Annual Average Concentration Of PM2 Research Articles

Long- and short-term health benefits attributable to PM2.5 constituents reductions from 2013 to 2021: A spatiotemporal analysis in China

Long- and short-term exposure to constituents of fine particulate matter (PM2.5) substantially affects human health. However, assessments of the health and economic benefits of reducing PM2.5 constituents are scarce. This study estimates the number of premature deaths from all-cause, cardiovascular (CVD), and respiratory diseases avoided due to reductions in daily and annual average concentrations of PM2.5 constituents. The Environmental Benefits Mapping and Analysis Program was used for two scenarios: we used yearly concentrations of PM2.5 constituents from 2013 to 2020 as the baseline concentration surface (Scenario I), and 2021 as the baseline year (Scenario II). With reductions in daily and annual average concentrations of PM2.5 constituents, 309,099 (95 % confidence interval [CI]: 37,265–571,485) and 195,297 (95 % CI: 178,192–211,914) premature deaths were avoided in Scenario I, respectively; meanwhile, 347,296 (95 % CI: 79,258–604,758) and 201,567 (95 % CI: 185,038–217,530) premature deaths were avoided in Scenario II, respectively. Moreover, economic benefits associated with the prevention of premature deaths were estimated using the willingness to pay (WTP) and modified human capital (AHC) methods. The total estimated economic benefits amounted to 563.32 billion RMB (WTP) and 322.03 billion RMB (AHC) in Scenario I. In Scenario II, the associated economic benefits were 751.48 billion RMB (WTP) and 427.56 billion RMB (AHC), accounting for 0.657 and 0.374 % of China's gross domestic product in 2021, respectively. Additionally, we analyzed the sensitivity of CVD-related premature deaths to the concentrations of PM2.5 constituents, and found that CVD-related premature deaths were more sensitive to black carbon.

Ambient air pollution exposure, plasma metabolomic markers, and risk of type 2 diabetes: A prospective cohort study

BackgroundBoth air pollution (AP) and impaired lipid metabolism contribute to type 2 diabetes (T2D). However, little is known about the detailed associations of AP to lipidomic markers and the specific lipid metabolomic profile that mediates the impact of AP on incident T2D. We aimed to examine the associations between long-term AP exposure, plasma metabolomic markers, and incident T2D, and subsequently determine the lipid metabolomic profile that mediates the relationship between AP and T2D. MethodsThis prospective study included 82,548 participants from the UK Biobank without a history of T2D at baseline. Baseline plasma samples were analyzed using the nuclear magnetic resonance (NMR) metabolomic platform, which measured 168 metabolomic markers, including lipids, lipoprotein subclasses, and other circulating metabolites. Land Use Regression models were utilized to estimate annual average concentrations of PM2.5 and NO2. The associations among AP, metabolomic markers, and T2D were investigated using multivariable linear regressions and Cox proportional hazards models. Mediation analyses were performed to assess the role of each metabolomic marker in the AP-T2D relationship. Furthermore, principal component (PC) analysis was conducted on 168 metabolomic markers to extract metabolic patterns. These patterns were utilized to determine their associations with AP and T2D, as well as their mediating role in the AP-T2D relationship. ResultsWe found that long-term AP exposure was associated with some lipid metabolites, including ApoA1, HDL concentration, HDL size, and lipid components within HDL, especially in very large, large, and medium HDL, as well as some other lipids, fatty acids, amino acids, glucose, and glycoprotein acetyls. In pairwise mediation analysis, these metabolites exhibited significant mediation effects in the AP-T2D relationship. We identified six PCS representing distinct metabolic patterns. Long-term exposure to PM2.5 and NO2 showed significantly negative associations with PC2 (characterized by high levels of ApoA1, larger HDL, other lipids, and low levels of larger VLDL). PC2 mediated 12.3% and 10.3% of the associations of PM2.5 and NO2 with incident T2D, respectively. ConclusionsThis study revealed the associations of AP with various lipid metabolites. A lipid metabolomic profile characterized by ApoA1 and larger HDL may mediate the association between AP and incident T2D.

Air Pollution and Allergic Rhinitis: Findings from a Prospective Cohort Study.

