Health Impact Of Air Pollution Research Articles

Short-term impacts of air pollution on the platelet-lymphocyte ratio and neutrophil-lymphocyte ratio among urban adults in China

The short-term impacts of urban air pollution on the platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) remain obscure. In this study, we included 3487 urban adults from the Wuhan-Zhuhai cohort. Individual inhalation exposure to air pollutants was estimated by combining participants' daily breath volume and ambient concentrations of six air pollutants (including fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3)). The cumulative impacts were assessed by applying lag structures of up to 7 days before the survey date. Associations of air pollutants with PLR and NLR were assessed using a linear mixed model and Bayesian kernel machine regression (BKMR) model. We found that PLR was negatively related to PM2.5 (lag02-lag06), PM10 (lag02-lag07), NO2 (lag02-lag07), and SO2 (lag03-lag05) and NLR was negatively related to PM10 (lag05 and lag07). In the BKMR model, a negative joint association between the six-air-pollutant mixture and PLR and NLR was observed, whereas PM10 and NO2 appeared to be more important than the other pollutants in the mixture. The negative impact of air pollutants was stronger in males, participants with lower body mass index (< 24 kg/m2), those cooking meals at home, drinkers, and non-exercisers. In conclusion, short-term exposure to air pollutants is significantly related to PLR and NLR in peripheral blood. PLR and NLR may provide new insight into the molecular mechanism underlying the adverse health impact of air pollutants.

Air Pollution Health Impact Monitoring and Health Risk Assessment Technology and Its Application - China, 2006-2019.

Air pollution is a significant risk factor contributing to the burden of disease in China. Health risk assessment and management are important to reduce the impact of air pollution on public health. To help formulate standardized health risk assessment techniques, a series of studies were conducted from 2006 to 2019. Through systematic review, study of molecular mechanisms, epidemiological investigation, and health effect monitoring, the overall project established a monitoring and evaluation indicator system, a comprehensive information platform, software for automatic data cleaning, and standardized health risk assessment techniques. Technical specifications have been issued by the National Health Commission for promoting health risk assessments across China. This paper introduces the project, the research approach, its main research accomplishments, innovations, and public health significance, and describes directions for further research.

Identifying meteorological drivers of PM2.5 levels via a Bayesian spatial quantile regression

AbstractRecently, due to accelerations in urban and industrial development, the health impact of air pollution has become a topic of key concern. Of the various forms of air pollution, fine atmospheric particulate matter (PM2.5; particles less than 2.5 micrometers in diameter) appears to pose the greatest risk to human health. While even moderate levels of PM2.5 can be detrimental to health, spikes in PM2.5 to atypically high levels are even more dangerous. These spikes are believed to be associated with regionally specific meteorological factors. To quantify these associations, we develop a Bayesian spatiotemporal quantile regression model to estimate the spatially varying effects of meteorological variables purported to be related to PM2.5 levels. By adopting a quantile regression model, we are able to examine the entire distribution of PM2.5 levels; for example, we are able to identify which meteorological drivers are related to abnormally high PM2.5 levels. Our approach uses penalized splines to model the spatially varying meteorological effects and to account for spatiotemporal dependence. The performance of the methodology is evaluated through extensive numerical studies. We apply our modeling techniques to 5 years of daily PM2.5 data collected throughout the eastern United States to reveal the effects of various meteorological drivers.

Establishment of the Korea National Health and Nutrition Examination Survey air pollution study dataset for the researchers on the health impact of ambient air pollution.

