Satellite-based short- and long-term exposure to PM2.5 and adult mortality in urban Beijing, China

Short-term associations between fine particulate air pollution and cardiovascular and respiratory mortality in 337 cities in Latin America

Ambient air pollution is a health concern in Latin America given its large urban population exposed to levels above recommended guidelines. Yet no studies have examined the mortality impact of air pollutants in the region across a wide range of cities. We assessed whether short-term levels of fine particulate matter (PM2.5) from modeled estimates, are associated with cardiovascular and respiratory mortality among adults in 337 cities from 9 Latin American countries. We compiled mortality, PM2.5 and temperature data for the period 2009-2015. For each city, we evaluated the association between monthly changes in PM2.5 and cardiovascular and respiratory mortality for sex and age subgroups using Poisson models, adjusted for seasonality, long-term trend, and temperature. To accommodate possibly different associations of mortality with PM2.5 by age, we included interaction terms between changes in PM2.5 and age in the models. We combined the city-specific estimates using a random effects meta-regression to obtain mortality relative risks for each sex and age group. We analyzed 3,026,861 and 1,222,623 cardiovascular and respiratory deaths, respectively, from a study population that represents 41 % of the total population of Latin America. We observed that a 10 μg/m3 increase in monthly PM2.5 is associated with an increase of 1.3 % (95 % confidence interval [CI], 0.4 to 2.2) in cardiovascular mortality and a 0.9 % increase (95 % CI -0.6 to 2.4) in respiratory mortality. Increases in mortality risk ranged between -0.5 % to 3.0 % across 6 sex-age groups, were larger in men, and demonstrated stronger associations with cardiovascular mortality as age increased. Socioeconomic, environmental and health contexts in Latin America are different than those present in higher income cities from which most evidence on air pollution impacts is drawn. Locally generated evidence constitutes a powerful instrument to engage civil society and help drive actions to mitigate and control ambient air pollution.

Effects of long-term exposure to ambient fine particulate air pollution on all-cause mortality in Taiwan

According to the US Environmental Protection Agency's Integrated Science Assessment (ISA), there is a causal relationship between fine particulate matter (PM2.5) exposure and increased mortality rates. A similar association was also reported by the International Agency for Research on Cancer (IARC). While many studies are available on this relationship between PM exposure and elevated mortality frequency in Europe and North America, there are limited investigations in Asia. Thus, the aim of this study was to perform an ecological investigation to determine the relationship between exposure to ambient PM2.5 levels and all-cause mortality in 66 in Taiwan municipalities. To undertake this investigation, annual PM2.5 levels and age-standardized all-cause mortality rates were calculated for male and female residents of these areas from 2010 to 2020. Weighted-multiple regression analyses were used to obtain adjusted risk ratio (RR) controlling for possible confounding by urbanization level, physician density, and annual mean household income. Annual PM2.5 levels of each municipality were divided into tertiles. Data demonstrated that men residing in areas with intermediate tertile PM2.5 levels (21.06 to 27.29 µg/m3) and the highest tertiles levels (27.30-33.11 µg/m3) exhibited adjusted RRs of 1.06 (95% CI = 1.03-1.08) and 1.13 (95% CI = 1.10-1.16), respectively. Women in these locations displayed a similar risk, 1.03 (0.99-1.06) and 1.07 (1.04-1.11), respectively. These findings indicate that ambient exposure to PM2.5 increased risk for all-cause mortality rates in both men and women in Taiwan during this time period.

Fine Particulate Matter Perturbs the Pulmonary Microbiota in Broiler Chickens

(1) Fine particulate matter (PM2.5) seriously affects the respiratory tract health of both animals and humans. Growing evidence indicates that the pulmonary microbiota is involved in the development of respiratory tract health; however, there is still much that is unknown about the specific changes of pulmonary microbiota caused by PM2.5 in broilers. (2) In this experiment, a total of 48 broilers were randomly divided into a control group and PM-exposure group. The experiment lasted for 21 days. Microbiota, inflammation biomarkers, and histological markers in the lungs were determined. (3) On the last day of the experiment, PM significantly disrupted the structure of lung tissue and induced chronic pulmonary inflammation by increasing IL-6, TNFα, and IFNγ expression and decreasing IL-10 expression. PM exposure significantly altered the α and β diversity of pulmonary microbiota. At the phylum level, PM exposure significantly decreased the Firmicutes abundance and increased the abundance of Actinobacteria and Proteobacteria. At the genus level, PM exposure significantly increased the abundance of Rhodococcus, Achromobacter, Pseudomonas, and Ochrobactrum. We also observed positive associations of the above altered genera with lung TNFα and IFNγ expression. (4) The results suggest that PM perturbs the pulmonary microbiota and induces chronic inflammation, and the pulmonary microbiota possibly contributes to the development of lung inflammation.

Long-Term Exposure to PM2.5 and Mortality: A Cohort Study in China

We investigated the association of long-term exposure to atmospheric PM2.5 with non-accidental and cause-specific mortality in Yinzhou, China. From July 2015 to January 2018, a total of 29,564 individuals aged ≥ 40 years in Yinzhou were recruited for a prospective cohort study. We used the Cox proportional-hazards model to analyze the relationship of the 2-year average concentration of PM2.5 prior to the baseline with non-accidental and cause-specific mortality. The median PM2.5 concentration was 36.51 μg/m3 (range: 25.57-45.40 μg/m3). In model 4, the hazard ratios per 10 μg/m3 increment in PM2.5 were 1.25 (95%CI: 1.04-1.50) for non-accidental mortality and 1.38 (95%CI:1.02-1.86) for cardiovascular disease mortality. We observed no associations between PM2.5 and deaths from respiratory disease or cancer. In the subgroup analysis, interactions were observed between PM2.5 and age, as well as preventive measures on hazy days. The observed association between long-term exposure to atmospheric PM2.5 at a relatively moderate concentration and the risk of non-accidental and cardiovascular disease mortality among middle-aged and elderly Chinese adults could provide evidence for government decision-makers to revise environmental policies towards a more stringent standard.

