Fine Particulate Air Pollution and Hospital Emergency Room Visits for Respiratory Disease in Urban Areas in Beijing,China, in 2013

BackgroundHeavy fine particulate matter (PM_2.5) air pollution occurs frequently in China. However, epidemiological research on the association between short-term exposure to PM_2.5 pollution and respiratory disease morbidity is still limited. This study aimed to explore the association between PM_2.5 pollution and hospital emergency room visits (ERV) for total and cause-specific respiratory diseases in urban areas in Beijing.MethodsDaily counts of respiratory ERV from Jan 1 to Dec 31, 2013, were obtained from ten general hospitals located in urban areas in Beijing. Concurrently, data on PM_2.5 were collected from the Beijing Environmental Protection Bureau, including 17 ambient air quality monitoring stations. A generalized-additive model was used to explore the respiratory effects of PM_2.5, after controlling for confounding variables. Subgroup analyses were also conducted by age and gender.ResultsA total of 92,464 respiratory emergency visits were recorded during the study period. The mean daily PM_2.5 concentration was 102.1±73.6 μg/m³. Every 10 μg/m³ increase in PM_2.5 concentration at lag₀ was associated with an increase in ERV, as follows: 0.23% for total respiratory disease (95% confidence interval [CI]: 0.11%-0.34%), 0.19% for upper respiratory tract infection (URTI) (95%CI: 0.04%-0.35%), 0.34% for lower respiratory tract infection (LRTI) (95%CI: 0.14%-0.53%) and 1.46% for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) (95%CI: 0.13%-2.79%). The strongest association was identified between AECOPD and PM_2.5 concentration at lag_0-3 (3.15%, 95%CI: 1.39%-4.91%). The estimated effects were robust after adjusting for SO₂, O₃, CO and NO₂. Females and people 60 years of age and older demonstrated a higher risk of respiratory disease after PM_2.5 exposure.ConclusionPM_2.5 was significantly associated with respiratory ERV, particularly for URTI, LRTI and AECOPD in Beijing. The susceptibility to PM_2.5 pollution varied by gender and age.     

Fine particulate matter air pollution and atherosclerosis: Mechanistic insights

BackgroundAtherosclerosis is a progressive disease characterized by the accumulation of lipids and fibrous plaque in the arteries. Its etiology is very complicated and its risk factors primarily include genetic defects, smoking, hyperlipidemia, hypertension, lack of exercise, and infection. Recent studies suggest that fine particulate matter (PM_2.5) air pollution may also contribute to the development of atherosclerosis.Scope of reviewThe present review integrates current experimental evidence with mechanistic pathways whereby PM_2.5 exposure can promote the development of atherosclerosis.Major conclusionsPM_2.5-mediated enhancement of atherosclerosis is likely due to its pro-oxidant and pro-inflammatory effects, involving multiple organs, different cell types, and various molecular mediators.General significanceStudies about the effects of PM_2.5inhalation on atherosclerosis may yield a better understanding of the link between air pollution and major cardiovascular diseases, and provide useful information for policy makers to determine acceptable levels of PM_2.5 air quality. This article is part of a Special Issue entitled Air Pollution, edited by Wenjun Ding, Andrew J. Ghio and Weidong Wu.     

Effects of Urban Landscape Pattern on PM2.5 Pollution—A Beijing Case Study

PM_2.5 refers to particulate matter (PM) in air that is less than 2.5μm in aerodynamic diameter, which has negative effects on air quality and human health. PM_2.5 is the main pollutant source in haze occurring in Beijing, and it also has caused many problems in other cities. Previous studies have focused mostly on the relationship between land use and air quality, but less research has specifically explored the effects of urban landscape patterns on PM_2.5. This study considered the rapidly growing and heavily polluted Beijing, China. To better understand the impact of urban landscape pattern on PM_2.5 pollution, five landscape metrics including PLAND, PD, ED, SHEI, and CONTAG were applied in the study. Further, other data, such as street networks, population density, and elevation considered as factors influencing PM_2.5, were obtained through RS and GIS. By means of correlation analysis and stepwise multiple regression, the effects of landscape pattern on PM_2.5 concentration was explored. The results showed that (1) at class-level, vegetation and water were significant landscape components in reducing PM_2.5 concentration, while cropland played a special role in PM_2.5 concentration; (2) landscape configuration (ED and PD) features at class-level had obvious effects on particulate matter; and (3) at the landscape-level, the evenness (SHEI) and fragmentation (CONTAG) of the whole landscape related closely with PM_2.5 concentration. Results of this study could expand our understanding of the role of urban landscape pattern on PM_2.5 and provide useful information for urban planning.     

