Tracking short-term health impacts attributed to ambient PM2.5 and ozone pollution in Chinese cities: an assessment integrates daily population.
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ABSTRACT:
SUBMITTER: Guan Y
PROVIDER: S-EPMC9315092 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundFew large multicity studies have been conducted in developing countries to address the acute health effects of atmospheric ozone pollution.ObjectiveWe explored the associations between ozone and daily cause-specific mortality in China.MethodsWe performed a nationwide time-series analysis in 272 representative Chinese cities between 2013 and 2015. We used distributed lag models and over-dispersed generalized linear models to estimate the cumulative effects of ozone (lagged over 0-3 d) on mortality in each city, and we used hierarchical Bayesian models to combine the city-specific estimates. Regional, seasonal, and demographic heterogeneity were evaluated by meta-regression.ResultsAt the national-average level, a 10-μg/m3 increase in 8-h maximum ozone concentration was associated with 0.24% [95% posterior interval (PI): 0.13%, 0.35%], 0.27% (95% PI: 0.10%, 0.44%), 0.60% (95% PI: 0.08%, 1.11%), 0.24% (95% PI: 0.02%, 0.46%), and 0.29% (95% PI: 0.07%, 0.50%) higher daily mortality from all nonaccidental causes, cardiovascular diseases, hypertension, coronary diseases, and stroke, respectively. Associations between ozone and daily mortality due to respiratory and chronic obstructive pulmonary disease specifically were positive but imprecise and nonsignificant. There were no statistically significant differences in associations between ozone and nonaccidental mortality according to region, season, age, sex, or educational attainment.ConclusionsOur findings provide robust evidence of higher nonaccidental and cardiovascular mortality in association with short-term exposure to ambient ozone in China. https://doi.org/10.1289/EHP1849.
| S-EPMC5947936 | biostudies-literature
Project description:Air pollution epidemiology studies of ambient fine particulate matter (PM2.5) and ozone (O3) often use outdoor concentrations as exposure surrogates. Failure to account for the variability of the indoor infiltration of ambient PM2.5 and O3, and time indoors, can induce exposure errors. We developed an exposure model called TracMyAir, which is an iPhone application ("app") that determines seven tiers of individual-level exposure metrics in real-time for ambient PM2.5 and O3 using outdoor concentrations, weather, home building characteristics, time-locations, and time-activities. We linked a mechanistic air exchange rate (AER) model, a mass-balance PM2.5 and O3 building infiltration model, and an inhaled ventilation model to determine outdoor concentrations (Tier 1), residential AER (Tier 2), infiltration factors (Tier 3), indoor concentrations (Tier 4), personal exposure factors (Tier 5), personal exposures (Tier 6), and inhaled doses (Tier 7). Using the application in central North Carolina, we demonstrated its ability to automatically obtain real-time input data from the nearest air monitors and weather stations, and predict the exposure metrics. A sensitivity analysis showed that the modeled exposure metrics can vary substantially with changes in seasonal indoor-outdoor temperature differences, daily home operating conditions (i.e., opening windows and operating air cleaners), and time spent outdoors. The capability of TracMyAir could help reduce uncertainty of ambient PM2.5 and O3 exposure metrics used in epidemiology studies.
| S-EPMC6766031 | biostudies-literature
Project description:India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015-2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM2.5 annual standard (40 μg m-3). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM2.5 in India. About 60 % of India's mean population-weighted PM2.5 concentrations come from anthropogenic source sectors, while the remainder are from "other" sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.
