Assessment of population exposure to PM10 for respiratory disease in Lanzhou (China) and its health-related economic costs based on GIS

Evaluating the mortality and health rate caused by the PM2.5 pollutant in the air of several important Iranian cities and evaluating the effect of variables with a linear time series model

All over the world, the level of special air pollutants that have the potential to cause diseases is increasing. Although the relationship between exposure to air pollutants and mortality has been proven, the health risk assessment and prediction of these pollutants have a therapeutic role in protecting public health, and need more research. The purpose of this research is to evaluate the ill-health caused by PM2.5 pollution using AirQ + software and to evaluate the different effects on PM2.5 with time series linear modeling by R software version 4.1.3 in the cities of Arak, Esfahan, Ahvaz, Tabriz, Shiraz, Karaj and Mashhad during 2019-2020. The pollutant hours, meteorology, population and mortality information were calculated by the Environmental Protection Organization, Meteorological Organization, Statistics Organization and Statistics and Information Technology Center of the Ministry of Health, Treatment and Medical Education for 24 h of PM2.5 pollution with Excel software. In addition, having 24 h of PM2.5 pollutants and meteorology is used to the effect of variables on PM2.5 concentration. The results showed that the highest and lowest number of deaths due to natural deaths, ischemic heart disease (IHD), lung cancer (LC), chronic obstructive pulmonary disease (COPD), acute lower respiratory infection (ALRI) and stroke in The effect of disease with PM2.5 pollutant in Ahvaz and Arak cities was 7.39-12.32%, 14.6-17.29%, 16.48-8.39%, 10.43-18.91%, 12.21-22.79% and 14.6-18.54 % respectively. Another result of this research was the high mortality of the disease compared to the mortality of the nose. The analysis of the results showed that by reducing the pollutants in the cities of Karaj and Shiraz, there is a significant reduction in mortality and linear modeling provides a suitable method for air management planning.

Heat exposure assessment based on high-resolution spatio-temporal data of population dynamics and temperature variations

Urban heat waves pose a significant risk to the health and safety of city dwellers, with urbanization potentially amplifying the health impact of extreme heat. Accurate assessments of population heat exposure hinge on the interplay between temperature, population spatial dynamics, and the epidemiological effects of temperature on health. Yet, many past studies have over-simplified the matter by assuming static populations, leading to substantial inaccuracies in heat exposure assessments. To address these issues, this study integrates dynamic population data, fluctuating temperature, and the exposure-response relationship between temperature and health to construct an advanced heat exposure assessment framework predicated on a population dynamic model. We analyzed urban heat island characteristics, population dynamics, and heat exposure during heat wave conditions in Beijing, a major city in China. Our findings highlight significant intra-day population movement between urban and suburban areas during heat wave conditions, with spatial population flow patterns showing clear scale-dependent characteristics. These population flow dynamics intensify heat exposure levels, and the disparity between dynamic population-weighted temperature and average temperature is most pronounced at night. Our research provides a more comprehensive understanding of real urban population heat exposure levels and can furnish city administrators with more scientifically rigorous evidence.

Hybrid unorganized machines to estimate the number of hospital admissions caused by PM[Formula: see text] concentration

Air pollution levels exceeding the recommended limit can be the main cause of illnesses that affect human health, mainly diseases of the respiratory system. Consequently, this high exposure can impact public health management, given the increase in hospital admissions. One of the most influential air pollution parameters related to respiratory diseases is particulate matter (PM) concentrations. Thus, this paper proposes to estimate hospital admissions due to respiratory diseases caused by PM concentration with an aerodynamic diameter less than 10 [Formula: see text]m (PM[Formula: see text]), using artificial neural networks. Three hybrid neural network models are developed by combining two architectures denoted unorganized machines: extreme learning machines and echo state networks. These models also comprise extension strategies that seek to improve the generalization capability and the variation in the nonlinear outputs. Case studies explore three cities' datasets from São Paulo state, Brazil: Cubatão, Campinas, and São Paulo, to assess the quality of the hospital admissions estimations obtained by applying the proposed models. Results demonstrate that the hybrid models outperform the previously developed standard approaches in several scenarios. An overall analysis shows that the hybrid models can be a suitable strategy considering the instance particularities, especially in large datasets.

