淮南市PM_(2.5)中PAHs污染特征及来源分析

通过采集淮南市6个功能区四季的PM_(2.5)样品,运用GC-MS仪测定样品中PAHs含量并分析其主要来源。结果表明:该市PM_(2.5)中PAHs质量浓度年均值为31.06 ng/m~3,呈现冬季污染程度最重,夏季最轻,采矿区商业区工业区文教区居民区对照区的特征;夏季PAHs以3环和4环为主,春、秋、冬季以4环、5环和6环为主;6个功能区均以4环PAHs为主;PAHs主要来源为煤燃烧、机动车尾气排放、生物质燃烧及焦炉挥发,其中燃煤和机动车尾气污染贡献最大。     

茂名市大气PM_(2.5)在线源解析

于2014年12月31日—2015年1月12日,利用单颗粒气溶胶质谱仪对茂名市大气中PM2.5进行在线监测和分析。结果表明,茂名市大气颗粒物污染来源分布(颗粒数占比)分别为扬尘6%、工业工艺源10.9%、生物质燃烧14.7%、机动车尾气27.5%、燃煤23.4%、二次无机源7.7%和其他9.9%。空气质量从重度污染转为优良天气过程中,机动车尾气的贡献率基本保持在20%以上,而燃煤占比从28.9%降至12.3%;空气质量从优良转为污染天气的过程中,工业工艺源、二次无机源、生物质燃烧、燃煤的占比增加,而机动车尾气占比不断下降。     

流动监测公路上机动车尾气中NO_x浓度分布及对环境大气影响

一、监测技术 机动车尾气是一种流动污染源,与固定污染源有着本质区别。我们利用法国Ac—30M NO_x分析仪对江苏、浙江、安徽省市部分地区公路上机动车尾气中NO_x作流动监测。由于考虑到污染源流动性必然带来污染情况偶然性,给出NO_x浓度都标上当时时间,只对公路长区     

广州市冬季PM_(2.5)污染过程二次水溶性无机离子组分特征

为了解广州地区灰霾天气成因,基于城市超级站,对2013年12月1日—12月8日期间2次灰霾天气过程的水溶性无机离子污染特征进行研究。结果表明:监测期间二次离子(SNA)SO_4~(2-)、NO_3~-、NH_4~+分别占PM_(2.5)质量浓度的15.8%、7.4%、7.0%;2次污染过程SNA对PM_(2.5)贡献显著,机动车排放和燃煤是PM_(2.5)的主要污染来源。广州冬季属于富氨区,2次污染过程都伴随着NH_4~+显著增加,NH_4~+主要以(NH_4)_2SO_4和NH_4NO_3形式存在。     

新疆机动车尾气污染现状及防治对策

本文结合新疆第二次全国污染源普查结果,统计了全区机动车统计数据及主要污染物排放情况,分析了机动车尾气污染的主要原因,提出了相应污染防治对策,为降低我区机动车尾气污染物排放,改善城市环境空气质量,打赢污染防治攻坚战提供参考。     

机动车排气对常州市区大气环境的影响

为弄清机动车排气对常州市区大气环境的影响,该市环境监测中心站于１９９８年夏季选择了具有代表性的７个交通路段和３个交通路口布点对机动车排气中的主要污染物ＣＯ、ＮＯｘ,Ｐｂ等进行监测,结果表明,交通路段和交通路口大气中Ｐｂ污染较轻;针对机动车排气的污染状况,提出了防治建议。     

机动车尾气的污染现状与控制

本文主要研究了机动车尾气的污染现状,对人和城市大气造成的危害,阐述了“十五“期间控制城市机动车尾气污染的有效措施和方法.     

合肥市冬季灰霾天气PM_(2.5)源解析

于2016年12月30日—2017年2月4日,利用单颗粒气溶胶飞行时间质谱仪(SPAMS),对合肥市PM_(2.5)开展来源解析连续监测,共捕捉到4次较为明显的灰霾过程,对颗粒物种类及质谱特征进行了分析。结果显示,监测期间合肥市主要颗粒物成分为元素碳(EC)(31. 9%)、富钾(K)(16. 6%)、有机碳(OC)(16. 0%)及混合碳颗粒(ECOC)(15. 0%)等。主要污染源为机动车尾气源(24. 5%)、工业工艺源(22. 7%)、燃煤源(14. 1%)、二次无机源(13. 5%)等。污染天气发生时,工业工艺源占比上升2. 2个百分点,生物质燃烧和燃煤源占比分别下降1. 7和2. 7个百分点,机动车尾气和扬尘源基本持平,表明此次污染过程主要受到工业工艺源的累积影响。     

