Evaluation of the temporal variations of air quality in Taipei City, Taiwan, from 1994 to 2003

Data collected from the five air-quality monitoring stations established by the Taiwan Environmental Protection Administration in Taipei City from 1994 to 2003 are analyzed to assess the temporal variations of air quality. Principal component analysis (PCA) is adopted to convert the original measuring pollutants into fewer independent components through linear combinations while still retaining the majority of the variance of the original data set. Two principal components (PCs) are retained together explaining 82.73% of the total variance. PC1, which represents primary pollutants such as CO, NO(x), and SO(2), shows an obvious decrease over the last 10 years. PC2, which represents secondary pollutants such as ozone, displays a yearly increase over the time period when a reduction of primary pollutants is obvious. In order to track down the control measures put forth by the authorities, 47 days of high PM(10) concentrations caused by transboundary transport have been eliminated in analyzing the long-term trend of PM(10) in Taipei City. The temporal variations over the past 10 years show that the moderate peak in O(3) demonstrates a significant upward trend even when the local primary pollutants have been well under control. Monthly variations of PC scores demonstrate that primary pollution is significant from January to April, while ozone increases from April to August. The results of the yearly variations of PC scores show that PM(10) has gradually shifted from a strong correlation with PC1 during the early years to become more related to PC2 in recent years. This implies that after a reduction of primary pollutants, the proportion of secondary aerosols in PM(10) may increase. Thus, reducing the precursor concentrations of secondary aerosols will be an effective way to lower PM(10) concentrations.     

基于LS-SVR、BP-ANN和MLR模型的PM10浓度预测

利用宁东能源化工基地PM10和气象监测数据,分别采用LS-SVR、BP-ANN和传统MLR模型预测PM10浓度变化。结果表明,较BP-ANN模型、MLR模型,LS-SVR模型能更好地刻画PM10浓度与各气象因素间的非线性相依关系,更准确地预测PM10浓度。     

佛山市高明区环境空气污染物变化分析

根据佛山市高明区2007—2012年环境空气监测数据资料,分析该区近6年来空气污染物的变化趋势和影响因素。结果表明,2007—2012年该区空气污染呈现由单一型污染向复合型污染转变,综合污染指数总体上升,污染物以SO2、PM10为主。SO2、NO2浓度呈逐年增长,PM10则呈平稳状态。三者污染浓度最高值均在每年第4季度出现。该区的SO2浓度主要受工业污染源影响;NO2也受工业影响显著,与机动车数量呈正相关;PM10与烟粉尘排放量呈正相关,与降水量呈负相关。因此,改善该区环境空气应着重从控制工业污染源、扬尘污染、机动车排气污染3大方面开展工作。     

郑州市 PM2．5和 PM10质量浓度变化特征分析

根据郑州市2013年PM2．5和PM10颗粒物连续自动监测数据,对郑州市各国控站点的PM2．5和PM10的达标情况、变化趋势等进行探讨分析。结果表明：2013年郑州市PM10和PM2．5的年均质量浓度均超过了新标准规定的年均值二级标准限值。 PM10和PM2．5月均值峰值出现在1月和10月,谷值出现在8月,各月PM2．5的超标天数都大于PM10。PM10和PM2．5冬季的日均值浓度明显高于其他季节,呈双峰型,夜晚浓度整体高于白天;PM2．5春、夏、秋三季日变化呈单峰型,PM10夏季和秋季呈单峰型,春季呈双峰型。 PM2．5和PM10日均值有着非常显著的线性相关关系,PM2．5和PM10浓度的比值（p）10月最高。     

Using the polychaete Arenicola marina to determine toxicity and bioaccumulation of PAHS bound to sediments

Transportation system has contributed significantly to the development of human civilization; on the other hand it has an enormous impact on the ambient air quality in several ways. In this paper the air and noise pollution at selected sites along three sections of National Highway was monitored. Pakistan National Highway Authority has started a Highway Improvement program for rehabilitations and maintenance of National highways to improve the traffic flows, and would ultimately improve the air quality along highways. The ambient air quality and noise level was monitored at nine different locations along these sections of highways to quantify the air pollution. The duration of monitoring at individual location was 72 h. The most of the sampling points were near the urban or village population, schools or hospitals, in order to quantify the air pollution at most affected locations along these roads. A database consisting of information regarding the source of emission, local metrology and air quality may be created to assess the profile of air quality in the area.     

