Gravimetric analysis for PM2.5 mass concentration based on year-round monitoring at an urban site in Beijing

Daily PM_(2.5)(particulate matter with an aerodynamic diameter of below 2.5 μm) mass concentrations were measured by gravimetric analysis in Chinese Research Academy of Environmental Sciences(CRAES), in the northern part of the Beijing urban area, from December 2013 to April 2015. Two pairs of Teflon(T1/T2) and Quartz(Q1/Q2) samples were obtained, for a total number of 1352 valid filters. Results showed elevated pollution in Beijing,with an annual mean PM_(2.5)mass concentration of 102 μg/m~3. According to the calculated PM_(2.5)mass concentration, 50% of our sampling days were acceptable(PM_(2.5) 75 μg/m~3), 30% had slight/medium pollution(75–150 μg/m~3), and 7% had severe pollution( 250 μg/m~3). Sampling interruption occurred frequently for the Teflon filter group(75%) in severe pollution periods,resulting in important data being missing. Further analysis showed that high PM_(2.5)combined with high relative humidity(RH) gave rise to the interruptions. The seasonal variation of PM_(2.5)was presented, with higher monthly average mass concentrations in winter(peak value in February, 422 μg/m~3), and lower in summer(7 μg/m~3 in June). From May to August, the typical summer period, least severe pollution events were observed, with high precipitation levels accelerating the process of wet deposition to remove PM_(2.5). The case of February presented the most serious pollution, with monthly averaged PM_(2.5)of 181 μg/m~3 and 32% of days with severe pollution. The abundance of PM_(2.5)in winter could be related to increased coal consumption for heating needs.     

Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016

With rapid economic growth and urbanization, the Yangtze River Delta(YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014–2016. In recent years, the concentrations of all air pollutants, except O_3,decreased. Spatially, the PM_(2.5), PM_(10), SO_2, and CO concentrations were higher in the northern YRD region, and NO_2 and O_3 were higher in the central YRD region. Based on the number of non-attainment days(i.e., days with air quality index greater than 100), PM_(2.5) was the largest contributor to air pollution in the YRD region, followed by O_3, PM_(10), and NO_2.However, particulate matter pollution has declined gradually, while O_3 pollution worsened.Meteorological conditions mainly influenced day-to-day variations in pollutant concentrations. PM_(2.5) concentration was inversely related to wind speed, while O_3 concentration was positively correlated with temperature and negatively correlated with relative humidity.The air quality improvement in recent years was mainly attributed to emission reductions.During 2014–2016, PM_(2.5), PM_(10), SO_2, NO_x, CO, NH_3, and volatile organic compound(VOC)emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.     

Chemical characteristics and source apportionment of PM2.5 between heavily polluted days and other days in Zhengzhou, China

PM_(2.5) samples were collected in Zhengzhou during 3 years of observation, and chemical characteristics and source contribution were analyzed. Approximately 96% of the daily PM_(2.5) concentrations and annual average values exceeded the Chinese National Ambient Air Quality Daily and Annual Standards, indicating serious PM_(2.5) pollution. The average concentration of water-soluble inorganic ions was 2.4 times higher in heavily polluted days(daily PM32.5 concentrations 250 μg/mand visibility 3 km) than that in other days, with sulfate, nitrate, and ammonium as major ions. According to the ratio of NO-3/SO2-4,stationary sources are still the dominant source of PM_(2.5) and vehicle emission could not be ignored. The ratio of secondary organic carbon to organic carbon indicated that photochemical reactivity in heavily polluted days was more intense than in other days.Crustal elements were the most abundant elements, accounting for more than 60% of 23 elements. Chemical Mass Balance results indicated that the contributions of major sources(i.e., nitrate, sulfate, biomass, carbon and refractory material, coal combustion, soil dust,vehicle, and industry) of PM_(2.5) were 13%, 16%, 12%, 2%, 14%, 8%, 7%, and 8% in heavily polluted days and 20%, 18%, 9%, 2%, 27%, 14%, 15%, and 9% in other days, respectively.Extensive combustion activities were the main sources of polycyclic aromatic hydrocarbons during the episode(Jan 1-9, 2015) and the total benzo[a]pyrene equivalency concentrations in heavily polluted days present significant health threat. Because of the effect of regional transport, the pollution level of PM_(2.5) in the study area was aggravated.     

