Spatiotemporal evolution of urban air quality and socioeconomic driving forces in China

Air pollution is a serious problem brought by the rapid urbanization and economic development in China, imposing great challenges and threats to population health and the sustainability of the society. Based on the real-time air quality monitoring data obtained for each Chinese city from 2013 to 2014, the spatiotemporal characteristics of air pollution are analyzed using various exploratory spatial data analysis tools. With spatial econometric models, this paper further quantifies the influences of socioeconomic factors on air quality at both the national and regional scales. The results are as follows: (1) From 2013 to 2014, the percentage of days compliance of urban air quality increased but air pollution deteriorated and the worsening situation in regions with poor air quality became more obvious. (2) Changes of air quality show a clear temporal coupling with regional socioeconomic activities, basically “relatively poor at daytime and relatively good at night”. (3) Urban air pollution shows a spatial pattern of “heavy in the east and light in the west, and heavy in the north and light in the south”. (4) The overall extent and distribution of regional urban air pollution have clearly different characteristics. The formation and evolution of regional air pollution can be basically induced as “the pollution of key cities is aggravated—pollution of those cities spreads—regional overall pollution is aggravated—the key cities lead in pollution governance—regional pollution joint prevention and control is implemented—regional overall pollution is reduced”. (5) At the national level, energy consumption, industrialization and technological progress are the major factors in the worsening of urban air quality, economic development is a significant driver for the improvement of that quality. (6) Influenced by resources, environment and the development stage, the socioeconomic factors had strongly variable impacts on air quality, in both direction and intensity in different regions. Based on the conclusion, the regional differentiation and development idea of the relationship between economic development and environmental changes in China are discussed.     

Assessment of Urban Air Pollution and Spatial Spillover Effects in China: Cases of 113 Key Environmental Protection Cities

With rapid urbanization and energy consumption, environmental pollution and degradation have become increasingly serious problems in China. At the beginning of 2013, China implemented new ambient air quality standards (GB 3095-2012) in which the concentration of six pollutants including PM_2.5, ozone, carbon monoxide, PM₁₀, sulfur dioxide and nitrogen dioxide were monitored. This study gathered annual air pollutant concentration data for the six pollutants in 113 key environmental protection cites throughout China in 2014 and 2015 to explain spatial patterns of urban air pollution. Based on the Kernel density estimation method, spatial hotspots of air pollution were illustrated through which spatial cluster of each pollutants could be plotted. By employing an entropy evaluation system, urban air quality was assessed in terms of the six atmospheric pollutants. We conclude that, in general, CO and SO₂ were two important pollutants in most Chinese cities, but this varied greatly among cities. The assessment results indicate that cities with the worst air quality were mainly located in northern and central provinces, dominantly in the Beijing-Tianjin-Hebei metropolitan area. Regression modeling showed that a combination of meteorological factors and human-related determinants, to say specifically, industrialization and urbanization factors, greatly influenced urban air quality variation in China. Results from spatial lag regression modeling confirmed that air pollution existed obvious spatial spillover effects among key cities. The spatial interdependence effects of urban air quality means that Chinese municipal governments should strengthen regional cooperation and deepen bilateral collaboration in terms of air regulation and pollution prevention.     

基于空间计量模型的中国城市化发展与城市空气质量关系

采用中国289个地级及以上城市2016年的空气质量指数（AQI）和夜间灯光数据,运用空间滞后模型,从空间溢出效应视角出发探究了城市化发展与空气质量之间的定量关系。从空间滞后模型的估计结果来看,城市空气污染存在显著的空间溢出效应,周边地区空气质量的下降会导致本地空气污染情况加重。在城市发展过程中,城市经济发展水平的提高,引致的城市建设用地的扩张使得空气质量不断恶化;政府管制力的加强对空气污染的治理起到了促进作用,而居民环保意识和城市技术创新水平的提高有利于空气质量的改善。此外,PM2.5质量浓度的上升导致空气质量恶化。公路货运量在统计上与空气质量的关系不显著。从研究结果来看,协调城市发展与空气质量的关系以及加强空气污染防治的联防联控机制,是未来空气污染治理工作的重点。     