To provide a nationwide representative dataset for the study on health impact of air pollution, we combined the data from the Korea National Health and Nutrition Examination Survey with the daily air quality and weather data by matching the date of examination and the residential address of the participants. The database of meteorological factors and air quality as sources of exposure data were estimated using the Community Multiscale Air Quality model. The linkage dataset was merged by three ways; administrative district, si-gun-gu (city, county, and district), and geocode (in latitude and longitude coordinate units) based on the participants’ residential address, respectively. During the study period, the exposure dataset of 85,018 individuals (38,306 men and 46,712 women) whose examination dates were recorded were obtained. According to the definition of exposure period, the dataset was combined with the data on short-term, mid-term, and long-term exposure to air pollutants and the meteorological indices. Calculation of the daily merged dataset’s average air pollution linked by si-gun-gu and geocode units showed similar results. This study generated a daily average of meteorological indices and air pollution exposure dataset for all regions including rural and remote areas in Korea for 11 years. It is expected to provide a platform for the researchers studying the health impact of air pollution and climate change on the representative population and area, which may facilitate the establishment of local health care plans by understanding the residents’ health status at the local as well as national level.

Assessing Health Impact of Air Pollutants in Five Iraqi Cities Using AirQ+ Model

Concentration of air pollutants CO, NO2, SO2, O3, PM10, PM2.5 in four Iraqi cities (Al-Najaf, Al-Muthanna, Maysan, Kirkuk) and PM2.5 in Baghdad city were monitored and analysed for the period September 1, 2019 to August 31, 2020. The results showed that the daily mean concentration of CO, NO2 for the four cities are well below the WHO air quality standard. In general, PM2.5 and PM10 concentrations are the factors that govern the air quality index in Iraqi cities under consideration. It is clear that, for all the cities under consideration, the daily AQI is mostly “Moderate” and to a less extent “Unhealthy for sensitive groups”. However, there are 53 days for Al-Muthanna (mainly due to PM10) and 58 days for Baghdad (due to PM2.5 alone) in which the AQI is “Unhealthy”. Moreover, there are another 53 days for Al-Muthanna in which the AQI is “Hazardus”. So, the air quality in Al-Muthanna and Baghdad can be considered lower than that in other cities. Indeed, this is attributed to dust storms in Al-Muthanna and high population of Baghdad city and consequently higher air pollutants emissions due to their industrial, transportation and electric generation activities. AirQ+ software was used to assess public health consequences of long term exposure to PM2.5 in terms of relative risk (RR). RR of acute lower respiratory disease, chronic obstructive pulmonary, mortality by lung cancer, ischemic heart disease, mortality by stroke for the five cities were assessed. RR of mortality by lung cancer due to exposure to PM2.5 in Baghdad is the highest among the cities under consideration. RRLC = 1.25 (95% CI = 1.14 – 1.4).

Cardiovascular effects of air pollution: current evidence from animal and human studies.

Air pollution is a global health concern. Particulate matter (PM)2.5, a component of ambient air pollution, has been identified by the World Health Organization as one of the pollutants that poses the greatest threat to public health. Cardiovascular health effects have been extensively documented, and these effects are still being researched to provide an overview of recent literature regarding air pollution-associated cardiovascular morbidity and mortality in humans. Additionally, potential mechanisms through which air pollutants affect the cardiovascular system are discussed based on human and additional animal studies. We used the strategy of a narrative review to summarize the scientific literature of studies that were published in the past 7 yr. Searches were carried out on PubMed and Web of Science using predefined search queries. We obtained an initial set of 800 publications that were filtered to 78 publications that were relevant to include in this review. Analysis of the literature showed significant associations between air pollution, especially PM2.5, and the risk of elevated blood pressure (BP), acute coronary syndrome, myocardial infarction (MI), cardiac arrhythmia, and heart failure (HF). Prominent mechanisms that underlie the adverse effects of air pollution include oxidative stress, systemic inflammation, endothelial dysfunction, autonomic imbalance, and thrombogenicity. The current review underscores the relevance of air pollution as a global health concern that affects cardiovascular health. More rigorous standards are needed to reduce the cardiovascular disease burden imposed by air pollution. Continued research on the health impact of air pollution is needed to provide further insight.