Chemical composition and source apportionment of PM10 and PM2.5 in different functional areas of Lanzhou, China

To elucidate the air pollution characteristics of northern China, airborne PM_10(atmospheric dynamic equivalent diameter ≤ 10 μm) and PM_(2.5)(atmospheric dynamic equivalent diameter ≤ 2.5 μm) were sampled in three different functional areas(Yuzhong County,Xigu District and Chengguan District) of Lanzhou, and their chemical composition(elements, ions, carbonaceous species) was analyzed. The results demonstrated that the highest seasonal mean concentrations of PM_10(369.48 μg/m~3) and PM_(2.5)(295.42 μg/m~3) were detected in Xigu District in the winter, the lowest concentration of PM_(2.5)(53.15 μg/m~3) was observed in Yuzhong District in the fall and PM_10(89.60 μg/m~3) in Xigu District in the fall.The overall average OC/EC(organic carbon/elemental carbon) value was close to the representative OC/EC ratio for coal consumption, implying that the pollution of Lanzhou could be attributed to the burning of coal. The content of SNA(the sum of sulfate, nitrate,ammonium, SNA) in PM_(2.5)in Yuzhong County was generally lower than that at other sites in all seasons. The content of SNA in PM_(2.5)and PM_10 in Yuzhong County was generally lower than that at other sites in all seasons(0.24–0.38), indicating that the conversion ratios from precursors to secondary aerosols in the low concentration area was slower than in the area with high and intense pollutants. Six primary particulate matter sources were chosen based on positive matrix factorization(PMF) analysis, and emissions from dust, secondary aerosols, and coal burning were identified to be the primary sources responsible for the particle pollution in Lanzhou.     

Heavy metals and their source identification in particulate matter (PM2.5) in Isfahan City, Iran

The presence of heavy metals(HMs) in particulate matters(PMs) particularly fine particles such as PM_(2.5) poses potential risk to the health of human being. The purpose of this study was to analyze the contents of HMs in PM_(2.5) in the atmospheric monitoring stations in Isfahan city,Iran, in different seasons between March 2014 and March 2015 and their source identification using principle component analysis(PCA). The samples of PM_(2.5) were taken using a high volume sampler in 7 monitoring stations located throughout the city and industrial zones since March 2014 to March 2015. The HMs content of the samples was measured using ICP-MS.The results showed that the concentrations of As, Cd and Ni were in a range of 23–36, 1–12,and 5–76 ng/m~3 at all the stations which exceeded the US-EPA standards. Furthermore,the concentrations of Cr and Cu reached to 153 and 167 ng/m~3 in some stations which were also higher than the standard levels. Depending on the potential sources of HMs, their concentration in PM_(2.5) through the various seasons was different. PCA illustrated that the different potential sources of HMs in the atmosphere, showing that the most important sources of HMs originated from fossil fuel combustion, abrasion of vehicle tires, industrial activities(e.g., iron and steel industries) and dust storms. Management and control of air pollution of industrial plants and vehicles are suggested for decreasing the risk of the HMs in the region.     

GIS-based analysis of population exposure to PM2.5 air pollution—A case study of Beijing

PM_(2.5), formally defined as particulate matter with diameter less than 2.5 μm, is one of most harmful air pollutants threatening human health. Numerous epidemiological studies have shown that both short-term and long-term exposures to PM_(2.5) are strongly linked with respiratory diseases. In this study, various types of spatio-temporal data were collected and used to estimate the spatio-temporal variation of PM_(2.5) exposure in Beijing in 2014. The seasonal and daily variation of the population-weighted exposure level(PWEL) in 2014 was estimated and compared. The results show that the population exposure to ambient air pollution differs significantly in the four seasons, and the exposure levels in winter and spring are notably higher than the other seasons; the exposure level changes greatly from North to South, and each sub-district maintains similarity to neighboring sub-districts.     

