首届“一带一路”会议期间北京市典型城区空气中VOCs的污染特征及健康风险评价

为研究"一带一路"国际合作高峰论坛在京召开期间北京市典型城区环境空气中挥发性有机物(VOCs)的污染特征及有毒有害VOCs的健康风险,本研究于2017年5月1—17日,在北京市典型城区利用Airmo VOC在线分析仪进行了观测研究.结果表明,整个观测期间总VOCs质量浓度日均值为29.99μg·m~(-3);空气质量保障期间(5月6—15日),大气中VOCs的浓度低于未采取控制措施的其它阶段,沙尘阶段VOCs浓度由于受到风速和气团传输影响出现最低值;各类VOCs的质量浓度在交通早高峰出现高值.PMF来源解析表明,移动源尾气排放(37.62%)、溶剂使用源(33.25%)、油气挥发源(16.39%)和天然气燃烧源(12.74%)的排放是北京市"一带一路"会议期间环境空气中VOCs的主要来源.化学活性分析表明,芳香烃和烯烃对臭氧生成潜势贡献的占比最多,需要重点控制的VOCs物种为间对二甲苯、甲苯和丙烯.健康风险评价结果表明,研究区整个观测期间及各阶段的苯和1,2-二氯乙烷均存在潜在的致癌风险,14种有毒有害VOCs(包括苯和1,2-二氯乙烷)不存在非致癌风险.     

Characteristics of atmospheric volatile organic compounds in urban area of Beijing: Variations, photochemical reactivity and source apportionment

Atmospheric volatile organic compounds(VOCs) were observed by an on-line gas chromatography-flame ionization detector monitoring system from November 2016 to August 2017 in Beijing.The average concentrations were winter(40.27±25.25 μg/m³)> autumn(34.25±19.90 μg/m3)> summer(32.53±17.39 μg/m³)> spring(24.72±17.22 μg/m³).Although benzene(15.70%),propane(11.02%),ethane(9.32%) and n-butane(6.77%) were the most abundant species,ethylene(14.07%) and propene(11....     

上海市某化工区夏季典型光化学过程VOCs特征及活性研究

本研究基于夏季某化工区外5 km处观测点O_3及VOCs在线观测结果,分析了VOCs污染及光化学反应活性特征.结果显示,西南风向的VOCs平均体积分数为63.9×10~(-9)±28.6×10~(-9),高于其他风向42%(45.0×10~(-9)±28.0×10~(-9)),不同主导风向下的VOCs特征具有一定的相似性,均以烯烃、卤代烃和烷烃为主要组分,说明化工园区局地排放和累积对观测点VOCs影响较大.主要VOCs物种的日变化都具有夜间体积分数累积增多,白天逐步降低的特征;但是异戊二烯呈现日变化较小的特征,显示其受到人为源和天然源的双重影响.西南风向的臭氧生成潜势(Ozone Formation Potential,OFP)为242.1×10~(-9),远高于其他风向的OFP(174.1×10~(-9)),而平均MIR(Maximum Increment Reactivity)则较为接近;烯烃在VOCs总OFP中的贡献比例均在70%以上,其次是芳香烃.使用乙苯和间/对二甲苯的比值来表征气团光化学反应进程,计算得到观测点西南风向VOCs消耗量为(51.7×10~(-9)±38.8×10~(-9)),烯烃和卤代烃是最主要VOCs消耗组分.     

徐州市区环境空气中TVOC污染现状及变化规律

2003年1-12月使用光离子化检测仪，对徐州市环境空气中的TVOC进行检测，监测结果显示：徐州市区环境空气中的TVOC浓度值1月份最高；其次为6月份；年平均值为82μL/m^3；交通干道两旁污染最严重。     

北京城区夏季静稳天气下大气边界层与大气污染的关系

利用ALS300激光雷达系统测量的信号,根据Fernald方法反演的气溶胶消光系数的最大突变即最大递减率的高度确定大气边界层高度. 结果表明:在夏季静稳天气下,大气边界层平均高度为600 m,其中晴天为1 000 m,雾天为700 m,阴雨天在200~300 m之间. 静稳天气下的大气边界层不容易被有效突破,故不利于大气污染物扩散. 大气边界层高度对污染物浓度影响显著,没有降雨时,大气边界层降低(400 m),大气污染加重,在城区宝联站监测的ρ(PM_2.5)近200 μg/m3,在大气本底站——上甸子站近150 μg/m3;如果伴有降水,大气边界层高度升至600 m,大气污染则减轻,2个站点观测的ρ(PM_2.5)均降至50 μg/m3以下. 静稳天气下的大气污染呈现区域性特点.      

