The impacts of long-term exposure to PM2.5 on cancer hospitalizations in Brazil

Mortality burden attributable to exceptional PM2.5 air pollution events in Australian cities: A health impact assessment

Background

People living in Australian cities face increased mortality risks from exposure to extreme air pollution events due to bushfires and dust storms. However, the burden of mortality attributable to exceptional PM2.5 levels has not been well characterised. We assessed the burden of mortality due to PM2.5 pollution events in Australian capital cities between 2001 and 2020.

Methods

For this health impact assessment, we obtained data on daily counts of deaths for all non-accidental causes and ages from the Australian National Vital Statistics Register. Daily concentrations of PM2.5 were estimated at a 5 km grid cell, using a Random Forest statistical model of data from air pollution monitoring sites combined with a range of satellite and land use-related data. We calculated the exceptional PM2.5 levels for each extreme pollution exposure day using the deviation from a seasonal and trend loess decomposition model. The burden of mortality was examined using a relative risk concentration-response function suggested in the literature.

Findings

Over the 20-year study period, we estimated 1454 (95 % CI 987, 1920) deaths in the major Australian cities attributable to exceptional PM2.5 exposure levels. The mortality burden due to PM2.5 exposure on extreme pollution days was considerable. Variations were observed across Australia. Despite relatively low daily PM2.5 levels compared to global averages, all Australian cities have extreme pollution exposure days, with PM2.5 concentrations exceeding the World Health Organisation Air Quality Guideline standard for 24-h exposure. Our analysis results indicate that nearly one-third of deaths from extreme air pollution exposure can be prevented with a 5 % reduction in PM2.5 levels on days with exceptional pollution.

Interpretation

Exposure to exceptional PM2.5 events was associated with an increased mortality burden in Australia's cities. Policies and coordinated action are needed to manage the health risks of extreme air pollution events due to bushfires and dust storms under climate change.

Exposure to outdoor particulate matter and risk of respiratory diseases: a systematic review and meta-analysis

According to epidemiological studies, particulate matter (PM) is an important air pollutant that poses a significant threat to human health. The relationship between particulate matter and respiratory diseases has been the subject of numerous studies, but these studies have produced inconsistent findings. The purpose of this systematic review was to examine the connection between outdoor particulate matter (PM2.5 and PM10) exposure and respiratory disorders (COPD, lung cancer, LRIs, and COVID-19). For this purpose, we conducted a literature search between 2012 and 2022 in PubMed, Web of Science, and Scopus. Out of the 58 studies that were part of the systematic review, meta-analyses were conducted on 53 of them. A random effect model was applied separately for each category of study design to assess the pooled association between exposure to PM2.5 and PM10 and respiratory diseases. Based on time-series and cohort studies, which are the priorities of the strength of evidence, a significant relationship between the risk of respiratory diseases (COPD, lung cancer, and COVID-19) was observed (COPD: pooled HR = 1.032, 95% CI: 1.004-1.061; lung cancer: pooled HR = 1.017, 95% CI: 1.015-1.020; and COVID-19: pooled RR = 1.004, 95% CI: 1.002-1.006 per 1 μg/m3 increase in PM2.5). Also, a significant relationship was observed between PM10 and respiratory diseases (COPD, LRIs, and COVID-19) based on time-series and cohort studies. Although the number of studies in this field is limited, which requires more investigations, it can be concluded that outdoor particulate matter can increase the risk of respiratory diseases.

Complex polycyclic aromatic compound mixtures in PM2.5 in a Chinese megacity: Spatio-temporal variations, toxicity, and source apportionment