Obesity and the relation between joint exposure to ambient air pollutants and incident type 2 diabetes: A cohort study in UK Biobank

BackgroundAir pollution has been related to incidence of type 2 diabetes (T2D). We assessed the joint association of various air pollutants with the risk of T2D and examined potential modification by obesity status and genetic susceptibility on the relationship.Methods and findingsA total of 449,006 participants from UK Biobank free of T2D at baseline were included. Of all the study population, 90.9% were white and 45.7% were male. The participants had a mean age of 56.6 (SD 8.1) years old and a mean body mass index (BMI) of 27.4 (SD 4.8) kg/m². Ambient air pollutants, including particulate matter (PM) with diameters ≤2.5 μm (PM_2.5), between 2.5 μm and 10 μm (PM_2.5–10), nitrogen dioxide (NO₂), and nitric oxide (NO) were measured. An air pollution score was created to assess the joint exposure to the 4 air pollutants. During a median of 11 years follow-up, we documented 18,239 incident T2D cases. The air pollution score was significantly associated with a higher risk of T2D. Compared to the lowest quintile of air pollution score, the hazard ratio (HR) (95% confidence interval [CI]) for T2D was 1.05 (0.99 to 1.10, p = 0.11), 1.06 (1.00 to 1.11, p = 0.051), 1.09 (1.03 to 1.15, p = 0.002), and 1.12 (1.06 to 1.19, p < 0.001) for the second to fifth quintile, respectively, after adjustment for sociodemographic characteristics, lifestyle factors, genetic factors, and other covariates. In addition, we found a significant interaction between the air pollution score and obesity status on the risk of T2D (p-interaction < 0.001). The observed association was more pronounced among overweight and obese participants than in the normal-weight people. Genetic risk score (GRS) for T2D or obesity did not modify the relationship between air pollution and risk of T2D. Key study limitations include unavailable data on other potential T2D-related air pollutants and single-time measurement on air pollutants.ConclusionsWe found that various air pollutants PM_2.5, PM_2.5–10, NO_2, and NO, individually or jointly, were associated with an increased risk of T2D in the population. The stratified analyses indicate that such associations were more strongly associated with T2D risk among those with higher adiposity.

Xiang Li and co-workers study the potential influence of obesity on associations between air pollutants and incidence of type 2 diabetes.     

大气颗粒物(PM2.5、PM10)对地表景观结构的响应研究进展

颗粒物PM_(2.5)、PM_(10)是近年来我国大气首要污染物,威胁环境和人类健康。地表景观结构直接或间接影响PM_(2.5)、PM_(10)浓度,了解其影响过程和机理对于改善生态环境具有重要意义。系统总结了国内外关于PM_(2.5)、PM_(10)对地表景观结构响应的研究成果,指出研究中出现不确定性的可能影响因素,并对今后的发展方向进行展望。得出基本结论:(1)地表景观类型的构成及其格局显著影响大气颗粒物浓度,对PM_(2.5)、PM_(10)起到"源"和"汇"的作用。(2)地表景观结构引起局地气候变化并影响颗粒物的迁移转化,但其影响过程和机理复杂,研究结论并不明确。(3)颗粒物浓度和地表景观数据主要通过实际监测或遥感处理方法获得,但因为获取方法、监测点微观环境及遥感影像等因素影响,导致数据具有不确定性,加上时空尺度相对应的复杂性,大大限制了地表景观结构与PM_(2.5)、PM_(10)响应关系的研究进展,是未来要突破的难点。(4)PM_(2.5)、PM_(10)对地表景观结构响应的区域时空差异及过程,局地小气候变化对颗粒物浓度的影响过程和强度,主要景观类型尤其是水体、湿地景观对大气颗粒物浓度的影响过程、机理与贡献程度等是未来需要关注的方向。     

