Association of emergency room visits for respiratory diseases with sources of ambient PM2.5

Previous studies have reported associations of short-term exposure to different sources of ambient fine particulate matter(PM_(2.5)) and increased mortality or hospitalizations for respiratory diseases. Few studies, however, have focused on the short-term effects of source-specific PM_(2.5) on emergency room visits(ERVs) of respiratory diseases. Source apportionment for PM_(2.5) was performed with Positive Matrix Factorization(PMF) and generalized additive model was applied to estimate associations between source-specific PM_(2.5) and respiratory disease ERVs. The association of PM_(2.5) and total respiratory ERVs was found on lag4(RR = 1.011, 95%CI: 1.002, 1.020) per interquartile range(76 μg/m~3) increase.We found PM_(2.5) to be significantly associated with asthma, bronchitis and chronic obstructive pulmonary disease(COPD) ERVs, with the strongest effects on lag5(RR = 1.072,95%CI: 1.024, 1.119), lag4(RR = 1.104, 95%CI: 1.032, 1.176) and lag3(RR = 1.091, 95%CI: 1.047,1.135), respectively. The estimated effects of PM_(2.5) changed little after adjusting for different air pollutants. Six primary PM_(2.5) sources were identified using PMF analysis, including dust/soil(6.7%), industry emission(4.5%), secondary aerosols(30.3%), metal processing(3.2%),coal combustion(37.5%) and traffic-related source(17.8%). Some of the sources were identified to have effects on ERVs of total respiratory diseases(dust/soil, secondary aerosols, metal processing, coal combustion and traffic-related source), bronchitis ERVs(dust/soil) and COPD ERVs(traffic-related source, industry emission and secondary aerosols). Different sources of PM_(2.5) contribute to increased risk of respiratory ERVs to different extents, which may provide potential implications for the decision making of air quality related policies, rational emission control and public health welfare.     

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.     

Exposure to air pollutants in Vietnam: Assessing potential risk for tourists

Tourism can form an important component of a nation's GDP,and Vietnam is among the most visited countries in Southeast Asia.Most studies on personal exposure focus on the general population,or occupational cohorts with exposure to specific pollutants.However,short-term exposure to air pollutants while visiting regions with high levels of air pollution can lead to acute health effects.A personal exposure study was conducted across three cities in Vietnam to estimate exposure to particulate matter(PM_(2.5)) and black carbon for tourists.Measurements were conducted during the wet season in 2014 in Ho Chi Minh City,Da Lat and Nha Trang using portable instrumentation.Average 24-hr PM_(2.5) and BC exposures were estimated as 18.9 ± 9.24 and 3.41 ± 1.33 μg/m~3 and among the three cities,Ho Chi Minh was found to have the highest PM_(2.5) concentrations.Environmental tobacco smoke,commuting and street food stands were found to contribute to highest levels of exposure to PM_(2.5) and BC across all cities.     

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing–Tianjin–Hebei region, China

In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of population and emissions vary greatly,we simulated the air quality benefit based on Ben MAP to satisfy the Action Plan.In this study,we estimate PM_(2.5) concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1 × 1 km~2.Combined with the exposure-response function between PM_(2.5) concentration and health endpoints,health effects of PM_(2.5) exposure are analyzed.The economic loss is assessed by using the willingness to pay(WTP) method and human capital(HC) method.When the PM_(2.5) concentration falls by 25% in BTH and reached 60 μg/m~3 in Beijing,the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year.Of the estimated mortality attributable to all causes,3117 annual deaths were due to lung cancer,1924 – 6318 annual deaths were due to cardiovascular,and343 – 1697 annual deaths were due to respiratory.Based on WTP,the estimated monetary values for the avoided cases of all cause mortality,cardiovascular mortality,respiratory mortality and lung cancer ranged from 1110 to 29632,673 to 13325,120 to 3579,1091 to 6574 million yuan,respectively.Based on HC,the corresponding values for the avoided cases of these four mortalities were 267 to 1178,161 to 529,29 to 143 and 261 million yuan,respectively.     

An economic assessment of the health effects and crop yield losses caused by air pollution in mainland China

Air pollution is severe in China, and pollutants such as PM_(2.5) and surface O_3 may cause major damage to human health and crops, respectively. Few studies have considered the health effects of PM_(2.5) or the loss of crop yields due to surface O_3 using model-simulated air pollution data in China. We used gridded outputs from the WRF-Chem model, high resolution population data, and crop yield data to evaluate the effects on human health and crop yield in mainland China. Our results showed that outdoor PM_(2.5) pollution was responsible for 1.70–1.99 million cases of all-cause mortality in 2006. The economic costs of these health effects were estimated to be 151.1–176.9 billion USD, of which 90% were attributed to mortality. The estimated crop yield losses for wheat, rice, maize, and soybean were approximately 9, 4.6, 0.44, and 0.34 million tons, respectively, resulting in economic losses of 3.4 billion USD. The total economic losses due to ambient air pollution were estimated to be 154.5–180.3 billion USD, accounting for approximately 5.7%–6.6% of the total GDP of China in 2006. Our results show that both population health and staple crop yields in China have been significantly affected by exposure to air pollution. Measures should be taken to reduce emissions, improve air quality, and mitigate the economic loss.     

