Interventions to reduce ambient air pollution and their effects on health: An abridged Cochrane systematic review

Cleaning indoor air-what works for respiratory health: An updated literature review and recommendations

Indoor air pollution is a growing public health concern globally and is associated with increased respiratory symptoms and morbidity. Individuals spend most of their time indoors, and pollutant-related health effects are often driven by the indoor environment. Understanding effective interventions to improve indoor air quality and their impact on respiratory outcomes is key to decreasing the burden of air pollution for high-risk populations across the life-span. This review applies a hierarchy of interventions framework specific to respiratory health effects and focuses on recent studies of interventions to improve indoor air quality among high-risk populations with chronic respiratory disease published in the past 3 years. While policy and source control interventions are likely the most effective and equitable approaches to improve indoor air quality and benefit population health, these were less extensively investigated. Engineering interventions, such as air cleaner interventions, were the most widely studied. Several studies, including those focused on asthma and chronic obstructive pulmonary disease, demonstrated improvement in symptoms and medication receipt with interventions in both home- and school-based settings. Combined multilevel interventions with engineering and behavioral interventions led to improved respiratory outcomes in some, but not all, studies. Placing the recent work in the context of the broader literature, we identify gaps in research. Further research is needed to understand intervention effectiveness over time and an increased focus on policy and source control interventions that can mitigate risk in vulnerable populations.

Assessing Adverse Health Effects of Long-Term Exposure to Low Levels of Ambient Air Pollution: The HEI Experience and What's Next?

Although concentrations of ambient air pollution continue to decline in high-income regions, epidemiological studies document adverse health effects at levels below current standards in many countries. The Health Effects Institute (HEI) recently completed a comprehensive research initiative to investigate the health effects of long-term exposure to low levels of air pollution in the United States (U.S.), Canada, and Europe. We provide an overview and synthesis of the results of this initiative along with other key research, the strengths and limitations of the research, and remaining research needs. The three studies funded through the HEI initiative estimated the effects of long-term ambient exposure to fine particulate matter (PM2.5), nitrogen dioxide, ozone, and other pollutants on a broad range of health outcomes, including cause-specific mortality and cardiovascular and respiratory morbidity. To ensure high quality research and comparability across studies, HEI worked actively with the study teams and engaged independent expert panels for project oversight and review. All three studies documented positive associations between mortality and exposure to PM2.5 below the U.S. National Ambient Air Quality Standards and current and proposed European Union limit values. Furthermore, the studies observed nonthreshold linear (U.S.), or supra-linear (Canada and Europe) exposure-response functions for PM2.5 and mortality. Heterogeneity was found in both the magnitude and shape of this association within and across studies. Strengths of the studies included the large populations (7-69 million), state-of-the-art exposure assessment methods, and thorough statistical analyses that applied novel methods. Future work is needed to better understand potential sources of heterogeneity in the findings across studies and regions. Other areas of future work include the changing and evolving nature of PM components and sources, including wildfires, and the role of indoor environments. This research initiative provided important new evidence of the adverse effects of long-term exposures to low levels of air pollution at and below current standards, suggesting that further reductions could yield larger benefits than previously anticipated.

EAACI guidelines on environmental science for allergy and asthma: The impact of short-term exposure to outdoor air pollutants on asthma-related outcomes and recommendations for mitigation measures

The EAACI Guidelines on the impact of short-term exposure to outdoor pollutants on asthma-related outcomes provide recommendations for prevention, patient care and mitigation in a framework supporting rational decisions for healthcare professionals and patients to individualize and improve asthma management and for policymakers and regulators as an evidence-informed reference to help setting legally binding standards and goals for outdoor air quality at international, national and local levels. The Guideline was developed using the GRADE approach and evaluated outdoor pollutants referenced in the current Air Quality Guideline of the World Health Organization as single or mixed pollutants and outdoor pesticides. Short-term exposure to all pollutants evaluated increases the risk of asthma-related adverse outcomes, especially hospital admissions and emergency department visits (moderate certainty of evidence at specific lag days). There is limited evidence for the impact of traffic-related air pollution and outdoor pesticides exposure as well as for the interventions to reduce emissions. Due to the quality of evidence, conditional recommendations were formulated for all pollutants and for the interventions reducing outdoor air pollution. Asthma management counselled by the current EAACI guidelines can improve asthma-related outcomes but global measures for clean air are needed to achieve significant impact.

