山西省武乡县城大气PM2.5痕量重金属的生态和健康风险分析

为了解山西省武乡县城大气PM_(2.5)污染特征及PM_(2.5)中痕量重金属的生态和健康风险,在分析县城环境空气质量状况的基础上,分别于秋季(2014-10-22~2014-11-19)和冬季(2015-01-12~2015-02-13)在武乡县环境保护局楼顶用中流量采样器采集大气PM_(2.5)样品,每天换膜一次,利用称重法计算PM_(2.5)浓度,运用电感耦合等离子体原子发射光谱仪(ICP-AES)测定样品中As、Cd、Cr、Cu、Ni、Pb、Zn 7种元素含量,运用地累积指数法、生态风险指数法、相关性分析和主成分分析、美国环保署暴露模型等表征痕量重金属的污染程度、来源、潜在的生态和健康风险等.结果表明,冬季大气PM_(2.5)浓度是秋季的3倍左右,有65%的天数超过国家环境空气质量二级标准(GB 3095-2012);PM_(2.5)中痕量重金属来源主要包括燃煤和交通等人为源,贡献率分别为58.38%和18.73%,所测重金属浓度顺序为CuZnPbCrAsNiCd,其中Cd、Cu的生态风险指数、Cr的非致癌和致癌暴露风险大于其它金属.冬季燃煤增加和大气扩散条件差是武乡县城大气PM_(2.5)浓度超标以及造成痕量重金属生态和健康风险增大的主要原因.     

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 PM_2.5. 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 PM_2.5 and 8-hour O₃ for a proposed emission control policy.     

The comparison of source contributions from residential coal and low-smoke fuels,using CMB modeling,in South Africa

D-grade residential coal is being widely used as a fuel source for heating and cooking by most of the lower-income urban communities in South Africa. Emissions from residential coal combustion have been a major cause of elevated air pollution levels in the industrialized areas of South Africa. The adverse health effects resulting from exposure to residential coal combustion emissions have been a major public concern for many years. To address this, the Department of Minerals and Energy of South Africa conducted a macro-scale experiment in the township of Qalabotjha during the winter of 1997 to assess the technical and social benefits of combusting low-smoke fuels.This paper reports the PM_2.5 and PM₁₀ chemical mass-balance (CMB) source apportionment results from Qalabotjha during a 30-day sampling period, including a 10-day period when a large proportion of low-smoke fuels was combusted. Though emission rates of D-grade coal and low-smoke fuels may vary, their chemical abundances are too similar to be separated in CMB calculations. The source apportionment study confirmed that residential coal combustion is by far the greatest source of air pollution, accounting for 62.1% of PM_2.5 and 42.6% of PM₁₀ at the three Qalabotjha sites. Biomass burning is also a major source, accounting for 13.8% of PM_2.5 and 19.9% of PM₁₀. Fugitive dust is only significant in the coarse particle fraction, accounting for 11.3% of PM₁₀. Contributions from secondary ammonium sulfate are three–four times greater than from ammonium nitrate, accounting for 5–6% of PM mass. Minor contributions (less than 1%) were found for power plant fly ash, motor vehicle exhaust, and agricultural lime. Average PM_2.5 and PM₁₀ mass decreased by 20 and 25%, respectively, from the D-grade coal combustion period (days 1–10) to the majority of the low-smoke fuel period (days 11–20). Relative source contribution estimates (SCE) were quite similar among the three sampling periods for PM_2.5, and were quite different for PM₁₀ during the second period when 14% higher residential coal combustion and 9% lower biomass burning source contributions were found.     

郑州市冬季大气PM2.5传输路径和潜在源分析

针对郑州市2017年12月~2018年2月的冬季气象数据和大气污染物质量浓度在线监测数据,分析了气象条件对颗粒物浓度的影响.通过混合型单粒子拉格朗日综合轨迹(HYSPLIT)方法模拟了郑州市冬季48 h的气流后向轨迹,同时进行了聚类分析,并使用潜在源贡献因子(PSCF)方法和浓度权重轨迹(CWT)方法分析了郑州市冬季PM_(2.5)的潜在污染来源和不同潜在源区对郑州市大气PM_(2.5)浓度的贡献.结果表明,低风速、高湿度和较少的降水是造成颗粒物污染严重的重要气象因素;超过60%的后向轨迹来自西北方向,其次是来自京津地区的轨迹占比为25.6%,而来自南边和东边的轨迹只占7.5%和6.1%,但对应着较高的PM_(2.5)浓度;郑州市冬季PM_(2.5)的潜在源区主要是北部的京津冀传输通道城市,包括焦作、开封、新乡、鹤壁、濮阳、安阳、邯郸和邢台,此外,相邻省份包括山西省、湖北省和安徽省部分区域对郑州市大气PM_(2.5)污染水平也有着较大的影响和贡献.     

