Morbidity and pollution: Model specification analysis for time-series data on hospital admissions

Time-series analysis of effects of pollutants on emergency hospital admissions indicates important synergistic interactions among pollutants and to a lesser degree nonlinearities in effects of single pollutants. Comparisons of alternative econometric specifications are made to determine the appropriateness of incorporating nonuniform pollution impacts. The data substantially support the existence of synergisms among pollutants with high levels of sulfur dioxide, SO₂ (particulates), increasing the impact of particulates (SO₂) on emergency hospital admissions. Marginal effects of either pollutant are, however, small at current ambient air quality levels. These results indicate that damage estimates were likely to be understated during the 1960's when pollution levels were high, while, at current levels of those pollutants considered here, marginal damages are lower than would be estimated in studies failing to incorporate synergistic and nonlinear impacts.     

Investigating the impact of air pollution on AMI and COPD hospital admissions in the coastal city of Qingdao,China

• The impact of air pollution on AMI/COPD hospital admissions were examined. • Significant connection was found between air pollutants and AMI/COPD in Qingdao. • Nonlinearity exists between air pollution and AMI/COPD hospital admissions. Air pollution has been widely associated with adverse effects on the respiratory and cardiovascular systems. We investigated the relationship between acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD) and air pollution exposure in the coastal city of Qingdao, China. Air pollution in this region is characterized by inland and oceanic transportation sources in addition to local emission. We examined the influence of PM_2.5, PM₁₀, NO₂, SO₂, CO and O₃ concentrations on hospital admissions for AMI and COPD from October 1, 2014, to September 30, 2018, in Qingdao using a Poisson generalized additive model (GAM). We found that PM_2.5, PM₁₀, NO₂, SO₂ and CO exhibited a significant short-term (lag 1 day) association with AMI in the single-pollutant model among older adults (>65 years old) and females, especially during the cold season (October to March). In contrast, only NO₂ and SO₂ had clear cumulative lag associations with COPD admission for females and those over 65 years old at lag 01 and lag 03, respectively. In the two-pollutant model, the exposure-response relationship fitted by the two-pollutant model did not change significantly. Our findings indicated that there is an inflection point between the concentration of certain air pollutants and the hospital admissions of AMI and COPD even under the linear assumption, indicative of the benefits of reducing air pollution vary with pollution levels. This study has important implications for the development of policy for air pollution control in Qingdao and the public health benefits of reducing air pollution levels.     

Air pollution effects on hospital admissions: a statistical analysis of parallel time series

A statistical model for longitudinal count data is used to examine the potential adverse health effects of ambient air pollution. Daily respiratory admissions to 164 acute care hospitals in Ontario are obtained for the period 1983 to 1988. Estimates of ozone levels in the vicinity of each hospital are determined from air pollution monitoring stations maintained by the Ontario Ministry of the Environment. Generalized estimating equation methods are used to make inferences about the regression and overdispersion parameters. The admission data display little evidence of serial correlation and extra Poisson variation. However, admission rates vary considerably among hospitals. This latter source of variation needs to be taken into account in examining the effects of air pollution on respiratory health status.     

大气生物污染与健康的研究

本文综述了大气生物污染及其引起疾病方面的研究。在大气微生物污染方面包括了细菌、病毒，特别是真菌污染及其引起的疾病，甚至癌症。在植物花粉对大气的污染方面，介绍了枯草热的发生原因和对健康的危害。作者认为，大气生物污染的评价、治理和毒理学效应等问题值得注意并应进一步研究。     

Risk of respiratory and cardiovascular hospitalisation with exposure to bushfire particulates: new evidence from Darwin, Australia

