seasons from 2013 to 2014 in Jinan,China.The seasonal average concentrations of PM_(2.5)were 120.9(autumn),156.6(winter),102.5(spring),and 111.8μg/m^(3)(summer).The reconstructed PM_(2.5)chemical composition showed that sulfate,nitrate,chlorine salt,organic matter(OM),mineral dust,elemental carbon(EC)and others accounted for 25%,14%,2%,24%,22%,3%and 10%,respectively.The relationship between the chemical composition of PM_(2.5)and visibility was reconstructed by the IMPROVE method,and ammonium sulfate,ammonium nitrate,OM and EC dominated the visibility.Seven main sources were resolved for PM_(2.5),including secondary particles,coal combustion,biomass burning,industry,motor vehicle exhaust,soil dust and cooking,which accounted for 37%,21%,13%,13%,12%,3%and 1%,respectively.The contributions of different sources to visibility were similar to those to PM_(2.5).With increasing severity of air pollution,the contributions of secondary particles and coal combustion increased,while the contribution of motor vehicle exhaust decreased.The results showed that coal combustion and biomass burning were still the main sources of air pollution in Jinan.展开更多
We present the continuously measurements of volatile organic compounds(VOCs)at a receptor site(Wan Qing Sha,WQS)in the Pearl River Delta(PRD)region from September to November of 2017.The average mixing ratios of total...We present the continuously measurements of volatile organic compounds(VOCs)at a receptor site(Wan Qing Sha,WQS)in the Pearl River Delta(PRD)region from September to November of 2017.The average mixing ratios of total VOCs(TVOCs)was 36.3±27.9 ppbv with the dominant contribution from alkanes(55.5%),followed by aromatics(33.3%).The diurnal variation of TVOCs showed a strong photochemical consumption during daytime,resulting in the formation of ozone(O_(3)).Five VOC sources were resolved by the positive matrix factorization(PMF)model,including solvent usage(28.6%),liquid petroleum gas(LPG)usage(24.4%),vehicle exhaust(21.0%),industrial emissions(13.2%)and gasoline evaporation(12.9%).The regional transport air masses from the upwind cities of south China can result in the elevated concentrations of TVOCs.Low ratios of TVOCs/NO_(x)(1.53±0.88)suggested that the O_(3) formation regime at WQS site was VOC-limited,which also confirmed by a photochemical box model with the master chemical mechanism(PBM-MCM).Furthermore,the observation on high-O_(3) episode days revealed that frequent O_(3) outbreaks at WQS were mainly caused by the regional transport of anthropogenic VOCs especially for aromatics and the subsequent photochemical reactions.This study provides valuable information for policymakers to propose the effective control strategies on photochemical pollution in a regional perspective.展开更多
A total of 168 PM_(10)samples were collected during the year of 2005 at eight sites in the city of Wuxi in China.Fifteen chemical elements,three water-soluble ions,total carbon and organic carbon were analyzed.Six sou...A total of 168 PM_(10)samples were collected during the year of 2005 at eight sites in the city of Wuxi in China.Fifteen chemical elements,three water-soluble ions,total carbon and organic carbon were analyzed.Six source categories were identified and their contributions to ambient PM_(10)in Wuxi were estimated using a nested chemical mass balance method that reduces the effects of colinearity on the chemical mass balance model.In addition,the concentrations of secondary aerosols,such as secondary organic carbon,sulfate and nitrate,were quantified.The spatially averaged PM_(10)was high in the spring and winter(123μg·m^(-3)and low in the summer-fall(90μg·m^(-3)).According to the result of source apportionment,resuspended dust was the largest contributor to ambient PM_(10),accounting for more than 50%of the PM_(10)mass.Coal combustion(14.6%)and vehicle exhaust(9.4%)were also significant source categories of ambient PM_(10).Construction and cement dust,sulfates,secondary organic carbon,and nitrates made contributions ranging between 4.1%and 4.9%.Other source categories such as steel manufacturing dust and soil dust made low contributions to ambient PM_(10).展开更多
The submicron particulate matter(PM_(1))and fine particulate matter(PM_(2.5))are very important due to their greater adverse impacts on the natural environment and human health.In this study,the daily PM_(1) and PM_(2...The submicron particulate matter(PM_(1))and fine particulate matter(PM_(2.5))are very important due to their greater adverse impacts on the natural environment and human health.In this study,the daily PM_(1) and PM_(2.5) samples were collected during early summer 2018 at a sub-urban site in the urban-industrial port city of Tianjin,China.The collected samples were analyzed for the carbonaceous fractions,inorganic ions,elemental species,and specific marker sugar species.The chemical characterization of PM_(1) and PM_(2.5) was based on their concentrations,compositions,and characteristic ratios(PM_(1)/PM_(2.5),AE/CE,NO3^-/SO4^2-,OC/EC,SOC/OC,OM/TCA,K^+/EC,levoglucosan/K^+,V/Cu,and V/Ni).The average concentrations of PM_(1) and PM_(2.5) were 32.4μg/m and 53.3μg/m^3,and PM_(1) constituted 63%of PM_(2.5) on average.The source apportionment of PM_(1) and PM_(2.5) by positive matrix factorization(PMF)model indicated the main sources of secondary aerosols(25%and 34%),biomass burning(17%and 20%),traffic emission(20%and 14%),and coal combustion(17%and 14%).The biomass burning factor involved agricultural fertilization and waste incineration.The biomass burning and primary biogenic contributions were determined by specific marker sugar species.The anthropogenic sources(combustion,secondary particle formation,etc)contributed significantly to PM_(1) and PM_(2.5),and the natural sources were more evident in PM_(2.5).This work significantly contributes to the chemical characterization and source apportionment of PM_(1) and PM_(2.5) in near-port cities influenced by the diverse sources.展开更多