To investigate the association of long-term exposure to ambient air pollution with the risk of allergic rhinitis (AR), we performed a longitudinal analysis of 379,488 participants (47.4% women) free of AR at baseline in the UK Biobank. The annual average concentrations of PM2.5, PMcoarse, PM10, NO2, and NOx were estimated by land use regression models. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). A weighted polygenic risk score was constructed. During a median follow-up period of 12.5 years, 3095 AR cases were identified. We observed significant associations between the risk of AR and PM2.5 (HR: 1.51, 95% CI: 1.27-1.79, per 5 μg/m3), PMcoarse (HR: 1.28, 95% CI: 1.06-1.55, per 5 μg/m3), PM10 (HR: 1.45, 95% CI: 1.20-1.74, per 10 μg/m3), NO2 (HR: 1.14, 95% CI: 1.09-1.19, per 10 μg/m3), and NOx (HR: 1.10, 95% CI: 1.05-1.15, per 20 μg/m3). Moreover, participants with high air pollution combined with high genetic risk showed the highest risk of AR, although no multiplicative or additive interaction was observed. In conclusion, long-term exposure to air pollutants was associated with an elevated risk of AR, particularly in high-genetic-risk populations, emphasizing the urgent need to improve air quality.

Mediating effect of body fat percentage in the association between ambient particulate matter exposure and hypertension: a subset analysis of China hypertension survey

BackgroundHypertension caused by air pollution exposure is a growing concern in China. The association between air pollutant exposure and hypertension has been found to be potentiated by obesity, however, little is known about the processes mediating this association. This study investigated the association between fine particulate matter (aerodynamic equivalent diameter ≤ 2.5 microns, PM2.5) exposure and the prevalence of hypertension in a representative population in southern China and tested whether obesity mediated this association.MethodsA total of 14,308 adults from 48 communities/villages in southern China were selected from January 2015 to December 2015 using a stratified multistage random sampling method. Hourly PM2.5 measurements were collected from the China National Environmental Monitoring Centre. Restricted cubic splines were used to analyze the nonlinear dose-response relationship between PM2.5 exposure and hypertension risk. The mediating effect mechanism of obesity on PM2.5-associated hypertension was tested in a causal inference framework following the approach proposed by Imai and Keele.ResultsA total of 20.7% (2966/14,308) of participants in the present study were diagnosed with hypertension. Nonlinear exposure-response analysis revealed that exposure to an annual mean PM2.5 concentration above 41.8 µg/m3 was associated with increased hypertension risk at an incremental gradient. 9.1% of the hypertension burden could be attributed to exposure to elevated annual average concentrations of PM2.5. It is noteworthy that an increased body fat percentage positively mediated 59.3% of the association between PM2.5 exposure and hypertension risk, whereas body mass index mediated 34.3% of this association.ConclusionsThis study suggests that a significant portion of the estimated effect of exposure to PM2.5 on the risk of hypertension appears to be attributed to its effect on alterations in body composition and the development of obesity. These findings could inform intersectoral actions in future studies to protect populations with excessive fine particle exposure from developing hypertension.

Job Exposure Matrix, a Solution for Retrospective Assessment of Particle Exposure in a Subway Network and Their Long-Term Effects.

Health effects after long-term exposure to subway particulate matter (PM) remain unknown due to the lack of individual PM exposure data. This study aimed to apply the job exposure matrix (JEM) approach to retrospectively assess occupational exposure to PM in the Parisian subway. Job, the line and sector of the transport network, as well as calendar period were four JEM dimensions. For each combination of these dimensions, we generated statistical models to estimate the annual average PM10 concentration using data from an exhaustive inventory of the PM measurement campaigns conducted between 2004 and 2020 in the Parisian subway and historical data from the Parisian air pollution monitoring network. The resulting JEM and its exposure estimates were critically examined by experts using the uncertainty analysis framework. The resulting JEM allows for the assignment of the estimated annual PM10 concentration to three types of professionals working in the subway: locomotive operators, station agents, and security guards. The estimates' precision and validity depend on the amount and quality of PM10 measurement data used in the job-, line-, and sector-specific models. Models using large amounts of personal exposure measurement data produced rather robust exposure estimates compared to models with lacunary data (i.e., in security guards). The analysis of uncertainty around the exposure estimates allows for the identification of the sources of uncertainty and parameters to be addressed in the future in order to refine and/or improve the JEM. The JEM approach seems relevant for the retrospective exposure assessment of subway workers. When applied to available data on PM10, it allows for the estimation of this exposure in locomotive operators and station agents with an acceptable validity. Conversely, for security guards, the current estimates have insufficient validity to recommend their use in an epidemiological study. Therefore, the current JEM should be considered as a valid prototype, which shall be further improved using more robust measurements for some jobs. This JEM can also be further refined by considering additional exposure determinants.

