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1.
米泉市大气污染与气象因子变化特征分析   总被引:3,自引:0,他引:3  
通过对米泉市大气污染状况进行分析,揭示大气污染与其所处的地理特征、气象特征的关系,并对大气污染物TSP、降尘污染与气象因子变化特征进行分析,进一步阐述尘污染是影响米泉市大气环境质量的重要指标。  相似文献   

2.
依据唐山市大气中TSP、PMl0监测数据、TSP源解析研究结果、对比实验结果及气象资料,分析了唐山市中心区大气颗粒物的结构组成和时空变化规律、颗粒物的粒径与空间分布及天气背景与大气颗粒物浓度的关系,得出唐山市中心区大气颗粒物的结构组成和污染特征,并提出了污染控制对策。  相似文献   

3.
唐山市"九五"期间大气环境中SO2、NOX、TSP污染状况分析   总被引:2,自引:0,他引:2  
根据唐山市大气环境污染特点,对主要污染指标SO2、NO、TSP进行了污染状况分析。结果表明,3项污染指标的平均值均超过国家环境空气质量二级标准。  相似文献   

4.
唐山市空气中SO2与TSP污染状况分析   总被引:1,自引:0,他引:1  
分析了唐山市从1988年至1992年大气中SO2和TSP的污染状况和变化规律,取得对该市环境管理的科学依据。  相似文献   

5.
沙尘暴是造成金昌市TSP污染的主要原因   总被引:2,自引:0,他引:2  
通过分析金昌市环境空气质量现状,提出了环境空气主要污染物为TSP,阐明了沙尘暴是导致环境空气中TSP污染严重的主要原因,提出了控制沙尘暴的对策及建议。  相似文献   

6.
根据米泉市大气环境污染特点,对主要污染因子SO2、NO2、TSP的污染状况及近五年的发展趋势进行了分析,同时也分析了米泉市大气污染成份的成因和来源.  相似文献   

7.
沙尘暴对金昌市环境空气质量的影响及控制对策   总被引:3,自引:1,他引:3  
通过对金昌市环境空气质量现状的分析,指出了环境空气主要污染物为TSP,阐明了沙尘暴是导致环境空气中TSP污染严重的主要原因,并提出了控制沙尘暴的对策及建议。  相似文献   

8.
唐山市钢铁行业大气污染物排放清单建立   总被引:1,自引:1,他引:0  
以唐山市钢铁企业为研究对象,在收集已有排放源数据的基础上,基于排放因子和活动水平数据采用排放因子法估算了唐山市钢铁企业多个大气污染物的排放量,得到了符合空气质量模型要求的污染源输入数据,建立钢铁行业和主要防控因子污染源数据库。结合唐山市各县区的环境空气质量状况,利用GIS技术,将不同污染因子的排放进行空间分布,最终形成准确完善的多尺度、高时空分辨率大气污染源排放清单。研究介绍了符合中国特色的区域高分辨率大气排放源清单建立的方法体系,为京津冀地区区域大气污染联防联控及2020年大气污染物区域削减计划工作提供数据支撑。  相似文献   

9.
报道了利用需氧菌、溶血性链球菌、绿脓干菌及真菌等微生物指标测定大气污染的结果.经统计学分析,需氧菌类浓度与有害的大气污染物TSP与SO_2有正相关性.在此基础上监测了南京地区不同功能区的大气污染,对其环境质量作出空气清洁度评价,评价结果显示出该城市地区不同生态环境条件,不同功能的大气采样点,存在着不同程序的污染,市区50%为清洁空气,50%已受到了不同程度的污染,其中有10%已被严重污染;郊区以清洁空气为主,占88.4%.  相似文献   

10.
根据伊宁市大气污染特点,通过对2001~2004年伊宁市大气中主要污染物SO2、NO2、TSP的变化状况进行分析,为了解和掌握伊宁市大气质量状况提供科学依据.  相似文献   

11.
Air pollution is one of the most important environmental problems in Balikesir, situated in the western part of Turkey, during the winter periods. The unfavorable climate as well as the city’s topography, and inappropriate fuel usage cause serious air pollution problems. The air pollutant concentrations in the city have a close relationship with meteorological parameters. In the present study, the relationship between daily average total suspended particulate (TSP) and sulphur dioxide (SO2) concentrations measured between 1999–2005 winter seasons were correlated with meteorological factors, such as wind speed, temperature, relative humidity and pressure. This statistical analysis was achieved using the stepwise multiple linear regression method. According to the results obtained through the analysis, higher TSP and SO2 concentrations are strongly related to colder temperatures, lower wind speed, higher atmospheric pressure and higher relative humidity. The statistical models of SO2 and TSP gave correlation coefficient values (R 2) of 0.735 and 0.656, respectively.  相似文献   

12.
In recent years, due to the rapid increase in population density, building density and energy consumption, the outdoor air quality has deteriorated in the crowded urban areas of Turkey. Elaz?? city, which is located in the east Anatolia region of Turkey, is also influenced by air pollutants. In the present study, relationship between monitored air pollutant concentrations such as SO2 and the total suspended particles (TSP) data and meteorological factors such as wind speed, temperature, relative humidity, solar radiation and atmospheric pressure was investigated in months of October, November, December, January, February, and March during the period of 3 years (2003, 2004 and 2005) for Elaz?? city. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elaz?? city. The correlation between the previous day’s SO2, TSP concentrations and actual concentrations of these pollutants on that day was investigated and the coefficient of determination R2 was found to be 0.64 and 0.54, respectively. The statistical models of SO2 and TSP including all of meteorological parameters gave R2 of 0.20 and 0.12, respectively. Further, in order to develop this model, previous day’s SO2 and TSP concentrations were added to the equations. The new model for SO2 and TSP was improved considerably with R2?=?0.74 and 0.61, respectively.  相似文献   

