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杭州城区春节PM2.5中水溶性离子在线观测   总被引:5,自引:4,他引:1  
利用大气细颗粒物水溶性组分在线连续监测分析系统(AIM-URG9000D),考察了杭州城区春节期间PM2.5中无机水溶性离子的浓度变化范围,探讨了这些离子的日变化特征和影响因素,同时分析了集中燃放烟花爆竹对水溶性离子浓度的影响。结果表明,SO42-、NO3-、NH4+是PM2.5中水溶性离子的主要成分,分别占全部水溶性组分的33.3%、28.4%、19.4%;强致癌物质NO2-浓度为2.07 μg/m3,远大于膜采样结果;NO3-与SO42-的质量比为0.85,表明机动车尾气排放导致的大气污染正逐步加重;各水溶性离子有着各自不同的日变化规律。相关性分析表明,NH4+与NO3-、SO42-的相关系数分别为0.92、0.81;K+、Cl-、Mg2+3者之间的相关系数均在0.9以上。烟花爆竹燃放期间,PM2.5浓度急剧上升,Cl-、SO42-、K+、Mg2+浓度分别达到燃放前的18、6、53、76倍。  相似文献
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珠三角地区不同季节颗粒物数谱分布特性   总被引:2,自引:1,他引:1  
基于珠三角大气超级站不同季节3 nm~10μm颗粒物数谱分布在线监测数据,系统分析不同季节颗粒物数浓度、表面积浓度与体积浓度的水平与构成及数谱分布日变化规律,揭示了珠三角地区颗粒物数谱分布特征。结果表明,冬季、春季和秋季珠三角大气超级站总颗粒物数浓度分别为2.17×104、1.97×104、2.24×104个/立方厘米,总颗粒物表面积浓度分别为2.98×103、2.28×103、2.78×103μm2/cm3,总颗粒物体积浓度分别为1.33×102、1.04×102、1.40×102μm3/cm3。颗粒物总数浓度中,爱根核模和积聚模态颗粒物是主要贡献者,在总数浓度的比例均达到40%以上;总颗粒物表面积浓度中,积聚模态颗粒物是主要贡献者,月平均比例高达88%以上;总颗粒物体积浓度中,积聚模态颗粒物也是主要贡献者,月平均贡献为65%~80%,其次为粗粒子模贡献较大,比例为20%~30%。积聚模态颗粒物的重要贡献较好地体现了超级站的区域性。冬季、春季和秋季颗粒物数浓度平均日变化趋势均为7:00~9:00和18:00~20:00存在较高的爱根核模态颗粒物数浓度,意味着机动车排放对细颗粒物污染的影响较显著。10月颗粒物数谱分布平均日变化中存在明显的颗粒物增长过程,体现了新粒子生成事件的重要影响。  相似文献
3.
提出了一种能自动连续监测CH4、CO2、TOC日变化及垂直分布的系统,利用该系统监测了2002年冬季CH4、CO2、TOC垂直分布的日变化的变化趋势.结果发现,距地面高度增加,受湍流扩散的影响,CH4、CO2、TOC浓度降低.冬季CH4浓度的日变化呈现明显的单峰周期变化,CO2日变化呈双峰形分布,TOC日变化没有明显的特征,其日变化受机动车尾气排放的影响很大.根据2002年冬季CO2浓度与2000年以前的对比结果发现,北京市冬季燃煤排放的污染物已处于一个相对稳定期,而随着北京市机动车保有量迅速增加,尾气排放成为影响某些大气微量气体日变化的主要因素.  相似文献
4.
为研究株洲市夏季优良天气下大气中气态总汞(TGM)的浓度特征,于2013年8月利用大气汞分析仪(2537X,加拿大)进行了20 d的连续在线观测。结果显示,实验期间株洲市大气TGM的平均浓度为(4.20±3.37)ng/m3,中值浓度为3.40 ng/m3,高于背景地区和沿海城市,略低于国内其他重点城市。晴天、阴雨天TGM浓度分别为3.59、7.96 ng/m3。晴天TGM浓度具有一定日变化规律,最高值出现在早上7:00~9:00,之后逐渐降低,17:00出现最低值;TGM白天和夜间浓度分别为3.57、3.62 ng/m3,昼夜变化不大。晴天TGM与一次污染物SO2、CO、NO2具有显著的正相关性,与O3呈显著负相关性。株洲市夏季主导风向为东南风,该方向没有明显污染源,西北方向风向频率较低,但TGM浓度明显升高,其主要来源可能是位于西北方向的清水塘工业区。  相似文献
5.