Fine particulate matter and cardiorespiratory health in China: A systematic review and meta-analysis of epidemiological studies

This review aimed to systematically summarize the epidemiological literature on the cardiorespiratory effects of PM_2.5 published during the 13^th Five-Year Plan period (2016-2020) in China. Original articles published between January 1, 2016 and June 30, 2021 were searched in PubMed, Web of Science, the China National Knowledge Internet Database and Wanfang Database. Random- or fixed-effects models were used to pool effect estimates where appropriate. Of 8558 records identified, 145 met the full eligibility criteria. A 10 µg/m³ increase in short-term PM_2.5 exposure was significantly associated with increases of 0.70%, 0.86%, 0.38% and 0.96% in cardiovascular mortality, respiratory mortality, cardiovascular morbidity, and respiratory morbidity, respectively. The specific diseases with significant associations included stroke, ischemic heart disease, heart failure, arrhythmia, chronic obstructive pulmonary disease, pneumonia and allergic rhinitis. The pooled estimates per 10 µg/m³ increase in long-term PM_2.5 exposure were 15.1%, 11.9% and 21.0% increases in cardiovascular, stroke and lung cancer mortality, and 17.4%, 11.0% and 4.88% increases in cardiovascular, hypertension and lung cancer incidence respectively. Adverse changes in blood pressure, heart rate variability, systemic inflammation, blood lipids, lung function and airway inflammation were observed for either short-term or long-term PM_2.5 exposure, or both. Collectively, we summarized representative exposure-response relationships between short- and long-term PM_2.5 exposure and a wide range of cardiorespiratory outcomes applicable to China. The magnitudes of estimates were generally smaller in short-term associations and comparable in long-term associations compared with those in developed countries. Our findings are helpful for future standard revisions and policy formulation. There are still some notable gaps that merit further investigation in China.

Classification of air quality zones and fine particulate matter sensitive areas by risk assessment approach

Many studies have shown that fine particulate matter can cause health problems. Thus, effectively controlling fine particulate matter concentration is an important issue around the world. The Taiwan Environmental Protection Administration (TWEPA) divides Taiwan into seven air quality zones based on counties and cities for managing air quality and analyzing pollution transmission. However, this artificial division by administrative areas relatively poorly match natural conditions and topographical and geographic factors and hence poorly represent air quality characteristics. This study proposes an air quality sensitive map analysis framework, which uses hierarchical agglomerative clustering with empirical orthogonal function and analysis of variance methods, to provide more detailed, reasonable, and township-level air quality zones incorporating the different spatial-temporal characteristics over the region. The risk concept is introduced to evaluate PM_2.5 risk sensitivity for each administrative district, combining three aspects: hazard (PM_2.5 exceedance probability), exposure (population density of sensitive groups), and vulnerability (average wind speed). Considering air quality spatial-temporal characteristics, Taiwan can be optimally divided into 14 air quality zones. PM_2.5 risk is highest for western inland towns than western coastal towns, with eastern regions exhibiting least risk. Adopting the proposed air quality zones and clarifying high risk areas allows PM_2.5 causes to be identified for different air quality zones. This allows a targeted control strategy for high risk areas to effectively improve domestic air quality. The proposed model also provides powerful reference for environmental management and environmental impact assessment for future construction and development.

Long-term nonlinear relationship between PM2.5 and ten leading causes of death

Air pollution has become a major concern worldwide. Many epidemiological studies have proved relationships between fine particulate matter (PM_2.5) and various diseases, but most studies only use short-term and models for specific groups to derive relationships with acute diseases. This makes it difficult to understand long-term exposure, nonlinear relationships, and spatial-temporal health risks regarding chronic diseases. Therefore, this study proposed to analyze and map PM_2.5 exceedance probability from long-term spatial-temporal monitoring data using radial basis function estimation. We then constructed and compared multiple linear regression and generalized additive models to investigate linear and nonlinear relationships between long-term average PM_2.5 concentration, PM_2.5 potential probability for exceeding the standard, and standardized mortality for the top ten causes of death in all towns and villages in Taiwan nationally from 2010 to 2017. Linear models indicate that increasing PM_2.5 concentration increased malignant neoplasm, pneumonia, and chronic lower respiratory disease mortalities; chronic liver diseases; and cirrhosis; whereas heart diseases and esophagus cancer mortality decreased. For the nonlinear model results, it can be found that there were also significant nonlinear relationships between PM_2.5 concentration and malignant mortalities for neoplasm, heart disease, diabetes; and trachea, bronchus, lung, liver, intrahepatic bile duct, and esophagus cancer. Thus, long-term exposure to PM_2.5 may be a significant risk factor for multiple acute and chronic diseases. Results from this study can be directly applied worldwide to provide air quality and health management references for governments, and important information on long-term health risks for local residents in the study area.

Gene expression in human umbilical vein endothelial cells exposed to fine particulate matter: RNA sequencing analysis

Exposure to airborne particulate matter (PM2.5) is associated with cardiovascular diseases. In order to investigate the molecular mechanisms of air pollution-induced CVDs toxicity, human umbilical vein endothelial cells (HUVECs) were exposed to PM2.5 collected from January, 2016 winter in Beijing, China. We performed RNA sequencing to elucidate key molecular mechanism of PM 2.5-mediated toxicity in HUVECs. A total of 1753 genes, 864 up-regulated and 889 down-regulated, were observed to be differentially expressed genes (DEGs). Among these, genes involved in metabolic response, oxidative stress, inflammatory response, and vascular dysfunction were significantly differentially expressed (log2 FC > 4). The results were validated by quantitative real-time PCR (qPCR) and Western blot for CYP1B1, HMOX1, IL8, and GJA4. Pathway analysis revealed that DEGs were involved in the biological processes related to metabolism, inflammation, and host defense against environmental insults. This research is providing a further understanding of the mechanisms underlying PM2.5-induced cardiovascular diseases (CVDs).