13.
河北省火电企业吨煤烟气排放量测定及污染动态预测   总被引:2,自引:2,他引:0  
火电企业大气污染动态预测是大气污染控制的基础。采用现场实测法,对河北省36家火电企业101台机组锅炉进行现场监测,经统计分析给出不同装机容量吨煤烟气排放量,并与其他方法进行了比较,发现实测结果更为合理。在此基础上,建立吨煤SO2、NOx,烟尘排放量和烟气浓度的关系,为火电企业大气污染动态预测提供新的公式,对定量测定火电企业污染物排放提供参考。  相似文献   

14.
The Keelung port, which is located on the northern tip of Taiwan, right next to the Taipei metropolitan area, is an important international harbor. However, any air pollutants generated from the Keelung port region, immediately travel to the neighboring Keelung city, and greatly impact the residents' daily life and the quality of their environment. This study has investigated and quantified pollution emissions, from the Keelung port region, between 1997 and 2002. Emissions from major air pollution sources were estimated. The estimated results indicated that total TSP (total suspended particles) emissions had significantly increased, from 5221 ton/yr in 1997 to 262 687 ton/yr in 2002, due to the greatly increased volume of sand imported into Keelung Harbor. Quantities of other emissions, such as SO2, NO2, CO and HC remained stable and were 440, 207, 78 and 25 ton/yr, respectively, on average, with variations within 7% over the previous six-year period. By examining the emissions from pollution sources, it was found that TSP emissions mainly originated from re-suspension of dust, due to both vehicle movement and the sand unloading process; this accounted for over 99% of the total TSP emissions produced in the port region. About 80% of the total SO2 emissions originated from the main ships' engines within the Keelung port region, due to the use of fuel with a high sulfur content. In addition, loading/unloading machines within the port region were the major sources of NO2, CO and HC pollution emissions, which comprised 54, 58 and 66% of the total emissions of these pollutants, respectively. TSP emissions from Keelung port were much higher than from the neighboring Keelung city; hence, alleviating TSP emissions should be the first priority for air pollution reduction within both the port of Keelung and Keelung city.  相似文献   

15.
李军 《干旱环境监测》2004,18(2):75-78,87
对遵义市1996-2001年TSP和FD为代表的尘污染情况进行了比较分析,结果显示TSP与FD之间缺乏相关性,同时确立了减少工业区排放控制TSP,加强局地扬尘管理控制FD的遵义市尘污染的防治思路,并依此提出了系列防治对策。  相似文献   

16.
This paper examines the significant differences in seasonal variations of criteria pollutant concentrations in various parts of a large urban area. These differences are caused by the microclimatic heterogeneity of the city and show the influence of breeze and orographic-type circulations on urban air pollution. The temperature heterogeneity of Krasnoyarsk territory during the winter leads to an increase of 150% in CO air pollution levels in the central part of city. During the summer the orographical heterogeneity of Krasnoyarsk City leads to increases of up to 400% in air pollution for different areas.  相似文献   

17.
北方某市环境空气颗粒物中重金属污染状况研究   总被引:5,自引:4,他引:1  
对我国北方某市大气颗粒物的污染状况进行了研究。在主导风向上设置采样点,于冬季、夏季分别采集TSP、PM10、PM2.5 3种不同动力学直径的大气颗粒物。采用ICP-MS对TSP、PM10、PM2.5中的元素浓度进行分析,并对3种不同粒径颗粒物中的10种重金属采用富集因子法进行评价。结果表明,北方某市环境空气颗粒物中富集程度最严重的为Cd、Pb;在采暖期,随着颗粒物粒径变小,Pb、Cd的富集指数呈现逐渐增大的趋势;非采暖期则无此趋势。  相似文献   

18.
建立了大气污染物浓度与影响因子之间的BP神经网络,对城市中各监测点位的次日大气污染物浓度进行预测,采用GIS的插值分析进行污染物空间分布预测,其中BP神经网络的输入向量采用AGNES算法进行处理。以太原市区SO2、PM10浓度预测为例,选择气温、湿度、降水量、大气压强、风速和前5天的污染物浓度等10个参数训练BP神经网络,结果表明,BP神经网络的训练效果较好,预测结果与实际浓度显著相关,R2分别为0.988、0.976;结合太原市8个监测点位的污染物浓度预测值,运用GIS空间差值法绘出SO2、PM10的浓度分布预测图,该图与实际情况大体符合,并且与国控大气污染企业的分布显著相关,Pearson相关系数分别为0.969、0.949。  相似文献   

19.
大气气溶胶对人体健康环境和全球气候都有一定的影响,是大气污染的主要来源。为了提升空气质量,大气污染防治刻不容缓。把气溶胶探测激光雷达和测风激光雷达集成在车辆上,进行走航和扫描探测可获得立体的大气气溶胶时空变化状态图。以合肥和芜湖等地大气气溶胶探测为例,基于激光雷达走航车的探测数据,获得大气气溶胶消光系数时空分布图,搜寻污染物排放源和估算颗粒物的PM2.5输送通量。由此可知,激光雷达走航式探测技术是获得大气污染立体图像便捷的、有效的方法,可为大气污染防治提供精准的科学依据,具有重要的应用价值。  相似文献   

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