道路绿化带内大气PM_(2.5)质量浓度变化特征

为了研究道路绿化带对大气PM2.5质量浓度变化的影响,在靠近五环路的北京市东升公园观测不同林带内PM2.5颗粒物的浓度变化,分析林带内外的PM2.5浓度变化特征以及植被结构配置对其的影响。结果表明,PM2.5颗粒物浓度的日变化基本一致,有明显的起伏,峰值出现在早上8:00和下午18:00,谷值出现在下午16:00左右;林内PM2.5浓度相比道路降低了10.49%,相较于纯林,混交林对PM2.5的阻滞作用更好。气象条件是影响PM2.5浓度的重要因素,在一定的范围内,PM2.5质量浓度随着温度的上升而下降,随着相对湿度的升高而增大。林带宽度对PM2.5的阻滞作用比较复杂,在0~20m林带宽度内,PM2.5浓度呈现上升趋势,在20~50m处,PM2.5浓度呈现下降趋势,50m外趋于稳定。单位面积三维绿量与PM2.5浓度呈负相关关系。     

室内模拟分析8种常绿景观植被对PM_(10)、PM_(2.5)的阻滞作用

为了研究静风、恒温恒湿条件下常绿景观植被对空气中PM_(10)、PM_(2.5)的阻滞作用,在全封闭的1m3室内模拟箱内放入植被,设置对照并监测其中颗粒物质量浓度变化,分析静风条件下8种常绿植被对大气可吸入颗粒物和细颗粒物附着作用差异性和常绿景观植被的空气净化率。结果表明,不同种类常绿景观植被对可吸入颗粒物和细颗粒物阻滞能力存在差异性,8种植被中叶表面附着PM_(10)、PM_(2.5)密度最大的是雪松,分别为0.813μg/cm2和0.689μg/cm2,最小的是大叶黄杨,分别为0.327μg/cm2和0.214μg/cm2。8种常绿景观植被附着PM_(10)、PM_(2.5)能力大小为乔木灌木,具体为松杉柏青扦黄杨。8种植被在静风条件下1m3空间中对PM_(10)、PM_(2.5)的阻滞作用存在时间极限,对PM_(10)阻滞作用的时间极限为7~12h,差异性较大,其中时间最短的是雪松和白皮松,最长的是大叶黄杨;对PM_(2.5)阻滞作用的时间极限为12~14h左右,植被间差异性不明显。8种植被对PM_(10)、PM_(2.5)的净化率范围从3%~15%不等,存在较大差异,其规律与植被附着颗粒物能力规律相似。     

冬春上海市郊外环林带防尘效应的初步研究

对上海市郊外环林带两侧总悬浮颗粒物浓度（简称TSP）和可吸入颗粒物浓度（简称PM10）同步测定表明：林带的防尘效应与风向有关,下风向处的TSP与PM10日均浓度均分别比上风向低19%-44%和39%-61%。林带边粒径分布测定结果表明：下风向处较大粒径颗粒物的相对含量比上风向处小一些;冬季的粒子谱分布呈现较大粒子和较小粒子重量累积百分比较高、中等粒子的重量累积百分比较低的态势;而春季则相反,中等粒子的重量累积百分比较高、较大粒子和较小粒子则比较低。说明冬春不同风向条件下上海市郊的大道旁林带区具有一定的防尘效应。     

西安市区不同绿化植物的滞尘效应季节变化研究

以西安市区乔木(山槐)、灌木(丁香)、草本(马蔺)3种植物为试材,研究比较了滞尘量的差异及蒙尘后的生理响应。结果表明:不同绿化植物的滞尘能力差异显著(p0.05),3种植物平均单位面积滞尘量大小顺序依次为:乔木灌木草本;春季和夏季不同绿化植物叶面滞尘量达到饱和时间约为12d,秋季和冬季不同绿化植物叶面滞尘量达到饱和时间约为9d,并且3种植物叶片平均滞尘量依次表现为夏季春季秋季冬季;对叶面尘粒径分析表明,叶面尘中滞留的颗粒物中大多数是TSP(悬浮颗粒物),同时对PM10和PM2.5均有一定量的吸收,降尘物中PM2.5,PM10和TSP相对含量均以乔木最高,灌木和草本较低,其中PM2.5和PM10在乔木、灌木和草本均达到显著差异水平(p0.05),而3种植物TSP差异并不显著(p0.05);随着叶片蒙尘时间的延长,相对含水量出现先下降后上升的趋势,比叶重和脯氨酸含量则呈现先增加后降低趋势,并且3种植物叶片秋季和冬季相对含水量、比叶重和脯氨酸含量均高于春季和夏季。相关性分析表明,3种植物滞尘能力与车流量呈极显著正相关(p0.01)。     