Tanshinone IIA-regulation of IL-6 antagonizes PM2 .5 -induced proliferation of human bronchial epithelial cells via a STAT3/miR-21 reciprocal loop

Particulate matter 2.5 (PM_2.5 ), a component of atmospheric particulate matter, leads to changes in gene expression and cellular functions. Epidemiological evidence confirms that PM_2.5 has a positive correlation with lung injury. However, the molecular mechanisms involved remain poorly understood, and preventive methods are needed. In the present study, with human bronchial epithelial (HBE) cells in culture, we showed that low concentrations of PM_2.5 resulted in acceleration of the G1/S transition and cell proliferation. Consistent with these effects, expression of the pro-inflammatory factor interleukin-6 (IL-6) was elevated in HBE cells exposed to PM_2.5 . Accordingly, signal transducer and activator of transcription 3 (STAT3) was activated, which down-regulated expression of cyclin D1. In addition, PM_2.5 exposure led to higher levels of miR-21, and there was a reciprocal loop between miR-21 and STAT3. For HBE cells, tanshinone IIA (Tan IIA) reversed the PM_2.5 -induced cell cycle alteration and cell proliferation, and reduced the expression of cytokines (IL-6, STAT3, and miR-21). These results show that, for HBE cells, Tan IIA attenuates the PM_2.5 -induced G1/S alteration and cell proliferation, and indicate that it has potential clinical application for PM_2.5 -induced respiratory injuries.

Projecting Lifetime Health Outcomes and Costs Associated with the Ambient Fine Particulate Matter Exposure among Adult Women in Korea

We sought to estimate the lifetime healthcare costs and outcomes associated with the exposure to the escalated concentration of fine particulate matter (particle size < 2.5 μm, PM2.5) among adult Korean women. We adapted a previously developed Markov model, and a hypothetical cohort composed of Korean women was exposed to either a standard (15 μg/m3) or increased (25 μg/m3) concentration of PM2.5. The time horizon of the analysis was 60 years, and the cycle length was 1 year. The outcomes were presented as direct healthcare costs and quality-adjusted life years (QALYs), and costs were discounted annually at 5%. Deterministic and probabilistic sensitivity analyses were performed. The model estimated that when the exposure concentration was increased by 10 μg/m3, the lifetime healthcare cost increased by USD 9309, which is an 11.3% increase compared to the standard concentration group. Women exposed to a higher concentration of PM2.5 were predicted to live 30.64 QALYs, compared to 32.08 QALYs for women who were exposed to the standard concentration of PM2.5. The tendency of a higher cost and shorter QALYs at increased exposure was consistent across a broad range of sensitivity analyses. The negative impact of PM2.5 was higher on cost than on QALYs and accelerated as the exposure time increased, emphasizing the importance of early intervention.

The prospective effects of long-term exposure to ambient PM2.5 and constituents on mortality in rural East China

Few cohort studies explored the associations of long-term exposure to ambient fine particulate matter with an aerodynamic diameter of 2.5 μm or less (PM2.5) and its chemical constituents with mortality risk in rural China. We conducted a 12-year prospective study of 28,793 adults in rural Deqing, China from 2006 to 2018. Annual mean PM2.5 and its constituents, including black carbon (BC), organic carbon (OC), ammonium (NH4+), nitrate (NO3-), sulfate (SO42-), and soil dust were measured at participants' addresses at enrollment from a satellite-based exposure predicting model. Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% confidence intervals (95%CIs) of long-term exposure to PM2.5 for mortality. A total of 1960 deaths were identified during the follow-up. We found PM2.5, BC, OC, NH4+, NO3-, and SO42- were significantly associated with an increased risk of non-accidental mortality. The HR for non-accidental mortality was 1.17 (95%CI: 1.07, 1.28) for each 10 μg/m3 increase in PM2.5. As for constituents, the strongest association was found for BC (HR = 1.21, 95%CI: 1.11, 1.33), followed by NO3-, NH4+, SO42-, and OC (HR = 1.14-1.17 per interquartile range). A non-linear relationship was found between PM2.5 and non-accidental mortality. Similar associations were found for cardio-cerebrovascular and cancer mortality. Associations were stronger among men and ever smokers. Conclusively, we found long-term exposure to ambient PM2.5 and its chemical constituents (especially BC and NO3-) increased mortality risk. Our results suggested the importance of adopting effective targeted emission control to improve air quality for health protection in rural East China.

Acute associations between air pollution on premature rupture of membranes in Hefei, China

Numerous studies had focused on the association between air pollution and health outcomes in recent years. However, little evidence is available on associations between air pollutants and premature rupture of membranes (PROM). Therefore, we performed time-series analysis to evaluate the association between PROM and air pollution. The daily average concentrations of PM_2.5, SO₂ and NO₂ were 54.58 μg/m³, 13.06 μg/m³ and 46.09 μg/m³, respectively, and daily maximum 8-h average O₃ concentration was 95.67 μg/m³. The strongest effects of SO₂, NO₂ and O₃ were found in lag4, lag06 and lag09, and an increase of 10 μg/m³ in SO₂, NO₂ and O₃ was corresponding to increase in incidence of PROM of 8.74% (95% CI 2.12-15.79%), 3.09% (95% CI 0.64-5.59%) and 1.68% (95% CI 0.28-3.09%), respectively. There were no significant effects of PM_2.5 on PROM. Season-specific analyses found that the effects of PM_2.5, SO₂ and O₃ on PROM were more obvious in cold season, but the statistically significant effect of NO₂ was observed in warm season. We also found the modifying effects by maternal age on PROM, and we found that the effects of SO₂ and NO₂ on PROM were higher among younger mothers (< 35 years) than advanced age mothers (≥ 35 years); however, ≥ 35 years group were more vulnerable to O₃ than < 35 years group. This study indicates that air pollution exposure is an important risk factor for PROM and we wish this study could provide evidence to local government to take rigid approaches to control emissions of air pollutants.

Fine particulate matter-induced lung inflammation is mediated by pyroptosis in mice

BACKGROUND

Exposure to ambient air-borne fine particulate matter (PM_2.5) increases respiratory morbidity and mortality. The mechanisms underlying PM_2.5-induced adverse effects remain unclear. This study aimed to uncover the molecular mechanisms of PM_2.5-induced lung toxicity using a mouse model.