Ambient PM2.5 and its components associated with 10-year atherosclerotic cardiovascular disease risk in Chinese adults

BackgroundExposure to particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) may increase the risk of 10-year atherosclerotic cardiovascular disease (ASCVD) risk. While PM2.5 is comprised of various components, the evidence on the correlation of its components with 10-year ASCVD risk and which component contributes most remains limited. MethodsData were derived from the baseline assessments of China Multi-Ethnic Cohort (CMEC). In total, 69,722 individuals aged 35–74 years were included into this study. The annual average concentration of PM2.5 and its components (black carbon, ammonium, nitrate, sulfate, organic matter, soil particles, and sea salt) were estimated by satellite remote sensing and chemical transport models. The ASCVD risk of individuals was calculated by the equations from the China-PAR Project (prediction for ASCVD risk in China). The relationship between single exposure to PM2.5 and its components and predicted 10-year ASCVD risk was assessed using the logistic regression model. The effect of joint exposure was estimated, and the most significant contributor was identified using the weighted quantile sum approach. ResultsTotally 69,722 participants were included, of which 95.8 % and 4.2 % had low and high 10-year ASCVD risk, respectively. Per standard deviation increases in the 3-year average concentration of PM2.5 mass (odds ratio [OR] 1.23, 95 % confidence interval [CI]: 1.12–1.35), black carbon (1.21, 1.11–1.33), ammonium (1.21, 1.10–1.32), nitrate (1.25, 1.14–1.38), organic matter (1.29, 1.18–1.42), sulfate (1.17, 1.07–1.28), and soil particles (1.15, 1.04–1.26) were related to high 10-year ASCVD risk. The overall effect (1.19, 1.11–1.28) of the PM2.5 components was positively associated with 10-year ASCVD risk, and organic matter had the most contribution to this relationship. Female participants were more significantly impacted by PM2.5, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles compared to others. ConclusionLong-term exposure to PM2.5 mass, black carbon, ammonium, nitrate, organic matter, sulfate, and soil particles were positively associated with high 10-year ASCVD risk, while sea salt exhibited a protective effect. Moreover, the organic matter might take primary responsibility for the relationship between PM2.5 and 10-year ASCVD risk. Females were more susceptible to the adverse effect.

Analysis of PM2.5 Synergistic Governance Path from a Socio-Economic Perspective: A Case Study of Guangdong Province

Analyzing the influencing factors of PM2.5 concentration, scenario simulations, and countermeasure research to address the problem of PM2.5 pollution in Guangdong Province is of great significance for governments at all levels for formulating relevant policies. In this study, the ChinaHighPM2.5 dataset and economic and social statistics for Guangdong Province from 2010 to 2019 were selected, and a PM2.5 pollution management compliance path formulation method based on the multi-scenario simulation was proposed by combining the differences in city types and PM2.5 concentration prediction. Based on the prediction model of PM2.5 concentration constructed by the Ridge and SVM models and facing the PM2.5 pollution control target in 2025, the urban PM2.5 pollution control scenario considering the characteristics of urban development was constructed. According to the scenario simulation results of the PM2.5 prediction model, the PM2.5 pollution control path suitable for Guangdong Province during the 14th Five-Year Plan period was explored. The coupling coordination model was used to explore the spatial and temporal pattern evolution of PM2.5 pollution collaborative governance in various prefecture-level cities under the standard path, and the policy recommendations for PM2.5 pollution control during the 14th Five-Year Plan period are proposed. The results showed the following: ① in the case of small samples, the model can provide effective simulation predictions for the study of urban pollutant management compliance pathways. ② Under the scenario of PM2.5 management meeting the standard, in 2025, the annual average mass concentration of PM2.5 in all prefecture-level cities in Guangdong Province will be lower than 22 μg/m3, and the annual average concentration of PM2.5 in the whole province will drop from 25.91 μg/m3 to 21.04 μg/m3, which will fulfil the goal of reducing the annual average concentration of PM2.5 in the whole province to below 22 μg/m3, as set out in the 14th Five-Year Plan for the Ecological Environmental Protection of Guangdong Province. ③ Under the path of PM2.5 control and attainment, the regional coordination relationship among prefecture-level cities in Guangdong Province is gradually optimized, the number of intermediate-level coordinated cities will increase, and the overall spatial distribution pattern will be low in the middle and high in the surrounding area. Based on the characteristics of the four city types, it is recommended that a staggered development strategy be implemented to achieve synergy between economic development and environmental quality. Urban type I should focus on restructuring freight transportation to reduce urban pollutant emissions. City type II should focus on urban transportation and greening. For city type III, the focus should be on optimizing the industrial structure, adjusting the freight structure, and increasing the greening rate of the city. For city type IV, industrial upgrading, energy efficiency, freight structure, and management of industrial pollutant emissions should be strengthened.