城市化对空气污染人群暴露贡献的定量方法研究

短期快速城市化引发一系列生态环境问题,尤其是近年来以细颗粒物(PM_(2.5))为代表的城市与区域空气污染问题。人群的污染暴露一方面是因为污染区范围的扩张,另外一方面则归因于城市化引发的人口迁移,目前的研究重点关注于前者的贡献,而忽略了后者的贡献。因此,建立了城市化对空气污染人群暴露贡献的定量方法,并选取我国PM_(2.5)污染最为严重的京津冀城市群开展了实证研究,通过利用2000、2005、2010、2015年PM_(2.5)浓度和人口栅格数据以及人口自然增长率数据,定量评估了城市化引发的人口迁移对空气污染人群暴露的贡献。研究结果显示:(1)京津冀地区受污染影响面积和人口变化显著,造成大量的人口暴露于PM_(2.5)污染。(2)城市化引发的人口迁移与自然增长贡献率方面:总体上,2000—2015年,京津冀城市群总的人口迁移贡献率为48%,北京市和天津市总的人口迁移贡献率分别为94%和88%,而河北省污染总的人口迁移贡献率为-32%。其中在污染保持区,北京市和天津市的人口迁移贡献率均接近100%,而河北省的迁移贡献率为-26%,尤其在2010—2015年,河北省衡水市的人口迁移贡献率达到-6613%;在污染新增区,北京市和天津市的人口迁移贡献率分别为86%和84%,而河北省污染的人口迁移贡献率为-757%。本研究建立了定量化的方法揭示了城市化在空气污染人群暴露中的定量贡献,为科学引导城市化发展提供了定量的手段,为合理规划京津冀城市群地区的人口流动与空气污染奠定了数据基础。     

不同污染程度下毛白杨叶表面PM2.5颗粒的数量及性质和叶片气孔形态的比较研究

选择了北京市环境PM_(2.5)浓度不同的两个采样点的毛白杨(Populus tomentosa Carr.)作为研究对象,利用环境扫描电镜及X-射线能谱仪对杨树叶片表面滞留的PM_(2.5)颗粒进行了观察、统计和成分分析,并研究了叶片气孔对环境颗粒物污染的适应性变化。结果表明:夏秋两季西直门叶片样品上下表面的PM_(2.5)数量均多于森林公园样品这说明环境PM_(2.5)浓度是影响叶片表面滞留颗粒物数量的主要原因;其中叶片上表面是滞留PM_(2.5)颗粒的主要区域。森林公园样品中PM_(2.5)颗粒性质比较单一,硅铝酸盐颗粒和石英颗粒占很大比例,二者的主要来源均为天然源,如土壤扬尘、矿物颗粒等;而西直门采样点叶片样品滞留的PM_(2.5)颗粒的元素组成更为复杂,其中50%以上的硅铝酸盐颗粒检测出了明显的铜、钾、氯、钠等元素的谱峰其来源主要是工业排放;西直门样品PM_(2.5)的含硫量高于森林公园样品,且夏季明显高于秋季。研究还发现有少数PM_(2.5)颗粒进入了毛白杨叶片的气孔而且不同污染程度下气孔的形态特征存在差异。与森林公园毛白杨叶片的气孔相比,西直门处的毛白杨叶片气孔的长度、宽度、面积和气孔密度均较小,说明较高的PM_(2.5)污染程度对毛白杨叶片的形态发育有一定影响。研究结果可以为揭示植物叶片阻滞、吸收大气颗粒污染物的机制、合理选择和优化城市绿化树种从而改善空气质量提供一定的科学理论依据。     

Development of Exposure Characterization Regions for Priority Ambient Air Pollutants