Knowledge, Attitudes, and Practices Regarding Air Pollution among Medical Students

Background: Air pollution has emerged as a global public health concern. Specifically, in Medellín, Colombia, episodes of elevated air pollution have been documented. Medical students' knowledge of air pollution is paramount for implementing future interventions directed toward patients. The aim of this research was to delineate the knowledge, attitudes, and practices regarding air pollution among medical students at a private university in Medellín. Methods: A cross-sectional study involving 352 medical students was conducted. A questionnaire was administered, generating scores ranging from 0 to 100, where a higher score signified better knowledge, attitudes, and practices. Data were analyzed using frequencies, summary measures, non-parametric tests, and linear regression. Results: In total, 31% rated the education received at the university on the relationship between health and air quality as fair to poor, and 81% perceived the air quality in the city as poor. The knowledge score was 77.8 (IQR 71.1-85.6), with 90% acknowledging that exposure to air pollution increases the risk of various diseases. The attitudes score was 82.1 (IQR 71.8-87.2), and 25.9% believed that air pollution is a multifactorial problem, rendering their actions ineffective. In terms of practices, the score was 50 (IQR 42.9-57.1), indicating that students either did not employ protective measures against pollution or used inappropriate practices such as masks or air purifiers. Regression analysis revealed no association between knowledge and practices. Conclusion: The findings of this study underscore that medical students possess commendable knowledge regarding the health effects of air pollution. However, their adoption of inappropriate practices for self-protection is evident. The lack of correlation between knowledge and practices highlights the necessity of educational initiatives to be complemented by regulatory and cultural interventions.

Associations between long-term exposure to air pollution, diabetes, and hypertension in metropolitan Iran: an ecologic study

Epidemiological studies on air pollution, diabetes, and hypertension conflict. This study examined air pollution, diabetes, and hypertension in adults in 11 metropolitan areas of Iran (2012-2016). Local environment departments and the Tehran Air Quality Control Company provided air quality data. The VIZIT website and Stepwise Approach to Chronic Disease Risk Factor Surveillance study delivered chronic disease data. Multiple logistic regression and generalized estimating equations evaluated air pollution-related diabetes and hypertension. In Isfahan, Ahvaz, and Tehran, PM2.5 was linked to diabetes. In all cities except Urmia, Yasuj, and Yazd, PM2.5 was statistically related to hypertension. O3 was connected to hypertension in Ahvaz, Tehran, and Shiraz, whereas NO2 was not. BMI and gender predict hypertension and diabetes. Diabetes, SBP, and total cholesterol were correlated. Iran's largest cities' poor air quality may promote diabetes and hypertension. PM2.5 impacts many cities' outcomes. Therefore, politicians and specialists have to control air pollution.

Beyond traffic jam alleviation: evaluating the health and health equity impacts of New York City's congestion pricing plan

New York City (NYC) is slated to be the first jurisdiction in the USA to implement a cordon-based congestion tax, which will be levied on vehicles entering its Central Business District. Several cities around the world, for example, London and Stockholm, have had similar cordon-based pricing programmes, defined as road pricing that charges drivers a fee for entering a specified area (typically a congested urban centre). In addition to reducing congestion and creating revenue, projections suggest the NYC congestion pricing plan may yield meaningful traffic-related air quality improvements that could result in health benefits. NYC is a large city with high air pollution and substantial racial/ethnic and socioeconomic health inequities. The distinct geography and meteorological conditions of the city also suggest that the policy's impact on air quality may extend beyond the NYC metropolitan area. As such, the potential breadth, directionality and magnitude of health impacts on communities who might be heavily affected by the nation's first congestion pricing plan should be empirically investigated. We briefly review evaluation studies of other cordon-based congestion pricing policies and argue that implementation of this policy provides an excellent opportunity to employ a quasi-experimental study design to evaluate the policy's impacts on air quality and health outcomes across population subgroups using a health equity lens. We discuss why real-time evaluations of the NYC congestion pricing plan can potentially help optimise benefits for communities historically negatively affected by traffic-related air pollution. Assessing intended and unintended impacts on health equity is key to achieving these goals.

Toward Better and Healthier Air Quality: Global PM2.5 and O3 Pollution Status and Risk Assessment Based on the New WHO Air Quality Guidelines for 2021

To reduce the high burden of disease caused by air pollution, the World Health Organization (WHO) released new Air Quality Guidelines (AQG) on September 22, 2021. In this study, the daily fine particulate matter (PM2.5) and surface ozone (O3) data of 618 cities around the world is collected from 2019 to 2022. Based on the new AQG, the number of attainment days for daily average concentrations of PM2.5 (≤ 15 µg m-3) and O3 (≤ 100 µg m-3) is approximately 10% and 90%, respectively. China and India exhibit a decreasing trend in the number of highly polluted days (> 75 µg m-3) for PM. Every year over 68% and 27% of cities in the world are exposed to harmful PM2.5 (> 35 µg m-3) and O3 (> 100 µg m-3) pollution, respectively. Combined with the United Nations Sustainable Development Goals (SDGs), it is found that more than 35% of the world's cities face PM2.5-O3 compound pollution. Furthermore, the exposure risks in these cities (China, India, etc.) are mainly categorized as "High Risk", "Risk", and "Stabilization". In contrast, economically developed cities are mainly categorized as "High Safety", "Safety", and "Deep Stabilization." These findings indicate that global implementation of the WHO's new AQG will minimize the inequitable exposure risk from air pollution.