Variability of PM2.5 and O3 concentrations and their driving forces over Chinese megacities during 2018-2020

Recently,air pollution especially?ne particulate matters (PM_2.5) and ozone (O₃) has become a severe issue in China.In this study,we?rst characterized the temporal trends of PM_2.5and O₃for Beijing,Guangzhou,Shanghai,and Wuhan respectively during 2018-2020.The annual mean PM_2.5has decreased by 7.82%-33.92%,while O₃concentration showed insigni?cant variations by-6.77%-4.65%during 2018-2020.The generalized additive models (GAMs) were ...     

Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015

Trajectory clustering, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods were applied to investigate the transport pathways and identify potential sources of PM_2.5 and PM₁₀ in different seasons from June 2014 to May 2015 in Beijing. The cluster analyses showed that Beijing was affected by trajectories from the south and southeast in summer and autumn. In winter and spring, Beijing was not only affected by the trajectories from the south and southeast, but was also affected by trajectories from the north and northwest. In addition, the analyses of the pressure profile of backward trajectories showed that backward trajectories, which have important influence on Beijing, were mainly distributed above 970 hPa in summer and autumn and below 950 hPa in spring and winter. This indicates that PM_2.5 and PM₁₀ were strongly affected by the near surface air masses in summer and autumn and by high altitude air masses in winter and spring. Results of PSCF and CWT analyses showed that the largest potential source areas were identified in spring, followed by winter and autumn, then summer. In addition, potential source regions of PM₁₀ were similar to those of PM_2.5. There were a clear seasonal and spatial variation of the potential source areas of Beijing and the airflow in the horizontal and vertical directions. Therefore, more effective regional emission reduction measures in Beijing''s surrounding provinces should be implemented to reduce emissions of regional sources in different seasons.     

北京市大气污染减排潜力及居民健康效益评估

北京市能源消费正面临着污染物减排和保障居民健康的双重约束. 针对未来城市能源消费设计BAU(基准情景)和2个分别基于近期和中长期节能环保要求的受控情景(EC1、EC2),模拟预测了3个情景下主要大气污染物(SO₂、NO_x、PM₁₀、PM_2.5)在目标年(2020年)的排放水平,以确定大气污染减排潜力. 分别采用综合暴露-反应关系模型(IER)和泊松回归模型,评估北京市居民对PM_2.5暴露的健康风险,估算健康损失的经济价值. 结果表明:相较BAU情景,在EC1情景下, SO₂、NO_x、PM₁₀、PM_2.5减排率分别达到52.95%、49.77%、32.82%、41.41%,可减少PM_2.5暴露下居民死亡和发病219 783例,其中死亡1 295例、住院3 920例、门诊182 558例、患病32 011例,获得健康效益111.87×108元;在EC2情景下,SO₂、NO_x、PM₁₀、PM_2.5的减排率分别达到66.61%、63.42%、54.96%、57.44%,可减少PM_2.5暴露下居民死亡和发病519 234例,其中死亡2 930例、住院9 248例、门诊427 070例、患病79 986例,获得健康效益290.10×108元. 相较EC1情景,EC2情景可产生更大的减排潜力和居民健康效益. 从空间分布上来看,北京主城区因能源方案优化获得的健康效益较大,约占总健康经济效益的60%.      

