Sources of ambient non-methane hydrocarbon compounds and their impacts on O3 formation during autumn, Beijing

The field observation of 54 non-methane hydrocarbon compounds (NMHCs) was conducted from September 1 to October 20 in 2020 during autumn in Haidian District, Beijing. The mean concentration of total NMHCs was 29.81 ± 11.39 ppbv during this period, and alkanes were the major components. There were typical festival effects of NMHCs with lower concentration during the National Day. Alkenes and aromatics were the dominant groups in ozone formation potential (OFP) and OH radical loss rate (L_OH). The positive matrix factorization (PMF) running results revealed that vehicular exhaust became the biggest source in urban areas, followed by liquefied petroleum gas (LPG) usage, solvent usage, and fuel evaporation. The box model coupled with master chemical mechanism (MCM) was applied to study the impacts of different NMHCs sources on ozone (O₃) formation in an O₃ episode. The simulation results indicated that reducing NMHCs concentration could effectively suppress O₃ formation. Moreover, reducing traffic-related emissions of NMHCs was an effective way to control O₃ pollution at an urban site in Beijing.     

京津地区大气中非甲烷烃(NMHCs)质量浓度水平和反应活性研究

2006年8月15日—9月15日同时在北京和天津对大气中的非甲烷烃（NMHCs）进行了同步观测,利用最大增量反应活性（MIR）计算了两地NMHCs的臭氧生成潜势以估计其对臭氧生成的影响. 结果表明,北京大气中ρ（NMHCs）平均值比天津高78.0 　μg/m3.用上午的ρ（NMHCs）计算了京津地区臭氧生成潜势,分别为1 470 和814 　μg/m3,其中苯系物对臭氧生成的影响最大,分别占总臭氧生成潜势的75%和73%,其次是烯烃（占13%和11%）和烷烃（占12%和16%）. 比较两地ρ（NMHCs）和NMHCs的反应活性可知,北京地区大气中NMHCs的组成比天津的稳定,且其反应活性强于天津. 结合臭氧浓度发现,北京地区大气的氧化能力比天津强.      

北京市春季交通干道移动源非甲烷总烃的在线跟踪观测与特征分析

机动车排放(Vehicular Emission,VE)是地面非甲烷烃(Non-methane hydrocarbon,NMHCs)的重要人为源之一.为获得北京市交通主干道NMHCs的实际排放情况,本研究以自主研发的吸附/热解吸前处理-单光子/化学复合软电离源飞行时间质谱(SPI/CI-TOFMS)为检测手段,于2018年3月14日在北京四环、五环主干道,对C_2～C_(10)挥发性有机物进行了车载在线跟踪观测.结果表明,C_2、C_3高挥发性物质浓度较高,其次是苯系物和丁烷;从空间分布来看,NMHCs浓度在离市中心较近的四环主干道相对较高,且车流量较大的南五环公路和西四环处NMHCs污染也较为严重;从NMHCs的结构组成来看,烷烃(63%、52%)占比最多,芳香烃(23%、32%)次之,烯烃(14%、16%)最少;对NMHCs特征物质之间的线性关系和比值关系进行分析,确定机动车排放对此次观测中NMHCs的生成贡献较大;通过计算各物种臭氧生成潜势(OFP),评估出C_3、C_4烯烃类物质和苯系物为北京四、五环地区优先控制物种.     

北京市道路空气中挥发性有机物时空分布规律

为研究城市交通道路空气中挥发性有机化合物(VOCs)的污染状况、变化规律和不同道路类型的浓度特点,于2008年5月—2009年7月对北京市3种典型道路(街道峡谷、交叉道路和开阔道路)进行空气质量监测. 采用气相色谱法测定道路空气中非甲烷烃(NMHCs)、苯系物(苯、甲苯和二甲苯)的质量浓度. 结果表明:北京市道路空气中挥发性有机化合物污染比较严重,其中ρ(NMHCs)日均值为1.0～3.3 mg/m3,ρ(苯系物)日均值为8.8～80.0 μg/m3. 污染物浓度日变化多呈现双峰型. 选取1,4,7和10月为不同季节的代表月份,7月的ρ(NMHCs)和ρ(苯系物)均最高,10月最低. 3种典型道路中,街道峡谷的污染物质量浓度高于另外2种道路. 道路附近的挥发性有机物质量浓度主要受到机动车排放、气象条件和地形条件等的影响.      