Association of long-term exposure to ambient air pollution with the incidence of sleep disorders: A cohort study in China

BackgroundSleep disorders have been verified to be associated with adverse health outcomes. Recent studies have linked ambient air pollution to sleep disorders. However, evidence with large sample size and especially prospective studies is very limited. MethodsWe used data from a prospective cohort study established from 2015 to 2018 in Ningbo, China. Participants were followed-up after baseline survey through linkage to the regional Health Information System (HIS). Sleep disorders were defined based on International Classification of Disease 10 (ICD-10). Spatial-temporal land-use regression (LUR) models were used to estimate the annual exposure to particulate matter with diameter ≤ 2.5 µm (PM2.5), ≤ 10 µm (PM10) and nitrogen dioxides (NO2). The associations between long-term exposure to air pollutants and prevalence of sleep disorders were examined using logistic regression models, and Cox regression models for the effects of air pollution on the incidence of sleep disorders. A generalized weighted quantile sum (gWQS) regression was used in the multipollutant analysis. ResultsA total of 38,775 participants were included in the final analysis. Based on baseline data, we observed significant positive associations between air pollution exposure and increased odds of prevalent sleep disorders (Odds Ratio (OR)= 1.48, 95% confidence interval (CI): 1.41–1.55 for PM2.5; OR= 1.47,95%CI:1.38–1.57 for PM10; OR= 1.38, 95%CI:1.31–1.46 for NO2). In the longitudinal analysis, hazard ratios for incident sleep disorders associated with per interquartile range (IQR) increase in PM2.5, PM10 and NO2 were 1.14 (1.03, 1.25), 1.13 (1.01, 1.27) and 1.13 (1.04, 1.23), respectively. A gWQS regression analysis showed significant association between air pollution mixture and incident sleep disorders (OR=1.11, 95%CI: 1.03–1.20). ConclusionsLong-term exposure to PM2.5, PM10 and NO2 were associated with increased risk of sleep disorders in a Chinese population. Our findings could provide evidence for a more general role in the adverse health impact of air pollution.

Seasonal Variations of Fine Particulate Matter and Mortality Rate in Seoul, Korea with a Focus on the Short-Term Impact of Meteorological Extremes on Human Health

Rapid industrialization of Korea’s economy has brought with it environmental pollution that threatens human health. Among various other pollutants, ambient fine particulate matter known to endanger human health often exceeds air quality standards in Seoul, South Korea’s capital. The goal of this research is to find the impact of meteorological extremes and particle levels on human health. The analysis was conducted using hourly air pollutant concentrations, meteorological variables, and the daily mortality from cerebrovascular disease. Results show that the effect of fine particulate matter on mortality from cerebrovascular disease was more noticeable during meteorological extremes. The linkage between extreme weather conditions and mortality was more apparent in winter than in summer. Comprehensive studies of various causes of diseases should be continued to more accurately analyze the effects of fine particulate matter on human health and meteorological extremes, and to further minimize the public health impact of air pollution and meteorological conditions.

An Improved Fault Diagnosis Strategy for Process Monitoring Using Reconstruction Based Contributions

Air pollution has become the fourth leading cause of premature death on Earth. Air pollution causes poor health and death; about one case out of every ten deaths worldwide is caused by air pollution, which is six times more than malaria. Human activities are the main cause of air pollution, such as chemical industries, road traffic, and fossil fuel power plants. Over the span of several years, monitoring air quality has become an exigent and essential task. In order to limit the health impact of air pollution and to ensure safe operation of chemical processes, it is necessary to quickly detect and locate instrumentation defects. There are several process monitoring techniques in the literature. Among these techniques is the one selected for this work for the detection and location of sensor faults: the kernel principal component analysis (KPCA) method, which was selected for its primary advantages of easy employment and less necessity for prior knowledge. Using the KPCA method for monitoring nonlinear systems, the calculation cost and the memory size are related to the number of initial data. This is currently a major limitation of the KPCA method, especially in industrial environments. In order to remedy this limitation, in this paper we propose a new method of detection and localization. The key idea of this approach is to extend the method of localization based on the principle of reconstruction-based contributions (RBC) by downsizing the kernel matrix in the characteristic space. The proposed technique is named reconstruction-based contribution reduced rank kernel principal component analysis(RBC-RRKPCA). The approach is demonstrated using real air quality monitoring network data and simulated data from the Tennessee Eastman process (TEP) as a challenging benchmark problem. We also present a comparative study of the performances of the conventional diagnostic technique RBC-KPCA and the proposed technique RBC-RRKPCA. The results in this paper reveal that the proposed technique achieves the highest detection and localization accuracy.