Estimation of health risk and economic loss attributable to PM2.5 and O3 pollution in Jilin Province, China

Ambient pollutants, particularly fine particulate matter (PM2.5) and ozone (O3), pose significant risks to both public health and economic development. In recent years, PM2.5 concentration in China has decreased significantly, whereas that of O3 has increased rapidly, leading to considerable health risks. In this study, a generalized additive model was employed to establish the relationship of PM2.5 and O3 exposure with non-accidental mortality across 17 districts and counties in Jilin Province, China, over 2015-2016. The health burden and economic losses attributable to PM2.5 and O3 were assessed using high-resolution satellite and population data. According to the results, per 10 µg/m3 increase in PM2.5 and O3 concentrations related to an overall relative risk (95% confidence interval) of 1.004 (1.001-1.007) and 1.009 (1.005-1.012), respectively. In general, the spatial distribution of mortality and economic losses was uneven. Throughout the study period, a total of 23,051.274 mortalities and 27,825.015 million Chinese Yuan (CNY) in economic losses were attributed to O3 exposure, which considerably surpassing the 5,450.716 mortalities and 6,553,780 million CNY in economic losses attributed to PM2.5 exposure. The O3-related health risks and economic losses increased by 3.75% and 9.3% from 2015 to 2016, while those linked to PM2.5 decreased by 23.33% and 18.7%. Sensitivity analysis results indicated that changes in pollutant concentrations were the major factors affecting mortality rather than baseline mortality and population.

Effect of gaseous pollutant and greenness exposure on mortality during treatment of newly treated tuberculosis patients: a provincial population-based cohort study

BACKGROUND

Previous studies addressing the impact of environmental factors on TB prognosis are scarce, with only some studies examining the effect of particulate pollutants on TB mortality. Moreover, few studies have evaluated the effects of multiple gaseous pollutants and greenness exposures on newly treated TB patients on a large population scale.

METHODS

Through the Centers for Disease Control and Prevention, data were collected from January 1, 2015 to December 31, 2020 for newly treated TB patients in Anhui Province, China. Data on gaseous pollutants sulfur dioxide, nitrogen dioxide, carbon monoxide, and ozone were collected through the National Earth System Science Data Center of China. Normalized vegetation index data were obtained through NASA. The Cox proportional risk model was also applied to calculate the hazard ratios of SO2, NO2, CO, O3, and NDVI with 95% confidence intervals for mortality among newly treated TB patients.

RESULTS

Multifactorial Cox regression analysis showed that for every 0.10 μg/m3 increase in SO2, the risk of death among newly treated TB patients increased by 13.2% (HR = 1.132, 95% CI: 1.045-1.1.225), for every 10 μg/m3 increase in NO2, the risk of death among newly treated TB patients increased by 11.4%, and for each 0.1 mg/m3 increase in CO, the risk of death among newly treated TB patients increased by 5.8%. For each 0.1 increase in NDVI 250m-buffer and 500m-buffer, the risk of death among newly treated TB patients decreased by 8.5% and 6.4%, respectively. The effect of gaseous pollutants on mortality decreased progressively with elevated greenness exposure when greenness exposure was grouped from low to high.

CONCLUSION

Gaseous pollutants are a risk factor during the treatment of newly treated TB patients and greenness exposure is a protective factor. Higher greenness exposure reduces the risk of death due to exposure to gaseous pollutants.

Cardiovascular, respiratory and all-cause (natural) health endpoint estimation using a spatial approach in Malaysia