Typical atmospheric haze during crop harvest season in northeastern China: A case in the Changchun region

This study presents the mass concentrations of PM_(2.5),O_3,SO_2 and NOxat one urban,one suburban and two rural locations in the Changchun region from September 25 to October 272013. Major chemical components of PM_(2.5)at the four sites were daily sampled and analyzed. Most of daily concentrations of SO_2(7–82 μg/m~3),O_3(27–171 μg/m~3) and NOx(14–213 μg/m~3) were below the limits of the National Ambient Air Quality Standard(NAAQS)in China. However,PM_(2.5)concentrations(143–168 μg/m~3) were 2-fold higher than NAAQS.Higher PM_(2.5)concentrations(~ 150 μg/m~3) were measured during the pre-harvest and harvest at the urban site,while PM_(2.5)concentrations significantly increased from 250 to400 μg m~(-3) at suburban and rural sites with widespread biomass burning. At all sites,PM_(2.5)components were dominated by organic carbon(OC) and followed by soluble component sulfate(SO_4~(2-)),ammonium(NH_4~+) and nitrate(NO_3~-). Compared with rural sites,urban site had a higher mineral contribution and lower potassium(K~+and K) contribution to PM_(2.5).Severe atmospheric haze events that occurred from October 21 to 23 were attributed to strong source emissions(e.g.,biomass burning) and unfavorable air diffusion conditions.Furthermore,coal burning originating from winter heating supply beginning on October 18 increased the atmospheric pollutant emissions. For entire crop harvest period,the Positive Matrix Factorization(PMF) analysis indicated five important emission contributors in the Changchun region,as follows: secondary aerosol(39%),biomass burning(20%),supply heating(18%),soil/road dust(14%) and traffic(9%).     

Characterization of personal exposure concentration of fine particles for adults and children exposed to high ambient concentrations in Beijing, China

In China, the health risk from overexposure to particles is becoming an important public health concern. To investigate daily exposure characteristics to PM 2.5 with high ambient concentration in urban area, a personal exposure study was conducted for school children, and office workers in Beijing, China. For all participants (N = 114), the mean personal 24-hr exposure concentration was 102.5, 14.7, 0.093, 0.528, 0.934, 0.174 and 0.703 μg/m 3 for PM 2.5 , black carbon, Mn, Al, Ca, Pb, and Fe. Children's exposure concentrations of PM 2.5 were 4-5 times higher than those in related studies. The ambient concentration of PM 2.5 (128.5 μg/m 3 ) was significantly higher than the personal exposure concentration (P 0.05), and exceed the reference concentration (25 μg/m 3 ) of WHO air quality guideline. Good correlation relationships and significant differences were identified between ambient concentration and personal exposure concentration. The relationships indicate that the ambient concentration is the main factor influencing personal exposure concentration, but is not a good indicator of personal exposure concentration. Outdoor activities (commute mode, exposure to heating, workday or weekend travel) influenced personal exposure concentrations significantly, but the magnitude of the influence from indoor activities (exposure to cooking) was masked by the high ambient concentrations.     

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.     

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.     

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.     

Design and demonstration of a next-generation air quality attainment assessment system for PM2.5 and O3

Due to the increasingly stringent standards, it is important to assess whether the proposed emission reduction will result in ambient concentrations that meet the standards. The Software for Model Attainment Test—Community Edition(SMAT-CE) is developed for demonstrating attainment of air quality standards of O3 and PM2.5. SMAT-CE improves computational efficiency and provides a number of advanced visualization and analytical functionalities on an integrated GIS platform. SMAT-CE incorporates historical measurements of air quality parameters and simulated air pollutant concentrations under a number of emission inventory scenarios to project the level of compliance to air quality standards in a targeted future year. An application case study of the software based on the U.S. National Ambient Air Quality Standards(NAAQS) shows that SMAT-CE is capable of demonstrating the air quality attainment of annual PM2.5and 8-hour O3 for a proposed emission control policy.     

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.     