对2005年北京大气中异戊二烯进行了一年的观测分析。结果表明,异戊二烯体积分数年平均值为0.58×10-9,月平均值为0.1×10-9~1.8×10-9,7月最高,1月最低。春、秋、冬三季,异戊二烯日变化形式呈三峰形,分别在14:00、18:00、02:00;18:00、02:00、08:00;02:00、10:00、16:00出现峰值;夏季异戊二烯体积分数日变化呈现白天高夜晚低且在14:00出现峰值。夏季异戊二烯源排放主要由生物排放控制,其日变化形式受温度、辐射影响大;春季和秋季异戊二烯源排放受汽车尾气和生物排放共同控制,其日变化形式受汽车尾气影响大,温度、辐射也有一定影响;冬季异戊二烯源排放主要由汽车尾气控制,其日变化形式主要受汽车尾气影响。不同季节北京大气中的异戊二烯体积分数日变化形式与PM2.5浓度日变化形式大致相同。  相似文献
6.
利用深圳自动气象站的气象要素和深圳大气成分监测系统采集的大气成分数据,分析了深圳城区和郊区灰霾季节变化、日变化差异和不同风向下污染物浓度差异,结果表明,城区由于人类活动频繁导致灰霾日比郊区多,以轻微灰霾偏多为主。秋、冬季城区冷空气活动频繁、能源消耗大,灰霾出现频率是郊区的1~2倍;春季冷空气和海上暖湿气流容易形成对峙,沿海颗粒物更容易吸湿增长,郊区灰霾频率反而比城区高25%;夏季对流强、降水频密,城郊差异最小。城区灰霾频率受早晚交通高峰期影响,日变化呈双峰型。而郊区受太阳辐射和光化学反应影响大,呈单峰型。偏北风条件下污染物浓度明显升高,偏南风带来的清洁空气使得颗粒物浓度降幅明显。  相似文献
7.
The diurnal variation of atmospheric carbonyls and VOCs in a forest in south China were studied in summer 2004. Twenty kinds of carbonyls and eight kinds of VOCs were identified and quantified. Formaldehyde and acetaldehyde were the two most abundant carbonyls, while the most abundant VOCs were isoprene, followed by o-xylene. Most C3-C10 carbonyls had higher concentrations from 09:00 to 15:00, and their levels were lower during night-time and often reached the lowest in early morning. Formaldehyde and acetaldehyde, however, showed two high levels in their diurnal patterns partly due to their different sources and sinks. The VOCs had different diurnal patterns compared to most carbonyls. The highest concentrations were observed from 03:00 to 06:00 for 1-butene, from 06:00 to 12:00 for isoprene, and from 12:00 to 15:00 for α-pinene. The highest levels for aromatic hydrocarbons occurred during midnight and the lowest in late afternoon. According to the study, emissions from vegetation and photo-oxidation of gas-phase hydrocarbons were the main sources for some carbonyls and VOCs in this region. Other compounds, such as formaldehyde, acetaldehyde and BTEX, showed anthropogenic sources.  相似文献
8.
Stratospheric input and photochemical ozone formation in the troposphere are the two main sources determining the ozone levels in the surface layer of the atmosphere. Because of the importance of ozone in controlling the atmospheric chemistry and its decisive role in the heat balance of atmosphere, leading to climate change, the examination of its formation and destruction are of great interest. This study characterized the distribution of Ground level Ozone (GLO) in Chandrapur district is lying between 19°25′N to 20°45′N and 78°50′E to 80°10′E. Continuous ozone analyzer was used to quantify GLO at thirteen locations fixed by Global Positioning System (GPS) during the winter of 2005–2006. The daily GLO at all the locations ranged between 6.4 and 24.8 ppbv with an average and standard deviation of 14.9 ± 6.5 ppbv. The maximum and minimum concentration occurs during 1300–1600 h and 0300–0500 h may be due to high solar radiation facilitating photochemical production of O3 and downward mixing from the overlying air mass and in situ destruction of ozone by deposition and/or the reaction between O3 and NO. GIS based spatial distribution of GLO in Chandrapur district is indicates that the central core of the district and southern sites experienced elevated levels of GLO relative to the northern and western areas. The sites near by Chandrapur city are particularly affected by elevated GLO. The average variation of GLO with temperature shows a significant correlation of r = 0.55 indicating a direct relationship between GLO and temperature. Similarly an attempt has been made to compare the GLO monitored data in Chandrapur district with the reported values for other locations in Indian cities. This generated database helps regulatory agencies to identify locations where the natural resources and human health could be at risk.  相似文献
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