Addition of PM 2.5 into the national ambient air quality standards of China and the contribution to air pollution control: the case study of Wuhan, China.
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ABSTRACT:
SUBMITTER: You M
PROVIDER: S-EPMC3997137 | biostudies-other | 2014
REPOSITORIES: biostudies-other
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Project description:China's efforts to curb air pollution have drastically reduced its concentrations of fine particulate matter (PM2.5) from 2013 to 2018 nationwide. However, few studies examined the most recent changes in PM2.5 concentrations and questioned if the previous PM2.5 declining trend was sustained or not. This study took a deep dive into the PM2.5 trend for 136 northern cities of China from 2015 to early 2020 before the coronavirus disease 2019 (the COVID-19 hereafter) crisis, using ground-based PM2.5 data notably adjusted for a key measurement method change. We find that mean PM2.5 concentrations in northern China increased by 5.16 µg/m3 in 2019, offsetting 80% of the large reduction achieved in 2018. The rebound was more significant during the heating seasons (HS; Nov to next Mar) over the 2 years: 10.49 µg/m3 from the 2017 HS to the 2019 HS. A multiple linear regression analysis further revealed that anthropogenic factors contributed to around 50% of the PM2.5 rebound in northern cities of China. Such a significant role of anthropogenic factors in driving the rebound was tightly linked to deep cuts in PM2.5 concentrations in the previous year, systemic adjustment of policy targets and mitigation measures by the government, and the rising marginal cost of these measures. These findings suggest the need to chart a more sustainable path for future PM2.5 emission reductions, with an emphasis on key regions during key pollution periods.
| S-EPMC8731191 | 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:BackgroundPositive associations between ambient PM2.5 and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM2.5 based on an entire population of a megalopolis. In addition, most studies in China have used averaged data, which results in variations between monitoring and personal exposure values, creating an inherent and unavoidable type of measurement error.MethodsThis study was conducted in Wuhan, a megacity in central China with about 10.9 million people. Daily hospital admission records, from October 2016 to December 2018, were obtained from the Wuhan Information center of Health and Family Planning, which administrates all hospitals in Wuhan. Daily air pollution concentrations and weather variables in Wuhan during the study period were collected. We developed a land use regression model (LUR) to assess individual PM2.5 exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposure to PM2.5. We also conducted stratification analyses by age, sex, and season.ResultsA total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 cardiovascular disease admissions and 159,365 respiratory disease admissions. Short-term exposure to PM2.5 was associated with an increased risk of a cardiorespiratory hospital admission. A 10 μg/m3 increase in PM2.5 (lag0-2 days) was associated with an increase in hospital admissions of 1.23% (95% CI 1.01-1.45%) and 1.95% (95% CI 1.63-2.27%) for cardiovascular and respiratory diseases, respectively. The elderly were at higher PM-induced risk. The associations appeared to be more evident in the cold season than in the warm season.ConclusionsThis study contributes evidence of short-term effects of PM2.5 on cardiorespiratory hospital admissions, which may be helpful for air pollution control and disease prevention in Wuhan.
| S-EPMC8080330 | biostudies-literature
Project description:Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM2.5 and PM10. We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.