规模化猪场妊娠母猪舍改进湿帘降温系统的环境特性

为研究湿帘与地道结合的改进湿帘降温系统对妊娠母猪舍的环境特性,该研究采取现场测试的方法,选取河南地区某规模化母猪场妊娠舍为试验猪舍,对该猪舍夏季和冬季舍内热环境和空气质量环境进行测试和分析,结果表明：1）改进湿帘降温系统夏季对新风的平均降温功率增加了?84.4 kW,提高了25%的降温效果;冬季对新风的平均加热功率增加了121.6 kW且舍内无需供暖,87%以上的节能效果发生在地下风道前半程。2）试验猪舍舍内温湿度、风速分布均匀,且舍内温度波动低于3.7 ℃;综合猪舍母猪体感有效温度和呼吸频率等应激程度指标,母猪冬季处于舒适状态,夏季有轻度热应激状态现象。3）夏季和冬季舍内氨气（NH3）、二氧化碳（CO2）、和粉尘（PM2.5和PM10）的质量浓度分布均匀,且均小于国家标准规定的妊娠舍空气污染物浓度极限水平。综上所述,改进湿帘降温系统不仅降低妊娠母猪舍热环境调控的能耗并维持舍内空气质量环境良好,对建立环境友好型规模化母猪场具有积极意义。     

基于GIS的大别山区东段雨季降水空间分布模拟

区域降水量是重要的环境变量,区域降水量的研究对区域水资源合理规划与利用具有重要科学价值。依据大别山区东段及附近14个气象台站和8个气候考察站34a雨季降水和风向等气象资料,以及各站点的经纬度、坡向、海拔高度等地理信息,并引进"主风向效应指数",建立大别山区东段雨季降水分布模拟模型。利用GIS技术进行栅格数据的空间分析,模拟大别山区东段降水空间分布。模拟结果表明,(1)针对不同区域特点,适当增加有效的地形和气象因子参与插值,可以提高山区降水模拟精度,大别山区东段雨季的逐月、夏季和雨季降水空间分布模拟相对误差均小于10%;(2)大别山区东段南北坡雨量分布具有明显的时空变化,边界层山地的扰动作用对降水量分布影响明显,雨量的南北坡的季节变化与大气环流的季节变化一致。     

环首都圈植被分布与可吸入颗粒物的空间相关性

为了分析空气中可吸入颗粒物含量与植被覆盖间的关系,进而为减轻雾霾污染提供依据和参考,该文立足于环首都地区的环境污染程度,对环首都地区的空气可吸入颗粒物进行了相关的研究和分析,建立以环首都地区100 km为单位的圈层,并对该圈层下植被、土壤、环境、地形等重要因子按照不同矩形格网尺度进行划分,并取格网中心点作为研究点。并以环首都地区2013年的植被分布特点和规律为基础,按照矩形格网法通过地统计学Moran’s I法结合SPSS软件非线性回归分析植被分布与空气中可吸入颗粒物浓度间随距离变化的关系。经过Moran’s指数法分析得出环首都地区植被分布与可吸入颗粒物间随着格网尺度的增大而自相关性降低,植被盖度的自相关影响范围是6 620~7 131 m,可吸入颗粒物自相关影响范围是2 998~6 864 m。通过SPSS软件的非线性回归分析得出植被分布与可吸入颗粒物间的空间相关性影响距离是41.87 km,标准误差P均在0.001~0.003之间,相关系数R2均在80%以上,非线性回归模型拟合较好,更好的说明了环首都地区植被分布与环境污染间的空间相关关系,为日后对其他地区的植被与环境污染指数的相关性分析的研究提供了理论依据。     