Spatiotemporal characteristics and driving mechanisms of PM10 in arid and semi-arid cities of northwest China

PM10 pollution is a pressing ecological concern within arid and semi-arid cities, adversely influencing the natural environment and human health. Based on the Geographically and Temporally Weighted Regression (GTWR) model, this study comparatively investigated the spatiotemporal dynamics of PM10 during non-dust and dust periods in five arid cities (Jiuquan, Jiayuguan, Zhangye, Jinchang, and Wuwei) and one semi-arid city (Lanzhou) in northwest China. Further, this study examined the critical mechanisms of PM10 via the GTWR and Geographic Detector model. A comparative analysis illustrated that dust period PM10 concentrations surpassed non-dust period concentrations. The annual average PM10 concentrations during the non-dust period wavily declined from 2015 to 2020, exhibiting significantly higher levels in the semi-arid city as opposed to arid cities. Conversely, during the dust period, PM10 levels rose initially between 2015 and 2017 and diminished from 2018 to 2020, with high concentration clusterings primarily observed in 2015–2016 in western arid cities, Jiuquan and Jiayuguan, in 2017–2019 in eastern cities, Wuwei and Lanzhou, and in 2020 in central arid cities, Jinchang and Zhangye. During the non-dust period from 2015 to 2020, the cumulative effects of single driving factors were ranked in the following order: soil moisture content (MOI), geographical location (LOC), precipitation (PRE), SO2, gross domestic product (GDP), wind speed (WS), and digital elevation (DEM) while during the dust period, the emphasized factors were ranked in the following order: MOI, LOC, PRE, WS, SO2, GDP, and DEM. The interaction between MOI and WS on PM10 was most noticeable in this study (non-dust: 0.787, dust: 0.832). Thus, MOI and WS are critical components in controlling PM10 pollution. The outcomes of this study can furnish theoretical foundations for ecological construction in Northwest China, unlock novel insights for ecological measures in other global arid and semi-arid cities.

Ambient PM2.5 Components Are Associated With Bone Strength: Evidence From a China Multi-Ethnic Study.

The relationship between the components of particulate matter with an aerodynamic diameter of 2.5 or less (PM2.5) and bone strength remains unclear. Based on a large-scale epidemiologic survey, we investigated the individual and combined associations of PM2.5 and its components with bone strength. A total of 65 906 individuals aged 30 to 79 years were derived from the China Multi-Ethnic Cohort Annual average concentrations of PM2.5 and its components were estimated using satellite remote sensing and chemical transport models. Bone strength was expressed by the calcaneus quantitative ultrasound index (QUI) measured by quantitative ultrasound. The logistic regression model and weighted quantile sum method were used to estimate the associations of single and joint exposure to PM2.5 and its components with QUI, respectively. Our analysis shows that per-SD increase (μg/m3) in 3-year average concentrations of PM2.5 (mean difference [MD] -7.38; 95% CI, -8.35 to -6.41), black carbon (-7.91; -8.90 to -6.92), ammonium (-8.35; -9.37 to -7.34), nitrate (-8.73; -9.80 to -7.66), organic matter (-4.70; -5.77 to -3.64), and soil particles (-5.12; -6.10 to -4.15) were negatively associated with QUI. In addition, these associations were more pronounced in men, and people older than 65 years with a history of smoking and chronic alcohol consumption. We found that long-term exposure to PM2.5 and its components may lead to reduced bone strength, suggesting that PM2.5 and its components may potentially increase the risk of osteoporosis and even fracture. Nitrate may be responsible for increasing its risk to a greater extent.

Chemical Characterization and Source Apportionment of PM10 Using Receptor Models over the Himalayan Region of India