To evaluate the relationship between air pollution and morbidity and mortality in epidemiological studies, the exposure of populations must be defined. Generally, ambient air monitoring networks are the source of the exposure data for these studies. In this study, we developed methods to define population exposure regions that represent minimal variation in air pollutant concentrations. We evaluated the spatial and temporal variation in concentrations for particulate matter less than 2.5 μm (PM_2.5) and 10 μm (PM₁₀) and ozone (O₃) across New York State. The results from the PM_2.5 and ozone analysis indicate a significant degree of regional transport and showed regions of consistent concentrations of 100 and 50 miles, respectively, around each monitor. PM₁₀ analysis indicated little temporal and spatial variation for this pollutant and larger regions were adopted. The exposure characterization regions for PM_2.5, PM₁₀, and ozone have been used in ecological epidemiological investigations by the New York State Department of Health. This work was conducted under the Environmental Public Health Tracking grant from the Centers for Disease Control and Prevention.     

Promoted Relationship of Cardiovascular Morbidity with Air Pollutants in a Typical Chinese Urban Area

BackgroundA large number of studies about effects of air pollutants on cardiovascular mortality have been conducted; however, those investigating association between air pollutants and cardiovascular morbidity are limited, especially in developing countries.MethodsA time-series analysis on the short-term association between outdoor air pollutants including particulate matter (PM) with diameters of 10 µm or less (PM₁₀), sulfur dioxide (SO₂) and nitrogen dioxide (NO₂) and cardiovascular morbidity was conducted in Tianjin, China based on 4 years of daily data (2008–2011). The morbidity data were stratified by sex and age. The effects of air pollutants during the warm season and the cool season were also analyzed separately.ResultsEach increase in PM₁₀, SO₂, and NO₂ by increments of 10 µg/m³ in a 2-day average concentration was associated with increases in the cardiovascular morbidity of 0.19% with 95 percent confidence interval (95% CI) of 0.08–0.31, 0.43% with 95% CI of 0.03–0.84, and 0.52% with 95% CI of −0.09–1.13, respectively. The effects of air pollutants were more evident in the cool season than those in the warm season, females and the elderly were more vulnerable to outdoor air pollution.ConclusionsAll estimated coefficients of PM₁₀, SO₂ and NO₂ are positive but only the effect of SO₂ implied statistical significance at the 5% level. Moreover, season, sex and age might modify health effects of outdoor air pollutants. This work may bring inspirations for formulating local air pollutant standards and social policy regarding cardiovascular health of residents.     

DDAH1 plays dual roles in PM2.5 induced cell death in A549 cells

BackgroundDimethylarginine dimethylaminohydrolase 1 (DDAH1) is an enzyme that can degrade asymmetric dimethylarginine (ADMA), an endogenous nitric oxide synthase (NOS) inhibitor. Emerging evidence suggests that alterations in the ADMA–DDAH1 pathway are involved in environmental pollution induced airway inflammation. However, the role of DDAH1 in protection against cytotoxicity of ambient airborne particulate matter is unclear.MethodsWe examined the influence of DDAH1 expression on oxidative stress and cell apoptosis in human type II alveolar epithelial A549 cells exposed to PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 μM).ResultsWe found that PM_2.5 exposure for 48 h significantly decreased DDAH1 expression. However, knockdown of DDAH1 prior to PM_2.5 exposure actually attenuated the cytotoxicity of PM_2.5. Cytoprotection in DDAH1 deficient cells was due to increased reactive oxygen species, activation of PI3K–AKT and mitogen-activated protein kinase (MAPK) pathways, subsequent activation of nuclear factor erythroid-2-related factor 2 (Nrf2) and this caused a subsequent reduction in PM_2.5 induced oxidative stress relative to control. DDAH1 depletion also repressed the induction of inducible NOS (iNOS) in PM_2.5-exposed cells and knockdown of iNOS protected cells against PM_2.5 induced cell death. Interestingly, overexpression of DDAH1 also exerted a protective effect against the cytotoxicity of PM_2.5 and this was associated with a reduction in oxidative stress and upregulation of the anti-apoptotic protein Bcl-2.ConclusionsOur data indicate that DDAH1 plays dual roles in protection against cytotoxicity of PM_2.5 exposure, apparently by limiting PM_2.5 induced oxidative stress.General significanceOur findings reveal new insights into the role(s) of the DDAH1/ADMA in pulmonary protection against airborne pollutants. This article is part of a Special Issue entitled Air Pollution, edited by Wenjun Ding, Andrew J. Ghio and Weidong Wu.     

