A county-level estimate of PM2.5 related chronic mortality risk in China based on multi-model exposure data

Alternative Energy Will Greatly Reduce the Impact of Aircraft Activities on Public Health in China

The increasing PM2.5 emissions from aviation in China significantly impact human health, necessitating the urgent adoption of clean energy solutions. This study assesses the impact of aviation-related PM2.5 emissions on deaths in China from 2024 to 2050. PM2.5 concentration data from 2015 to 2022 are used as a baseline, and three healthcare development scenarios are considered. The study then compares the changes in aviation PM2.5 concentrations under different mitigation pathways, including Sustainable Aviation Fuel (SAF), Hydrogen Turbine Engine (HTE), and Hydrogen Fuel Cell (HFC) engine. It incorporates these into the Global Exposure Mortality Model (GEMM) to estimate the excess deaths attributable to aviation activities in China. The scenario with significant medical improvements results in 4365 deaths by 2050, only 15.37% of the deaths in Business as Usual (BAU), and 32.91% in the scenarios with medical congestion due to severe aging. Using clean energy in China's aviation sector can reduce the number of deaths caused by PM2.5 emissions from aviation, with varying degrees of improvement depending on the start time and type of clean energy used. Further analysis reveals that in all scenarios, the proportion of male deaths is higher than that of females, at 58.10, 61.20, and 59.23%. Deaths due to ischemic heart disease (IHD) constitute the highest proportion, approximately 49.43%.

Occurrence, Seasonal Variation, and Health Risks of PM2.5-bound Liquid Crystal Monomers (LCMs) in Beijing, China

Liquid crystal monomers (LCMs) are potentially persistent, bioaccumulative, and toxic emerging pollutants. However, their occurrence in outdoor PM2.5 and related human exposure risks remain unknown. In this study, 32 composite samples were analyzed, which were prepared from daily PM2.5 samples collected throughout the year 2021 -2022 in Beijing, China. In total, fifty-six of 78 LCMs were presented at a median concentration of 66.0 pg/m3 (range: 13.3-375.6 pg/m3), with fluorinated LCMs (FBAs) predominating and accounting for 90.7 % of the total LCMs. This concentration surpasses that of halogenated persistent organic pollutants (e.g., polychlorinated dibenzo-p-dioxins/furans) in ambient PM2.5. Higher concentrations of LCMs were found in spring and summer compared to autumn and winter, which could be explained by correlations of concentrations with temperature (p < 0.05). Trans,trans-3,4-Difluoro-4'-(4'-pentylbicyclohexyl-4-yl)biphenyl, trans,trans-3,4-Difluoro-4'-(4'-propylbicyclohexyl-4-yl)biphenyl, and trans,trans-3,4,5-Trifluoro-4'-(4'-propylbicyclohexyl-4-yl)biphenyl were identified for the first time as dominant compounds in ambient samples. Based on predicted biological toxicities, 48 LCMs were categorized as high priority due to their high potential for human absorption, including several compounds previously overlooked. The non-carcinogenic risks of LCMs through inhalation and dermal were negligible for children and adults. This study firstly established a priority list of LCMs in PM2.5, highlighting the need for heightened awareness of their health risks.

National and provincial burden of disease attributable to fine particulate matter air pollution in China, 1990-2021: an analysis of data from the Global Burden of Disease Study 2021

BACKGROUND

Fine particulate matter (PM2·5) is the leading environmental risk factor for mortality and disability worldwide. We aimed to evaluate the temporal trend in, and spatial distribution of, the disease burden attributable to PM2·5 in China from 1990 to 2021.

METHODS

Based on the methodology framework and general analytical strategies applied in the Global Burden of Diseases, Injuries, and Risk Factors Study 2021, we calculated the numbers, age-standardised rates, and percentage of deaths and disability-adjusted life-years (DALYs) attributable to PM2·5 air pollution from 1990 to 2021 at the national and provincial level in China, by disease, sex, and age groups. Exposure to PM2·5, including ambient PM2·5 pollution and household PM2·5 pollution from solid fuels, was evaluated across 33 provincial administrative units in China.

FINDINGS

In 2021, 2·3 million (95% uncertainty interval [UI] 1·8-2·9) deaths and 46·7 million (36·6-59·7) DALYs could be attributable to PM2·5 pollution in China, accounting for 19·4% (16·0-23·6) of total deaths and 11·6% (9·4-14·1) of total DALYs. Of these, 1·9 million (95% UI 1·3-2·3) deaths and 37·8 million (26·3-46·5) DALYs resulted from ambient exposure, while 0·4 million (0·1-1·3) deaths and 8·9 million (1·5-27·8) DALYs were due to household exposure from solid fuel use. Stroke, ischaemic heart disease, and chronic obstructive pulmonary disease were the leading three causes. Two peaks in the burden were observed: in children aged younger than 5 years, and in people aged 70 years and older. The percentage of deaths and DALYs due to ambient PM2·5 was higher in men, while that due to household PM2·5 was higher in women. Geographically, the disease burden from ambient PM2·5 was higher in north and northwest China, while that from household PM2·5 was higher in southwest China. From 1990 to 2021, age-standardised death rates attributable to total PM2·5 decreased by 66·0% (95% UI 57·7-73·1) and those attributable to household PM2·5 decreased by 92·2% (76·6-98·7), with larger reductions observed in east and south China. By contrast, the disease burden related to ambient PM2·5 continued to increase and only began to decline in the past decade.

INTERPRETATION

Despite the decline in the disease burden attributable to total PM2·5 in China during 1990-2021, ambient PM2·5 remains a major contributor to mortality and disability. This study highlights considerable spatial heterogeneity across different provinces and provides valuable insights for developing geographically tailored strategies for PM2·5 control and public health promotion in China. Stricter control of ambient air pollution is needed in northern and northwestern regions, while promoting clean cooking energy is more urgently warranted in southwestern areas.

FUNDING

National Natural Science Foundation of China, National Key Research and Development Program of China, Shanghai Municipal Science and Technology Major Project, China Postdoctoral Science Foundation.

New evidence on the nephrotoxicity of fine particulate matter: Potential toxic components from different emission sources

Associations exist between fine particulate matter (PM2.5) exposure and impaired kidney function. However, the specific mechanisms and components causing renal damage remain unclear. PM2.5 was collected from an industrial and a rural area. Mice were categorized according to exposure, and biochemical, western blotting, histological, and immunohistochemical analyses were performed to evaluate the impact of PM2.5 constituents on their kidneys. To assess the impact of different PM2.5 components on inflammatory responses, a study was conducted by exposing the murine macrophage cell line (RAW 264.7). The study used a chelating resin to remove the influence of heavy metals from the water extract and employed a Toll-like receptor 4 (TLR4) antagonist to eliminate the effects of endotoxin, thereby evaluating the cellular inflammatory responses induced by various PM2.5 components. The major metallic elements at the industrial site were Fe, Mg, Zn, and Ca, whereas those at site Rural were Ca, K, and Mg. PM2.5 water extracts from both sites induced inflammatory cytokine upregulation in the lungs and kidneys, and inflammatory cell infiltration, antioxidant activity downregulation, and elevated levels of kidney injury molecule 1 in the kidneys. Exposure to PM2.5 water extract increased the mRNA levels of tumor necrosis factor-α, interleukin-6, and nitrite production in RAW264.7 macrophages. The inflammatory response and nitrite production induced by the industrial-site PM2.5 water extract were significantly suppressed after treatment with a chelating resin, whereas those from the rural area were suppressed by the Toll-like receptor 4 (TLR4) antagonist. These results suggest that heavy metals are crucial factors in PM2.5-induced cellular inflammatory responses in industrial areas, whereas endotoxin receptor--TLR4 mediated inflammatory pathways are the primary factor responsible for this response in rural areas. Furthermore, at equivalent dosages, the renal toxicity induced by the water-soluble components of rural-site PM2.5 may exceed that from industrial areas.

Increased impacts of aircraft activities on PM2.5 concentration and human health in China

The rapid development of China's aviation industry has caused a rapid increase in airport PM2.5 emissions. This study uses the Global Exposure Mortality Model (GEMM) to evaluate the monthly deaths caused by aircraft activities at 164 airports in China from 2015 to 2023, based on the PM2.5 concentration of airport aircraft activities and the detection data of the China National Environmental Monitoring Center, including twenty age groups, six diseases, and gender. This paper presents three main conclusions. Firstly, aviation PM2.5 emissions significantly impact mortality, with notable variations by year and season. The highest cumulative deaths are recorded in 2023, particularly in the third quarter, which peaked at 8,305 deaths. Despite the comparatively modest total of 11,604 deaths in 2022, a mere 0.2965 μg/m3 increase in PM2.5 concentration would precipitate an additional 39,138 deaths, representing a 1.05-fold rise from 2015. Secondly, the 80-84 age bracket exhibited the highest death proportion (16.51 %-18.73 %), while the 5-9 and 10-14 age groups had the lowest (0 %-0.13 %). Males aged 80-84 are the most affected demographic, with each 1 μg/m3 increase in PM2.5 leading to an additional 87 male deaths monthly in 2023, primarily from stroke and ischemic heart disease. In contrast, females only experienced 67 additional deaths per month from the same concentration increase. Lastly, airports in the economically vibrant Beijing-Shanghai-Guangzhou-Shenzhen region showed the highest mortality rates due to PM2.5 emissions. Airports in eastern coastal areas are more severely impacted than those in central and western China, revealing a spatial clustering of high death tolls in developed regions.