基于AOD数据的新疆大型露天煤炭开采区PM2.5和PM10反演

MODIS气溶胶产品AOD与PM2.5、PM10浓度高度相关,已广泛应用在PM2.5、PM10浓度模拟.该研究以新疆维吾尔自治区大型露天煤炭开采区准东矿区为研究对象,结合实测的2014年5月、7月、9月、12月PM2.5、PM10质量浓度数据与经过垂直湿度订正的MODIS气溶胶产品AOD,利用多元回归进行拟合建模,从建立的40个模型中选取最优模型并据此对研究区PM2.5、PM10的质量浓度进行定量估算.结果表明:AOD与PM2.5、PM10呈极显著正相关;4个月AOD与PM2.5、PM10质量浓度估算模型最优模型均为多项式模型;其中7月AOD与PM2.5质量浓度拟合模型较好(R2=0.6258),实测值与预测值拟合趋势线R2为0.8057;9月PM10拟合模型效果理想(R2=0.7329),实测值与预测值拟合趋势线R2为0.8077;将AOD代入最优模型反演PM2.5,从空间层面上反映出各区域PM2.5浓度差异明显.研究结果可为AOD的深度利用与PM2.5、PM10浓度的遥感估算提供参考,在大气污染物空间分布、监测大气环境质量、污染预测等方面都具有重要意义.     

大型自然通风奶牛舍空气颗粒物浓度监测方法中采样间隔优化

规模化奶牛养殖产生的颗粒物会对人员和奶牛的呼吸道以及周边环境健康产生不利影响。对于奶牛舍空气颗粒物的实时连续监测,除了监测点数量和位置外,监测设备的采样间隔同样会影响监测结果的准确性。为确定合理的采样间隔,该研究采用环境物联网技术在大型自然通风奶牛舍内共计布置了17个采样点,对秋季至冬季舍内的总悬浮颗粒物(total suspended particulate, TSP)和细颗粒物(PM_2.5)浓度进行连续6个月的实时监测,计算舍内17个采样点的平均浓度(视为“真值”)。基于误差分析法,分别计算了30 min和1、2、3、6、12 h采样间隔下秋季和冬季的颗粒物浓度日均值,以及10、15、20、30 min和1 h采样间隔下白天、夜间与生产管理操作期间的颗粒物浓度小时均值及其与真值的相对误差(E_r),统计了E_r在5%与10%范围内的占比情况,以66.7%作为可接受标准,确定了秋冬季节颗粒物浓度日均值和小时均值的最大可接受采样间隔。结果显示,在5%的相对误差允许范围内,秋冬季节TSP日均值的最大可接受采样间隔为2 h(秋季...     

不同类型植被过滤带拦蓄效率随时间的变化

过滤带建立后,因上部土地利用变化,导致土壤和植被条件发生改变,过滤带功能亦可能会有所变化。美国生态学者就相关问题进行了10 a的试验研究。结果表明,1995~1997年新植草被出流溶液质量浓度逐年下降,新植乔灌草植被的拦蓄效率起初与作物植被相近,随后增大到与老草植被接近,这与植被盖度的增加和径流速度的下降相同,表明入渗量增加引起过滤带功能提高;且新植草被与新植乔灌草植被具有相似的变化规律。由此可见,过滤带在建立后几年中功能的增强主要与土壤的入渗特性变化有关,且建立后10 a草被过滤带与乔灌草植被有着相似的过滤效果。但此项研究模拟降雨强度较小,不能反映整体过滤带的功能,相对大雨强下的结果有待于进一步研究。     

大气环境对育肥猪舍内颗粒物浓度的影响

2014年10月-2015年8月,以北京昌平某猪场3栋育肥猪舍为例,在猪舍内外设置监测点,对猪舍内外空气动力学直径≤2.5μm的颗粒物（PM2.5）、≤10μm的颗粒物（PM10）和≤100μm的颗粒物（TSP）浓度进行周年监测,并将舍外监测数据与昌平国家环境监测数据进行比较分析,以研究探讨大气环境颗粒物浓度对育肥猪舍内环境的影响。试验结果表明,试验期间舍内外PM2.5浓度的变化范围分别为23～245μgm^-3和11～372μgm^-3,PM10浓度变化范围分别为113～1182μgm^-3和25～444μgm^-3,TSP浓度变化范围分别为334～4396μgm^-3和31～742μgm^-3。育肥猪舍内PM10和TSP浓度远高于猪舍外,说明育肥猪舍内PM2.5浓度受大气环境的影响,而育肥猪舍内粒径大于2.5μm的颗粒物主要源于养殖生产活动。     