The risk of hospitalisation from bushfire exposure events in Darwin, Australia, is examined. Several local studies have found evidence for the effects of exposure to bushfire particulates on respiratory and cardiovascular hospital admissions. They have characterised the risk of admission from seasonal exposures to biomass air pollution. A new, unanalysed data set presented an additional chance to examine unique exposure effects, as there are no anthropogenic sources of particulates in the vicinity of the exposure monitor. The incidence of daily counts of hospital admissions for respiratory and cardiovascular diagnoses was calculated with respect to exposures of particulate matter (PM₁₀), course particulate matter, fine particulate matter (FPM) and black carbon composition. A Poisson model was used to calculate unadjusted (crude) measures of effect and then adjusted for known risk factors and confounders. The final model adjusted for the effects of minimum temperature, relative humidity, a smoothed spline for seasonal effects, ‘date’ for a linear effect over time, day of the week and public and school holidays. A subset analysis adjusted for an influenza epidemic in a particular year. The main findings suggest that respiratory admissions were associated with exposure to PM₁₀ with a lag of 1?day when adjusted for flu and other confounders (RR?=?1.025, 95?% CI 1.000–1.051, p?<?0.05). This effect is strongest for exposure to FPM concentrations (RR?=?1.091, 95?% CI 1.023–1.163, p?<?0.01) when adjusted for flu. Respiratory admissions were also associated with black carbon concentrations recorded the previous day (RR?=?1.0004, 95?% CI 1.000–1.0008, p?<?0.05), which did not change strength when adjusted for flu. Cardiovascular admissions had the strongest association with exposure to same-day PM and highest RR for exposure to FPM when adjusted for confounders (RR?=?1.044, 95?% CI 0.989–1.102). Consistent risks were also found with exposure to black carbon with lags of 0–3?days.     

PM2.5 concentration declining saves health expenditure in China

● Monthly hospitalization expenses are sensitive to increases in PM_2.5 exposure. ● The increased PM_2.5 causes patients with CHD and LRI to stay longer in the hospital. ● The impact of PM_2.5 on total expenses for stroke is greater in southern China. ● Males may be more sensitive to air pollution than females. Air pollution has been a severe issue in China. Exposure to PM_2.5 has adverse health effects and causes economic losses. This study investigated the economic impact of exposure to PM_2.5 pollution using monthly city-level data covering 88.5 million urban employees in 2016 and 2017. This study mainly focused on three expenditure indicators to measure the economic impact considering lower respiratory infections (LRIs), coronary heart disease (CHD), and stroke. The results show that a 10 µg/m³ increase in PM_2.5 would cause total monthly expenses of LRIs, CHD, and stroke to increase by 0.226%, 0.237%, and 0.374%, respectively. We also found that LRI, CHD, and stroke hospital admissions increased significantly by 10%, 8.42%, and 5.64%, respectively. Furthermore, the total hospital stays of LRIs, CHDs, and strokes increased by 2.49%, 2. 51%, and 1.64%, respectively. Our findings also suggest heterogeneous impacts of PM_2.5 exposures by sex and across regions, but no statistical evidence shows significant differences between the older and younger adult subgroups. Our results provide several policy implications for reducing unequal public health expenditures in overpolluted countries.     

广州市空气污染物和气象要素的主成分与典型相关分析

用主成分和典型相关分析方法分析广州市近4a(2001—2004年)的空气污染物与气象要素之间的关系,按夏半年、冬半年和全年3个时间尺度分别进行。结果表明:污染物数据所得到的主成分分别代表机动车污染源(汽油燃烧和扬尘)和工业污染源(工业燃煤和燃油),气象数据的主成分分析表明空气的温度、湿度及对流速度对空气污染作用明显,而污染物和气象要素的主成分分析表明气温高低和空气干湿程度对大气污染的影响较大。污染物与气象要素两组数据之间的典型相关分析表明污染物与气象要素之间存在显著的相关关系,其中温度和风速对气态污染物有显著影响。     

天津市大港石化发展规划区大气SO2排放总量控制实例分析

污染物排放总量控制是控制环境污染、实现可持续发展的一项根本措施，本文在全面调查和监测天津市大港石化发展规划区大气ＳＯ２现状污染水平的基础上，分析和计算出该区域ＳＯ２排放控制总量。提出了在周围边缘重点大气污染源存在下对区域大气污染物排放总量方法的一种改进。     