中国城市空气质量时空演化特征及社会经济驱动力

城市空气污染是中国在快速城镇化和经济发展过程中亟待解决的难题。利用2013年和2014年全国城市空气质量数据,综合ArcGIS空间分析和统计分析,从年度、季节、月份、小时4个时间尺度比较归纳了全国城市空气质量的时空间演化特征,并采用空间计量模型,从全国和区域两个空间尺度,量化分析了城市空气质量变化的社会经济驱动力。结果表明：① 全国城市空气质量全年达标天数比例增加,但空气污染程度加重,高污染区域恶化态势明显;② 城市空气质量与生产生活活动表现出一定的时间耦合性,基本呈现“日出趋差、日落趋优”的态势;③ 全国城市空气污染表现出“东重西轻、北重南轻”的空间格局,区域一体化态势明显;④ 区域城市空气污染的总体程度和分布结构具有明显的分异特征,区域空气污染形成和演化路径可基本归纳为：“重点城市污染加重—重点城市污染扩散—区域整体污染加重—重点城市引领治污—区域污染联防联控—区域整体污染减轻”;⑤ 从全国层面看,能源消耗、工业化和技术进步是推动城市空气质量恶化的重要因素,经济发展对城市空气质量改善具有显著的推动作用。⑥ 受各地区资源环境基础和社会经济发展阶段影响,各类社会经济因素对城市空气质量改善的驱动方向和驱动强度差异明显。在结论的基础上,讨论了中国经济发展和环境变化关系的区域分异以及发展理念。     

京津冀城市群大气污染的时空特征与影响因素解析

京津冀城市群是中国雾霾最严重的区域,在京津冀协同发展背景下,探究该地区大气污染的时空分布和影响因素具有重要意义。运用空间自相关分析和三种空间计量模型,分析了京津冀202个区县PM_2.5的时空分异特征,创新性地对自然与人文影响因素贡献及其空间溢出效应进行系统地甄别和量化。结果表明：2000-2014年来京津冀城市群PM_2.5浓度整体呈上升趋势,季节上呈秋冬高、春夏低,空间上呈东南高、西北低的特点,且城市建成区PM_2.5浓度比周围郊区和农村平均高10~20 μg/m³;2014年仅有13.9%的区县空气质量达标,PM_2.5浓度存在显著的空间集聚性与扩散性,城市间交互影响距离平均为200 km,邻近地区的PM_2.5每升高1%,将导致本地PM_2.5至少升高0.5%;社会经济内因对PM_2.5主要是正向影响,自然外因主要是负向影响;影响因素中对本地大气污染的直接效应贡献强度依次是：年均风速>年均气温>人口密度>地形起伏度>第二产业占比>能源消费>植被覆盖度,人均GDP、年降水量和相对湿度对本地PM_2.5没有显著影响;对邻近地区大气污染具有显著空间溢出效应的因素排序是：植被覆盖度>地形起伏度>能源消费>人口密度;对于自然和人文影响因素应分别采取针对性的适应策略和调控策略,加强区域间联防联控与合作治理,在城市群规划中注重环保规划与立法。     

2003-2016年中国PM2.5质量浓度时空格局演变及影响因素解析

以中国286个主要地级市为研究区域,基于2003—2016年中国地级市大气PM_2.5质量浓度栅格数据及各地级市社会经济数据,运用空间自相关和空间面板杜宾模型,揭示了中国地级市PM_2.5质量浓度的时空格局与影响因素。研究显示：(1)中国PM_2.5污染在时序演化上呈“M”型波动态势,在空间分布上以胡焕庸线为界呈现出“东高西低”的集聚型格局;(2)中国地级市PM_2.5污染在空间效应上呈现出显著的正相关性,表明区域间大气污染存在交互影响;(3)人口密度与非农产业从业人员占比对PM_2.5质量浓度升高的贡献最大,而液化石油气供气总量与第三产业占GDP的比重对PM_2.5有较为显著的负向消减作用。     