A review of atmospheric benzene homologues in China: Characterization, health risk assessment, source identification and countermeasures

Benzene homologues are important chemical precursors to the formation of ground-level ozone and secondary organic aerosol(SOA) in the atmosphere,in addition,some toxic species are harmful to human health.Strict countermeasures have been taken to fight air pollution since 2013,and total amount control of volatile organic compounds is being promoted in China at present.Therefore,it is important to understand the pollution situation and the control status of ambient benzene homologues in China.This...     

A preliminary analysis of the surface chemistry of atmospheric aerosol particles in a typical urban area of Beijing

Atmospheric aerosol particle samples were collected using an Ambient Eight Stage(Non-Viable) Cascade Impactor Sampler in a typical urban area of Beijing from 27 th Sep.to 5th Oct.,2009.The surface chemistry of these aerosol particles was analyzed using Static Time of Flight-Secondary Ion Mass Spectrometry(Static TOF-SIMS).The factors influencing surface compositions were evaluated in conjunction with the air pollution levels,meteorological factors,and air mass transport for the sampling period.The results show that a variety of organic ion groups and inorganic ions/ion groups were accumulated on the surfaces of aerosol particles in urban areas of Beijing;and hydrophobic organic compounds with short-or middle-chain alkyl as well as hydrophilic secondary inorganic compounds were observed.All these compounds have the potential to affect the atmospheric behavior of urban aerosol particles.PM1.1–2.1and PM3.3–4.7had similar elements on their surfaces,but some molecules and ionic groups demonstrated differences in Time of Flight-Secondary Ion Mass Spectrometry spectra.This suggests that the quantities of elements varied between PM1.1–2.1and PM3.3–4.7.In particular,more intense research efforts into fluoride pollution are required,because the fluorides on aerosol surfaces have the potential to harm human health.The levels of air pollution had the most significant influence on the surface compositions of aerosol particles in our study.Hence,heavier air pollution was associated with more complex surface compositions on aerosol particles.In addition,wind,rainfall,and air masses from the south also greatly influenced the surface compositions of these urban aerosol particles.     

Observation and analysis of atmospheric volatile organic compounds in a typical petrochemical area in Yangtze River Delta, China

Volatile organic compounds (VOCs) are a kind of important precursors for ozone photochemical formation. In this study, VOCs were measured from November 5th, 2013 to January 6th, 2014 at the Second Jinshan Industrial Area, Shanghai, China. The results showed that the measured VOCs were dominated by alkanes (41.8%), followed by aromatics (20.1%), alkenes (17.9%), and halo-hydrocarbons (12.5%). The daily trend of the VOC concentration showed a bimodal feature due to the rush-hour traffic in the morning and at nightfall. Based on the VOC concentration, a receptor model of Positive Matrix Factorization (PMF) coupled with the information related to VOC sources was applied to identify the major VOC emissions. The result showed five major VOC sources: solvent use and industrial processes were responsible for about 30% of the ambient VOCs, followed by rubber chemical industrial emissions (23%), refinery and petrochemical industrial emissions (21%), fuel evaporations (13%) and vehicular emissions (13%). The contribution of generalized industrial emissions was about 74% and significantly higher than that made by vehicle exhaust. Using a propylene-equivalent method, alkenes displayed the highest concentration, followed by aromatics and alkanes. Based on a maximum incremental reactivity (MIR) method, the average hourly ozone formation potential (OFP) of VOCs is 220.49?ppbv. The most significant source for ozone chemical formation was identified to be rubber chemical industrial emissions, following one by vehicular emission. The data shown herein may provide useful information to develop effective VOC pollution control strategies in industrialized area.     