Quantifying the Deposition of Airborne Particulate Matter Pollution on Skin Using Elemental Markers.

Airborne particulate matter (PM) pollution is an environmental and health concern. The health impact of PM pollution has typically focused on the respiratory system. The impact of PM pollution on skin has been largely understudied due to the lack of a quantitative method to measure the deposition on skin. This manuscript presents a method to quantify PM pollution on skin using elemental markers as a proxy for PM. Skin tape strips were collected from forehead and buttock of 100 outdoor workers in Beijing, China. Skin samples were analyzed for 19 elemental markers using inductively coupled plasma mass spectrometry. To determine the specific elemental signature of PM for the region, air samples were collected over 7 days for PM < 2.5 μm (PM2.5) and analyzed for the same 19 elements as the skin samples. An enrichment factor was calculated for each element and the potential source was evaluated. Using the elemental markers unique to PM pollution for the region, the PM concentration deposited on skin was determined to be 0.621-2.53 μg PM2.5 /cm2. This method can be re-applied in different regions and the PM concentration on skin can inform future studies on the health impact of air pollution on skin.

Health Impact of Air Pollution from Shipping in the Baltic Sea: Effects of Different Spatial Resolutions in Sweden.

In 2015, stricter regulations to reduce sulfur dioxide emissions and particulate air pollution from shipping were implemented in the Baltic Sea. We investigated the effects on population exposure to particles <2.5 µm (PM2.5) from shipping and estimated related morbidity and mortality in Sweden’s 21 counties at different spatial resolutions. We used a regional model to estimate exposure in Sweden and a city-scale model for Gothenburg. Effects of PM2.5 exposure on total mortality, ischemic heart disease, and stroke were estimated using exposure–response functions from the literature and combining them into disability-adjusted life years (DALYS). PM2.5 exposure from shipping in Gothenburg decreased by 7% (1.6 to 1.5 µg/m3) using the city-scale model, and 35% (0.5 to 0.3 µg/m3) using the regional model. Different population resolutions had no effects on population exposures. In the city-scale model, annual premature deaths due to shipping PM2.5 dropped from 97 with the high-sulfur scenario to 90 in the low-sulfur scenario, and in the regional model from 32 to 21. In Sweden, DALYs lost due to PM2.5 from Baltic Sea shipping decreased from approximately 5700 to 4200. In conclusion, sulfur emission restrictions for shipping had positive effects on health, but the model resolution affects estimations.

Air pollution and implications of health research for policy-making byNational Centre for Disease Control, India

