2013年北京市PM2.5重污染日时空分布特征研究

根据2013年北京市环境保护监测中心监测的PM2.5数据,系统分析了北京市重污染日PM2.5污染的时空分布特征,并利用克里格插值初步统计了全年和重污染日PM2.5不同浓度区间的国土面积。2013年全市PM2.5年均浓度为89.5μg/m3,重污染日平均浓度为218μg/m3,重污染日主要集中在冬季;PM2.5年均浓度呈现明显的南高北低梯度分布特征,而重污染日空间分布较均匀,南部及城六区存在明显的高污染区,平均浓度在180μg/m3以上;2013年北京市重污染日PM2.5平均浓度为150~250μg/m3,其对应的国土面积约为12 656 km2,PM2.5平均浓度在250μg/m3以上的国土面积约为883 km2,而全年无PM2.5平均浓度在150μg/m3以上所对应的国土面积。     

北京市冬季大气细粒子数浓度的粒径分布特征

考虑到对人体的健康危害,大气颗粒物的数浓度值可能比质量浓度值更重要.通过对北京市交通道路边、生活区和远郊背景点大气细粒子数浓度的监测,对北京市大气细粒子数浓度的主要来源、浓度和粒径分布特征进行研究.文章认为交通源是城市大气细粒子数浓度的主要来源.城市生活区的大气细粒子主要是污染源稀释后扩散而来.远郊区既可能存在气象污染物光化学成核生成的超细颗粒物,也存在外部运移而来的细粒子.与国外其他城市相比,北京市大气细粒子数浓度在道路边处于中等偏下水平,但生活区和背景点处于相当或偏高的水平.     

北京市昌平区大气环境PM10中多环芳烃的含量及变化趋势

通过采集了2004～2006年北京市昌平区四个季节中大气PM10样品,采用超声抽提方法,使用GC/MS分析了该区PAHs含量和组成.结果显示,三年中四个季度的18种PAHs总量范围分别为21.64～656.39ng/m3、31.94～164.33ng/m3和7.294～209.3ng/m3,其中致癌性极强的苯并[a]芘含量范围为2.69～36.95 ng/m3、1.44～6.6ng/m3和0.256～8.625ng/m1,其变化趋势与PAHs总量有较好的相关性.PAHs的浓度是冬季＞秋季＞夏季＞春季,这与夏季时雨水冲刷和阳光照射强度大导致PAHs光解,冬季时燃煤排放大等影响因素有关.文章还使用多种方法判断昌平区大气PM10中的PAHs主要来源于燃煤和汽车尾气,其它污染源贡献较小.     

北京沙尘天气与源地气象条件的关系

本介绍了影响北京地区沙尘天气的沙尘源地,沙尘暴发生的条件和传输路径,分析了沙尘暴源地的气候要素特征及其对北京地区沙尘天气的影响,说明了北京沙尘天气发生和加剧的原因,影响北京地区沙尘天气的境外源地主要位于哈萨克斯坦,俄罗斯以及蒙古国境内,境内源地主要位于内蒙古和新疆,以及甘肃和青海的部分地区,沙尘天气发生必须具备三个条件：沙源,大风,气流辐合（垂直对流）,有沙源不一定起沙,但无沙源一定不起沙,沙尘暴源地的气候特征主要表现为冬季寒冷,夏季炎热,全年降水稀水,影响北京的沙尘传输路径,最主要的有两条,即西路传输和北路传输,北京沙尘天气与沙尘暴源地的春季降水比较结果表明,北京地区沙尘暴和浮尘天气发生次数与沙尘源区春季大气降水量有比较显的负相关关系,北京扬沙天气的发生与沙源区冬春季降水量相关关系不显,说明北京扬沙天气起因与源区降水没有明显的关系,北京扬沙天气主要受本地的自然条件和人为活动的影响。     

首都大学生的自然灾害认知调查与减灾教育建议

2006年国际减灾日的主题是"减灾始于学校",了解学生的灾害认知水平有助于减灾教育工作的有效开展。以北京5所高校的大学生为调查对象,通过问卷方式调查大学生对自然灾害的关注程度、防灾意识、灾害理论知识、应急行为知识以及对减灾教育的看法。问卷统计结果表明:大学生总体的灾害认知水平较低,现行减灾教育方式和内容与学生的期望有较大偏差。在此基础上,提出了减灾教育内容要将学生"该知道的"与"想知道的"相结合,通过演练演习等方式提高学生的防灾应急实际技能等减灾教育建议。     

Decomposition Analysis of Sectoral Energy Use in Beijing （1981-2005） Using the LMDI Method

This paper aims to identify the main driving force for changes of total primary energy consumption in Beijing during the period of 1981-2005. Sectoral energy use was investigated when regional economic structure changed significantly. The changes of total primary energy consumption in Beijing are decomposed into production effects, structural effects and intensity effects using the additive version of the logarithmic mean Divisia index （LMDI） method. Aggregate decomposition analysis showed that the major contributor of total effect was made by the production effect followed by the intensity effect, and the structural effect was relatively insignificant. The total and production effects were all positive. In contrast, the structural effect and intensity effect were all negative. Sectoral decomposition investigation indicated that the most effective way to slow down the growth rate of total primary energy consumption （TPEC） was to reduce the production of the energy-intensive industrial sectors and improving industrial energy intensity. The results show that in this period, Beijing＇s economy has undergone a transformation from an industrial to a service economy. However, the structures of sectoral energy use have not been changed yet, and energy demand should be increasing until the energy-intensive industrial production to be reduced and energy intensity of the region reaches a peak. As sequence energy consumption data of sub-sectors are not available, only the fundamental three sectors are considered： agriculture, industry and service. However, further decomposition into secondary and tertiary sectors is definitely needed for detailed investigations.     