Analysis of air quality characteristics of Beijing–Tianjin–Hebei and its surrounding air pollution transport channel cities in China

Beijing–Tianjin–Hebei(BTH) and its surrounding areas are very important to air pollution control in China.To analyze the characteristics of BTH and its surrounding areas of China,we collected 5,641,440 air quality data from 161 air monitoring stations and 37,123,000 continuous monitoring data from air polluting enterprises in BTH and surrounding cities to establish an indicator system for urban air quality portraits.The results showed that particulate matter with aerodynamic diameters of 2.5 μm(PM_(2.5)),particulate matter with aerodynamic diameters of 10 μm(PM_(10)) and SO_2 improved significantly in 31 cities from2015 to 2018,but ozone deteriorated.Air quality in BTH and the surrounding areas showed obvious seasonal characteristics,among which PM_(2.5),PM_(10),SO_2,and NO_2 showed a "U" type distribution from January to December,while O_3 had an "inverted U" distribution.The hourly changes in air quality revealed that peaks of PM_(2.5),PM_(10) and NO_2 appeared from 8:00 to 10:00,while those for O_3 appeared at 15:00–16:00.The exposure characteristics of the 31 cities showed that six districts in Beijing had the highest air quality population exposure,and that exposure levels in Zhengzhou,Puyang,Anyang,Jincheng were higher than the average of the 31 investigated cities.Additionally,multiple linear regression revealed a negative correlation between meteorological factors(especially wind and precipitation) and air quality,while a positive correlation existed between industrial pollution emissions and air quality in most of BTH and its surrounding cities.     

Characterization of atmospheric aerosol (PM10 and PM2.5) from a medium sized city in São Paulo state, Brazil

Air pollution causes deleterious effects on human health with aerosols being among the most polluting agents.The objective of this work is the characterization of the PM_(2.5) and PM_(10) aerosol mass in the atmosphere.The methods of analysis include WD-XRF and EDS.Data were correlated with meteorological information and air mass trajectories(model HYSPLIT)by multivariate analysis.A morphological structural analysis was also carried out to identify the probable sources of atmospheric aerosols in the city of Sao Jose do Rio Preto,Brazil.The mean mass concentration values obtained were 24.54 μg/m~3 for PM_(10),above the WHO annual standard value of 20 μg/m~3 and 10.88 μg/m~3 for PM_(2.5) whose WHO recommended limit is10 μg/m~3.WD-XRF analysis of the samples revealed Si and Al as major components of the coarse fraction.In the fine fraction,the major elements were Al and S.The SEM-FEG characterization allowed identifying the morphology of the particles in agglomerates,ellipsoids and filaments in the PM_(10),besides spherical in the PM_(2.5).The analysis by EDS corroborated WD-XRF results,identifying the crustal elements,aluminosilicates and elements of anthropogenic origin in the coarse fraction.For the fine fraction crustal elements were also identified;aluminosilicates,black carbon and spherical particles(C and O) originating from combustion processes were predominant.The use of multivariate analysis to correlate air mass trajectories with the results of the morpho-structural characterization of the particulate matter allowed confirmation of the complex composition of the particles resulting from the combination of both local and long-distance sources.     

Effects of relative humidity and PM2.5 chemical compositions on visibility impairment in Chengdu, China

To better understand the potential causes of visibility impairment in autumn and winter in Chengdu, relative humidity(RH), visibility, the concentrations of PM_(2.5) and its chemical components were on-line measured continuously in Chengdu from Nov. 2016 to Jan. 2017.Six obvious haze episodes occurred in Chengdu, with the total time of haze episodes accounted for more than 90% of the total observation period, and higher NO_2 concentrations and RH were related to the high particle concentrations in haze episodes. The visibility decreased in a non-linear tendency under different RH conditions with the increase of PM_(2.5) concentrations, which was more sensitive to RH under lower PM_(2.5) concentrations. The threshold concentration of PM_(2.5) got more smaller with the increase of RH. During the entire observation period, organic matter(OM) was the largest contributor(31.12% to extinction coefficient(bext)), followed by NH_4NO_3 and(NH_4)_2SO_4 with 28.03% and 23.01%, respectively.However, with the visibility impairment from Type I(visibility 10 km) to Type IV(visibility ≤ 2 km), the contribution of OM to bextdecreased from 38.12% to 26.77%, while the contribution of NH_4NO_3 and(NH_4)_2SO_4 to bextincreased from 19.09% and 20.20% to 34.29% and 24.35%, respectively, and NH_4NO_3 became the largest contributor to bextat Type IV. The results showed that OM and NH_4NO_3 were the key components of PM_(2.5) for visibility impairment in Chengdu, indicating that the control of precursors emissions of carbonaceous species and NH_4NO_3 could effectively improve the visibility in Chengdu.     