Disease burden of COPD attributable to PM2.5 in China, Japan and South Korea from 1990 to 2019: a comparative study based on Global Burden of Disease Study 2019

OBJECTIVE

We hope to reveal the changing trends of chronic obstructive pulmonary disease (COPD) burden attributable to particulate matter pollution (PM2.5) and its age, period and cohort effects in China, Japan and Korea.

DESIGN

We analysed the trend of COPD disease burden attributable to PM2.5 from 1990 to 2019 based on the latest Global Burden of Disease Database (GBD 2019) using JoinPoint model and analysed the effect of age, period and cohort on COPD burden attributable to PM2.5 in China, Japan and Korea from 1990 to 2019 using age-period-cohort model (model).

SETTING

GBD data from 1990 to 2019.

PARTICIPANTS

Data were publicly available and individuals were not involved.

MAIN OUTCOMES

Outcomes included the age standardised mortality rate (ASMR), the age-standardised disability-adjusted life year (DALY), average annual per cent change (AAPC), net drift, local drift, longitudinal age curves, period (cohort) rate ratios, age (period, cohort) bias coefficient.

RESULTS

From 1990 to 2019, the ASMR of COPD attributable to PM2.5 in China (AAPC=-5.862), Japan (AAPC=-1.715) and Korea (AAPC=-1.831) showed a downward trend. The age-standardised DALY of COPD attributable to PM2.5 in China (AAPC=-5.821), Japan (AAPC=-1.39) and Korea (AAPC=-1.239) showed a downward trend. Mortality of COPD attributable to PM2.5 increased slowly with age in Korea and Japan. Mortality of COPD attributable to PM2.5 in China decreased after rising (95% CI: 404.66 to 466.01). Mortality of COPD attributable to PM2.5 decreased over time in China and Korea, while it increased in Japan from 2015 to 2019. In China and Japan, mortality of COPD attributable to PM2.5 was approximately lower the later the birth, while in Korea it decreased after an increase (95% CI: 2.13 to 2.40) in the 1900-1910.

CONCLUSIONS

Most COPD burden attributable to PM2.5 is on the decline; COPD mortality attributable to PM2.5 both increased with age and decreased with time and cohort. Countries with high burden should develop targeted measures to control PM2.5.

Cardiovascular diseases burden attributable to ambient PM2.5 pollution from 1990 to 2019: A systematic analysis for the global burden of disease study 2019

BACKGROUND

Ambient PM2.5 pollution (APMP2.5) was the leading environmental risk factor for cardiovascular diseases (CVDs) worldwide. An up-to-date comprehensive study is needed to provide global epidemiological patterns.

METHODS

Detailed data on CVDs burden attributable to APMP2.5 were obtained from the Global Burden of Disease Study (GBD) 2019. We calculated the estimated annual percentage change (EAPC) to assess temporal trends in age-standardized rates of deaths and disability-adjusted life years (DALYs) over 30 years.

RESULTS

Globally, CVDs attributable to APMP2.5 resulted in 2.48 million deaths and 60.91 million DALYs, with an increase of 122%, respectively from 1990 to 2019. In general, men suffered markedly higher burden than women, but the gap will likely turn narrow. As for age distribution, CVDs deaths and DALYs attributable to APMP2.5 mainly occurred in the elder group (>70 years). Low- and middle-income regions endured the higher CVDs burden due to the higher exposure to APMP2.5, and the gap may potentially expand further compared with high-income regions. For regions, the highest age-standardized rates of APMP2.5-related CVDs deaths and DALYs were observed mainly in Central Asia, while the lowest was observed in Australasia. At the national level, countries with the largest ASDR decline were clustered in western Europe, while Equatorial Guinea, Timor-Leste and Bhutan exhibited relatively rapid increases over this period.

CONCLUSIONS

The global CVDs burden attributable to APMP2.5 has contributed to the heterogeneity of spatial and temporal distribution. APMP2.5-related CVDs deaths have largely shifted from higher SDI regions to those with a lower SDI. Globally, APMP2.5-attributable CVDs pose a significant threat to public health and diseases burden has increased over time, particularly in male, old-aged populations. The governments and health systems should take measures to reduce air pollution to impede this rising trend.

Particulate Matter and Its Impact on Macrophages: Unraveling the Cellular Response for Environmental Health

Particulate matter (PM) imposes a significant impact to environmental health with deleterious effects on the human pulmonary and cardiovascular systems. Macrophages (Mφ), key immune cells in lung tissues, have a prominent role in responding to inhaled cells, accommodating inflammation, and influencing tissue repair processes. Elucidating the critical cellular responses of Mφ to PM exposure is essential to understand the mechanisms underlying PM-induced health effects. The present review aims to give a glimpse on literature about the PM interaction with Mφ, triggering the cellular events causing the inflammation, oxidative stress (OS) and tissue damage. The present paper reviews the different pathways involved in Mφ activation upon PM exposure, including phagocytosis, intracellular signaling cascades, and the release of pro-inflammatory mediators. Potential therapeutic strategies targeting Mφ-mediated responses to reduce PM-induced health effects are also discussed. Overall, unraveling the complex interplay between PM and Mφ sheds light on new avenues for environmental health research and promises to develop targeted interventions to reduce the burden of PM-related diseases on global health.