Direct effects of airborne PM2.5 exposure on macrophage polarizations

BackgroundExposure of atmospheric particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) is epidemiologically associated with illnesses. Potential effects of air pollutants on innate immunity have raised concerns. As the first defense line, macrophages are able to induce inflammatory response. However, whether PM_2.5 exposure affects macrophage polarizations remains unclear.MethodsWe used freshly isolated macrophages as a model system to demonstrate effects of PM_2.5 on macrophage polarizations. The expressions of cytokines and key molecular markers were detected by real-time PCR, and flow cytometry. The specific inhibitors and gene deletion technologies were used to address the molecular mechanisms.ResultsPM_2.5 increased the expression of pro-inflammatory cytokines granulocyte-macrophage colony-stimulating factor (GM-CSF), interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor alpha (TNFα). PM_2.5 also enhanced the lipopolysaccharide (LPS)-induced M1 polarization even though there was no evidence in the change of cell viability. However, PM_2.5 significantly decreased the number of mitochondria in a dose dependent manner. Pre-treatment with NAC, a scavenger of reactive oxygen species (ROS), prevented the increase of ROS and rescued the PM_2.5-impacted M1 but not M2 response. However, mTOR deletion partially rescued the effects of PM_2.5 to reduce M2 polarization.ConclusionsPM_2.5 exposure significantly enhanced inflammatory M1 polarization through ROS pathway, whereas PM_2.5 exposure inhibited anti-inflammatory M2 polarization through mTOR-dependent pathway.General significanceThe present studies suggested that short-term exposure of PM_2.5 acts on the balance of inflammatory M1 and anti-inflammatory M2 macrophage polarizations, which may be involved in air pollution-induced immune disorders and diseases. This article is part of a Special Issue entitled Air Pollution, edited by Wenjun Ding, Andrew J. Ghio and Weidong Wu.     

川渝地区空气质量时空分布格局及影响因素

川渝地区尤其是四川盆地已成为我国空气污染最严重的地区之一,基于2018—2019年川渝地区128个城市站和71个县级站空气质量监测及自然与社会经济数据,采用全局和局部莫兰指数分析了川渝地区空气质量指数(AQI)和不同空气质量分指数(IAQI)的时空格局,并采用偏最小二乘回归(PLSR)从较为宏观的尺度综合分析了川渝地区空气污染的主要驱动因素。研究结果表明：(1)川渝地区空气质量整体为良,主要污染物为O₃,其次为PM₁₀和PM_2.5。盆地区与高原区的主要污染物分别为PM_2.5和O₃;(2)AQI及PM_2.5、PM₁₀、NO₂呈“U”型变化,春冬季最高,夏秋季最低;O₃则在内部两区域都大致呈倒“U”型变化,但峰值分布时间与持续时长明显不同;SO₂和CO年内无明显变化;(3)各污染物具有明显的空间聚集性特征,AQI及PM₁₀、PM_2.5     

Air Pollution and Stillbirth Risk: Exposure to Airborne Particulate Matter during Pregnancy Is Associated with Fetal Death

Objective

To test the hypothesis that exposure to fine particulate air pollution (PM_2.5) is associated with stillbirth.

Study Design

Geo-spatial population-based cohort study using Ohio birth records (2006-2010) and local measures of PM_2.5, recorded by the EPA (2005-2010) via 57 monitoring stations across Ohio. Geographic coordinates of the mother’s residence for each birth were linked to the nearest PM_2.5 monitoring station and monthly exposure averages calculated. The association between stillbirth and increased PM_2.5 levels was estimated, with adjustment for maternal age, race, education level, quantity of prenatal care, smoking, and season of conception.

