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.     

Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania: Effects of varying source profiles and seasonal trends in ambient marker concentrations

We present estimates of the vehicular contribution to ambient organic carbon (OC) and fine particle mass (PM) in Pittsburgh, PA using the chemical mass balance (CMB) model and a large dataset of ambient molecular marker concentrations. Source profiles for CMB analysis are selected using a method of comparing the ambient ratios of marker species with published profiles for gasoline and diesel vehicle emissions. The ambient wintertime data cluster on a hopanes/EC ratio–ratio plot, and therefore can be explained by a large number of different source profile combinations. In contrast, the widely varying summer ambient ratios can be explained by a more limited number of source profile combinations. We present results for a number of different CMB scenarios, all of which perform well on the different statistical tests used to establish the quality of a CMB solution. The results illustrate how CMB estimates depend critically on the marker-to-OC and marker-to-PM ratios of the source profiles. The vehicular contribution in the winter is bounded between 13% and 20% of the ambient OC (274±56–416±72 ng-C m⁻³). However, variability in the diesel profiles creates uncertainty in the gasoline–diesel split. On an OC basis, one set of scenarios suggests gasoline dominance, while a second set indicates a more even split. On a PM basis, all solutions indicate a diesel-dominated split. The summer CMB solutions do not present a consistent picture given the seasonal shift and wide variation in the ambient hopanes-to-EC ratios relative to the source profiles. If one set of source profiles is applied to the entire dataset, gasoline vehicles dominate vehicular OC in the winter but diesel dominates in the summer. The seasonal pattern in the ambient hopanes-to-EC ratios may be caused by photochemical decay of hopanes in the summer or by seasonal changes in vehicle emission profiles.     

二次颗粒物源成分谱的建立在尘源解析中的作用

通过CMB模型计算各类尘源对TSP、PM10的影响时发现，二次颗粒物对尘源解析起到了不容忽视的作用，因此就二次颗粒物源成分谱进行了专门解析研究，并把二次颗粒物解析也纳入到模型中来，从而完善了源解析结果。     

Characteristics and source attribution of PM2.5 during 2016 G20 Summit in Hangzhou: Efficacy of radical measures to reduce source emissions

A field campaign was conducted to study the PM_2.5 and atmospheric gases and aerosol's components to evaluate the efficacy of radical measures implemented by the Chinese government to improve air quality during the 2016 G20 Summit in Hangzhou China. The lower level of PM_2.5 (32.48 ± 11.03 µg/m³) observed during the control period compared to pre-control and post-control periods showed that PM_2.5 was alleviated by control policies. Based on the mass concentrations of particulate components, the emissions of PM_2.5 from local sources including fossil fuel, coal combustion, industry and construction were effectively reduced, but non-exhaust emission was not reduced as effectively as expected. The accumulation of SNA (SO₄^2?, NO₃^?, NH₄⁺) was observed during the control period, due to the favourable synoptic weather conditions for photochemical reactions and heterogeneous hydrolysis. Because of transboundary transport during the control period, air masses from remote areas contributed significantly to local PM_2.5. Although, secondary organic carbon (OC_sec) exhibited more sensitivity than primary organic carbon (OC_pri) to control measures, and the increased nitrogen oxidation ratio (NOR) implied the regional transport of aged secondary aerosols to the study area. Overall, the results from various approaches revealed that local pollution sources were kept under control, indicating that the implementation of mitigation measures were helpful in improving the air quality of Hangzhou during G20 summit. To reduce ambient levels of PM_2.5 further in Hangzhou, regional control policies may have to be taken so as to reduce the impact of long-range transport of air masses from inland China.     

北京市大气细颗粒物PM2.5的来源研究

2000-2001年在北京联合大学化学学院、中国预防科学研究院和中国环境科学研究院3个采样点采集北京市PM2.5样品,并对其中无机元素、阴阳离子、有机碳(OC)、元素碳(EC)和有机物进行测定.以多环芳烃和部分无机组分为示踪物,利用CMB受体模型对PM2.5来源进行解析.结果表明,北京市PM2.5的主要来源为燃煤、扬尘、机动车排放、建筑尘、生物质燃烧、二次硫酸盐和硝酸盐及有机物.污染源贡献率随地域变化不大,燃煤、扬尘、生物质燃烧、二次硫酸盐和硝酸盐随季节变化比较明显.与1989-1990年解析结果相比,10年间PM2.5来源发生了一定变化.      

