枣庄市大气污染现状及防治建议

对枣庄市近几年的环境空气质量进行了全面回顾,研究了污染物的时空变化规律,根据可吸入颗粒物（PM10）源解析结果,明确了主要污染物来源,并发现枣庄市环境空气质量影响因素为能源结构、工业比重不合理,城市扬尘及汽车尾气等。按照环境目标要求,提出了加强扬尘污染防治、加大产业结构调整和工业污染防治力度等措施。     

西宁市城市扬尘污染现状与控制对策

颗粒物 (TSP和PM10 )是西宁市城市空气污染的首要污染物。随着环境管理和污染治理工作的不断加强 ,工业粉尘在颗粒污染物中所占比例在逐年减少 ,而来源于扬尘的颗粒物在颗粒污染物总量中所占的比重却在逐年增加 ,已成为西宁市颗粒物污染的重要因素。文章分析了西宁市扬尘污染的现状、危害和来源 ,并提出了控制城市扬尘污染的几点对策和措施     

二重源解析技术在西宁市PM_（10）来源解析中的应用研究

在西宁市（青海大学、振兴、朝阳、马坊、颐豪、开发区、多巴）采样点采集大气PM10环境样品,针对西宁市颗粒物主要排放源采集土壤尘、建筑水泥尘、燃煤尘等排放源PM10样品,应用二重源解析技术得到了西宁市PM10源解析结果,六类污染源的年总贡献值213.6μg/m3,其中燃煤尘、建筑水泥尘、土壤风沙尘和机动车尾气尘对PM10的年分担率达到了83.2%。     

2020年自贡市主城区PM2.5污染特征及来源解析

PM_2.5主要污染物来源解析对空气质量管理具有十分重要的意义。本研究利用自贡市国控站点气象、大气污染物及PM_2.5组分监测数据,基于颗粒物源解析模型,分析了2020年自贡城区PM_2.5的主要污染特征,识别并量化了PM_2.5的污染来源及贡献。结果表明：自贡城区的PM_2.5年均浓度为43.2μg/m³,按总体贡献度排序,二次源、移动源、扬尘源和工业源是PM_2.5的主要影响因素,时段及季节变化特征明显;春季贡献最大的为移动源和扬尘源,夏季贡献最大的为移动源和工业源,冬季移动源贡献最大。为自贡市城区空气质量管理及控制提供了重要的决策依据。     

乌鲁木齐地区环境空气中TSP达标方案的探讨

TSP是乌鲁木齐市大气污染的首要污染物。根据TSP污染源调查和污染物源解析研究成果，对乌鲁木齐市TSP污染现状和污染物来源进行了分析，在对TSP污染进行科学预测的基础上，根据大气污染控制技术研究成果和污染治理经验。提出了TSP达标规划实施方案。     

2020年第一季度枣庄市PM2.5源解析的分析研究

为了评估分析枣庄市不同来源污染物排放强度削减与大气环境质量变化之间的关系,使用统计方法和正定矩阵因子分解法对枣庄市2020年第一季度大气污染变化特征和污染来源进行了解析,探究了枣庄市大气固体悬浮微粒浓度变化影响机制。结果表明:2020年第一季度PM2.5、PM10、NO2、SO2浓度较2019年同期显著下降,但枣庄市采暖季内社会活动造成的正常排放仍高于大气环境容量;受新冠疫情影响,2020年较2019年PM2.5源因子浓度削减最大的为机动车源(46.5%)和工业源(17.9%),应长期采取机动车减排、产业结构调整等措施,科学规划“十四五”大气污染防治。     