北京市门头沟区大气降尘污染特征及其化学组分特征与质量重构

为研究北京市门头沟区大气降尘污染特征,收集了2018～2022年门头沟区2个国控环境空气站57个大气降尘量月平均监测结果,分析了门头沟区大气降尘污染状况及其时间变化特征.为探究大气降尘化学组分特征与质量重构结果及其来源,在三家店国控环境空气站,使用主动抽滤法模拟采集降尘样品57个,测定了降尘的质量浓度及其化学组分的质量浓度,研究了大气降尘中的化学组分特征,并利用颗粒物质量重构技术对大气降尘主要组分进行质量重构,探讨了质量重构的结果可靠性及其未确定成分的原因.结果表明,2018～2022年,北京市门头沟区月降尘量呈周期性变化,最大值在春季4、 5月,最小值在秋季10、 11月,且最大月降尘量是最小月降尘量的3.2～8.4倍.季度平均月降尘量大小表现为：春季>夏季>秋季>冬季,且降尘主要来自于春季和夏季,其降尘量分别占全年总降尘量的40.1%～43.0%和23.8%～37.5%.北京市门头沟区大气降尘年平均月降尘量下降趋势明显,2022年较2018年降尘量下降了52.8%,年均下降了13.2%,与近年来北京市城市环境保护精细化管理水平的提高有关;2021年沙尘对门头沟区降...     

Pollution characteristics and health risk assessment of benzene homologues in ambient air in the northeastern urban area of Beijing, China

Ambient benzene homologues were measured at a site in the northeastern urban area of Beijing, China, from August 24 to September 4, 2012 by SUMMA canister sampling followed by laboratory determination using cryogenic cold trap pre-concentration-GC-MS/FID, and their health risks were also assessed. Daily total benzene homologues ranged from 0.99 to 49.71 μg/m3with an average of 11.98 μg/m3. Benzene homologues showed higher concentrations in the morning and evening than that at noontime. Comparison with previous studies revealed a trend of decrease for ambient benzene homologues probably due to the efective emission control in Beijing in recent years. Vehicular exhaust was the main source while volatilization of paints and solvents also made substantial contributions. Health risk assessment showed that BTEX(benzene, toluene, ethylbenzene, o-xylene, m-xylene and p-xylene) and styrene had no appreciable adverse non-cancer health risks for the exposed population, while benzene has potential cancer risk of 1.34E-05. Available data from cities in China all implied that benzene imposes relatively higher cancer risk on the exposed populations and therefore strict control measures should be taken to further lower ambient benzene levels in China.     

北京市典型城区餐饮业VOCs和PM2.5排放量估算

以北京市餐饮企业分布密度最大的西城区为案例区,通过对研究区域内餐饮企业进行实地污染物检测及排放活动水平调查,计算得到基于就餐人数、就餐时间、烹饪油用量和灶头数4种核算基准的餐饮业VOCs和PM_2.5排放因子,并利用排放因子法分别估算该区域在餐饮废气净化设备升级改造前后餐饮企业VOCs和PM_2.5年排放量.结果表明：本研究区域餐饮业废气净化设备升级改造前VOCs排放量范围为319.03~506.38t/a,改造后为92.14~109.89t/a;改造前PM_2.5排放量范围为166.55~211.09t/a,改造后为30.22~36.05t/a,排放量明显减少.餐饮业废气净化设备改造后VOCs和PM_2.5减排率分别为71%~82%和80%~86%,餐饮业废气净化设备升级改造减排效果良好.计算得到以街道为单元的餐饮源VOCs和PM_2.5排放强度范围分别为1.45~4.32t/km²和0.47~1.42t/km².通过PM_2.5实测浓度（小时值）数据分析,餐饮业废气净化设备升级改造前、后PM_2.5浓度平均减少了28.9%,最接近于用油量为核算基准的排放因子降低比例.     