Polycyclic aromatic compounds (PACs) are important toxic organic components in fine particulate matter (PM2.5), whereas the links between PM2.5 toxicity and associated PACs in ambient air are poorly understood. This study investigated the spatial-temporal variations of PACs in PM2.5 collected from 11 sampling sites across a Chinese megacity and characterized the reactive oxygen species (ROS) generation and cytotoxicity induced by organic extracts of PM2.5 based on cellular assays. The extra trees regression model based on machine learning and ridge regression were used to identify the key toxicants among complex PAC mixtures. The total concentrations of these PACs varied from 2.12 to 71.7 ng/m3 across the study city, and polycyclic aromatic hydrocarbons (PAHs) are the main PACs. The spatial variations of the toxicological indicators generally resembled those of the PAC concentrations, and the PM2.5 related to waste treatment facilities exhibited the strongest toxic potencies. The ROS generation was highly correlated with high molecular weight PAHs (MW302 PAHs), followed by PAHs with MW<302 amu and oxygenated PAHs, but not with nitrated PAHs and the plastics additives. The cell mortality showed weak correlations with these organic constituents. The associations between the biological endpoints and these PM2.5-bound contaminants were further confirmed by exposure to authentic chemicals. Four primary sources of PACs were identified, among which coal and biomass combustion sources (30.2% of the total PACs) and industrial sources (31.0%) were predominant. PACs emitted from industrial sources were highly associated with ROS generation in this city. Our findings highlight the potent ROS-generating potential of MW302 PAHs and the importance of industrial sources contributing to PM2.5 toxicity in this megacity, raising public concerns and further administration.

Impact of COVID-19 restrictions on hourly levels of PM10, PM2.5 and black carbon at an industrial suburban site in northern Spain

Due to the COVID-19 pandemic, lockdown restrictions were established around the world. Many studies have assessed whether these restrictions affected atmospheric pollution. Comparison between them is difficult as the periods of time considered are generally not the same and thus, different conclusions may be reached. Besides, most of them consider mean daily pollutant concentration, despite differences being observed according to the time of day. In this study, the hourly levels of PM10, PM2.5 and black carbon (BC) in an industrial suburban area in the north of Spain were analysed from May 2019 to June 2020 and compared with those from the literature, using the same period in each case. In general, the highest concentrations were reached when the wind direction came from the southwest (where a steelworks, a coal-fired power plant and other industries are located) and during the night-time, both before and during the lockdown. The highest concentrations of PM10, PM2.5 and BC were observed from December to February (on average: 45, 17 and 1.3 μg m^-3, respectively). The decrease/increase in those pollutants levels during the lockdown were found to be highly dependent on the period considered. Indeed, PM10 can be found to decrease by up to 39% or increase by 12%; PM2.5 can decrease by 21% or increase by up to 36%; and BC, although it generally decreases (by up to 42%), can increase by 7.4%.

Estimating the effect of increasing ambient temperature on antimicrobial resistance in China: A nationwide ecological study with the difference-in-differences approach

Antimicrobial resistance (AMR) and the possible consequences of rising ambient temperatures brought on by global warming have been extensively discussed. However, the epidemiological evidence on the effects of temperature on AMR is rare and little is known about the role of socioeconomic inequities. This ecological study obtained 31 provinces AMR data of Escherichia Coli (E. coli) from the China Antimicrobial Resistance Surveillance System (CARSS) over the period from 2014 to 2020, which were linked to the meteorological and socioeconomic data published in the China Statistical Yearbook. Modified difference-in-differences (DID) analyses were performed to estimate the effect of ambient temperature on AMR of E. coli to third-generation cephalosporins (ceftriaxone and cefotaxime), carbapenems, and quinolones, adjusting for variations in meteorological and socioeconomic factors. We estimated that every 1 °C increase in average ambient temperature was associated with 2.71 % (95 % confidence interval [CI]: 1.20-4.24), 32.92 % (95 % CI: 15.62-52.81), and 1.81 % (95 % CI: 0.47-3.16) increase in the prevalence of E. coli resistance to third-generation cephalosporins (ceftriaxone and cefotaxime), carbapenems and quinolones, respectively. The link was more profound in the regions with lower temperature and a median level of average humidity, and the regions with lower income, lower expenditure (in economics), lower health resources, and lower hospital admissions. Neither the replacement of the temperature variable nor the alternative approaches for confounding adjustment changed the positive association between ambient temperature and AMR. In general, there exists a positive association between ambient temperature and AMR, although the strength of such an association varies by socioeconomic and health services factors. The association is possibly nonlinear, especially for E. coli resistance to third-generation cephalosporins. The findings suggest that AMR control programs should explicitly incorporate weather patterns to increase their effectiveness.