In 2016, the World Health Organization (WHO) estimated that approximately 4.2 million premature deaths worldwide were attributable to exposure to particulate matter 2.5 μm (PM_2.5). This study assessed the environmental burden of disease attributable to PM_2.5 at the national level in Malaysia. We estimated the population-weighted exposure level (PWEL) of PM10 concentrations in Malaysia for 2000, 2008, and 2013 using aerosol optical density (AOD) data from publicly available remote sensing satellite data (MODIS Terra). The PWEL was then converted to PM_2.5 using Malaysia's WHO ambient air conversion factor. We used AirQ+ 2.0 software to calculate all-cause (natural), ischemic heart disease (IHD), stroke, chronic obstructive pulmonary disease (COPD), lung cancer (LC), and acute lower respiratory infection (ALRI) excess deaths from the National Burden of Disease data for 2000, 2008 and 2013. The average PWELs for annual PM_2.5 for 2000, 2008, and 2013 were 22 μg m-3, 18 μg m-3 and 24 μg m-3, respectively. Using the WHO 2005 Air Quality Guideline cut-off point of PM_2.5 of 10 μg m-3, the estimated excess deaths for 2000, 2008, and 2013 from all-cause (natural) mortality were between 5893 and 9781 (95 % CI: 3347-12,791), COPD was between 164 and 957 (95 % CI: 95-1411), lung cancer was between 109 and 307 (95 % CI: 63-437), IHD was between 3 and 163 deaths, according to age groups (95 % CI: 2-394) and stroke was between 6 and 155 deaths, according to age groups (95 % CI: 3-261). An increase in estimated health endpoints was associated with increased estimated PWEL PM_2.5 for 2013 compared to 2000 and 2008. Adhering the ambient PM_2.5 level to the Malaysian Air Quality Standard IT-2 would reduce the national health endpoints mortality.

Health Damage of Air Pollution, Governance Uncertainty and Economic Growth

The evaluation of environmental and health governance processes is an important part of the innovation and perfection of modern governance systems. Based on the macropanel samples, this paper analyzes the impact of the health damage caused by air pollution (APHD) on economic growth and the related mechanisms accordingly using the moderate model and the threshold model. The results can be concluded as follows: (1) After locking in the health damage perspective, the APHD has a negative impact on economic growth. When other conditions are met, economic growth will significantly drop by 1.233 percent for each unit increase in the APHD index. (2) There is a moderate effect of governance uncertainty in APHD on economic growth with different characteristics. The combination of governance uncertainty and APHD can significantly inhibit economic growth, and this moderating effect has different impacts due to heterogeneous conditions. Spatially, this inhibitory effect is significantly obvious in the eastern, central, and western regions, while the negative effect is significant in areas north of the Huai River with medium and low self-defense ability. Additionally, compared with the delegating of governance power at the municipal level, when the governance power is delegated at the county level, the interaction between the governance uncertainty constructed by income fiscal decentralization and APHD has a less negative economic effect. (3) There is a threshold effect under the conditions of a low level of decentralization of prevention and control, a high level of investment in governance, and a low level of APHD. However, under the condition of a certain APHD level, when the decentralization level of pollution control is higher than 7.916 and the input level of pollution control in GDP is lower than 1.77%, the negative moderating effect can be effectively reduced.

The influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza activity in China

Previous research has extensively studied the seasonalities of human influenza infections and the effect of specific climatic factors in different regions. However, there is limited understanding of the influences of monsoons. This study applied generalized additive model with monthly surveillance data from mainland China to explore the influences of the East Asian Monsoon on the spatio-temporal pattern of seasonal influenza in China. The results suggested two influenza active periods in northern China and three active periods in southern China. The study found that the northerly advancement of East Asian Summer Monsoon (EASM) influences the summer influenza spatio-temporal patterns in both southern and northern China. At the interannual scale, the north-south converse effect of EASM on influenza activity is mainly due to the converse effect of EASM on humidity and precipitation. Within the annual scale, influenza activity in southern China gradually reaches its maximum during the summer exacerbated by the northerly advancement of EASM. Furthermore, the winter epidemic in China is related to the low temperature and humidity influenced by the East Asian Winter Monsoon (EAWM). Moreover, the active period in transition season is related partially to the large rapid temperature change influenced by the transition of EAWM and EASM. Despite the delayed onset and instability, the climatic condition influenced by the East Asian Monsoon is one of the potential key drivers of influenza activity.

Scenarios of demographic distributional aspects of health co-benefits from decarbonising urban transport

BACKGROUND

There is limited knowledge on the distribution of the health co-benefits of reduced air pollutants and carbon emissions in the transport sector across populations.