“十二五”南充市城区空气质量变化及污染成因浅析

"十二五"期间,南充市城区空气质量于2014年之后有所改善,2015年达标率为74.37%,同比上年上升7.61个百分点;城区酸雨污染状况不断改善,酸雨频率和酸度逐年下降。城区主要污染物为可吸入颗粒物(PM10)和细颗粒物(PM_(2.5)),根据污染源排放情况,结合2016年3~4月细颗粒物(PM_(2.5))源解析结果,PM_(2.5)的来源主要为机动车尾气、二次无机源、燃煤、工业工艺源、扬尘、生物质燃烧等,严格控制机动车尾气和VOCs排放应为今后首要工作任务。     

炼化企业厂区PM2.5无机元素污染特征及来源研究

为研究炼化企业厂区大气PM2.5无机元素污染特征及其来源,于2015年非采暖期和2016年采暖 期采集两处炼化企业厂区环境空气中PM2.5样品,采用电感耦合等离子体质谱法（ICP-MS）分析其中14种无机 元素质量浓度与富集情况,并通过主成分分析法解析其来源。结果表明：Na、Fe、Ca、K、Mg 5种地壳元素的质 量浓度 ρ（Na）、ρ（Fe）、ρ（Ca）、ρ（K）、ρ（Mg）占PM2.5中14种无机元素质量浓度总量ρＴ的93.4％,V、Cr、Mn、Ni、Cu、Zn、As、Cd、Pb人为活动排放元素的质量浓度占 ρＴ的6.6％。相较于我国主要城市地区,所述炼化企业厂 区PM2.5中 ρ（Cd）、ρ（Cu）、ρ（Fe）、 ρ（Pb）、ρ（Mn）、 ρ（ Ni）、 ρ（Cr）、 ρ（Zn）均较低,说明厂区各污染源并未对所在地 区环境空气造成严重的无机元素污染。厂区PM2.5中Zn、Cd、Cr元素富集因子分别为43.2,38.4,34.4,说明这 些元素受人为活动的影响较为严重。富集因子分析和主成分分析均表明,所述炼化企业厂区PM2.5来源复杂多 样,包括燃煤、机动车尾气排放、土壤扬尘、生物质燃烧、道路扬尘、建筑扬尘、燃煤及垃圾焚烧等,其中燃煤和机动车尾气排放对厂区PM2.5的贡献大于47.97％;土壤扬尘、生物质燃烧、道路扬尘和建筑扬尘对PM2.5的贡献 大于31.36％。     

南昌市颗粒物污染现状、原因及防治对策

2013—2017年南昌市环境空气PM_(10)、PM_(2.5)浓度总体呈逐年下降趋势,2017年,PM_(10)、PM_(2.5)年均浓度分别为76μg/m~3和41μg/m~3。污染主要来源于机动车尾气、燃煤、工艺过程、扬尘、餐饮油烟等,同时还受区域传输和不利扩散气象条件影响。针对南昌市颗粒物污染现状、原因,提出了加强机动车尾气污染防治;加大工业污染源综合治理力度;严控煤炭消费总量,调整燃煤结构;提高城市精细化管理水平,有效控制扬尘污染;加强科学研究及其能力建设的防治对策和建议。     

池州市环境空气中PM10产生的原因及防治对策

正PM10是指环境空气中小于等于10微米的颗粒物,也称可吸入颗粒物。PM10是大气颗粒物中对人体健康威胁最大的一类。同时,PM10还大量吸收可见光使大气能见度降低,对温度和酸雨都有一定的影响。国外学者从20世纪60年代就从不同方面对PM10展开了研究,我国学者从90年代起开始关注PM10。2000年起,我国重点城市陆续开展PM10的日报和预报工作。2003年起,池州市开展主城区环境空气质     