Observation-based sources evolution of non-methane hydrocarbons (NMHCs) in a megacity of China

Both concentrations and emissions of many air pollutants have been decreasing due to implement of control measures in China, in contrast to the fact that an increase in emissions of non-methane hydrocarbons (NMHCs) has been reported. This study employed seven years continuous NMHCs measurements and the related activities data of Shanghai, a megacity in China, to explore evolution of emissions and effectiveness of air pollution control measures. The mixing ratio of NMHCs showed no statistical interannual changes, of which their compositions exhibited marked changes. This resulted in a decreasing trend of ozone formation potential by 3.8%/year (p < 0.05, the same below), which should be beneficial to ozone pollution mitigation as its production in Shanghai is in the NMHCs-limited regime. Observed alkanes, aromatics and acetylene changed by +3.7%/year, -5.9%/year and -7.4%/year, respectively, and alkenes showed no apparent trend. NMHCs sources were apportioned by a positive matrix factorization model. Accordingly, vehicular emissions (-5.9%/year) and petrochemical industry emissions (-7.1%/year) decreased significantly, but the decrease slowed down; significant reduction in solvent usage (-9.0%/year) appeared after 2010; however, emissions of natural gas (+12.6%/year) and fuel evaporation (with an increasing fraction) became more important. The inconsistency between observations and inventories was found in interannual trend and speciation as well as source contributions, emphasizing the need for further validation in NMHCs emission inventory. Our study confirms the effectiveness of measures targeting mobile and centralized emissions from industrial sources and reveals a need focusing on fugitive emissions, which provided new insights into future air policies in polluted region.     

Trend and seasonal variations of atmospheric CH4 in Beijing

The atmospheric CH4 in Beijing is still increasing, even though its increasing rate has significantly decreased from 1.76 ％/a during 1985-1989 to 0.50 ％/a during 1990-1997. The seasonal variation of CH4 concentration showed a double-peak pattern, one peak appearing in winter and the other in summer. It is evident that the annually seasonal variations of atmospheric CH4 in Beijing are different. From 1986 to 1997, the atmospheric CH4 increased by 185 ppbv, 37％ and 21％ of which were due to the increase in winter and in summer, respectively. After 1993, the annually seasonal increasing rate of CH4 concentration in summer (due to emission from biogenic sources) is negative while the increasing rate in winter (due to emission from non-biogenic sources) is positive about 25 ppbv/a. As a result, the increase of CH4 emission from non-biogenic sources in winter is the major reason that caused theannually seasonal increasing rate from 1993 to 1997. The biogenic sources in Beijing are shrinking while the non-biogenic ones (such as fossil fuel combustion) are enlarging.     

Trend and seasonal variations of atmospheric CH_4 in Beijing

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沙尘天气对大气环境质量影响的量化研究

利用沙尘天气年鉴资料和颗粒物浓度监测数据,构建了沙尘天气对大气环境质量影响的量化指标(贡献率和绝对贡献),并利用该量化指标分析了沙尘天气对位于沙尘源区和影响区内典型城市大气环境的影响,同时比较了沙尘天气对北京城、郊区的不同影响. 结果表明:2001—2009年沙尘天气对沙尘源区城市呼和浩特的贡献率年均值为6.84%,对影响区内的城市北京、天津、济南的贡献率年均值分别为5.96%、3.57%、1.66%;沙尘天气对沙尘源区城市(呼和浩特)和影响区城市(北京、天津和济南)的贡献率最大值均出现在3月,其中,对呼和浩特、北京、天津、济南的贡献率最大值分别达到19.21%、15.02%、9.41%和8.69%;2000年4月和2001年3月沙尘天气对北京ρ(PM₁₀)的绝对贡献较大,分别为0.062和0.077mg/m3,占GB 3095—2012《环境空气质量标准》ρ(PM₁₀)二级标准限值(0.15mg/m3)的41.3%和51.3%;沙尘天气过程对于北京城、郊区的影响也不完全一致.      