METHODS

This Article describes a health impact assessment used to estimate the health co-benefits of alternative land passenger transport scenarios for the city of Beijing, China, testing the effect of five transport-based scenarios from 2020 to 2050 on health outcomes. New potential scenarios range from implementing a green transport infrastructure, to scenarios primarily based on the electrification of vehicle fleets and a deep decarbonisation scenario with near zero carbon emissions by 2050. The health co-benefits are disaggregated by age and sex and estimated in monetary terms.

FINDINGS

The results show that all the alternative mitigation scenarios result in reduced PM_2·5 and CO₂ emissions compared to a business-as-usual scenario during 2020-50. The near zero scenario achieves the largest health co-benefits and economic benefits annually relative to the sole mitigation strategy, preventing 300 (95% CI 229-450) deaths, with health co-benefits and CO₂ cost-saving an equivalent of 0·01% (0·00-0·03%) of Beijing's Gross domestic product in 2015 by 2050. Given Beijing's ageing population and higher mortality rate, individuals aged 50 years and older experience the greatest benefit from the mitigation scenarios. Regarding sex, the greatest health benefits occur in men.

INTERPRETATION

This assessment provides estimates of the demographic distribution of benefits from the effects of combinations of green transport and decarbonising vehicles in transport futures. The results show that there are substantial positive health outcomes from decarbonising transport in Beijing. Policies aimed at encouraging active travel and use of public transport, increasing the safety of active travel, improving public transport infrastructure, and decarbonising vehicles lead to differential benefits. In addition, disaggregation by age and sex shows that the health impacts related to transport pollution disproportionately influence different age cohorts and genders.

FUNDING

National Natural Science Foundation of China and FRIEND Project (through the National Research Foundation of Korea, funded by the Ministry of Science and ICT).

Air pollution epidemiology: A simplified Generalized Linear Model approach optimized by bio-inspired metaheuristics

Studies in air pollution epidemiology are of paramount importance in diagnosing and improve life quality. To explore new methods or modify existing ones is critical to obtain better results. Most air pollution epidemiology studies use the Generalized Linear Model, especially the default version of R, Splus, SAS, and Stata softwares, which use maximum likelihood estimators in parameter optimization. Also, a smooth time function (usually spline) is generally used as a pre-processing step to consider seasonal and long-term tendencies. This investigation introduces a new approach to GLM, proposing the estimation of the free coefficients through bio-inspired metaheuristics - Particle Swarm Optimization (PSO), Genetic Algorithms, and Differential Evolution, as well as the replacement of the spline function by a simple normalization procedure. The considered case studies comprise three important cities of São Paulo state, Brazil with distinct characteristics: São Paulo, Campinas, and Cubatão. We considered the impact of particles with an aerodynamic diameter less than 10 μm (PM₁₀), ambient temperature, and relative humidity in the number of hospital admissions for respiratory diseases (ICD-10, J00 to J99). The results showed that the new approach (especially PSO) brings performance gains compared to the default version of statistical software like R.

Effects of Population Weighting on PM10 Concentration Estimation

Particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) pollution poses a considerable threat to human health, and the first step in quantifying health impacts of human exposure to PM₁₀ pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provide a more refined exposure assessment as it includes the spatiotemporal distribution of the population into the pollution concentration estimation. This study assessed the population weighting effects on the estimated PM₁₀ concentrations in Malaysia for years 2000, 2008, and 2013. Estimated PM₁₀ annual mean concentrations with a spatial resolution of 5 kilometres retrieved from satellite data and population count obtained from the Gridded Population of the World version 4 (GPWv4) from the Centre for International Earth Science Information Network (CIESIN) were overlaid to generate the PWEL of PM₁₀ for each state. The calculated PWEL of PM₁₀ concentrations were then classified based on the World Health Organization (WHO) and the national Air Quality Guidelines (AQG) and interim targets (IT) for comparison. Results revealed that the annual mean PM₁₀ concentrations in Malaysia ranged from 31 to 73 µg/m³ but became generally lower, ranging from 20 to 72 µg/m³ after population weighting, suggesting that the PM₁₀ population exposure in Malaysia might have been overestimated. PWEL of PM₁₀ distribution showed that the majority of the population lived in areas that complied with the national AQG, but were vulnerable to exposure level 3 according to the WHO AQG and IT, indicating that the population was nevertheless potentially exposed to significant health effects from long-term exposure to PM₁₀ pollution.