北京市“大气十条”实施的空气质量改善效益

大气污染防治行动计划（"大气十条"）等政策措施实施以来,北京市空气质量改善显著.为科学评估"大气十条"的效果,以北京市为例,采用疾病成本法、人力资本法和市场价值法核算空气质量改善带来的人体健康、农业、建筑材料和清洁损失减少的效果,并通过货币化北京市"大气十条"的政策收益,从而肯定地方开展大气污染防治工作的积极成效.结果表明：①政策实施以来,北京市空气质量明显改善,改善效益稳定增长,2013~2017年分别达到-19.82、-18.93、157.07、152.64和223.30亿元,在当年GDP占比分别为-0.85‰、-0.81‰、6.68‰、6.16‰和8.77‰.5 a实施的总效益为494.26亿元,占GDP总值的4.11‰.②改善效益以健康损失改善效益和清洁损失改善效益为主,体现了颗粒物浓度降低带来的明显效果.③北京16个行政区大多在政策后期达到较高效益,其中延庆区、密云区、平谷区、昌平区、通州区、石景山区和朝阳区这7个区连续5 a改善指数为正,朝阳区和海淀区等由于人口密集,大气污染暴露人口多,获得效益稍差.本研究结果证实了北京市"大气十条"实施的有效性和必要性.     

Physico-chemical characterization and source tracking of black carbon at a suburban site in Beijing

Particles from ambient air and combustion sources including vehicle emission, coal combustion and biomass burning were collected and chemically pretreated with the purpose of obtaining isolated BC (black carbon) samples. TEM (transmission electron microscopy) results indicate that BC from combustion sources shows various patterns, and airborne BC appears spherical and about 50 nm in diameter with a homogeneous surface and turbostratic structure. The BET (Barrett–Emmett–Teller) results suggest that the surface areas of these BC particles fall in the range of 3–23 m²/g, with a total pore volume of 0.03–0.05 cm³/g and a mean pore diameter of 7–53 nm. The nitrogen adsorption–desorption isotherms are indicative of the accumulation mode and uniform pore size. O₂-TPO (temperature programmed oxidation) profiles suggest that the airborne BC oxidation could be classified as the oxidation of amorphous carbon, which falls in the range of 406–490°C with peaks at 418, 423 and 475°C, respectively. Generally, the BC characteristics and source analysis suggest that airborne BC most likely comes from diesel vehicle emission at this site.     

北京春季一次霾-沙天气污染特性与成因分析

2017年5月3～5日,北京发生一次特别的重污染过程,与之相配的气象条件较为特殊,对污染形态和成因展开研究.基于北京35个环境监测站和与之最近的35个自动气象站,获取本次污染过程的总体特征及PM_(10)、PM_(2.5)浓度与地面风场的匹配形态;利用MODIS和CALIPSO研究污染空间分布、输送路径、污染物类别;根据欧洲中期天气预报中心ECMWF第三代再分析资料ERA-Interim及风廓线雷达数据研究污染成因.以期以地-空立体监测技术手段配合气象条件得到本次污染特有的形态特征和影响因素.结果表明,利用以上多源数据,对本次污染进行立体观测和综合分析,能较好地反映污染特性和受制因素.本次污染骤然开始,陡然下降,持续约30h,整个过程PM_(10)和PM_(2.5)浓度高,分别可达600～1 000μg·m~(-3)和200～700μg·m~(-3).全过程分为三段,前半段、间歇期、后半段.前、后半段污染成因以及由此造成的PM_(10)和PM_(2.5)浓度在空间分布上各有特点.前半段主导风向为西北风,风速小,PM_(10)浓度空间差异小,在800μg·m~(-3)以上,而PM_(2.5)浓度空间差异大,南部和城区高,达600～700μg·m~(-3),其余地方低,在350～500μg·m~(-3).间歇期低层风向从西北风切变为南风,高层维持西北风,南部和城区PM_(10)浓度下降明显,到650μg·m~(-3),北部依然在800μg·m~(-3),而此时北部PM_(2.5)浓度甚至降到200μg·m~(-3).后半段主导风又回到了西北风,且风速激增,此时PM_(2.5)浓度空间差异小且同一站点的浓度均小于前半段,在250～500μg·m~(-3).而PM_(10)浓度又回到了800μg·m~(-3)的水平.说明本次过程属典型霾-沙混合型污染.在偏西气流的影响下,对北京污染的主要贡献是沙尘型的PM_(10),而在偏南气流下,对北京污染的贡献除了沙尘外,还有PM_(2.5).污染重的同时,风速也大,大气垂直运动交汇于大约2～3 km高度,在此高度层内有大量污染物累积.     

