Specific differences and responses to reductions for premature mortality attributable to ambient PM2.5 in China

Two Decades of Air Pollution Health Risk Assessment: Insights From the Use of WHO's AirQ and AirQ+ Tools

Objectives

We evaluated studies that used the World Health Organization's (WHO) AirQ and AirQ+ tools for air pollution (AP) health risk assessment (HRA) and provided best practice suggestions for future assessments.

Methods

We performed a comprehensive review of studies using WHO's AirQ and AirQ+ tools, searching several databases for relevant articles, reports, and theses from inception to Dec 31, 2022.

Results

We identified 286 studies that met our criteria. The studies were conducted in 69 countries, with most (57%) in Iran, followed by Italy and India (∼8% each). We found that many studies inadequately report air pollution exposure data, its quality, and validity. The decisions concerning the analysed population size, health outcomes of interest, baseline incidence, concentration-response functions, relative risk values, and counterfactual values are often not justified, sufficiently. Many studies lack an uncertainty assessment.

Conclusion

Our review found a number of common shortcomings in the published assessments. We suggest better practices and urge future studies to focus on the quality of input data, its reporting, and associated uncertainties.

Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors

Exposure scenario and receptor behavior significantly affect PM2.5 exposure quantity of persons and resident groups, which in turn influenced indoor or outdoor air quality & health management. An Internet of Things (IoT) system, EnvironMax+, was developed to accurately and conveniently assess residential dynamic PM2.5 exposure state. A university community "QC", as the application area, was divided into four exposure scenarios and five groups of residents. Low-cost mobile sensors and indoor/outdoor pollution migration (IOP) models jointly estimated multi-scenario real-time PM2.5 concentrations. Questionnaire was used to investigate residents' indoor activity characteristics. Mobile application (app) "Air health management (AHM)" could automatic collect residents' activity trajectory. At last, multi-scenario daily exposure concentrations of each residents-group were obtained. The results showed that residential exposure scenario was the most important one, where residents spend about 60 % of their daily time. Closing window was the most significant behavior affecting indoor contamination. The annual average PM2.5 concentration in the studied scenarios: residential scenario (RS) < public scenario (PS) < outdoor scenario (OS) < catering scenario (CS). Except for CS, the outdoor PM2.5 in other scenarios was higher than indoor by 5-10 μg/m3. The multi-scenario population weighted annual average exposure concentration was 37.1 μg/m3, which was 78 % of the annual average outdoor concentration. The exposure concentration of 5 groups: cooks > outdoor workers > indoor workers > students > the elderly, related to their daily activity time proportion in different exposure scenario.

Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches

Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and interconnection still need to be better understood. Thus, this study aims to detect common differential genes and potential hub genes (HubGs), emphasizing their actions, signaling pathways, regulatory biomarkers for diagnosing RD and candidate drugs for treating RD. In this paper we used integrated bioinformatics approaches (such as, gene ontology (GO) and KEGG pathway enrichment analysis, molecular docking, molecular dynamic simulation and network-based molecular interaction analysis). We discovered 73 common DEGs (CDEGs) and ten HubGs (ATAD2B, PPP1CB, FOXO1, AKT3, BCR, PDE4D, ITGB1, PCBP2, CD44 and SMARCA2). Several significant functions and signaling pathways were strongly related to RD. We recognized six transcription factor (TF) proteins (FOXC1, GATA2, FOXL1, YY1, POU2F2 and HINFP) and five microRNAs (hsa-mir-218-5p, hsa-mir-335-5p, hsa-mir-16-5p, hsa-mir-106b-5p and hsa-mir-15b-5p) as the important transcription and post-transcription regulators of RD. Ten HubGs and six major TF proteins were considered drug-specific receptors. Their binding energy analysis study was carried out with the 63 drug agents detected from network analysis. Finally, the five complexes (the PDE4D-benzo[a]pyrene, SMARCA2-benzo[a]pyrene, HINFP-benzo[a]pyrene, CD44-ketotifen and ATAD2B-ponatinib) were selected for RD based on their strong binding affinity scores and stable performance as the most probable repurposable protein-drug complexes. We believe our findings will give readers, wet-lab scientists, and pharmaceuticals a thorough grasp of the biology behind RD.