Aerosol optical properties under different pollution levels in the Pearl River Delta (PRD) region of China

To clarify the aerosol hygroscopic growth and optical properties of the Pearl River Delta(PRD)region,integrated observations were conducted in Heshan City of Guangdong Province from October 19 to November 17,2014.The concentrations and chemical compositions of PM_(2.5),aerosol optical properties and meteorological parameters were measured.The mean value of PM_(2.5) increased from less than 35(excellent) to 35-75 μg/m~3(good) and then to greater than 75 μg/m~3(pollution),corresponding to mean PM_(2.5) values of 24.9,51.2,and 93.3 μg/m~3,respectively.The aerosol scattering hygroscopic growth factor(f(RH = 80%)) values were 2.0,2.12,and 2.18 for the excellent,good,and pollution levels,respectively.The atmospheric extinction coefficient(σext)and the absorption coefficient of aerosols(σ_(ap)) increased,and the single scattering albedo(SSA)decreased from the excellent to the pollution levels.For different air mass sources,under excellent and good levels,the land air mass from northern Heshan had lower f(RH) and σ_(sp) values.In addition,the mixed aerosol from the sea and coastal cities had lower f(RH) and showed that the local sources of coastal cities have higher scattering characteristics in pollution periods.     

Environmental impact and health risk assessment of volatile organic compound emissions during different seasons in Beijing

Volatile organic compounds (VOCs) are major contributors to air pollution. Based on the emission characteristics of 99 VOCs that daily measured at 10 am in winter from 15 December 2015 to 17 January 2016 and in summer from 21 July to 25 August 2016 in Beijing, the environmental impact and health risk of VOC were assessed. In the winter polluted days, the secondary organic aerosol formation potential (SOAP) of VOC (199.70 ± 15.05 μg/m³) was significantly higher than that on other days. And aromatics were the primary contributor (98.03%) to the SOAP during the observation period. Additionally, the result of the ozone formation potential (OFP) showed that ethylene contributed the most to OFP in winter (26.00% and 27.64% on the normal and polluted days). In summer, however, acetaldehyde was the primary contributor to OFP (22.00% and 21.61% on the normal and polluted days). Simultaneously, study showed that hazard ratios and lifetime cancer risk values of acrolein, chloroform, benzene, 1,2-dichloroethane, acetaldehyde and 1,3-butadiene exceeded the thresholds established by USEPA, thereby presenting a health risk to the residents. Besides, the ratio of toluene-to-benzene indicated that vehicle exhausts were the main source of VOC pollution in Beijing. The ratio of m-/p-xylene-to-ethylbenzene demonstrated that there were more prominent atmospheric photochemical reactions in summer than that in winter. Finally, according to the potential source contribution function (PSCF) results, compared with local pollution sources, the spread of pollution from long-distance VOCs had a greater impact on Beijing.     

Baosteel emission control significantly benefited air quality in Shanghai

As the largest iron and steel producer in China, a part of Baosteel moved out of Shanghai deserves close attention due to its environmental impact. To understand the effect of Baosteel emission control on air quality in Shanghai, daily PM_(10), PM_(2.5), SO_2, NO_2 and CO were measured from 2010 to 2016. Concentrations of pollutants in Baoshan District presented a decreased trend during 2010–2016, with a reduction rate of 28.6% for PM_(10), 67.3% for SO_2, 8.6% for NO_2 and 42.0% for CO. However, fine particle pollution in Baoshan District during 2012–2016 seems to become more prominent, with PM_(2.5) concentration of 47 ± 28,45 ± 33, 38 ± 24, 54 ± 41 and 51 ± 34 μg/m3, respectively, indicating a slight increase of 8.5%in PM_(2.5). Concentrations of PM_(10) and CO decreased by 12.5% and 33.8% in the second half year in 2016(compared with that in 2015) probably due to closure of blast furnace of Baosteel. Baosteel was identified as the largest pollution source in Baoshan District.Emission from Baosteel accounted for 58.0% of SO_2, 43.6% of NO_2 and 79.3% of dust in total emission from Baoshan District during 2010–2015. Meanwhile, pollutant emission and coal consumption from Baosteel decreased by 52.0% for SO_2, 40.1% for NO_2, 15.7% for dust and22% for coal consumption. Energy consumption in Baoshan District reduced by 31% from2011 to 2015. Air quality improvement in Shanghai was attributed to local emission reduction, together with regional air quality improvement.     