This study presents the source apportionment of coarse-mode particulate matter (PM10) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), water-soluble organic carbon (WSOC), carbon fractions (organic carbon (OC) and elemental carbon (EC)), and trace elements of PM10 were analyzed over the IHR. Nainital (62 ± 39 µg m−3) had the highest annual average mass concentration of PM10 (average ± standard deviation at 1 σ), followed by Mohal Kullu (58 ± 32 µg m−3) and Darjeeling (54 ± 18 µg m−3). The annual total ∑WSIIS concentration order was as follows: Darjeeling (14.02 ± 10.01 µg m−3) > Mohal-Kullu (13.75 ± 10.21 µg m−3) > Nainital (10.20 ± 6.30 µg m−3), contributing to 15–30% of the PM10 mass. The dominant secondary ions (NH4+, SO42−, and NO3−) suggest that the study sites were strongly influenced by anthropogenic sources from regional and long-range transport. Principal component analysis (PCA) with an absolute principal component score (APCS), UNMIX, and Positive Matrix Factorization (PMF) were used for source identification of PM10 at the study sites of the IHR. All three models showed relatively similar results of source profiles for all study sites except their source number and percentage contribution. Overall, soil dust (SD), secondary aerosols (SAs), combustion (biomass burning (BB) + fossil fuel combustion (FFC): BB+FFC), and vehicular emissions (VEs) are the major sources of PM10 identified by these models at all study sites. Air mass backward trajectories illustrated that PM10, mainly attributed to dust-related aerosols, was transported from the Thar Desert, Indo-Gangetic Plain (IGP), and northwestern region of India (i.e., Punjab and Haryana) and Afghanistan to the IHR. Transported agricultural or residual burning plumes from the IGP and nearby areas significantly contribute to the concentration of carbonaceous aerosols (CAs) at study sites.

Pollution characteristics and human health risks of PM2.5-bound heavy metals: a 3-year observation in Suzhou, China.

This study aimed to analyze the temporal trends, pollution levels, and health risks associated with eleven PM2.5-bound heavy metals (Sb, Al, As, Hg, Cd, Cr, Mn, Ni, Pb, Se and Tl). A total of 504 PM2.5 samples were collected in Suzhou from January 2019 to December 2021. The pollution levels were estimated based on enrichment factors (EFs) which can be used to calculate the enrichment of heavy metals in PM2.5 and determine whether the concentrations of PM2.5-bound heavy metals are influenced by the crustal or anthropogenic sources, and the health risk of PM2.5-bound heavy metals via inhalation was assessed following US EPA's Risk Assessment Guidance for Superfund (RAGS). The annual average concentration of PM2.5 was 46.76μgm-3, which was higher than the WHO recommended limit of 5μgm-3. The average of the sum of eleven PM2.5-bound heavy metals was 180.61ngm-3, dominated by Al, Mn, and Pb. The concentration of PM2.5 in 2020 was significantly lower than that in 2019 and 2021. The PM2.5 and PM2.5-bound heavy metal concentrations in winter and spring were significantly higher than those in autumn and summer. The EF of As, Cr, Cd, Hg, Ni, Pb, Sb, Mn, Se, and Tl was higher than 10, indicating they were mainly from anthropogenic sources. Exposure to a single non-carcinogenic heavy metal via inhalation was unlikely to cause non-carcinogenic effects (HQ < 1), but the integrated non-carcinogenic risks should be taken seriously (HI > 1). The cumulative carcinogenic risks from the carcinogenic elements were exceeding the lower limit (1 × 10-6) of the acceptable risk range. The carcinogenic risks of As and Cr(VI) contributed 60.98% and 26.77%, respectively, which were regarded as two key carcinogenic risk factors. Overall, the government policies and countermeasures for the PM2.5 pollution control should be performed not only based on the PM2.5 concentration but also based on the PM2.5-bound heavy metals and their health risks for the local residents.

Evaluation of Changes in PM2.5 Exposure Concentration and Health Risk for Urban Resident in Zhengzhou Based on High Spatial Resolution Grids

In recent years, complex air pollution with the characteristic pollutant of PM2.5 has remained serious in China. Long term exposure to PM2.5 might harm residential health and can increase premature death from specific diseases. The annual average concentration of PM2.5 in Zhengzhou was much higher than the national secondary standard, which has an extremely negative impact on the health of residents. Based on the high spatial resolution grids of population density established through web-crawling and outdoor monitoring concentrations and urban residential emissions used to evaluate PM2.5 exposure concentration, the exposure concentration of PM2.5 for urban residents of Zhengzhou was assessed, considering both indoor and outdoor exposures. Relevant health risks were quantified with the integrated exposure-response model. Finally, the contributions of various reducing measures and different standards of air quality to the decreases in PM2.5 exposure concentration were analyzed. The results showed that in 2017 and 2019, the time weighted exposure concentrations of PM2.5 for Zhengzhou's urban residents were 74.06 μg·m-3 and 60.64 μg·m-3, respectively, which was decreased by 18.12%. In addition, the mass fractions of the indoor exposure concentrations in the time weighted exposure concentrations were 83.58% and 83.01%, and its contribution to the drop of the time weighted exposure concentrations was 84.06%. In 2017 and 2019, the numbers of premature deaths attributed to PM2.5 exposures for urban residents of Zhengzhou over the age of 25 were 13285 and 10323, respectively, showing a 22.30% decrease. By using these comprehensive measures, PM2.5 exposure concentration for Zhengzhou's urban residents could be reduced by 86.23% at most, and 8902 premature deaths could be avoided.