Higher risk of patients after stent(s) insertion with vessel bifurcation treated in the association between PM2.5 and cardiovascular hospital readmission

Stent(s) insertion is a common form of surgery for patients with cardiovascular diseases, and is associated with a high rate of hospital readmission. This study aims to investigate the acute association between PM2.5 exposure and hospital readmission for patients with cardiovascular disease and a history of stent(s) insertion. The records of hospital admission were collected from the Beijing Municipal Commission of Health and Family Planning Information Center between 1st January 2013 and 31st December 2017. Subsequent hospital readmission records for patients with a history of stent(s) insertion or without any surgery were extracted. The conditional logistic regression model was applied to investigate the association between PM2.5 concentration and cardiovascular disease readmission in patients who had undergone stent(s) insertion or without any surgery. A total of 81,468 patients who had a history of stent(s) insertion were included in this study. Of these, 17,224 patients (21.1 % of the total number of patients) were readmitted 27,749 times due to cardiovascular disease. The median daily PM2.5 concentration was 62.8 μg/m3 with an interquartile range (IQR) of 71.5 μg/m3. The excess risk (ER) associated 10 μg/m3 increase in PM2.5 concentration for readmission due to cardiovascular disease was 0.48 % (95 % CI: 0.09 %, 0.87 %) in patients with a history of stent(s) insertion. Patients who had stent(s) insertion at the vessel bifurcation site showed the highest risk of readmission for cardiovascular disease when exposed to PM2.5; the ER was 4.12 % (95 % CI: 1.60 %, 6.70 %). PM2.5 was significantly associated with angina pectoris and readmission for chronic ischemic heart disease in patients with a history of stent(s) insertion. PM2.5 had a significant association with cardiovascular readmission among patients with a history of insertion of stent(s). Patients who had vessel bifurcation treated showed the highest risk of readmission.

A systematic review of spatial and temporal epidemiological approaches, focus on lung cancer risk associated with particulate matter

BACKGROUND

Particulate matter (PM), including the major risk factor for lung cancer (LC), greatly impacts human health. Although numerous studies have highlighted spatiotemporal patterns and PM-LC associations, these studies have not been well-reviewed. Thus, we examined epidemiological studies linked with PM-LC and provided concise, up-to-date data.

METHODS

We used certain keywords to review articles published in PubMed, Web of Science, Scopus, and Google Scholar until 30th June 2024 and identified 1474 research articles. We then filtered the research articles based on our criteria and ultimately dropped down to 30 for this review.

RESULTS

Out of the thirty reviewed studies on the PM-LC relation, twenty-four focused on PM2.5, four on PM10, and two on both, indicating that approximately 80% of the respondents were inclined toward fine particles and their health impacts. The study revealed that 22 studies used visualization, 12 used exploration, and 15 used modeling methods. A strong positive relationship was reported between LC and PM2.5, ranging from 1.04 to 1.60 (95% CI) for a 10 µg/m3 increase in PM2.5 exposure. However, compared to PM2.5, PM10 was found to have a significantly less positive association.

CONCLUSIONS

Very few studies have used advanced spatiotemporal methods to examine the association between LC and PM. Advanced spatiotemporal analysis techniques should be employed to explore this association in specific geographical locations. Further research should utilize spatiotemporal epidemiological approaches to study the link between PM and lung cancer.

Assessment of short-term effects of ambient air pollution exposure on osteoarthritis outpatient visits

The association of short-term ambient air pollution exposure with osteoarthritis (OA) outpatient visits has been unclear and no study has assessed the modifying roles of district-level characteristics in the association between ambient air pollution exposure and OA outpatient visits. We investigated the cumulative associations of ambient air pollution exposure with daily OA outpatient visits and vulnerable factors influencing the associations using data from 16 districts of Beijing, China during 2013-2019. A total of 18,351,795 OA outpatient visits were included in the analyses. An increase of 10 μg/m3 in fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), maximum 8-hour moving-average ozone (8 h-O3), and 0.1 mg/m3 in carbon monoxide (CO) at representative lag days were associated with significant increases of 0.31 %, 0.06 %, 0.77 %, 0.87 %, 0.30 %, and 0.48 % in daily OA outpatient visits, respectively. Considerable OA outpatient visits were attributable to short-term ambient air pollution exposure. In addition, low temperature and high humidity aggravated ambient air pollution associated OA outpatient visits. District-level characteristics, such as population density, green coverage rate, and urbanization rate modified the risk of OA outpatient visits associated with air pollution exposure. These findings highlight the significance of controlling ambient air pollution during the urbanization process, which is useful in policy formation and implementation.

Risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 over 2017-2022 in Sanandaj, an area of Iran

The risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 has been less investigated. In this study, the attributable risk was estimated in an area of Iran. The predicted air PM2.5 using satellite data and a two-stage regression model was used as the predictor of the diseases. The dose-response linkage between the bias-corrected predictor employing a strong statistical approach and the outcomes was evaluated using the distributed lag nonlinear model. We considered two distinct scenarios of PM2.5 for the risk estimation. Alongside the risk, the attributable risk and number were estimated for different levels of PM2.5 by age and gender categories. The cumulative influence of PM2.5 particles on respiratory illnesses was statistically significant at 13-16 µg/m3 relative to the reference value (median), mostly apparent in the middle delays. The cumulative relative risk of 90th and 95th percentiles were 2.03 (CI 95%: 1.28, 3.19) and 2.25 (CI 95%: 1.28, 3.96), respectively. Nearly 600 cases of the diseases were attributable to the non-optimum values of the pollutant during 2017-2022, of which more than 400 cases were attributed to high values range. The predictor's influence on cardiovascular illnesses was along with uncertainty, indicating that additional research into their relationship is needed. The bias-corrected PM2.5 played an essential role in the prediction of respiratory illnesses, and it may likely be employed as a trigger for a preventative strategy.

Meta-analysis of fine particulate matter exposure during pregnancy and birth weight: Exploring sources of heterogeneity

BACKGROUND

Several meta-analyses assessed the relationship between exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) during pregnancy and birth weight (BW), but results were inconsistent and substantial unexplained heterogeneity was reported. We aimed to investigate the above association and to explore sources of heterogeneity across studies.

METHODS

We systematically reviewed the current worldwide evidence examining the association between PM2.5 and BW. The review protocol was registered on the PROSPERO website (CRD42020188996) and followed PRISMA guidelines. We extracted association measures for BW and low birth weight (LBW, BW < 2500 g) from each study to evaluate pooled summary measures and to explore sources of between-study heterogeneity.

FINDINGS

Of the 2677 articles identified, 84 met the inclusion criteria (~42 M births). Our random effects meta-analyses revealed substantial heterogeneity among included studies (I2 = 98.4 % and I2 = 77.7 %, for BW and LBW respectively). For LBW, the heterogeneity decreased (I2 = 59.7 %) after excluding four outlying studies, with a pooled odds ratio 1.07 (95 % confidence interval, CI: 1.05, 1.09) per a 10-μg/m3 increase in mean PM2.5 exposure over the entire pregnancy. Further subgroup analysis revealed geographic heterogeneity with higher association in Europe (1.34, (1.16, 1.55)) compared to Asia (1.06, (1.03, 1.10)) and US (1.07, (1.04, 1.10)).

CONCLUSION

The association between PM2.5 and birth weight varied depending on several factors. The sources of heterogeneity between studies included modifiers such as study region and period. Hence, it is advisable not to pool summary measures of PM2.5-BW associations and that policy would be informed by local evidence.

Spatial-temporal evolution characteristics of PM2.5 and its driving mechanism: spatially explicit insights from Shanxi Province, China

In China, despite the fact that the atmospheric environment quality has continued to improve in recent years, the PM2.5 pollution still had not been controlled fundamentally and its driving mechanism was complex which remained to be explored. Based on the 1-km ground-level PM2.5 datasets of China from 2000 to 2020, this study combined spatial autocorrelation, trend analysis, geographical detector, and multi-scale geographically weighted regression (MGWR) model to explore the spatial-temporal evolution of PM2.5 in Shanxi Province and revealed its complex driving mechanism behind this process. The results reflected that (1) there was a pronounced spatial clustering of PM2.5 concentration within Shanxi Province, with PM2.5 concentrations decreasing from southwest to northeast. From 2000 to 2020, the levels of PM2.5 pollution demonstrated a decline over time, with its concentrations decreasing by 9.15 µg/m3 overall. The Hurst exponent indicated a projected decrease in PM2.5 concentrations in the central and northern areas of Shanxi Province, contrasting with an anticipated increase in other regions. (2) The geographical detector indicated that all drivers had significant influences on PM2.5 concentrations, with meteorological factors exerting the greatest effects then followed by human activity and vegetation cover showing the least effects. (3) Both gross domestic product and population density exhibited positive correlations with PM2.5 concentration, while vegetation fractional cover, wind speed, precipitation, and elevation exerted negative influences on PM2.5 concentration all over the space. This study enriched the research content and ideas on the driving mechanism of PM2.5 and provided a reference for similar studies.