Drivers of ozone-related premature mortality in China: Implications for historical and future scenarios

Long-term exposure to ambient ozone (O3) poses a severe public health threat in China. However, the drivers of premature mortality caused by O3 pollution are still poorly constrained, despite being prerequisites for addressing the threat. Here, we demonstrate the contributions of historical and future changes in peak-season O3, population size, age structure, and baseline mortality to China's O3-related mortality using decomposition analysis. From 2013 to 2021, O3-related mortality decreased dramatically from 78.8 (40.8-124.6) to 68.7 (36.0-107.2) thousand, especially in densely populated areas with high pollution. Variations in peak-season O3, population size, age structure, and baseline mortality led to changes in O3-related mortality of +27.3 (14.8-41.3), +2.6 (1.4-4.1), +22.3 (11.5-35.2), and -40.3 (20.9-63.7) thousand, respectively. The influence of peak-season O3 on O3-related mortality shifted from positive during 2013-2019 (+8.4% per year) to negative during 2019-2021 (-8.8% per year), which highly regulated the interannual trend of mortality. From 2021 to 2035, O3-related mortality is expected to increase by 31% in the current context of peak-season O3 levels, primarily caused by increased aging. Even reducing peak-season O3 to the WHO interim target 1 (IT-1) would only reduce O3-related mortality by 3.9%, while a more rigorous standard (IT-2) would prevent 83.7% of mortality. These findings suggest that improving ambient O3 can lead to significant health benefits, but substantial mitigation strategies are merited given the future trend of population aging.

Observation of black carbon in Northern China in winter of 2018-2020 and its implications for black carbon mitigation

Enhanced observations of BC in hotspot regions with a high temporal resolution are critical to refining our BC mitigation strategies, which are co-directed by air-quality and climate goals. In this work, the temporal variation and emission sources of BC in Shijiazhuang, Northern China, during the winter of 2018-2020 were investigated on the basis of multi-wavelength Aethalometer BC observations. The average BC concentrations decreased from 9.13 ± 6.63 μg/m³ in the winter of 2018 to 3.51 ± 2.48 μg/m³ in the winter of 2020. The BC source attributions derived from the Aethalometer model showed that the BC concentrations in Shijiazhuang in the winter of 2018 were mainly contributed by biomass burning (53 %). In contrast, during the winter of 2019 and 2020, fossil fuel combustion (BC_ff) exhibited higher contributions, and higher BC concentrations attributed to greater BC_ff contributions. Potential source contribution function (PSCF) analysis suggested that local emissions in Shijiazhuang and transport from highly industrialized regions like central Shanxi and southern Hebei contributed significantly to BC in Shijiazhuang. Concentration weighted trajectory (CWT) analysis revealed that the BC contributions from source regions decreased successively from the winter of 2018 to the winter of 2020. Our results also implied an air quality/climate co-benefit effect of enforcing multi-scale air-quality improvement regulations. Yet, it is still worth noting that some of the measures in favor of reducing BC emissions contradict the measures for reducing CO₂. The synergies of BC to air quality and climate should be considered and addressed by policymakers with the aim of realizing a sustainable environment.

Exploring the contributions of major emission sources to PM2.5 and attributable health burdens in China

Ambient fine particulate matter (PM_2.5) pollution is the principal environmental risk factor for health burdens in China. Identifying the sectoral contributions of pollutant emissions sources on multiple spatiotemporal scales can help in the formulation of specific strategies. In this study, we used sensitivity analysis to explore the specific contributions of seven major emission sources to ambient PM_2.5 and attributable premature mortality across mainland China. In 2016, about 60% of China's population lived in areas with PM_2.5 concentrations above the Chinese Ambient Air Quality Standard of 35 μg/m³. This percentage was expected to decrease to 35% and 39% if industrial and residential emissions were fully eliminated. In densely populated and highly polluted regions, residential sources contributed about 50% of the PM_2.5 exposure in winter, while industrial sources contributed the most (29-51%) in the remaining seasons. The three major sectoral contributors to PM_2.5-related deaths were industry (247,000 cases, 35%), residential sources (219,000 cases, 31%), and natural sources (87,000, 12%). The relative contributions of the different sectors varied in the different provinces, with industrial sources making the largest contribution in Shanghai (65%), while residential sources predominated in Heilongjiang (63%), and natural sources dominated in Xinjiang (82%). The contributions of the agricultural (11%), transportation (6%), and power (3%) sources were relatively low in China, but emissions mitigation was still effective in densely populated areas. In conclusion, to effectively alleviate health burdens across China, priority should be given to controlling residential emissions in winter and industrial emissions all year round, taking additional measures to curb emissions from other sources in urban hotspots, and formulating air pollution control strategies tailored to local conditions.