Significant contribution of spring northwest transport to volatile organic compounds in Beijing

High values of ozone (O₃) occur frequently in the dry spring season; thus, understanding the evolution characteristics of volatile organic compounds (VOCs) in spring is of great significance for preventing O₃ pollution. In this study, a total of 101 VOCs from April 16 to May 21, 2019, were quantified using an online gas chromatography mass spectrometer/flame ionization detector (GCMS/FID). The results indicated that the observed concentration of total VOCs (TVOCs) was 30.4 ± 17.0 ppbv, and it was dominated by alkanes (44.3%), followed by oxygenated VOCs (OVOCs) (17.4%), halocarbons (12.7%), aromatics (9.5%), alkenes (8.2%), acetylene (5.3%) and carbon disulfide (2.5%). The average mixing ratio of VOCs showed obvious diurnal variation (high at night, low during daytime). We conducted a source apportionment study based on 32 major VOCs using positive matrix factorization (PMF), and coal + biomass burning (25.2%), diesel exhaust (16.0%), gasoline exhaust + evaporation (17.4%), secondary + long-lived species (16.7%), biogenic sources (4.3%), industrial emissions (9.3%) and solvent use (11.2%) were identified as major sources of VOCs. In addition to local emissions, most of the atmospheric VOCs were derived from long-distance air masses (65.7%), and the average mixing ratio of VOCs in the northwest direction was 29.4 ppbv. Combined with the results of the potential source contribution function (PSCF) indicate that research should focus on the local emissions of combustion, transportation sources and solvents usage to control atmospheric VOCs. Additionally, transmission of the northwest air mass is an important component that cannot be ignored during spring in Beijing.     

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.      

Characteristics and anthropogenic sources of carbonyl sulfide in Beijing

Atmospheric mixing ratios of carbonyl sulfide (COS) in Beijing were intensively measured from March 2011 to June 2013. COS mixing ratios exhibited distinct seasonal variation, with a maximum average value of 849 ± 477 pptv in winter and a minimal value of 372 ± 115 pptv in summer. The seasonal variation of COS was mainly ascribed to the combined effects of vegetation uptake and anthropogenic emissions. Two types of significant linear correlations (R² > 0.66) were found between COS and CO during the periods from May to June and from October to March, with slopes (ΔCOS/ΔCO) of 0.72 and 0.14 pptv/ppbv, respectively. Based on the emission ratios of COS/CO from various sources, the dominant anthropogenic sources of COS in Beijing were found to be vehicle tire wear in summer and coal burning in winter. The total anthropogenic emission of COS in Beijing was roughly estimated as 0.53 ± 0.02 Gg/year based on the local CO emission inventory and the ΔCOS/ΔCO ratios.     

北京潜在蒸散发量年内-年际的气候变化特征及成因辨识

论文基于北京站1951—2009 年的气象资料,采用Penman-Monteith 公式估算潜在蒸散发,并对其年际年内的变化特征进行辨析。结果表明:北京1951—2009 年年均潜在蒸散发量呈显著上升趋势;气象要素的敏感性从强到弱依次为:空气相对湿度、温度、太阳辐射和风速;论文提出实测变幅均值法,基于此方法考虑气象要素年内变化特征,估算温度、饱和差、风速和太阳辐射的贡献率分别为13%、58%、17%和11%;对气象因子的年际变化趋势进行分析,平均气温在0.05 显著水平下增加趋势显著,太阳辐射和空气相对湿度在0.05 显著水平下减少趋势显著,风速变化趋势没有通过显著性检验;综合考虑年际变化和敏感性的去趋势分析显示:温度增加和空气相对湿度减少是造成潜在蒸散发增加的主要原因,太阳辐射的减少使得其增加趋势有所减弱,但未改变其增加趋势。     

北京清洁区大气颗粒物污染特征及长期变化趋势

清洁对照区表征了区域环境的影响,是全面评价城市大气环境质量变化的基础.本研究分析了北京清洁区定陵不同粒径颗粒物质量的历史监测数据,包括1980～2009年大气降尘、1991～2009年总悬浮颗粒物(TSP)、2000～2009年可吸入颗粒物(PM10).结果表明,北京清洁区大气颗粒物总体呈下降趋势,年际短期变化受沙尘天...     