空气质量AQI实时发布的改进探讨

针对《环境空气质量指数(AQI)技术规定(试行)》(HJ 633-2012)中对空气质量AQI实时发布存在的欠缺,从增加颗粒物1 h浓度的AQI分级浓度限值及颗粒物24 h滑动平均值计算方法改进着手,解决PM2.5和PM10的24 h滑动平均值实时延迟、1 h平均值代替24 h滑动平均值偏高等问题。     

Extension of the EUROS Integrated Air Quality Model to Fine Particulate Matter by Coupling to CACM/MADRID 2

The European Operational Smog (EUROS) integrated air quality modelling system has been extended to model fine particulate matter (PM). From an extended literature study, the Caltech Atmospheric Chemistry Mechanism and the Model of Aerosol Dynamics, Reaction, Ionisation and Dissolution were selected and recently coupled to EUROS. Currently, modelling of mass and chemical composition of aerosols in two size fractions (PM_2.5 and PM_10–2.5) is possible. The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, elementary carbon, primary inorganic compounds, primary organic compounds and secondary organic compounds. Calculated PM₁₀ concentrations and chemical composition are presented for two summer months of the year 2003 (1 July to 31 August).     

青岛市区春夏季大气能见度与颗粒物的关系

利用青岛市灰霾综合观测站2012年3月2日-2012年6月7日期间的监测数据,分析了青岛市区大气能见度与不同粒径颗粒物质量浓度的日变化特征,比较了各级别大气能见度下不同粒径颗粒物质量浓度及所占比例的相关性,研究了相对湿度对大气能见度和颗粒物质量浓度相关性的影响.结果表明,监测时段大气能见度与颗粒物质量浓度呈现较好的负相关,每天大气能见度最低值出现在早晨07:00--09:00;剔除相对湿度高于90％的前提下,PM2.5是影响大气能见度的主要因子,随着其在PM1o中所占比例上升,大气能见度级别不断下降,相关系数为-0.84;不同相对湿度区间下,PM2.5对大气能见度的影响最明显,其中,相对湿度为60％ ～ 70％,大气能见度与颗粒物质量浓度之间的相关性最好.     

天津市夏季PM10浓度及组成元素垂直分布特征

通过天津市气象局大气边界层观测站高255 m的气象铁塔,获得了10m、40m、120m和220 m 4个高度共80个PM10样品,分析了PM10的日均质量浓度及其元素的垂直分布特征.结果表明,4个高度处PM10质量浓度时序变化基本一致;PM10质量浓度及其组成元素总量随高度增加递减;10 m、40m和120m3个高度处的PM10质量浓度时间序列分布的相关性较好,组分分歧系数较小,而220 m处的PM10质量浓度时间序列分布与其他3个高度处的相关性较差,组分分歧系数较大.样品中元素质量浓度由高到低依次是Si、Al、Ca、Fe、Na、Mg、K、Zn、Ti、Cu、Mn、Pb、Cr、Ni、Co、V、As、Cd和Hg.其中,Si、Al、Na、K质量分数随高度变化不大;Ca、Fe、Mg质量分数随高度增加递减明显;Zn、Cu、Mn、Pb、Cr在10m、40m和120 m3个高度处质量分数接近,而在220m处明显降低;Ti元素在4个高度处的质量浓度接近,质量分数总体上随高度增加递增;Ni、Co、V、As、Cd、Hg质量分数随高度的变化不同,其中与燃煤有密切关系的Hg在120 m处质量分数明显高于其他高度处,而在220m处最低.Al、Fe、Na、K等元素相对富集因子小于或接近1,其质量浓度与PM10质量浓度时序分布的相关性较好,其中Al、Na相关系数随高度增加显著递减;Zn,Cu、Pb、Cr、As、Ni的相对富集因子显著大于1,其质量浓度与PM10质量浓度时序分布的相关性较差,相关系数随高度增加变化不大.     

衡水市道路交通环境颗粒物污染特性及控制对策研究

针对衡水市机动车污染问题,本文选择衡水市代表性路段,对其进行了实验,如采样点的确定、采样时间和频率、监测方法及标准和使用的实验仪器,得到了结果与分析,如交通环境中PM10和TSP的变化特征、PM10/TSP比值和交通环境中PM10和TSP的影响因素分析,并提出衡水市道路交通环境空气污染控制措施,主要是完善城市交通和城市规划、城市绿化、发展清洁能源、完善管理体制和加强交通管理宣传教育,给出了切实可行的改善和控制措施.