公路隧道内运动汽车尾气污染扩散数值仿真研究

利用计算流体力学(CFD)方法,结合标准k-ε湍流模型、Mixture混合多相流模型和动网格技术,数值仿真了公路隧道内运动汽车的尾气污染扩散,结果与实验测量值吻合较好。表明,在没有其他通风方式的公路隧道内,运动汽车排出的污染物主要分布在近地面;运动汽车后方会形成1条高速风带,对隧道内污染物纵向扩散具有关键作用。     

基于轮廓似然函数的PM_(10)极值浓度分析

以R软件为分析工具,选择GEV(generalized extreme value distribution)模型拟合四川省泸州市2003～2007年期间PM10每月最高日平均浓度数据,采用极大似然法估计模型的3个参数即位置参数、尺度参数、形状参数,利用所得的参数估计值计算得出某一标准值(如GB3095—1996)的重现期;进一步利用参数估计值计算轮廓似然函数,估计某一段固定时间间隔的PM10浓度的重现值以及其置信区间。结果表明,GEV模型能很好地拟合泸州市PM10数据,利用轮廓似然函数估计的不同时间间隔的重现值准确度高,统计结果可以为环境主管部门发布污染状况预警信息提供参考。     

成都PM2.5与气象条件的关系及城市空间形态的影响

2013年2月1日至3月20日、2013年7月10日至8月10日对成都市大气中细颗粒物(PM2.5)进行连续监测,同步记录气象数据。将PM2.5质量浓度与城市气象条件进行相关性分析,研究气象条件对PM2.5质量浓度的影响。2月1日至3月20日PM2.5质量浓度平均为147.38μg/m3,7月10日至8月10日平均为50.19μg/m3,大气细颗粒物污染最严重的时间出现在2月1—6日。成都市各气象条件中,PM2.5质量浓度与能见度、风速呈现显著负相关,而与其他气象要素相关性较弱,降水对PM2.5质量浓度影响也很大。改善城市通风有利于成都市大气中PM2.5的稀释和消散。通过建立3D模型并运用计算流体力学(CFD)软件模拟成都市选定的一处密集的建成区域,分析城市空间形态对通风的影响。研究发现,在假设等温的情况下,多层密集的区域对城市通风影响小,而高层对城市通风影响很大,建筑高度相近的街道与风向平行的风速大于与风向成角度的,与风向平行的街道沿线为高层的风速高于沿线为多层的,较大的开敞空间及背景风速更有利于城市通风环境。     

广州大型购物中心室内空气中PM10、CO和CO2的分布和来源特征

利用便携式测量仪,对广州市大型购物中心室内空气中的PM10、CO和CO2等进行了现场测定.结果表明,室内CO2和PM10浓度偏高.CO2全部超出了我国的室内空气标准,PM10全部超出了国家年平均标准,大部分超出了日平均标准.本文同时对购物中心内不同场所CO、CO2和PM10的浓度水平变化和来源特征进行了分析.     

库尔勒市PM_(10)与气象条件的关系

利用库尔勒市2006—2013年的PM10监测数据以及同期常规气象资料,使用非参数分析(spearman秩相关系数)方法分析了常规气象要素与PM10浓度的相关关系。结果表明PM10浓度与各气象要素关系密切:气压较高时,PM10浓度易超过《环境空气质量标准》(GB 3095-2012)二级标准;当气温≥20℃时,温度越高PM10浓度超标天数越少,当气温20℃时,较高的气温则不利于PM10的稀释扩散;温度露点差越小,PM10的超标率越大;PM10浓度随风速的增大先降低后增加;降水对PM10有清除作用。     

上海市郊春季PM10 污染的观测研究

利用上海市郊金山环境监测站2007年春季的逐时PM10和气象参数的观测数据,分析了PM10日平均质量浓度和最大质量浓度的时间变化规律,小时平均质量浓度的分布规律,气象条件对PM10质量浓度的影响,并利用HYSPLIT轨迹模型结合气象观测数据对一次最严重的PM10污染过程进行了分析.结果表明,PM10在春季有11日出现超标,污染比较严重;风和降雨对PM10质量浓度均有较为明显的影响;4月2日监测点PM10日平均和最高质量浓度分别达到0.78 mg/m3和1.0 mg/m3,均为全年最高值,这与北方冷空气携带沙尘南下的影响有关.     