江苏省机动车排气污染监控体系探讨

机动车保有量的快速发展使得机动车排气污染已成为江苏省城市大气污染的重要来源。开展在用机动车排气污染的防治工作,建立切实有效的机动车排气污染监控体系刻不容缓。对江苏省机动车监控体系和保障体系的建设内容进行了探讨。     

南京市机动车排气污染现状分析

阐述了南京市机动车发展现状、道路交通现状和机动车污染监测情况，对机动车排放因子、机动车污染、交通干线的污染物日排放特征、机动车源排放污染物的分担率以及机动车尾气污染物排放进行了分析和预测。指出南京市机动车污染状况必须采取有效措施加以控制，并提出了贯彻机动车尾气控制标准，完善污染控制管理机制；重点控制公交、出租和专业物流的机动车污染；严格控制车用油品质量；建立车辆污染数据库；加快道路建设，运用交通综合管理制度削减污染；实施保护区和控制区管理以及实施机动车标志管理等合理化建议。     

对应分析在大气颗粒物源解析中的应用研究

采用对应分析方法定性研究龙岩市大气颗粒物来源问题。结果表明:龙岩市4个监测点位中龙岩市环境监测站的主要污染源为高岭土矿和土壤风沙尘;龙岩学院与闽西职业技术学院的主要污染源为机动车尾气尘、燃煤尘和土壤风沙尘;龙岩师专的主要污染源为燃煤尘、小煤炉尘、水泥成品、水泥厂除尘器集尘和钢铁厂除尘器集尘。该方法能将R型因子分析和Q型因子分析结合起来,综合体现样品和元素之间的关系,为大气颗粒物源解析提供了一种新的途径。     

典型街道环境空气质量分析

根据对深南东路环境空气的监测及车流量、气象条件的调查,分析机动车及气象因素对深圳市环境空气质量的影响。根据分析可知,机动车尾气是深圳市环境空气中污染物的主要来源,但污染程度不断变化的主要原因是风速,深圳市环境空气中污染物浓度与风速有着非常显著的负相关。     

CALRoads模式在上海市典型道路CO扩散预测中的应用

根据上海市市区、郊区典型主干道的气象条件、车流量、车型比例,以及CO小时质量浓度的监测资料,采用CALRoads模式中CALINE4和CAL3QHC模块,对郊区主干道和市区典型路口的适用条件分别进行了验证.结果表明,在稳定的气象条件下,CALINE4模式在模拟周围相对空旷主干道附近的CO质量浓度时,具有较好的结果,将CAL3QHC模式应用于市区典型交叉口,可以得到同监测值相对吻合的模拟结果,但准确性低于郊区.应用CALRoads模型对未来城郊典型道路附近CO高峰小时质量浓度的发展趋势进行了预测,并基于情景分析给出了减少交通污染的对策建议.     

江淮地区秋季一次典型污染过程分析

结合2018年10月15—20日国控站点监测数据、气象资料及激光雷达走航观测结果,对江淮地区一次重度污染过程进行了分析。利用拉格朗日粒子扩散模型和拉格朗日混合单粒子轨迹模型定性分析了区域污染来源,分别基于激光雷达和空气站实测数据提出了外来源占比的估算方法,结合嵌套网格空气质量预报模式(NAQPMS)的源解析结果,对比分析了外来源占比。以淮北市为例,结合NAQPMS和单颗粒气溶胶质谱的PM2.5在线源解析结果,对比分析此次污染过程的行业来源。结果表明,本地污染累积时段,主要以燃煤和机动车尾气混合源为主(占比>70%);受北方污染输送时段,机动尾气占比显著升高,从19.4%(16日00:00)升至66.7%(17日11:00),淮北市、蚌埠市、合肥市3个城市污染物外来输送占比分别为52.2%~70.6%、48.8%~58.8%、41.5%~59.0%。     

Mean Vehicle Speed Distributions for the Spatiotemporal Estimation of Exhaust Emissions

Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality.     