Assessment of German population exposure levels to PM10 based on multiple spatial-temporal data

Particulate matter is the key to increasing urban air pollution, and research into pollution exposure assessment is an important part of environmental health. In order to classify PM₁₀ air pollution and to investigate the population exposure to the distribution of PM₁₀, daily and monthly PM₁₀ concentrations of 379 air pollution monitoring stations were obtained for a period from 01/01/2017 to 31/12/2017. Firstly, PM₁₀ concentrations were classified using the head/tail break clustering algorithm to identify locations with elevated PM₁₀ levels. Subsequently, population exposure levels were calculated using population-weighted PM₁₀ concentrations. Finally, the power-law distribution was used to test the distribution of PM₁₀ polluted areas. Our results indicate that the head/tail break algorithm, with an appropriate segmentation threshold, can effectively identify areas with high PM₁₀ concentrations. The distribution of the population according to exposure level shows that the majority of people is living in polluted areas. The distribution of heavily PM₁₀ polluted areas in Germany follows the power-law distribution well, but their boundaries differ from the boundaries of administrative cities; some even cross several administrative cities. These classification results can guide policymakers in dividing the country into several areas for pollution control.

A systematic review of financial implications of air pollution on health in Asia

Economic losses due to health-related implications of air pollution were huge and incurred significant burdens towards healthcare providers. The objective of this study is to systematically review published literature on the financial implications of air pollution on health in Asia. Four databases: PubMed, Scopus, NHS Economic Evaluation Database (NHS EED), and Web of Science (WoS) were used to identify all the relevant articles. It was limited to all articles that had been published in the respected databases from January 2007 until March 2017. Twenty-four articles were included in this review. Five of the 24 studies (20.8%) reported financial implications of air pollution-related disease through value of statistical life (VOSL) which ranged from USD180 million to USD2.2 billion, six (25%) studies used cost of illness (COI) to evaluate air pollution-related morbidity and found that the cost ranged from USD5.4 million to USD9.1 billion. Another six studies (25%) used a combination of VOSL and COI for both mortality and morbidity valuation and found that the financial implications ranging from USD253 million to USD2.9 billion. Thirteen (54.2%) studies reported healthcare cost associated with both hospital admission and outpatient visit, five (20.1%) on hospital admission only, and one (4.2%) on outpatient visit only. Economic impacts of air pollution can be huge with significant deterioration of health among the Asians.

Impact of air pollution on cause-specific mortality in Korea: Results from Bayesian Model Averaging and Principle Component Regression approaches

Health effects related to air pollution are a major global concern. Related studies based on reliable exposure assessment methods would potentially enable policy makers to propose appropriate environmental management policies. In this study, integrated Bayesian Model Averaging (BMA) and Principle Component Regression (PCR) were adopted to assess the severity of air pollution impacts on mortality related to circulatory, respiratory and skin diseases in 25 districts of Seoul, South Korea for the years 2005-2015. These methods were consistent in determining the best regression models and most important pollutants related to mortality in those highly susceptible to poor air quality. Specifically, the results demonstrated that pneumonia was highly associated with air pollution, with a large determination coefficient (BMA: 0.46, PCR: 0.51) and high model's posterior probability (0.47). The most reliable prediction model for pneumonia was indicated by the lowest Bayesian Information Criterion. Among the pollutants, particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) was associated with serious health risks on evaluation, with the highest posterior inclusion probabilities (range, 80.20 to 100.00%) and significantly positive correlation coefficients (range, 0.14 to 0.34, p < 0.05). In addition, excessive PM₁₀ concentration (approximately 2.54 times the threshold) and a continuous increase in mortality due to respiratory diseases (approximately 1.50-fold in 10 years) were also exhibited. Overall, the results of this study suggest that currently, socio-environmental policies and international collaboration to mitigate health effects of air pollution is necessary in Seoul, Korea. Moreover, consideration of uncertainty of the regression model, which was verified in this research, will facilitate further application of this approach and enable optimal prediction of interactions between human and environmental factors.

