Mutagenicity of particulate matter fractions in areas under the impact of urban and industrial activities

Organisms in the environment are exposed to a mixture of pollutants. Therefore the purpose of this study was to analyze the mutagenicity of organic and inorganic responses in two fractions of particulates (TSP and PM2.5) and extracts (organic and aqueous). The mutagenicity of organic and aqueous particulate matter extracts from urban-industrial and urban-residential areas was evaluated by Salmonella/microsome assay, through the microsuspension method, using strain TA98 with and without liver metabolization. Additionally, strains YG1021 and YG1024 (nitro-sensitive) were used for organic extracts. Aqueous extracts presented negative responses for mutagenesis and cytotoxicity was detected in 50% of the samples. In these extracts the presence of potential bioavailable metals was identified. All organic extracts presented mutagens with a higher potential associated with PM2.5. This study presents a first characterization of PM2.5 in Brazil, through the Salmonella/microsome assay. The evaluation strategy detected the anthropic influence of groups of compounds characteristically found in urban and industrial areas, even in samples with PM values in accordance with quality standards. Thus, the use of a genotoxic approach in areas under different anthropic influences will favor the adoption of preventive measures in the health/environment relation.     

西安市及周边地区MODIS气溶胶光学厚度与PM10浓度关系模型研究

西安是空气污染监控和防治有代表性的西部大型城市。研究了西安市及周边地区上空气溶胶光学厚度与PM10浓度的关系模型。利用2011—2012年MODIS卫星气溶胶光学厚度（AOD）遥感产品，通过数据匹配，利用地面气象观测站点的能见度数据和相对湿度数据对AOD产品进行垂直标高订正和湿度订正，2项订正显著提高了AOD和地面PM10浓度的相关性，相关系数从0．36提高到0．65，按季节分类统计和订正春至冬四季的相关系数分别为0．57、0．71、0．62和0．87，夏季和冬季的订正更为有效，可用性更高，这可能由于受到不同季节气溶胶来源和特征的影响。为研究中国西部大型城市，特别是西安市空气环境监测和区域联防联控提供了一种有效方法。     

衡山PM_（2.5）中痕量金属元素的分析

建立了微波消解-电感耦合等离子体质谱法同时测定PM2.5中12种痕量金属元素的方法。对不同消解体系进行了讨论,确定采用HNO3＋H2O2消解体系。方法检出限在0.01～6.4 ng/m3之间,精密度为0.5%～8.9%,加标回收率在69.2%～92.6%之间。应用该方法测定了衡山PM2.5中痕量金属元素的含量,讨论了痕量元素的浓度分布特征,对各元素进行了相关性分析,并应用富集因子法对来源进行了分析。     

A new direct thermal desorption-GC/MS method: Organic speciation of ambient particulate matter collected in Golden, BC

Particulate matter having an aerodynamic diameter less than 2.5 μm (PM2.5) is thought to be implicated in a number of medical conditions, including cancer, rheumatoid arthritis, heart attack, and aging. However, very little chemical speciation data is available for the organic fraction of ambient aerosols. A new direct thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS) method was developed for the analysis of the organic fraction of PM2.5. Samples were collected in Golden, British Columbia, over a 15-month period. n-Alkanes constituted 33–98% by mass of the organic compounds identified. PAHs accounted for 1–65% and biomarkers (hopanes and steranes) 1–8% of the organic mass. Annual mean concentrations were: n-alkanes (0.07–1.55 ng m⁻³), 16 PAHs (0.02–1.83 ng m⁻³), and biomarkers (0.02–0.18 ng m⁻³). Daily levels of these organics were 4.89–74.38 ng m⁻³, 0.27–100.24 ng m⁻³, 0.14–4.39 ng m⁻³, respectively. Ratios of organic carbon to elemental carbon (OC/EC) and trends over time were similar to those observed for PM2.5. There was no clear seasonal variation in the distribution of petroleum biomarkers, but elevated levels of other organic species were observed during the winter. Strong correlations between PAHs and EC, and between petroleum biomarkers and EC, suggest a common emission source – most likely motor vehicles and space heating.     