Causal reasoning about epidemiological associations in conversational AI

We present a Socratic dialogue with ChatGPT, a large language model (LLM), on the causal interpretation of epidemiological associations between fine particulate matter (PM2.5) and human mortality risks. ChatGPT, reflecting probable patterns of human reasoning and argumentation in the sources on which it has been trained, initially holds that "It is well-established that exposure to ambient levels of PM2.5 does increase mortality risk" and adds the unsolicited remark that "Reducing exposure to PM2.5 is an important public health priority." After patient questioning, however, it concludes that "It is not known with certainty that current ambient levels of PM2.5 increase mortality risk. While there is strong evidence of an association between PM2.5 and mortality risk, the causal nature of this association remains uncertain due to the possibility of omitted confounders." This revised evaluation of the evidence suggests the potential value of sustained questioning in refining and improving both the types of human reasoning and argumentation imitated by current LLMs and the reliability of the initial conclusions expressed by current LLMs.

Assessing capabilities of conducted ambient air pollution health effects studies in 22 Eastern Mediterranean countries to adopt air quality standards: a review

Purpose

The Eastern Mediterranean Region (EMR) countries suffer from exposure to high levels of ambient air pollutants due to dust storms and have unique climatic as well as topographic and socio-economic conditions which lead to adverse health effects on humans. The purpose of the review was to evaluate the quantity and quality of published articles on air pollution and health-based studies in 22 EMR countries to determine if they can be applied to adopting air quality standards.

Methods

We designed a review based on a broad search of the literature in the Scopus, PubMed, and web of science (WOS) databases published from January 1, 2000, to January 2, 2022, using combinations of the following relevant terms: air pollution, health, and EMR countries. The generic eligibility criteria for this review were based on the population, exposure, comparator, outcome, and study design (PECOS) statement.

Results

The search results showed that following the PRISMA approach, of 2947 identified articles, 353 studies were included in this review. The analysis of the types of studies showed that about 70% of the studies conducted in EMR countries were Health Burden Estimation studies (31%), Ecological and time trend ecological studies (23%), and cross-sectional studies (16%). Also, researchers from Iran participated in the most published relevant studies in the region 255 (~ 63%) and just 10 published documents met all the PECOS criteria.

Conclusion

The lack of sufficient studies which can meet the PECOS appraising criteria and the lack of professionals in this field are some of the issues that make it impossible to use as potential documents in the WHO future studies and adopt air quality standards.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-023-00862-1.

[A geriatric perspective on the sixth IPCC synthesis report]

Climate change brings with it many foreseeable consequences for ecosystems and populations, including health consequences that could have a particular impact on older populations. Extreme climatic events, including heat waves, are associated with higher morbidity and mortality among the elderly. Air pollution has a deleterious effect on illnesses associated with aging, or which become more frequent with age. The health consequences of climate change must be anticipated, as they will require the adaptation of healthcare systems, which could be of particular interest to geriatric medicine.

Improving interventional causal predictions in regulatory risk assessment

In 2022, the US EPA published an important risk assessment concluding that "Compared to the current annual standard, meeting a revised annual standard with a lower level is estimated to reduce PM2.5-associated health risks in the 30 annually-controlled study areas by about 7-9% for a level of 11.0 µg/m3… and 30-37% for a level of 8.0 µg/m3." These are interventional causal predictions: they predict percentage reductions in mortality risks caused by different counterfactual reductions in fine particulate (PM2.5) levels. Valid causal predictions are possible if: (1) Study designs are used that can support valid causal inferences about the effects of interventions (e.g., quasi-experiments with appropriate control groups); (2) Appropriate causal models and methods are used to analyze the data; (3) Model assumptions are satisfied (at least approximately); and (4) Non-causal sources of exposure-response associations such as confounding, measurement error, and model misspecification are appropriately modeled and adjusted for. This paper examines two long-term mortality studies selected by the EPA to predict reductions in PM2.5-associated risk. Both papers use Cox proportional hazards (PH) models. For these models, none of these four conditions is satisfied, making it difficult to interpret or validate their causal predictions. Scientists, reviewers, regulators, and members of the public can benefit from more trustworthy and credible risk assessments and causal predictions by insisting that risk assessments supporting interventional causal conclusions be based on study designs, methods, and models that are appropriate for predicting effects caused by interventions.