Agricultural sources and non-agricultural emissions contribute to gaseous ammonia(NH_(3))that plays a vital role in severe haze formation.Qualitative and quantitative contributions of these sources to ambient PM_(2.5)...Agricultural sources and non-agricultural emissions contribute to gaseous ammonia(NH_(3))that plays a vital role in severe haze formation.Qualitative and quantitative contributions of these sources to ambient PM_(2.5)(particulate matter with an aerodynamic equivalent diameter below 2.5µm)concentrations remains uncertain.Stable nitrogen isotopic composition(δ^(15)N)of NH_(3)and NH_(4)+(δ^(15)N(NH_(3))andδ^(15)N(NH_(4)+),respectively)can yield valuable information about its sources and associated processes.This review provides an overview of the recent progress in analytical techniques forδ^(15)N(NH_(3))andδ^(15)N(NH_(4)+)measurement,sampling of atmospheric NH_(3)and NH_(4)+in the ambient air and their sources signature(e.g.,agricultural vs.fossil fuel),and isotope-based source apportionment of NH_(3)in urban atmosphere.This study highlights that collecting sample that are fully representative of emission sources remains a challenge in fingerprintingδ^(15)N(NH_(3))values of NH_(3)emission sources.Furthermore,isotopic fractionation during NH_(3)gas-to-particle conversion under varying ambient field conditions(e.g.,relative humidity,particle pH,temperature)remains unclear,which indicates more field and laboratory studies to validate theoretically predicted isotopic fractionation are required.Thus,this study concludes that lack of refinedδ^(15)N(NH_(3))fingerprints and full understanding of isotopic fractionation during aerosol formation in a laboratory and field conditions is a limitation for isotope-based source apportionment of NH_(3).More experimental work(in chamber studies)and theoretical estimations in combinations of field verification are necessary in characterizing isotopic fractionation under various environmental and atmospheric neutralization conditions,which would help to better interpret isotopic data and our understanding on NH_(x)(NH_(3)+NH_(4)+)dynamics in the atmosphere.展开更多
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 ana...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 ΣPAHs(sum of all 16 measured PAHs) concentrations ranged from 51.89 to 132.82 ng/g with an average of 80.39 ng/g. TheΣ 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 ΣPAHs 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.展开更多
Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain.In this study,an industrial district(Shahe City)with a large glass manufactur-ing sector was investigated t...Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain.In this study,an industrial district(Shahe City)with a large glass manufactur-ing sector was investigated to clarify the relative contribution of fine particulate matter(PM_(2.5))to the city's high levels of pollution.The Nest Air Quality Prediction Model System(NAQPMS),paired with Weather Research and Forecasting(WRF),was adopted and applied with a spatial resolution of 5 km.During the study period,the mean mass concentrations of PM_(2.5),SO_(2),and NO_(2)were observed to be 132.0,76.1,and 55.5μg/m^(3),respectively.The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level.The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4%of the city's total PM_(2.5)concentration.This contribu-tion increased to 73.9±21.2%when unfavorable meteorological conditions(high relative hu-midity,weak wind,and low planetary boundary layer height)were present;such conditions are more frequently associated with severe pollution(PM_(2.5)≥250μg/m^(3)).The contribution from Shahe was 52.3±21.6%.The source apportionment results showed that industry(47%),transportation(10%),power(17%),and residential(26%)sectors were the most important sources of PM_(2.5)in Shahe.The glass factories(where chimney stack heights were normally<70 m)in Shahe contributed 32.1%of the total PM_(2.5)concentration in Shahe.With an in-crease in PM_(2.5)concentration,the emissions from glass factories accumulated vertically and narrowed horizontally.At times when pollution levels were severe,the horizontally influ-enced area mainly covered Shahe.Furthermore,sensitivity tests indicated that reducing emissions by 20%,40%,and 60% could lead to a decrease in themass concentration of PM_(2.5) of of 12.0%,23.8%,and 35.5%,respectively.展开更多
基金supported by Project of Chongqing Ecology and Environment Bureau(2021111)Project of Chongqing Science and Technology Bureau(cstc2022jxjl0005)。
文摘This study studied the characteristics and source apportionment of heavy metal pollution in the agricultural soil surrounding a gangue coal heap in Chongqing,China by using absolute principal component scores-multiple linear regression(APCSMLR)model and positive matrix factorization(PMF)model.The applicability of the models was compared in the assessment of source apportionment.The results showed that the average contents of Cd,Hg,As,Pb,Cr,Cu,Ni,and Zn in the surface soil were 0.46,0.14,9.66,31.2,127,95.6,76.0,and 158 mg/kg,respectively.Combined with the spatial distribution and correlation analyses,the results of source apportionment were consistent for both the APCSMLR and PMF models.Cd,Hg,As,and Pb were mainly affected by the gangue heap accumulation,with respective contributions of 74.6%,79.4%,69.1%,and 67.2%based on the APCS-MLR model and respective contributions of 69.7%,60.7%,57.4%,and 41.9%based on the PMF model.Ni and Zn were mainly affected by industrial and agricultural activities,while Cr and Cu were mainly affected by natural factors.The results of the source apportionment were approximately consistent between the APCS-MLR and PMF models.The combined application of the two receptor models can make the results of source apportionment more comprehensive,accurate,and reliable.