环境空气质量综合指数计算方法比选研究

环境空气质量综合指数是进行逐月城市环境空气质量比较和排序的重要方法,提出了4种涵盖SO2、NO2、PM10、PM2.5、CO、O3等6项污染物的综合指数计算方法,基于2013年74个城市逐月污染物浓度数据使用主成分分析方法进行了对比分析。结果表明,综合指数计算方法中污染物统计指标和标准化方法不同对于主要污染物的判定有重要影响,各种计算方法中PM2.5、PM10、O3是出现频率最多的主要污染物;除O3外其他5项污染物逐月统计指标间均有极显著的正相关性,冬季O3统计指标与SO2、NO2、PM10、PM2.5呈显著负相关,夏季则呈显著正相关;主成分分析结果表明,在去除冗余信息后,PM2.5、PM10的权重被相对削弱,SO2、NO2、CO的权重得到相对强化,O3的权重夏季得到强化、冬季被削弱;综合考虑不同方案下主要污染物频率分布情况和PM2.5、PM10、O3权重变化特征,建议计算逐月环境空气质量综合指数时,SO2、NO2、PM10、PM2.5宜以月均值除以年均值标准进行标准化,CO、O3宜以特定百分位数浓度除以日均值标准(或8 h均值标准)进行标准化;该方法可延伸到季、半年和年度的环境空气质量综合指数计算。     

北京地区PM_(2.5)与空气污染物的关系模型

为了研究北京地区PM2.5与空气污染物的质量浓度关系。从PM2.5监测网收集2013-04-01~2014-05-15期间PM2.5、PM10、SO2、NO2、CO、O3等主要空气污染物数据,用多元线性回归模型建立PM2.5与空气污染物的质量浓度关系。结果表明:北京地区PM2.5与空气污染物PM10、SO2、NO2、CO、O3的质量浓度相关系数分别为0.9172、0.6332、0.7683、0.8166和-0.1797,优化的拟合方程为:[PM2.5]=-22.5925+0.569109×[PM10]+23.94913×[CO]+0.113025×[BPM2.5],模型的估算值与观测值相关系数为0.9426,此方程能较好地模拟北京地区的PM2.5质量浓度。     

珠三角秋冬季节长时间灰霾污染特性与成因

利用珠三角大气超级站2012年10月与2013年1月能见度、不同粒径颗粒物与BC质量浓度、气溶胶光散射系数、O3、相对湿度等在线监测数据,分析秋冬季节2次持续时间超过10 d的长时间灰霾过程污染特性与成因。结果表明,冬季灰霾过程中气溶胶吸光系数和光散射系数对大气总消光系数的贡献分别为13%和67%;PM2.5、PM1占PM10质量浓度分别为66%和39%;较高的PM2.5与BC日均浓度相关系数(R2=0.88)体现了一次排放对颗粒物质量浓度及能见度的显著影响。秋季灰霾过程中气溶胶吸光系数和光散射系数对大气总消光系数的贡献分别为11%和69%,由BC导致的吸光效应较冬季下降了约20%;PM2.5和PM1占PM10质量浓度比例分别为68%和45%,均高于冬季;O3浓度日最大小时值的平均值接近冬季的2倍;二次来源对PM2.5浓度升高和能见度下降起主导作用。来自不同方向的2种气团在珠三角僵持,大气扩散条件差是导致这2次灰霾过程的重要外在条件,应成为灰霾预报预警的重点关注对象。     

