Long-term air pollution exposure contributes to mortality but there are few studies examining effects of very long-term (>25 years) exposures.This study investigated modelled air pollution concentrations at residence for 1971, 1981, 1991 (black smoke (BS) and SO2) and 2001 (PM10) in relation to mortality up to 2009 in 367,658 members of the longitudinal survey, a 1% sample of the English Census. Outcomes were all-cause (excluding accidents), cardiovascular (CV) and respiratory mortality.BS and SO2 exposures remained associated with mortality decades after exposure-BS exposure in 1971 was significantly associated with all-cause (OR 1.02 (95% CI 1.01 to 1.04)) and respiratory (OR 1.05 (95% CI 1.01 to 1.09)) mortality in 2002-2009 (ORs expressed per 10 μg/m(3)). Largest effect sizes were seen for more recent exposures and for respiratory disease. PM10 exposure in 2001 was associated with all outcomes in 2002-2009 with stronger associations for respiratory (OR 1.22 (95% CI 1.04 to 1.44)) than CV mortality (OR 1.12 (95% CI 1.01 to 1.25)). Adjusting PM10 for past BS and SO2 exposures in 1971, 1981 and 1991 reduced the all-cause OR to 1.16 (95% CI 1.07 to 1.26) while CV and respiratory associations lost significance, suggesting confounding by past air pollution exposure, but there was no evidence for effect modification. Limitations include limited information on confounding by smoking and exposure misclassification of historic exposures.This large national study suggests that air pollution exposure has long-term effects on mortality that persist decades after exposure, and that historic air pollution exposures influence current estimates of associations between air pollution and mortality.Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

构建基于环境污染的人口健康压力指数模型,引入空间集聚和收敛性检验方法,对中国各省区2005~2014年的污染健康压力的时空差异特征进行研究,结果表明：① 2005~2014年各省区的污染健康压力指数发生明显下降,省际差异程度有所降低,但“东高、西低、中部居中”的基本格局没有变化。② 各省区健康压力指数的空间分布在宏观上呈现出一定的空间集聚性,集聚趋势随时间有所弱化。③ 在控制城市化率、人均GDP、人口死亡率、森林覆盖率等变量的条件下,考察时段内各省区健康压力指数变化存在微弱的收敛性,各省区的健康压力预期将逐步趋同于某一较低水平。

Health is the basic right of human beings, and is also one of the important goals of the construction of well-off society in China. Nowadays, the rapid urbanization and industrialization have resulted in serious environmental pollution, which did harm to human health. To harmonize the relationships between economic development, environmental conservation and population health, it is necessary to measure the health pressure caused by environmental pollution at macro level to explore the spatial distribution pattern and changing rules of pollution’s health pressure. This paper established the population health pressure model based on environmental pollution, and used the spatial agglomeration and convergence test model to study the temporal and spatial differences characteristics of health pressure caused by pollution in China in the recent decade. At first, this paper built the index system of pollution health pressure. And then, the analytic hierarchy process based on expert knowledge was employed to determine the weight of index. And the findings showed that: 1) The pollution health pressure of each province decreased from 2005 to 2014, as well as the provincial differences, while the spatial pattern of “high in the east, middle in the central and low in the west” still existed; 2) The spatial agglomeration was one of the main characteristics of health pressure distribution, which could describe the spatial relations of geographic position and pressure index. This paper used the spatial autocorrelation and the global exponential of Moran’s I to study the spatial agglomeration. The spatial distribution of provincial pollution health pressure was not completely random. But instead it present the trend of spatial agglomeration, which meant that the high (low) pressure provinces were tend to adjacent high(low) level provinces. And compared with 2005, the space agglomeration in 2014 of pollution health pressure decreased; 3) Studying the convergence of temporal and spatial changes of health pressure helped learning the changing trends of health pressure, which could provide references for the formulation of relevant optimization policy. And the statistical test shown that the provincial pollution health pressure in 2005-2014 present the weak convergence trend while controlling the variables (urbanization rate, per capita GDP, population mortality and the forest coverage rate). And it meant that the provincial health pressure would be tend to the low-level convergence, in accordance with the continual decrease of health pressure difference and the weaker tendency of spatial agglomeration. Obviously, this article aimed at exploring the temporal and spatial differences characteristics of health pressure caused by environmental pollution in China, and the findings could provide references for government to optimize and coordinate the complicated relationships between environment and health.