Comparisons of two serious air pollution episodes in winter and summer in Beijing

Characteristics of two serious air pollution episodes(9–15 January, as the winter case; and30 June to 1 July, as the summer case), which occurred in Beijing in 2013 were investigated and compared using multi-method observations and numerical simulations. During these two air pollution episodes, PM_(2.5) concentrations varied significantly within Beijing, with PM_(2.5) concentrations in southern parts of Beijing being significantly higher than in northern areas. Typically, heavy air pollution episodes begin in the southern parts and disperse towards the northern parts of Beijing. Clearly, synoptic patterns and the stability of atmospheric circulation patterns were the main factors controlling air pollution in Beijing.During the winter case, a warm center above 900 h Pa occurred over Beijing. Meanwhile, in the summer case, although there was only a weak inversion, the convective inhibition energy was strong(over 200 J/k G). This clearly influenced the duration of the air pollution event. Except for the local accumulation and secondary atmospheric reactions in both cases, regional straw burnings contributed a lot to the PM_(2.5) concentrations in summer case.Using the CAMxmodel, we established that regional transport contributed almost 59% to the PM_(2.5) averaged concentration in Beijing in the winter case, but only 31% in the summer case. Thus, the winter case was a typical regional air pollution episode, while the summer case resulted from local accumulation straw burnings transportation and strong secondary atmospheric reactions. Given that air pollution is a regional problem in China, consistent and simultaneous implementation of regional prevention and control strategies is necessary to improve regional air quality.     

Insights into the phenomenon of an explosive growth and sharp decline in haze: A case study in Beijing

A severe haze episode occurred in winter in the North China Plain(NCP),and the phenomenon of an explosive growth and sharp decline in PM_(2.5)(particulate matter with an aerodynamic diameter equal to or less than 2.5μm)concentration was observed.To study the systematic causes for this phenomenon,comprehensive observations were conducted in Beijing from November 26 to December 2,2015;during this period,meteorological parameters,LIDAR data,and the chemical compositions of aerosols were determined.The haze episode was characterized by rapidly varying PM2.5 concentration,and the highest PM_(2.5) concentration reached 667μg/m~3.During the haze episode,the NCP was dominated by a weak high-pressure system and continuously low PBL(planetary boundary layer)heights,which are unfavorable conditions for the diffusion of pollutants.The large increases in the concentrations of SNA(SO_4~(2-),NO_3~-and NH_4~+)during the haze implied that the formation of SNA was the largest contribution.Water vapor also played a vital role in the formation of haze by promoting the chemical transformation of secondary pollutants,which led to higher PM_(2.5) concentrations.The spatial distributions of PM_(2.5) in Beijing at different times and the backward trajectories of the air masses also indicated that pollutants from surrounding provinces in particular,contributed to the higher PM_(2.5)concentration.     