2008年春季呼和浩特沙尘天气与TSP和PM_(10)污染的关系

利用TSP和PM10逐时监测数据,对2008年春季呼和浩特市TSP和PM10浓度的变化及其在沙尘天气过程中的相关性进行了分析,结果表明:(1)2008年春季TSP和PM10浓度值多高于国家环境空气质量二级标准,沙尘天气是影响空气环境质量的主要诱因。(2)TSP和PM10浓度在沙尘暴发生当日及前后几天均会有不同程度的增加,且以沙尘天气发生当日浓度最大。TSP和PM10浓度3月份最低,4月份次之,5月份最高。(3)不同沙尘天气过程中,TSP和PM10浓度相差明显,且TSP与PM10/TSP值随沙尘天气强度的增加而增大,PM10在不同沙尘天气过程中均为主要组成成分。(4)沙尘天气过程中TSP与PM10呈线性相关。     

库尔勒市大气颗粒物污染特征与影响因素分析

针对库尔勒市PM 10、PM 2.5年均浓度超标现象,基于市区3个环境监测站2013—2017年的逐时观测数据,分析PM 10、PM 2.5污染特征、成因及其主要影响因素。结果表明:①2013—2017年库尔勒市PM 10年均浓度变化较大且无明显趋势,PM 2.5年均浓度整体呈下降趋势;②季节尺度上,库尔勒市PM 10在每年2—5月呈现高浓度,PM 2.5高浓度期则为10月至翌年5月;③城郊的开发区站PM 10浓度最高,老城区的州政府站PM 2.5浓度最高,在PM 10和PM 2.5的高浓度期空间差异尤其显著;④PM 10与风速显著正相关,来自塔克拉玛干沙漠的风蚀沙尘颗粒物是库尔勒地区颗粒污染物的主要来源;⑤库尔勒市PM 10主要为外源输入,PM 2.5则以城市内源为主,相对湿度、风速、风向、温度等气象条件是影响大气颗粒物浓度及分布的重要因素。     

Aspiration and sampling efficiencies of the TSP and louvered particulate matter inlets

An experimental system was developed for the rapid measurement of the aspiration/transfer efficiency of aerosol samplers in a wind tunnel. We attempted to measure the aspiration and particle transfer characteristics of two inlets commonly used for sampling airborne Particulate Matter (PM): the 'Total Suspended Particulate' or TSP inlet, and the louvered 'dichotomous sampler inlet' typically used in sampling PM10 or PM2.5. We were able to determine the fraction of the external aerosol that enters the inlet and is transferred through it, and hence is available for collection by a filter, or further size fractionation into PM10 or PM2.5. This 'sampling efficiency' was analysed as a function of dimensionless aerodynamic parameters in order to understand the factors governing inlet performance. We found that for the louvered inlet the sampling efficiency increases as the external wind increases. Under all conditions expected in practical use the louvered inlet aspirates sufficient PM to allow either PM10 or PM2.5 to be selected downstream. The TSP inlet's sampling efficiency decreases with increasing external wind, and the TSP inlet is likely to under-sample the coarse end of the PM10 fraction at moderate and high external winds. As this inlet is generally not used with a downstream size fractionator, changes in sampling efficiency directly affect the measured aerosol concentration. We also investigated whether it is possible to dimensionally scale the PM inlets to operate at either higher or lower flow rates, while preserving the same sampling characteristics as the current full-scale, 16.67 L min(-1) versions. In the case of the louvered inlet, our results indicate that scaling to lower flow rates is possible; scaling to higher flow rates was not tested. For the TSP sampler, the sampling efficiency changes if the sampler is scaled to operate at smaller or larger flow rates, leading to unreliable performance.     