基金supported by the 2021 Graduate Science Research Project of the Anhui Higher Education Institutions(Grant No.YJS20210375)the Natural Science Research Project of Universities in Anhui Province(Grant No.KJ2020ZD64)+2 种基金the Natural Science Foundation of Anhui Province(Grant No.2008085MD122)the Outstanding Young Talents in Higher Education Institutions of Anhui Province(Grant No.ZD2021134)the Research Development Foundation of Suzhou University(Grant No.2021fzjj28).
文摘The deterioration of the surface water environment has become a serious challenge for water resources management due to increasing anthropogenic disturbance. Water resources protection requires control of potential pollution sources. In this study, 99 water samples were collected from a river in a typical agricultural city of Anhui Province in eastern China, and these samples were analyzed in terms of pH, electrical conductivity, and the concentrations of F-, Cl-, SO42-, Na+, K+, Mg2+, Ca2+, As, Cr, Cu, Zn, and Pb. Cluster analysis, co-occurrence network analysis, and principal component analysis/factor analysis were conducted to qualitatively identify the potential sources of river water pollution in the study area. An absolute principal component score-multiple linear regression receptor model was used to quantitatively evaluate the contribution of each source to water quality parameters. The results showed that all observed water quality indices met the quality criteria specified in the Chinese drinking water standards, except for pH, ρ(F-), ρ(SO42-), and ρ(As). The heat map showed that the frequent recharge of pollutants from the tributaries during the wet season was the main reason for the deterioration of water quality. Five sources of river water pollution were identified, and their contribution ratios in a descending order were as follows: the geogenic process (24%) > agricultural activities (21%) > poultry farming sources (17%) > domestic pollution (9%) > transportation pollution (5%). Therefore, controlling pollution from agricultural activities, strengthening the regulation of livestock farming, and improving the sewage network are the recommended strategies for improving the quality of surface water resources in this area.
基金This research was supported by the Natural Science Foundation of China(Grant No.41907188)Natural Science Foundation of Shaanxi Province,China(Grant No.2019JQ-386)the China Postdoctoral Science Foundation(Grant No.2019M653658).
文摘Summer and winter campaigns for the chemical compositions and sources of nonmethane hydrocarbons(NMHCs)and oxygenated volatile organic compounds(OVOCs)were conducted in Xi’an.Data from 57 photochemical assessment monitoring stations for NMHCs and 20 OVOC species were analyzed.Significant seasonal differences were noted for total VOC(TVOC,NMHCs and OVOCs)concentrations and compositions.The campaign-average TVOC concentrations in winter(85.3±60.6 ppbv)were almost twice those in summer(47.2±31.6 ppbv).Alkanes and OVOCs were the most abundant category in winter and summer,respectively.NMHCs,but not OVOCs,had significantly higher levels on weekends than on weekdays.Total ozone formation potential was higher in summer than in winter(by 50%)because of the high concentrations of alkenes(particularly isoprene),high temperature,and high solar radiation levels in summer.The Hybrid Environmental Receptor Model(HERM)was used to conduct source apportionment for atmospheric TVOCs in winter and summer,with excellent accuracy.HERM demonstrated its suitability in a situation where only partial source profile data were available.The HERM results indicated significantly different seasonal source contributions to TVOCs in Xi’an.In particular,coal and biomass burning had contributions greater than half in winter(53.4%),whereas traffic sources were prevalent in summer(53.1%).This study’s results highlight the need for targeted and adjustable VOC control measures that account for seasonal differences in Xi’an;such measures should target not only the severe problem with VOC pollution but also the problem of consequent secondary pollution(e.g.,from ozone and secondary organic aerosols).