Mortality and morbidity due to exposure to ambient air PM10 in Zahedan city, Iran: The AirQ model approach

Eastern cities of Iran, including Zahedan have been experiencing a dust storm phenomenon, causing air quality to worsen every year. The purpose of this study was to evaluate the health impact of PM10 on the inhabitants of Zahedan using AirQ2.2.3 model software. The findings of this study revealed that the annual average and maximum concentrations of PM10 were 110 and 1447 μg/m3 in 2018, which were 7.3 and 32.2 times higher than the World Health Organization (WHO) guidelines, respectively. By increasing every 10 μg/m3, the relative risk (RR) rate of PM10 on cardiovascular and respiratory morbidity were 8.03% and 7.2% (95% CI), with a total number of excess cases of 210 and 544 people, respectively. Accordingly, the attributable proportion of total mortality from cardiovascular and respiratory diseases were 8.03% and 11.2% (95% CI), attributed to the total number of excess cases of 111 and 33 people, respectively. The findings of this study revealed that PM10 has a health impact on Zahedan citizens, according to the predicted results using AirQ model. Thus, the development of management strategies at the local and regional levels to reduce PM10 is required to improve the air quality in this city.

Potential causal links between long-term ambient particulate matter exposure and cardiovascular mortality: New evidence from a large community-based cohort in South China

BackgroundCardiovascular disease (CVD) mortality is associated with long-term particulate matter (PM) exposure. However, evidence from large, highly-exposed population cohort and observational-data-based causal inference approaches remains limited. AimsWe examined the potential causal links between PM exposure and the CVD mortality in South China. Methods580,757 participants were recruited during 2009–2015 and followed up through 2020. Satellite-based annual concentrations of PM2.5, PM10, and PMcoarse (i.e., PM10 - PM2.5) at 1 km2 spatial resolution were estimated and assigned to each participant. Marginal structural Cox models with time-varying covariates, adjusted using inverse probability weighting, were developed to evaluate the association between prolonged PM exposure and CVD mortality. ResultsFor overall CVD mortality, the hazard ratios and 95% confidence interval for each 1 μg/m3 increase in the annual average concentration of PM2.5, PM10, and PMcoarse were 1.033 (1.028–1.037), 1.028 (1.024–1.032), and 1.022 (1.012–1.033), respectively. All three PMs were linked to a higher mortality risk for myocardial infarction and ischemic heart disease (IHD). The mortality risk of chronic IHD and hypertension was linked to PM2.5 and PM10. Significant association between PMcoarse and other heart disease mortality was also observed. The older, women, less-educated participants, or inactive participants exhibited particularly higher susceptibility. Participants who were generally exposed to PM10 concentrations below 70 μg/m3 were more vulnerable to PM2.5-, PM10- and PMcoarse-CVD mortality risks. ConclusionThis large cohort study provides evidence for the potential causal links between increased CVD mortality and ambient PM exposure, as well as socio-demographics linked to the highest vulnerability.

Change in Air Quality during 2014-2021 in Jinan City in China and Its Influencing Factors.

Air pollution affects climate change, food production, traffic safety, and human health. In this paper, we analyze the changes in air quality index (AQI) and concentrations of six air pollutants in Jinan during 2014-2021. The results indicate that the annual average concentrations of PM10, PM2.5, NO2, SO2, CO, and O3 and AQI values all declined year after year during 2014-2021. Compared with 2014, AQI in Jinan City fell by 27.3% in 2021. Air quality in the four seasons of 2021 was obviously better than that in 2014. PM2.5 concentration was the highest in winter and PM2.5 concentration was the lowest in summer, while it was the opposite for O3 concentration. AQI in Jinan during the COVID epoch in 2020 was remarkably lower compared with that during the same epoch in 2021. Nevertheless, air quality during the post-COVID epoch in 2020 conspicuously deteriorated compared with that in 2021. Socioeconomic elements were the main reasons for the changes in air quality. AQI in Jinan was majorly influenced by energy consumption per 10,000-yuan GDP (ECPGDP), SO2 emissions (SDE), NOx emissions (NOE), particulate emissions (PE), PM2.5, and PM10. Clean policies in Jinan City played a key role in improving air quality. Unfavorable meteorological conditions led to heavy pollution weather in the winter. These results could provide a scientific reference for the control of air pollution in Jinan City.