南京市可吸入颗粒物（PM10）来源解析研究

基于《南京市环境空气中可吸入颗粒物（PM10）源解析及控制对策研究》课题研究成果,课题于2004年-2005年间共采集了197个源和受体样品,每个样品分析测试了三类化学元素,采用化学质量平衡（CMB）模型解析南京市环境空气中可吸入颗粒物的来源,其中48%来源于扬尘、土壤尘等开放源类。研究认为扬尘等开放源类是南京市可吸入颗粒物污染的首要因素。     

珠江三角洲大气细颗粒物的致癌风险及源解析

于2004年4、7、10月和2005年1月对广州、深圳大气细颗粒物(PM2.5)中17种多环芳烃(PAHs)的浓度进行了分析,以苯并[a]芘(BaP)为毒性参照物的致癌毒性当量浓度(BaPeq),通过线性剂量-反应模型计算了呼吸致癌风险水平,结合源排放谱和化学质量平衡受体模型(CMB),研究了对致癌风险的各排放源贡献.结果表明,PAHs的浓度为5.87~63.36ng/m3,平均浓度深圳为32.68 ng/m3,广州为28.15ng/m3,且呈冬高夏低的分布规律.BaP和BaPeq日均超标率达到2.78%和5.56%,相对于WHO的日均标准的超标率达到50.0%和61.1%.该地区呼吸致癌风险平均水平为1×10-6~1×10-5,高于日常活动所致风险,低于引起关注的最低风险值.共解析出3种OC及致癌风险的排放源,分别为燃煤排放、机动车排放、生物质燃烧,其中燃煤排放和生物质燃烧贡献最大,对OC及BaPeq的贡献呈现相似规律.     

徐州市城市大气中的PAHs来源解析

采用化学质量平衡模型（CMB）对徐州市大气颗粒物中的多环芳烃（PAHs）进行来源分析,从而来确定各个源对大气的PAHs贡献值。主要通过利用大流量采样器配置PM10切割头在冬季和夏季对不同功能区,即生活区、工业区和旅游区采样大气中的可吸入颗粒物（PM10）样品,并用高效液相色谱法（HPLC）重点分析和研究了美国环保局（EPA）列出的16种PHAS优先污染物。研究结果表明：徐州市PM10污染比较严重,PM10污染质量浓度水平冬季是（288.81μg·m-3）大于夏季（276.34μg·m-3）,特别是工业区,污染数值达到393.13μg·m-3。夏季的总PAHs质量浓度为22.89 ng·m-3,分别是生活区28.35 ng·m-3、工业区21.75 ng·m-3和旅游区18.58 ng·m-3。冬季的总PAHs质量浓度为306.29 ng·m-3,分别是工业区388.03 ng·m-3、生活区276.29 ng·m-3和旅游区254.28 ng·m-3。夏季和冬季情况下,旅游区的污染相对来说都是最低的PM10中多环芳烃的源解析结果为,煤烟尘污染源的全年贡献率为64.00%,冬季煤烟尘污染源的贡献率为66.51%,夏季煤烟尘污染源的贡献率为57.21%,说明煤烟尘是PM10中多环芳烃的主要贡献源,土壤尘次之,全年贡献率为24.90%,冬季为25.48%,夏季为28.97%,因此,扬尘和烟煤尘的污染是徐州市的PM10中PAHs的最主要来源。     

太原市环境空气中TSP和PM_(10)来源解析

2001年到2002年,在太原市5个采样点分别采集了环境空气中的总悬浮颗粒物(TSP)和可吸入颗粒物(PM10)。用化学质量平衡模型和二重源解析技术解析了TSP和PM10的来源,结果表明,各主要源类对TSP的分担率依次为燃煤尘28%、扬尘24%、建筑水泥尘14%、硫酸盐10%、机动车尾气尘10%、土壤风沙尘5%、钢铁尘4%、硝酸盐4%、其它1%;对PM10的分担率依次为扬尘30%、燃煤尘18%、机动车尾气尘15%、硫酸盐11%、土壤风沙尘9%、建筑水泥尘7%、硝酸盐4%、其它1%。     

重庆主城区大气PM10及PM2.5来源解析

为探讨重庆主城区4个季节大气PM₁₀和PM_2.5的主要来源,于2012年2—12月在重庆主城区的工业区、文教区和居住区5个环境监测点同步采集PM₁₀及PM_2.5样品,分析了无机元素、水溶性离子、有机碳和元素碳含量及其分布特征. 采集了重庆主城区土壤尘、建筑水泥尘、扬尘、移动源(包括机动车、施工机械及船舶)、工业源(包括固定燃烧源及工业工艺过程源)、生物质燃烧源及餐饮源等7类污染源,建立了重庆市本地化的污染源成分谱库. 利用CMB(化学质量平衡)受体模型及二重源解析技术分析了PM₁₀及PM_2.5的来源. 结果表明:重庆主城区大气中ρ(PM₁₀)及ρ(PM_2.5)的年均值分别为153.2和113.1 μg/m3,超过GB 3095—2012《环境空气质量标准》二级标准限值2倍以上. 大气PM₁₀的主要来源为扬尘、二次粒子和移动源(贡献率分别为23.9%、23.5%和23.4%),大气PM_2.5主要来源于二次粒子和移动源(贡献率分别为30.1%和27.9%).PM₁₀和PM_2.5的主要源类贡献率差别不大,表明研究区域内大气颗粒物污染控制应采取多源控制原则. 大气PM₁₀来源的季节性变化特征表现为春季和秋季主要以扬尘为主、夏季和冬季主要以二次粒子为主.