Re-assessing human mortality risks attributed to PM2.5-mediated effects of agricultural ammonia

How can and should epidemiologists and risk assessors assemble and present evidence for causation of mortality or morbidities by identified agents such as fine particulate matter or other air pollutants? As a motivating example, some scientists have warned recently that ammonia from the production of meat significantly increases human mortality rates in exposed populations by increasing the ambient concentration of fine particulate matter (PM2.5) in air. We reexamine the support for such conclusions, including quantitative calculations that attribute deaths to PM2.5 air pollution by applying associational results such as relative risks, odds ratios, or slope coefficients from regression models to predict the effects on mortality or morbidity of reducing PM2.5 exposures. Taking an outside perspective from the field of causal artificial intelligence (CAI), we conclude that these attribution calculations are methodologically unsound. They produce unreliable conclusions because they ignore an essential distinction between differences in outcomes observed at different levels of exposure and changes in outcomes caused by changing exposure. We find that multiple studies that have examined associations between changes over time in particulate exposure and mortality risk instead of differences in exposures and corresponding mortality risks have found no clear evidence that observed changes in exposure help to predict or explain subsequent changes in mortality risks. We conclude that there is no sound theoretical or empirical reason to believe that reducing ammonia emissions from farms has reduced or would reduce human mortality risks. More generally, applying CAI principles and methods can potentially improve current widespread practices of unsound causal inferences and policy-relevant causal claims that are made without the benefit of formal causal analysis in air pollution health effects research and in other areas of applied epidemiology and public health risk assessment.

Detecting high emitting vehicle subsets using emission remote sensing systems

It is often assumed that a small proportion of a given vehicle fleet produces a disproportionate amount of air pollution emissions. If true, policy actions to target the highly polluting section of the fleet could lead to significant improvements in air quality. In this paper, high-emitter vehicle subsets are defined and their contributions to the total fleet emission are assessed. A new approach, using enrichment factor in cumulative Pareto analysis is proposed for detecting high emitter vehicle subsets within the vehicle fleet. A large dataset (over 94,000 remote-sensing measurements) from five UK-based EDAR (emission detecting and reporting system) field campaigns for the years 2016-17 is used as the test data. In addition to discussions about the high emitter screening criteria, the data analysis procedure and future issues of implementation are discussed. The results show different high emitter trends dependent on the pollutant investigated, and the vehicle type investigated. For example, the analysis indicates that 23 % and 51 % of petrol and diesel cars were responsible for 80 % of NO emissions within that subset of the fleet, respectively. Overall, the contributions of vehicles that account for 80 % of total fleet emissions usually reduce with EURO class improvement, with the subset fleet emissions becoming more homogenous. The high emitter constituent was more noticeable for pollutant PM compared with the other gaseous pollutants, and it was also more prominent for petrol cars when compared to diesel ones.

School-Based Interventions to Support Healthy Indoor and Outdoor Environments for Children: A Systematic Review

Environmental exposures are associated with children's health. Schools are often urban exposure 'hotspots' for pollution, noise, lack of green space and un-walkable built environments. The aim of this systematic review was to explore the impact of school-based interventions on the modification of indoor and outdoor stressors related to the built and natural environment on children's exposure and health. A systematic review of seven databases was performed. We included quantitative studies on children aged 5-12, which reported intervention delivered within school settings aimed at addressing key environmental exposures including air pollution, green spaces, traffic noise or active travel; and reported physical and mental health, physical activity or active travel behavior. The quality of studies was assessed and interventions were described using a standardized framework. A narrative synthesis approach was used to describe the findings. Thirty-nine papers were included on three main intervention types: improve indoor air quality by the increase of ventilation rates in classrooms; increase children's green time or greening schools, and multicomponent interventions to increase active travel to school by changes in pedestrian facilities. No eligible intervention to reduce traffic noise at school was found. Increasing ventilation rates improved short-term indoor air quality in classrooms, but the effect on cognitive performance was inconsistent. Greening schools and increasing children's green time have consistent positive effects on cognition and physical activity, but not in behavior. Multi-component interventions can increase walking and cycling after three years. Overall, the studies were rated as having poor quality owing to weak study designs. We found modest evidence that school-based built and natural environment interventions can improve children's exposure and health.

Triggering of ST-elevation myocardial infarction by ultrafine particles in New York: Changes following Tier 3 vehicle introduction

BACKGROUND

Previously, we found increased rates of ST-elevation myocardial infarction (STEMI) associated with increased ultrafine particle (UFP; <100 nm) concentrations in the previous few hours in Rochester, New York. Relative rates were higher after air quality policies and a recession reduced pollutant concentrations (2014-2016 versus 2005-2013), suggesting PM composition had changed and the same PM mass concentration had become more toxic. Tier 3 light duty vehicles, which should produce less primary organic aerosols and oxidizable gaseous compounds, likely making PM less toxic, were introduced in 2017. Thus, we hypothesized we would observe a lower relative STEMI rate in 2017-2019 than 2014-2016.

METHODS

Using STEMI events treated at the University of Rochester Medical Center (2014-2019), UFP and other pollutants measured in Rochester, a case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increased UFP and other pollutants in the previous hours and days in the 2014-2016 and 2017-2019 periods.