Short-term air pollution exposure and hospital admissions for cardiorespiratory diseases in Brazil: A nationwide time-series study between 2008 and 2018

The established evidence associating air pollution with health is limited to populations from specific regions. Further large-scale studies in several regions worldwide are needed to support the literature to date and encourage national governments to act. Brazil is an example of these regions where little research has been performed on a large scale. To address this gap, we conducted a study looking at the relationship between daily PM_2.5, NO₂, and O₃, and hospital admissions for circulatory and respiratory diseases across Brazil between 2008 and 2018. A time-series analytic approach was applied with a distributed lag modeling framework. We used a generalized conditional quasi-Poisson regression model to estimate relative risks (RRs) of the association of each air pollutant with the hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. Our study population includes 23, 791, 093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. Our findings suggest significant associations of ambient air pollution (PM_2.5, NO₂, and O₃) with respiratory and circulatory hospital admissions in Brazil. The national meta-analysis for the whole population showed that for every increase of PM_2.5 by 10 μg/m³, there is a 3.28% (95%CI: 2.61; 3.94) increase in the risk of hospital admission for respiratory diseases. For O₃, we found positive associations only for some sub-group analyses by age and sex. For NO₂, our findings suggest that a 10 ppb increase in this pollutant, there was a 35.26% (95%CI: 24.07; 46.44) increase in the risk of hospital admission for respiratory diseases. This study may better support policymakers to improve the air quality and public health in Brazil.

Transcriptome and pan-cancer system analysis identify PM2.5-induced stanniocalcin 2 as a potential prognostic and immunological biomarker for cancers

Epidemiological studies have shown that air pollution and particulate matter (PM) are closely related to the occurrence of cancer. However, the potential prognostic and immunological biomarkers for air pollution related cancers are lacking. In this study, we proved PM2.5 exposure was correlated with lung cancer through transcriptome analysis. Importantly, we identified STC2 as a key gene regulated by PM2.5, whose expression in epithelial cells was significantly increased after PM2.5 treatment and validated by using RT-qPCR and immunofluorescence. Kaplan-Meier OS curves suggested that high STC2 expression positively correlated with a poor prognosis in lung cancer. Furthermore, we discovered that STC2 was associated with multiple cancers and pathways in cancer. Next, Pan-Cancer Expression Landscape of STC2 showed that STC2 exhibited inconsistent expression across 26 types of human cancer, lower in KIRP in cancer versus adjacent normal tissues, and significantly higher in another cancers. Cox regression results suggested that STC2 expression was positively or negatively associated with prognosis in different cancers. Moreover, STC2 expression was associated with clinical phenotypes including age, gender, stage and grade. Mutation features of STC2 were also analyzed, in which the highest alteration frequency of STC2 was presented in KIRC with amplification. Meanwhile, the effects of copy number variation (CNV) on STC2 expression were investigated across various tumor types, suggesting that STC2 expression was significantly correlated with CNV in tumors. Additionally, STC2 was closely related to tumor heterogeneity, tumor stemness and tumor immune microenvironment like immune cell infiltration. In the meantime, we analyzed methylation modifications and immunological correlation of STC2. The results demonstrated that STC2 expression positively correlated with most RNA methylation genes and immunomodulators across tumors. Taken together, the findings revealed that PM2.5-induced STC2 might be a potential prognostic and immunological biomarker for cancers related to air pollution.

Life-course exposure to ambient fine particulate matter and hypertension in adulthood: a longitudinal cohort study

PM_2.5-hypertension association were well documented in adults, while the effects of life-course exposure to PM_2.5 on adulthood hypertension remained unclear. This study aimed to investigate the associations between life-course exposure to ambient PM_2.5 and incident hypertension in adulthood in Asia. We included 4272 participants with 17,814 medical visits from two open cohorts in Taiwan and Hong Kong between 2000 and 2018. We used a satellite-based model to assess 2-year average PM_2.5 exposure at a resolution of 1 km². A linear mixed model was used to examine the association with blood pressure. A Cox regression model with time-dependent covariates was used to examine the overall association with the development of hypertension in adulthood. Life-course mixed models were used to examine the effects of PM_2.5 exposure at different life stages on blood pressure and hypertension. For every 10 μg/m³ increase in PM_2.5, the overall risk of adulthood hypertension increased by 40% (95% confidence interval [CI] 8-80%). The health effects of PM_2.5 exposure at different life-stages on incident hypertension were generally independent of each other. In critical model, the risk of developing hypertension increased 23%, 27%, and 55% for each 10 μg/m³ increase in PM_2.5 exposure during school age, adolescence, and adulthood, respectively. Similar associations were found between life-course PM_2.5 exposure and blood pressure. Association between PM_2.5 and adulthood hypertension can be traced back to childhood. Our study suggests that life-course control of air pollution exposure should be implemented to alleviate the huge burden of adulthood hypertension.