健康不公平作为影响人类发展的核心问题,已引起世界各国的广泛关注。基于变异系数、泰勒指数、空间自相关分析和空间面板计量模型,本文探讨了2003年以来中国居民健康水平的区域差异、时空变化及其关键影响因素,旨在为政府制定全民健康政策提供科学依据。结果发现：① 2003-2013年,中国居民健康水平提高26.98%,西部增幅高于东、中部,但始终保持着“东—中—西”阶梯式递减态势;② 中国居民健康水平的区域差异总体呈扩大趋势,其中地带间差异趋于缩小,地带内差异趋于扩大,西部地带内差异扩大尤为显著;③ 居民健康水平的空间分布转为明显的“T”字型格局,并呈“东—中—西”阶梯式及“北—中—南”对称式递减;④ 居民健康水平的空间集聚程度趋于减小,热点区与冷点区均呈收缩态势,且西部形成规模显著的稳定性冷点,东部沿海形成规模显著的稳定性热点;⑤ 人均GDP、人均公共医疗卫生支出、城市化水平及环境质量等因素对居民健康水平时空变化具有显著影响,随着人均GDP与人均公共医疗卫生支出的增加、城市化水平的提高及环境质量的改善,居民健康水平随之提高。未来,还需对居民健康水平的多时域、多尺度及多影响机制等问题开展深入研究。

As one of the core problems clsoely related with human development, health inequality has aroused an increasing concern in the world. Through an integration of the coefficient of variation, Theil index, exploratory spatial data analysis (ESDA) and spatial panel econometric model, we examine the regional inequality, spatial-temporal dynamic patterns and the key factors of the residents' health level (RHL) in China from 2003 to 2013. The aim is to provide scientific basis for policy making on regional health inequality reduction in China. The results are shown as follows: (1) China's RHL index decreased from 0.404 to 0.295 in 2003-2013, with an annual rate of 2.698%. Specifically speaking, the growing rate in the western region was higher than that in the eastern and central regions, but the there is no change in RHL in terms of the basic pattern which decreases from the east to central part then to the west. (2) The regional inequality of RHL presented an extending trend in 2003-2013. Among this, the RHL inequality between regions presented a reducing trend, but that within a region presented an expanding trend. And the growing rate of inequalities of RHL in the western region was higher than that of the eastern and central regions. (3) The spatial distribution of RHL has tended into the letter "T" shape, and the RHL presented a stepped decrease from the east to the central part then to the west and a symmetric decrease from the north to the central part then to the south. (4) By observing the change of Moran's I in 2003, 2008 and 2013, we found that the spatial agglomeration range of RHL presented a narrowing trend. All the hot spots and cold spots presented a shrinking tendency, the RHL in the west formed a stable cold spot, including Xinjiang, Qinghai and Xizang, but that in the east coastal area formed a stable hot spot, including Shandong, Henan, Qinghai, Hubei, Anhui, Jiangsu and Shanghai. (5) The selected explanatory variables, such as per capita GDP, per capita spending on health, urbanization level and environment quality, have significant direct impacts on the RHL in China. With the increase of per capita GDP, per capita spending on health and urbanization level and the improvement of environment quality, the RHL will be raised. Finally, this paper points out the attention should be focused on the research of the regional inequality of RHL, such as the problems of the residents' multi-time-domain, multi-scale and multi-influencing mechanism.

全球气候变化及快速城市化增加了极端天气事件的发生频率,高温热浪作为其中的典型效应,增加了与热相关的健康风险,越来越受到气象学、医学与地理学学者的关注。论文系统梳理了高温热浪的定义,从地理学视角,以空间评估作为切入点,总结分析了高温热浪脆弱性评估中的空间指标、空间制图方法与空间对策等方面的研究进展,指明该领域已从单一视角逐步深入到气象学、医学、地理学等复合学科的交叉研究,地理学作为桥梁将气象学与医学有机结合,为脆弱性评估提供空间指标参数、为制图提供思路与方法,并提供空间对策连接规划和风险预警等实践工作。未来的研究展望包括：空间指标综合各学科研究需要、集成各学科优势进行构建,空间制图在社区小尺度到区域大尺度的耦合机理分析基础上探讨跨区域研究表达方式,空间对策针对不同风险人群采取差异化研究,为城市适应气候变化提供科学依据。