| S-EPMC7697898 | biostudies-literature
Project description:Long-term air pollution exposure, notably fine particulate matter, is a global contributor to morbidity and mortality and a known risk factor for coronary artery disease (CAD) and myocardial infarctions (MI). Knowledge of impacts related to source-apportioned PM2.5 is limited. New modeling methods allow researchers to estimate source-specific long-term impacts on the prevalence of CAD and MI. The Catheterization Genetics (CATHGEN) cohort consists of patients who underwent a cardiac catheterization at Duke University Medical Center between 2002 and 2010. Severity of coronary blockage was determined by coronary angiography and converted into a binary indicator of clinical CAD. History of MI was extracted from medical records. Annual averages of source specific PM2.5 were estimated using an improved gas-constrained source apportionment model for North Carolina from 2002 to 2010. We tested six sources of PM2.5 mass for associations with CAD and MI using mixed effects multivariable logistic regression with a random intercept for county and multiple adjustments. PM2.5 fractions of ammonium bisulfate and ammonium nitrate were associated with increased prevalence of CAD (odds ratio [OR] 1.20; 95% CI = 1.11, 1.22 and OR 1.18; 95% CI = 1.05, 1.32, respectively). PM2.5 from ammonium bisulfate and ammonium nitrate were also associated with increased prevalence of MI (OR 1.20; 95% CI = 1.10, 1.29 and OR 1.35; 95% CI = 1.20, 1.53, respectively). Greater PM2.5 concentrations of ammonium bisulfate and ammonium nitrate are associated with greater MI and CAD prevalence. The association with bisulfate suggests aerosol acidity may play a role. Our findings suggest analyses of source specific PM2.5 mass can reveal novel associations.
| S-EPMC8196100 | biostudies-literature
Project description:Frailty is common among older people and results in adverse health outcomes. We investigated whether exposure to PM2.5 is associated with frailty. This cross-sectional study involved 20,606 community-dwelling participants aged ≥ 65 years, residing in New Taipei City, Taiwan. Analytic data included phenotypic frailty, disease burden by Charlson Comorbidity Index (CCI), urban or rural residence, and household income. PM2.5 exposure was calculated from air quality monitoring records, with low exposure defined as the lowest quartile of the study population. 1,080 frail participants (5.2%) were older, predominantly female, had more comorbidities, lived rurally, and had low PM2.5 exposure (all p < 0.001). In multinomial logistic regression analyses, the likelihood of high PM2.5 exposure was higher in prefrail (OR 1.4, 95% CI 1.3-1.5) and frail adults (OR 1.5, 95% CI 1.2-1.9) than in robust individuals, with stronger associations in those who were male (frail: OR 2.1, 95% CI 1.5-3.1; prefrail: OR 2.2, 95% CI 1.9-2.6), ≥ 75 years old (frail: OR 1.8, 95% CI 1.3-2.4; prefrail: OR 1.5, 95% CI 1.3-1.8), non-smokers (frail: OR 1.6, 95% CI 1.3-2.0; prefrail: OR 1.4, 95% CI 1.2-1.5), had CCI ≥ 2 (frail: OR 5.1, 95% CI 2.1-12.6; prefrail: OR 2.1, 95% CI 1.2-3.8), and with low household income (frail: OR 4.0, 95% CI 2.8-5.8; prefrail: OR 2.7, 95% CI 2.2-3.3). This study revealed a significant association between PM2.5 exposure and frailty, with a stronger effect in vulnerable groups.
| S-EPMC7468121 | biostudies-literature
Project description:BackgroundAir pollution disparities by socioeconomic status (SES) are well documented for the United States, with most literature indicating an inverse relationship (i.e., higher concentrations for lower-SES populations). Few studies exist for China, a country accounting for 26% of global premature deaths from ambient air pollution.ObjectiveOur objective was to test the relationship between ambient air pollution exposures and SES in China.MethodsWe combined estimated year 2015 annual-average ambient levels of nitrogen dioxide (NO2) and fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] with national demographic information. Pollution estimates were derived from a national empirical model for China at 1-km spatial resolution; demographic estimates were derived from national gridded gross national product (GDP) per capita at 1-km resolution, and (separately) a national representative sample of 21,095 individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2015 cohort. Our use of global data on population density and cohort data on where people live helped avoid the spatial imprecision found in publicly available census data for China. We quantified air pollution disparities among individual's rural-to-urban migration status; SES factors (education, occupation, and income); and minority status. We compared results using three approaches to SES measurement: individual SES score, community-averaged SES score, and gridded GDP per capita.ResultsAmbient NO2 and PM2.5 levels were higher for higher-SES populations than for lower-SES population, higher for long-standing urban residents than for rural-to-urban migrant populations, and higher for the majority ethnic group (Han) than for the average across nine minority groups. For the three SES measurements (individual SES score, community-averaged SES score, gridded GDP per capita), a 1-interquartile range higher SES corresponded to higher concentrations of 6-9 μg/m3 NO2 and 3-6 μg/m3 PM2.5; average concentrations for the highest and lowest 20th percentile of SES differed by 41-89% for NO2 and 12-25% for PM2.5. This pattern held in rural and urban locations, across geographic regions, across a wide range of spatial resolution, and for modeled vs. measured pollution concentrations.ConclusionsMultiple analyses here reveal that in China, ambient NO2 and PM2.5 concentrations are higher for high-SES than for low-SES individuals; these results are robust to multiple sensitivity analyses. Our findings are consistent with the idea that in China's current industrialization and urbanization stage, economic development is correlated with both SES and air pollution. To our knowledge, our study provides the most comprehensive picture to date of ambient air pollution disparities in China; the results differ dramatically from results and from theories to explain conditions in the United States. https://doi.org/10.1289/EHP9872.