An empirical analysis of air pollution dose-response curves

The authors combine information from 2 million death certificates and 2 million observations from the Public Use Sample. With several strategies for controlling extraneous variation, the authors explore these data in order to measure the chronic effects of several air pollutants on white mortality rates. In the United States, approximately 140,000 deaths a year (Wo of all deaths) may be associated with air pollution. The size of this effect increases dramatically with age, with children displaying no detectable associations. Some pollutants, especially sulfate, are closely associated with many deaths, whereas other pollutants, especially ozone and nitrogen dioxide, have no apparent effect on expected lifetimes.     

表观遗传学机制与空气污染的健康效应

空气污染是一个全球性的问题,并且具有深远的环境影响。暴露于空气污染会对人体健康产生许多不同的影响,理解空气污染的健康效应又是一个复杂命题,既要考虑不同类型的污染物同时也要考虑相关疾病的复杂性。然而越来越多的研究表明,表观遗传学在空气污染相关疾病的发生、发展中发挥着重要的作用。空气污染物可引起DNA甲基化、组蛋白修饰和miRNA表达等表观遗传学改变,这种改变往往发生在疾病产生的早期,因此相关研究不仅可以了解疾病的发病机制,而且还为疾病早期诊断和预防筛选可能的标志物。本文综述了表观遗传学的几种修饰方式和空气污染物造成不良健康损伤机制的一些研究进展。     

嘉善冬季PM2.5化学组分特征及来源分析

为研究嘉兴地区嘉善冬季污染时段和清洁时段PM_2.5化学组分特征,结合气象数据对2019年1月嘉兴市嘉善县善西超级站在线自动监测PM_2.5及化学组分数据、气态污染物(NO₂和SO₂)进行了分析.结果表明,2019年1月嘉善善西超级站污染时段PM_2.5浓度(97.18μg·m^-3)为清洁时段(36.77μg·m^-3)的2.6倍.污染时段水溶性离子浓度(41.58μg·m^-3)较清洁时段(19.82μg·m^-3)高21.76μg·m^-3,但占比有所降低,含碳组分比例增加.OC;EC比值为3.93,可能受到燃煤及机动车排放的共同影响.低风速及高湿有利于NO₂和SO₂等气态污染物进行二次转化,污染时段硫转化率和氮转化率均比清洁时段高,分别增高7.93%和54.11%,说明NOx向硝酸盐二次转化较为明显,导致颗粒物浓度升高.聚类分析结果显示67.34%气流来自北方,且相应的气流轨迹上污染物浓度比周边高,说明污染物存在一定的长距离输送.结合风玫瑰图可以看出,污染主要为本地及其周边的输送,污染物的长距离输送在短时会使污染浓度突增.因此,在重点关注本地及周边污染的同时,偏北气流下的污染物区域输送不可忽视.     

大气中黑碳的健康效应及机制研究进展

虽然人类社会不断进步发展,但大量工业和自然排放也导致了严重的空气污染。大气颗粒物是大气污染物的主要成分之一,黑碳是其中的重要组成成分,被国际癌症研究机构(IARC)归类为2B类致癌物。黑碳可以吸附其他致癌物质,会对环境和人体健康产生不利影响,因此黑碳暴露对人类的危害得到越来越多的重视。空气中黑碳的水平与心血管、呼吸和神经系统疾病的发生都有关系;黑碳主要通过引起氧化应激和炎症反应,诱发基因突变等一系列损伤。虽然现今对于黑碳健康效应的研究已取得了一些进展,但研究多数处于起步阶段,且仅针对黑碳本身进行单独研究,未来还需要加强开展对黑碳和其他污染物联合毒性效应及机制的研究。本综述主要针对近年来已开展的研究进行了总结归纳。     