| S-EPMC7935015 | biostudies-literature
Project description:Background: Exposure to 2.5-micron diameter air pollutants (PM 2.5) has been associated with an increased risk of illness and death worldwide; however, in Latin American health impacts assessment of this risk factor is scarce. Medellín is one of the most polluted cities in the region, with a population growth rate that is twice as high as that of other Colombian cities, which implies a growing population at risk. Methods: A descriptive study of the disease burden was carried out using the city as the unit of observation. Health events were selected based on epidemiologic evidence and the availability of the population attributable fraction associated with PM 2.5. The mortality records were taken from the module of deceased of the Single Registry of Affiliates of the Health System; the morbidity records were taken from the Individual Health Services Registries. For the estimation of the burden of disease, the current Global Burden of Disease guidelines were followed. Results: Attributable disability-adjusted life years to exposure to ambient PM 2.5 pollution (DALYs PM2.5) constituted 13.8% of total burden of the city. Males showed the greatest loss of DALYs PM2.5 due to acute events, while in women the greatest loss was due to chronic events. Ischemic heart disease, chronic diseases of the lower respiratory tract, and influenza and pneumonia were the events that contributed the most to DALYs PM2.5. 71.4% of the DALYs PM2.5 corresponded to mortality, mainly in the population over 65 years of age. Regarding attributable morbidity, acute events were more prevalent in both sexes, especially due to respiratory diseases Conclusion: Premature death among the elderly population has the greatest weight on burden of disease attributable to ambient PM 2.5 pollution, mainly due to respiratory and cardiovascular diseases, without significant differences according to gender.
| S-EPMC8564742 | biostudies-literature
Project description:With the continuous promotion of urbanization in China, air pollution problems have become increasingly prominent in recent years. Various factors, such as emissions, meteorology, and physical and chemical reactions, jointly affect the severity of PM2.5 pollution to a large extent. This study selected five meteorological variables (planetary boundary layer height (PBLH), wind speed (WS), temperature(T), water vapor mixing ratio(Q), and precipitation (PCP)) for perturbation, and 21 different scenarios were set up. In this study, the effects of changes in a single meteorological variable on the pollutants produced in the area were represented by subtracting the baseline scenario (i.e., without perturbation of meteorological variables) simulated in January 2017 separately from each post-disturbance scenario. The results showed that Handan (HD) has the highest annual mean PM2.5 concentration of 85.75 μg/m3 in 2017, while all cities in study area exceeded the secondary concentration limit of urban atmospheric particulate matter. The correlation coefficient (R) between the simulation values of models and the actual monitoring values ranges from 0.41 to 0.74, indicating good model performance and acceptable simulation errors. PBLH (±10%-±20%), WS(±10%-±20%), and PCP(±10%-±20%) all showed a single adverse effect among the five meteorological variables, meaning that a reduction in these three factors led to an increase in PM2.5 concentrations. However, T (±1 K-±1.5 K) and Q (±10%-±20%) could indicate a positive impact under certain conditions. From the sensitivity calculations of single meteorological variables, it is clear that WS, PBLH, and PCP show a highly linear trend in all cities at the 0.01 level of significance. The hypothesis that T changes linearly in 10 cities in the study area is valid, while for Q, the hypothesis that Q changes linearly only occurs in Shijiazhuang and Baoding. When different meteorological variables are disturbed, there are significant spatial differences in the main affected areas of PM2.5 concentrations. By discussing the impact of meteorological variable disturbance on air quality in critically polluted cities in China, this study identified the meteorological variables that can substantially affect PM2.5 concentration. The more complex T and Q should be considered when formulating relevant emission measures.
| S-EPMC10359771 | biostudies-literature
Project description:Here we retrieve global daily 1 km gapless PM2.5 concentrations via machine learning and big data, revealing its spatiotemporal variability at an exceptionally detailed level everywhere every day from 2017 to 2022, valuable for air quality monitoring, climate change, and public health studies. We find that 96%, 82%, and 53% of Earth's populated areas are exposed to unhealthy air for at least one day, one week, and one month in 2022, respectively. Strong disparities in exposure risks and duration are exhibited between developed and developing countries, urban and rural areas, and different parts of cities. Wave-like dramatic changes in air quality are clearly seen around the world before, during, and after the COVID-19 lockdowns, as is the mortality burden linked to fluctuating air pollution events. Encouragingly, only approximately one-third of all countries return to pre-pandemic pollution levels. Many nature-induced air pollution episodes are also revealed, such as biomass burning.