深圳城市大气中非甲烷烃季节变化特征

应用GCMS-QP2010对深圳2015~2016年4个季节大气56种非甲烷碳氢化合物（NMHCs）进行在线监测分析.从成分来看,四季总NMHCs平均浓度为23.6×10^-9,呈现出冬季 > 秋季 > 夏季≈春季的变化特征,其中烷烃比例最高（65.4%~74.7%）,其次是芳香烃（13.3%~21.7%）和烯烃（7.1%~11.6%）,丙烷、甲苯、乙烷、正己烷、正丁烷、乙炔、2-甲基戊烷、异丁烷、乙烯和3-甲基戊烷是浓度最高的10个物种.相关性和日变化分析表明,深圳大气中NMHCs受到机动车、溶剂挥发相关工业源以及植物释放等多重来源的共同影响,其中甲苯、2-甲基戊烷、3-甲基戊烷和正己烷受工业源影响最为显著,而异戊二烯主要来自于天然源.     

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.     

道路机动车温室气体排放评估与情景分析:以北京市为例

基于LEAP模型（long-range energy alternatives planning system）评估北京市历史阶段（2000—2018年）道路机动车温室气体排放量的变化规律,并设置5种情景预测未来阶段（2019—2030年）机动车保有量、能源需求、温室气体排放量的发展趋势,探究达峰年份,寻求最优发展路径。结果显示:未来北京市机动车保有量仍将持续增长,但平均年增长率降低至1.63%。机动车温室气体排放总量已于2013年达峰,峰值为21758563 t CO_2e,对应能源消耗量为306383 TJ,未来所有情景下机动车温室气体排放量均呈不同程度下降。单一措施中提高机动车燃料经济性的减排效果最佳,综合3种减排措施的ODS情景（最优发展情景）是最优发展路径。     

京津冀及周边民用散煤燃烧控制对北京市PM2.5的影响

为评估京津冀及周边“2+26”城市农村居民面源污染控制成效,揭示其对北京市秋冬季重污染天气PM_2.5污染的改善作用,及其对PM_2.5组分硫酸盐形成机制的影响,采用空气质量模型对北京市2018—2019年秋冬季5次重污染事件进行了模拟. 结果表明:①在“2+26”城市平原地区民用散煤削减90%的控制情景下,区域PM_2.5浓度最大值由324 μg/m3降至251 μg/m3,下降了23%. 北京市城区PM_2.5浓度由139 μg/m3降至124 μg/m3,下降了11%;同时,北京市城区SO₂、硫酸盐浓度分别降至6.2、14.9 μg/m3,分别下降了45%、24%. ②农村居民面源污染控制前北京市硫酸盐浓度的正贡献来源主要受水平平流输送过程影响,控制后水平平流输送过程仍起主导作用,但该过程在水平平流输送、垂直平流输送、水平扩散、垂直扩散这4个物理过程中的绝对重要性上升了2%;此外,农村居民面源污染控制后垂直扩散清除过程对硫酸盐浓度的贡献下降了33%,气溶胶二次转化过程的贡献下降了25%,但SO₂向硫酸盐转化的速率加快,其小时转化率上升了1.44%. ③ISAM源解析方法结果表明,控制情景下区域工业过程是影响北京市SO₂浓度的最主要行业源因素,平均贡献率为65%,硫酸盐工业过程源的平均贡献率为82%. 区域来源分析表明,北京市SO₂来源主要为外地源输送,硫酸盐主要来源与SO₂一致,其中河北省贡献较大,其对SO₂、硫酸盐的平均贡献率分别达43%、40%. 研究显示,控制情景下污染期间北京市PM_2.5污染改善,且污染物浓度、形成过程和来源贡献均发生明显变化.      