京津冀地区面向人居环境之水安全格局初探

采用文献法对近年京津冀水资源、水环境、水污染、水灾害、水管理等水安全情势进行相关数据分析,从总体上显示出水危机问题和京津冀地区快速城市化发展的关联性.结果表明:1)京津冀城市群必须向节水型社会模式转型;2)建立区域及城市间的协调机制,才能有效克服流域与区域等级的水问题;3)实现京津冀地区水安全格局的治理行动计划网络,提出保护恢复体系、净化循环体系、限制节约体系、调度再造体系、蓄滞防洪减灾体系五大体系.     

北京山区主体功能区协调发展的区域背景分析

主体功能区划主要在于解决区域问题，用科学发展观协调区域发展。本文从区域发展的整体性出发，用空间发展的相互作用理论分析了北京山区各主体功能区协调发展的区域背景。     

Characteristics and recent trends of sulfur dioxide at urban, rural, and background sites in North China: Effectiveness of control measures

SO₂ measurements made in recent years at sites in Beijing and its surrounding areas are performed to study the variations and trends of surface SO₂ at different types of sites in Northern China. The overall average concentrations of SO₂ are (16.8 ± 13.1) ppb, (14.8 ± 9.4) ppb, and (7.5 ± 4.0) ppb at China Meteorological Administration (CMA, Beijing urban area), Gucheng (GCH, relatively polluted rural area, 110 km to the southwest of Beijing urban area), and Shangdianzi (SDZ, clean background area, 100 km to the northeast of Beijing urban area), respectively. The SO₂ levels in winter (heating season) are 4-6 folds higher than those in summer. There are highly significant correlations among the daily means of SO₂ at different sites, indicating regional characteristics of SO₂ pollution. Diurnal patterns of surface SO₂ at all sites have a common feature with a daytime peak, which is probably caused by the downward mixing and/or the advection transport of SO₂-richer air over the North China Plain. The concentrations of SO₂ at CMA and GCH show highly significant downward trends (-4.4 ppb/yr for CMA and -2.4 ppb/yr for GCH), while a less significant trend (-0.3 ppb/yr) is identified in the data from SDZ, reflecting the character of SDZ as a regional atmospheric background site in North China. The SO₂ concentrations of all three sites show a significant decrease from period before to after the control measures for the 2008 Olympic Games, suggesting that the SO₂ pollution control has long-term effectiveness and benefits. In the post-Olympics period, the mean concentrations of SO₂ at CMA, GCH, and SDZ are (14.3 ± 11.0) ppb, (12.1 ± 7.7) ppb, and (7.5 ± 4.0) ppb, respectively, with reductions of 26%, 36%, and 13%, respectively, compared to the levels before. Detailed analysis shows that the differences of temperature, relative humidity, wind speed, and wind direction were not the dominant factors for the significant differences of SO₂ between the pre-Olympics and post-Olympics periods. By extracting the data being more representative of local or regional characteristics, a reduction of up to 40% for SO₂ in polluted areas and a reduction of 20% for regional SO₂ are obtained for the effect of control measures implemented for the Olympic Games.     

An air quality forecasting system in Beijing - Application to the study of dust storm events in China in May 2008

An air pollution forecast system, ARIA Regional, was implemented in 2007-2008 at the Beijing Municipality Environmental Monitoring Center, providing daily forecast of main pollutant concentrations. The chemistry-transport model CHIMERE was coupled with the dust emission model MB95 for restituting dust storm events in springtime so as to improve forecast results. Dust storm events were sporadic but could be extremely intense and then control air quality indexes close to the source areas but also far in the Beijing area. A dust episode having occurred at the end of May 2008 was analyzed in this article, and its impact of particulate matter on the Chinese air pollution index (API) was evaluated. Following our estimation, about 23 Tg of dust were emitted from source areas in Mongolia and in the Inner Mongolia of China, transporting towards southeast. This episode of dust storm influenced a large part of North China and East China, and also South Korea. The model result was then evaluated using satellite observations and in situ data. The simulated daily concentrations of total suspended particulate at 6:00 UTC had a similar spatial pattern with respect to OMI satellite aerosol index. Temporal evolution of dust plume was evaluated by comparing dust aerosol optical depth (AOD) calculated from the simulations with AOD derived from MODIS satellite products. Finally, the comparison of reported Chinese API in Beijing with API calculated from the simulation including dust emissions had showed the significant improvement of the model results taking into account mineral dust correctly.