郑州大气PM10的形貌特征及生物活性研究

采集郑州市区和郊区秋季大气PM10样品,利用场发射扫描电镜(FESEM)和图像分析技术对PM10颗粒进行形貌特征和粒度分布进行分析,同时应用质粒DNA评价法研究了市区和郊区PM10样品的生物活性.结果显示,在市区采集的样品中燃煤飞灰占有相当大的数量,而在郊区采集的样品中矿物质占有较大的数量,粒径分析表明,市区PM10的数量-等效球直径分布较为集中,主要分布在0.1～0.4 ìm范围内,郊区则相对比较分散;PM10的体积-等效球直径主要分布在>1ìm范围内.结果表明,在郑州市秋季大气PM10中,数量上细粒子占优势,而在体积上(质量上)较粗颗粒占优势.质粒DNA评价结果表明,郑州市区和郊区PM10;颗粒对DNA的损伤程度不同,市区样品的生物活性大于郊区样品.     

PM_(10)浓度时间序列多时间尺度分析的小波方法

文章利用Morlet小波函数进行小波变换,以乌鲁木齐市的大气污染物时间序列为例,分析了当地PM10的多时间尺度的演变特性。研究结果显示,其年际变化和季节性变化的时间尺度在尺度空间中分布不均匀,受气象和污染源因素影响,具有较明显的局部化特征。     

机动车行驶过程道路扬尘影响因素试验研究

机动车行驶过程道路扬尘是城区颗粒物污染的主要因素,其贡献率可达30％-50％。城市路面积尘是机动车行驶过程道路扬尘的主要尘源。路面尘受机动车车轮积压作用、机车行驶过程诱导气流、热射流等综合尘化作用的影响,再次扬向空中并扩散,造成空气中颗粒污染物TSP、PM10浓度增高。实验模拟单车行驶,研究道路粉尘负荷、车速、排放源距离对总悬浮颗粒物（TSP）、可吸入颗粒物（PM10）浓度的影响,结果显示：TSP、PM10浓度与机动车行驶速度呈显著正相关;同一车速下与路面粉尘负荷呈对数变化规律;与排放源距离呈负相关。     

Sudden high concentration of TSP affected by atmospheric boundary layer in Seoul metropolitan area during duststorm period

Hourly concentrations of TSP, PM(10), PM(2.5) near the surface at Seoul city were examined from March 20 to March 25, 2001 (duststorm event) in order to investigate the effect of a duststorm generated in China on the local aerosol concentration in Korea, The ratios of fine to coarse particles such as TSP to PM(10), TSP to PM(2.5) and PM(10)-PM(2.5) to PM(2.5) showed that a great amount of dust transported from the origin of the duststorm was remarkable with a maximum ratio of 9.77 between TSP and PM(2.5). Back trajectories every 6 h showed the movement of dust particles in the lower atmosphere near 500 m to 1500 m (atmospheric boundary layer), which implied transport from Baotou in inner Mongolia of northern China to the direction of Seoul city in Korea and then the back trajectories passed near the southern border of Mongolia and Baotou through Zengzhou in the midlevels (3000 m) and low levels (500 m) of China, finally reaching Seoul city. So, the TSP concentration at Seoul city was partially influenced by the duststorm, under the prevailing westerly wind and the transported aerosols could influence high concentrations of pollutants of TSP, PM(10) and PM(2.5) in Seoul. The sudden high concentrations of TSP and PM(10) were found for a few hours, especially at 1500 to 1800 LST, March 22. At 1200 LST, before the passage of a cold front through the Korean peninsula, the convective boundary layer (CBL) near Seoul was not shallow, but at 1500 LST, under the frontal passage, the CBL was remarkably thinner (less than 300 m), due to the compression of the boundary layer by the intrusion of cold air. This resulted in the increase of the TSP concentration, even though the mixed layer above maintained almost the same depth. At 1800 LST shortly after the frontal passage, that is, near sunset, the nocturnal cooling of the ground caused air parcels to cool, thereby enhancing the shallower nocturnal surface inversion layer and producing the maximum concentration of TSP of 1388 microg/m(3) near Seoul city.     

Minimizing external indirect health costs due to aerosol population exposure: a case study from Northern Italy

Environmental Agencies require Decision Support Systems, in order to plan Air Quality Policies considering the cost of emission reduction measures and the human health effects (with related social costs). The use of Decision Support Systems is also useful to spread information to general public, explaining the effectiveness of proposed air quality plans. In this paper, a multi-objective approach to control PM10 concentration at a regional level is presented. The problem considers both the internal costs (due to the implementation of emission reduction measures) and the external costs (due to population exposure to high PM10 concentrations). To model PM10 concentrations, a single surrogate model is used for the entire domain, allowing the implementation of a very efficient optimization procedure. The surrogate model is derived through a set of 10 simulations, performed using a Chemistry Transport Model fed with different emission reduction scenarios. The methodology is applied to Northern Italy, a region affected by very high PM10 concentrations that exceed the limit values specified by the EU legislation.     