Estimation of daily PM2.5 concentration and its relationship with meteorological conditions in Beijing

When investigating the impact of air pollution on health, particulate matter less than 2.5 μm in aerodynamic diameter(PM_(2.5)) is considered more harmful than particulates of other sizes. Therefore, studies of PM_(2.5) have attracted more attention. Beijing, the capital of China,is notorious for its serious air pollution problem, an issue which has been of great concern to the residents, government, and related institutes for decades. However, in China,significantly less time has been devoted to observing PM_(2.5) than for PM_(10). Especially before 2013, the density of the PM_(2.5) ground observation network was relatively low, and the distribution of observation stations was uneven. One solution is to estimate PM_(2.5) concentrations from the existing data on PM_(10). In the present study, by analyzing the relationship between the concentrations of PM_(2.5) and PM_(10), and the meteorological conditions for each season in Beijing from 2008 to 2014, a U-shaped relationship was found between the daily maximum wind speed and the daily PM concentration, including both PM_(2.5) and PM_(10). That is, the relationship between wind speed and PM concentration is not a simple positive or negative correlation in these wind directions; their relationship has a complex effect, with higher PM at low and high wind than for moderate winds.Additionally, in contrast to previous studies, we found that the PM_(2.5)/PM_(10) ratio is proportional to the mean relative humidity(MRH). According to this relationship, for each season we established a multiple nonlinear regression(MNLR) model to estimate the PM_(2.5) concentrations of the missing periods.     

Process analysis of PM2.5 pollution events in a coastal city of China using CMAQ

US EPA's Community Multiscale Air Quality modeling system(CMAQ) with Process Analysis tool was used to simulate and quantify the contribution of individual atmospheric processes to PM_(2.5) concentration in Qingdao during three representative PM_(2.5) pollution events in the winter of 2015 and 2016. Compared with the observed surface PM_(2.5) concentrations, CMAQ could reasonably reproduce the temporal and spatial variations of PM_(2.5) during these three events. Process analysis results show that primary emissions accounted for 72.7%–93.2% of the accumulation of surface PM_(2.5) before and after the events.When the events occurred, primary emissions were still the major contributor to the increase of PM_(2.5) in Qingdao, however the contribution percentage reduced significantly,which only account for 51.4%–71.8%. Net contribution from horizontal and vertical transport to the accumulation of PM_(2.5) was also positive and its percentage increased when events occurred. Only 1.1%–4.6% of aerosol accumulation was due to PM processes and aqueous chemical processes before and after events. When the events occurred,contribution from PM processes and aqueous chemistry increased to 6.0%–11.8%. Loss of PM_(2.5) was mainly through horizontal transport, vertical transport and dry deposition, no matter during or outside the events. Wet deposition would become the main removal pathway of PM_(2.5), when precipitation occurred.     

Modeling study on the roles of the deposition and transport of PM2.5 in air quality changes over central-eastern China

The role of PM_2.5 (particles with aerodynamic diameters ≤ 2.5 µm) deposition in air quality changes over China remains unclear. By using the three-year (2013, 2015, and 2017) simulation results of the WRF/CUACE v1.0 model from a previous work (Zhang et al., 2021), a non-linear relationship between the deposition of PM_2.5 and anthropogenic emissions over central-eastern China in cold seasons as well as in different life stages of haze events was unraveled. PM_2.5 deposition is spatially distributed differently from PM_2.5 concentrations and anthropogenic emissions over China. The North China Plain (NCP) is typically characterized by higher anthropogenic emissions compared to southern China, such as the middle-low reaches of Yangtze River (MLYR), which includes parts of the Yangtze River Delta and the Midwest. However, PM_2.5 deposition in the NCP is significantly lower than that in the MLYR region, suggesting that in addition to meteorology and emissions, lower deposition is another important factor in the increase in haze levels. Regional transport of pollution in central-eastern China acts as a moderator of pollution levels in different regions, for example by bringing pollution from the NCP to the MLYR region in cold seasons. It was found that in typical haze events the deposition flux of PM_2.5 during the removal stages is substantially higher than that in accumulation stages, with most of the PM_2.5 being transported southward and deposited to the MLYR and Sichuan Basin region, corresponding to a latitude range of about 24°N-31°N.     