基金supposed by Shandong Natural Science Foundation[Grant number:ZR2016GM03]Ministry of Education[Grant number:17YJA790054]
文摘Long-lasting expansion of haze pollution in China has already presented a stern challenge to regional joint prevention and control. There is an urgent need to enlarge and reconstruct the coverage of joint prevention and control of air pollution in key area. Air quality models can identify and quantify the regional contribution of haze pollution and its key components with the help of numerical simulation, but it is difficult to be applied to larger spatial scale due to the complexity of model parameters. The time series analysis can recognize the existence of spatial interaction of haze pollution between cities, but it has not yet been used to further identify the spatial sources of haze pollution in large scale. Using econometric framework of time series analysis, this paper developed a new approach to perform spatial source apportionment. We applied this approach to calculate the contribution from spatial sources of haze pollution in China, using the monitoring data of particulate matter(PM_(2.5)) across 161 Chinese cities. This approach overcame the limitation of numerical simulation that the model complexity increases at excess with the expansion of sample range, and could effectively deal with severe large-scale haze episodes.
基金Supported by Research Project of Young and Middle-aged Teachers in Fujian Province(JAT170817)Innovation and Entrepreneurship Project of College Students(201712709011)
文摘The formation of heavy metal pollution in soil is closely related to human production and life. In order to effectively control heavy metal pollution and repair damaged soil,the pollution source should be known and judged first. Based on the preliminary analysis of major sources of soil heavy metal pollution in soil,combined with relevant literatures on heavy metal pollution source of soil or sediment at home and abroad in recent years,application progress of isotope tracer technique,especially lead isotope tracer technique,in the study of heavy metal pollution sources in soils and sediments were reviewed. The key points of future isotope tracer technology in the field of heavy metal pollution source apportionment were prospected.
基金supported by the National Natural Science Foundation of China (No.41875155)Natural Key Research and Development Program of China (No.2019YFA0607004)+1 种基金Environment and Conservation Fund/Woo Wheelock Green Fund (No.ECWW09EG04)Strategic Priority Research Program (B)of the Chinese Academy of Sciences (No.XDB05040502)。
文摘Fireworks(FW)could significantly worsen air quality in short term during celebrations.Due to similar tracers with biomass burning(BB),the fast and precise qualification of FW and BB is still challenging.In this study,online bulk and single-particle measurements were combined to investigate the contributions of FW and BB to the overall mass concentrations of PM_(2.5)and specific chemical species by positive matrix factorization(PMF)during the Chinese New Year in Hong Kong in February 2013.With combined information,fresh/aged FW(abundant ^(140)K_(2)NO_(3)^(+)and ^(213)K_(3)SO_(4)^(+)formed from ^(113)K_(2)Cl^(+)discharged by fresh FW)can be extracted from the fresh/aged BB sources,in addition to the Second Aerosol,Vehicles+Road Dust,and Sea Salt factors.The contributions of FW and BB were investigated during three high particle matter episodes influenced by the pollution transported from the Pearl River Delta region.The fresh BB/FW contributed 39.2%and 19.6%to PM_(2.5)during the Lunar Chinese New Year case.However,the contributions of aged FW/BB enhanced in the last two episodes due to the aging process,evidenced by high contributions from secondary aerosols.Generally,the fresh BB/FW showed more significant contributions to nitrate(35.1%and15.0%,respectively)compared with sulfate(25.1%and 5.9%,respectively)and OC(14.8%and11.1%,respectively)on average.In comparison,the aged FW contributed more to sulfate(13.4%).Overall,combining online bulk and single-particle measurement data can combine both instruments’advantages and provide a new perspective for applying source apportionment of aerosols using PMF.
基金supported by the National Key R&D Program of China(Nos.2019YFC1804502 and 2019YFC1804503)the Guangdong Provincial Natural Science Fund for Distinguished Young Scholars(No.2022B1515020051)+2 种基金the National Natural Science Foundation of China(No.42077332)the Science and Technology Program of Guangzhou(No.202201010149)the Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program(No.2017BT01Z032)。
文摘Industrial coking facilities are an important emission source for volatile organic compounds(VOCs).This study analyzed the atmospheric VOC characteristics within an industrial coking facility and its surrounding environment.Average concentrations of total VOCs(TVOCs)in the surrounding residential activity areas(R1 and R2),the coking facility(CF)and the control area(CA)were determined to be 138.5,47.8,550.0,and 15.0μg/m^(3),respectively.The cold drum process and coking and quenching areas within the coking facility were identified as the main polluting processes.The spatial variation in VOCs composition was analyzed,showing that VOCs in the coking facility and surrounding areas were mainly dominated by aromatic compounds such as BTX(benzene,toluene,and xylenes)and naphthalene,with concentrations being negatively correlated with the distance from the coking facility(p<0.01).The sources of VOCs in different functional areas across the monitoring area were analyzed,finding that coking emissions accounted for 73.5%,33.3% and 27.7% of TVOCs in CF,R1 and R2,respectively.These results demonstrated that coking emissions had a significant impact on VOC concentrations in the areas surrounding coking facility.This study evaluates the spatial variation in exposure to VOCs,providing important information for the influence of VOCs concentration posed by coking facility to surrounding residents and the development of strategies for VOC abatement.