With global climate change and rapid urbanization, extreme weather events have become much more frequent. As one of the most typical extreme weather events caused by climate change, heat wave has been enhancing the heat-related health risks, and continuously attracting widespread attention from meteorologists, medical professionals and geographers. As a bridging actor integrating meteorological and medical fields, geography provides spatial indicators for heat wave vulnerability assessment, ideas and methods for mapping, spatial solutions for practical work such as planning and early warning. This article systematically reviews the progress of spatial assessment of heat wave vulnerability based on the perspective of geography. The contents include the definition of heat wave, spatial indicators and mapping methods. The literature reviews indicate that heat wave vulnerability assessment has gradually deepened from single perspective to the interdisciplinary study of meteorology, medicine, geography and other disciplines. In the future, more detailed exploration will be carried out, such as the construction of spatial indicators to integrate the advantages and research demands of various disciplines; the exploration about small-scale community to regional large-scale links and cross-regional research expression by mapping. Spatial approaches require differentiated research among different groups, which provide a scientific basis for climate change adaptation of cities.

环境污染是全球共同面对的重大问题之一,严重危害居民的健康状况。已有关于环境污染与健康研究主要包括宏观区域层面的环境污染与健康指标的相关关系研究;基于居民日常交通出行的空气污染暴露与健康效应的研究;以及关注社会经济属性,重点探讨黑人、儿童、低收入者等弱势群体所承受的环境负面影响,即环境公正和健康不平等研究。本文对上述研究进行较为系统的梳理与评价,基于时空行为、环境公正等学科前沿议题,为研究环境污染与健康之间的复杂性提供多样化的理论视角以及较为完整的分析框架。同时提出,需要将个体时空行为、环境污染与健康相关联,从微观层面深入研究基于居民时空行为轨迹的环境污染暴露与健康影响机理,挖掘不同社会、空间背景下的环境公正与健康不平等的内在关系,为发展更为公平、有效的城市与交通规划措施以及环境健康政策等提供科学依据。

Environmental pollution is a major problem worldwide, subjecting people to serious health risks. Numerous studies on environmental pollution and health impact have been conducted, focusing on various aspects such as the associations between environmental pollution and health at the aggregate level, air pollution exposure and health effects based on daily travel behavior of residents, and environmental justice and health inequality. The environmental justice and health inequality research focuses on the adverse environmental impacts on the disadvantaged groups, such as the minority, children, people with low-level income, and migrants. This article aims to provide a comprehensive review on environmental pollution and health studies from various perspectives, and presents a diversified research framework to investigate the complexity between environmental pollution and health. Moreover, we propose that future research needs to link individual space-time behavior with environmental pollution and health, to explore the microscale or personal-level real-time air pollution exposure and its health effects based on the residents' space-time behavior trajectory. More research needs to be conducted to investigate the complex relationship between environmental justice and health inequality at microscale under different social and spatial contexts, in order to develop more just, effective urban/transportation planning measures and environmental health policies.

环境污染与健康的研究一直受到世界各国的广泛关注。基于2016年郑州市区的大规模问卷调查,运用GIS空间分析技术、多元线性回归模型以及logistic回归模型等方法,研究微观尺度下居民健康与环境危害感知的空间分布,并探讨影响居民健康的关键因素。研究表明：①郑州市居民对自身健康状况的感知总体上处于中等水平,多数居民认为空气污染最严重,其次是噪声污染,垃圾污染与水污染相对较轻,但这4种环境污染均对居民健康状况具有显著影响。②居民健康感知的空间差异显著,呈现出明显的“中间低—外围高”的分布特征,即市中心的居民健康水平较低,而处于外围地区的居民健康水平较高。③不同社会经济属性个体对自身健康状况感知差异明显,随着年龄的增长对健康状况的感知越来越差,尤其是60岁以上的人群感知最差;高学历与高收入者认为自己健康状况很好或者非常好的比例远大于低学历与低收入者;性别与婚姻状况对健康感知的影响并不明显。④居住地到工作单位的距离越远,健康状况感知很好或者非常好的人数比例越低,街道区位也是影响居民感知自身健康状况的显著因素。研究结果可为郑州市制定更加公平、有效的环境健康政策提供科学依据。