Genetic susceptibility and lifestyle modify the association of long-term air pollution exposure on major depressive disorder: a prospective study in UK Biobank

BackgroundEvidence linking air pollution to major depressive disorder (MDD) remains sparse and results are heterogeneous. In addition, the evidence about the interaction and joint associations of genetic risk and lifestyle with air pollution on incident MDD risk remains unclear. We aimed to examine the association of various air pollutants with the risk of incident MDD and assessed whether genetic susceptibility and lifestyle influence the associations.MethodsThis population-based prospective cohort study analyzed data collected between March 2006 and October 2010 from 354,897 participants aged 37 to 73 years from the UK Biobank. Annual average concentrations of PM2.5, PM10, NO2, and NOx were estimated using a Land Use Regression model. A lifestyle score was determined based on a combination of smoking, alcohol drinking, physical activity, television viewing time, sleep duration, and diet. A polygenic risk score (PRS) was defined using 17 MDD-associated genetic loci.ResultsDuring a median follow-up of 9.7 years (3,427,084 person-years), 14,710 incident MDD events were ascertained. PM2.5 (HR: 1.16, 95% CI: 1.07–1.26; per 5 μg/m3) and NOx (HR: 1.02, 95% CI: 1.01–1.05; per 20 μg/m3) were associated with increased risk of MDD. There was a significant interaction between the genetic susceptibility and air pollution for MDD (P-interaction < 0.05). Compared with participants with low genetic risk and low air pollution, those with high genetic risk and high PM2.5 exposure had the highest risk of incident MDD (PM2.5: HR: 1.34, 95% CI: 1.23–1.46). We also observed an interaction between PM2.5 exposure and unhealthy lifestyle (P-interaction < 0.05). Participants with the least healthy lifestyle and high air pollution exposures had the highest MDD risk when compared to those with the most healthy lifestyle and low air pollution (PM2.5: HR: 2.22, 95% CI: 1.92–2.58; PM10: HR: 2.09, 95% CI: 1.78–2.45; NO2: HR: 2.11, 95% CI: 1.82–2.46; NOx: HR: 2.28, 95% CI: 1.97–2.64).ConclusionsLong-term exposure to air pollution is associated with MDD risk. Identifying individuals with high genetic risk and developing healthy lifestyle for reducing the harm of air pollution to public mental health.

Fine Particulate Matter Concentration and Early Deaths Related to Thermal Power Plants and National Industrial Complexes in South Korea

Thermal power plants (TPPs) and national industrial complexes (NICs) are widely known as being among the major causes of changes in the concentrations of fine particulate matter (PM2.5). However, little is known about the changes in PM2.5 concentration caused by the operation of these facilities in South Korea and the health burden attributable to them, including early death. There were two purposes to this study. The first was to quantitatively evaluate the changes in PM2.5 concentration caused by TPPs and NICs in Korea. The second was to estimate the number of early deaths as a health burden attributable to such changes in PM2.5 concentration. The changes in PM2.5 concentration caused by the operation of TPPs and NICs were investigated within TPPs in 2013 and within NICs in 2015. The number of early deaths in 2015 caused by changes in PM2.5 concentration was estimated using the Environmental Benefits Mapping and Analysis Program (BenMAP). Nationwide, the annual average concentration of PM2.5 caused by the operation of TPPs and NICs was estimated to increase by 0.611 μg/m3 and 1.245 μg/m3, respectively, suggesting that NICs contributed about twice as much to this concentration as TPPs. The same trend was also observed regarding the number of early deaths, with TPPs and NICs accounting for 1017 and 2091 early deaths per year, respectively, indicating that the operation of NICs causes a health burden about twice as high as that caused by TPPs. However, the changes in PM2.5 concentration were found to be high near TPPs and NICs, while the health burden caused by exposure to PM2.5 varied according to the level of population distribution and mortality in each air (quality) control zone (ACZ) to which one is exposed. The findings of this study are expected to be utilized as reference data when setting goals to strengthen air quality management (AQM) in each ACZ in Korea.