深圳大气PM2.5化学组成的长期变化特征

为分析深圳市大气细颗粒物（PM_2.5）浓度长期持续下降的原因,进而明确PM_2.5下一步减排潜力和精细化管理方向,本研究基于2019年在深圳市西乡点位采集的PM_2.5样品,分析了西乡PM_2.5的化学组成及季节分布特征.结果表明,2019年西乡点位PM_2.5年均浓度为29.4μg/m³,总体上呈现夏低冬高的季节特征,有机物（OM）和硫酸根（SO₄^2-）仍是主要的组分,分别占总质量的42.3%和17.6%.对2009、2014、2019年典型月份PM_2.5的组分进行对比,PM_2.5全年质量浓度从42.3μg/m³（2009年）下降至24.6μg/m^3.（2019年）,OM、SO₄^2-、硝酸根（NO₃^-）、铵根（NH₄⁺）和元素碳（EC）等都有明显的下降趋势.矿物质元素（Al、Ca）是地面扬尘和建筑尘的标识组分,近年来Al、Ca浓度的增加趋势表明宝安区西乡扬尘的影响在逐渐扩大.2009、2014、2019年OC/EC的值逐渐扩大,说明了一次燃烧源排放的影响逐渐减小,但二次有机物（SOC）的贡献逐渐凸显.通过分析2004、2009、2014、2019年夏、冬季PM_2.5中6种主要组分变化趋势,表明6种主要组分夏冬两季皆有下降趋势,但由于气象因素导致冬季污染物受到区域传输的影响较大,夏季各组分浓度的下降幅度普遍高于冬季.总体来说深圳市PM_2.5浓度持续下降的原因是深圳市对机动车、工业VOC （挥发性有机物）、远洋船舶以及一次燃烧源的管控和减排.     

北京气象塔夏季大气臭氧观测研究

2000年夏季7～8月,以北京325m气象塔为观测平台,分别在8,120,280m高度上进行了大气污染物臭氧(O₃)及其前体物氮氧化物(NO_x)和气象要素加强期的同步观测.对观测资料的分析表明,边界层内存在明显的臭氧浓度垂直差异;低层臭氧浓度呈明显的日变化,且昼夜振幅较大;对O₃浓度与NO₂/NO的比值作线性拟合分析发现,白天(10:00～16:00)O₃浓度与[NO₂/NO]的比值成线性关系,即达到光化学稳定态,但受气象背景场影响较大.     

2015年北京“阅兵蓝”特征及成因探讨

利用大气成分和气象要素观测数据,对2015年8~9月北京田径世锦赛和抗战胜利70周年纪念活动期间的北京PM_2.5浓度变化特征及其相关的大气污染气象条件进行了研究,并采用大气化学数值模式模拟了气象条件、减排措施和区域减排联合行动对北京PM_2.5浓度下降的作用和贡献.结果表明：纪念活动期间北京地区空气质量显著改善,PM_2.5平均浓度仅为18.7μg/m³,比前期8月1~19日下降70%,比2014年同期降低74.0%;东北冷涡长时间稳定少动为空气质量改善提供了良好的大气环流条件,北京地区混合层高度相比前期升高20%,相对湿度降低17%,风速增大7%,气象要素变化为庆祝活动期间PM_2.5浓度下降提供了良好的气象条件,尤其是地面主导风向转为偏北风后,阻止了北京城南及华北中南部地区的污染物输入北京城区;CAMx模式的模拟结果表明,与2014年同期相比,气象条件变化在北京PM_2.5浓度降幅中的贡献率达73%;纪念活动期间有无减排的模拟分析显示,在相同的气象条件下,减排措施使北京PM_2.5浓度下降约33%;期间北京PM_2.5来源以本地排放为主,本地的减排措施对改善空气质量的贡献率约为72%,周边地区减排的贡献率约为28%.