2013年1月宁波市PM_(2.5)污染的形成过程与传输规律

为了深入认识宁波市冬季细颗粒物(PM2.5)的污染特征和主要影响因素的作用规律,利用Models-3/CMAQ模式系统对2013年1月宁波市的PM2.5污染形成过程进行了模拟分析.结果表明,宁波市PM2.5的重点污染区主要分布在市区、北部地区及东部沿海,除了受到局地污染源排放的影响外,对比非污染的情况,大气输入和气溶胶生成作用的增强是引起PM2.5污染的主导因素,其中水平传输过程对PM2.5浓度升高的贡献最为突出.气溶胶过程的贡献在近地面(0~80 m)最显著,随着高度升高而逐渐减弱.硝酸盐在局地二次生产的细颗粒物中占主要份额(~70%).对于硫酸盐,局地二次生成所占的比例很低,主要来自宁波局地排放和宁波以外地区的大气传输(贡献比例分别为44%和40%).宁波市的PM2.5污染主要受到来自北向沿岸气团(占比54%)、西北向大陆气团(占比21%)和西向局地气团(占比25%)的传输影响.在西北方向短距离区域传输的作用下PM2.5浓度最高;在我国中东部大范围灰霾天气的影响下,西北向和北向的长距离传输作用也会导致宁波地区的PM2.5污染.     

武汉地区秋冬季清洁与重污染过程的水溶性离子特征研究

利用武汉地区2014年秋、冬季在线离子色谱分析仪Marga监测所得的大气PM_(2.5)中水溶性离子数据和武汉市环境空气质量自动监测的细颗粒物数据,分析了武汉地区秋、冬季重污染和清洁过程的大气污染特征.结果表明,PM_(2.5)是武汉地区秋、冬季大气污染的首要污染物,无论是在清洁还是重污染过程中,NO_3~-、SO_4~(2-)和NH_4~+3种成分都是PM_(2.5)的主要无机成分.重污染过程中PM_(2.5)的平均浓度是清洁过程的4.5倍,而3种主要水溶性离子平均浓度增长至清洁过程的5~6倍,且有着显著的相关性,二次生成水溶性离子的污染已成为武汉秋、冬季大气污染的主要因素.Cl-在重污染过程中的浓度及与PM_(2.5)的相关系数显著增大,表明化石燃料燃烧等过程也对重污染的形成产生了较显著的作用,值得关注的是,K~+在重污染过程中的浓度及与PM_(2.5)的相关系数增大也验证了燃烧过程对重污染起到的贡献.硫氧化率和氮氧化率的分析结果表明,重污染过程中的二次转化要多于清洁过程,可能是非均相反应生成了二次污染的硫酸盐和硝酸盐.线性回归分析的方程系数研究表明,NH_4NO_3和(NH_4)_2SO_4可能是清洁和重污染过程中主要的盐类物质.NO_3~-/SO_4~(2-)的平均质量浓度比说明移动源对武汉地区秋、冬季二次污染的形成和发展已经起到越来越大的作用,特别是重污染过程中的影响更大.     

Moving towards ambitious climate policies: Monetised health benefits from improved air quality could offset mitigation costs in Europe

Air quality and related health effects are not only affected by policies directly addressed at air pollution but also by other environmental strategies such as climate mitigation. This study addresses how different climate policy pathways indirectly bear upon air pollution in terms of improved human health in Europe. To this end, we put in perspective mitigation costs and monetised health benefits of reducing PM_2.5 (particles less than 2.5 μm in diameter) and ozone concentrations.Air quality in Europe and related health impacts were assessed using a comprehensive modelling chain, based on global and regional climate and chemistry-transport models together with a health impact assessment tool. This allows capturing both the impact of climate policy on emissions of air pollutants and the geophysical impact of climate change on air quality.Results are presented for projections at the 2050 horizon, for a set of consistent air pollution and climate policy scenarios, combined with population data from the UN's World Population Prospects, and are expressed in terms of morbidity and mortality impacts of PM_2.5 and ozone pollution and their monetised damage equivalent.The analysis shows that enforcement of current European air quality policies would effectively reduce health impacts from PM_2.5 in Europe even in the absence of climate policies (life years lost from the exposure to PM_2.5 decrease by 78% between 2005 and 2050 in the reference scenario), while impacts for ozone depend on the ambition level of international climate policies. A move towards stringent climate policies on a global scale, in addition to limiting global warming, creates co-benefits in terms of reduced health impacts (68% decrease in life years lost from the exposure to PM_2.5 and 85% decrease in premature deaths from ozone in 2050 in the mitigation scenario relative to the reference scenario) and air pollution cost savings (77%) in Europe. These co-benefits are found to offset at least 85% of the additional cost of climate policy in this region.     