Results

There were 349,188 live births and 1,848 stillbirths of non-anomalous singletons (20-42 weeks) with residence ≤10 km of a monitor station in Ohio during the study period. The mean PM_2.5 level in Ohio was 13.3 μg/m³ [±1.8 SD, IQR(Q1: 12.1, Q3: 14.4, IQR: 2.3)], higher than the current EPA standard of 12 μg/m³. High average PM_2.5 exposure through pregnancy was not associated with a significant increase in stillbirth risk, _adjOR 1.21(95% CI 0.96,1.53), nor was it increased with high exposure in the 1^st or 2^nd trimester. However, exposure to high levels of PM_2.5 in the third trimester of pregnancy was associated with 42% increased stillbirth risk, _adjOR 1.42(1.06,1.91).

Conclusions

Exposure to high levels of fine particulate air pollution in the third trimester of pregnancy is associated with increased stillbirth risk. Although the risk increase associated with high PM_2.5 levels is modest, the potential impact on overall stillbirth rates could be robust as all pregnant women are potentially at risk.     

Collection and characterization of a bulk PM2.5 air particulate matter material for use in reference materials

A contemporary PM_2.5 (particulate matter smaller than 2.5 Μm aerodynamic diameter) aerosol material from an urban site has been collected for the production of a new standard reference material that will be made available for the development of new PM_2.5 air quality standards. Air particulate matter corresponding to the PM_2.5 fraction was collected at an established Environmental Protection Agency monitoring site in Baltimore, Maryland. The air-sampling system that has been constructed for this collection separates fine particles with a cyclone separator and deposits them onto an array of Teflon membrane filters. The fine air particulate material is removed by ultrasonication or by mechanical means and collected for further preparation of standards. The composition of the collected PM_2.5 aerosol, as well as the composition of the deposited PM_2.5 aerosol, are determined by instrumental nuclear activation analysis and other techniques.     

Air Pollution in China: Mapping of Concentrations and Sources

China has recently made available hourly air pollution data from over 1500 sites, including airborne particulate matter (PM), SO₂, NO₂, and O₃. We apply Kriging interpolation to four months of data to derive pollution maps for eastern China. Consistent with prior findings, the greatest pollution occurs in the east, but significant levels are widespread across northern and central China and are not limited to major cities or geologic basins. Sources of pollution are widespread, but are particularly intense in a northeast corridor that extends from near Shanghai to north of Beijing. During our analysis period, 92% of the population of China experienced >120 hours of unhealthy air (US EPA standard), and 38% experienced average concentrations that were unhealthy. China’s population-weighted average exposure to PM_2.5 was 52 μg/m³. The observed air pollution is calculated to contribute to 1.6 million deaths/year in China [0.7–2.2 million deaths/year at 95% confidence], roughly 17% of all deaths in China.     

Ambient and household PM2.5 pollution and adverse perinatal outcomes: A meta-regression and analysis of attributable global burden for 204 countries and territories

BackgroundParticulate matter <2.5 micrometer (PM_2.5) is associated with adverse perinatal outcomes, but the impact on disease burden mediated by this pathway has not previously been included in the Global Burden of Disease (GBD), Mortality, Injuries, and Risk Factors studies. We estimated the global burden of low birth weight (LBW) and preterm birth (PTB) and impacts on reduced birth weight and gestational age (GA), attributable to ambient and household PM_2.5 pollution in 2019.Methods and findingsWe searched PubMed, Embase, and Web of Science for peer-reviewed articles in English. Study quality was assessed using 2 tools: (1) Agency for Healthcare Research and Quality checklist; and (2) National Institute of Environmental Health Sciences (NIEHS) risk of bias questions. We conducted a meta-regression (MR) to quantify the risk of PM_2.5 on birth weight and GA. The MR, based on a systematic review (SR) of articles published through April 4, 2021, and resulting uncertainty intervals (UIs) accounted for unexplained between-study heterogeneity. Separate nonlinear relationships relating exposure to risk were generated for each outcome and applied in the burden estimation.The MR included 44, 40, and 40 birth weight, LBW, and PTB studies, respectively. Majority of the studies were of retrospective cohort design and primarily from North America, Europe, and Australia. A few recent studies were from China, India, sub-Saharan Africa, and South America. Pooled estimates indicated 22 grams (95% UI: 12, 32) lower birth weight, 11% greater risk of LBW (1.11, 95% UI: 1.07, 1.16), and 12% greater risk of PTB (1.12, 95% UI: 1.06, 1.19), per 10 μg/m³ increment in ambient PM_2.5. We estimated a global population–weighted mean lowering of 89 grams (95% UI: 88, 89) of birth weight and 3.4 weeks (95% UI: 3.4, 3.4) of GA in 2019, attributable to total PM_2.5. Globally, an estimated 15.6% (95% UI: 15.6, 15.7) of all LBW and 35.7% (95% UI: 35.6, 35.9) of all PTB infants were attributable to total PM_2.5, equivalent to 2,761,720 (95% UI: 2,746,713 to 2,776,722) and 5,870,103 (95% UI: 5,848,046 to 5,892,166) infants in 2019, respectively. About one-third of the total PM_2.5 burden for LBW and PTB could be attributable to ambient exposure, with household air pollution (HAP) dominating in low-income countries. The findings should be viewed in light of some limitations such as heterogeneity between studies including size, exposure levels, exposure assessment method, and adjustment for confounding. Furthermore, studies did not separate the direct effect of PM_2.5 on birth weight from that mediated through GA. As a consequence, the pooled risk estimates in the MR and likewise the global burden may have been underestimated.ConclusionsAmbient and household PM_2.5 were associated with reduced birth weight and GA, which are, in turn, associated with neonatal and infant mortality, particularly in low- and middle-income countries.