The levels, sources and reactivity of volatile organic compounds in a typical urban area of Northeast China

Air concentrations of volatile organic compounds (VOCs) were continually measured at a monitoring site in Shenyang from 20 August to 16 September 2017. The average concentrations of alkanes, alkenes, aromatics and carbonyls were 28.54, 6.30, 5.59 and 9.78 ppbv, respectively. Seven sources were identified by the Positive Matrix Factorization model based on the measurement data of VOCs and CO. Vehicle exhaust contributed the most (36.15%) to the total propene-equivalent concentration of the measured VOCs, followed by combustion emission (16.92%), vegetation emission and secondary formation (14.33%), solvent usage (10.59%), petrochemical industry emission (9.89%), petrol evaporation (6.28%), and liquefied petroleum gas (LPG) usage (5.84%). Vehicle exhaust, solvent usage and combustion emission were found to be the top three VOC sources for O₃ formation potential, accounting for 34.52%, 16.55% and 11.94%, respectively. The diurnal variation of the total VOCs from each source could be well explained by their emission characteristics, e.g., the two peaks of VOC concentrations from LPG usage were in line with the cooking times for breakfast and lunch. Wind rose plots of the VOCs from each source could reveal the possible distribution of the sources around the monitoring site. The O₃ pollution episodes during the measurement period were found to be coincident with the elevation of VOCs, which was mainly due to the air parcel from the southeast direction where petrochemical industry emission was found to be dominant, suggesting that the petrochemical industry emission from the southeast was probably a significant cause of O₃ pollution in Shenyang.     

北京市大气细颗粒物污染与来源解析研究

采集北京市2014年冬、春、夏、秋4个季节代表月1、4、7、10月的大气细颗粒物PM_2.5样品,分析研究了PM_2.5质量浓度、化学特征、季节变化和污染成因.同时,采用正交矩阵因子分析法（PMF）对PM_2.5进行了来源解析.结果表明,北京市2014年PM_2.5年均浓度为87.74μg/m³,是国家环境空气质量标准年均浓度限值的2.5倍.轻、重污染期间,PM_2.5浓度较常日分别增加了1.5和3.9倍,其季节变化表现为冬季 >夏季 >秋季 >春季.地壳元素Mg、Al、Fe、Ca、Ti在轻度污染和重度污染期间较常日略有升高,分别是常日浓度的1.1~1.2倍和1.2~1.5倍.污染元素S、Pb、Zn、Cu浓度变化显著,轻度污染和重度污染期间分别是常日浓度的1.3~2.7倍和1.9~5.9倍.S元素是PM_2.5中受人为活动影响较为严重的组分,其相应的SO₄^2-年均浓度为13.43μg/m³,在轻度污染和重度污染期间分别是常日浓度的2.7和5.9倍.硫酸盐的形成主要受O₃浓度、温度、相对湿度等气象要素的协同影响,较高的O₃浓度、较高温度和相对湿度有利于硫酸盐的生成.PM_2.5主要来源于机动车排放、燃煤、地面扬尘和工业排放,其贡献率分别为37.6%、30.7%、16.6%和15.1%.     