METHODS

Scanning electron microscopy and inductively coupled plasma mass spectrometry were used to examine and analyze PM_2.5 morphology and element compositions, respectively. Twenty four male mice were randomly divided into three groups: control (PBS), PM_2.5 (4.0 mg/kg b.w.), and PM_2.5 + Z-YVAD-FMK. In the latter group, the pan-caspase inhibitor (Z-YVAD-FMK) was intraperitoneally injected into mice at a dose of 12.5 mg/kg body weight prior to intratracheal instillation of PM_2.5 (4.0 mg/kg b.w.) every other day for a total of 3 times (n = 8 in each group). Bronchoalveolar lavage fluids (BALFs) were collected 24 h after the last instillation of PM_2.5. Levels of total proteins (TP), lactate dehydrogenase (LDH), IL-1β and IL-18 were analyzed for biomarkers of cell injury and inflammation. Additionally, histological alterations of lung tissues were assessed by hematoxylin-eosin staining. mRNA and protein expression of Caspase1, NLRP3 and GSDMD were examined by real-time fluorescent quantitative PCR and immunohistochemical staining.

RESULTS

Exposure to PM_2.5 increased levels of TP, LDH, IL-1β, IL-18 and inflammatory cell counts in lung. The mRNA and protein expression of Caspase1, NLRP3 and GSDMD were increased. Inhibition of the NALRP3/Caspase-1 signaling pathway ameliorated PM_2.5-induced lung injury and inflammation, partially through suppressing pyroptosis in lung.

CONCLUSION

PM_2.5 exposure induces lung injury and inflammation, which is mediated by the NALRP3/Caspase-1 signaling pathway.

Estimating Short- and Long-Term Associations Between Air Quality Index and COVID-19 Transmission: Evidence From 257 Chinese Cities

Objectives: To evaluate the long- and short-term effects of air pollution on COVID-19 transmission simultaneously, especially in high air pollution level countries.

Methods: Quasi-Poisson regression was applied to estimate the association between exposure to air pollution and daily new confirmed cases of COVID-19, with mutual adjustment for long- and short-term air quality index (AQI). The independent effects were also estimated and compared. We further assessed the modification effect of within-city migration (WM) index to the associations.

Results: We found a significant 1.61% (95%CI: 0.51%, 2.72%) and 0.35% (95%CI: 0.24%, 0.46%) increase in daily confirmed cases per 1 unit increase in long- and short-term AQI. Higher estimates were observed for long-term impact. The stratifying result showed that the association was significant when the within-city migration index was low. A 1.25% (95%CI: 0.0.04%, 2.47%) and 0.41% (95%CI: 0.30%, 0.52%) increase for long- and short-term effect respectively in low within-city migration index was observed.

Conclusions: There existed positive associations between long- and short-term AQI and COVID-19 transmission, and within-city migration index modified the association. Our findings will be of strategic significance for long-run COVID-19 control.

Technical note: Understanding the effect of COVID-19 on particle pollution using a low-cost sensor network

The 2020 coronavirus pandemic and the following quarantine measures have led to significant changes in daily life worldwide. Preliminary research indicates that air quality has improved in many urban areas as a result of these measures. This study takes a neighborhood-scale approach to quantifying this change in pollution. Using data from a network of citizen-hosted, low-cost particulate matter (PM) sensors, called Air Quality & yoU (AQ&U), we obtained high-spatial resolution measurements compared to the relatively sparse state monitoring stations. We compared monthly average estimated PM_2.5 concentrations from February 11 to May 11, 2019 at 71 unique locations in Salt Lake County, UT, USA with the same (71) sensors' measurements during the same timeframe in 2020. A paired t-test showed significant reductions (71.1% and 21.3%) in estimated monthly PM_2.5 concentrations from 2019 to 2020 for the periods from March 11-April 10 and April 11-May 10, respectively. The March time period corresponded to the most stringent COVID-19 related restrictions in this region. Significant decreases in PM_2.5 were also reported by state monitoring sites during March (p < 0.001 compared to the previous 5-year average). While we observed decreases in PM_2.5 concentrations across the valley in 2020, it is important to note that the PM_2.5 concentrations did not improve equally in all locations. We observed the greatest reductions at lower elevation, more urbanized areas, likely because of the already low levels of PM_2.5 at the higher elevation, more residential areas, which were generally below 2 μg/m³ in both 2019 and 2020. Although many of measurements during March and April were near or below the estimated detection limit of the low-cost PM sensors and the federal equivalent measurements, every low-cost sensor (51) showed a reduction in PM_2.5 concentration in March of 2020 compared to 2019. These results suggest that the air quality improvement seen after March 11, 2020 is due to quarantine measures reducing traffic and decreasing pollutant emissions in the region.

Particulate Matter-Induced Cardiovascular Dysfunction: A Mechanistic Insight

Air pollution and particulate matter (PM) are significant factors for adverse health effects most prominently cardiovascular disease (CVD). PM is produced from various sources, which include both natural and anthropogenic. It is composed of biological components, organic compounds, minerals, and metals, which are responsible for inducing inflammation and adverse health effects. However, the adverse effects are related to PM size distribution. Finer particles are a significant cause of cardiovascular events. This review discusses the direct and indirect mechanisms of PM-induced CVD like myocardial infarction, the elevation of blood pressure, cardiac arrhythmias, atherosclerosis, and thrombosis. The two potential mechanisms are oxidative stress and systemic inflammation. Prenatal exposure has also been linked with cardiovascular outcomes later in life. Moreover, we also mentioned the epidemiological studies that strongly associate PM with CVD.