Contingent valuation of health and mood impacts of PM2.5 in Beijing, China

Air pollution from PM₂.₅ affects many cities worldwide, causing both health impacts and mood depression. One of the obstacles to implementing environmental regulations for PM₂.₅ reduction is that there are limited studies of PM₂.₅ welfare loss and few investigations of mood depression caused by PM₂.₅. This article describes a survey study conducted in Beijing, China to estimate the welfare loss due to PM₂.₅. In total, 1709 participants completed either a face-to-face or online survey. A contingent valuation method was applied to elicit people's willingness to pay to avoid PM₂.₅ pollution and willingness to accept a compensation for such pollution. The payment/compensation was evaluated for two outcome variables: perceived health impacts and mood depression caused by PM₂.₅ pollution. This is one of few papers that explicitly studies the effects of PM₂.₅ on subjective well-being, and to the authors' knowledge, the first to estimate welfare loss from PM₂.₅ using a random forest model. Compared to the standard Turnbull, probit, and two-part models, the random forest model gave the best fit to the data, suggesting that this may be a useful tool for future studies too. The welfare loss due to health impacts and mood depression is CNY 1388.4/person/year and CNY 897.7/person/year respectively, indicating that the public attaches great importance to mood, feelings and happiness. The study provides scientific support to the development of economic policy instruments for PM₂.₅ control in China.

Spatiotemporal characteristics of PM2.5 and PM10 at urban and corresponding background sites in 23 cities in China

Air pollution episodes in China are frequent and a more comprehensive understanding of pollution sources and impacts is needed to design appropriate strategies and set emission reduction targets. This study analyzes PM2.5 and PM10 concentrations measured in 23 cities at 178 urban sites and at 23 corresponding "urban contrast" sites in China with the goals of understanding spatial and temporal trends and quantifying the regional component of PM pollution. The contrast sites, located an average of 29km from cities in the upwind direction, are intended to represent "background" levels. Using daily measurements from April 2013 to March 2014, we assess compliance with air quality standards, PM2.5/PM10 ratios and urban "increments," defined as the increase in PM levels in the city compared to the contrast site. Spatial and temporal patterns at daily, monthly and annual levels are shown using distributions, correlations, spatial autocorrelation, and factor analyses. At the contrast sites, PM2.5 and PM10 concentrations averaged 56±26 and 91±44μgm-3, respectively, and China's daily and annual average air quality standards were frequently exceeded. PM2.5 and PM10 concentrations in most cities exceeded levels at the corresponding contrast sites, but by an average of only 14±14 and 26±27μgm-3, respectively. Seasonal changes in PM2.5 and PM10 concentrations and urban increments were striking, e.g., levels increased 2 to 3-fold in winter at several sites. The significance of exurban and regional sources of PM2.5 is demonstrated by the small urban increments, the strong correlations across broad regions, and the correlation between daily levels at city and contrast sites. These sources will require control to achieve air quality goals, in particular, the PM10 and PM2.5 targets announced by the Chinese government in 2013.

Efficiency of Emission Control Measures on Particulate Matter-Related Health Impacts and Economic Cost during the 2014 Asia-Pacific Economic Cooperation Meeting in Beijing

Background: The Asia-Pacific Economic Cooperation (APEC) meeting was held from 5 November to 11 November 2014 in Beijing, and comprehensive emission control measures were implemented. The efficiency of these measures on particulate matter-related health impacts and economic cost need to be evaluated. Methods: The influences of emission control measures during APEC on particulate matter were evaluated, and health economic effects were assessed. Results: Average concentrations of PM_2.5 and PM₁₀ during APEC were reduced by 57.0%, and 50.6% respectively, compared with pre-APEC period. However, the concentrations of particulate matter rebounded after APEC. Compared with the pre-APEC and post-APEC periods, the estimated number of deaths caused by non-accidental, cardiovascular and respiratory diseases that could be attributed to PM_2.5 and PM₁₀ during the APEC were the lowest. The economic cost associated with mortality caused by PM_2.5 and PM₁₀ during the APEC were reduced by (61.3% and 66.6%) and (50.3% and 60.8%) respectively, compared with pre-APEC and post-APEC. Conclusions: The emission control measures were effective in improving short term air quality and reducing health risks and medical expenses during 2014 APEC, but more efforts is needed for long term and continuous air quality improvement and health protection.