大中型商场PM10、PM2.5污染水平与来源分析

利用便携式气溶胶监测仪,对平顶山市区的中原商场、商业大楼、食品城总店三家大型商场不同楼层空气PM10和PM2.5进行了现场测定。结果显示,平顶山市大中型商场可吸入颗粒物污染严重,PM10、PM2.5污染平均超标率分别为13.7%和48.0%;PM10、PM2.5的质量浓度在时间和空间分布上存在很大差异;PM10中PM2.5所占比例为83%。     

上海市青浦区PM10污染状况及其与气象要素的关系

利用2006-2010年上海市青浦区PM10和同期地面气象要素的监测资料,定量分析PM10的季节变化规律以及PM10与降雨量、大气湿度和风速之间的关系。分析结果表明:PM10浓度在夏季处于低值,冬季处于高值;5mm/d以上的降雨对PM10有显著的清除作用,且春夏季降雨的清除作用大于秋冬季节。PM10浓度与大气湿度基本呈负相关关系。风速在一定范围内有利于PM10的扩散但不至造成扬尘,春夏季节的适宜风速是1.5～3.5m/s,冬季的适宜风速是1.5～2.5m/s。     

区域大气环境中PM2．5／PM10空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM2.5／PM10空间分布的方法，并在2004年12月进行了宁波市全市域PM2.5／PM10空间分布的研究。数据显示：相同路径所代表的地区PM2.5和PM10具有很好的相关性，多数路径上PM2.5与PM10数据的相关系数平方在0．95以上，而不同路径上PM2.5与PM10的比值不同。文中给出了宁波市PM2.5／PM10污染的空间分布图，直观地显示出PM2.5／PM10污染的空间分布情况，突出了污染的重点点位和地区。     

基于BP人工神经网络的城市PM2.5浓度空间预测

针对PM2.5日均质量浓度,采用BP人工神经网络模型,预测研究区空气中PM2.5浓度的空间变异,通过与普通克里格(Ordinary Kriging)插值方法对比验证BP人工神经网络预测模型的精度.结果表明:BP人工神经网络预测模型下研究区检验样本点位置的PM2.5仿真浓度与观测浓度之间的均方差、平均绝对误差、平均相对偏差和相关系数分别为0.296 μg2/m6、0.412 μg/m3、1.650％和0.851;而与此同时,普通克里格插值方法下的对应结果分别为1.041 μg2/m6、0.689 μg/m3、11.910％、0.638.研究成果在肯定BP人工神经网络预测模型可用于揭示PM2.5浓度空间变异特征的同时,也证实了其相对于普通克里格插值方法在固定空间点位准确预测PM2.5浓度方面的优势.     

辽宁省典型城市道路尘PM2.5成分谱研究

为构建辽宁省典型城市道路尘源成分谱，分别采集了鞍山市和盘锦市道路尘样品，分析了其化学组分特征，用富集因子法和比值法分析了其主要来源，用分歧系数法分析了两个城市成分谱的相似度.结果表明：盘锦市和鞍山市道路尘PM_2.5中的化学组成以有机碳组分（OC）和地壳类元素（Al、Ca、Mg、Fe和K）为主.除Cu和V元素外，其余元素均表现为鞍山市的富集因子大于盘锦市.由比值法可得，盘锦市和鞍山市OC/EC分别为（13.20±6.26）和（3.94±0.63），均存在二次污染现象；NO₃^-/SO₄^2-的均值分别为（0.52±0.55）和（0.46±0.13），说明其道路尘PM_2.5受固定源影响更大.盘锦市与鞍山市道路尘成分谱分歧系数为0.354，说明两个源成分谱可能相似.     

Indoor and outdoor PM mass and number concentrations at schools in the Athens area

Simultaneous indoor and outdoor PM₁₀ and PM_2.5 concentration measurements were conducted in seven primary schools in the Athens area. Both gravimetric samplers and continuous monitors were used. Filters were subsequently analyzed for anion species. Moreover ultrafine particles number concentration was monitored continuously indoors and outdoors. Mean 8-hr PM₁₀ concentration was measured equal to 229 ± 182 μg/m³ indoors and 166 ± 133 μg/m³ outdoors. The respective PM_2.5 concentrations were 82 ± 56 μg/m³ indoors and 56 ± 26 μg/m³ outdoors. Ultrafine particles 8-h mean number concentration was measured equal to 24,000 ± 17,900 particles/cm³ indoors and 32,000 ± 14,200 particles/cm³ outdoors. PM₁₀ outdoor concentrations exhibited a greater spatial variability than the corresponding PM_2.5 ones. I/O ratios were close or above 1.00 for PM₁₀ and PM_2.5 and smaller than 1.00 for ultrafine particles. Very high I/O ratios were observed when intense activities took place. The initial results of the chemical analysis showed that accounts for the 6.6 ± 3.5% of the PM₁₀ and for the 3.1 ± 1.4%.The corresponding results for PM_2.5 are 12.0 ± 7.7% for and 3.1 ± 1.9% for . PM_2.5 indoor concentrations were highly correlated with outdoor ones and the regression line had the largest slope and a very low intercept, indicative of no indoor sources of fine particulate . The results of the statistical analysis of indoor and outdoor concentration data support the use of as a proper surrogate for indoor PM of outdoor origin.