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河北廊坊市连续重污染天气的气象条件分析 被引量:54
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作者 郭立平 乔林 +1 位作者 石茗化 王旭光 《干旱气象》 2015年第3期497-504,共8页
利用2013年1月至2014年7月廊坊市空气污染资料及逐小时风向风速、相对湿度、气压等地面自动站观测资料,通过统计学方法对廊坊市该期间发生的17次连续3d及以上重污染天气过程进行分析,结果表明:(1)17次连续重污染天气过程主要发生在... 利用2013年1月至2014年7月廊坊市空气污染资料及逐小时风向风速、相对湿度、气压等地面自动站观测资料,通过统计学方法对廊坊市该期间发生的17次连续3d及以上重污染天气过程进行分析,结果表明:(1)17次连续重污染天气过程主要发生在1~3月和11—12月,1月最多,最长连续时间长达7d;(2)连续重污染天气过程中,首要污染物主要是细颗粒物PM2.5;有高污染浓度持续日和高污染浓度间断分布日2种情况,平均浓度分别达到314μg/m3和193μG/m3,高污染浓度持续日的比例达60%;(3)500hPa高空廊坊市处于高压脊前西北偏西气流中,地面分别位于弱高气压场区及低压场(倒槽)区是连续重污染天气过程最主要的2类配置类型,后者是6级空气严重污染的主要控制形势;(4)连续重污染天气形成的气象条件是:廊坊市地面风向为西南风至偏西风或者为偏东风至东南风,风力≤2级;2—3月|△P3|≤3.0hPa,其余月|△P3|≤2.0hPa;相对湿度在40%-95%之间;日降水量G0.6mm,近地层有逆温层存在,平均高度900hPa以下,厚度≥10hPa,逆温层强度≥1℃;(5)当廊坊市地面处于低压场(倒槽)控制下,逆温层高度在925hPa以下、厚度320hPa及逆温层强度33℃,有利于严重污染天气的形成,若同时廊坊市地面风向为东北风至偏东风、风力为1级,相对湿度350%,则有利于高污染浓度持续日的形成和发展;(6)2014年2月11~15日河北省区域性空气重污染的演变状态及利用美国NOAA的Hysplit-4模式计算得到的空气质点的后向轨迹表明,燕山、太行山山脉的阻挡以及河北省和周边重污染区域分布导致的污染物区域输送是廊坊市连续重污染天气产生的重要因素之一。 展开更多
关键词 连续重污染天气 环流配置特征 气象条件 高污染浓度 成因分析
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Air Pollution Concentration Approach to Potential Area Selection of the Air Quality Monitoring Station in Nakhon Ratchasima Municipality, Thailand 被引量:1
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作者 Patiwat Littidej Sunya Sarapirome Warunee Aunphoklang 《Journal of Environmental Science and Engineering(A)》 2012年第4期484-494,共11页
The purpose of the study is to generate traffic air information system) to determine a proper zone of AQMS (air analyzed were carbon monoxide (CO), and nitrogen oxides (NOx) pollution map using mathematical mode... The purpose of the study is to generate traffic air information system) to determine a proper zone of AQMS (air analyzed were carbon monoxide (CO), and nitrogen oxides (NOx) pollution map using mathematical model and GIS (geographic quality monitoring station) in municipality area. The pollutants which can be harmful to people living in the area. The three steps of mapping process were performed under the GIS environment using the existing vehicle emission rates and pollutant dispersion model. First, traffic volume, road network, and the emission rates of road segments varying with types of vehicle were collected from existing data. Second, the pollutant concentrations were calculated by use of CALINE4, a tool with Gaussian dispersion model. The model parameters include emission rate, wind directions and speeds, ambient temperature and observed pollutant concentration, and atmospheric stability during all seasons from the January 1, 2010 to May 31,2011 with regardless the rainy season. This resulted in concentrations at many receptor points along links of the road network. Third, distributions of pollution concentrations were generated by means of the spatial interpolation of those from receptors. The results of pollution raster-based maps are used for determining frequency of violence and combined pollution map. The resulting frequency of violence and intensity concentration will be further integrated to determine a potential area of AQMS. Finally, achieving pollution potential area of AQMS can be located as helpful basic data for efficient traffic and transportation planning. 展开更多
关键词 Frequency of violence intensity concentration AQMS (air quality monitoring station) dispersion model CALINE4 Nakhon Ratchasima Thailand.
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Magnitude and Trends of High-elevation Cloud Water Pollutant Concentrations and Modeled Deposition Fluxes
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作者 Selma Isil Thomas Lavery +2 位作者 Kristi Gebhart Christopher Rogers Carol Armbrust Wanta 《Journal of Environmental Science and Engineering(B)》 2017年第3期127-143,共17页
Cloud water samples, LWC (Liquid Water Content) and meteorological data were collected at the Clingmans Dome, Tennessee, high-elevation site in Great Smoky Mountains National Park during the warm season from 1994 th... Cloud water samples, LWC (Liquid Water Content) and meteorological data were collected at the Clingmans Dome, Tennessee, high-elevation site in Great Smoky Mountains National Park during the warm season from 1994 through 2011. This paper presents results from 2000 through the conclusion of the study in 2011. Samples were analyzed for SO42", NO3, NH4+ and H+. These measurements were supplemented by measurements of ambient air and precipitation concentrations to estimate dry and wet deposition. Cloud water concentrations, LWC, cloud frequency, various meteorological measurements and information on nearby forest canopy were used to model cloud water deposition to gauge trends in deposition. Total deposition was calculated as the sum of cloud, dry and wet deposition estimates. Concentrations and deposition fluxes declined over the study period. The decreases in cloud water SO42" and NO3 concentrations were 40 percent and 26 percent, respectively. Three-year mean 5042 and NO3 deposition rates decreased by 71 percent and 70 percent, respectively. Trends in concentrations and depositions were comparable with trends in SO2 and NOx emissions from Tennessee Valley Authority power plants and aggregated emission reductions from electric generating units in adjacent states. Back trajectories were simulated with the HYSPLIT model and aggregated over cloud sampling periods from 2000 through 2007 and 2009 through 2011. Trajectories during periods with high H+ concentrations traveled over local EGU (Electric Generating Unit) emission sources in Tennessee and Kentucky to the Ohio River Valley, Alabama and Georgia with the conclusion that these source regions contributed to acidic cloud water deposition at Clingmans Dome. This work was supported by U.S. Environmental Protection Agency and the Tennessee Valley Authority with infrastructure support provided by the National Park Service. 展开更多
关键词 Cloud water acid deposition liquid water content EMISSIONS back trajectory high elevation.
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