RESULTS

An increased rate of STEMI was associated with each 3111 particles/cm³ increase in UFP concentration in the previous hour in 2014-2016 (lag hour 0: OR = 1.22; 95% CI = 1.06, 1.39), but not in 2017-2019 (OR = 0.94; 95% CI = 0.80, 1.10). There were similar patterns for black carbon, UFP_11-50nm, and UFP_51-100nm. In contrast, increased rates of STEMI were associated with each 0.6 ppb increase in SO₂ concentration in the previous 120 h in both periods (2014-2016: OR = 1.26, 95% CI = 1.03, 1.55; 2017-2019: OR = 1.21, 95% CI = 0.87, 1.68).

CONCLUSIONS

Greater rates of STEMI were associated with short term increases in concentrations of UFP and other motor vehicle related pollutants before Tier 3 introduction (2014-2016), but not afterwards (2017-2019). This change may be due to changes in PM composition after Tier 3 introduction, as well as to increased exposure misclassification and greater underestimation of effects from 2017 to 2019.

Air Pollution and the Heart: Updated Evidence from Meta-analysis Studies

PURPOSE OF REVIEW

Although environmental exposure such as air pollution is detrimental to cardiovascular disease (CVD), the effects of different air pollutants on different CVD endpoints produced variable findings. We provide updated evidence between air pollutants and CVD outcomes including mitigation strategies with meta-analytic evidence.

RECENT FINDINGS

An increased exposure to any class of air pollutants including particulate matter (PM), gas, toxic metals, and disruptive chemicals has been associated with CVD events. Exposure to PM < 2.5 μm has been consistently associated with most heart diseases and stroke as well as CVDs among at-risk individuals. Despite this, there is no clinical approach available for systemic evaluation of air pollution exposure and management. A large number of epidemiological evidence clearly suggests the importance of air pollution prevention and control for reducing the risk of CVDs and mortality. Cost-effective and feasible strategies for air pollution monitoring, screening, and necessary interventions are urgently required among at-risk populations and those living or working, or frequently commuting in polluted areas.

Health Equity Impact Assessment Related to Air Pollution Reduction

Despite considerable improvements in terms of prevention, management, and regulation, air pollution remains a leading environmental health issue worldwide [...].

Engaging communities in addressing air quality: a scoping review

BACKGROUND

Exposure to air pollution has a detrimental effect on health and disproportionately affects people living in socio-economically disadvantaged areas. Engaging with communities to identify concerns and solutions could support organisations responsible for air quality control, improve environmental decision-making, and widen understanding of air quality issues associated with health. This scoping review aimed to provide an overview of approaches used to engage communities in addressing air quality and identify the outcomes that have been achieved.

METHODS

Searches for studies that described community engagement in air quality activities were conducted across five databases (Academic Search Complete, CABI, GreenFILE, MEDLINE, Web of Science). Data on study characteristics, community engagement approach, and relevant outcomes were extracted. The review process was informed by a multi-stakeholder group with an interest in and experience of community engagement in air quality. Thirty-nine papers from thirty studies were included in the final synthesis.

CONCLUSION

A range of approaches have been used to engage communities in addressing air quality, most notably air quality monitoring. Positive outcomes included increased awareness, capacity building, and changes to organisational policy and practice. Longer-term projects and further exploration of the impact of community engagement on improving air quality and health are needed as reporting on these outcomes was limited.

Air pollution and lung cancer survival in Pennsylvania

OBJECTIVE

Lung cancer is a leading cause of cancer death in the United States. Exposure to outdoor air pollution (OAP) is associated with increased lung cancer incidence, however little is known about the association of OAP and survival after diagnosis.

METHODS

We investigated the effects of OAP and lung cancer survival in Pennsylvania using data from Pennsylvania Cancer Registry. The study population consisted of 252,123 patients diagnosed between 1990 and 2017. The Environmental Protection Agency's ambient air monitoring network provided information on OAP exposure of NO₂, O₃, PM_2.5, and PM₁₀. Mean OAP exposures were calculated by interpolating exposure concentrations from the five nearest monitors within a 50-kilometer radius of each patient's residential address from date of diagnosis to date of death or last contact. Cox proportional-hazards models were used to estimate the hazard ratios (HR) for OAP exposures for overall and lung cancer-specific survival. Statistical analyses were stratified by SEER cancer stage groupings (localized, regional, and distant) and adjusted for individual-level and area-level covariates.

RESULTS

Median survival time was 0.76 [CIs: 0.75, 0.77] years for the study population and for localized, regional, and distant site diagnosis were 2.2 [CIs: 2.17, 2.23], 1.13 [CIs: 1.12, 1.15], and 0.42 [CIs: 0.41, 0.43] years, respectively. NO₂ indicated the greatest HR which increased with increasing magnitude of exposure across all cancer staging groups for deaths before 2-years post-diagnosis. HRs varied by stage and magnitude of OAP exposure with greatest overall effects shown in NO₂ followed by PM_2.5, O_3, and PM₁₀. A subgroup analysis of patients with treatment status information (2010-2017) showed similar associations of increasing HRs with increasing exposure.