Community-Based Measurements Reveal Unseen Differences during Air Pollution Episodes

Short-term exposure to fine particulate matter (PM_2.5) pollution is linked to numerous adverse health effects. Pollution episodes, such as wildfires, can lead to substantial increases in PM_2.5 levels. However, sparse regulatory measurements provide an incomplete understanding of pollution gradients. Here, we demonstrate an infrastructure that integrates community-based measurements from a network of low-cost PM_2.5 sensors with rigorous calibration and a Gaussian process model to understand neighborhood-scale PM_2.5 concentrations during three pollution episodes (July 4, 2018, fireworks; July 5 and 6, 2018, wildfire; Jan 3-7, 2019, persistent cold air pool, PCAP). The firework/wildfire events included 118 sensors in 84 locations, while the PCAP event included 218 sensors in 138 locations. The model results accurately predict reference measurements during the fireworks (n: 16, hourly root-mean-square error, RMSE, 12.3-21.5 μg/m³, n(normalized)RMSE: 14.9-24%), the wildfire (n: 46, RMSE: 2.6-4.0 μg/m³; nRMSE: 13.1-22.9%), and the PCAP (n: 96, RMSE: 4.9-5.7 μg/m³; nRMSE: 20.2-21.3%). They also revealed dramatic geospatial differences in PM_2.5 concentrations that are not apparent when only considering government measurements or viewing the US Environmental Protection Agency's AirNow visualizations. Complementing the PM_2.5 estimates and visualizations are highly resolved uncertainty maps. Together, these results illustrate the potential for low-cost sensor networks that combined with a data-fusion algorithm and appropriate calibration and training can dynamically and with improved accuracy estimate PM_2.5 concentrations during pollution episodes. These highly resolved uncertainty estimates can provide a much-needed strategy to communicate uncertainty to end users.

The short-term harvesting effects of ambient particulate matter on mortality in Taiyuan elderly residents: A time-series analysis with a generalized additive distributed lag model

The evaluation on mortality displacement and distributed lag effects of airborne particulate matter (PM) on death risks is important to understand the positive association of short-term pollution from both ambient PM₁₀ and PM_2.5 with daily mortality. Herein, short-term influences of urban PM₁₀ and PM_2.5 exposure on the mortality of respiratory diseases (RD) and cardiovascular diseases (CVD) were studied at Taiyuan, China, a typical inland city suffering from heavy ambient PM loading and having high morbidity of RD and CVD. Using a time-series analysis with generalized additive distributed lag model (DLM), the potential mortality displacement was determined and the single-day and cumulative lag-day effects of PM on mortality were estimated after the daily mass concentrations of urban PM_2.5 and PM₁₀ from January 2013 to October 2015 and the daily number of non-accidental death (NAD) and cause-specific mortality in the residents aged more than 65 years old were obtained. Results showed there were significant associations of PM_2.5 and PM₁₀ with daily mortality on the current day and within one week. And a statistically significant increase (P < 0.05) in the cumulative effect estimates of PM_2.5 and PM₁₀ on CVD, ischemic heart disease (IHD), and myocardial infarction (MI) mortality (as well as PM_2.5 on NAD) was observed, while the associations of PM_2.5 with RD and pneumonia mortality, PM₁₀ with NAD and RD mortality were not statistically significant, when the exposure window was extended to lag 0-30 days. It was concluded that there were harvesting effects and cumulative effects of ambient PM_2.5 and PM₁₀ on the elderly residents' mortality due to RD and CVD at Taiyuan and they could be estimated quantitatively when the broader time window was used, suggesting that the underestimation on the association of ambient PM with non-accidental death can be avoided using the present method in our study.

Long-Term PM2.5 Exposure and Risks of Ischemic Heart Disease and Stroke Events: Review and Meta-Analysis

Background

Fine particulate matter <2.5 µm in diameter (PM_2.5) has known effects on cardiovascular morbidity and mortality. However, no study has quantified and compared the risks of incident myocardial infarction, incident stroke, ischemic heart disease (IHD) mortality, and cerebrovascular mortality in relation to long‐term PM_2.5 exposure.

Methods and Results

We sought to quantitatively summarize studies of long‐term PM_2.5 exposure and risk of IHD and stroke events by conducting a review and meta‐analysis of studies published by December 31, 2019. The main outcomes were myocardial infarction, stroke, IHD mortality, and cerebrovascular mortality. Random effects meta‐analyses were used to estimate the combined risk of each outcome among studies. We reviewed 69 studies and included 42 studies in the meta‐analyses. In meta‐analyses, we found that a 10‐µg/m³ increase in long‐term PM_2.5 exposure was associated with an increased risk of 23% for IHD mortality (95% CI, 15%–31%), 24% for cerebrovascular mortality (95% CI, 13%–36%), 13% for incident stroke (95% CI, 11%–15%), and 8% for incident myocardial infarction (95% CI, −1% to 18%). There were an insufficient number of studies of recurrent stroke and recurrent myocardial infarction to conduct meta‐analyses.

Conclusions

Long‐term PM_2.5 exposure is associated with increased risks of IHD mortality, cerebrovascular mortality, and incident stroke. The relationship with incident myocardial infarction is suggestive of increased risk but not conclusive. More research is needed to understand the relationship with recurrent events.

Investigating a Potential Map of PM2.5 Air Pollution and Risk for Tourist Attractions in Hsinchu County, Taiwan

In the past few years, human health risks caused by fine particulate matters (PM2.5) and other air pollutants have gradually received attention. According to the Disaster Prevention and Protection Act of Taiwan's Government enforced in 2017, "suspended particulate matter" has officially been acknowledged as a disaster-causing hazard. The long-term exposure to high concentrations of air pollutants negatively affects the health of citizens. Therefore, the precise determination of the spatial long-term distribution of hazardous high-level air pollutants can help protect the health and safety of residents. The analysis of spatial information of disaster potentials is an important measure for assessing the risks of possible hazards. However, the spatial disaster-potential characteristics of air pollution have not been comprehensively studied. In addition, the development of air pollution potential maps of various regions would provide valuable information. In this study, Hsinchu County was chosen as an example. In the spatial data analysis, historical PM2.5 concentration data from the Taiwan Environmental Protection Administration (TWEPA) were used to analyze and estimate spatially the air pollution risk potential of PM2.5 in Hsinchu based on a geographic information system (GIS)-based radial basis function (RBF) spatial interpolation method. The probability that PM2.5 concentrations exceed a standard value was analyzed with the exceedance probability method; in addition, the air pollution risk levels of tourist attractions in Hsinchu County were determined. The results show that the air pollution risk levels of the different seasons are quite different. The most severe air pollution levels usually occur in spring and winter, whereas summer exhibits the best air quality. Xinfeng and Hukou Townships have the highest potential for air pollution episodes in Hsinchu County (approximately 18%). Hukou Old Street, which is one of the most important tourist attractions, has a relatively high air pollution risk. The analysis results of this study can be directly applied to other countries worldwide to provide references for tourists, tourism resource management, and air quality management; in addition, the results provide important information on the long-term health risks for local residents in the study area.