| S-EPMC9175641 | 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:Epidemiologic observations suggest that exposure to ambient fine particulate matter (PM2.5) is associated with increased risk of chronic kidney disease (CKD) and diabetes, a causal driver of CKD. We evaluated whether diabetes mediates the association between PM2.5 and CKD. A cohort of 2,444,157 United States veterans were followed over a median 8.5 years. Environmental Protection Agency data provided PM2.5 exposure levels. Regression models assessed associations and their proportion mediated. A 10 µg/m3 increase in PM2.5 was associated with increased odds of having a diabetes diagnosis (odds ratio: 1.18, 95% CI: 1.06-1.32), use of diabetes medication (1.22, 1.07-1.39), and increased risk of incident eGFR <60 ml/min/1.73 m2 (hazard ratio:1.20, 95% CI: 1.13-1.29), incident CKD (1.28, 1.18-1.39), ≥30% decline in eGFR (1.23, 1.15-1.33), and end-stage renal disease (ESRD) or ≥50% decline in eGFR (1.17, 1.05-1.30). Diabetes mediated 4.7% (4.3-5.7%) of the association of PM2.5 with incident eGFR <60 ml/min/1.73 m2, 4.8% (4.2-5.8%) with incident CKD, 5.8% (5.0-7.0%) with ≥30% decline in eGFR, and 17.0% (13.1-20.4%) with ESRD or ≥50% decline in eGFR. Diabetes minimally mediated the association between PM2.5 and kidney outcomes. The findings will help inform more accurate estimates of the burden of diabetes and burden of kidney disease attributable to PM2.5 pollution.
| S-EPMC7067761 | biostudies-literature
Project description:Fine-particulate pollution is a major public health concern in China. Accurate assessment of the population exposed to PM2.5 requires high-resolution pollution and population information. This paper assesses China's potential population exposure to PM2.5, maps its spatiotemporal variability, and simulates the effects of the recent air pollution control policy. We relate satellite-based Aerosol Optical Depth (AOD) retrievals to ground-based PM2.5 observations. We employ block cokriging (BCK) to improve the spatial interpolation of PM2.5 distribution. We use the subdistrict level population data to estimate and map the potential population exposure to PM2.5 pollution in China at the subdistrict level, the smallest administrative unit with public demographic information. During 8 April 2013 and 7 April 2014, China's population-weighted annual average PM2.5 concentration was nearly 7 times the annual average level suggested by the World Health Organization (WHO). About 1322 million people, or 98.6% of the total population, were exposed to PM2.5 at levels above WHO's daily guideline for longer than half a year. If China can achieve its Action Plan on Prevention and Control of Air Pollution targets by 2017, the population exposed to PM2.5 above China's daily standard for longer than half a year will be reduced by 85%.
| S-EPMC6313548 | biostudies-literature