长三角地区产业转型的大气污染效应——基于空间溢出视角

The Yangtze River Delta(YRD) is a region in China with a serious contradiction between economic growth and environmental pollution. Exploring the spatiotemporal effects and influencing factors of air pollution in the region is highly important for formulating policies to promote the high-quality development of urban industries. This study uses the spatial Durbin model(SDM) to analyze the local direct and spatial spillover effects of industrial transformation on air pollution and quantifies the contribution of each factor. From 2008 to 2018, there was a significant spatial agglomeration of industrial sulfur dioxide emissions(ISDE) in the YRD, and every 1% increase in ISDE led to a synchronous increase of 0.603% in the ISDE in adjacent cities. The industrial scale index(ISCI) and industrial structure index(ISTI), as the core factors of industrial transformation, significantly affect the emissions of sulfur dioxide in the YRD, and the elastic coefficients are 0.677 and-0.368, respectively. The order of the direct effect of the explanatory variables on local ISDE is ISCI>ISTI>foreign direct investment(FDI)>enterprise technological innovation(ETI)>environmental regulation(ER)> per capita GDP(PGDP). Similarly, the order of the spatial spillover effect of all variables on ISDE in adjacent cities is ISCI>PGDP>FDI>ETI>ISTI>ER, and the coefficients of the ISCI and ISTI are 1.531 and 0.113, respectively. This study contributes to the existing research that verifies the environmental Kuznets curve in the YRD, denies the pollution heaven hypothesis, indicates the Porter hypothesis, and provides empirical evidence for the formation mechanism of regional environmental pollution from a spatial spillover perspective.     

中国城市全要素生产率的演化格局及其影响因素

基于数据包络分析,以资本、土地和劳动力为生产要素,非农GDP为经济产出,以中国县级市及其以上城市为研究对象,定量评估中国城市全要素生产率的空间布局及其波动影响因素。结果表明,近年来中国城市技术效率总体呈东高西低、有一定空间外溢的地域性特征。不过,近年来中国城市规模效率较高城市主要为大城市周边临近小城镇,环渤海地区、长三角地区与珠三角地区尤为显著。同时,近年来中国城市技术效率变化与城市经济效率变化都有明显的地域性特征,经济落后地区优于经济发达地区,中小城市区域好于大中城市区域。不过,近年来中国城市规模效率变化的高值区域主要集聚于环渤海地区、珠三角地区与长三角地区等主要城镇化区域,而大中城市规模效率增长状况整体上也好于中小城市。另外,近年来中国城市经济效率波动受制于城镇产业模式、政府经济策略与社会发展水平及其城镇化进程,而城市规模也有非线性的影响作用,而地方政府大力依赖的房地产开发投资并不能有效推动城市经济效率趋于提高态势。     

中国城市流动人口社会融合的空间格局与影响机制

城市流动人口的社会融合是新型城镇化建设的重点任务。针对现有研究在社会融合的空间特征及流入地作用方面的研究不足,本文基于2017年全国流动人口动态监测调查数据,引入空间分析和分层线性模型,揭示了中国地级以上城市流动人口社会融合的空间格局与影响机制。研究发现：① 中国城市流动人口的总体社会融合指数为0.43,存在行为融合（0.71）>心理融合（0.61）>经济融合（0.33）的维度特征。② 流动人口的社会融合存在空间自相关性和集聚性,高水平社会融合区主要分布在东北地区、山东半岛和川渝地区,低水平社会融合区主要分布在东南沿海、关中平原和华北平原地区。在这些地区中,总体上存在人口50万以下的小城市的流动人口社会融合水平高于大城市的基本特征。③ 流入地因素和个体因素共同影响和形塑了流动人口社会融合的水平和空间格局,且流入地的人口规模、住房支出（房价水平）和公共服务等因素对个体因素的影响具有调节作用,包含正向极化、负向极化、正向均化、负向均化等4种调节机制。本文呼吁从流入地—个体因素关联的人地关系视角开展流动人口社会融合研究,重视流入地因素对个体因素的影响,为基于流入地的政策调控来推进新型城镇化建设提供科学依据。     