Air pollution is a major risk factor for ill health in India. In India, 1·24 million deaths in 2017 were attributable to air pollution. The National Programme on Climate Change and Human Health (NPCCHH) of the Health Ministry, formed in 2019, and the National Centre for Disease Control (NCDC), the nodal technical agency for it, are working on strategies related to air pollution and health issues. Under NPCCHH, following areas are being addressed: Firstly, initiation of surveillance of respiratory illnesses at sentinel hospitals and analysis in context of changing air quality indices (AQI). This surveillance is run in Delhi since 2017 and has helped understanding pattern of emergency visits in relation to changing pattern of AQI. Now another 11 States, 42 hospitals in 35 cities have started this surveillance. NPCCHH targets to establish it in hospitals of all polluted cities. States are being supported to develop Heath Adaptation Plans which would detail their health sector preparedness plans to be undertaken for protecting against health impact of air pollution. Meanwhile NCDC issues advisories to states about necessary activities to be implemented. NCDC is working on increasing awareness among general and vulnerable population. Health message templates have been created and disseminated using social messaging platforms, and also are shared with states for translation in local languages and dissemination. Awareness drives are organized on various occasions. Another area being addressed is capacity building of medical professionals in topics related to air pollution. One of the challenges is about having evidence on intervention measures that protect human health. NCDC has identified some areas for research and requested research institutions to develop and fund proposals on them so as to help Health Ministry with making informed policy decisions.

Health impact ofenvironmental pollution and protective effect of masks in Japan

Background/Aim: The health effects of cross-border air pollution and Asian dust (AD) originating from drylands, such as the Gobi Desert and Taklamakan Desert, have been a concern in Asia. To overcome the global issue of air pollution, wearing masks is recommended. However, the protective effect of wearing masks are unclear. We assessed the health impact of air pollution and the protective effect of masks.Methods: We administered diary-style web-based questionnaires to 48 volunteers who lived in Yonago City in Japan between 2015 and 2016. The results were evaluated using a 4-level subjective symptom score (29 variables include respiratory, nasal, ocular, and skin symptoms), history of the disease, and preventive behaviors (e.g., mask use). Association between the symptom scores and analyzed components for AD, splash sea salt, sulfate aerosol, nitrate aerosol, Organic carbon, Black carbon were assessed using a linear mixed model. Data regarding climate (temperature, humidity, and atmospheric pressure) and environmental factors were used as covariates. Regarding symptom prevention measures, we measured particle leakage rates of participants’ masks. Results: The association between respiratory symptoms and sulfate aerosol was significant (P trend=0.013, odds ratio [OR] of the highest quartile [Q4] vs. the lowest[Q1]=1.34, 95% CI=1.10 to 1.65). The relationship between symptoms and sulfate aerosol was also significant in the mask-wearing groups. Even with N95 or virus filtration efficiency masks, the leakage rate was high, suggesting that fitting is more important in addition to mask filter quality.Conclusions: We found that exposure to air pollution increased the risk of adverse subjective symptoms. We also found that it is essential to wear a mask that fits the facial features without a gap between the face and mask.

What does calculating impacts of specific morbidity outcomes add to perceptions of air pollution health impact assessment?

Introduction: Health impact assessments often use broad categories of outcomes, e.g. all respiratory or all cardiovascular admissions. This minimises diagnostic misclassification but does not fully communicate the evidence on associations between air pollution and specific diseases. More specific health impact calculations may resonate with the public more than severe but rarer outcomes.Methods: Literature searches were done for meta-analyses pooling evidence on a variety of pollutants (PM10, PM2.5, NO2 and O3) and 40 health outcomes. We investigated the effects of short- and long-term exposure to pollution and did final calculations on 17 morbidity outcomes, rejecting those with weaker evidence, lack of baseline rates, and no priority from focus groups. The selected concentration-response functions were combined with monitoring site, baseline rate/cases and population (e.g. beside roads) data to calculate health impacts in up to 4 scenarios (roadside vs background (daily and annual); 75th vs 25th percentile daily average and a 20% reduction in annual average) across 9 UK and 4 Polish cities. The largest result per pollutant was given rather than summing across pollutants.Results: The largest change in number of cases was for children with low lung function in London (7927 for a 20% reduction in NO2). Changes in cases of acute bronchitis in children in London were also high (3683 for a 20% reduction in PM10). Warsaw had greater impacts on cardiovascular than respiratory endpoints compared with London. Other example statements include ‘living near busy roads in Oxford may stunt lung growth in children by 14%’ and ‘in London on higher pollution days, 142 more children with asthma experience symptoms than on lower pollution days’.Conclusions: Health impact statements for a wider variety of outcomes may aid communication of the importance of different health effects to policymakers and the public.

