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应用WRF/Chem模拟河南冬季大气颗粒物的区域输送特征   总被引:3,自引:1,他引:3  
基于WRF/Chem模式,设置多组区域排放源的情景实验定量估算河南、京津冀、山东、山西、安徽和江苏、湖北6个区域人为源排放对河南省2015年12月PM_(2.5)和PM_(10)浓度贡献率,并结合气象资料研究3个代表性城市的污染输送特征.结果表明:河南省冬季PM_(2.5)和PM_(10)主要来源为本省排放,平均贡献率分别为54.83%、61.32%.区域污染输送对河南颗粒物的贡献也占有很大比例,京津冀、安徽和江苏、山东、山西以及湖北对PM_(2.5)平均贡献率分别为11.95%、11.69%、7.95%、7.40%、4.30%,对PM_(10)平均贡献率分别为10.42%、10.03%、7.00%、6.89%、3.80%.PM_(2.5)外来输送率比PM_(10)要高,表明细颗粒物比粗颗粒物更易跨区域长距离输送.冬季长持续时间的污染过程大多受静风或小风控制,省内污染贡献最大,过程结束时伴随着大风,周边区域的污染贡献有所增加.不同城市的颗粒物来源与其地理位置、风速、风向等气象条件密切相关.区域污染来源具有复杂性,改善河南省空气质量是需要整个区域共同面对和解决的问题.  相似文献   
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Environmental Science and Pollution Research - The COVID-19 pandemic outbreak posed serious threats not only to global health but also to the worldwide development regime. The experts, economists,...  相似文献   
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In this study, we conducted an observation experiment from May 1 to June 30, 2018 in Zhengzhou, a major city in central China, where ground ozone (O3) pollution has become serious in recent years. The concentrations of O3 and its precursors, as well as H2O2 and meteorological data were obtained from the urban site (Yanchang, YC), suburban (Zhengzhou University, ZZU) and background sites (Ganglishuiku, GLSK). Result showed that the rates of O3 concentration exceeded Chinese National Air Quality Standard Grade II (93.3 ppbv) were 59.0%, 52.5%, and 55.7% at the above three sites with good consistency, respectively, indicating that O3 pollution is a regional problem in Zhengzhou. The daily peak O3 appeared at 15:00–16:00, which was opposite to VOCs, NOx, and CO and consistent with H2O2. The exhaustive statistical analysis of meteorological factors and chemical effects on O3 formation at YC was advanced. The high concentration of precursors, high temperature, low relative humidity, and moderately high wind speed together with the wind direction dominated by south and southeast wind contribute to urban O3 episodes in Zhengzhou. O3 formation analysis showed that reactive alkenes such as isoprene and cis-2-butene contributed most to O3 formation. The VOCs/NOx ratio and smog production model were used to determine O3-VOC-NOx sensitivity. The O3 formation in Zhengzhou during early summer was mainly under VOC-limited and transition regions alternately, which implies that the simultaneous emission reduction of alkenes and NOx is effective in reducing O3 pollution in Zhengzhou.  相似文献   
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为研究郑州冬、春季重度污染期间细颗粒物的组分特征、污染来源、气象影响因素及外来传输影响,基于本地超级站污染监测数据及相关气象要素监测数据对重污染时段进行分析,并对本地污染成因进行探讨.结果表明,2019年1—3月郑州共有426 h达到重度及以上污染水平,首要污染物均为PM2.5.重污染时段碳组分(OC+EC)共占PM2.5的14.6%,OC与EC存在显著相关性,1、2、3月的r值分别为0.72、0.89和0.91,且二者比值多介于2~4之间,表明机动车和燃煤排放是碳组分的主要来源;水溶性离子浓度排序为NO3- > NH4+ > SO42- > Cl- > K+ > Ca2+ > Mg2+ > Na+,SNA(SO42-、NO3-、NH4+)浓度达123.37 μg·m-3,占PM2.5的61.2%,且NO3-占比达30.2%, NO3-/SO42-值为1.98,说明移动源对水溶性组分的贡献大于固定源. PMF受体解析结果按污染源贡献量大小依次为:机动车源(34.9%)、二次源(24.6%)、燃煤源(20.2%)、扬尘源(9.2%)、生物质及烟花爆竹源(8.2%)和工业源(2.9%),机动车和燃煤燃烧是造成大气重污染的主要排放源.气象分析表明,与清洁时段相比,重污染期间大气整体处于有利于颗粒物二次生成和不利于污染扩散的条件下,整体温度偏低(3.2 ℃),相对湿度较高(67%),风速较弱(1.3 m·s-1).除本地污染物的累积外,来自偏东和偏南方向的短距离传输及东北方向中长距离输送(分别占外界传输的36.4%、22.6%和22.0%)也是造成郑州重污染天气的重要原因.  相似文献   