Spatial and temporal variation of particulate matter and gaseous pollutants in 26 cities in China

O3and PM2.5were introduced into the newly revised air quality standard system in February 2012, representing a milestone in the history of air pollution control, and China's urban air quality will be evaluated using six factors(SO2, NO2, O3, CO, PM2.5and PM10) from the beginning of 2013. To achieve the new air quality standard, it is extremely important to have a primary understanding of the current pollution status in various cities. The spatial and temporal variations of the air pollutants were investigated in 26 pilot cities in China from August 2011 to February 2012, just before the new standard was executed. Hourly averaged SO2, NO2and PM10were observed in 26 cities, and the pollutants O3, CO and PM2.5were measured in 15 of the 26 cities. The concentrations of SO2and CO were much higher in the cities in north China than those in the south. As for O3and NO2, however, there was no significant diference between northern and southern cities. Fine particles were found to account for a large proportion of airborne particles, with the ratio of PM2.5to PM10ranging from 55% to 77%. The concentrations of PM2.5(57.5 μg/m3) and PM10(91.2 μg/m3) were much higher than the values(PM2.5: 11.2 μg/m3; PM10 : 35.6 μg/m3) recommended by the World Health Organization. The attainment of the new urban air quality standard in the investigated cities is decreased by 20% in comparison with the older standard without considering O3, CO and PM2.5, suggesting a great challenge in urban air quality improvement, and more eforts will to be taken to control air pollution in China.     

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.     

PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) in Beijing: Seasonal variations, sources, and risk assessment

Polycyclic aromatic hydrocarbons(PAHs) have been of health concern due to its carcinogenesis and mutagenesis. In this study, we aimed to assess the variations, sources, and lifetime excessive cancer risk(ECR) attributable to PAHs bound to ambient particulate matters with aerodynamic diameter less than 2.5 μm(PM_(2.5)) in metropolitan Beijing, China. We collected24-hour integrated PM_(2.5) samples on daily basis between November 2014 and June 2015 across both central heating(cold months) and non-heating(warm months) seasons, and further analyzed the PAH components in these daily PM_(2.5) samples. Our results showed that total concentrations of PM_(2.5)-bound PAHs varied between(88.6 ± 75.4) ng/m~3 in the cold months and(11.0 ± 5.9) ng/m~3 in the warm months. Benzo[a]pyrene(Ba P), the carcinogenic marker of PAHs,averaged at 5.7 and 0.4 ng/m~3 in the cold and warm months, respectively. Source apportionment analyses illustrated that gasoline, biomass burning, diesel, coal combustion and cooking were the major contributors, accounting for 12.9%, 17.8%, 24.7%, 24.3% and 6.4% of PM_(2.5)-bound PAHs, respectively. The BaP equivalent lifetime ECR from inhalation of PM_(2.5)-bound PAHs was 16.2 cases per million habitants. Our results suggested that ambient particulate reduction from energy reconstruction and adaption of clean fuels would result in reductions PM_(2.5)-bound PAHs and its associated cancer risks. However, as only particulate phased PAHs was analyzed in the present study, the concentration of ambient PAHs could be underestimated.     

Large inter annual variation in air quality during the annual festival ‘Diwali' in an Indian megacity

A network of air quality and weather monitoring stations was established under the System of Air Quality Forecasting and Research(SAFAR) project in Delhi. We report observations of ozone(O_3), nitrogen oxides(NO_x), carbon monoxide(CO) and particulate matter(PM_2.5and PM_(10)) before, during and after the Diwali in two consecutive years, i.e., November 2010 and October 2011. The Diwali days are characterised by large firework displays throughout India. The observations show that the background concentrations of particulate matter are between 5 and 10 times the permissible limits in Europe and the United States. During the Diwali-2010, the highest observed PM_(10) and PM_2.5mass concentration is as high as2070 μg/m~3 and 1620 μg/m3, respectively(24 hr mean), which was about 20 and 27 times to National Ambient Air Quality Standards(NAAQS). For Diwali-2011, the increase in PM_(10) and PM_2.5mass concentrations was much less with their peaks of 600 and of 390 μg/m~3 respectively, as compared to the background concentrations. Contrary to previous reports,firework display was not found to strongly influence the NO_x, and O_3 mixing ratios, with the increase within the observed variability in the background. CO mixing ratios showed an increase. We show that the large difference in 2010 and 2011 pollutant concentrations is controlled by weather parameters.     