我国PM2.5与臭氧污染协同控制策略研究

近年来,我国大气污染格局发生了深刻变化,PM_2.5与臭氧（O₃）成为影响我国城市和区域空气质量的主要空气污染物,二者协同控制已成为我国空气质量改善的焦点和打赢蓝天保卫战的关键.PM_2.5与臭氧之间具有复杂的关联性,使得二者的协同控制具有复杂性与艰巨性.分析了PM_2.5与臭氧成因的关联性及其相互影响,阐明了PM_2.5与臭氧污染协同控制所涉及的重要科学问题,并在此基础上研究了目前我国PM_2.5与臭氧的污染形势及二者的关联性,梳理了我国自2013年以来在PM_2.5与臭氧污染控制中已采取的重要举措,论述了目前我国PM_2.5与臭氧协同控制在科学与管理上所面临的挑战.结合对国外成功经验的分析,提出推进我国PM_2.5与臭氧污染协同控制工作的相关建议:①加快监测能力建设,完善管理体系;②强化科技支撑,提高PM_2.5与臭氧污染控制精准性;③加快构建VOCs与NO_x治理技术体系;④加大VOCs与NO_x的协同减排力度,保障减排方案落实到位.      

基于16S rRNA基因测序法分析北京霾污染过程中PM2.5和PM10细菌群落特征

2013年1月8~14日,北京出现了严重的霾污染.霾污染时高浓度的大气颗粒物增加了暴露人群的健康风险,而大气中的微生物也可能带来一些风险,但目前对霾污染时大气中微生物组成了解较少.本研究选取了2013年1月8~14日北京7d的PM2.5和PM10采样样本,通过对细菌16S rRNA基因V3区扩增和Mi Seq测序,得到PM2.5和PM10中的细菌群落结构特征,并将结果与相同采样样本的宏基因组测序结果及三项国外基于16S rRNA基因测序方法的大气中细菌研究结果进行了比较.研究发现7 d连续采样条件下,PM2.5中细菌群落结构在门和属的水平上均差别不大.在属级别上,节杆菌属(Arthrobacter)和弗兰克氏菌属(Frankia)是北京冬季大气中细菌群落的主要类群.16S rRNA基因测序与宏基因组测序结果对比分析发现,在属级别上,两种分析方法中有39个相同的属类群(两种分析方法丰度前50的细菌类群合并所得),弗兰克氏菌属(Frankia)和副球菌属(Paracoccus)在16S rRNA基因测序分析结果中相对含量较多,而考克氏菌属(Kocuria)和地嗜皮菌属(Geodermatophilus)在宏基因组测序结果中相对含量较高.在门和属的水平上,PM2.5和PM10中细菌群落结构特征呈现出相似的规律.在门水平上,放线菌门(Actinobacteria)在PM2.5中的相对百分比较大,而厚壁菌门(Firmicutes)在PM10中的相对百分比较大.在属水平上,梭菌属(Clostridium)在PM10中的相对百分比较大.与三项国外基于16S rRNA基因测序研究结果对比发现,尽管在采样地点和采样时间上有较大差异,大气中普遍存在一些相同的细菌类群,且近地面大气细菌群落结构特征相似度较高,区别于高空对流层中细菌群落结构特征.     

林冠特征对城市森林斑块消减空气PM2.5质量浓度的影响

研究城市森林斑块消减空气PM_(2.5)质量浓度的能力,以及这种能力的主要影响因素,对改善城市空气环境具有重要的意义.本研究测定了南昌市典型城市森林斑块消减PM_(2.5)质量浓度的能力(PM_(2.5)AC),并分析了PM_(2.5)AC对城市森林斑块林分组成、冠层特征的响应.研究表明:南昌市城市森林斑块具有显著消减空气PM_(2.5)质量浓度的能力,其中针叶林斑块PM_(2.5)AC最高,达到9.15%,阔叶纯林最低3.82%;整体上春季PM_(2.5)AC最高,达到7.34%,冬季最低3.76%.城市森林斑块PM_(2.5)AC与林冠特征中的LAI(叶面积指数)显著正相关,与DIFN(天空开度)显著负相关,与斑块特征中的斑块面积、林分结构、斑块总叶面积显著正相关.通过综合分析,城市森林斑块总叶面积是主导PM_(2.5)AC的主要影响因素.     