Multi-Scenario Validation and Assessment of a Particulate Matter Sensor Monitor Optimized by Machine Learning Methods

OBJECTIVE

The aim was to evaluate and optimize the performance of sensor monitors in measuring PM2.5 and PM10 under typical emission scenarios both indoors and outdoors.

METHOD

Parallel measurements and comparisons of PM2.5 and PM10 were carried out between sensor monitors and standard instruments in typical indoor (2 months) and outdoor environments (1 year) in Shanghai, respectively. The optimized validation model was determined by comparing six machining learning models, adjusting for meteorological and related factors. The intra- and inter-device variation, measurement accuracy, and stability of sensor monitors were calculated and compared before and after validation.

RESULTS

Indoor particles were measured in a range of 0.8-370.7 μg/m3 and 1.9-465.2 μg/m3 for PM2.5 and PM10, respectively, while the outdoor ones were in the ranges of 1.0-211.0 μg/m3 and 0.0-493.0 μg/m3, correspondingly. Compared to machine learning models including multivariate linear model (ML), K-nearest neighbor model (KNN), support vector machine model (SVM), decision tree model (DT), and neural network model (MLP), the random forest (RF) model showed the best validation after adjusting for temperature, relative humidity (RH), PM2.5/PM10 ratios, and measurement time lengths (months) for both PM2.5 and PM10, in indoor (R2: 0.97 and 0.91, root-mean-square error (RMSE) of 1.91 μg/m3 and 4.56 μg/m3, respectively) and outdoor environments (R2: 0.90 and 0.80, RMSE of 5.61 μg/m3 and 17.54 μg/m3, respectively), respectively.

CONCLUSIONS

Sensor monitors could provide reliable measurements of PM2.5 and PM10 with high accuracy and acceptable inter and intra-device consistency under typical indoor and outdoor scenarios after validation by RF model. Adjusting for both climate factors and the ratio of PM2.5/PM10 could improve the validation performance.

Is model-estimated PM2.5 exposure equivalent to station-observed in mortality risk assessment? A literature review and meta-analysis

Model-estimated air pollution exposure assessments have been extensively employed in the evaluation of health risks associated with air pollution. However, few studies synthetically evaluate the reliability of model-estimated PM2.5 products in health risk assessment by comparing them with ground-based monitoring station air quality data. In response to this gap, we undertook a meticulously structured systematic review and meta-analysis. Our objective was to aggregate existing comparative studies to ascertain the disparity in mortality effect estimates derived from model-estimated ambient PM2.5 exposure versus those based on monitoring station-observed PM2.5 exposure. We conducted searches across multiple databases, namely PubMed, Scopus, and Web of Science, using predefined keywords. Ultimately, ten studies were included in the review. Of these, seven investigated long-term annual exposure, while the remaining three studies focused on short-term daily PM2.5 exposure. Despite variances in the estimated Exposure-Response (E-R) associations, most studies revealed positive associations between ambient PM2.5 exposure and all-cause and cardiovascular mortality, irrespective of the exposure being estimated through models or observed at monitoring stations. Our meta-analysis revealed that all-cause mortality risk associated with model-estimated PM2.5 exposure was in line with that derived from station-observed sources. The pooled Relative Risk (RR) was 1.083 (95% CI: 1.047, 1.119) for model-estimated exposure, and 1.089 (95% CI: 1.054, 1.125) for station-observed sources (p = 0.795). In conclusion, most model-estimated air pollution products have demonstrated consistency in estimating mortality risk compared to data from monitoring stations. However, only a limited number of studies have undertaken such comparative analyses, underscoring the necessity for more comprehensive investigations to validate the reliability of these model-estimated exposure in mortality risk assessment.

The N6-methyladenosine modification in pathologic angiogenesis

The vascular system is a vital circulatory network in the human body that plays a critical role in almost all physiological processes. The production of blood vessels in the body is a significant area of interest for researchers seeking to improve their understanding of vascular function and maintain normal vascular operation. However, an excessive or insufficient vascular regeneration process may lead to the development of various ailments such as cancer, eye diseases, and ischemic diseases. Recent preclinical and clinical studies have revealed new molecular targets and principles that may enhance the therapeutic effect of anti-angiogenic strategies. A thorough comprehension of the mechanism responsible for the abnormal vascular growth in disease processes can enable researchers to better target and effectively suppress or treat the disease. N6-methyladenosine (m6A), a common RNA methylation modification method, has emerged as a crucial regulator of various diseases by modulating vascular development. In this review, we will cover how m6A regulates various vascular-related diseases, such as cancer, ocular diseases, neurological diseases, ischemic diseases, emphasizing the mechanism of m6A methylation regulators on angiogenesis during pathological process.

Uptake and distribution of the inorganic components NH4+ and NO3- in PM2.5 by two Chinese conifers

Plants can effectively purify PM2.5 in the air, thereby improving air quality. Understanding the mechanisms of the uptake and distribution of PM2.5 in plants is crucial for enhancing their ecological benefits. In this study, the uptake and distribution of the water-soluble inorganic compounds ammonium (NH4+) and nitrate (NO3-) ions in PM2.5 by the two native Chinese conifers Manchurian red pine (Pinus tabuliformis) and Bunge's pine (P. bungeana) were investigated using a one-time aerosol treatment method combined with 15N tracing. The results showed the following: (1) Plants can efficiently uptake NH4+ (0.08-0.21 μg/g) and NO3- (0.03-0.68 μg/g) from PM2.5. Manchurian red pine uptakes these compounds more effectively with increases of 2.01-fold for NH4+ and 1.02-fold for NO3- compared with Bunge's pine. (2) The aboveground organs of the plants uptake and distribute more 15N than the belowground organs. The branches had the highest unit mass uptake (0.08-1.60 μg/g) and rate of distribution (16.91-53.60 %) for NH4+, while the leaves had the highest unit mass uptake (0.15-1.18 μg/g) and rate of distribution (50.78-84.88 %) for NO3-. (3) The ability of the aboveground organs to uptake 15N is influenced by the concentration of PM2.5, which showed an overall increase with increasing concentrations with some fluctuations in specific organs. However, the belowground organs were not affected by the concentration of PM2.5. (4) A larger specific leaf area, root-shoot ratio, branch biomass ratio, coarse root biomass ratio, and lower trunk biomass ratio favors the uptake of NH4+ from PM2.5, whereas these traits had a minimal influence on the uptake of NO3-. Manchurian red pine uptaked significantly more NH4+ compared with Bunge's pine, which benefited from the traits described above. These findings further revealed the mechanism of PM2.5 uptake by plants and its relationship with PM2.5 concentration and plant traits, and provided a scientific basis for how to effectively utilize plants to reduce PM2.5 pollution and purify the environment in areas with different pollution concentrations.

Oral Administration of Sargassum horneri Suppresses Particulate Matter-Induced Oxidative DNA Damage in Alveolar Macrophages of Allergic Airway Inflammation: Relevance to PM-Mediated M1/M2 AM Polarization

SCOPE

Particulate matter (PM) can cause cellular oxidative damage and promote respiratory diseases. It has recently shown that Sargassum horneri ethanol extract (SHE) containing sterols and gallic acid reduces PM-induced oxidative stress in mice lung cells through ROS scavenging and metal chelating. In this study, the role of alveolar macrophages (AMs) is identified that are particularly susceptible to DNA damage due to PM-triggered oxidative stress in lungs of OVA-sensitized mice exposed to PM.

METHODS AND RESULTS

The study scrutinizes if PM exposure causes oxidative DNA damage to AMs differentially depending on their type of polarization. Further, SHE's potential is investigated in reducing oxidative DNA damage in polarized AMs and restoring AM polarization in PM-induced allergic airway inflammation. The study discovers that PM triggers prolonged oxidative stress to AMs, leading to lipid peroxidation in them and alveolar epithelial cells. Particularly, AMs are polarized to M2 phenotype (F4/80+ CD206+ ) with enhanced oxidative DNA damage when subject to PM-induced oxidative stress. However, SHE repairs oxidative DNA damage in M1- and M2-polarized AMs and reduces AMs polarization imbalance due to PM exposure.

CONCLUSION

These results suggest the possibility of SHE as beneficial foods against PM-induced allergic airway inflammation via suppression of AM dysfunction.

A comparative study of life-years lost attributable to air particulate matter in Asia-Pacific and European countries

Air particulate matter (PM) and its harmful effects on human health are of great concern globally due to all-cause and cause-specific mortality impacts across different population groups. While Europe has made significant progress in reducing particulate air pollution-related mortality through innovative technologies and policies, many countries in Asia-Pacific region still rely on high-polluting technologies and have yet to implement effective policies to address this issue, resulting in higher levels of mortality due to air pollution in the region. This study has three aims related to quantifying life-years lost (LYL) attributable to PM, and further separated into ambient PM and household air pollution (HAP): (1) to investigate LYL by causes of death; (2) to compare LYL between Asia-Pacific (APAC) and Europe; and (3) to assess LYL across different socio-demographic index (SDI) countries. The data used come from the Institute for Health Metrics and Evaluation (IHME) and Health Effects Institute (HEI). Our results show that average LYL due to PM in APAC was greater than in Europe, with some Pacific island countries particularly affected by the exposure to HAP. Three quarters of LYL came from premature deaths by ischemic heart disease and stroke, in both continents. There were significant differences between SDI groups for causes of death due to ambient PM and HAP. Our findings call for urgent improvement of clean air to reduce indoor and outdoor air pollution-related mortality in the APAC region.