CONCLUSION

These findings supported the hypotheses that OAP can influence the carcinogenic process, impairing chemotherapy treatment, and provide important public health implications since environmental factors are not often considered in prognosis of survival after diagnosis.

State of ambient air quality in a low-income urban settlement of South Africa

Air pollution remains one of the leading global environmental-health challenges the world is facing today, particularly within urban environments. amidst the COVID-19 pandemic, air pollution has been brought back into the spotlight as both attack the human respiratory systems. The purpose of the study was to investigate the quality of ambient air in a low-income urban settlement of Jabavu located within the City of Johannesburg during the year 2018. Air pollution and meteorological data were gathered from the South African Air Quality System network. The study focused on three pollutants namely PM₁₀, SO₂ and O₃. Findings were that the seasonal ambient mean concentrations for PM₁₀ in summer was (28.99 µg/m³), autumn (33.32 µg/m³), winter (61.71 µg/m³) and spring (48.44 µg/m³). On the other hand, the seasonal ambient mean concentrations for SO₂ was summer (4.45ppb), autumn (3.19ppb), winter (5.65ppb) and spring (3.54ppb). The O₃ seasonal ambient mean concentrations were summer (40.97ppb), autumn (21.01ppb), winter (15.90ppb) and spring (33.59ppb). Furthermore, the study observed that in summer, winter and spring the dominant long-range transport air masses originated from the South Atlantic Ocean, Madagascar Island-India Ocean and the Indian Ocean while in autumn the dominant air masses are short-range inland air masses. For SO₂ and PM_10, ambient concentrations were found to be more problematic during winter; while for O₃ substantial levels were unexpectedly recorded in summer. When analysing the diurnal profiles of PM₁₀, SO₂ and O_3, each of these pollutants revealed a unique distribution pattern, which, despite having seasonal variance, was consistent throughout the year. For instance, irrespective of the season, PM₁₀ mostly peaked in the mornings and evenings; meanwhile SO₂ and O₃ often spiked during the midday and mid-afternoon, respectively. These findings indicate that air quality within this low-income settlement is poor. To improve air quality within low-income settlements there is a need for a shift from reliance on solid fuels to cleaner energy sources such as LP gas, biogas and solar accompanied by an increase in community awareness about air quality issues. This study contributes to knowledge building within the air quality monitoring scientific community while for policymakers it assists in policy formulation to enable air quality management.

A spatiotemporal analysis of NO 2 concentrations during the Italian 2020 COVID-19 lockdown

When a new environmental policy or a specific intervention is taken in order to improve air quality, it is paramount to assess and quantify-in space and time-the effectiveness of the adopted strategy. The lockdown measures taken worldwide in 2020 to reduce the spread of the SARS-CoV-2 virus can be envisioned as a policy intervention with an indirect effect on air quality. In this paper we propose a statistical spatiotemporal model as a tool for intervention analysis, able to take into account the effect of weather and other confounding factor, as well as the spatial and temporal correlation existing in the data. In particular, we focus here on the 2019/2020 relative change in nitrogen dioxide (NO2 ) concentrations in the north of Italy, for the period of March and April during which the lockdown measure was in force. We found that during March and April 2020 most of the studied area is characterized by negative relative changes (median values around - 25%), with the exception of the first week of March and the fourth week of April (median values around 5%). As these changes cannot be attributed to a weather effect, it is likely that they are a byproduct of the lockdown measures. There are two aspects of our research that are equally interesting. First, we provide a unique statistical perspective for calculating the relative change in the NO2 by jointly modeling pollutant concentrations time series. Second, as an output we provide a collection of weekly continuous maps, describing the spatial pattern of the NO2 2019/2020 relative changes.

Global burden of chronic obstructive pulmonary disease attributable to ambient particulate matter pollution and household air pollution from solid fuels from 1990 to 2019