基金supported by the National Key Research and Development Program,China(No.2018YFC1800400).
文摘Metal smelting have brought severe metal(loid)s contamination to the soil.Spatial distribution and pollution source analysis for soil metal(loid)s in an abandoned lead/zinc smelter were studied.The results showed that soil was contaminated heavily withmetal(loid)s.The mean of lead(Pb),arsenic(As),cadmium(Cd),mercury(Hg)and antimony(Sb)content in topsoil is 9.7,8.2,5.0,2.3,and 1.2 times higher than the risk screening value for soil contamination of development land of China(GB36600-2018),respectively.Cd ismainly enriched in the 0–6mdepth of site soil while As and Pbmainly deposited in the 0–4mlayer.The spatial distribution of soil metal(loid)s is significantly correlated with the pollution source in the different functional areas of smelter.As,Hg,Sb,Pb and copper(Cu)were mainly distributed in pyrometallurgical area,while Cd,thallium(Tl)and zinc(Zn)was mainly existed in both hydrometallurgical area and raw material storage area.Soil metal(loid)s pollution sources in the abandoned smelter are mainly contributed to the anthropogenic sources,accounting for 84.5%.Specifically,Pb,Tl,As,Hg,Sb and Cumainly from atmospheric deposition(55.9%),Cd and Zn mainly from surface runoff(28.6%),While nickel(Ni)mainly comes from parent material(15.5%).The results clarified the spatial distribution and their sources in different functional areas of the smelter,providing a new thought for the risk prevention and control of metal(loid)s in polluted site soil.
基金supported by the Ministry of Science and Technology of China(Nos. 2016YFC0202000, 2019YFC0214203)。
文摘Based on the online and membrane sampling data of Yuncheng from January 1st to February 12th,2020,the formation mechanism of haze under the dual influence of Spring Festival and COVID-19 (Corona Virus Disease) was analyzed.Atmospheric capacity,chemical composition,secondary transformation,source apportionment,backward trajectory,pollution space and enterprise distribution were studied.Low wind speed,high humidity and small atmospheric capacity inhibited the diffusion of air pollutants.Four severe pollution processes occurred during the period,and the pollution degree was the highest around the Spring Festival.In light,medium and heavy pollution periods,the proportion of SNA (SO_(4)^(2-),NO_(3)-and NH_(4)^(+)) was 59.6%,56.0%and 54.9%,respectively,which was the largest components of PM_(2.5);the[NO_(3)-]/[SO_(4)^(2-)]ratio was 2.1,1.5 and 1.7,respectively,indicating that coal source had a great influence;the changes of NOR (nitrogen oxidation ratio,0.44,0.45,0.61)and SOR (sulphur oxidation ratio,0.40,0.49,0.65) indicated the accumulation of secondary aerosols with increasing pollution.The coal combustion,motor vehicle,secondary inorganic sources and industrial sources contributed 36.8%,26.59%,11.84%and 8.02%to PM_(2.5)masses,respectively.Backward trajectory showed that the influence from the east was greater during the Spring Festival,and the pollutants from the eastern air mass were higher,which would aggravate the pollution.Meteorological and Spring Festival had a great impact on heavy pollution weather.Although some work could not operate due to the impact of the COVID-19 epidemic,the emission of pollutants did not reduce much.
基金supported by the National Nature Science Foundation for Young Scientists of China(Nos.41605094,41905115).
文摘Volatile organic compounds(VOCs)are important precursors of secondary organic compounds and ozone,which raise major environmental concerns.To investigate the VOC emission characteristics,measurements of VOCs based on proton transfer reaction-mass spectrometry during 2017 were conducted in a coastal industrial area in Ningbo,Zhejiang Province,China.Based on seasonal variation in species concentration,the positive matrix factorization(PMF)receptor model was applied to apportion the sources of VOCs in each season.The PMF results revealed that unknown acetonitrile source,paint solvent,electronics industry,biomass burning,secondary formation and biogenic emission were mainly attributed to VOC pollution.Biomass burning and secondary formation were the major sources of VOCs and contributed more than 70%of VOC emissions in spring and autumn.Industry-related sources contributed 8.65%–31.2%of the VOCs throughout the year.The unknown acetonitrile source occurred in winter and spring,and contributed 7.6%–43.73%of the VOC emissions in the two seasons.Conditional probability function(CPF)analysis illustrated that the industry sources came from local emission,while biomass burning and biogenic emission mainly came from the northwest direction.The potential source contribution function(PSCF)model showed that secondary formation-related source was mainly from Jiangsu Province,northeastern China and the surrounding ocean.The potential source areas of unknown acetonitrile source were northern Zhejiang Province,southern Jiangsu Province and the northeastern coastal marine environments.
基金supported by the National Natural Science Foundation of China(No.42175135)the Science and Technology Commission of the Shanghai Municipality(No.20ZR1447800).