Toward a Better Air-Assisted Flare Design for Safe and Efficient Operation during Purge Flow Conditions: Designing and Performance Testing

In this study, a new air-assisted flare tip was designed, built, and tested under different operating conditions. Lacking sufficient energy to mix with air, low waste gas flow rates will lead to incomplete combustion of these gases. This increases pollutant emissions and soot formation which leads to a decline in flare performance. This flare tip design enhances the waste gas mixing energy through implementation of an air jet in a crossflow orientation. This is done by adjusting the exit area of the waste gas exit by injecting a radial jet of air from an inclined slot jet located around the flare tip. This flare tip design also provides protection for the flare tip from high flame temperatures that can damage through convective cooling. Several tests were conducted to assess the new flare tip design with varying waste gas flow rates of 5, 10, 25, and 120 standard liters per minute (SLPM). These tests also considered varying assistant air flow rates. In addition, test results showed high combustion efficiency of the flaring process and significant soot formation suppression. The new flare tip design yielded better flame behavior with respect to the flare tip, caused by the flame stability that prevented the flame from attaching to the flare tip.

The spatiotemporal correlation of PM2.5 concentration on esophageal cancer hospitalization rate in Fujian province of China

This paper aimed to explore the correlation between PM_2.5 concentration and hospitalization rate of esophageal cancer in Fujian province, and tried to find out the accurate lag effect between PM_2.5 and hospitalization rate in 70 counties from the linear and nonlinear aspects. We extracted inpatients data of esophageal cancer from the New Rural Cooperative Medical Scheme (NRCMS) database and air pollutant PM_2.5 grid data published by the atmospheric composition analysis group. The study showed that the hospitalization rate of esophageal cancer presented spatial aggregation in 70 counties of Fujian province. Southeast urban agglomerations had high hospitalization rates, while central and western regions had low hospitalization rates. The study found that the spatial distribution of the hospitalization rate of esophageal cancer in 2016 was not consistent with that of the PM_2.5 concentration in the same year. The concentration of PM_2.5 in 2003 and 2004 had the strongest correlation with the hospitalization rate of esophageal cancer in 2016, with Pearson correlation coefficient r value of - 0.365 and Geodetector q-statistic value of 0.148 (p < 0.05). Our findings showed that there existed a 13-year lag period of air pollutant PM_2.5 on the esophageal cancer hospitalization rate, which can provide helpful guidance in the early screening strategy of esophageal cancer in Fujian. The research progress of this paper will help to understand the lag period of the impact of air pollutants on the hospitalization rate of esophageal cancer, provide valuable information for the prevention and treatment strategy of esophageal cancer in Fujian province, and provide relevant experience for alike regions.

Research on adaption to air pollution in Chinese cities: Evidence from social media-based health sensing

Air pollution seriously threats to human health. Understanding the health effects of air pollution is of great importance for developing countermeasures. However, little is known about the real-time impacts of air pollution on the human heath in a comprehensive way in developing nations, like China. To fill this research gap, the Chinese urbanites' health were sensed from more than 210.82 million Weibo (Chinese Twitter) data in 2017. The association between air pollution and the health sensing were quantified through generalized additive models, based on which the sensitivities and adaptions to air pollution in 70 China's cities were assessed. The results documented that the Weibo data can well sense urbanites' health in real time. With the different geographical characteristics and socio-economic conditions, the Chinese residents have adaption to air pollution, indicated by the spatial heterogeneity of the sensitivities to air pollution. Cities with good air quality in South China and East China were more sensitive to air pollution, while cities with worse air quality in Northwest China and North China were less sensitive. This research provides a new perspective and methodologies for health sensing and the health effect of air pollution.