荆州市大气污染物周边源影响域的气候模拟研究

以大气污染物协同控制与精准治理的需求为导向,开展湖北省荆州市大气污染物的来源分析.基于FLEXPART-WRF模式揭示了2008—2017年荆州市PM_2.5周边源"影响域"的季节气候特征,估算了大气污染物区域传输和局地排放的相对贡献,确定出不同季节的大气污染物主要传输通道.结果表明,荆州地区PM_2.5主要"影响域"为湖北、湖南、河南和安徽省.不同季节湖北省外源传输对荆州PM_2.5"影响域"的贡献率分别为春季50.4%、夏季33.9%、秋季42.6%、冬季43.0%和年均45.1%.春季3条区域传输通道分别为北通道（沿南阳盆地-荆州）、东通道（沿长江航道-荆州）以及南通道（沿雪峰山-荆州）;夏季主要为南通道;秋、冬季分别为北通道、东北通道（沿大别山低山丘陵-荆州）及东通道.针对荆州主要3类重污染天气型的典型个例"影响域"分析表明,高压静稳型PM_2.5污染主要来源于本地排放,省内贡献率达87.8%;低压倒槽型PM_2.5污染主要来源于偏南输送和本地累积,省内贡献率达55.0%;冷锋输送型PM_2.5污染主要来源于北路区域传输,省外贡献率达77.2%.对于冬季重污染期间,建议重点围绕荆州本地与省内荆门、襄阳、孝感、天门、潜江、武汉、随州、宜昌及省外常德、南阳、信阳等地开展协作,加强区域间大气污染联防联控.该项研究可为区域大气污染精细化管控与靶向治理提供科学依据.     

珠三角冬季PM2.5重污染区域输送特征数值模拟研究

利用嵌套网格空气质量模式系统(NAQPMS)及其耦合的污染来源追踪模块,针对2013年1月珠三角区域的PM_(2.5)重污染过程输送特征进行了数值模拟研究.结果表明,污染气团首先形成于广州、佛山地区,并在弱偏北风的作用下南移加强,影响整个珠三角区域.重污染期间,广州(64.9%)、佛山(58.9%)的PM_(2.5)主要来自本地贡献,是区域输送最主要的来源地区;中山(51.9%)、珠海(66.2%)的PM_(2.5)主要来自外来贡献,是区域输送主要的受体地区.重污染期间,广州和佛山对中山的PM_(2.5)日均贡献率之和总体保持在25%以上,污染最重时达到40%.交通(26%)、工业(24%)、扬尘(16%)、火力发电(15%)和生物质燃烧(8%)是对中山贡献最大的5类源:工业源中山本地与外来输送贡献率基本相当;交通和扬尘源以中山本地贡献为主,贡献率分别为55%和67%;火力发电和生物质燃烧源以外来输送为主,贡献率分别为56%和62%.各类排放源的外来输送中,以广州、佛山所占的比例最大.     

华中地区冬季灰霾天气下PM2.5中重金属污染特征及健康风险评价:以湖北黄冈为例

为探究华中地区灰霾天PM_2.5中重金属元素的污染特征及其潜在健康风险,于2018年1月13~24日对华中区域观测点——黄冈站点加密采集PM_2.5样品.采用电感耦合等离子体质谱仪（ICP-MS）对PM_2.5中Cr、Mn、Co、Ni、Cu、Zn、As、Cd、Sn和Pb进行分析,通过富集因子法对其污染特征进行探讨,并采用美国环保署推荐的暴露模型对其潜在风险进行评估.结果表明,观测期间PM_2.5中Zn质量浓度最高,致癌物质As、Cd质量浓度均高于我国环境空气质量标准（GB 3095-2012）的二级标准限值,70%的元素质量浓度在灰霾中期占比最大.富集因子分析显示,Cd、Sn、Co、Pb和Zn富集程度最高,特别是在灰霾中期,这些物质主要来源于交通和燃煤.人体健康风险评价结果显示,手口摄食是引起非致癌风险的主要途径,儿童的暴露量和非致癌风险均明显高于成人.Pb对儿童存在非致癌风险,PM_2.5中重金属对成人不具有非致癌风险且致癌重金属不具有致癌风险.     