Reduced inequality in ambient and household PM2.5 exposure in China

The society has high concerns on the inequality that people are disproportionately exposed to ambient air pollution, but with more time spent indoors, the disparity in the total exposure considering both indoor and outdoor exposure has not been explored; and with the socioeconomical development and efforts in fighting against air pollution, it is unknown how the exposure inequality changed over time. Based on the city-level panel data, this study revealed the Concentration Index (C) in ambient PM_2.5 exposure inequality was positive, indicating the low-income group exposed to lower ambient PM_2.5; however, the total PM_2.5 exposure was negatively correlated with the income, showing a negative C value. The low-income population exposed to high PM_2.5 associated with larger contributions of indoor exposure from the residential emissions. The total PM_2.5 exposure caused 1.13 (0.63-1.73) million premature deaths in 2019, with only 14 % were high-income population. The toughest-ever air pollution countermeasures have reduced ambient PM_2.5 exposures effectively that, however, benefited the rich population more than the others. The transition to clean household energy sources significantly affected on indoor air quality improvements, as well as alleviation of ambient air pollution, resulting in notable reductions of the total PM_2.5 exposure and especially benefiting the low-income groups. The negative C values decreased from 2000 to 2019, indicating a significantly reducing trend in the total PM_2.5 exposure inequality over time.

The impact of technological progress on China's haze pollution-based on decomposition and rebound research

In order to effectively analyze and explore the socio-economic impact of haze pollution, the article constructs a comprehensive two-stage decomposition model to verify that technological progress plays a key role in controlling haze pollution. And for the first time, a macro-level research framework for the rebound effect of haze pollution has been constructed to compare and analyze the heterogeneity of the rebound effect of technological progress in different industries in different regions. The study found that (1) during the period 2000-2017, haze pollution situation deteriorated. Economic effects were the main reasons for haze pollution. Among these effects, technological progress was the main driving force for haze control, followed by the emission intensity during 2000-2011 and the reduction of industrial structure since 2014. (2) The significant drive of emission reduction is in the secondary industry, showing a trend of first increasing and then decreasing. Besides, there was a difference in spatial distribution, which shows an increased trend from east to west. (3) The rebound effect of haze pollution at the macro level in China presented high-level fluctuations, and there were certain spatial distribution differences. However, due to the convergence of technological development stages, regional differences have a gradual convergence trend. In the future, in the process of haze control, it is necessary to increase support for technological innovation, implement energy total control and price reform, promote technological progress, and implement differentiated haze reduction policies to solve problems according to local conditions.

Effects of using different exposure data to estimate changes in premature mortality attributable to PM2.5 and O3 in China

The assessment of premature mortality associated with the dramatic changes in fine particulate matter (PM_2.5) and ozone (O₃) has important scientific significance and provides valuable information for future emission control strategies. Exposure data are particularly vital but may cause great uncertainty in health burden assessments. This study, for the first time, used six methods to generate the concentration data of PM_2.5 and O₃ in China between 2014 and 2018, and then quantified the changes in premature mortality due to PM_2.5 and O₃ using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) model. The results show that PM_2.5-related premature mortality in China decreases by 263 (95% confidence interval (CI95): 142-159) to 308 (CI95: 213-241) thousands from 2014 to 2018 by using different concentration data, while O₃-related premature mortality increases by 67 (CI95: 26-104) to 103 (CI95: 40-163) thousands. The estimated mean changes are up to 40% different for the PM_2.5-related mortality, and up to 30% for the O₃-related mortality if different exposure data are chosen. The most significant difference due to the exposure data is found in the areas with a population density of around 10³ people/km², mostly located in Central China, for both PM_2.5 and O₃. Our results demonstrate that the exposure data source significantly affects mortality estimations and should thus be carefully considered in health burden assessments.

Particulate Matter and Premature Mortality: A Bayesian Meta-Analysis

BACKGROUND

We present a systematic review of studies assessing the association between ambient particulate matter (PM) and premature mortality and the results of a Bayesian hierarchical meta-analysis while accounting for population differences of the included studies.

METHODS

The review protocol was registered in the PROSPERO systematic review registry. Medline, CINAHL and Global Health databases were systematically searched. Bayesian hierarchical meta-analysis was conducted using a non-informative prior to assess whether the regression coefficients differed across observations due to the heterogeneity among studies.

RESULTS

We identified 3248 records for title and abstract review, of which 309 underwent full text screening. Thirty-six studies were included, based on the inclusion criteria. Most of the studies were from China (n = 14), India (n = 6) and the USA (n = 3). PM_2.5 was the most frequently reported pollutant. PM was estimated using modelling techniques (22 studies), satellite-based measures (four studies) and direct measurements (ten studies). Mortality data were sourced from country-specific mortality statistics for 17 studies, Global Burden of Disease data for 16 studies, WHO data for two studies and life tables for one study. Sixteen studies were included in the Bayesian hierarchical meta-analysis. The meta-analysis revealed that the annual estimate of premature mortality attributed to PM_2.5 was 253 per 1,000,000 population (95% CI: 90, 643) and 587 per 1,000,000 population (95% CI: 1, 39,746) for PM₁₀.