文摘Monocyclic aromatic hydrocarbons(MAHs)and polycyclic aromatic hydrocarbons(PAHs)are both well known as hazardous air pollutants and also important anthropogenic precursors of tropospheric ozone(O3)and secondary organic aerosols(SOA).In recent years,there have been intensive studies covering MAHs emission from various sources and their behavior under stimulated photochemical conditions.Yet in-situ measurements of PAHs presence and variations in ambient air are sparse.Herein we conducted large geometrical scale mobile measurements for 16 aromatic hydrocarbons(AHs,including 7 MAHs and 9 PAHs)in eastern China between October 27 and November 8,2019.This unique dataset has allowed for some insights in terms of AHs concentration variations,accompanying chemical composition,source contributions and spatial distributions in eastern China.In general,AHs showed a clear concentration variability between the south and the north of the Yangtze River Delta(YRD).The concentrations of PAHs were approximately 9%of AHs,but contributed 23%of SOA formation potential.Source apportionment via positive matrix factorization(PMF)model revealed that industrial processes as the largest source(44%)of observed AHs,followed by solvent usage(21%),vehicle exhaust(19%),coal combustion(11%)and coking processes(6%).In the perspective of PAHs sources,coal combustion emissions were identified as the dominating factor of a share of 41%–52%in eastern China.Our findings complemented the simultaneously monitoring information of PAHs and MAHs in eastern China,revealed the importance of PAHs to SOA formation and highlighted the necessity of formulating strategies to reduce emissions from anthropogenic sources and reduce risks to human health.
基金supported by the National Key Research and Development Program of China(No.2018YFC0214102)。
文摘The source apportionment of PM2.5 is essential for pollution prevention.In view of the weaknesses of individual models,we proposed an integrated chemical mass balancesource emission inventory(CMB-SEI)model to acquire more accurate results.First,the SEI of secondary component precursors(SO2,NOx,NH3,and VOCs)was compiled to acquire the emission ratios of these sources for the precursors.Then,a regular CMB simulation was executed to obtain the contributions of primary particle sources and secondary components(SO4^2-,NO3^-3,NH4^+,and SOC).Afterwards,the contributions of secondary components were apportioned into primary sources according to the source emission ratios.The final source apportionment results combined the contributions of primary sources by CMB and SEI.This integrated approach was carried out via a case study of three coastal cities(Zhoushan,Taizhou,and Wenzhou;abbreviated WZ,TZ,and ZS)in Zhejiang Province,China.The regular CMB simulation results showed that PM2.5 pollution was mainly affected by secondary components and mobile sources.The SEI results indicated that electricity,industrial production and mobile sources were the largest contributors to the emission of PM2.5 gaseous precursors.The simulation results of the CMB-SEI model showed that PM2.5 pollution in the coastal areas of Zhejiang Province presented complex pollution characteristics dominated by mobile sources,electricity production sources and industrial production sources.Compared to the results of the CMB and SEI models alone,the CMB-SEI model completely apportioned PM2.5 to primary sources and simultaneously made the results more accurate and reliable in accordance with local industrial characteristics.
基金supported by the National Natural Science Foundation of China (Nos.41675127, 41475116)。
文摘Characteristics of atmospheric VOCs(volatile organic compounds) have been extensively studied in megacities in China, however, they are scarcely investigated in medium/smallsized cities in North China Plain(NCP).A comprehensive research on possible sources of VOCs was conducted in a medium-sized city of NCP, from May to September 2019.A total of 143 canister samples of 8 sites in Xuchang city were collected, and 57 VOC species were detected.The average VOC concentrations were 42.6 ± 31.6 μg/m3, with 53.7 ± 31.0 μg/m3 and 32.1 ± 27.8 μg/m^(3), in the morning and afternoon, respectively.Alkenes and aromatics contributed 80% of the total ozone formation potential(OFP).Aromatics accounted for more than 95% of secondary organic aerosol potential(SOAP).VOCs were dominated by the local emission with significant transport from the southeast direction.PMF analysis extracted 6 sources, which were combustion(33.1%), LPG usage(19.3%), vehicular exhaust & fuel evaporation(15.8%), solvent usage(15.2%), industrial(9.11%) and biogenic(7.51%), respectively and they contributed 33.4%, 17.6%, 12.9%, 18.6%, 9.28% and 8.22% to the OFP, respectively.Combustion and LPG usage were the dominant VOC sources;and combustion, solvent usage and LPG usage were the main sources of OFP in Xuchang city, which were different to megacities in China with a high contribution from vehicular exhaust, solvent usage and industry,suggesting specific control strategies on VOCs need to be implemented in medium-sized city such as Xuchang city.