Association of ambient particle pollution with gestational diabetes mellitus and fasting blood glucose levels in pregnant women from two Chinese birth cohorts

BackgroundFasting blood glucose may capture the adverse effects of air pollution on pregnant women better than the incidence of gestational diabetes mellitus (GDM), but evidence on the association between air pollution and maternal glucose concentrations is limited. ObjectiveTo investigate the associations between air pollutants, GDM and fasting blood glucose during pregnancy. MethodsWe recruited 2326 pregnant women from two birth cohorts located in Guangzhou and Heshan, the Pearl River Delta region (PRD), China. PM10, PM2.5 and black carbon (BC) exposure concentrations in the first and second trimesters of pregnancy were collected at fixed-site monitoring stations for each cohort. Multiple logistic regressions were employed to estimate the associations between particle pollution and GDM. Mixed-effects models were used to evaluate the associations of air pollutants with blood glucose levels. Restricted cubic spline functions were fitted to visualize the concentration-response relationships. Distributed lag non-linear models were used to estimate week-specific lag effects of particle pollution exposure on GDM and blood glucose. Unconstrained distributed lag models with lags of 0–3 weeks were used to examine potential cumulative effects. ResultsWe observed positive and significant associations of PM10, PM2.5 and BC exposure with fasting glucose, particularly in the second trimester. PM10, PM2.5 and BC were strongly correlated and displayed similar cumulative (lag 0–3 weeks) associations with fasting blood glucose. Exposure to particle pollution was not associated with 1-h or 2-h blood glucose. Models estimating the association between air pollutants and GDM were consistent with statistical insignificance. ConclusionsBased on the results of the present study, exposure to air pollution during pregnancy exerts cumulative, adverse effects on fasting glucose levels. This study provides preliminary support for the use of blood glucose levels to explore the potential health impact of air pollution on pregnant women.

Health Impact Assessment of Volcanic Ash Inhalation: A Comparison With Outdoor Air Pollution Methods.

This paper critically appraises the extrapolation of concentration‐response functions (CRFs) for fine and coarse particulate matter, PM2.5 and PM10, respectively, used in outdoor air pollution health impact assessment (HIA) studies to assess the extent of health impacts in communities exposed to volcanic emissions. Treating volcanic ash as PM, we (1) consider existing models for HIA for general outdoor PM, (2) identify documented health effects from exposure to ash in volcanic eruptions, (3) discuss potential issues of applying CRFs based on the composition and concentration of ash‐related PM, and (4) critically review available case studies of volcanic exposure scenarios utilizing HIA for outdoor air pollution. We identify a number of small‐scale studies focusing on populations exposed to volcanic ash; exposure is rarely quantified, and there is limited evidence concerning the health effects of PM from volcanic eruptions. That limited evidence is, however, consistent with the CRFs typically used for outdoor air pollution HIA. Two health assessments of exposure to volcanic emissions have been published using population‐ and occupational‐based CRFs, though each application entails distinct assumptions and limitations. We conclude that the best available strategy, at present, is to apply outdoor air pollution risk estimates to scenarios involving volcanic ash emissions for the purposes of HIA. However, due to the knowledge gaps on, for example, the health effects from exposure to volcanic ash and differences in ash composition, there is inherent uncertainty in this application. To conclude, we suggest actions to enable better prediction and assessment of health impacts of volcanic emissions.

Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs.