Numerical Modeling of Particulate Matter Dispersion from Kerman Cement Plant, Iran

A three dimensional diffusion model has been developed for computing the concentration of PM10 from Kerman Cement Plant, Iran. This model incorporates source-related factors, meteorological factors, surface roughness, and settling particles to estimate pollutant concentration from continuous sources. The study focused on the local environmental impact of Kerman Cement Plant. The performance of the model was found to be in good agreement with measured data; the average absolute percent deviation is 25.53%. In addition, the result of this modeling shows that the PM10 concentration in the ambient air at distances of about 600–1,400 m from the stacks is higher than the WHO guidelines of an annual average of 260 μg/m³.     

Development of monitoring technology for airborne particulate matter

Particulate matter suspended in the air has adverse effects onhuman health. Its level of concentration is an important parameter in evaluating the degree of hazard it poses to the atmosphere. Conventional methods used in measuring particulatematter are often filter-based, which indicates some disadvantagesbecause such a base requires labor and time. In this study, to achieve real-time measurements, a new electrical method was developed for measuring PM10 and PM2.5 concentrations. The basicprinciple is to electrically charge particles passing through thePM inlet using a corona charger and measure the currents createdby charged particles to obtain the number concentration of particulate matter. A new type inlet based on the particle cupimpactor configuration was designed and its performance was evaluated. A unipolar diffusion charger was developed and thecharger's efficiency was determined experimentally in terms ofPn, which represents the penetration through the charger,P, times the average charge number acquired by a particle,n, for different particle sizes. The correlation was constructed between the PM10 (or the PM2.5) mass concentrationsand the electrical currents due to particles, which were chargedby the diffusion charger.     

A Statistical Analysis of Particulate Data Sets for Jawaharlal Nehru Port and Surrounding Harbour Region in India

The concentrations of total suspended particulate matter (TSP) and particulate matter less than 10 microns (PM10) were measured at various locations in a Jawaharlal Nehru port and surrounding harbour region. Meteorological data was also collected to establish the correlation with air pollutant concentration. The results are analysed from the standpoint of monthly and seasonal variations, annual trends as well as meteorological effects. The monthly mean concentration of TSP was in the range of 88.2 to 199.3 microg m(-3). The maximum and minimum-recorded value of PM10 was 135.8 and 20.3 microg m(-3), respectively. The annual average concentration of PM10 was 66.1 microg m(-3). There are clear associations between TSP and PM10 data set at all the measured three sites with a correlation coefficient of 0.89, 0.69 and 0.81, respectively. PM10 data appears to be a constant fraction of the TSP data throughout the year, indicating common influences of meteorology and sources. Particle size analysis showed PM10 to be 47% of the total TSP concentration, which is lower than reported for industrial area and traffic junctions in Mumbai. Anthropogenic sources contribute significantly to the PM10 fraction in an industrial region, while contributions from natural sources are more in a port and harbour area. Statistical analysis of air quality data shows that TSP is strongly correlated with wind speed but weakly correlated with temperature. There appears to be a simple inverse relationship between TSP and wind speed data, indicating the dilution and transport by winds.     

Particulate matter concentration levels during intense haze event in an urban environment

This study assessed concentration levels of particulate matter (PM) in the ambient environment of Ilorin metropolis, Nigeria, during haze episodes. Meteorological data (wind speed and direction, rainfall data, sunshine data, relative humidity and temperature) were obtained. Aerocet 531S particle counter (MetOne Instruments, USA) was used to measure four mass concentration ranges of PM (PM_1.0, PM_2.5, PM₁₀ and the total suspended particles (TSP)) in 10 locations taking into consideration land use patterns. Surfer® version 8 (Golden Software LLC, USA) was used to model the spatial variation of particulate matter concentration levels using kriging interpolation griding method. Human exposure assessment was done using the total respiratory deposition dose (TRDD) estimates and statutory limit breach (SLB) approaches. The appearance of dominating weak southern atmospheric wind flow was observed as wind speed ranged from 0 to 6.811 m/s while solar radiation periods ranged from 0.3 to 3.5 h/day. The relative humidity of the metropolis ranged between 28 and 57%, while daily temperature was 15 to 36 °C. Highest concentration levels of PM measured were 73.4, 562.7, 7066.3 and 9907.8 μg/m³ for PM_1.0, PM_2.5, PM₁₀ and TSP, respectively. Very strong negative correlations existed between the PM concentration levels and microclimatic parameters. Spatial variation of the concentration level as modelled using Surfer® version 8 indicated that particulate concentration level increases from south to north. Concentration levels of PM for the 24-h averaging period were generally above the 24-h threshold limit value set by the regulatory agencies for all the locations.     