Trends in all causes and cause specific mortality attributable to ambient particulate matter pollution in China from 1990 to 2019: A secondary data analysis study

BACKGROUND

Particularly fine particulate matter (PM2.5) has become a significant public health concern in China due to its harmful effects on human health. This study aimed to examine the trends in all causes and cause specific morality burden attributable to PM2.5 pollution in China.

METHODS

We extracted data on all causes and cause specific mortality data attributable to PM2.5 exposure for the period 1990-2019 in China from the Global Burden of Disease 2019. The average annual percent change (AAPC) in age-standardized mortality rates (ASMR) and years of life lost (YLLs) due to PM2.5 exposure were calculated using the Joinpoint Regression Program. Using Pearson's correlation, we estimated association between burden trends, urban green space area, and higher education proportions.

RESULTS

During the period 1990-1999, there were increases in mortality rates for All causes (1.6%, 95% CI: 1.5% to 1.8%), Diabetes mellitus (5.2%, 95% CI: 4.9% to 5.5%), Encephalitis (3.1%, 95% CI: 2.6% to 3.5%), Ischemic heart disease (3.3%, 95% CI: 3% to 3.6%), and Tracheal, bronchus and lung cancer (5%, 95% CI: 4.7% to 5.2%). In the period 2010-2019, Diabetes mellitus still showed an increase in mortality rates, but at a lower rate with an AAPC of 1.2% (95% CI: 1% to 1.4%). Tracheal bronchus and lung cancer showed a smaller increase in this period, with an AAPC of 0.5% (95% CI: 0.3% to 0.6%). In terms of YLLs, the trends appear to be similar.

CONCLUSION

Our findings highlight increasing trends in disease burden attributable to PM2.5 in China, particularly for diabetes mellitus, tracheal, bronchus, and lung cancer.

Chronic and acute health effects of PM2.5 exposure and the basis of pollution control targets

Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.

Influence of survey engagement and multiple-choice heuristics in the estimation of the value of a statistical life

Estimating the value of non-market goods, such as reductions in mortality risks due to traffic accidents or air pollution, is typically done using stated choice (SC) data. However, issues with potential estimation biases due to the hypothetical nature of SC experiments arise, as protest choices are common and survey engagement is not constant across respondents. Further, if respondents choose to use different choice mechanisms and this is not considered, the results may also be biased. We designed an SC experiment to estimate the willingness to pay (WTP) for mortality risk reductions, that allowed us to simultaneously estimate the WTP to reduce the risk of traffic accident deaths and cardiorespiratory deaths due to air pollution. We formulated and estimated a multiple heuristic latent class model that also considered two latent constructs: Institutional Belief, to consider protest responses, and survey Engagement as a class membership covariate. We found, first, that individuals with lower institutional belief gave a higher probability of choice to the status-quo alternative, shying away from programs involving governmental action. Second, that not identifying respondents who do not appropriately engage in the experiment, biased the WTP estimators. In our case WTP decreased up to 26% when two different choice heuristics were allowed for in the model.

Oxidative stress indices induced by industrial and urban PM2.5-bound metals in A549 cells

The detrimental effects of atmospheric fine particulate matter (PM_2.5) on human health are of major global concern. PM_2.5-bound metals are toxic compounds that contribute to cellular damage. To investigate the toxic effects of water-soluble metals on human lung epithelial cells and their bioaccessibility to lung fluid, PM_2.5 samples were collected from both urban and industrial areas in the metropolitan city of Tabriz, Iran. Oxidative stress indices, including proline content, total antioxidant capacity (TAC), cytotoxicity, and DNA damage levels of water-soluble components of PM_2.5, were evaluated. Furthermore, an in vitro test was conducted to assess the bioaccessibility of various PM_2.5-bound metals to the respiratory system using simulated lung fluid. PM_2.5 average concentrations in urban and industrial areas were 83.11 and 97.71 μg/m³, respectively. The cytotoxicity effects of PM_2.5 water-soluble constituents from urban areas were significantly higher than in industrial areas and the IC₅₀ was found to be 96.76 ± 3.34 and 201.31 ± 5.96 μg/mL for urban and industrial PM_2.5 samples, respectively. In addition, higher PM_2.5 concentrations increased the proline content in a concentration-dependent manner in A549 cells, which plays a protective role against oxidative stress and prevents PM_2.5-induced DNA damage. Also, the partial least squares regression revealed that Be, Cd, Co, Ni, and Cr, were significantly correlated with DNA damage and proline accumulation, which caused cell damage through oxidative stress. The results of this study showed that PM_2.5-bound metals in highly polluted metropolitan city caused substantial changes in the cellular proline content, DNA damage levels and cytotoxicity in human lung A549 cells.

Impact of lifetime air pollution exposure patterns on the risk of chronic disease

Long-term exposure to air pollution can lead to cardiovascular disease, metabolic syndrome, and chronic respiratory disease. However, from a lifetime perspective, the critical period of air pollution exposure in terms of health risk is unknown. This study aimed to evaluate the impact of air pollution exposure at different life stages. The study participants were recruited from community centers in Northern Taiwan between October 2018 and April 2021. Their annual averages for fine particulate matter (PM2.5) exposure were derived from a national visibility database. Lifetime PM2.5 exposures were determined using residential address information and were separated into three stages (<20, 20-40, and >40 years). We employed exponentially weighted moving averages, applying different weights to the aforementioned life stages to simulate various weighting distribution patterns. Regression models were implemented to examine associations between weighting distributions and disease risk. We applied a random forest model to compare the relative importance of the three exposure life stages. We also compared model performance by evaluating the accuracy and F1 scores (the harmonic mean of precision and recall) of late-stage (>40 years) and lifetime exposure models. Models with 89% weighting on late-stage exposure showed significant associations between PM_2.5 exposure and metabolic syndrome, hypertension, diabetes, and cardiovascular disease, but not gout or osteoarthritis. Lifetime exposure models showed higher precision, accuracy, and F1 scores for metabolic syndrome, hypertension, diabetes, and cardiovascular disease, whereas late-stage models showed lower performance metrics for these outcomes. We conclude that exposure to high-level PM_2.5 after 40 years of age may increase the risk of metabolic syndrome, hypertension, diabetes, and cardiovascular disease. However, models considering lifetime exposure showed higher precision, accuracy, and F1 scores and lower equal error rates than models incorporating only late-stage exposures. Future studies regarding long-term air pollution modelling are required considering lifelong exposure pattern. .¹.

Characteristics, health risks, and premature mortality attributable to ambient air pollutants in four functional areas in Jining, China

Air pollution is one of the leading causes for global deaths and understanding pollutant emission sources is key to successful mitigation policies. Air quality data in the urban, suburban, industrial, and rural areas (UA, SA, IA, and RA) of Jining, Shandong Province in China, were collected to compare the characteristics and associated health risks. The average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, and CO show differences of -3.87, -16.67, -19.24, -15.74, and -8.37% between 2017 and 2018. On the contrary, O₃ concentrations increased by 4.50%. The four functional areas exhibited the same seasonal variations and diurnal patterns in air pollutants, with the highest exposure excess risks (ERs) resulting from O₃. More frequent ER days occurred within the 25-30°C, but much larger ERs are found within the 0-5°C temperature range, attributed to higher O₃ pollution in summer and more severe PM pollution in winter. The premature deaths attributable to six air pollutants can be calculated in 2017 and 2018, respectively. Investigations on the potential source show that the ER of O₃ (r of 0.86) had the tightest association with the total ER. The bivariate polar plots indicated that the highest health-based air quality index (HAQI) in IA influences the HAQI in UA and SA by pollution transport, and thus can be regarded as the major pollutant emission source in Jining. The above results indicate that urgent measures should be taken to reduce O₃ pollution taking into account the characteristics of the prevalent ozone formation regime, especially in IA in Jining.

Potential health and economic impacts of shifting manufacturing from China to Indonesia or India

The diversification or decoupling of production chains from China to alternative Asian countries such as India or Indonesia would impact the spatial distribution of anthropogenic emissions, with corresponding economic impacts due to mortality associated with particulate matter exposure. We evaluated these changes using the Community Earth System Model, the Integrated Exposure-Response (IER) model and Willingness To Pay (WTP) method. Significant effects on PM_2.5 related mortality and economic cost for these deaths were seen in many East, Southeast and South Asian countries, particularly those immediately downwind of these three countries. Transferring all of export-related manufacturing to Indonesia resulted in significant mortality decreases in China and South Korea by 78k (5 per 100k) and 1k (2 per 100k) respectively, while Indonesia's mortality significantly increased (73.7k; 29 per 100k), as well as India, Pakistan and Nepal. When production was transferred to India, mortality rates in East Asia show similar changes to the Indonesian scenario, while mortalities in India increased dramatically (87.9k; 6 per 100k), and mortalities in many neighbors of India were also severely increased. Nevertheless, the economic costs for PM_2.5 related mortality were much smaller than national GDP changes in China (0.9 % of GDP vs. 18.3 % of GDP), India (2.7 % of GDP vs. 84.3 % of GDP) or Indonesia (9.4 % of GDP vs. 337 % of GDP) due to shifting all of export-related production lines from China to India or Indonesia. Morally, part of the benefits of economic activity should be used to compensate the neighboring communities where mortality increases occur.