An Integrated Approach to Street Canyon Pollution Modelling

An integrated method for the prediction of the spatial pollution distribution within a street canyon directly from a microscopic traffic simulation model is outlined. The traffic simulation package Paramics is used to model the flow of vehicles in realistic traffic conditions on a real road network. This produces details of the amount of pollutant produced by each vehicle at any given time. The authors calculate the dispersion of the pollutant using a particle tracking diffusion method which is superimposed on a known velocity and turbulence field. This paper shows how these individual components may be integrated to provide a practical street canyon pollution model. The resulting street canyon pollution model provides isoconcentrations of pollutant within the road topography.     

广东省南海市主干道气溶胶中多环芳烃(PAHs)的研究

气溶胶采样点位于广东省南海市桂江路边缘及两侧 ,采集时间为 2 4 h,连续采集三天。使用仪器为国产大体积采样器。同时在公园内设点采样 ,以作背景研究。样品经超声波抽提和层析柱分离得到正构烷烃、芳烃 (AHs)和极性组分等三种有机组分。对 PAHs进行 GC MS分析 ,气溶胶中具有较高含量的芴、菲、蒽、荧蒽、芘、苯并 [a]蒽、、苯并 [b]荧蒽、苯并 [k]荧蒽、苯并 [a]芘、茚并 [1 ,2 ,3-cd]芘、二苯并 [a,h]蒽、苯并 [g,h,i]等。通过 TSP研究认为 ,主干道的机动车排放和扬尘是气溶胶的主要来源 ,气候改变也是 TSP变化的另一重要因素。     

Morphology,microstructure and chemical composition of single inhalable particles in Shanghai,China

The morphology, microstructure, and chemical composition of a variety of particles emitted from coal-fired power plants, steel plants, and vehicle exhausts, which are possible sources of particulate matter (PM) in the atmosphere, were investigated by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) and compared with particle samples collected from urban atmosphere to identify the best footprint or the suitable indicator relating the existence of studied particles and their possible emitters by the morphology, microstructure, and chemical composition of the particles. The investigation indicated that the particles from these three sources are different in morphology, microstructure, and chemical composition. Sphere aggregates were generally the most abundant components, with silicon and aluminum as major elements. The urban air particulate contained particles similar to those observed in the power plant, steel plant, and vehicle exhaust samples suggesting that all three sources are contributing to the pollution in the city.     

杭州市大气PM2.5和PM10污染特征及来源解析

2006年在杭州市两个环境受体点位采集不同季节大气中PM_2.5和PM₁₀样品,同时采集了多种颗粒物源类样品,分析了其质量浓度和多种化学成分,包括21种无机元素、5种无机水溶性离子以及有机碳和元素碳等,并据此构建了杭州市PM_2.5和PM₁₀的源与受体化学成分谱;用化学质量平衡(CMB)受体模型解析其来源。结果表明,杭州市PM_2.5和PM₁₀污染较严重,其年均浓度分别为77.5μg/m³和111.0μg/m³;各主要源类对PM_2.5的贡献率依次为机动车尾气尘21.6%、硫酸盐18.8%、煤烟尘16.7%、燃油尘10.2%、硝酸盐9.9%、土壤尘8.2%、建筑水泥尘4.0%、海盐粒子1.5%。各主要源类对PM₁₀贡献率依次为土壤尘17.0%、机动车尾气尘16.9%、硫酸盐14.3%、煤烟尘13.9%、硝酸盐粒8.2%、建筑水泥尘8.0%、燃油尘5.5%、海盐粒子3.4%、冶金尘3.2%。     

The temporal changes in road stormwater runoff quality and the implications to first flush control in Chongqing, China

This study investigates the quality of stormwater runoff from a driveway in the southwest mountainous urban area of Chongqing, China, from 2010 to 2011. The results showed that the mean concentrations of chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) were 4.1, 2.4, and 2.2 times the grade V levels of the national surface water standard of China. The pollutant concentration peak preceded or synchronized with the rainfall intensity peak and occurred 10 min after the runoff started. The significant high pollutant concentration in the initial stage of the rainfall suggested that first flush control is necessary, especially for the most polluted constitutes, such as total suspended solids, COD, and TN. Three potential pollution sources were identified: the atmospheric dry and wet deposition (TN, NO₃ ^?-N, NH₄ ⁺-N, and DCu), the road sediment and materials (total suspended solids, COD, and TP), and the vehicle emissions (DPb and DZn). Therefore, this study indicates that reductions in road sediments and material pollution and dry and wet deposition should be the priority factors for pollution control of road stormwater runoff in mountainous urban areas.