Rakesh Ghosh and co-workers report on associations between particulate matter air pollution and adverse perinatal health outcomes.     

Beyond PM2.5: The role of ultrafine particles on adverse health effects of air pollution

BackgroundAir pollution constitutes the major threat to human health, whereas their adverse impacts and underlying mechanisms of different particular matters are not clearly defined.Scope of reviewUltrafine particles (UFPs) are high related to the anthropogenic emission sources, i.e. combustion engines and power plants. Their composition, source, typical characters, oxidative effects, potential exposure routes and health risks were thoroughly reviewed.Major conclusionsUFPs play a major role in adverse impacts on human health and require further investigations in future toxicological research of air pollution.General significanceUnlike PM_2.5, UFPs may have much more impacts on human health considering loads of evidences emerging from particulate matters and nanotoxicology research fields. The knowledge of nanotoxicology contributes to the understanding of toxicity mechanisms of airborne UFPs in air pollution. This article is part of a Special Issue entitled Air Pollution, edited by Wenjun Ding, Andrew J. Ghio and Weidong Wu.     

城市群空气污染综合评估范式与应用——以京津冀城市群PM2.5污染为例

城市群已成为中国城市发展的主要形式,城市化发展引发的一系列环境污染问题成为目前的研究重点之一,尤其是近年来明显的空气污染问题。由于传统的针对某一城市地区进行细致研究,难以解决在城市聚集的城市群下形成的区域性空气污染来源和影响机制等问题,使区域性空气污染造成的负面效应难以评估。通过构建综合评估模型范式,并运用空间分析,对京津冀168个区县2000年,2005年,2010年,2015年PM_2.5人口暴露风险、人类活动对PM_2.5的贡献、以及5种土地利用类型的"源汇"特征进行了实证研究。结果发现:(1)2000—2015年,京津冀城市群的人口暴露风险、空气污染分布、综合评估结果总体呈现北低南高的现象。(2)2000—2015年,各县域的人口暴露风险和空气污染的程度、范围呈上升趋势。不同的土地利用类型具有不同的源汇特征,且对污染的贡献不同。本研究通过综合评估模型范式对城市群或区域城市发展与空气质量的权衡关系模式开展量化解析,为城市的可持续发展提供了科学的范式和初步的实证示范。     

PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing,China

Objective

Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM_2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM_2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM_2.5 and meteorological factors.

Methods

Daily and hourly PM_2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM_2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM_2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM_2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM).

Results

Annual mean and median of PM_2.5 concentrations were 88.07 μg/m³ and 71.00 μg/m³, respectively, from August 2013 to July 2014. PM_2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM_2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM_2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM_2.5 concentration using the GAMM model (R ² = 0.59, AIC = 7373.84).

Conclusion

PM_2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM_2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM_2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM_2.5.