Despite the increased attention given to the health impact assessment of air pollution and to the strategies to control it in both scientific literature and concrete interventions, the results of the implementations, especially those involving traffic, have not always been satisfactory and there is still disagreement about the most appropriate interventions and the methods to assess their effectiveness. This state-of-the-art article reviews the recent interpretation of the concepts that concern the impact assessment, and compares old and new measurements of attributable risk and attributable fraction. It also summarizes the ongoing discussion about the designs and methods for assessing the air pollution impact with particular attention to improvements due to spatio-temporal analysis and other new approaches, such as studying short term effects in cohorts, and the still discussed methods of predicting the values of attributable risk (AR). Finally, the study presents the more recent analytic perspectives and the methods for directly assessing the effects of not yet implemented interventions on air quality and health, in accordance with the suggestion in the strategic plan 2020−2025 from the Health Effect Institute.

The winter choke: Coal-Fired heating, air pollution, and mortality in China

China’s coal-fired winter heating systems generate large amounts of hazardous emissions that significantly deteriorate air quality. Exploiting regression discontinuity designs based on the exact starting dates of winter heating across different cities, we estimate the contemporaneous impact of winter heating on air pollution and health. We find that turning on the winter heating system increased the weekly Air Quality Index by 36% and caused 14% increase in mortality rate. This implies that a 10-point increase in the weekly Air Quality Index causes a 2.2% increase in overall mortality. People in poor and rural areas are particularly affected by the rapid deterioration in air quality; this implies that the health impact of air pollution may be mitigated by improved socio-economic conditions. Exploratory cost-benefit analysis suggests that replacing coal with natural gas for heating can improve social welfare.

Estimating health burden and economic loss attributable to short-term exposure to multiple air pollutants in China

Existing studies focused on the evaluation of health burden of long-term exposure to air pollutants, whereas limited information is available on short-term exposure, particularly in China. Air pollutant concentrations in 338 Chinese cities in 2017 were used to estimate the air pollutants related health burden which was defined as premature mortalities from all-cause, cardiovascular and respiratory disease as well as hospital admissions for cardiovascular and respiratory disease. Log-linear model was used as the exposure-response function to estimate the health burden attributable to each air pollutant. The value of statistical life and cost of illness methods were used to estimate economic loss of the premature mortalities and hospital admissions, respectively. The national all-cause premature mortalities attributable to all air pollutants was 1.35 million, accounting for 17.2% of reported deaths in China in 2017. Among all-cause premature mortality, contributions of PM2.5, PM2.5-10, NO2, SO2, O3 and CO were11.1%, 5.2%, 28.9%, 9.6%, 23.0%, and 22.2%, respectively. The national cardiovascular and respiratory premature mortalities were 0.77 and 0.21 million, respectively. About 7.8 million cardiovascular and respiratory disease hospital admissions were attributed to short-term exposure to all air pollutants. The economic loss of the overall health burden (premature mortality and hospital admissions) was 2065.54 billion Yuan, which was equivalent to 2.5% of the national GDP in 2017. The health burden and economic loss attributable to short-term exposure to ambient air pollutant are substantial in China. It suggested that the adverse health effects attributable to short-term exposure to air pollutant should not be neglected in China. In order to reduce the health impact of air pollution, each city should develop air pollution prevention and control measures based on existing scientific evidence.

Geographically distributed longitudinal nitrogen dioxide and other air pollution sensor measurements in the Avon Longitudinal Study of Parents and Children cohort catchment area

Longitudinal cohort studies provide unique opportunities to investigate the health impact of air pollution. We aimed to enhance the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort study through the systematic collection of routinely monitored air pollution data collected by local authorities and the Department for Environment, Food and Rural Affairs (DEFRA) using a range of sensor technologies. These sensor data are in themselves not well suited for population epidemiology, rather these data are primarily used for validating and calibrating modelled air pollution concentration data over study areas. In this data note we describe the sources of routine air pollution monitoring data and detail data of pollutants including nitrogen dioxide, nitric oxide, nitrogen oxides, particulate matter, benzene and ozone collated from the local authorities that overlap the ALSPAC catchment area (Bristol, North Somerset, South Gloucestershire and part of Bath and North East Somerset).