Air pollution-induced health impacts and health economic losses in China driven by US demand exports

Understanding how trade between regions or countries drives the transfer of air pollution has attracted considerable interest recently, but few studies have explored the various transfer pathways or evaluated economic losses due to the health impact of such air pollution. Here, we assess the air pollutant emissions and related health impacts and economic losses in China caused by export trade due to US demand by combining the linked multi-regional input-output (MRIO) model, GEOS-Chem model, integrated exposure-response model, and the willingness to pay method. We show that the air pollutant emissions embedded in China's export due to the US demand reached 5792.38 Kt in 2012 (2.48% of the total), which includes direct exports of intermediate (40.27%) and final (33.61%) products and indirect exports of intermediate products via domestic provinces (16.43%, domestic spillover) and other countries (9.69%, foreign spillover). The resulting increase in PM_2.5 (<2.8 μg m^-3) leads to additional 27,963 deaths in 30 provinces, with a higher death toll in coastal areas and the corresponding economic loss was higher in more developed regions and reached USD 2.08 billion. This study highlights the region-different air pollution and health impacts in China embedded in the US-demand trade, and provides a framework for the analysis of health and economic losses hidden in global trade, particularly between developing and developed countries.

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 dynamics of cardiovascular and respiratory deaths attributed to long-term PM2.5 exposures in global megacities

Exposure to ambient fine particulate matter (PM_2.5) air pollution is a significant driver of premature deaths. We estimate the number of cardiovascular and respiratory (CR) premature deaths attributed to long-term exposure to PM_2.5 in 33 global megacities based on long-term remotely sensed observations from 2000 to 2019. Our analysis uses high-resolution (0.01 degree) PM_2.5 concentration data and cause-specific integrated exposure-response (IER) functions developed for the Global Burden of Disease Project. From 2000 to 2019, PM_2.5-related CR death rates per 1000 people increased in 6 of 33 megacities, decreased in 9, and remained constant in 18 megacities. The increase in PM_2.5-related CR mortality in 11 megacities located in South and East Asia during the period 2000-2019 can be attributed to the increases in PM_2.5 concentrations. All 33 megacities could avoid 30,248 (9 %), 62,989 (20 %), 128,457 (40 %), 198,462 (62 %) and all of the estimated 322,515 CR deaths attributed to PM_2.5 pollution in 2019 if they were to attain the World Health Organization's four interim PM_2.5 targets (IT-1, IT-2, IT-3, and IT-4) and the new air quality guideline (AQG), respectively. Major improvements in air quality are needed to reduce the number of CR deaths attributed to PM_2.5 in South and East Asia, in addition to ny reductions that would likely follow shifts in the population structures of these megacities moving forward.

Health burden and economic loss attributable to ambient PM2.5 in Iran based on the ground and satellite data

We estimated mortality and economic loss attributable to PM_2·5 air pollution exposure in 429 counties of Iran in 2018. Ambient PM_2.5-related deaths were estimated using the Global Exposure Mortality Model (GEMM). According to the ground-monitored and satellite-based PM_2.5 data, the annual mean population-weighted PM_2·5 concentrations for Iran were 30.1 and 38.6 μg m^-3, respectively. We estimated that long-term exposure to ambient PM_2.5 contributed to 49,303 (95% confidence interval (CI) 40,914-57,379) deaths in adults ≥ 25 yr. from all-natural causes based on ground monitored data and 58,873 (95% CI 49,024-68,287) deaths using satellite-based models for PM_2.5. The crude death rate and the age-standardized death rate per 100,000 population for age group ≥ 25 year due to ground-monitored PM_2.5 data versus satellite-based exposure estimates was 97 (95% CI 81-113) versus 116 (95% CI 97-135) and 125 (95% CI 104-145) versus 149 (95% CI 124-173), respectively. For ground-monitored and satellite-based PM_2.5 data, the economic loss attributable to ambient PM_2.5-total mortality was approximately 10,713 (95% CI 8890-12,467) and 12,792.1 (95% CI 10,652.0-14,837.6) million USD, equivalent to nearly 3.7% (95% CI 3.06-4.29) and 4.3% (95% CI 3.6-4.5.0) of the total gross domestic product in Iran in 2018.

PM2.5 induces pulmonary microvascular injury in COPD via METTL16-mediated m6A modification

Fine particulate matter (PM2.5) exposure is a significant cause of chronic obstructive pulmonary disease (COPD), but the detailed mechanisms involved in COPD remain unclear. In this study, we established PM2.5-induced COPD rat models and showed that PM2.5 induced pulmonary microvascular injury via accelerating vascular endothelial apoptosis, increasing vascular permeability, and reducing angiogenesis, thereby contributing to COPD development. Moreover, microvascular injury in COPD was validated by measurements of plasma endothelial microparticles (EMPs) and serum VEGF in COPD patients. We then performed m⁶A sequencing, which confirmed that altered N⁶-methyladenosine (m⁶A) modification was induced by PM2.5 exposure. The results of a series of experiments demonstrated that the expression of methyltransferase-like protein 16 (METTL16), an m⁶A regulator, was upregulated in PM2.5-induced COPD rats, while the expression of other regulators did not differ upon PM2.5-induction. To clarify the regulatory effect of METTL16-mediated m⁶A modification induced by PM2.5 on pulmonary microvascular injury, cell apoptosis, permeability, and tube formation, the m⁶A level in METTL16-knockdown pulmonary microvascular endothelial cells (PMVECs) was evaluated, and the target genes of METTL16 were identified from a set of the differentially expressed and m⁶A-methylated genes associated with vascular injury and containing predicted sites of METTL16 methylation. The results showed that Sulfatase 2 (Sulf2) and Cytohesin-1 (Cyth1) containing the predicted METTL16 methylation sites, exhibited higher m⁶A methylation and were downregulated after PM2.5 exposure. Further studies demonstrated that METTL16 may regulate Sulf2 expression via m⁶A modification and thereby contribute to PM2.5-induced microvascular injury. These findings not only provide a better understanding of the role played by m⁶A modification in PM2.5-induced microvascular injury, but also identify a new therapeutic target for COPD.

What drives long-term PM2.5-attributable premature mortality change? A case study in central China using high-resolution satellite data from 2003 to 2018

Ambient PM_2.5 was reported to be related to numerous negative health outcomes, leading to adverse public health impacts in many countries such as China. Despite the apparent reduction in PM_2.5 levels over China due to its emission control policies in recent years, the health burdens were not reduced as much as expected. This calls for a comprehensive analysis to explain the reasons behind to provide a useful reference for formulating effective emission control strategies. Taking central China as an example due to its large population and high levels of PM_2.5, this study quantified the spatiotemporal dynamics of premature mortality associated with PM_2.5 pollution in central China for each year during 2003-2018 and applied a decomposition analysis to dissect the contribution of various driving factors including ambient PM_2.5 level, demographic distribution and baseline incidence rate of four diseases related to air pollution. Results show significant spatiotemporal variations in PM_2.5-attributed health impact in central China, including Henan, Hubei, and Hunan provinces. Five Henan cities had the largest PM_2.5-attributable premature mortality (∼8-12 K premature mortalities), while three Hubei cities and one Hebei city had the least chronic PM_2.5-related all-cause mortality numbers (<1 K mortalities). Throughout the study period, the PM_2.5-caused premature mortality decreased by 54 K, in which changes in PM_2.5 levels and baseline incidence rates of stroke and chronic obstructive pulmonary disease contributed to the positive effect, whereas demographic changes and baseline incidence rate change of ischemic heart disease and lung cancer brought a countervailing effect. Our findings suggest more dynamic and comprehensive policies and measures that take into account spatiotemporal variations of health burden for effective alleviation of the health impact of PM_2.5 pollution in the country.