中国城市脆弱性的综合测度与空间分异特征（英文）

The urban vulnerability poses a serious challenge to achieving sustainable development. With the concentration of the population and the economy,cities must manage the higher frequencies and risks of various hazards and are becoming more vulnerable. Research on the assessment and regulatory control of urban vulnerability is of great significance for both urbanization quality improvement and sustainable development in China or other countries in the world. Because of the complexity of cities and vulnerability concepts,existing studies have focused on different aspects of urban vulnerability. And the research content of urban vulnerability is scattered and relatively independent,leading to a lack of comparability among the research data and resulting in tremendous difficulties in summarizing the conclusions through comparison of independent research data. Therefore the goal of this study was to construct urban vulnerability index(UVI) from the perspective of sustainable development that could assess urban vulnerability comprehensively. In this study,we selected 10 subindexes involving 36 specific parameters from four aspects(resources,eco-environmental systems,economics,and social development) to construct a comprehensive index system. We also established the standard values of measurements. Then we take 288 prefecture-level cities in China as a study area and evaluate its overall urban vulnerability and its spatial differentiation. Results indicate that urban vulnerability of China has a remarkable spatial differentiation of both "gradient distribution" and "clustered distribution"; the extent of urban vulnerability corresponds to city size,the bigger the city,the lower its vulnerability; resource-based cities are more vulnerable than comprehensive cities; a city's economic growth rate does not reflect the extent of its urban vulnerability. Further,we offer a few suggestions to cope with urban vulnerability in China.     

基于航空客流的中国城市对外联系网络结构与演化

改革开放以来,经济全球化和快速城市化促进了中国城市外向型联系的发展,改变了中国城市对外联系的空间格局。越来越复杂化的城市空间分布和组织规律需要一个全新的、综合的网络视角来考察。航空运输是当前城市间相互联系的重要物质基础,体现了城市间的直接关系,是研究城市网络的合适工具。本文以中国城市对外的航空客运联系作为衡量城市关系的指标,借鉴社会网络分析中的2-模网络概念构建了中国城市对外联系网络,并对网络的结构特征和演化规律进行了分析。研究结果表明,中国城市对外联系网络存在北京-上海-广州的三中心结构。中心城市以外,西部城市上升势头迅猛,体现了网络多元化发展的趋势。此外,中国城市对外联系的主要对象逐渐从东南亚向东亚转移,并呈现出以首尔为核心的网络结构。同时,中国城市对外联系扩张以强化区域内部联系为主,洲际联系发展滞后。     

Spatiotemporal evolution of PM2.5 concentrations in urban agglomerations of China

As the main form of new urbanization in China,urban agglomerations are an im-portant platform to support national economic growth,promote coordinated regional devel-opment,and participate in international competition and cooperation.However,they have become core areas for air pollution.This study used PM2.5 data from NASA atmospheric re-mote sensing image inversion from 2000 to 2015 and spatial analysis including a spatial Durbin model to reveal the spatio-temporal evolution characteristics and main factors con-trolling PM2.5 in China's urban agglomerations.The main conclusions are as follows:(1)From 2000 to 2015,the PM2.5 concentrations of China's urban agglomerations showed a growing trend with some volatility.In 2007,there was an inflection point.The number of low-concentration cities decreased,while the number of high-concentration cities increased.(2)The concentrations of PM2.5 in urban agglomerations were high in the west and low in the east,with the"Hu Line"as the boundary.The spatial differences were significant and in-creasing.The concentration of PM2.5 grew faster in urban agglomerations in the eastern and northeastern regions.(3)The urban agglomeration of PM2.5 had significant spatial concentra-tions.The hot spots were concentrated to the east of the Hu Line,and the number of hot-spot cities continued to rise.The cold spots were concentrated to the west of the Hu Line,and the number of cold-spot cities continued to decline.(4)There was a significant spatial spillover effect of PM2.5 pollution among cities within urban agglomerations.The main factors control-ling PM2.5 pollution in different urban agglomerations had significant differences.Industriali-zation and energy consumption had a significant positive impact on PM2.5 pollution.Foreign direct investment had a significant negative impact on PM2.5 pollution in the southeast coastal and border urban agglomerations.Population density had a significant positive impact on PM2.5 pollution in a particular region,but this had the opposite effect in neighboring areas.Urbanization rate had a negative impact on PM2.5 pollution in national-level urban agglomer-ations,but this had the opposite effect in regional and local urban agglomerations.A high degree of industrial structure had a significant negative impact on PM2.5 pollution in a region,but this had an opposite effect in neighboring regions.Technical support level had a signifi-cant impact on PM2.5 pollution,but there were lag effects and rebound effects.     