北京市道路防护林带内外PM2.5质量浓度特征及与气象要素的相关性

以北京市奥林匹克森林公园北侧的北五环路防护林带为研究对象,通过在林带外及林带内布设5处PM2.5质量浓度监测点进行3个月的定位监测,分析北京市道路防护林带内外PM2.5质量浓度特征,并通过建立PM2.5质量浓度与风速、温度、相对湿度等气象要素的相关关系,分析气象要素对PM2.5质量浓度的相关性.结果表明：1）在时间变化规律上,林带内PM2.5质量浓度08：00和12：00相对较高,其他时间段相对较低,18：00后质量浓度又开始增加,林带内PM2.5质量浓度在日变化规律上呈单峰或双峰变化,林带内外PM2.5质量浓度的日变化规律基本一致;2）在空间变化规律上,林带内PM2.5质量浓度水平比林带外相对较高,距北五环路40 m处PM2.5质量浓度值相对其他布置点2、20、30和60m处都高;3）林带内PM2.5质量浓度与风速、温度呈负相关关系,与相对湿度、气压呈正相关关系;4）林带内PM2.5质量浓度与温度的关系可以用幂函数来描述.     

Monitoring of Submicron Particulate Matter Concentrations in the Air of Turin City, Italy. Influence of Traffic-limitations

Several studies have shown the association between ambient particulate matter (PM) and adverse health effects, thus highlighting the need to limit the anthropogenic sources of PM, especially motor vehicle emissions. PM exposure is commonly monitored as mass concentration of PM10 or PM2.5, although increasing toxicity with decreasing aerodynamic diameter has been reported. In the present study an analysis was performed of the concentration and size distribution of airborne PM fractions collected at street level in the city center of Turin, Italy, to verify the usefulness of “ecological” days with traffic limitations. PM levels were determined daily at five different outdoor sites, from Thursday to Tuesday for 7 weeks (five with “ecological” Sunday, two with normal traffic density). Air sampling was performed using a six-channel laser particle counter to determine the number of particles (n°/l) in six size ranges between 0.3 and 10 μm. Climatic conditions and indoor PM levels were also monitored. The PM size distribution was constant for all the samples tested, with the 90% of the particles smaller than 0.5 μm, suggesting that measurements for count are needed in addition to the traditional ones based on the mass. The total number of particles was highly variable comparing days or weeks of monitoring, but much less among the sites of air sampling. The restriction of motor vehicle circulation has not determined any significant effect on PM levels and, in the winter period, PM0.5 peak concentrations were measured also on the ecological days.     

Development and Assessment of Neural Network and Multiple Regression Models in Order to Predict PM10 Levels in a Medium-sized Mediterranean City

Suspended particulate matter is significantly related to the degradation of air quality in urban agglomerations, generating adverse health effects. Therefore, the ability to make accurate predictions of particulate ambient concentrations is important in order to improve public awareness and air quality management. This study aims at developing models using multiple regression and neural network (NN) methods that might produce accurate 24-h predictions of daily average (DA) value of PM10 concentration and at comparatively assessing the above mentioned techniques. Pollution and meteorological data were collected in the urban area of Volos, a medium-sized coastal city in central Greece, whose population and industrialization is continuously increasing. Both models utilize five variables as inputs, which incorporate meteorology (difference between daily maximum and minimum hourly value of ground temperature and DA value of wind speed), persistency in PM10 levels and weekly and annual variation of PM10 concentration. The validation of the models revealed that NN model showed slightly better skills in forecasting PM10 concentrations, as the regression and the NN model can forecast 55 and 61% of the variance of the data, respectively. In addition, several statistical indexes were calculated in order to verify the quality and reliability of the developed models. The results showed that their skill scores are satisfying, presenting minor differences. It was also found that both are capable of predicting the exceedances of the limit value of 50 μg/m³ at a satisfactory level.     

Seasonal Abundance of Particle-Phase Organic Pollutants in an Urban/Industrial Atmosphere

Polycyclic aromatic hydrocarbons (PAHs); their derivatives nitro, and methyl-PAHs; n-alkanes; and organic acids were investigated in the aerosol samples collected during two field campaigns conducted at three sampling stations in an industrialized city in southern Italy. The main sources affecting the atmosphere and its toxicity were investigated by means of the diagnostic ratios of: specific particulate-phase PAHs, marker compounds among nitro-PAHs, alkanes, and acids, the dominant wind direction, daily and seasonal abundance of carcinogenic organic substances. The potential importance of the non-regulated pollutants to assess the air quality was confirmed; in fact the carcinogenic organic compounds showed to have scarce correlation with particulate matter (PM) concentration. An exceptionally high variability of toxic compounds at a daily scale was due to meteorological condition causing periods of extremely high pollution levels.     

