2000~2020年京津冀BVOCs排放量估算及时空分布特征

为研究京津冀地区天然源挥发性有机化合物(BVOCs)近20a排放量及时空分布特征,本文基于卫星遥感解译获得的2000年、2005年、2010年、2015年、2020年共5期中国土地利用数据,计算获得了京津冀地区各市县BVOCs排放量及排放组成,同时对京津冀地区近20a的BVOCs排放的时空分布进行了特征分析.结果表明,近20a京津冀地区BVOCs平均排放总量为76.40万t/a,其中河北省、北京市、天津市的平均排放总量分别为59.11万t/a,15.29万t/a,2.00万t/a;按照排放组成分析,ISOP平均排放总量为16.80万t/a,占总排放量的21.99%,TMT平均排放总量为29.62万t/a,占总排放量的38.77%,OVOCs平均排放总量为29.97万t/a,占总排放量的39.23%.根据排放时间特征分析,京津冀地区冬季BVOCs排放量最低、夏季BVOCs排放量最高.BVOCs排放的空间分布与土地利用类型和植被分布密切相关,不同土地利用类型的BVOCs排放贡献具有显著差异,近20a京津冀地区林地、耕地、草地的BVOCs平均排放量分别为60.33万t/a,12.78万t/a,2.31万t/a,分别占总排放量的78.90%,16.79%,3.04%.京津冀地区BVOCs空间排放分布差异比较明显,北部、东北部的整体排放量明显高于南部、东南部.本研究可为BVOCs的计算提供研究思路,同时可为京津冀地区空气污染治理提供有关基础数据.     

Comprehensive Assessment and Promotion Policy of Producer Services’ Competitiveness in Beijing City:A Comparative Analysis among Beijing,Tianjin,Shanghai,Guangzhou and Shenzhen

The five central cities-Beijing,Tianjin,Shanghai,Guangzhou and Shenzhen-of the three most important strategic regions in China,namely Beijing-Tianjin-Hebei metropolitan region,the Yangtze River Delta and the Pearl River Delta,are taken as a comparative analysis on urban producer services’ competitiveness,especially focusing on the comparative advantages and disadvantages of producer services in Beijing.Firstly,based on an integrated indicator system including one objective hierarchy,four standard hierarchies and 35 indicator hierarchies,the study applies factor analysis model and analytic hierarchy process model reformed by entropy technology to measure the comprehensive competitiveness of producer services in the above five cities.Secondly,Beijing has comparative advantages of capital resource,industrial base,scientific research resource and market scale,since it takes the first place of the five cities in the comprehensive competitiveness of producer services,the competitiveness of industrial development,business environment and living environment,only inferior to Shanghai in the competitiveness of talent capital.Thirdly,Beijing has comparative disadvantages in the level of producer services development,urban innovation capability and living environment.Finally,five proposals are put forth to enhance the competitiveness of producer services in Beijing,namely perfecting the system of laws and statutes,supporting the development of industry association,implementing scientific development planning,introducing preferential fiscal and taxation policies and strengthening human capital reserve.     

北京市人口老龄化的时空变化特征

人口老龄化现已成为当今主要的人口问题之一,并引起越来越多的关注,人口老龄化进程与老年人口空间分布特征研究是未来人口问题研究的一个重要分支.本文基于ESDA全局和局部空间自相关分析,利用北京市第四次和第五次人口普查数据以及1995和2005年1％人口抽样调查数据,对北京市县域尺度老龄人口分布总体和局部空间差异的变化趋势、特征进行了初步探索.结果表明,北京市老龄人口空间分布各区县差异较大,且呈现出明显的圈层结构特征,中心四城区老龄人口比重较高,近郊区老龄人口比重较全市平均水平低,远郊区老年人口比重又有所回升；同时,北京地区老年人口各区县的空间分布差异随着时间的推移而不断扩大,中心老城区呈现不断增强的集聚趋势,而远郊区的老年人口扩散效应明显大于集聚效应.     

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。     

生态工业园评价方法研究:以北京市为例

建立科学有效的评价方法将有助于稳步推进我国的生态工业园建设．而园区所处区域的特点对于评价指标的选择和评价体系的建立具有重要影响。本研究在借鉴国内外最新研究成果的基础上．针对北京工业开发区的发展现状和特点．考虑相关性、可操作等原则，初步提出了一套生态工业园评价指标体系框架及其计算评价方法。评价指标共分为6大类准则，共计25个具体指标．划分为“控制性”指标和“指导性”指标。前者包括：信息基建共事类指标、管理与发展类指标、减量消耗类指标、园区环保类指标。后者包括：循环利用类指标和产业共生类指标。该指标体系蕴涵的思想和理论方法已成为推进北京生态工业园建设的重要借鉴，也可作为国家生态工业园评价方法研究的有益补充。     

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.     

Particle number size distribution and new particle formation: New characteristics during the special pollution control period in Beijing

New particle formation is a key process in shaping the size distribution of aerosols in the atmosphere.We present here the measurement results of number and size distribution of aerosol particles (10-1...     

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.     

2013年1月北京市一次空气重污染成因分析

采用数值模式与观测资料相结合的方式,对北京市2013年1月9日至15日一次空气重污染过程的大气环境背景、气象条件和形成原因进行了初步分析.结果表明,重污染过程期间10日至14日PM2.5平均值为323μg·m-3;重污染过程与当地气象条件密切相关,稳定的大气环流形势为污染的持续提供了大气环流背景,风速较小、湿度较大、边界层较低、持续逆温是造成重污染的主要原因;重污染过程中区域输送对北京PM2.5贡献率在53%~69%之间且存在明显的二次转化,区域输送起着更为重要的作用;气象条件对持续性重污染的形成和破坏起到了关键性的作用,因此需要加强对重污染预警预报研究,以有效预防和控制空气重污染.     

基于数据挖掘算法和数值模拟技术的大气污染减排效果评估

近年来,京津冀地区采取了大量污染减排措施进行大气污染治理,如何客观评估减排效果是目前大气环境领域的研究难点.为准确评估大气污染过程的减排效果,本文利用北京地区常规气象资料、国控站PM_(2.5)浓度资料,遴选了北京地区2018年3月11—14日和2013年3月14—17日两次空气污染过程,计算了大气容量系数、静稳指数,并利用KNN数据挖掘算法和WRF-Chem模式,对比分析了有无减排条件下的PM_(2.5)日均浓度.结果表明:两次空气污染过程的天气形势和局地气象条件较相似,就大气热力和动力的垂直结构来看,2018年空气污染过程比2013年空气污染过程的大气稳定性更强、边界层高度更低、环境容量更小,但PM_(2.5)峰值浓度却显著下降,平均浓度明显降低,PM_(2.5)小时浓度的增长趋势相对平缓,重污染持续时间缩短.KNN数据挖掘算法减排评估结果显示,该方法能够较好地预测PM_(2.5)日均浓度的变化趋势,2018年3月11—14日,在减排和不减排情景下PM_(2.5)日均值分别为171和229μg·m~(-3),减排使得污染过程PM_(2.5)平均浓度下降了25.3%.数值模拟结果与KNN数据分析结论吻合,进一步验证了减排措施的有效性.综合看来,2018年空气污染过程中PM_(2.5)浓度相比历史相似气象条件下的污染过程显著降低,这是长期大力度减排效果的体现.