Causal Effects of Air Pollution on Mortality Rate in Massachusetts

Air pollution epidemiology studies have primarily investigated long- and short-term exposures separately, have used multiplicative models, and have been associational studies. Implementing a generalized propensity score adjustment approach with 3.8 billion person-days of follow-up, we simultaneously assessed causal associations of long-term (1-year moving average) and short-term (2-day moving average) exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), ozone, and nitrogen dioxide with all-cause mortality on an additive scale among Medicare beneficiaries in Massachusetts (2000-2012). We found that long- and short-term PM2.5, ozone, and nitrogen dioxide exposures were all associated with increased mortality risk. Specifically, per 10 million person-days, each 1-μg/m3 increase in long- and short-term PM2.5 exposure was associated with 35.4 (95% confidence interval (CI): 33.4, 37.6) and 3.04 (95% CI: 2.17, 3.94) excess deaths, respectively; each 1-part per billion (ppb) increase in long- and short-term ozone exposure was associated with 2.35 (95% CI: 1.08, 3.61) and 2.41 (95% CI: 1.81, 2.91) excess deaths, respectively; and each 1-ppb increase in long- and short-term nitrogen dioxide exposure was associated with 3.24 (95% CI: 2.75, 3.77) and 5.60 (95% CI: 5.24, 5.98) excess deaths, respectively. Mortality associated with long-term PM2.5 and ozone exposure increased substantially at low levels. The findings suggested that air pollution was causally associated with mortality, even at levels below national standards.

Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998-2018)

Exposure to outdoor fine particulate matter (PM_2.5) is a leading risk factor for mortality. We develop global estimates of annual PM_2.5 concentrations and trends for 1998-2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM_2.5 concentrations using geophysical relationships between surface PM_2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM_2.5 estimates are highly consistent with globally distributed ground monitors (R² = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM_2.5 estimates to predict and account for the residual bias with PM_2.5 monitors, yielding even higher cross validated agreement (R² = 0.90-0.92; slope = 0.90-0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (-0.28 ± 0.03 μg/m³/yr), Europe (-0.15 ± 0.03 μg/m³/yr), India (1.13 ± 0.15 μg/m³/yr), and globally (0.04 ± 0.02 μg/m³/yr). The positive trend (2.44 ± 0.44 μg/m³/yr) for India over 2005-2013 and the negative trend (-3.37 ± 0.38 μg/m³/yr) for China over 2011-2018 are remarkable, with implications for the health of billions of people.

Associations of long-term exposure to ambient PM2.5 with mortality in Chinese adults: A pooled analysis of cohorts in the China-PAR project

BACKGROUND

The concentration-response relationship between mortality and long-term exposure to fine particulate matter (PM_2.5) has not been fully elucidated, especially at high levels of PM_2.5 concentrations.

OBJECTIVE

We aimed to evaluate chronic effects of ambient PM_2.5 exposure on deaths among Chinese adults in high-exposure settings.

METHODS

Participants of the Prediction for Atherosclerotic cardiovascular disease Risk in China (China-PAR) project were included from four prospective cohorts among Chinese adults aged ≥18 years old. The overall follow-up rate of the four cohorts was 93.4% until the recent follow-up survey that ended in 2015. The average of satellite-based PM_2.5 concentrations during 2000-2015 at 1-km spatial resolution was assigned to each participant according to individual residence addresses. Based on the pooled analysis of individual data from the four cohorts, a Cox proportional hazards model was used to estimate the hazard ratio (HR) and corresponding 95% confidence intervals (95% CIs) for the association of PM_2.5 exposure with mortality after multivariate adjustment.

RESULTS

A total of 116,821 participants were eligible in the final analysis. During a mean of 7.7 years of follow-up, 6,395 non-accidental deaths and 2,507 cardio-metabolic deaths occurred. The mean of PM_2.5 concentration was 64.9 μg/m³ ranging from 31.2 μg/m³ to 97.0 μg/m³. For each 10 μg/m³ increment in PM_2.5, the HR was 1.11 (95% CI: 1.08-1.14) for non-accidental mortality and 1.22 (95% CI: 1.16-1.27) for cardio-metabolic mortality. In addition, a weak exponential curve for the concentration-response association between mortality and PM_2.5 was observed among Chinese adults.

CONCLUSIONS

Our study provided important evidence of the long-term effects of PM_2.5 exposure on deaths among Chinese adults. The findings expand our knowledge on concentration-response relationship in high-exposure environments, which is essential to address the urgent challenge of reducing the disease burden attributable to PM_2.5 exposure in rapidly industrializing countries such as China.

Estimating historical SO2 level across the whole China during 1973-2014 using random forest model

Ambient SO₂ pollution poses a great threat on air quality, human health, and ecosystem safety. The ground-level SO₂ monitoring sites over China have been established during the past years, while the long-term SO₂ data was still missing before 2014, which cannot reveal the evolution trend of SO₂ pollution and assess its response to the anthropogenic activity. In this work, we developed a high-quality random forest (RF) model to simulate the long-term SO₂ concentration across the entire China from 1973 to 2014, based on substantial explanatory variables (e.g., meteorological factors, SO₂ emission intensity, land use types). The 10-fold cross-validation R² value and root mean square error (RMSE) over China reached 0.64 and 17.06 μg/m³, respectively, both of which were significantly higher than those of other models such as back propagation neural network (BPNN) and generalized regression neutral network (GRNN). Among all of the predictors, T displayed the highest relative importance value, followed by WS, Prec, SO₂ emission intensity, RH, DOY, elevation, and the lower one for land use types and P. The estimated mean SO₂ concentration during 1973-2014 displayed the remarkably spatial variation with the higher value in North China Plain (NCP) and Middle part of Inner Mongolia. This historical SO₂ level estimation suggested that air pollution was not a new environmental issue that could be dated back to 1973. Overall, the annually mean SO₂ level for each grid increased from 29.46 ± 9.79 to 31.44 ± 8.77 μg/m³ from 1973 to 2014. The annually mean SO₂ concentration in NCP showed rapid increase from 34.32 ± 3.05 to 36.97 ± 3.18 μg/m³ during 1973-2002, whereas they decreased significantly after 2003 (from 37.46 ± 3.20 to 36.13 ± 3.48 μg/m³ during 2003-2014). The gradual decrease since 2003 was benefitted from the adjustment of the energy consumption structure and the adoption of emission control technologies. However, the SO₂ levels in some western regions showed the violent increases since 2003 due to the proposal of "development of the western region". The estimated daily SO₂ concentration across the entire China could provide the essential data for epidemiological research and air pollution prevention.