Assessment and management of air quality for an opencast coal mining area

A study for the assessment and management of the air quality was carried out at Lakhanpur area of Ib Valley Coalfield in Orissa state in India. The 24-h average concentrations of total suspended particulate (TSP) matter, respirable particulate matter (PM10), sulphur dioxide (SO2) and oxides of nitrogen (NOx) were monitored during 1 year period. Samplings were done at a regular interval through out the year at 13 monitoring stations in the residential areas and four monitoring stations in the mining/industrial areas. The 24-hr average TSP and PM10 concentrations ranged from 338.8 to 799.8 microg m(-3) and 102.5-425.6 microg m(-3) for industrial area, and 72.3-497.1 microg m(-3) and 40.8-171.9 microg m(-3) for residential area, respectively. During the study period 24-hr and annual average TSP and PM10 concentrations exceeded the respective standards set in the national ambient air quality standard (NAAQS) protocol at most residential and industrial areas. However, 24-hr and annual average concentrations of SO2 and NOx were well within the prescribed limit of NAAQS both in the residential and industrial areas. The annual and 24-hr average concentrations varied from 23.3 to 36.8 microg m(-3) and 16.0-55.2 microg m(-3) for SO2 and 23.9-41.9 microg m(-3) and 19.0-58.1 microg m(-3) for NOx, respectively. The temporal variations of TSP and PM10 fitted polynomial trend with an average correlation coefficient (R2) of 0.77 (+/-0.17) for TSP and 0.85 (+/-0.10) for PM10. On average the PM10 in the ambient air of the mining area constituted 31.94 (+/-1.76)% of the TSP. The linear regression correlation coefficient (R2) between TSP with PM10 and NOx with SO2 was 0.86 (+/-0.12) and 0.57 (+/-0.20), respectively. Maximal concentrations of TSP and PM10 occurred within the mining site based on the kriging technique. A management strategy is formulated for effective control of air pollution at source and other mitigative measures recommended including implementation of green belts around the sensitive areas where the concentration of air pollutants exceeded the standard limit.     

Air quality impact assessment of multiple open pit coal mines in northern Colombia

The coal mining region in northern Colombia is one of the largest open pit mining regions of the world. In 2009, there were 8 mining companies in operation with an approximate coal production of ～70 Mtons/year. Since 2007, the Colombian air quality monitoring network has reported readings that exceed the daily and annual air quality standards for total suspended particulate (TSP) matter and particles with an equivalent aerodynamic diameter smaller than 10 μm (PM??) in nearby villages. This paper describes work carried out in order to establish an appropriate clean air program for this region, based on the Colombian national environmental authority requirement for modeling of TSP and PM(10) dispersion. A TSP and PM?? emission inventory was initially developed, and topographic and meteorological information for the region was collected and analyzed. Using this information, the dispersion of TSP was modeled in ISC3 and AERMOD using meteorological data collected by 3 local stations during 2008 and 2009. The results obtained were compared to actual values measured by the air quality monitoring network. High correlation coefficients (>0.73) were obtained, indicating that the models accurately described the main factors affecting particle dispersion in the region. The model was then used to forecast concentrations of particulate matter for 2010. Based on results from the model, areas within the modeling region were identified as highly, fairly, moderately and marginally polluted according to local regulations. Additionally, the contribution particulate matter to the pollution at each village was estimated. Using these predicted values, the Colombian environmental authority imposed new decontamination measures on the mining companies operating in the region. These measures included the relocation of three villages financed by the mine companies based on forecasted pollution levels.     

泸州市主城区2019年3月至2020年2月大气颗粒物污染特征及防治对策研究

为了解泸州市主城区颗粒物污染变化特征及成因,选取2019年3月至2020年2月空气自动监测数据,运用Origin2017等技术手段对PM2.5与PM10的时间变化特征、污染来源方向以及污染物之间的相关性进行了分析。结果表明:PM2.5与PM10在不同季节的变化趋势均具有较好的一致性,不同站点污染物相关性特征明显。分析表明:泸州市主城区颗粒物污染成因为工业企业排放、机动车尾气、生物质燃烧、燃煤、扬尘以及不利气象条件等,建议对6类污染排放进行管控。     