Assessment of health and economic benefits of reducing fine particulate matter (PM2.5) concentration in Ho Chi Minh City, Vietnam

Ambient fine particulate matter (PM2.5) is a growing issue in Ho Chi Minh City (HCMC), the most populous province in Viet Nam. Estimating the benefits of reducing PM2.5 levels has still been sparse in HCMC.The study used the Environmental Benefits Mapping and Analysis Program – Community Edition (BenMAP-CE) to estimate the health, and economic benefits in three controlling scenarios of annual average PM2.5 concentration in 2019 (28.9 µg/m3) rolling back to the World Health Organization's annual average Air Quality Guideline values of 5 µg/m3 (guideline value in 2021), and 10 µg/m3 (guideline value in 2005 which becomes Interim Target 4 of 2021 WHO Air Quality Guideline), and the Vietnamese annual average standard of 25 µg/m3.The annual average concentration of PM2.5 in 2019 was 28.9 µg/m3. Applying BenMAP-CE, the pooled number of avoided deaths of all causes was 3,785 (1,179–6,335), 3,195 (982–5,468), and 1,300 (384–2,386) for three scenarios, respectively. The economic benefits were $ 2.4 (0.8–4.1), $ 2.1 (0.6–3.5), and $ 0.8 (0.2–1.5) billion, using the Value of Statistical Life (VSL) of OECD (the Organization for Economic Cooperation and Development) and $ 3.7 (1.2–6.2), $ 3.1 (1.0–5.4) and $ 1.3 (0.4–2.3) billion, using the VSL of USEPA (the United States Environmental Protection Agency).The annual average PM2.5 concentration in HCMC exceeded the Vietnamese standard and WHO guidelines. Controlling PM2.5 showed massive benefits for health and the economy; thus, the city should have action plans for mitigating the PM2.5 pollution.

Fine particulate matter and its chemical constituents' levels: A troubling environmental and human health situation in Karachi, Pakistan

Like many urban centers in developing countries, the effect of air pollution in Karachi is understudied. The goal of this study was to determine the chemical characterization, temporal and seasonal variability, sources, and health impacts of fine particulate matter (PM2.5) in Karachi, Pakistan. Daily samples of PM2.5 were collected using a low-volume air sampler at two different sites (Makro and Karachi University) over the four seasons between October 2009 and August 2010. Samples were analyzed for black carbon (BC), trace metals, and water-soluble ions. Results showed that the annual average concentrations of PM2.5 at Makro and Karachi University were 114 ± 115 and 71.7 ± 56.4 μg m−3, respectively, about 22.8 and 14.3-fold higher than the World Health Organization annual guideline of 5 μg m−3. BC concentrations were 3.39 ± 1.97 and 2.70 ± 2.06 μg m−3, respectively. The concentrations of PM2.5, BC, trace metals, and ions at the two sites showed clear seasonal trends, with higher concentrations in winter and lower concentrations in summer. The trace metals and ionic species with the highest concentrations were Pb, S, Zn, Ca, Si, Cl, Fe, and SO42−. The air quality index in the fall and winter at both sites was about 68 %, which is “unhealthy” for the general population. Positive Matrix Factorization revealed the overall contribution to PM2.5 at the Makro site came from three major sources – industrial emissions (13.3 %), vehicular emissions (59.1 %), and oil combustion (23.3 %). The estimates of expected number of deaths due to short-term exposure to PM2.5 were high in the fall and winter at both sites, with an annual mean estimate of 3592 expected number of deaths at the Makro site. Attention should be paid to the reduction of inorganic pollutants from industrial facilities, vehicular traffic, and fossil fuel combustion, due to their extremely high contribution to PM2.5 mass and health risks.

Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter as Affected by Relevant Policies.

With the increase in global environmental pollution, it is important to understand the concentration characteristics and correlations with other pollutants of atmospheric particulate matter as affected by relevant policies. The data presented in this paper were obtained at monitoring stations in Xi'an, China, in the years from 2016 to 2020, and the spatial distribution characteristics of the mass and quantity concentrations of particulate matter in the atmosphere, as well as its correlation with other pollutants, were analyzed in depth. The results showed that the annual average concentrations of PM10 and PM2.5 decreased year by year from 2016 to 2020. The annual concentrations of PM2.5 decreased by 20.3 μg/m3, and the annual concentrations of PM10 decreased by 47.3 μg/m3. The days with concentrations of PM10 exceeding the standards decreased by 82 days, with a decrease of 66.7%. The days with concentrations of PM2.5 exceeding the standards decreased by 40 days, with a decrease of 35.4%. The concentration values of PM10 and PM2.5 were roughly consistent with the monthly and daily trends. The change in monthly concentrations was U-shaped, and the change in daily concentrations showed a double-peak behavior. The highest concentrations of particulate matter appeared at about 8:00~9:00 am and 11:00 pm, and they were greatly affected by human activity. The proportion of particles of 0~1.0 μm decreased by 1.94%, and the proportion of particles of 0~2.5 μm decreased by 2.00% from 2016 to 2020. A multivariate linear regression model to calculate the concentrations of the pollutants was established. This study provides a reference for the comprehensive analysis and control of air pollutants in Xi'an and even worldwide.