Potential gains in life expectancy by attaining daily ambient fine particulate matter pollution standards in mainland China: A modeling study based on nationwide data

BACKGROUND

Ambient fine particulate matter pollution (PM2.5) is one leading cause of disease burden, but no study has quantified the association between daily PM2.5 exposure and life expectancy. We aimed to assess the potential benefits in life expectancy by attaining the daily PM2.5 standards in 72 cities of China during 2013-2016.

METHODS AND FINDINGS

We applied a two-stage approach for the analysis. At the first stage, we used a generalized additive model (GAM) with a Gaussian link to examine the city-specific short-term association between daily PM2.5 and years of life lost (YLL); at the second stage, a random-effects meta-analysis was used to generate the regional and national estimations. We further estimated the potential gains in life expectancy (PGLE) by assuming that ambient PM2.5 has met the Chinese National Ambient Air Quality Standard (NAAQS, 75 μg/m3) or the ambient air quality guideline (AQG) of the World Health Organization (WHO) (25 μg/m3). We also calculated the attributable fraction (AF), which denoted the proportion of YLL attributable to a higher-than-standards daily mean PM2.5 concentration. During the period from January 18, 2013 to December 31, 2016, we recorded 1,226,849 nonaccidental deaths in the study area. We observed significant associations between daily PM2.5 and YLL: each 10 μg/m3 increase in three-day-averaged (lag02) PM2.5 concentrations corresponded to an increment of 0.43 years of life lost (95% CI: 0.29-0.57). We estimated that 168,065.18 (95% CI: 114,144.91-221,985.45) and 68,684.95 (95% CI: 46,648.79-90,721.11) years of life lost can be avoided by achieving WHO's AQG and Chinese NAAQS in the study area, which corresponded to 0.14 (95% CI: 0.09-0.18) and 0.06 (95% CI: 0.04-0.07) years of gain in life expectancy for each death in these cities. We observed differential regional estimates across the 7 regions, with the highest gains in the Northwest region (0.28 years of gain [95% CI: 0.06-0.49]) and the lowest in the North region (0.08 [95% CI: 0.02-0.15]). Furthermore, using WHO's AQG and Chinese NAAQS as the references, we estimated that 1.00% (95% CI: 0.68%-1.32%) and 0.41% (95% CI: 0.28%-0.54%) of YLL could be attributable to the PM2.5 exposure at the national level. Findings from this study were mainly limited by the unavailability of data on individual PM2.5 exposure.

CONCLUSIONS

This study indicates that significantly longer life expectancy could be achieved by a reduction in the ambient PM2.5 concentrations. It also highlights the need to formulate a stricter ambient PM2.5 standard at both national and regional levels of China to protect the population's health.

Predicting gestational personal exposure to PM2.5 from satellite-driven ambient concentrations in Shanghai

BACKGROUND

It has been widely reported that gestational exposure to fine particulate matters (PM_2.5) is associated with a series of adverse birth outcomes. However, the discrepancy between ambient PM_2.5 concentrations and personal PM_2.5 exposure would significantly affect the estimation of exposure-response relationship.

OBJECTIVE

Our study aimed to predict gestational personal exposure to PM_2.5 from the satellite-driven ambient concentrations and analyze the influence of other potential determinants.

METHOD

We collected 762 72-h personal exposure samples from a panel of 329 pregnant women in Shanghai, China as well as their time-activity patterns from Feb 2017 to Jun 2018. We established an ambient PM_2.5 model based on MAIAC AOD at 1 km resolution, then used its output as a major predictor to develop a personal exposure model.

RESULTS

Our ambient PM_2.5 model yielded a cross-validation R² of 0.96. Personal PM_2.5 exposure levels were almost identical to the corresponding ambient concentrations. After adjusting for time-activity patterns and meteorological factors, our personal exposure has a CV R² of 0.76.

CONCLUSION

We established a prediction model for gestational personal exposure to PM_2.5 from satellite-based ambient concentrations and provided a methodological reference for further epidemiological studies.

Contributions of Indoor and Outdoor Sources to Ozone in Residential Buildings in Nanjing

Ozone has become one of the most serious air pollutants in China in recent years. Since people spend most of their time indoors, the ozone in the indoor environment could be a major factor affecting the occupants’ health. The indoor ozone in residential buildings mainly comes from two sources: outdoor atmosphere and indoor ozone produced by electrical devices. In this study, a typical residence in Nanjing was taken as an example to calculate and compare the contributions of indoor and outdoor sources to ozone in the building. A questionnaire survey about the type, the placement, and the frequency of use of the ozone emission devices was performed to provide the basis for the settings of indoor ozone sources. The multi-zone software CONTAM was used hourly to simulate the ozone concentration in summer and in winter with inner doors either closed or open, and it was noted whether there were ozone emission devices indoors or not. Source contribution was quantified and compared by three methods in this paper: (1) the average indoor/outdoor (I/O) ratio, (2) the I/O ratio frequency, and (3) the ratio of indoor ozone concentration without ozone sources to that with ozone sources. The results showed that the contribution of outdoor sources was much greater than that of indoor sources in summer, but in winter, the frequency of I/O > 1 could reach 55.8% of the total seasonal time, and the ratio of indoor ozone concentration without sources to that with sources could reach as high as 74.3%. This meant that the indoor concentration had the potential to exceed the outdoor. Furthermore, human respiratory exposure in different ages and genders was calculated. It was found that teenagers aged 10–18 years old and female adults had a higher respiratory exposure level.