过敏症状儿童室内PM_(2.5)对小鼠巨噬细胞的氧化损伤及VE的抗氧化保护作用研究

越来越多的研究提示,主要空气污染物PM_(2.5)暴露浓度的升高与儿童过敏性疾病的发病率有着密切的关系,然而PM_(2.5)暴露与过敏性疾病之间的关联尚未完全阐明。为探究患有过敏症状儿童的室内PM_(2.5)对小鼠巨噬细胞的氧化损伤作用以及维生素E(vitamin E,VE)的抗氧化保护作用,从5户患有1种或1种以上的过敏性症状(如过敏性鼻炎、哮喘)儿童的室内采集PM_(2.5),分别考察了不同剂量PM_(2.5)暴露24 h后如何影响小鼠巨噬细胞的氧化应激水平,指标包括活性氧(ROS),还原型谷胱甘肽(GSH),丙二醛(MDA),8-羟基脱氧鸟苷(8-OH-dG),以及炎症因子水平,指标包括肿瘤坏死因子ɑ(TNF-ɑ),白介素8β(IL-8β)的影响。结果表明,200μg·mL~(-1)PM_(2.5)暴露组与对照组比较,细胞内ROS积累,出现脂质过氧化以及DNA损伤,并伴有炎症反应的发生,差异均有统计学意义(P0.05或P0.01);VE(50 mg·mL~(-1))+200μg·mL~(-1)PM_(2.5)组的ROS、MDA、8-OHdG、TNF-ɑ、IL-8β含量低于200μg·mL~(-1)PM_(2.5)组,GSH含量高于200μg·mL~(-1)PM_(2.5)组。较高剂量(200μg·mL~(-1))PM_(2.5)可诱导小鼠腹腔巨噬细胞出现氧化损伤,VE在该应激过程中起着一定的保护作用。     

抚顺城区大气悬浮颗粒物污染与呼吸系统疾病死亡率相关性的定量分析

为了定量分析大气总悬浮颗粒物(TSP)对居民呼吸系统疾病死亡率的影响,采用单因素泊松(Poisson)回归分析法,研究了辽宁省抚顺市城区TSP浓度变化与市区1999～2003年呼吸系统疾病死亡率的相关关系.结果发现,在消除了时间、气象等因素影响后,滞后4日TSP浓度每增加50μg·m-3,呼吸系统疾病总人群组死亡率相对危险度(OR)增加1.02195(95%CI=1.00195～1.04245),即滞后4日TSP浓度变化造成总人群组呼吸系统疾病死亡率明显增加的超额死亡率为2.195%.抚顺城区大气TSP污染可能是市区居民呼吸系统疾病死亡率增加的原因之一.     

Discovery of emerging organic pollutants in the atmosphere through an omics approach

● We review the framework of discovering emerging pollutants through an omics approach. ● High-resolution MS can digitalize atmospheric samples to full-component data. ● Chemical features and databases can help to translate untargeted data to compounds. ● Biological effect-directed untargeted analyses consider both existence and toxicity. Ambient air pollution, containing numerous known and hitherto unknown compounds, is a major risk factor for public health. The discovery of harmful components is the prerequisite for pollution control; however, this raises a great challenge on recognizing previously unknown species. Here we systematically review the analytical techniques on air pollution in the framework of an omics approach, with a brief introduction on sample preparation and analysis, and in more detail, compounds prioritization and identification. Through high-resolution mass spectrometry (HRMS, typically coupled with chromatography), the complicated environmental matrix can be digitalized into “full-component” data. A key step to discover emerging compounds is the prioritization of compounds from massive data. Chemical fingerprints, suspect lists and biological effects are the most vital untargeted strategies for comprehensively screening critical and hazardous substances. Afterward, compressed data of compounds can be identified at various confidence levels according to exact mass and the derived molecular formula, MS libraries, and authentic standards. Such an omics approach on full-component data provides a paradigm for discovering emerging air pollutants; nonetheless, new technological advancements of instruments and databases are warranted for further tracking the environmental behaviors, hence to evaluate the health risk of key pollutants.     