城市景观格局与大气颗粒物污染的关系研究

随着城市化和工业化发展,大气颗粒物对城市空气环境造成了严重污染,选取西安市作为研究区,分析不同时间和空间尺度下城市景观格局与大气颗粒物污染的关系。通过GIS软件、Fragstats4.2软件和SPSS软件对西安市2014年土地利用数据和2014年整年的大气颗粒物监测数据进行分析,结果显示,西安市土地利用类型分布较为集中;西安市大气颗粒物浓度的空间分布特征为浓度从市中心至城郊呈梯度递减趋势,在整体上呈现西北高于东南的倾向,大气颗粒物污染物浓度峰值基本都集中出现在建设用地范围内(PM10:102.7μg/m^3;PM2.5:99.7μg/m^3);相关性结果证实了城市景观格局与大气颗粒物浓度的空间分布特征。研究结果为中国西部内陆城市大气颗粒物污染控制、土地利用规划以及生态建设提供参考。     

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。     

我国城市大气污染现状与特点

中国城市化和工业化的快速发展与能源消耗的迅速增加，给中国城市带来了很多空气污染问题。20世纪70年代期间，煤烟型污染排放成为中国工业城市的特点；80年代，许多南方城市遭受严重的酸雨危害；近年来，汽车尾气排放的NOx、CO及随后形成的光化学烟雾，使得许多大城市的空气质量恶化。城市空气污染影响着城市居民的健康和城市的发展。为控制空气污染和保护大气环境质量，我国政府已经实施了许多规划。本文概述了当前中国城市特别是重点城市的空气质量状况，描述一些主要城市空气污染物包括总悬浮颗粒、PM10、PM2．5、SO2、酸雨、NOx/NO2的特点。尽管采取了很多应对措施，但目前我国城市的空气质量依然不容乐观，文中还讨论了未来城市空气污染控制面临的问题。     

Analyzing the cost effectiveness of Santiago, Chile's policy of using urban forests to improve air quality

Santiago, Chile has the distinction of having among the worst urban air pollution problems in Latin America. As part of an atmospheric pollution reduction plan, the Santiago Regional Metropolitan government defined an environmental policy goal of using urban forests to remove particulate matter less than 10 microm (PM(10)) in the Gran Santiago area. We used cost effectiveness, or the process of establishing costs and selecting least cost alternatives for obtaining a defined policy goal of PM(10) removal, to analyze this policy goal. For this study, we quantified PM(10) removal by Santiago's urban forests based on socioeconomic strata and using field and real-time pollution and climate data via a dry deposition urban forest effects model. Municipal urban forest management costs were estimated using management cost surveys and Chilean Ministry of Planning and Cooperation documents. Results indicate that managing municipal urban forests (trees, shrubs, and grass whose management is under the jurisdiction of Santiago's 36 municipalities) to remove PM(10) was a cost-effective policy for abating PM(10) based on criteria set by the World Bank. In addition, we compared the cost effectiveness of managing municipal urban forests and street trees to other control policies (e.g. alternative fuels) to abate PM(10) in Santiago and determined that municipal urban forest management efficiency was similar to these other air quality improvement measures.     

大气细粒子(PM2.5)监测技术进展

大气细粒子(PM2.5)的污染对人和生态环境等影响巨大,迫切需要进行PM2.5质量浓度的监测;本文介绍了PM2.5国内外监测研究进展、监测网络应用情况以及监测技术;重点介绍了几种先进的技术:β射线法、振荡天平法和光散射法,并详细描述了各种监测设备的原理及结构,提出最好采用PM2.5在线监测仪进行日常监测。     

基于灰色预测法的空气污染来源及控制对策分析

以2005年~2012年三明市公布的环境空气质量指数为基础,用2005年~2010年的环境空气质量指数数据以改进的灰色预测方法来构建模型。通过对预测值与实际值出现较大差异的地方进行比较和分析,表明大型城建项目、机动车辆爆炸性增长对三明市区的环境空气质量有较大影响。因此针对相应的污染机制和源头提出整治措施,为三明市下一步的环境治理规划的制定提供指导和依据。