基金supported by the National Key R&D Program of China(No.2017YFC0210000)the National Natural Science Foundation of China(Nos.41705113 and 41877312)+1 种基金the Young Talent Project of the Center for Excellence in Regional Atmospheric Environment CAS(CERAE201802)the Beijing Major Science and Technology Project(No.Z181100005418014)。
文摘Atmospheric extinction is impacted by the chemical composition of particles.To better understand the chemical composition of PM_(2.5)(particles with diameters of less than 2.5μm)and its relationship with extinction,one-month sampling campaigns were carried out in four different seasons from 2013 to 2014 in Jinan,China.The seasonal average concentrations of PM_(2.5)were 120.9(autumn),156.6(winter),102.5(spring),and 111.8μg/m^(3)(summer).The reconstructed PM_(2.5)chemical composition showed that sulfate,nitrate,chlorine salt,organic matter(OM),mineral dust,elemental carbon(EC)and others accounted for 25%,14%,2%,24%,22%,3%and 10%,respectively.The relationship between the chemical composition of PM_(2.5)and visibility was reconstructed by the IMPROVE method,and ammonium sulfate,ammonium nitrate,OM and EC dominated the visibility.Seven main sources were resolved for PM_(2.5),including secondary particles,coal combustion,biomass burning,industry,motor vehicle exhaust,soil dust and cooking,which accounted for 37%,21%,13%,13%,12%,3%and 1%,respectively.The contributions of different sources to visibility were similar to those to PM_(2.5).With increasing severity of air pollution,the contributions of secondary particles and coal combustion increased,while the contribution of motor vehicle exhaust decreased.The results showed that coal combustion and biomass burning were still the main sources of air pollution in Jinan.
基金supported by the National Key R&D Program of China(Nos.2017YFC0212802 and 2017YFC0212004)the support of MOST project(No.2017YFC0212001)for the collaboration。
文摘We present the continuously measurements of volatile organic compounds(VOCs)at a receptor site(Wan Qing Sha,WQS)in the Pearl River Delta(PRD)region from September to November of 2017.The average mixing ratios of total VOCs(TVOCs)was 36.3±27.9 ppbv with the dominant contribution from alkanes(55.5%),followed by aromatics(33.3%).The diurnal variation of TVOCs showed a strong photochemical consumption during daytime,resulting in the formation of ozone(O_(3)).Five VOC sources were resolved by the positive matrix factorization(PMF)model,including solvent usage(28.6%),liquid petroleum gas(LPG)usage(24.4%),vehicle exhaust(21.0%),industrial emissions(13.2%)and gasoline evaporation(12.9%).The regional transport air masses from the upwind cities of south China can result in the elevated concentrations of TVOCs.Low ratios of TVOCs/NO_(x)(1.53±0.88)suggested that the O_(3) formation regime at WQS site was VOC-limited,which also confirmed by a photochemical box model with the master chemical mechanism(PBM-MCM).Furthermore,the observation on high-O_(3) episode days revealed that frequent O_(3) outbreaks at WQS were mainly caused by the regional transport of anthropogenic VOCs especially for aromatics and the subsequent photochemical reactions.This study provides valuable information for policymakers to propose the effective control strategies on photochemical pollution in a regional perspective.
基金This work was supported by the National Natural Science Foundation of China(Grant No.20877042)National Science and Technology Supporting Program during the Eleventh Five-year Plan Period(No.2007BAC16B01).
文摘A total of 168 PM_(10)samples were collected during the year of 2005 at eight sites in the city of Wuxi in China.Fifteen chemical elements,three water-soluble ions,total carbon and organic carbon were analyzed.Six source categories were identified and their contributions to ambient PM_(10)in Wuxi were estimated using a nested chemical mass balance method that reduces the effects of colinearity on the chemical mass balance model.In addition,the concentrations of secondary aerosols,such as secondary organic carbon,sulfate and nitrate,were quantified.The spatially averaged PM_(10)was high in the spring and winter(123μg·m^(-3)and low in the summer-fall(90μg·m^(-3)).According to the result of source apportionment,resuspended dust was the largest contributor to ambient PM_(10),accounting for more than 50%of the PM_(10)mass.Coal combustion(14.6%)and vehicle exhaust(9.4%)were also significant source categories of ambient PM_(10).Construction and cement dust,sulfates,secondary organic carbon,and nitrates made contributions ranging between 4.1%and 4.9%.Other source categories such as steel manufacturing dust and soil dust made low contributions to ambient PM_(10).
基金the Tianjin Science and Technology Program(No.18ZXSZSF00160)the Fundamental Research Funds for the Central Universities of China(Nos.ZB19500210 and ZB19000804)。
文摘The submicron particulate matter(PM_(1))and fine particulate matter(PM_(2.5))are very important due to their greater adverse impacts on the natural environment and human health.In this study,the daily PM_(1) and PM_(2.5) samples were collected during early summer 2018 at a sub-urban site in the urban-industrial port city of Tianjin,China.The collected samples were analyzed for the carbonaceous fractions,inorganic ions,elemental species,and specific marker sugar species.The chemical characterization of PM_(1) and PM_(2.5) was based on their concentrations,compositions,and characteristic ratios(PM_(1)/PM_(2.5),AE/CE,NO3^-/SO4^2-,OC/EC,SOC/OC,OM/TCA,K^+/EC,levoglucosan/K^+,V/Cu,and V/Ni).The average concentrations of PM_(1) and PM_(2.5) were 32.4μg/m and 53.3μg/m^3,and PM_(1) constituted 63%of PM_(2.5) on average.The source apportionment of PM_(1) and PM_(2.5) by positive matrix factorization(PMF)model indicated the main sources of secondary aerosols(25%and 34%),biomass burning(17%and 20%),traffic emission(20%and 14%),and coal combustion(17%and 14%).The biomass burning factor involved agricultural fertilization and waste incineration.The biomass burning and primary biogenic contributions were determined by specific marker sugar species.The anthropogenic sources(combustion,secondary particle formation,etc)contributed significantly to PM_(1) and PM_(2.5),and the natural sources were more evident in PM_(2.5).This work significantly contributes to the chemical characterization and source apportionment of PM_(1) and PM_(2.5) in near-port cities influenced by the diverse sources.