Environmental pollution and health issues have aroused increasing concerns in the world. Based on a large-scale questionnaire survey in Zhengzhou City, Henan Province in 2016, this study examined the spatial differentiation and key influencing factors of self-rated health and perceived environmental hazards in the city on the micro-scale by using GIS spatial analysis technique, multiple linear regression model, and logistic regression model. The following conclusions can be drawn: (1) The perception of residents on own health was generally at a moderate level. The majority of the surveyed residents believed that air pollution was the most serious problem in Zhengzhou, followed by noise pollution and landfill and water pollution, but all four kinds of environmental pollution had a significant impact on the health of the residents. (2) The spatial differentiation of residents’ health perception was evident, which showed a clear pattern of low values in the core area and high values in the periphery, namely, the health levels in the central city regions were lower, while the suburban regions showed higher health levels. (3) Individuals with different socioeconomic status showed significant differences in their own health perception. Perception of health was getting worse for older people. In particular, the people over 60 years old had the worst perception of health conditions. The proportion of highly-educated and high-income people who considered their health as excellent or good was far greater than the proportion for poorly educated and low-income residents. The effects of gender and marital status on health perception were not obvious. The longer the distance between residence and workplace, the lower proportion of people who felt excellent or good with their health. Meanwhile, location of subdistricts had a remarkable effect on residents’ health perception. The aim of the study was to provide a scientific basis for more equal and effective policies on resident health in Zhengzhou City.

To investigate the association between ambient fine particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) and the risk on preterm birth.A total of 1 882 pregnant women with local residency of Taiyuan city and underwent delivery at the First Hospital of Shanxi Medical University with the dates of conception between January 1 and December 31, 2013, were enrolled in the study. Information on general demographics, home address and history on pregnancy, lifestyle and related environmental factors were collected through in-person interview. Birth outcomes and maternal complications were abstracted from medical records. Data on the amount of daily average PM2.5 from 8 monitor points in Taiyuan city, between March 1, 2012 and December 31, 2013 were also collected. Individual exposure during pregnancy were calculated using the inverse-distance weighting method, based on home address. Multivariate unconditional logistic regression model was used to examine the associations among PM2.5 exposure, risk of preterm birth and related clinical subtypes.The overall incidence of preterm birth was 8.21% (151/1 839)in 1 839 pregnant women. Exposure to ambient PM2.5 during the second week prior to delivery was associated with an increased risk of preterm birth (OR=1.087, 95% CI: 1.001-1.182 per 10 μg/m(3) increase) and mild preterm birth (OR=1.099, 95% CI: 1.007-1.200 per 10 μg/m(3)). Compared to data from the China Environmental Air Quality Standard, higher level of exposure (≥75 μg/m(3)) of PM2.5 during the second week before delivery was associated with an increased risk of preterm birth (OR=1.008, 95%CI: 1.000-1.017) but the association was mainly seen for mild preterm birth (OR=1.010, 95%CI: 1.001-1.018).RESULTS from our study showed that exposure to high level of PM2.5 during late pregnancy would increase the risk of preterm birth. Future large studies are needed to examine the association by preterm clinical subtypes and to elucidate potential underlying mechanisms.

为查明汾渭平原典型城乡地区重度污染天气PM_2.5中多环芳烃（PAHs）污染特征及其人群健康效应,本文于2018—2019年冬季分别选取西安和陇县作为城乡对比参照点,采集了重度污染天气PM_2.5颗粒态气溶胶样品。利用气相色谱—质谱联用仪（GC-MS）检测样品中具有“三致效应”的15种PAHs含量及组分特征,使用特征比值法及主成分法进行PAHs源解析,并分析了气象因素对PAHs质量浓度的可能影响,通过对苯并芘（BaP）等效毒性浓度和终生超额致癌风险度（ILCR）的计算,对人群健康风险进行评估。结果表明：西安与陇县在重度污染天气条件下PM_2.5中15种PAHs总平均质量浓度分别为243.78 ng/m³、609.39 ng/m³,其中4~6环PAHs占比最高;且PAHs浓度与气温、气压及风速呈显著负相关,与相对湿度则无明显相关性。西安PAHs污染主要来自燃烧源与交通排放源,而煤炭及生物质燃烧是造成陇县PAHs质量浓度偏高的主要原因。健康风险评估结果显示,重污染天气下陇县人群通过呼吸引发的致癌风险要高于西安,女性致癌风险高于男性,成人致癌风险高于儿童,且两地区成人ILCR值均超过风险阈值,存在潜在致癌风险,儿童则无明显致癌风险。