Size-resolved carbonaceous components and water-soluble ions measurements of ambient aerosol in Beijing

A MOUDI-120 sampler was used in Beijing to collect multi-stage samples in the summer and winter of 2013 to 2015. Thirty-three sample sets were collected during the daytime,nighttime, and different pollution levels. The actual relative humidity in the impactors was calculated for the first time. The carbonaceous components(organic and elemental carbon,OC and EC, respectively) and water-soluble inorganic ions(Na~+, NH_4~+, K~+, Mg~(2+), Ca~(2+), Cl~-, NO_3~-,and SO_4~(2-)) were analyzed in each sample. The characteristics of the mass concentration distribution and charge balance were discussed. On the basis of relative humidity in the impactors, aerosols less than 1.0 μm were sampled under relatively dry conditions in most cases. The concentration levels for the chemical species were higher in the winter than in the summer. Three modes(condensation mode, droplet mode, and coarse mode) could be identified from the distributions of NH_4~+, NO_3~-, SO_4~(2-), Cl~-, K~+, OC and EC. The distribution characteristics for the pollution dissipation process were different from the pollution accumulation process. NO_3~-and NO_2~-contributed most of the negative electric charges in the stage below 0.1 μm. In the condensation mode, the cations were dominated by NH_4~+, which was sufficient to balance the anions. In the droplet mode of the heavily polluted samples,the ammonium was not sufficient to balance the anions. In the coarse mode, the positive electric charges were primarily composed of metal cations. The analyzed anions were not sufficient to neutralize the measured cations.     

Spatial and temporal variations of water quality in Cao-E River of eastern China

Evaluation and analysis of water quality variations were performed with integrated consideration of water quality parameters, hydrological-meteorologic and anthropogenic factors in Cao-E River, Zhejiang Province of China. Cao-E River system has been polluted and the water quality of some reaches are inferior to Grade V according to National Surface Water Quality Standard of China （GB2002）. However, mainly polluted indices of each tributary and mainstream are different. Total nitrogen （TN） and total phosphorus （TP） in the water are the main polluted indices for mainstream that varies from 1.52 to 45.85 mg/L and 0.02 to 4.02 mg/L, respectively. TN is the main polluted indices for Sub-watershed Ⅰ, Ⅱ, Ⅳ and Ⅴ（0.76 to 18.27 mg/L）. BOD5 （0.36 to 289.5 mg/L）, CODMn （0.47 to 78.86 mg/L）, TN （0.74 to 31.09 mg/L） and TP （0 to 3.75 mg/L） are the main polluted indices for Sub-watershed Ⅲ. There are tow pollution types along the river including nonpoint source pollution and point source pollution types. Remarkably temporal variations with a few spatial variations occur in nonpoint pollution type reaches （including mainstream, Sub-watershed Ⅰ and Ⅱ） that mainly drained by arable field and/or dispersive rural dwelling district, and the maximum pollutant concentration appears in flooding seasons. It implied that the runoff increases the pollutant concentration of the water in the nonpoint pollution type reaches. On the other hand, remarkably spatial variations occur in the point pollution type reaches （include Sub-watershed Ⅲ, Ⅳ and Ⅴ） and the maximum pollutant concentration appears in urban reaches. The runoff always decreases the pollutant concentration of the river water in the seriously polluted reaches that drained by industrial point sewage. But for the point pollution reaches resulted from centralized town domestic sewage pipeline and from frequent shipping and digging sands, rainfall always increased the concentration of pollutant （TN） in the river water too. Pollution controls were respectively suggested for these tow types according to different pollution causes.     

Urban air quality, meteorology and traffic linkages: Evidence from a sixteen-day particulate matter pollution event in December 2015, Beijing

A heavy 16-day pollution episode occurred in Beijing from December 19, 2015 to January 3,2016. The mean daily AQI and PM_(2.5) were 240.44 and 203.6 μg/m~3. We analyzed the spatiotemporal characteristics of air pollutants, meteorology and road space speed during this period, then extended to reveal the combined effects of traffic restrictions and meteorology on urban air quality with observational data and a multivariate mutual information model. Results of spatiotemporal analysis showed that five pollution stages were identified with remarkable variation patterns based on evolution of PM_(2.5) concentration and weather conditions. Southern sites(DX, YDM and DS) experienced heavier pollution than northern ones(DL, CP and WL). Stage P2 exhibited combined functions of meteorology and traffic restrictions which were delayed peak-clipping effects on PM_(2.5).Mutual information values of Air quality–Traffic–Meteorology(ATM–MI) revealed that additive functions of traffic restrictions, suitable relative humidity and temperature were more effective on the removal of fine particles and CO than NO_2.