基金supported by Key Projects of National Key Research and Development Program of the Ministry of Science and Technology of China(No.2017YFC0213005)National Natural Science Foundation of China(Grant No.21625701)+1 种基金Beijing Municipal Science and Technology Commission(No.Z191100009119001)the Samsung Advanced Institute of Technology.
文摘Agricultural sources and non-agricultural emissions contribute to gaseous ammonia(NH_(3))that plays a vital role in severe haze formation.Qualitative and quantitative contributions of these sources to ambient PM_(2.5)(particulate matter with an aerodynamic equivalent diameter below 2.5µm)concentrations remains uncertain.Stable nitrogen isotopic composition(δ^(15)N)of NH_(3)and NH_(4)+(δ^(15)N(NH_(3))andδ^(15)N(NH_(4)+),respectively)can yield valuable information about its sources and associated processes.This review provides an overview of the recent progress in analytical techniques forδ^(15)N(NH_(3))andδ^(15)N(NH_(4)+)measurement,sampling of atmospheric NH_(3)and NH_(4)+in the ambient air and their sources signature(e.g.,agricultural vs.fossil fuel),and isotope-based source apportionment of NH_(3)in urban atmosphere.This study highlights that collecting sample that are fully representative of emission sources remains a challenge in fingerprintingδ^(15)N(NH_(3))values of NH_(3)emission sources.Furthermore,isotopic fractionation during NH_(3)gas-to-particle conversion under varying ambient field conditions(e.g.,relative humidity,particle pH,temperature)remains unclear,which indicates more field and laboratory studies to validate theoretically predicted isotopic fractionation are required.Thus,this study concludes that lack of refinedδ^(15)N(NH_(3))fingerprints and full understanding of isotopic fractionation during aerosol formation in a laboratory and field conditions is a limitation for isotope-based source apportionment of NH_(3).More experimental work(in chamber studies)and theoretical estimations in combinations of field verification are necessary in characterizing isotopic fractionation under various environmental and atmospheric neutralization conditions,which would help to better interpret isotopic data and our understanding on NH_(x)(NH_(3)+NH_(4)+)dynamics in the atmosphere.
基金supported by the National Natural Science Foundation of China (Nos. 41773097, 41971286)the Postgraduate Research Innovation project of Jiangsu Province (No. KYCX21_1330)。
文摘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 ΣPAHs(sum of all 16 measured PAHs) concentrations ranged from 51.89 to 132.82 ng/g with an average of 80.39 ng/g. TheΣ 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 ΣPAHs 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.
基金This work was supported by the National Key R&D Program of China(Grant 2017YFC0209904)National Natural Science Foundation of China(Grant 41877314)。
文摘Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain.In this study,an industrial district(Shahe City)with a large glass manufactur-ing sector was investigated to clarify the relative contribution of fine particulate matter(PM_(2.5))to the city's high levels of pollution.The Nest Air Quality Prediction Model System(NAQPMS),paired with Weather Research and Forecasting(WRF),was adopted and applied with a spatial resolution of 5 km.During the study period,the mean mass concentrations of PM_(2.5),SO_(2),and NO_(2)were observed to be 132.0,76.1,and 55.5μg/m^(3),respectively.The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level.The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4%of the city's total PM_(2.5)concentration.This contribu-tion increased to 73.9±21.2%when unfavorable meteorological conditions(high relative hu-midity,weak wind,and low planetary boundary layer height)were present;such conditions are more frequently associated with severe pollution(PM_(2.5)≥250μg/m^(3)).The contribution from Shahe was 52.3±21.6%.The source apportionment results showed that industry(47%),transportation(10%),power(17%),and residential(26%)sectors were the most important sources of PM_(2.5)in Shahe.The glass factories(where chimney stack heights were normally<70 m)in Shahe contributed 32.1%of the total PM_(2.5)concentration in Shahe.With an in-crease in PM_(2.5)concentration,the emissions from glass factories accumulated vertically and narrowed horizontally.At times when pollution levels were severe,the horizontally influ-enced area mainly covered Shahe.Furthermore,sensitivity tests indicated that reducing emissions by 20%,40%,and 60% could lead to a decrease in themass concentration of PM_(2.5) of of 12.0%,23.8%,and 35.5%,respectively.