鞍山市TSP及PM10相关性分析研究

分别在冬季及夏季选取具有典型气候特性的天气,采集空气中TSP和PM10.根据采样前、后滤膜重量之差及采样标况体积,计算TSP质量浓度,分析了TSP和PM10在大气中污染状况,研究了TSP和PM10的相关性及PM10占TSP的比例,并得出结论:在冬、夏二季TSP和PM10的浓度值变化趋势非常相似,在冬季时TSP和PM10...     

东北区域空气质量时空分布特征及重度污染成因分析

东北已成为我国又一个霾污染多发和重发区域.采用2013～2017年东北区域大气污染物地面监测数据、卫星数据和气象数据等信息,探讨了中国东北地区空气质量时空分布特征与重度污染成因.结果表明,"沈阳-长春-哈尔滨"带状城市群是全年污染最严重的区域,空气质量指数(AQI)的空间分布具有明显的季节性,冬季污染最严重,春季吉林省西部周围为椭圆形污染区,夏季和秋季大部分时间空气质量最佳.3个典型的霾污染时期是10月下旬和11月上旬(即秋末和初冬,时期一),12月下旬和1月(即冬季最冷的时候,时期二),及4月到5月中旬(即春季沙尘和农业耕作期).时期一,季节性作物残茬焚烧和冬季采暖用煤燃烧产生的PM_(2.5)强排放是极端霾事件发生的主要原因(AQI 300);时期二,在最严寒月份里,重度霾污染事件(200 AQI 300),主要由燃煤和汽车燃料消耗的PM_(2.5)排放量高,大气边界层较低,以及大气扩散性差等共同引起;时期三,春季PM_(10)浓度较高,主要是由内蒙古中部退化草原的风沙和吉林省西部裸地的区域性扬尘传输造成的.同时,当地农业耕作本身也释放PM_(10),并提升了裸土的人为源矿物尘的排放强度.     

我国主要粮产区PM2.5、PM10时空分布特征及影响因素——以河南省为例

利用2018年河南省PM_2.5、PM₁₀监测数据,结合统计学方法及克里格插值技术,分析河南省PM_2.5、PM₁₀的时空分布特征及影响因素,结果表明:（1）PM_2.5、PM₁₀日均、月均浓度均呈现出“U”型变化特征,PM_2.5/PM₁₀月均值呈现出“W”型变化特征,PM_2.5、PM₁₀季均浓度及其比值均呈现出冬季>秋季>春季>夏季的规律;（2）PM_2.5、PM₁₀月均浓度的空间分布差异较大,而年均浓度则呈现出相似的分布规律,PM_2.5/PM₁₀季均值呈现出不同的空间分布规律,总体上东部及东南部较高,中西部区域较低;（3）PM_2.5、PM₁₀与NDVI、年降水量呈显著负相关,与人口密度、第二产业占比呈显著正相关。研究结论可为粮产区大气污染防治及粮食安全生产提供重要的科学依据。     

沧州市大气污染特征观测研究

利用沧州2009年7月～2011年7月的NOx(NOx=NO+NO2)、O3、SO2以及PM10的观测数据,分析了沧州市大气污染物的日变化、月平均变化、年变化以及季节平均变化特征.结果表明,NOx、PM10日变化为双峰型,O3为单峰.SO2日变化也呈现为双峰型,但是其变化幅度较平缓.NO、NO2、NOx、SO2有较相同的季节变化趋势.NO、NO2、NOx、SO2及PM10冬季值最大,分别为(30.0±18.9)μg·m-3、(50.5±19.8)μg·m-3、(80.5±38.7)μg·m-3、(62.1±34.7)μg·m-3、(201.6±98.5)μg·m-3.臭氧夏季浓度最高,其月均值为(88.0±22.3)μg·m-3.NO、NO2、NOx、O3、SO2及PM10年均值分别为(18.9±14.5)μg·m-3、(37.6±13.0)μg·m-3、(56.5±27.5)μg·m-3、(49.9±16.3)μg·m-3、(31.6±19.5)μg·m-3、(156.7±79.1)μg·m-3.秋冬季污染物主要为NOx(NOx=NO+NO2)、SO2以及PM10,夏季污染物主要为O3.     

北京清洁区大气颗粒物污染特征及长期变化趋势

清洁对照区表征了区域环境的影响,是全面评价城市大气环境质量变化的基础.本研究分析了北京清洁区定陵不同粒径颗粒物质量的历史监测数据,包括1980～2009年大气降尘、1991～2009年总悬浮颗粒物(TSP)、2000～2009年可吸入颗粒物(PM10).结果表明,北京清洁区大气颗粒物总体呈下降趋势,年际短期变化受沙尘天...