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郑州市冬季VOCs污染特征、来源及健康风险评估   总被引:8,自引:0,他引:8  
采用GC5000在线气相色谱仪于2018年1月8—26日对郑州市城区进行大气环境挥发性有机化合物(VOCs)监测,开展污染特征分析、来源解析和苯系物(BTEX)健康风险评估.结果表明,监测期间郑州市城区TVOC平均浓度为64×10-9,污染期时段平均浓度为84×10-9,约是非污染时段的2倍;组分构成显示烷烃占比最大,其次是烯炔烃和芳香烃;源解析结果显示,VOCs主要来源是液化石油气/天然气(25%)、机动车尾气(24%)、燃烧(21%)、工业排放(16%)和溶剂使用(14%);监测期间苯系物非致癌风险危害值(HQ)在美国环保署规定的安全范围内,苯的致癌风险(R)为2.2×10-6,超过了美国环保署规定的安全阈值(1.0×10-6).对成年人存在致癌风险,需要引起关注.  相似文献   
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2018年汾渭平原及其周边地区大气颗粒物的传输特征   总被引:6,自引:0,他引:6  
煤炭产业的集中使汾渭平原及其周边地区成为中国大气污染新高地.本研究基于FLEXPART-WRF模式,数值模拟了2018年三门峡、西安和郑州粒子逐日72 h后向轨迹,并利用停留时间分析方法(RTA)分析了在不同城市、不同季节和不同污染程度的情况下大气颗粒物在水平和垂直方向的传输特征.结果表明,秋冬季汾渭平原及其周边地区存在偏西和偏东北两条主要的传输路径,偏西路径是源自关中平原西部的粒子沿秦岭向东的传输,偏东北路径为来源于京津冀及其周边地区的粒子沿太行山向西南的传输.由于地形等因素的影响,到达西安的粒子水平传输距离最短,其次是三门峡,到达郑州的粒子传输距离最长,重污染期间三门峡的垂直传输高度最高,其次是西安,郑州最低.秋冬季重污染期间汾渭平原及其周边地区水平传输距离r≤100 km,垂直传输高度在300 m<h≤900 m的粒子占主导,春季重污染期间传输距离r≤200 km,垂直传输高度在300 m<h≤900 m的粒子占主导.2017年和2018年重污染期间,粒子穿越边界层的概率偏低.  相似文献   
7.
A distinctive kind of organic carbon aerosol that could absorb ultraviolet-visible radiation is called brown carbon (BrC), which has an important positive influence on radiative budget and climate change. In this work, we reported the absorption properties and potential source of BrC based on a seven-wavelength aethalometer in the winter of 2018–2019 at an urban site of Sanmenxia in Fenwei Plain in central China. Specifically, the mean value of BrC absorption coefficient was 59.6 ± 36.0 Mm?1 at 370 nm and contributed 37.7% to total absorption, which made a significant impact on visibility and regional environment. Absorption coefficients of BrC showed double-peak pattern, and BrC had shown small fluctuations under haze days compared with clean days. As for the sources of BrC, BrC absorption coefficients expressed strong correlations with element carbon aerosols and primary organic carbon aerosols, indicating that most of BrC originated from primary emissions. The linear correlations between trace metal elements (K, As, Fe, Mn, Zn, and Pb) and BrC absorption coefficients further referred that the major sources of BrC were primary emissions, like coal burning, biomass burning, and vehicle emissions. The moderate relationship between BrC absorption coefficients and secondary organic aerosols suggested that secondary production of BrC also played an important role. The 120 hr backward air mass trajectories analysis and concentration-weighted trajectories analysis were also used to investigate potential sources of BrC in and around this area, which inferred most parts of BrC were derived from local emissions.  相似文献   
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