A Health Impact and Economic Loss Assessment of O3 and PM2.5 Exposure in China From 2015 to 2020

China is in a critical air quality management stage. Rapid industrial development and urbanization has resulted in non-ignorable air pollution, which seriously endangers human health. Assessment of the health impacts and economic losses of air pollution is essential for the prevention and control policy formulation. Based on ozone (O3) and fine particulate matter concentration (PM2.5) monitoring data in 331 Chinese cities from 2015 to 2020, this study evaluated the health effects and the corresponding economic losses of O3 and PM2.5 pollution on three health endpoints. The ratio of population exposed to O3 levels that exceeded the Chinese Ambient Air Quality Standards (CAAQS) increased from 13.35% in 2015 to 14.15% in 2020, which resulted in 133,415 (2015) - 156,173 (2020) all-cause deaths, 88,941 (2015) - 104,051 (2020) cardiovascular deaths, and 28,614 (2015) - 33,456 (2020) respiratory deaths. The ratio of population exposed to PM2.5 levels that exceeded the CAAQS decreased, but in many regions, especially in North China and the Yangtze River Delta, the PM2.5 concentration remained high. By 2020, nearly half of the population in China was still exposed to PM2.5 levels that exceeded the CAAQS, and the corresponding economic losses reached CNY 3.46 and 3.05 billion, respectively. These results improved the understanding of the spatial-temporal variation trends of major air pollutants at city scale in China, and emphasize the continued coordination urgently needed for controlling O3 and PM2.5 following the implementation of the 2013 policy to mitigate air pollution to protect human health.

PM2.5 and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China

BACKGROUND

Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of <2.5μm (PM2.5)] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which PM2.5 contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of PM2.5, gut microbiota, and metabolic diseases are unclear.

OBJECTIVES

We investigated the associations between personal exposure to PM2.5 and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between PM2.5 and insulin resistance and the mediating effects between PM2.5 and sphingolipid metabolism.

METHODS

We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between PM2.5 and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures (PM2.5) and featured metabolism outcomes.

RESULTS

Our prospective panel study illustrated that exposure to PM2.5 was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that PM2.5 exposure may contribute to systemic inflammation and altered sphingolipid metabolism.

DISCUSSION

Our findings demonstrated that PM2.5 was associated with the genera of the gut microbiota, which partially mediated the association between PM2.5 and sphingolipid metabolism. These findings may extend our current understanding of the pathways of PM2.5 and IR. https://doi.org/10.1289/EHP9688.

Urban-rural disparity of the short-term association of PM2.5 with mortality and its attributable burden

Although studies have investigated the associations between PM_2.5 and mortality risk, evidence from rural areas is scarce. We aimed to compare the PM_2.5-mortality associations between urban cities and rural areas in China. Daily mortality and air pollution data were collected from 215 locations during 2014–2017 in China. A two-stage approach was employed to estimate the location-specific and combined cumulative associations between short-term exposure to PM_2.5 (lag 0–3 days) and mortality risks. The excess risks (ER) of all-cause, respiratory disease (RESP), cardiovascular disease (CVD), and cerebrovascular disease (CED) mortality for each 10 μg/m³ increment in PM_2.5 across all locations were 0.54% (95% confidence interval [CI]: 0.38%, 0.70%), 0.51% (0.10%, 0.93%), 0.74% (0.50%, 0.97%), and 0.52% (0.20%, 0.83%), respectively. Slightly stronger associations for CVD (0.80% versus 0.60%) and CED (0.61% versus 0.26%) mortality were observed in urban cities than in rural areas, and slightly greater associations for RESP mortality (0.51% versus 0.43%) were found in rural areas than in urban cities. A mean of 2.11% (attributable fraction [AF], 95% CI: 1.48%, 2.76%) of all-cause mortality was attributable to PM_2.5 exposure in China, with a larger AF in urban cities (2.89% [2.12%, 3.67%]) than in rural areas (0.61% [−0.60%, 1.84%]). Disparities in PM_2.5-mortality associations between urban cities and rural areas were also found in some subgroups classified by sex and age. This study provided robust evidence on the associations of PM_2.5 with mortality risks in China and demonstrated urban-rural disparities of PM_2.5-mortality associations for various causes of death.

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PM_2.5 had greater effects on CVD/CED mortality in urban cities than in rural areas

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PM_2.5 had stronger effects on RESP mortality in rural areas than in urban cities

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An annual mean of 16.5/100,000 deaths was attributable to PM_2.5 in urban cities

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An annual mean of 3.4//100,000 deaths was attributable to PM_2.5 in rural areas

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Spatially targeted measures are needed to reduce PM_2.5-related mortality in China

Short-term associations between particulate matter air pollution and hospital admissions through the emergency room for urinary system disease in Beijing, China: A time-series study

Evidence on the relationship between particulate matter air pollution and urinary system disease (UD) is scarce. This study aims to evaluate the associations between short-term exposures to PM_2.5 and PM₁₀ and risk of daily UD inpatient hospital admissions through the emergency room (ER-admissions) in Beijing. We obtained 41,203 weekday UD ER-admissions for secondary and tertiary hospitals in all 16 districts in Beijing during 2013-2018 from the Beijing Municipal Health Commission Information Center and obtained district-level air pollution concentrations based on 35 fixed monitoring stations in Beijing. We conducted a two-stage time-series analysis, with district-specific generalized linear models for each of Beijing's 16 districts, followed by random effects meta-analysis to obtain pooled risk estimates. We evaluated lagged and cumulative associations up to 30 days. In single-pollutant models, for both PM_2.5 and PM₁₀, cumulative exposure averaged over the day of admission and the previous 10 days (lag 0-10 days) showed the strongest association, with per interquartile range increases of PM_2.5 or PM₁₀ concentrations associated with a 7.5 % (95 % confidence interval [CI]: 3.0 %-12.2 %) or 6.0 % (95 % CI: 1.1 %-11.2 %) increased risk of daily UD hospital admissions, respectively. The risk estimates were robust to adjustment for co-pollutants and to a variety of sensitivity analyses. However, due to the strong correlation between PM_2.5 and PM₁₀ concentrations, we were unable to disentangle the respective relationships between these two exposures and UD risk. In this study, we found that short-term exposures to PM_2.5 and PM₁₀ are risk factors for UD morbidity and that cumulative exposure to PM pollution over a period of one to two weeks (i.e., 11 days) could be more important for UD risk than transient exposure during each of the respective single days.

Global trends in diabetes-related mortality with regard to lifestyle modifications, risk factors, and affordable management: A preliminary analysis

Background

According to the World Health Organization (WHO), a global reduction of 17% has been achieved in the major noncommunicable disease-associated mortality rate since 2000. This decline was due to the decreasing mortality associated with cardiovascular and chronic respiratory diseases. The WHO has not made any comments on diabetes-related mortality thus far. The objective of this study was to demonstrate trends in diabetes-related mortality associated with country-wide interventions.

Methods

The WHO statistics were used to assess trends in diabetes-related mortality from 2000 to 2016. Different types of community-based interventions in 49 countries were compared and assessed.

Results

The baseline mortality decreased by 7%. Mortality in middle-income countries was higher than that in high-income countries. The prevalence of obesity showed a gradual increase in all countries. After implementation of the WHO “best buy” in 2010, mortality increased in 17 countries and decreased in 32 countries. Regarding the smoking prevalence trend, 87% countries with decreasing diabetes-related mortality had a gradual decline in tobacco usage since 2000. The decline was observed only in 43% countries with increasing diabetes-related mortality. The prevalence of hypertension increased in 19% countries with declining diabetes-related mortality and in 35% countries with increasing diabetes-related mortality. Physical activity measures tended to be better implemented in countries with declining diabetes-related mortality than in countries with increasing diabetes-related mortality.

Conclusion

Smoking cessation and better blood pressure control are associated with declining diabetes-related mortality. Longer implementation periods are needed for other lifestyle interventions.

Health and economic impacts from PM2.5 pollution transfer attributed to domestic trade in China: a provincial-level analysis

In recent years, severe air pollution has had a serious impact on the health and economy of residents and has attracted great attention. Due to the spatial separation between consumption and production, the transfer of PM_2.5 pollution and its health and economic effects caused by interprovincial trade have not been taken seriously. In this study, economic, atmospheric, and epidemiological models were combined to assess air pollution transfer and its health and economic impacts that are attributed to provincial trade in China. The analyses were performed under the PM_2.5 transfer scenario in which economically developed areas in eastern China transferred many health and economic impacts to inland areas through interprovincial trade in 2012. As a result of interprovincial trade, 1980 (95% CI 0, 4114) extra deaths and 208,000 (95% CI 74.5, 395.6) additional illnesses accrued, but 0.184 (95% CI 0.017, 0.372) billion USD of residents' economic loss was avoided in China. The results illustrate the serious impact of domestic trade on regional health and economics. It is necessary to comprehensively consider supply chains in designing policies to mitigate the negative health and economic impacts of air pollution across China.

Health Impact Attributable to Improvement of PM2.5 Pollution from 2014–2018 and Its Potential Benefits by 2030 in China

With the advancement of urbanization and industrialization, air pollution has become one of the biggest challenges for sustainable development. In recent years, ambient PM2.5 concentrations in China have declined substantially due to the combined effect of PM2.5 control and meteorological conditions. To this end, it is critical to assess the health impact attributable to PM2.5 pollution improvement and to explore the potential benefits which may be obtained through the achievement of future PM2.5 control targets. Based on PM2.5 and population data with a 1 km resolution, premature mortality caused by exposure to PM2.5 in China from 2014 to 2018 was estimated using the Global Exposure Mortality Model (GEMM). Then, the potential benefits of achieving PM2.5 control targets were estimated for 2030. The results show that premature mortality caused by PM2.5 pollution decreased by 22.41%, from 2,361,880 in 2014 to 1,832,470 in 2018. Moreover, the reduction of premature mortality in six major regions of China accounted for 52.82% of the national total reduction. If the PM2.5 control target can be achieved by 2030, PM2.5-related premature deaths will further decrease by 403,050, accounting for 21.99% of those in 2018. Among them, 87.02% of cities exhibited decreases in premature deaths. According to the potential benefits in 2030, all cities were divided into three types, of which type III cities should set stricter PM2.5 control targets and further strengthen the associated monitoring and governance. The results of this study provide a reference for the formulation of air pollution control policies based on regional differences.