Short-term and long-term exposures to fine particulate matter constituents and health: A systematic review and meta-analysis

BACKGROUND

Fine particulate matter (Particulate matter with diameter ≤ 2.5 μm) is associated with multiple health outcomes, with varying effects across seasons and locations. It remains largely unknown that which components of PM_2.5 are most harmful to human health.

METHODS

We systematically searched all the relevent studies published before August 1, 2018, on the associations of fine particulate matter constituents with mortality and morbidity, using Web of Science, MEDLINE, PubMed and EMBASE. Studies were included if they explored the associations between short term or long term exposure of fine particulate matter constituents and natural, cardiovascular or respiratory health endpoints. The criteria for the risk of bias was adapted from OHAT and New Castle Ottawa. We applied a random-effects model to derive the risk estimates for each constituent. We performed main analyses restricted to studies which adjusted the PM_2.5 mass in their models.

RESULTS

Significant associations were observed between several PM_2.5 constituents and different health endpoints. Among them, black carbon and organic carbon were most robustly and consistently associated with all natural, cardiovascular mortality and morbidity. Other potential toxic constituents including nitrate, sulfate, Zinc, silicon, iron, nickel, vanadium, and potassium were associated with adverse cardiovascular health, while nitrate, sulfate and vanadium were relevant for adverse respiratory health outcomes.

CONCLUSIONS

Our analysis suggests that black carbon and organic carbon are important detrimental components of PM_2.5, while other constituents are probably hazardous to human health. However, more studies are needed to further confirm our results.

Association between short-term exposure to particulate matter air pollution and cause-specific mortality in Changzhou, China

BACKGROUND

Extensive studies have linked ambient particulate matter (PM) to an increased mortality burden from a wide range of causes. However, the effects of PM on mortality rates from specific causes were unclear. This study aimed to estimate the detrimental effects of PM on cause specific deaths in Changzhou, China.

METHOD

Data representing daily mortality rates, weather conditions and particulate air pollution levels were obtained from government-controlled agencies of Changzhou, from January 1, 2015 to December 31, 2016. An inverse distance weighting method was used to assess the population exposure to PM and a time-series was performed to detect the detrimental effects of PM.

RESULTS

Positive associations were identified between PMs and daily mortality rates from non-accidental, circulatory, hypertensive, respiratory and chronic lower respiratory causes at a lag of 0-3 days. The effects of PMs were strongest on hypertensive mortality, with an increase of 5.27% (95% confidence interval (CI): 2.43-8.19%) and 3.52% (95% CI: 1.55-5.53%), per 10 μg/m³ increment in PM_2.5 and PM₁₀ respectively. The elderly exhibited a higher mortality risk with PMs exposure. Females were more vulnerable to circulatory, hypertensive and respiratory death while males were more sensitive to chronic lower respiratory and neurodegenerative mortality. The effects were stronger in warm seasons for circulatory mortality and stronger in cold seasons for respiratory mortality.

CONCLUSION

These findings indicate that PM could exert adverse influences on the outcomes of several pathological processes, especially for women and the elderly with hypertension disease.

PM2.5 Upregulates MicroRNA-146a-3p and Induces M1 Polarization in RAW264.7 Cells by Targeting Sirtuin1

Background: Fine particulate matter (PM_2.5) exposure is proved to be associated with illnesses, but the mechanism is not clear. Potential effects of PM_2.5 on innate immunity have become a hotspot recently. Confronting PM_2.5, macrophages are able to be activated and induce inflammatory responses. Whether PM_2.5 exposure affects macrophage polarization and associated mechanisms remains to be further explored. Afterwards, whether Sirtuin1 (SIRT1) an important intermediate regulator in various physiological processes takes part in the macrophage polarization induced by PM_2.5 is unknown. MiRNAs are acknowledged as key regulator in posttranscriptional modification and our previous study found that miR-146a is a novel biomarker of PM_2.5 exposure. Thus, we propose a hypothesis, PM_2.5 exposure induces M1 polarization and miR-146a-3p is a potential upstream regulator by targeting SIRT1. Methods: RAW264.7 cells were treated with different concentrations of PM_2.5 for 24h. The expressions of cytokines and key molecular markers were detected by qRT-PCR, Western blotting and ELISA. The activation degree of TLRs and NF-κB was assessed by Western blotting. The specific agonist and antagonist of SIRT1 were used to explore the potential role of SIRT1 in M1 polarization induced by PM_2.5. MiR-146a-3p mimic and inhibitor were pre-transfected into RAW264.7 cells and the effects on M1 polarization induced by PM_2.5 were evaluated. Luciferase analysis was used to identify the binding site of miR-146a-3p and SIRT1. Results: PM_2.5 increased the mRNA and protein expression of M1 markers including interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α) and inducible nitric oxide synthase (iNOS) in RAW264.7 cells. The protein level of TLR4 was significantly increased and the ratio of phosphorylated NF-κB p65 versus p65 subunit was also elevated in PM_2.5 group. PM_2.5 decreased the protein level of SIRT1 but not the mRNA expression in vitro and in vivo experiments. Pre-treatment with SIRT1 agonist SRT1720 rescued the PM_2.5 induced M1 response. Whereas, SIRT1 antagonist EX527 augment the effect. MiR-146a-3p was upregulated in PM_2.5 treated RAW264.7 cells. Luciferase experiments reported that SIRT1 was directly targeted by miR-146a-3p. Overexpression of miR-146a-3p downregulated the expression of SIRT1 protein in untreated RAW264.7 cells. Importantly, inhibition of miR-146a-3p upregulated SIRT1 protein and suppressed M1 polarization in PM_2.5 treated RAW264.7 cells. Conclusions: These results suggested that PM_2.5 induces the inflammatory M1 polarization and TLR4/NF-κB signal transduction pathway might be involved in the process. MiR-146a-3p is a novel regulator of PM_2.5 exerted M1 polarization by targeting SIRT1.