成渝地区城镇化质量测度及空间差异分析

基于对城镇化质量内涵的理解,从人口、经济、社会、基础设施、生态、空间发展、发展效率、城乡统筹8个方面构建城镇化质量评价指标体系,运用熵值法对2014年成渝地区13个城市城镇化质量进行测度,采用协调度模型对成渝地区城镇化水平与质量的协调状况进行评价,应用典型相关分析探讨成渝地区的区域差异。结果表明:成渝地区城镇化质量整体不高;区域内各城市城镇化质量综合得分差距明显,空间差异显著。在此基础上,采用聚类分析法将成渝地区13个城市划分为四大类型区:高质量类型区、质量较高区、质量一般地区、质量较低区。成渝地区的城镇化水平与质量协调度地域差异较大,整体水平较低。经济、人口、基础设施是成渝地区城镇化质量空间差异的主要影响因素。     

Spatiotemporal characteristics of urban air quality in China and geographic detection of their determinants

Ambient air pollution brought by the rapid economic development and industrial production in China has exerted a significant influence on socio-economic activities and public health, especially in the densely populated urban areas. Therefore, scientific examination of regional variation of urban air quality and its dominant factors is of great importance to regional environmental management. Based on daily air quality index (AQI) datasets spanning from 2014 to 2016, this study analysed the spatiotemporal characteristics of air quality across different regions throughout China and ascertained the determinants of urban air quality in disparate regions. The main findings are as follows: (1) The annual average value of the urban AQI in China decreased from 2014 to 2016, indicating a desirable trend in air quality at the national scale. (2) The attainment rate of the urban AQI exhibited an apparent spatially stratified heterogeneity, wherein North China retained a high AQI value. The increase of Moran’s I Index reported an apparent spillover effect among adjacent regions. (3) Both at the national and regional scales, the seasonal tendency of air quality in each year is similar, wherein good in summer and relatively poor in winter. (4) Results drawn from the Geographic Detector analysis show that dominant factors influencing AQI vary significantly across urban agglomerations. Topographical and meteorological variations in urban areas may lead to complex spatiotemporal variations in pollutant concentration. Whereas given the same natural conditions, the human-dominated factors, such as industrial structure and urban form, exert significant impacts on urban air quality.The spatial spillover effects and regional heterogeneity of urban air quality illustrated in this study suggest the governments and institutions should set priority to the importance of regional cooperation and collaboration in light of environment regulation and pollution prevention.     

中国城市空气质量时空特征及其影响因素的地理探测（英文）

Ambient air pollution brought by the rapid economic development and industrial production in China has exerted a significant influence on socio-economic activities and public health, especially in the densely populated urban areas. Therefore, scientific examination of regional variation of urban air quality and its dominant factors is of great importance to regional environmental management. Based on daily air quality index(AQI) datasets spanning from 2014 to 2016, this study analysed the spatiotemporal characteristics of air quality across different regions throughout China and ascertained the determinants of urban air quality in disparate regions. The main findings are as follows:(1) The annual average value of the urban AQI in China decreased from 2014 to 2016, indicating a desirable trend in air quality at the national scale.(2) The attainment rate of the urban AQI exhibited an apparent spatially stratified heterogeneity, wherein North China retained a high AQI value. The increase of Moran's I Index reported an apparent spillover effect among adjacent regions.(3) Both at the national and regional scales, the seasonal tendency of air quality in each year is similar, wherein good in summer and relatively poor in winter.(4) Results drawn from the Geographic Detector analysis show that dominant factors influencing AQI vary significantly across urban agglomerations. Topographical and meteorological variations in urban areas may lead to complex spatiotemporal variations in pollutant concentration. Whereas given the same natural conditions, the human-dominated factors, such as industrial structure and urban form, exert significant impacts on urban air quality.The spatial spillover effects and regional heterogeneity of urban air quality illustrated in this study suggest the governments and institutions should set priority to the importance of regional cooperation and collaboration in light of environment regulation and pollution prevention.     