Associations between long-term exposure to PM2.5 and site-specific cancer mortality: A nationwide study in Brazil between 2010 and 2018

Long-term exposure to PM_2.5 has been linked to lung cancer incidence and mortality, but limited evidence existed for other cancers. This study aimed to assess the association between PM_2.5 on cancer specific mortality. An ecological study based on the cancer mortality data collected from 5,565 Brazilian cities during 2010-2018 using a difference-in-differences approach with quasi-Poisson regression, was applied to examine PM_2.5-cancer mortality associations. Globally gridded annual average surface PM_2.5 concentration was extracted and linked with the residential municipality of participants in this study. Sex, age stratified and exposure-response estimations were also conducted. Totalling 1,768,668 adult cancer deaths records of about 208 million population living across 5,565 municipalities were included in this study. The average PM_2.5 concentration was 7.63 μg/m³ (standard deviation 3.32) with range from 2.95 μg/m³ to 28.5 μg/m³. With each 10 μg/m³ increase in three-year-average (current year and previous two years) concentrations of PM_2.5, the relative risks (RR) of cancer mortality were 1.16 (95% confidence interval [CI]: 1.11-1.20) for all-site cancers. The PM_2.5 exposure was significantly associated with several cancer-specific mortalities including oral, nasopharynx, oesophagus, and stomach, colon rectum, liver, gallbladder, larynx, lung, bone, skin, female breast, cervix, prostate, brain and leukaemia. No safe level of PM_2.5 exposure was observed in the exposure-response curve for all types of cancer. In conclusion, with nationwide cancer death records in Brazil, we found that long-term exposure to ambient PM_2.5 increased risks of mortality for many cancer types. Even low level PM_2.5 concentrations had significant impacts on cancer mortality.

Spatiotemporal Patterns and Dominant Factors of Urban Particulate Matter Islands: New Evidence from 240 Cities in China

With rapid urbanization and industrialization, PM2.5 pollution exerts a significant negative impact on the urban eco-environment and on residents’ health. Previous studies have demonstrated that cities in China are characterized by urban particulate matter island (UPI) phenomena, i.e., higher PM2.5 concentrations are observed in urban areas than in rural settings. How, though, nature and socioeconomic environments interact to influence UPI intensities is a question that still awaits a general explanation. To fill this knowledge gap, this study investigates spatiotemporal variations in UPI effects with respect to different climatic settings and city sizes in 240 cities in China from 2000 to 2015 using remotely sensed data and explores the effective mechanism of human–environmental factors on UPI dynamics based upon the Geographically Weighted Regression (GWR) model. In particular, a conceptual framework that considers natural environments, technology, population, and economics is proposed to explore the factors influencing UPIs. The results show (1) that about 70% of the cities in China selected exhibited UPI effects from 2000 to 2015. In addition, UPI intensities and the number of UPI-related cities decreased over time. It is noteworthy that PM2.5 pollution shifted from urban to rural areas. (2) Elevation was the most efficient driving factor of UPI variations, followed by precipitation, population density, NDVI, per capita GDP, and PM2.5 emission per unit GDP. (3) Climatic backgrounds and city sizes influenced the compositions and performance of dominant factors regarding UPI phenomena. This study provides valuable a reference for PM2.5 pollution mitigation in cities experiencing global climate change and rapid urbanization and thus can help sustainable urban developments.

COVID-19, a double-edged sword for the environment: a review on the impacts of COVID-19 on the environment

This review paper discusses the most relevant impacts of the COVID-19 pandemic on the environment. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in Wuhan, China, in December 2019. The disease has infected 70 million people and caused the death of 1.58 million people since the US Food and Drug Administration issued an Emergency Use Authorization to develop a vaccine to prevent COVID-19 on December 11, 2020. COVID-19 is a global crisis that has impacted everything directly connected with human beings, including the environment. This review discusses the impacts of COVID-19 on the environment during the pandemic and post-COVID-19 era. During the first months of the COVID pandemic, global coal, oil, gas, and electricity demands declined by 8%, 5%, 2%, and 20%, respectively, relative to 2019. Stay-at-home orders in countries increased the concentrations of particles in indoor environments while decreasing the concentrations of PM2.5 and NOX in outdoor environments. Remotely working in response to the COVID-19 pandemic increased the carbon, water, and land footprints of Internet usage. Microplastics are released into our environment from the mishandling and mismanagement of personal protective equipment that endanger our water, soils, and sediments. Since the COVID-19 vaccine cannot be stored for a long time and spoils rapidly, more awareness of the massive waste of unused doses is needed. So COVID-19 is a double-edged sword for the environment.