北京东北部城区大气细粒子与相关气体污染特征研究

于2008年7月~2009年4月的4个季节,在北京市朝阳区北部,利用VAPS通用型大气污染物采样仪(URG3000K)对大气细粒子(PM2.5)和环境空气中相关气体进行了同时采集,并利用IC离子色谱仪(DX-600型)分析了PM2.5中水溶性无机离子成分和环境空气中相关气体的含量.结果表明,PM2.5质量浓度春季>夏季>冬季>秋季;SO42-、NO3-和NH4+是PM2.5中最主要的3种水溶性无机离子,年均质量浓度分别为14.82μg/m3、11.57μg/m3和8.35μg/m3,三者浓度之和占PM2.5中总水溶性无机离子浓度的86.28%.SO42-、NH4+浓度占PM2.5浓度百分比均为夏、秋季高于冬、春季; NO3-浓度占PM2.5浓度的百分比为秋季>春季>夏季>冬季.空气中的SO2、NO2和NH3等气态污染物的含量直接影响PM2.5中二次离子SO42-、NO3-和NH4+的浓度, SO2、NO2浓度的季节特征为冬、春季高于夏、秋季,与SO42-、NO3-的季节变化规律相反; NH3浓度在夏季最高,冬季最低. PM2.5酸度在夏、秋季高于冬、春季,且夏、秋季PM2.5样品全部呈酸性,冬、春季PM2.5样品一部分呈酸性,一部分呈碱性.夏季SOR值和NOR值分别为冬季的4.8倍和3倍,表明夏季SO2和NO2更易转化生成SO42-和NO3-.PM2.5中SO42-、NO3-和NH4+主要以(NH4)2SO4、NH4NO3的形式共存于气溶胶体系中.     

北京城市大气N2O浓度及其变化

1993~2000年对北京大气N2O进行了连续8年的观测,结果表明,北京大气N2O浓度8年平均值为315.85.9nmol/mol;浓度由1993年的309.7nmol/mol增长到2000年的328.6nmol/mol,年平均增长率为0.9%.1995年以来增长加速,年平均增长率为1.3%.化石燃料燃烧N2O排放量的逐年增长对北京大气N2O浓度的上升趋势有促进作用.北京大气N2O浓度季节变化不十分明显,N2O浓度日变化在所有季节中也无明显规律.     

哈尔滨市环境空气污染特征变化趋势及雾霾突发原因研究

通过对哈尔滨市近3年环境空气质量变化趋势及污染特征进行分析,进一步明确哈尔滨雾霾现象的原因,主要为进入冬季供暖期,供热源增加的大气污染物与工业源排放的大气污染物以及汽车尾气等面源污染物累积使环境空气中颗粒物激增,导致哈尔滨市环境空气中的大气污染物总量超出了环境承载能力,加上不利污染物扩散的气象条件,大气污染物积聚在哈尔滨城市上空无法扩散,导致了这种雾霾现象。     

重庆市主城区大气细颗粒物污染特征与来源解析

重庆市主城区大气细颗粒物(PM_(2.5))浓度从1990s的100μg·m~(-3)下降至当前的约70μg·m~(-3),但仍高于环境标准限值.为探讨重庆市主城区PM_(2.5)化学组成与来源特征,于2012—2013年在渝北区大气超级站利用四通道采样仪连续采集了颗粒物样品,分析了其中水溶性离子、碳质组分和无机元素含量.采样期间,重庆市主城区大气PM_(10)和PM_(2.5)的年日均浓度分别为103.9和75.3μg·m~(-3),扩散条件不利的冬季,细颗粒物污染较为严重.受静稳天气影响的1月和2月,受沙尘影响的3月,及二次转化显著的6月是重庆市细颗粒物污染较重的月份.重庆市PM_(2.5)组成以有机物(OM,30.8%)为主,其次为硫酸盐(SO_4~(2-),23.0%)、硝酸盐(NO_3~-,11.7%)、铵盐(NH_4~+,10.9%)、地壳物质(Soil,8.2%)、元素碳(EC,5.2%)、K~+(1.1%)、Cl~-(1.0%)和微量元素(Trace,0.6%).较高的SO_4~(2-)浓度和逐步上升的[NO_3~-]/[SO_4~(2-)]比值反映了重庆市燃煤污染较重,同时机动车污染比例逐步增加.采用主因子分析/绝对主因子得分法解析了重庆城区细颗粒物5类主要来源是:二次粒子(41.7%)、燃煤(15.6%)、建筑/道路尘(12.4%)、土壤尘(11.0%)和工业尘(10.4%),通过各污染源季节变化及与其他结果对比,该源解析结果能够较可靠反映重庆市细颗粒物的来源信息.