Arsenic species in electronic cigarettes: Determination and potential health risk

Human exposure to contaminants from electronic cigarettes(e-cigarettes) and the associated health effects are poorly understood.There has been no report on the speciation of arsenic in e-liquid(solution used for e-cigarettes) and aerosols.We report here determination of arsenic species in e-liquids and aerosols generated from vaping the e-liquid.Seventeen e-liquid samples of major brands,purchased from local and online stores in Canada and China,were analyzed for arsenic species using high-performance liquid chromatography and inductively coupled plasma mass spectrometry.Aerosols condensed from vaping the eliquids were also analyzed and compared for arsenic species.Six arsenic species were detected,including inorganic arsenate(iAs~Ⅴ),arsenite(iAs~Ⅲ),monomethylarsonic acid(MMA),and three new arsenic species not reported previously.In e-liquids,iAs~Ⅲ was detected in 59%,iAs~Ⅴ in 94%,and MMA in 47% of the samples.In the condensate of aerosols from vaping the e-liquids,iAs~Ⅲ was detected in 100%,iAsv in 88%,and MMA in 13% of the samples.Inorganic arsenic species were predominant in e-liquids and aerosols of e-cigarettes.The concentration of iAs~Ⅲ in the condensate of aerosols(median 3.27 μg/kg) was significantly higher than that in the e-liquid(median 1.08 μg/kg) samples.The concentration of inorganic arsenic in the vaping air was approximately 3.4 μg/m~3,which approaches to the permissible exposure limit(10 μg/m~3) set by the United States Occupational Safety and Health Administration(OSHA).According to the Environmental Protection Agency's unit risk factor(4.3 × 10~(-3) per μg/m~3) for inhalation exposure to inorganic arsenic in the air,the estimated excess lung cancer risk from lifetime exposure to inorganic arsenic in the ecigarette vaping air(3.4 μg/m~3),assuming e-cigarette vaping at 1% of the time,is as high as1.5 × 10~(-4).These results raise health concerns over the exposure to arsenic from electronic cigarettes.     

Temporal variability of atmospheric particulate matter and chemical composition during a growing season at an agricultural site in northeastern China

This study presents the observations of PM_(10) and PM_(2.5) concentrations at an agricultural site from April to October 2012 in Dehui city,China.Ambient air was sampled by filter-based samplers and online PM monitors.The filter samples were analyzed to determine the abundance of ionic/inorganic elements,organic carbon(OC) and elemental carbon(EC).The daily PM_(10) concentrations varied significantly over the monitoring period,with an average of168 ± 63(in the range of 52-277) μg/m~3 during the land preparation/planting period(26 April-15 June),85 ± 65(36-228) μg/m~3 during the growing season(16 June-25 September),and 207 ±88(103-310) μg/m~3 during the harvest period(26 September-31 October).PM_(2.5) accounted for44%,56%and 66%of atmospheric PM_(10) during these periods,respectively.The PM_(10) diurnal variation showed a distinct peak from 16:00 to 21:00(LST) during the growing and harvesting seasons,while a gradual increase throughout the daytime until 17:00 was observed during tilling season.Mineral dust elements(Al,Ca,Fe,and Mg) dominated the PM_(10) chemical composition during the tilling season;OC,NO_3~-,SO_4~(2-) and NH_4~+ during the growing season;and carbonaceous species(i.e.,OC and EC) during the harvesting season.Our results indicate that the soil particles emitted by farm tillage and organic matter released from straw burning are the two most significant sources of PM_(10) emissions contributing to the recurring high pollution events in this region.Therefore,development of agricultural PM inventories from soil tillage and straw burning is prioritized to support air quality modeling.     

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.     

A framework for investigating the air quality variation characteristics based on the monitoring data: Case study for Beijing during 2013–2016

In this study, an analysis framework based on the regular monitoring data was proposed for investigating the annual/inter-annual air quality variation and the contributions from different factors(i.e., seasons, pollution periods and airflow directions), through a case study in Beijing from 2013 to 2016. The results showed that the annual mean concentrations(MC) of PM_(2.5), SO_2, NO_2 and CO had decreased with annual mean ratios of 7.5%, 28.6%, 4.6%and 15.5% from 2013 to 2016, respectively. Among seasons, the MC in winter contributed the largest fractions(25.8%～46.4%) to the annual MC, and the change of MC in summer contributed most to the inter-annual MC variation(IMCV) of PM_(2.5) and NO2. For different pollution periods, gradually increase of frequency of S-1(PM_(2.5), 0～ 75 μg/m~3) made S-1 become the largest contributor(28.8%) to the MC of PM_(2.5) in 2016, it had a negative contribution(-13.1%) to the IMCV of PM_(2.5); obvious decreases of frequencies of heavily polluted and severely polluted dominated(44.7% and 39.5%) the IMCV of PM_(2.5). For different airflow directions, the MC of pollutants under the south airflow had the most significant decrease(22.5%～62.5%), and those decrease contributed most to the IMCV of PM_(2.5)(143.3%),SO2(72.0%), NO_2(55.5%) and CO(190.3%); the west airflow had negative influences to the IMCV of PM_(2.5), NO_2 and CO. The framework is helpful for further analysis and utilization of the large amounts of monitoring data; and the analysis results can provide scientific supports for the formulation or adjustment of further air pollution mitigation policy.