Impact of air pollution on the burden of chronic respiratory diseases in China: time for urgent action

In China, where air pollution has become a major threat to public health, public awareness of the detrimental effects of air pollution on respiratory health is increasing-particularly in relation to haze days. Air pollutant emission levels in China remain substantially higher than are those in developed countries. Moreover, industry, traffic, and household biomass combustion have become major sources of air pollutant emissions, with substantial spatial and temporal variations. In this Review, we focus on the major constituents of air pollutants and their impacts on chronic respiratory diseases. We highlight targets for interventions and recommendations for pollution reduction through industrial upgrading, vehicle and fuel renovation, improvements in public transportation, lowering of personal exposure, mitigation of the direct effects of air pollution through healthy city development, intervention at population-based level (systematic health education, intensive and individualised intervention, pre-emptive measures, and rehabilitation), and improvement in air quality. The implementation of a national environmental protection policy has become urgent.

Spatiotemporal analysis for the effect of ambient particulate matter on cause-specific respiratory mortality in Beijing, China

This study explored the association between particulate matter with an aerodynamic diameter of less than 10 μm (PM10) and the cause-specific respiratory mortality. We used the ordinary kriging method to estimate the spatial characteristics of ambient PM10 at 1-km × 1-km resolution across Beijing during 2008-2009 and subsequently fit the exposure-response relationship between the estimated PM10 and the mortality due to total respiratory disease, chronic lower respiratory disease, chronic obstructive pulmonary disease (COPD), and pneumonia at the street or township area levels using the generalized additive mixed model (GAMM). We also examined the effects of age, gender, and season in the stratified analysis. The effects of ambient PM10 on the cause-specific respiratory mortality were the strongest at lag0-5 except for pneumonia, and an inter-quantile range increase in PM10 was associated with an 8.04 % (95 % CI 4.00, 12.63) increase in mortality for total respiratory disease, a 6.63 % (95 % CI 1.65, 11.86) increase for chronic lower respiratory disease, and a 5.68 % (95 % CI 0.54, 11.09) increase for COPD, respectively. Higher risks due to the PM10 exposure were observed for females and elderly individuals. Seasonal stratification analysis showed that the effects of PM10 on mortality due to pneumonia were stronger during spring and autumn. While for COPD, the effect of PM10 in winter was statistically significant (15.54 %, 95 % CI 5.64, 26.35) and the greatest among the seasons. The GAMM model evaluated stronger associations between concentration of PM10. There were significant associations between PM10 and mortality due to respiratory disease at the street or township area levels. The GAMM model using high-resolution PM10 could better capture the association between PM10 and respiratory mortality. Gender, age, and season also acted as effect modifiers for the relationship between PM10 and respiratory mortality.

Monetary Valuation of PM10-Related Health Risks in Beijing China: The Necessity for PM10 Pollution Indemnity

Severe health risks caused by PM₁₀ (particulate matter with an aerodynamic diameter ≤10 μm) pollution have induced inevitable economic losses and have rendered pressure on the sustainable development of society as a whole. In China, with the “Polluters Pay Principle”, polluters should pay for the pollution they have caused, but how much they should pay remains an intractable problem for policy makers. This paper integrated an epidemiological exposure-response model with economics methods, including the Amended Human Capital (AHC) approach and the Cost of Illness (COI) method, to value the economic loss of PM₁₀-related health risks in 16 districts and also 4 functional zones in Beijing from 2008 to 2012. The results show that from 2008 to 2012 the estimated annual deaths caused by PM₁₀ in Beijing are around 56,000, 58,000, 63,000, 61,000 and 59,000, respectively, while the economic losses related to health damage increased from around 23 to 31 billion dollars that PM₁₀ polluters should pay for pollution victims between 2008 and 2012. It is illustrated that not only PM₁₀ concentration but also many other social economic factors influence PM₁₀-related health economic losses, which makes health economic losses show a time lag discrepancy compared with the decline of PM₁₀ concentration. In conclusion, health economic loss evaluation is imperative in the pollution indemnity system establishment and should be considered for the urban planning and policy making to control the burgeoning PM₁₀ health economic loss.