In order to investigate the pollution characteristics and human health risk of polycyclic aromatic hydrocarbons (PAHs) in heavy polluted weather in the typical urban and rural areas of the Fenwei Plain, PM2.5 samples were collected from Xi'an and Longxian in the winter of 2018-2019. The mass concentrations of 15 PAHs characterized by carcinogenicity, mutagenicity and teratogenicity in the samples were determined using gas chromatograph-mass spectrometer (GC-MS). The source of PAHs was analyzed by the diagnostic ratio and principal component method and the possible relation between PAHs mass concentrations and meteorological parameters was elaborated. In addition, human health risk caused by PAHs in PM2.5 was assessed through the equivalent carcinogenic concentration of benzo(a)pyrene (BaP) and incremental lifetime cancer risk (ILCR). The results showed that the average mass concentrations of PAHs in PM2.5 in heavy polluted weather in Xi'an and Longxian were 243.78 μg/m3 and 609.39 μg/m3, respectively, and 4-6 rings of PAHs had the highest proportion of the total. Moreover, PAHs concentrations had a significant negative correlation with atmospheric temperature, atmospheric pressure and wind speed, but irrelevant with relative humidity. Combustion source and automobile exhaust emissions were the main factors contributing to the high concentration of PAHs in Xi'an, while coal and biomass burning were the main factors contributing most to PAHs of Longxian. Health risk assessment results revealed that the carcinogenic risk caused by breathing during heavy polluted weather was higher in Longxian than that in Xi'an and the cancer risk for females was higher than that for males, and the cancer risk for adults was higher than that for children. In addition, the ILCR value of adults in both urban and rural areas exceeded the risk threshold recommended by EPA and had potential carcinogenic risks, while there was no obvious carcinogenic risk for children.

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。

Air pollution is now the most serious environmental problem in China, especially for Beijing-Tianjin-Hebei (Jing-Jin-Ji) urban agglomeration. Under the background of Jing-Jin-Ji integrated development, it is of great importance to study the spatio-temporal distribution and its influencing factors. This paper firstly analyzed the spatio-temporal characteristics of PM2.5 concentration in 202 counties of Jing-Jin-Ji urban agglomeration using spatial analysis and visualization. Then we quantified the effect degree of different natural and human factors and the spatial spillover effect of these factors using Spatial Durbin Model (SDM). The results are as follows: (1) The PM2.5 concentration was on the rise as a whole from 2000-2014, and it was high in autumn and winter, while low in spring and summer. Seen from spatial distribution, the PM2.5 concentration was high in the southeast, while low in the northwest of the study area, and the concentration in urban built-up area was 10-20 μg/m3 higher than that of its surrounding suburban and rural areas. (2) The counties, whose PM2.5 concentration was below 35 μg/m3, only accounted for 13.9% in 2014. There were significant spatial agglomeration and diffusivity of PM2.5, and the mean distance interacting among the cities was 200 km. The PM2.5 of a city increased by more than 0.5% for every 1% increase in the average PM2.5 of neighboring cities. (3) Socio-economic factors have positive impact on PM2.5, and most of natural factors have negative impact. (4) Among the influencing factors, contributions to local atmospheric pollution with direct effect are: mean wind speed > annual mean temperature > population density > relief amplitude > the secondary industry share of GDP > energy consumption > vegetation coverage; however, per capita GDP, annual precipitation, and relative humidity have no significant effect on local pollution. (5) Contributions to neighborhood atmospheric pollution with spatial spillover effect are: vegetation coverage > relief amplitude > population density. The findings suggest that we should adopt the adaptation strategies for natural factors and control strategies for human factors. A coordinated and strengthened cooperation between local governments should be established for air pollution control, and environmental planning and legislation should be strengthened in a new round of urban agglomeration planning in China.