四川盆地PM2.5浓度时空变化特征遥感监测与影响因子分析

四川盆地因其独特的地形地貌、静风和高湿等气象条件,导致盆地内部大气污染物扩散难度大,随着城市化与工业化进程加快,区内PM_2.5污染日益加重,四川盆地已成为国家大气污染防治的重点地区之一.基于PM_2.5浓度遥感反演产品,采用空间自相关分析与灰色关联分析方法,研究了四川盆地PM_2.5浓度的时空分布特征及其影响因素.结果表明,四川盆地PM_2.5浓度具有显著的空间聚集性,高-高聚集类型分布集中,低-低聚集类型分布较为分散;针叶林对PM_2.5的吸收抑制作用明显高于灌丛和草地等其他植被类型.研究认为,影响四川盆地PM_2.5浓度的主要气象因子是风速和气温,人口密度与经济规模则是影响四川盆地PM_2.5浓度的主要人类活动因子,产业结构及其规模变化对四川盆地PM_2.5浓度也产生一定影响.     

Emissions from the combustion of eucalypt and pine chips in a fluidized bed reactor

Interest in renewable energy sources has increased in recent years due to environmental concerns about global warming and air pollution,reduced costs and improved efficiency of technologies.Under the European Union(EU)energy directive,biomass is a suitable renewable source.The aim of this study was to experimentally quantify and characterize the emission of particulate matter(PM_(2.5))resulting from the combustion of two biomass fuels(chipped residual biomass from pine and eucalypt),in a pilot-scale bubbling fluidized bed(BFB)combustor under distinct operating conditions.The variables evaluated were the stoichiometry and,in the case of eucalypt,the leaching of the fuel.The CO and PM_(2.5)emission factors were lower when the stoichiometry used in the experiments was higher(0.33±0.1 g CO/kg and 16.8±1.0 mg PM_(2.5)/kg,dry gases).The treatment of the fuel by leaching before its combustion has shown to promote higher PM_(2.5)emissions(55.2±2.5 mg/kg,as burned).Organic and elemental carbon represented 3.1 to 30 wt.% of the particle mass,while carbonate(CO_3~(2-))accounted for between 2.3 and 8.5 wt.%.The particulate mass was mainly composed of inorganic matter(71% to 86% of the PM_(2.5)mass).Compared to residential stoves,BFB combustion generated very high mass fractions of inorganic elements.Chloride was the water soluble ion in higher concentration in the PM_(2.5)emitted by the combustion of eucalypt,while calcium was the dominant water soluble ion in the case of pine.     

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.     

2014~2016年京津冀沿山城市空气质量首要污染物特征分析

对北京、保定、石家庄、邢台和邯郸这5个京津冀太行山沿山城市2014~2016年空气质量首要污染物进行分析,探讨其空间分布特征和时间变化趋势.结果表明,北京首要污染物由主到次为PM_2.5、O₃-8h、NO₂和PM₁₀,其他4个城市首要污染物排序为PM_2.5、PM₁₀、O₃-8h、NO₂、SO₂和CO.在空间分布上,各城市PM_2.5首要污染物天数比例3 a均值相当（53.3%~58.1%）,但从北向南,5个城市PM₁₀天数比例基本呈上升趋势,而O₃-8h反之.除邯郸PM_2.5首要污染物天数比例逐年明显下降外,其他4个城市的天数比例年际变化幅度较小;2016年石家庄、邢台和邯郸O₃-8h天数比例均显著上升.各城市PM_2.5和O₃-8h首要污染物天数月变化曲线分别呈"W"型和"倒U"型,PM₁₀首要污染物天数在3~5月出现明显高值区.从良至严重污染,各城市PM_2.5和PM₁₀首要污染物天数比例之和随空气质量级别逐级递增,其中PM₁₀天数比例逐级下降,而PM_2.5表现相反;O₃-8h首要污染物天基本出现在良至中度污染级别,且总体上逐级下降;NO₂仅在良级天有较高的天数比例贡献.