CONCLUSION

253 premature deaths per million population are associated with exposure to ambient PM_2.5. We observed an unstable estimate for PM₁₀, most likely due to heterogeneity among the studies. Future research efforts should focus on the effects of ambient PM₁₀ and premature mortality, as well as include populations outside Asia. Key messages: Ambient PM_2.5 is associated with premature mortality. Given that rapid urbanization may increase this burden in the coming decades, our study highlights the urgency of implementing air pollution mitigation strategies to reduce the risk to population and planetary health.

Analysis of Spatial Heterogeneity and the Scale of the Impact of Changes in PM2.5 Concentrations in Major Chinese Cities between 2005 and 2015

Deteriorating air quality is one of the most important environmental factors posing significant health risks to urban dwellers. Therefore, an exploration of the factors influencing air pollution and the formulation of targeted policies to address this issue are critically needed. Although many studies have used semi-parametric geographically weighted regression and geographically weighted regression to study the spatial heterogeneity characteristics of influencing factors of PM2.5 concentration change, due to the fixed bandwidth of these methods and other reasons, those studies still lack the ability to describe and explain cross-scale dynamics. The multi-scale geographically weighted regression (MGWR) method allows different variables to have different bandwidths, which can produce more realistic and useful spatial process models. By applying the MGWR method, this study investigated the spatial heterogeneity and spatial scales of impact of factors influencing PM2.5 concentrations in major Chinese cities during the period 2005–2015. This study showed the following: (1) Factors influencing changes in PM2.5 concentrations, such as technology, foreign investment levels, wind speed, precipitation, and Normalized Difference Vegetation Index (NDVI), evidenced significant spatial heterogeneity. Of these factors, precipitation, NDVI, and wind speed had small-scale regional effects, whose bandwidth ratios are all less than 20%, while foreign investment levels and technologies had medium-scale regional effects, whose bandwidth levels are 23% and 32%, respectively. Population, urbanization rates, and industrial structure demonstrated weak spatial heterogeneity, and the scale of their influence was predominantly global. (2) Overall, the change of NDVI was the most influential factor, which can explain 15.3% of the PM2.5 concentration change. Therefore, an enhanced protection of urban surface vegetation would be of universal significance. In some typical areas, dominant factors influencing pollution were evidently heterogeneous. Change in wind speed is a major factor that can explain 51.6% of the change in PM2.5 concentration in cities in the Central Plains, and change in foreign investment levels is the dominant influencing factor in cities in the Yunnan-Guizhou Plateau and the Sichuan Basin, explaining 30.6% and 44.2% of the PM2.5 concentration change, respectively. In cities located within the lower reaches of the Yangtze River, NDVI is a key factor, reducing PM2.5 concentrations by 9.7%. Those results can facilitate the development of region-specific measures and tailored urban policies to reduce PM2.5 pollution levels in different regions such as Northeast China and the Sichuan Basin.

Premature mortality attributable to PM2.5 pollution in China during 2008-2016: Underlying causes and responses to emission reductions

Long-term exposure to fine particulate matter (PM_2.5) poses a great threat to public health in China. To this end, the Chinese government promulgated the Air Pollution Prevention and Control Action Plan (the Action Plan) in 2013. However, the health benefits of the Action Plan have not been well explained. In this paper, the underlying causes of changes in premature mortality attributable to PM_2.5 pollution and the response of this mitigation policy in China were explored using sensitivity analysis. The simulated annual average PM_2.5 concentration reduced by 24.9% over mainland China from 2008 to 2016. Subsequently, national premature mortality would decrease by 14.4% from 1.14 million (95% CI: 0.54, 1.55) in 2008 to 0.98 million (95% CI: 0.44, 1.38) in 2016. Specifically, premature mortality reduced by 209,600 cases (-18.3%) owing to PM_2.5 reduction during 2008-2016, of which 188,500 cases were from 2014 to 2016 due to the Action Plan in 2013. Note that the health benefits were limited when compared with air quality improvements, mainly due to that the IER functions have a stable curve at higher concentration intervals. Meanwhile, premature mortality would have increased by 14.2% from 2008 to 2016 owing to demographic changes, substantially weakening the impact of the decrease in PM_2.5 and baseline mortality. The effectiveness of China's new air pollution mitigation policy was proved through the research. However, considering the non-linear response of mortality to PM_2.5 changes and the aggravation of demography trends, stronger emission control steps should be further taken to protect public health in China.