The Role of Mucus in Mytella falcata (Orbigny 1842) Gills from Polluted Environments

Water, Air, & Soil Pollution - This paper presents experimental data on particulate matter (PM10 and PM2.5) in the atmosphere of Candiota—South Brazil. Samples were collected using...     

西安市污染气象特征和大气环境容量分析

利用2010年西安市环境监测资料及同期气象资料,分析了3种主要污染物(SO2,NO2,PM10)的时空分布特征以及各种气象条件对城市大气污染的影响;采用A—P值法计算大气环境容量。结果表明:(1)西安市区低空大气全年以较稳定—稳定为主,污染物浓度随稳定度频率的增大而增大;(2)风速对污染物浓度的影响非常显著。随风速增大各污染物浓度相应减小;而在春季大风沙尘天气里,PM10浓度随风速增大而增大;(3)降水对污染物的稀释作用很强,降水量小于1mm时浓度不降反增,大于10mm时稀释作用却相对减弱;(4)受气象条件的综合影响,污染物排放造成环境容量的利用率高甚至出现超负荷现象。     

Concentration Distribution and Bioaccessibility of Trace Elements in Nano and Fine Urban Airborne Particulate Matter: Influence of Particle Size

Trace elements, especially those associated with fine particles in airborne particulate matter (PM), may play an important role in PM adverse health effect. The aim of this paper is to characterize elements in a wide particle size range from nano (57–100 nm) to fine (100–1,000 nm) and to coarse (1,000–10,000 nm) fractions of two urban PM samples collected in Ottawa. Size-selective particle sampling was performed using a micro-orifice uniform deposit impactor, and element concentrations were determined in each different size fraction by inductively coupled plasma-mass spectroscopy. A general trend of increasing element concentration with decreasing aerodynamic diameter was observed for elements V, Mn, Ni, Cu, Zn, Se, and Cd, indicating they were predominately concentrated in the nanoparticle size range. Other elements including Fe, Sr, Mo, Sn, Sb, Ba, and Pb were predominately concentrated in the fine-size range. Increased concentration of elements in the nano and fine particle size range is significant due to their ability to penetrate into the deepest alveolar area of the lungs. This was confirmed by the calculation of median concentration diameters, which were less than 800 nm for most of the investigated elements. Particle size distribution and element correlation analysis suggest that the elements concentrated in the nano- and fine-size fractions originated mainly from vehicular combustion and emission. Long-range airborne transport and soil or road dust resuspension may also contribute. Particle size had an important effect on element bioaccessibility for the studied urban PM samples showing a general trend of increasing element bioaccessibility with decreasing particle size. These results emphasize the importance of acquiring information on nano and/or fine PM-bound elements and their bioaccessibilities for accurate element and PM exposure assessment.     

Toxic Metals (As, Cd, Ni and Pb) and PM2.5 in Air Concentration of a Model Ceramic Cluster

The relationship between ambient concentrations of fine particulate matter and detrimental health effects remains a highly controversial issue. Increased incidence of mortality and morbidity due to cardiopulmonary complications has been associated with elevated levels of urban air particles with an aerodynamic of <2.5 ??m (PM2.5). The main aim of this paper was to present the assessment of the temporal and spatial variations of the PM2.5 fraction and its contents in arsenic, cadmium, nickel and lead in order to identify possible emission sources of these pollutants. Daily ambient aerosol samples (PM2.5) were taken in the province of Castellón from 2008 to 2009. Particle concentration levels were determined by gravimetry, and the As, Cd, Ni and Pb levels in the samples were determined by inductively coupled plasma mass spectroscopy. The season variation of these pollutants differs according to the emission source and the factors involved in dispersion. In the weekly trend, there were no significant differences in levels among sampling sites in relation to the day activity (working vs. non-working) due to chemical pollutants that are found in fine particulate fractions residing in the atmosphere longer than coarse particles, resulting in a more homogeneous concentration of pollutants over time. In order to identify similar behaviour between chemical pollutants and PM2.5, an assessment of the correlation between them was carried out. This behaviour study shows whether the source of contaminants is the same. A statistical analysis of the levels of PM2.5 and the presence of As, Cd, Ni and Pb in the different sampling sites was performed in order to evaluate the influence of the sampling point on the concentrations of these pollutants.