河南省五城市环境空气PM_(10)手工标准方法与自动监测法比对分析

在焦作、安阳、开封、三门峡、信阳5个城市开展PM_(10)手工标准方法和自动监测法比对实验,并用相关性和相对偏差对比对结果进行分析和评价。结果表明:12015年5个城市采集的PM_(10)手工和自动监测值均具有良好的相关性。22015年5个城市采集的PM_(10)手工和自动监测值的相对偏差为-19.1%~9.68%;负偏差数据占总数据量的75%。3PM_(10)手工和自动监测值|RD|平均值在中浓度下最小,高浓度下最大,低浓度介于二者之间,说明在高浓度和低浓度时PM_(10)的监测数据质量尤其值得关注。     

克拉玛依市大气PM2.5、PM10污染水平浅析

根据从2012年1月1日至2012年3月30日在同一个监测点取得的PM2.5和PM10监测数据,分析采暖期颗粒物污染水平特征。结果表明,PM2.5浓度和PM10浓度之间高度线性相关;克拉玛依市冬季空气环境中PM2.5是PM10中的主要组成成分;PM2.5浓度在一天内基本保持稳定,而PM10浓度在一天之中的变化幅度较大,峰值出现在中午上下班高峰期。     

基于GIS的石家庄市PM10和PM2.5时空分布研究

利用2018年261个乡镇环境空气自动监测站监测数据,结合GIS空间分析技术,对石家庄市PM10和PM2.5的时空污染特征进行了研究。结果表明,石家庄地区PM10和PM2.5污染的空间分布整体表现为西北部山区好于东南部的平原地区,主城区好于周边县(市、区)的特征。采暖期PM10和PM2.5的污染程度明显重于非采暖期。PM2.5稳定性差于PM10,PM10和PM2.5的稳定性与污染程度具有一定的负相关性,表现出污染越轻的区域稳定性越差。两者的日均值浓度变化在时间序列上呈极强正相关,且污染越重的区域时间相关性越强。与日均值相关性不同,污染程度越轻的区域PM10和PM2.5年均值的线性相关性越强。     

宁波和温州地区夏季大气中不同粒径颗粒物特征分析

对宁波地区北仑和奉化站、温州地区乐清站3个监测点夏季TSP、PM10、PM2.5和PM1.0进行监测,测试分析各种粒径颗粒物浓度水平和粒径分布特征,并通过化学质量平衡(CMB)受体模型对颗粒物进行源解析。监测结果显示,夏季宁波、温州地区TSP和PM10日均浓度为0.049～0.134mg/m3和0.025～0.084mg/m3,均未超过我国环境空气质量二级标准;PM2.5日均浓度为0.007～0.069mg/m3,按美国2006年EPA最新标准限值0.035mg/m3衡量,奉化、乐清、北仑站的超标天数占总监测天数的比例分别为75%、40%和37.5%。粒径分布统计结果显示,3个监测站点PM10占TSP的比例为48.78%～86.96%;PM2.5占TSP的比例为33.33%～72.46%;奉化和乐清监测点PM10中PM2.5和PM1.0的比例平均值在50%以上。源解析结果显示,夏季TSP主要来源于土壤尘,其次是建筑尘和煤烟尘,其贡献率分别为40.70%～55.49%、9.62%～13.64%和5.85%～17.28%。