广州市区大气污染特征与影响因子分析

以2000—2004年广州市国控测点的空气环境质量自动监测结果为基础数据,以我国《大气环境质量标准》的日平均质量浓度二级标准为依据计算广州市2000—2004年的各大气污染物的指数及污染负荷率,阐明广州市区主要大气污染物SO2、NO2、PM10、CO的地域分布特征、季节变化特征、年际变化特征以及由于大气中的酸性物质而形成的酸雨的变化特征并提出研究对策。结果表明:各污染物质量浓度存在明显的季节变化规律,除SO2春夏秋季污染最严重,其余几项污染程度由高到低的顺序均为冬季,春季,秋季,夏季。近5年来空气中的一氧化碳呈显著下降趋势,但二氧化硫、二氧化氮和可吸入颗粒物则呈显著上升趋势,综合污染指数也呈明显上升趋势;酸雨频率呈不显著上升且夏秋季污染大于春冬两季。广州市大气污染分布规律与风向频率以北和东北偏北方向较大,东和东南方向次之的分布基本一致。     

Air pollutant levels are 12 times higher than guidelines in Varanasi,India. Sources and transfer

Air quality in an urban atmosphere is regulated by both local and distant emission sources. For air quality management in urban areas, identification of sources and their relationships with local meteorology and air pollutants are essential. The critical condition of air quality in Indo-Gangetic plain is well known, but lack of data on both local and distant emission sources limits the scope of improving air quality in this region. Concentrations of particulate matter of size lower than 10 μm (PM₁₀) were assessed in the highly urbanized Varanasi city situated in middle Indo-Gangetic plain of India from 2014 to 2017, to identify the distant air pollution sources based on trajectory statistical models and local sources by conditional bivariate probability function. Modifying effects of meteorology and air pollutants on PM₁₀ were also explored. Mean PM₁₀ concentration for the study period was 244.8 ± 135.8 μg m^?3, which was 12 times higher than the WHO annual guideline. Several distinct sources of traffic as the major source of PM₁₀ were identified in the city. Trajectory statistical models like cluster analysis, potential source contribution function and concentration-weighted trajectory showed significant contributions from north-west and eastern directions in the transport of polluted air masses to the city. Dew point, wind speed, temperature and ventilation coefficient are the major factors in PM₁₀ formation and dispersion.     

Multivariate imputation in cross-sectional analysis of health effects associated with air pollution

We demonstrate a recently developed spatial interpolation methodology in a study of the chronic effects of air pollution on respiratory morbidity. Our study uses data from the Ontario Health Study, a large survey of households in Ontario conducted for the province by Statistics Canada. The interpolation procedure imputes unobserved vectors of air pollution concentrations for individual Public Health Units, from those observed at a few fixed air pollution monitoring sites. We use logistic regression methods to assess the significance of air pollution levels based on the imputed values after modelling the relationship between binary health responses and assorted covariates such as measures of life style. Our findings prove negative; no significant relationship between chronic respiratory morbidity and air pollution is found. The imputation methodology is seen to be promising and might well be used in other such analyses.     

Bewertungsverfahren Verfahren zur Bewertung von immissionsbedingten Stoffanreicherungen in standardisierten Graskulturen

Standardized grass cultures are routinely used to evaluate the accumulation of air pollutants. For the assessment of air pollutant accumulation in grass cultures, it is particularly important to distinguish between “normal” concentrations and the significantly increased accumulation caused by air pollution. This article presents a method to determine “normal” element concentrations (background levels) and define threshold values for the significantly elevated accumulation of pollutants for individual series of grass cultures. By applying the same method for the data from six regional air quality measuring programs, it was possible to derive universally applicable “normal” concentrations and threshold values for grass cultures. The described method is not limited to the evaluation of data from grass cultures but is also suitable for other biological or ecological data. It allows to distinguish between “normal” element concentrations and unusually high or low concentrations.