| S-EPMC10724144 | biostudies-literature
Project description:Background & aimsEmerging evidence supports ambient fine particulate matter (PM2.5) exposure is associated with insulin resistance (IR) and hepatic lipid accumulation. In this study, we aimed to evaluate the sex-dependent vulnerability in response to PM2.5 exposure and investigate the underlying mechanism by which PM2.5 modulates hepatic lipid metabolism.MethodsBoth male and female C57BL/6 mice were randomly assigned to ambient PM2.5 or filtered air for 24?weeks via a whole body exposure system. High-coverage quantitative lipidomics approaches and liquid chromatography-mass spectrometry techniques were performed to measure hepatic metabolites and hormones in plasma. Metabolic studies, histological analyses, as well as gene expression levels and molecular signal transduction analysis were applied to examine the effects and mechanisms by which PM2.5 exposure-induced metabolic disorder.ResultsFemale mice were more susceptible than their male counterparts to ambient PM2.5 exposure-induced IR and hepatic lipid accumulation. The hepatic lipid profile was changed in response to ambient PM2.5 exposure. Levels of hepatic triacylglycerols (TAGs), free fatty acids (FFAs) and cholesterol were only increased in female mice from PM group compared to control group. Plasmalogens were dysregulated in the liver from PM2.5-exposed mice as well. In addition, exposure to PM2.5 led to enhanced hepatic ApoB and microsomal triglyceride transport protein expression in female mice. Finally, PM2.5 exposure inhibited hypothalamus-pituitary-adrenal (HPA) axis and decreased glucocorticoids levels, which may contribute to the vulnerability in PM2.5-induced metabolic dysfunction.ConclusionsAmbient PM2.5 exposure inhibited HPA axis and demonstrated sex-associated differences in its effects on IR and disorder of hepatic lipid metabolism. These findings provide new mechanistic evidence of hormone regulation in air pollution-mediated metabolic abnormalities of lipids and more personalized care should be considered in terms of sex-specific risk factors.
| S-EPMC7178763 | biostudies-literature
Project description:BackgroundThe systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias.MethodsWe evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 ?m or less (PM10) and fine PM with an aerodynamic diameter of 2.5 ?m or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived.ResultsOn average, an increase of 10 ?g per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations.ConclusionsOur data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).
| S-EPMC7891185 | biostudies-literature
Project description:The spatial disparity of air pollutants is one of the key influential factors for environmental inequality. We quantitatively evaluated the evolution of PM2.5 spatial disparity in China during 2013-2020, and investigated the associations between PM2.5 spatial disparity and economic indicators. Differences in PM2.5 between more- and less-polluted cities declined over time, suggesting decreased absolute disparity. However, the more polluted cities in 2013 remained so in 2017 and 2020, and vice versa, indicating persistent relative disparity. PM2.5 pollution levels increased with higher GDP per capita in less-developed areas of China, but such negative effects weakened over time, while economic development tended to promote cleaner air in developed areas of China. Therefore, policies to improve air quality and promote economic development simultaneously are needed in China to reduce the disparity of air pollution and promote all people to enjoy environmental equality.
| S-EPMC10902506 | biostudies-literature
Project description:While there have been substantial efforts to quantify the health burden of exposure to PM2.5 from solid fuel use (SFU), the sensitivity of mortality estimates to uncertainties in input parameters has not been quantified. Moreover, previous studies separate mortality from household and ambient air pollution. In this study, we develop a new estimate of mortality attributable to SFU due to the joint exposure from household and ambient PM2.5 pollution and perform a variance-based sensitivity analysis on mortality attributable to SFU. In the joint exposure calculation, we estimate 2.81 (95% confidence interval: 2.48-3.28) million premature deaths in 2015 attributed to PM2.5 from SFU, which is 580,000 (18%) fewer deaths than would be calculated by summing separate household and ambient mortality calculations. Regarding the sources of uncertainties in these estimates, in China, India, and Latin America, we find that 53-56% of the uncertainty in mortality attributable to SFU is due to uncertainty in the percent of the population using solid fuels and 42-50% from the concentration-response function. In sub-Saharan Africa, baseline mortality rate (72%) and the concentration-response function (33%) dominate the uncertainty space. Conversely, the sum of the variance contributed by ambient and household PM2.5 exposure ranges between 15 and 38% across all regions (the percentages do not sum to 100% as some uncertainty is shared between parameters). Our findings suggest that future studies should focus on more precise quantification of solid fuel use and the concentration-response relationship to PM2.5, as well as mortality rates in Africa.
| S-EPMC7007171 | biostudies-literature