中国366个城市空气污染综合程度的时空演变特征分析

采用2016—2017年中国366个城市1 484个监测站点的空气质量近地监测数据,以期最大程度覆盖西部地区,填补现状对西北热点地区污染因子探讨的空白。运用空间描述性统计、空间插值、空间自相关、标准差椭圆与重心分析方法,从年度、季度、月度、日度对比的角度探讨中国空气质量的污染类型、发展趋势、集聚与迁移特征。研究发现:基于插值法,可将全国分为3个区域,临海性与山地性对空气质量优良区产生显著的正响应。山西是污染加重程度最大的省份,主要受SO₂浓度升高影响,而北京与河南是污染改善效果最明显的省份,主要是PM_2.5的治理成效显著。空气质量分布格局以新疆西部和冀鲁豫形成双核高值聚类模式,并且集聚深受温度分带的影响。空气质量总体分布朝向呈东北—西南方向,转移重心均分布在河南省,以向东北方向移动为主,这种分布变迁又重新定义了其季节分异。全国主要的污染类型以PM₁₀与PM_2.5为主。PM10主要分布在新疆地区,受风沙过境扬尘污染自然因素更大,PM_2.5主要分布在华中、华北、苏北地区,受人为经济活动影响更大。     

长三角多维城市化对PM2.5浓度的非线性影响及驱动机制

探索多维城市化对PM_2.5浓度的非线性影响及驱动机制,是城市群高质量发展的重要课题。以2000—2017年长江三角洲地区城市面板遥感影像和统计数据为样本,采用反距离权重空间插值、空间自相关和标准差椭圆等方法探查其PM_2.5浓度的时空演变规律,并运用系统动态面板回归模型研判多维城市化对PM_2.5浓度的非线性影响及驱动机制。结果表明：① 2000—2017年,长三角PM_2.5浓度由低污染等级向高污染等级演替;PM_2.5浓度整体呈现由东南向西北方向递增的空间趋势。② PM_2.5浓度呈现显著空间集聚与关联特征;PM_2.5浓度重心总体由东南向西北方向偏移,在东西方向上趋向分散,在南北方向上逐渐极化。③ 长三角城市化子系统不同发展阶段对PM_2.5浓度的非线性影响存在显著差异。经济城市化与PM_2.5浓度呈倒“N”型曲线关系,二者存在环境库兹涅茨曲线（EKC）关系,当人均GDP大于63709元时,经济城市化对PM_2.5浓度将产生抑制效应,表明城市综合质量提升和发展方式转变是PM_2.5治理的关键;而人口城市化、土地城市化与PM_2.5浓度的关系仅是倒“U”型曲线的左侧部分,二者与空气质量改善的拐点尚有一定距离。人口规模、外商直接投资、工业产业结构均对PM_2.5浓度具有显著的正向效应,而环境规制对PM_2.5浓度具有显著的抑制效应。长三角PM_2.5浓度的时空异质性特征是在经济社会因素和政府调控等诸多因素交互叠加、循环累积作用下形成,其中,经济社会因素扮演着主角。本文为探索多维城市化对PM_2.5浓度的非线性影响提供了新视角,以期为实现长三角环境保护与城市可持续发展的协调提供重要参考。     