Non-optimum temperature-related mortality burden in China: Addressing the dual influences of climate change and urban heat islands

Under the dual effects of climate change and urban heat islands (UHI), non-optimum temperature-related mortality burdens are complex and uncertain, and are rarely discussed in China. In this study, by applying city-specific exposure-response functions to multiple temperature and population projections under different climate and urbanization scenarios, we comprehensively assessed the non-optimum temperature-related mortality burdens in China from 2000 to 2050. Our results showed that temperature-related deaths will decrease from 1.19 million in 2010 to 1.08-1.17 million in 2050, with the exception of the most populous scenario. Excess deaths attributable to non-optimal temperatures under representative concentration pathway 8.5 (RCP8.5) were 2.35% greater than those under RCP4.5. This indicates that the surge in heat-related deaths caused by climate change will be offset by the reduction in cold-related deaths. As the climate changes, high-risk areas will be confronted with more severe health challenges, which requires health protection resource relocation strategies. Simultaneously, the net effects of UHIs are beneficial in the historical periods, preventing 3493 (95% CI: 22-6964) deaths in 2000. But UHIs will cause an additional 6951 (95% CI: -17,637-31,539, SSP4-RCP4.5) to 17,041 (95% CI: -10,516-44,598, SSP5-RCP8.5) deaths in 2050. The heavier health burden in RCP8.5 than RCP4.5 indicates that a warmer climate aggravates the negative effects of UHIs. Considering the synergistic behavior of climate change and UHIs, UHI mitigation strategies should not be developed without considering climate change. Moreover, the mortality burden exhibited strong spatial variations, with heavy burdens concentrated in the hotspots including Beijing-Tianjin Metropolitan Region, Yangtze River Delta, Chengdu-Chongqing City Group, Guangzhou, Wuhan, Xi'an, Shandong, and Henan. These hotspots should be priority areas for the allocation of the national medical resources to provide effective public health interventions.

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.

Synergistic effects of carbon nanoparticle-Cr-Pb in PM2.5 cause cell cycle arrest via upregulating a novel lncRNA NONHSAT074301.2 in human bronchial epithelial cells

Inhalation of carcinogenic PM_2.5 particles is a severe threat to all the people in both developing and developed nations. However, which components of PM_2.5 and how they perturb human cells to cause various diseases are still not understood. Here, employing a reductionism approach, we revealed that one of the crucial toxic and pathogenic mechanisms of PM_2.5 was the blocking of human bronchial cell cycle through upregulation of a novel long non-coding RNA NONHSAT074301.2 by carbon particles with payloads of Cr(VI) and Pb²⁺. We also discovered that NONHSAT074301.2 is a key regulatory molecule controlling cell cycle arrest at G2/M phase. This work highlights cellular function and molecular signaling events investigations using a 16-membered combinational model PM_2.5 library which contain carbon particles carrying four toxic pollutants in all possible combinations at environmental relevant concentrations. This work demonstrates a very powerful methodology to elucidate mechanisms at molecular level and help unlock the "black box" of PM_2.5-induced toxicities.

All-Cause Mortality Risk and Attributable Deaths Associated with Long-Term Exposure to Ambient PM2.5 in Chinese Adults

Several recent studies in China have associated raised mortality risks with chronic exposure to ambient PM_2.5. However, cohort evidence covering general populations and more homogeneous regions is extensively scarce. We conceived a nationwide perspective cohort study from 2010 through 2018, by enrolling 30 946 adult men and women aged 16-110 years from 25 provincial regions in mainland China. Cox proportional hazards models with time-varying exposures were adopted to quantify longitudinal association of PM_2.5 exposure with all-cause mortality. A total of 1762 death events occurred during a median follow-up of 8.1 years. Participants were exposed to a broad range of annual mean PM_2.5 concentrations (2.4-112 μg/m³), with an average estimate of 47.5 μg/m³. A 10-μg/m³ increase in annual average of PM_2.5 exposure was associated with an hazard ratio of 1.055 (95% confidence interval: 1.022-1.088, p < 0.001) for all-cause mortality. We estimated totally 2.68 million deaths attributable to ambient PM_2.5 in 2015, yielding a remarkable reduction of 36.7 thousand compared to the estimate in 2010 (2.72 million deaths). This study added nationally representative evidence regarding concentration-response function for long-term PM_2.5-mortality association in Chinese adults, which may significantly contribute to national and global assessments of PM_2.5-attributable death burden.

Interaction of Sirtuin 1 (SIRT1) candidate longevity gene and particulate matter (PM2.5) on all-cause mortality: a longitudinal cohort study in China

BACKGROUND

The SIRT1 gene was associated with the lifespan in several organisms through inflammatory and oxidative stress pathways. Long-term air particulate matter (PM) is detrimental to health through the same pathways.

METHODS

We used the Chinese Longitudinal Healthy Longevity Survey (CLHLS) to investigate whether there is a gene-environment (G × E) interaction of SIRT1 and air pollution on mortality in an older cohort in China. Among 7083 participants with a mean age of 81.1 years, we genotyped nine SIRT1 alleles for each participant and assessed PM_2.5 concentration using 3-year average concentrations around each participant's residence. We used Cox-proportional hazards models to estimate the independent and joint effects of SIRT1 polymorphisms and PM_2.5 exposure on all-cause mortality, adjusting for a set of confounders.

RESULTS

There were 2843 deaths over 42,852 person-years. The mortality hazard ratio (HR) and 95% confidence interval (CI) for each 10 μg/m³ increase in PM_2·5 was 1.08 (1.05-1.11); for SIRT1_391 was 0.77 (0.61, 0.98) in the recessive model after adjustment. In stratified analyses, participants carrying two SIRT1_391 minor alleles had a significantly higher HR for each 10 μg/m³ increase in PM_2.5 than those carrying zero minor alleles (1.323 (95% CI: 1.088, 1.610) vs. 1.062 (1.028, 1.096) p for interaction = 0.03). Moreover, the interaction of SIRT1 and air pollution on mortality is significant among women but not among men. We did not see significant relationships for SIRT1_366, SIRT1_773, and SIRT1_720.

CONCLUSION

We found a gene-environment interaction of SIRT1 and air pollution on mortality, future experimental studies are warranted to depict the mechanism observed in this study.

Improvement in life expectancy for ischemic heart diseases by achieving daily ambient PM2.5 standards in China

BACKGROUND

The potential impacts of daily ambient fine particulate pollution (PM_2.5) exposure on year of life lost (YLL) due to ischemic heart diseases (IHD) remain uncertain. We aimed to estimate the improvement in IHD-related life expectancy by attaining the daily air quality standards of ambient PM_2.5 in China.

METHODS AND RESULTS

This study was based on daily mortality data covering 96 Chinese cities from 2013 to 2016. Regional- and national-associations between IHD-related YLLs and daily PM_2.5 were estimated by generalized additive models. We further evaluated the IHD-related avoidable YLLs with an assumption that the daily PM_2.5 was below the ambient air quality standards of World Health Organization (WHO) and China, and calculated the improvement of life expectancy by dividing the avoidable YLLs by the overall number of IHD mortality. We totally recorded 1,485,140 IHD deaths from 2013 to 2016. At the national level, we found a positive association between IHD-related YLLs and daily PM_2.5. Per 10 μg/m³ increment of four-day averaged ambient PM_2.5 related to an increase of 0.40 IHD-related YLLs (95% CI: 0.28, 0.51). By achieving the WHO's air quality guideline, we estimated that an averaged number of 1346.94 (95% CI: 932.61, 1761.27) YLLs can be avoided for the IHD deaths in each city. On average, the life expectancy can be improved by 0.15 years (95% CI: 0.11, 0.19) for each death.

CONCLUSIONS

Our study provides a nationwide picture of the life expectancy improvements by reaching the daily PM_2.5 standards in China, indicating that people can live longer in an environment with higher air quality.

The long-term trend of PM2.5-related mortality in China: The effects of source data selection

Quantification of PM_2.5 exposure and associated mortality is critical to inform policy making. Previous studies estimated varying PM_2.5-related mortality in China due to the usage of different source data, but rarely justify the data selection. To quantify the sensitivity of mortality assessment to source data, we first constructed state-of-the-art PM_2.5 predictions during 2000-2018 at a 1-km resolution with an ensemble machine learning model that filled missing data explicitly. We also calibrated and fused various gridded population data with a geostatistical method. Then we assessed the PM_2.5-related mortality with various PM_2.5 predictions, population distributions, exposure-response functions, and baseline mortalities. We found that in addition to the well documented uncertainties in the exposure-response functions, missingness in PM_2.5 prediction, PM_2.5 prediction error, and prediction error in population distribution resulted to a 40.5%, 25.2% and 15.9% lower mortality assessment compared to the mortality assessed with the best-performed source data, respectively. With the best-performed source data, we estimated a total of approximately 25 million PM_2.5-related mortality during 2001-2017 in China. From 2001 to 2017, The PM_2.5 variations, growth and aging of population, decrease in baseline mortality led to a 7.8% increase, a 42.0% increase and a 24.6% decrease in PM_2.5-related mortality, separately. We showed that with the strict clean air policies implemented in 2013, the population-weighted PM_2.5 concentration decreased remarkably at an annual rate of 4.5 μg/m³, leading to a decrease of 179 thousand PM_2.5-related deaths nationwide during 2013-2017. The mortality decrease due to PM_2.5 reduction was offset by the population growth and aging population.

