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An evaluation of the health benefits achieved at the time of an air quality intervention in three Israeli cities.

ABSTRACT: BACKGROUND:The statistical association between increased exposure to air pollution and increased risk of morbidity and mortality is well established. However, documentation of the health benefits of lowering air pollution levels, which would support the biological plausibility of those past statistical associations, are not as well developed. A better understanding of the aftereffects of interventions to reduce air pollution is needed in order to: 1) better document the benefits of lowered air pollution; and, 2) identify the types of reductions that most effectively provide health benefits. METHODS:This study analyzes daily health and pollution data from three major cities in Israel that have undergone pollution control interventions to reduce sulfur emissions from combustion sources. In this work, the hypothesis tested is that transitions to cleaner fuels are accompanied by a decreased risk of daily cardiovascular and respiratory mortalities. Interrupted time series regression models are applied in order to test whether the cleaner air interventions are associated with a statistically significant reduction in mortality. RESULTS:In the multi-city meta-analysis we found statistically significant reductions of 13.3% [CI -21.9%, -3.8%] in cardiovascular mortality, and a borderline significant (p=0.06) reduction of 19.0% [CI -35.1%, 1.1%] in total mortality. CONCLUSIONS:Overall, new experiential evidence is provided consistent with human health benefits being associated with interventions to reduce air pollution. The methods employed also provide an approach that may be applied elsewhere in the future to better document and optimize the health benefits of clean air interventions.

SUBMITTER: Yinon L

PROVIDER: S-EPMC5771478 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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An evaluation of the health benefits achieved at the time of an air quality intervention in three Israeli cities.

Yinon Lital L Thurston George G

Environment international 20170223

<h4>Background</h4>The statistical association between increased exposure to air pollution and increased risk of morbidity and mortality is well established. However, documentation of the health benefits of lowering air pollution levels, which would support the biological plausibility of those past statistical associations, are not as well developed. A better understanding of the aftereffects of interventions to reduce air pollution is needed in order to: 1) better document the benefits of lower ...[more]

PMID: 28237065

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Project description:With the ongoing challenge of air pollution posing serious health and environmental threats, particularly in rapidly industrializing regions, accurate forecasting and effective pollutant identification are crucial for enhancing public health and ecological stability. This study aimed to optimize air quality management through the prediction of the Air Quality Index (AQI) and identification of air pollutants. Our study spans nine representative cities (Hohhot, Yinchuan, Lanzhou, Beijing, Taiyuan, Xi'an, Shanghai, Nanjing, Wuhan) in China, with data collected from January 1, 2015, to November 30, 2021. We proposed a new model for daily AQI prediction, termed VMD-CSA-CNN-LSTM, which employed advanced machine learning techniques, including convolutional neural networks (CNN) and long short-term memory (LSTM) networks, and leveraged the chameleon swarm algorithm (CSA) for hyperparameter optimization, integrated through a variational mode decomposition approach. The model was developed using data from Lanzhou, with a split ratio of 8:1:1 into training, validation, and test sets, achieving an RMSE of 2.25, MAPE of 0.02, adjusted R-squared of 98.91%, and training efficiency of 5.31%. The model was further externally validated in the other eight cities, yielding comparable results, with an adjusted R-squared above 96%, MAPE below 0.1, and RMSE below 7.5. Additionally, we employed a random forest algorithm to identify the primary pollutants contributing to AQI levels. Our results indicated that PM2.5 was the most significant pollutant in Beijing, Taiyuan, and Xi'an, while PM10 was dominant in Hohhot, Yinchuan, and Lanzhou. In Shanghai, Nanjing, and Wuhan, both PM2.5 and PM10 were critical, with ozone also identified as a major air pollutant. This study not only advances the predictive accuracy of AQI models but also aids policymakers by providing a reliable tool for air quality management and strategic planning aimed at pollution reduction. The integration of these advanced computational techniques into environmental monitoring practices offers a promising avenue for enhancing air quality and mitigating pollution-related risks.

Project description:In response to the rapid spread of coronavirus disease-2019 (COVID-19) within and across countries and the need to protect public health, governments worldwide introduced unprecedented measures such as restricted road and air travel and reduced human mobility in 2020. The curtailment of personal travel and economic activity provided a unique opportunity for researchers to assess the interplay between anthropogenic emissions of primary air pollutants, their physical transport, chemical transformation, ultimate fate and potential health impacts. In general, reductions in the atmospheric levels of outdoor air pollutants such as particulate matter (PM), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and volatile organic compounds (VOCs) were observed in many countries during the lockdowns. However, the levels of ozone (O3), a secondary air pollutant linked to asthma and respiratory ailments, and secondary PM were frequently reported to remain unchanged or even increase. An increase in O3 can enhance the formation of secondary PM2.5, especially secondary organic aerosols, through the atmospheric oxidation of VOCs. Given that the gaseous precursors of O3 (VOCs and NOx) are also involved in the formation of secondary PM2.5, an integrated control strategy should focus on reducing the emission of the common precursors for the co-mitigation of PM2.5 and O3 with an emphasis on their complex photochemical interactions. Compared to outdoor air quality, comprehensive investigations of indoor air quality (IAQ) are relatively sparse. People spend more than 80% of their time indoors with exposure to air pollutants of both outdoor and indoor origins. Consequently, an integrated assessment of exposure to air pollutants in both outdoor and indoor microenvironments is needed for effective urban air quality management and for mitigation of health risk. To provide further insights into air quality, we do a critical review of scientific articles, published from January 2020 to December 2020 across the globe. Finally, we discuss policy implications of our review in the context of global air quality improvement.

Project description:Objectives To estimate the short term effect of particulate air pollution (particle diameter <10 ?m, or PM10) on mortality and explore the heterogeneity of particulate air pollution effects in major cities in China.Design Generalised linear models with different lag structures using time series data.Setting 38 of the largest cities in 27 provinces of China (combined population >200 million).Participants 350?638 deaths (200?912 in males, 149?726 in females) recorded in 38 city districts by the Disease Surveillance Point System of the Chinese Center for Disease Control and Prevention from 1 January 2010 to 29 June 2013.Main outcome measure Daily numbers of deaths from all causes, cardiorespiratory diseases, and non-cardiorespiratory diseases and among different demographic groups were used to estimate the associations between particulate air pollution and mortality.Results A 10 µg/m3 change in concurrent day PM10 concentrations was associated with a 0.44% (95% confidence interval 0.30% to 0.58%) increase in daily number of deaths. Previous day and two day lagged PM10 levels decreased in magnitude by one third and two thirds but remained statistically significantly associated with increased mortality. The estimate for the effect of PM10 on deaths from cardiorespiratory diseases was 0.62% (0.43% to 0.81%) per 10 µg/m3 compared with 0.26% (0.09% to 0.42%) for other cause mortality. Exposure to PM10 had a greater impact on females than on males. Adults aged 60 and over were more vulnerable to particulate air pollution at high levels than those aged less than 60. The PM10 effect varied across different cities and marginally decreased in cities with higher PM10 concentrations.Conclusion Particulate air pollution has a greater impact on deaths from cardiorespiratory diseases than it does on other cause mortality. People aged 60 or more have a higher risk of death from particulate air pollution than people aged less than 60. The estimates of the effect varied across cities and covered a wide range of domain.

Dataset Information

An evaluation of the health benefits achieved at the time of an air quality intervention in three Israeli cities.

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An evaluation of the health benefits achieved at the time of an air quality intervention in three Israeli cities.

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