北京批发企业空间格局演化与区位选择因素

随着服务业对居民生产、生活影响程度逐渐增强,其企业区位选择已成为从微观视角解析城市空间结构的重要途径。以北京为典型案例地,将批发企业作为研究对象,运用核密度估计方法、Ripley's K(d)函数以及条件Logit模型,分析了北京批发企业空间格局演变规律与集聚特征,在此基础上探究了批发企业区位选择的影响因素。结果表明：① 从空间分布特征来看,批发企业主要集中在北京五环以内,且呈现明显的空间集聚特征,集聚规模主要集中在0~28 km范围内;② 从空间集聚强度看,集聚峰值出现的距离不断向外扩张,二环内集聚强度有所下降,并在外围形成了3个核心集聚区;③ 地方化经济、城市化经济、土地价格、集聚效益、劳动力成本等因素对批发企业区位选择具有显著影响,其中土地价格和集聚效益的影响最大,新企业在区位选择中都存在明显的集聚效益;④ 从不同类型批发企业来看,外资批发企业通过检验的影响因素较少,受已有该企业空间分布的影响显著且对交通区位条件、创新环境要求更高,但商业基准地价在外资企业区位选择中影响不显著。     

A comprehensive assessment of urban vulnerability and its spatial differentiation in China

The urban vulnerability poses a serious challenge to achieving sustainable development. With the concentration of the population and the economy, cities must manage the higher frequencies and risks of various hazards and are becoming more vulnerable. Research on the assessment and regulatory control of urban vulnerability is of great significance for both urbanization quality improvement and sustainable development in China or other countries in the world. Because of the complexity of cities and vulnerability concepts, existing studies have focused on different aspects of urban vulnerability. And the research content of urban vulnerability is scattered and relatively independent, leading to a lack of comparability among the research data and resulting in tremendous difficulties in summarizing the conclusions through comparison of independent research data. Therefore the goal of this study was to construct urban vulnerability index (UVI) from the perspective of sustainable development that could assess urban vulnerability comprehensively. In this study, we selected 10 subindexes involving 36 specific parameters from four aspects (resources, eco-environmental systems, economics, and social development) to construct a comprehensive index system. We also established the standard values of measurements. Then we take 288 prefecture-level cities in China as a study area and evaluate its overall urban vulnerability and its spatial differentiation. Results indicate that urban vulnerability of China has a remarkable spatial differentiation of both “gradient distribution” and “clustered distribution”; the extent of urban vulnerability corresponds to city size, the bigger the city, the lower its vulnerability; resource-based cities are more vulnerable than comprehensive cities; a city’s economic growth rate does not reflect the extent of its urban vulnerability. Further, we offer a few suggestions to cope with urban vulnerability in China.     

中国城市群地区PM2.5时空演变格局及其影响因素

城市群作为中国新型城镇化主体形态,是支撑全国经济增长、促进区域协调发展、参与国际分工合作的重要平台,也是空气污染的核心区域。本文选取2000-2015年NASA大气遥感影像反演PM_2.5数据,运用GIS空间分析和空间面板杜宾模型,揭示了中国城市群PM_2.5的时空演变特征与主控因素。结果显示：① 2000-2015年中国城市群PM_2.5浓度呈现波动增长趋势,2007年出现拐点,低浓度城市减少,高浓度城市增多。② 城市群PM_2.5浓度以胡焕庸线为界呈现东高西低的格局,城市群间空间差异性显著且不断扩大,东部、东北地区浓度提升更快。③ 城市群PM_2.5年均浓度空间集聚性显著,以胡焕庸线为界,热点区域集中东部,范围持续增加,冷点集中在西部,范围持续缩小。④ 城市群内各城市间PM_2.5浓度存在空间溢出效应。不同城市群影响要素差异显著,工业化和能源消耗对PM_2.5污染有正向影响;外商投资在东南沿海和边境城市群对PM_2.5污染具有负向影响;人口密度对本地区PM_2.5污染主要具有正向影响,对邻近地区则相反;城市化水平在国家级城市群对PM_2.5污染有负向影响,在区域性和地方性城市群则相反;产业结构高级度对本地区PM_2.5污染有负向影响,对邻近地区则相反;技术扶持度对PM_2.5污染的影响显著,但存在滞后性和回弹效应。