Assessment of Population Exposure to Coarse and Fine Particulate Matter in the Urban Areas of Chennai, India

Research outcomes from the epidemiological studies have found that the course (PM₁₀) and the fine particulate matter (PM_2.5) are mainly responsible for various respiratory health effects for humans. The population-weighted exposure assessment is used as a vital decision-making tool to analyze the vulnerable areas where the population is exposed to critical concentrations of pollutants. Systemic sampling was carried out at strategic locations of Chennai to estimate the various concentration levels of particulate pollution during November 2013–January 2014. The concentration of the pollutants was classified based on the World Health Organization interim target (IT) guidelines. Using geospatial information systems the pollution and the high-resolution population data were interpolated to study the extent of the pollutants at the urban scale. The results show that approximately 28% of the population resides in vulnerable locations where the coarse particulate matter exceeds the prescribed standards. Alarmingly, the results of the analysis of fine particulates show that about 94% of the inhabitants live in critical areas where the concentration of the fine particulates exceeds the IT guidelines. Results based on human exposure analysis show the vulnerability is more towards the zones which are surrounded by prominent sources of pollution.

Air Quality in Lanzhou, a Major Industrial City in China: Characteristics of Air Pollution and Review of Existing Evidence from Air Pollution and Health Studies

Air pollution contributes substantially to global health burdens; however, less is known about pollution patterns in China and whether they differ from those elsewhere. We evaluated temporal and spatial heterogeneity of air pollution in Lanzhou, an urban Chinese city (April 2009-December 2012), and conducted a systematic review of literature on air pollution and health in Lanzhou. Average levels were 141.5, 42.3, and 47.2 µg/m³ for particulate matter with an aerodynamic diameter ≤10 µm (PM₁₀), NO₂, and SO₂, respectively. Findings suggest some seasonality, particularly for SO₂, with higher concentrations during colder months relative to warmer months, although a longer time frame of data is needed to evaluate seasonality fully. Correlation coefficients generally declined with distance between monitors, while coefficients of divergence increased with distance. However, these trends were not statistically significant. PM₁₀ levels exceeded Chinese and other health-based standards and guidelines. The review identified 13 studies on outdoor air pollution and health. Although limited, the studies indicate that air pollution is associated with increased risk of health outcomes in Lanzhou. These studies and the high air pollution levels suggest potentially serious health consequences. Findings can provide guidance to future epidemiological studies, monitor placement programs, and air quality policies.

Particulate matter pollution and population exposure assessment over mainland China in 2010 with remote sensing

The public is increasingly concerned about particulate matter pollution caused by respirable suspended particles (PM₁₀) and fine particles (PM_2.5). In this paper, PM₁₀ and PM_2.5 concentration are estimated with remote sensing and individual air quality indexes of PM₁₀ and PM_2.5 (IPM₁₀ and IPM_2.5) over mainland China in 2010 are calculated. We find that China suffered more serious PM_2.5 than PM₁₀ pollution in 2010, and they presented a spatial differentiation. Consequently, a particulate-based air quality index (PAQI) based on a weighting method is proposed to provide a more objective assessment of the particulate pollution. The study demonstrates that, in 2010, most of mainland China faced a lightly polluted situation in PAQI case; there were three areas obviously under moderate pollution (Hubei, Sichuan-Chongqing border region and Ningxia-Inner Mongolia border region). Simultaneously, two indicators are calculated with the combination of population density gridded data to reveal Chinese population exposure to PM_2.5. Comparing per capita PM_2.5 concentration with population-weighted PM_2.5 concentration, the former shows that the high-level regions are distributed in Guangdong, Shanghai, and Tianjin, while the latter are in Hebei, Chongqing, and Shandong. By comparison, the results demonstrate that population-weighted PM_2.5 concentration is more in line with the actual situation.