The impacts of coal dust on miners' health: A review

As one of the most important energy resources in the world, coal contributes a great deal to the world economy. Coal mining and processing involve multiple dust generation processes including coal cutting, transport, crushing and milling etc. Coal dust is one of the main sources of health hazard for the coal workers. Exposure of coal dusts can be prevented through administrative controls and engineering controls. Ineffective control of coal dust exposure can harm coal workers' health. Although many efforts have been made to eliminate these threats, recent years have seen an unexpected increase in coal workers' pneumoconiosis (CWP) in Appalachian basin in US. To explore the reasons for this phenomenon, in this review, we first reviewed the historical studies on coal mine dust including the regulation and engineering controls. Then, the effects of coal dust on human health was comprehensively reviewed. Next, the effects of nanoparticles on human health were reviewed, with an emphasis on toxicity of nanoparticles such as carbon nanotubes in other industries. From all this information, we hypothesize that nano-sized coal dust has contributed to the increase of CWP prevalence in recent years. As no research has been reported in this area, four directions which may need further investigation and future studies are recommended in this review. They include: 1) Systematic characterization of physicochemical properties of nano-size coal dust; 2) Toxicity and pathogenesis of nano-sized coal dust; 3) Development of real-time monitoring technology and equipment for nano-sized coal dust; 4) Development of exposure control technology and equipment. The intent of this review paper is to demonstrate the variation of coal dust properties and their impact on the mine worker's health. We suggest that the impact of nano-sized coal mine dust on miner's health has not yet been understood well and further improvements are necessary.

County-level variation in the long-term association between PM2.5 and lung cancer mortality in China

INTRODUCTION

The relative risk (RR) of long-term exposure to PM_2.5 in lung cancer mortality (LCM) may vary spatially in China. However, previous studies applying global regression have been unable to capture such variation. We aimed to employ a geographically weighted Poisson regression (GWPR) to estimate the RRs of LCM among the elderly (≥65 years) related to long-term exposure to PM_2.5 and the LCM attributable to PM_2.5 at the county level in China.

METHODS

We obtained annual LCM in the elderly between 2013 and 2015 from the National Death Surveillance. We linked annual mean concentrations of PM_2.5 between 2000 and 2004 with LCM using GWPR model at 148 counties across mainland China, adjusting for smoking and socioeconomic covariates. We used county-specific GWPR models to estimate annual average LCM in the elderly between 2013 and 2015 attributable to PM_2.5 exposure between 2000 and 2004.

RESULTS

The magnitude of the association between long-term exposure to PM_2.5 and LCM varied with county. The median of county-specific RRs of LCM among elderly men and women was 1.52 (range: 0.90, 2.40) and 1.49 (range: 0.88, 2.56) for each 10 μg/m³ increment in PM_2.5, respectively. The RRs were positively significant (P < 0.05) at 95% (140/148) of counties among both elderly men and women. Higher RRs of PM_2.5 among elderly men were located at Southwest and South China, and higher RRs among elderly women were located at Northwest, Southwest, and South China. There were 99,967 and 54,457 lung cancer deaths among elderly men and women that could be attributed to PM_2.5, with the attributable fractions of 31.4% and 33.8%, respectively.

CONCLUSIONS

The relative importance of long-term exposure to PM_2.5 in LCM differed by county. The results could help the government design tailored and efficient interventions. More stringent PM_2.5 control is urgently needed to reduce LCM in China.

Spatiotemporal variability in long-term population exposure to PM2.5 and lung cancer mortality attributable to PM2.5 across the Yangtze River Delta (YRD) region over 2010-2016: A multistage approach

The Yangtze River Delta region (YRD) is one of the most densely populated regions in the world, and is frequently influenced by fine particulate matter (PM_2.5). Specifically, lung cancer mortality has been recognized as a major health burden associated with PM_2.5. Therefore, this study developed a multistage approach 1) to first create dasymetric population data with moderate resolution (1 km) by using a random forest algorithm, brightness reflectance of nighttime light (NTL) images, a digital elevation model (DEM), and a MODIS-derived normalized difference vegetation index (NDVI), and 2) to apply the improved population dataset with a MODIS-derived PM_2.5 dataset to estimate the association between spatiotemporal variability of long-term population exposure to PM_2.5 and lung cancer mortality attributable to PM_2.5 across YRD during 2010-2016 for microscale planning. The created dasymetric population data derived from a coarse census unit (administrative unit) were fairly matched with census data at a fine spatial scale (street block), with R² and RMSE of 0.64 and 27,874.5 persons, respectively. Furthermore, a significant urban-rural difference of population exposure was found. Additionally, population exposure in Shanghai was 2.9-8 times higher than the other major cities (7-year average: 192,000 μg·people/m³·km²). More importantly, the relative risks of lung cancer mortality in high-risk areas were 28%-33% higher than in low-risk areas. There were 12,574-14,504 total lung cancer deaths attributable to PM_2.5, and lung cancer deaths in each square kilometer of urban areas were 7-13 times higher than for rural areas. These results indicate that moderate-resolution information can help us understand the spatiotemporal variability of population exposure and related health risk in a high-density environment.

The 17-y spatiotemporal trend of PM2.5 and its mortality burden in China

Investigations on the chronic health effects of fine particulate matter (PM_2.5) exposure in China are limited due to the lack of long-term exposure data. Using satellite-driven models to generate spatiotemporally resolved PM_2.5 levels, we aimed to estimate high-resolution, long-term PM_2.5 and associated mortality burden in China. The multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) at 1-km resolution was employed as a primary predictor to estimate PM_2.5 concentrations. Imputation techniques were adopted to fill in the missing AOD retrievals and provide accurate long-term AOD aggregations. Monthly PM_2.5 concentrations in China from 2000 to 2016 were estimated using machine-learning approaches and used to analyze spatiotemporal trends of adult mortality attributable to PM_2.5 exposure. Mean coverage of AOD increased from 56 to 100% over the 17-y period, with the accuracy of long-term averages enhanced after gap filling. Machine-learning models performed well with a random cross-validation R ² of 0.93 at the monthly level. For the time period outside the model training window, prediction R ² values were estimated to be 0.67 and 0.80 at the monthly and annual levels. Across the adult population in China, long-term PM_2.5 exposures accounted for a total number of 30.8 (95% confidence interval [CI]: 28.6, 33.2) million premature deaths over the 17-y period, with an annual burden ranging from 1.5 (95% CI: 1.3, 1.6) to 2.2 (95% CI: 2.1, 2.4) million. Our satellite-based techniques provide reliable long-term PM_2.5 estimates at a high spatial resolution, enhancing the assessment of adverse health effects and disease burden in China.

The changing PM2.5 dynamics of global megacities based on long-term remotely sensed observations

Satellite observations show that the rapid urbanization and emergence of megacities with 10 million or more residents have raised PM2.5 concentrations across the globe during the past few decades. This study examines PM2.5 dynamics for the 33 cities included on the UN list of megacities published in 2018. These megacities were classified into densely (>1500 residents per km²), moderately (300-1500 residents per km²) and sparsely (<300 residents per km²) populated areas to examine the effect of human population density on PM2.5 concentrations in these areas during the period 1998-2016. We found that: (1) the higher population density areas experienced higher PM2.5 concentrations; and (2) the megacities with high PM2.5 concentrations in these areas had higher concentrations than those in the moderately and sparsely populated areas of other megacities as well. The numbers of residents experiencing poor air quality is substantial: approximately 452 and 163 million experienced average annual PM2.5 levels exceeding 10 and 35 μg/m³, respectively in 2016. We also examined PM2.5 trends during the past 18 years and predict that high PM2.5 levels will likely continue in many of these megacities in the future without substantial changes in their economies and/or pollution abatement practices. There will be more megacities in the highest PM2.5 pollution class and the number of megacities in the lowest PM2.5 pollution class will likely not change. Finally, we analyzed how the PM2.5 pollution burden varies geographically and ranked the 33 megacities in terms of PM2.5 pollution in 2016. The most polluted regions are China, India, and South Asia and the least polluted regions are Europe and Japan. None of the 33 megacities currently fall in the WHO's PM2.5 attainment class (<10 μg/m³) while 9 megacities fall into the PM2.5 non-attainment class (>35 μg/m³). In 2016, the least polluted megacity was New York and most polluted megacity was Delhi whose average annual PM2.5 concentration of 110 μg/m³ is nearly three times the WHO's non-attainment threshold.