We aimed to estimate the spatiotemporal trends in the global burden of chronic obstructive pulmonary disease (COPD) attributable to both household air pollution from solid fuels (HAP) and ambient particulate matter (APM) from 1990 to 2019 and compared the possible differences between the burdens attributable to APM and HAP. The number of deaths, disability-adjusted life-years (DALYs), and years of life lost (YLLs) of COPD attributable to HAP from solid fuels and APM during 1990-2019 were extracted from the Global Burden of Diseases Study 2019. The proportion of YLLs in DALYs and average YLLs per COPD death were also calculated. Subgroup analyses by sex, age, and socio-demographic index (SDI) were conducted. The estimated annual percentage change (EAPC) was used to assess the temporal trend of age-standardized rate of mortality (ASMR) and DALYs (ASDR). Over the past 30 years, we observed a clear downward trend in COPD deaths attributable to HAP and an upward trend by 97.61% in COPD deaths attributable to APM. The global COPD burden attributable to APM in 2019 was higher than those due to HAP, except in low-SDI regions. For both HAP and APM, YLLs continued to predominate in DALYs of COPD, with an average YLLs per death of more than 10 years in different regions. The ASMR was higher in males and lower in high-SDI regions. The ASMR and ASDR attributable to HAP decreased globally in all age groups during 1990-2019, while those attributable to APM increased among people older than 80 years and in regions with lower SDI. Our study reveals an increasing trend in APM-attributable COPD burden over the past three decades. Comparatively, the global burden due to HAP decreased markedly, but it was still pronounced in low-SDI regions. Continued efforts on PM mitigation are needed for COPD prevention.

Effects of short-term increases in personal and ambient pollutant concentrations on pulmonary and cardiovascular function: A panel study analysis of the Multicenter Ozone Study in oldEr subjects (MOSES 2)

BACKGROUND

The cardiovascular effects of ozone exposure are unclear. Using measurements from the 87 participants in the Multicenter Ozone Study of oldEr Subjects (MOSES), we examined whether personal and ambient pollutant exposures before the controlled exposure sessions would be associated with adverse changes in pulmonary and cardiovascular function.

METHODS

We used mixed effects linear regression to evaluate associations between increased personal exposures and ambient pollutant concentrations in the 96 h before the pre-exposure visit, and 1) biomarkers measured at pre-exposure, and 2) changes in biomarkers from pre-to post-exposure.

RESULTS

Decreases in pre-exposure forced expiratory volume in 1 s (FEV₁) were associated with interquartile-range increases in concentrations of particulate matter ≤2.5 μm (PM_2.5) 1 h before the pre-exposure visit (-0.022 L; 95% CI -0.037 to -0.006; p = 0.007), carbon monoxide (CO) in the prior 3 h (-0.046 L; 95% CI -0.076 to -0.016; p = 0.003), and nitrogen dioxide (NO₂) in the prior 72 h (-0.030 L; 95% CI -0.052 to -0.008; p = 0.007). From pre-to post-exposure, increases in FEV₁ were marginally significantly associated with increases in personal ozone exposure (0.010 L; 95% CI 0.004 to 0.026; p = 0.010), and ambient PM_2.5 and CO at all lag times. Ambient ozone concentrations in the prior 96 h were associated with both decreased pre-exposure high frequency (HF) heart rate variability (HRV) and increases in HF HRV from pre-to post-exposure.

CONCLUSIONS

We observed associations between increased ambient PM_2.5, NO₂, and CO levels and reduced pulmonary function, and increased ambient ozone concentrations and reduced HRV. Pulmonary function and HRV increased across the exposure sessions in association with these same pollutant increases, suggesting a "recovery" during the exposure sessions. These findings support an association between short term increases in ambient PM_2.5, NO₂, and CO and decreased pulmonary function, and increased ambient ozone and decreased HRV.

Health effects in people relocating between environments of differing ambient air pollution concentrations: A literature review

People who relocate to a new environment may experience health effects from a change in ambient air pollution. We undertook a literature review of studies of such relocations and health effects and report the results as a narrative analysis. Fifteen articles of heterogeneous designs met the inclusion criteria. Four short-term (relocation duration less than six months) and three long-term (relocation duration six months or greater) studies reported evidence of the effect of relocation on physiological outcome, biomarkers or symptoms. All had potential weaknesses of design or analysis but, as a whole, their results are broadly consistent in suggesting short-term adverse effects of air pollutants or their reversibility. One long-term study provided evidence that changes in air pollution exposure during adolescence have a measurable effect on lung function growth. Four cohort studies were also identified that used relocation to strengthen evidence of air-pollution-exposure relationships by using a design that incorporates effective randomization of exposure or the use of relocation to improve exposure classification. However, three studies of relocation during pregnancy provided limited evidence to conclude an effect of relocation-related change in exposure on pregnancy outcome. Overall, most relocation studies are consistent with short- or long-term adverse effects of air pollution on biological function or mortality, but many studies of change in exposure have design weaknesses that limit the robustness of interpretation. We outline principles for improved design and analysis to help strengthen future studies for the insights they can provide from their quasi-experimental designs, including on the nature and timing of functional changes of relocation-related changes in exposure to ambient air pollution.

Multi-antibiotic resistant bacteria in landfill bioaerosols: Environmental conditions and biological risk assessment

Landfills, as well as other waste management facilities are well-known bioaerosols sources. These places may foment antibiotic-resistance in bacterial bioaerosol (A.R.B.) due to inadequate pharmaceutical waste disposal. This issue may foster the necessity of using last-generation antibiotics with extra costs in the health care system, and deaths. The aim of this study was to reveal the multi-antibiotic resistant bacterial bioaerosol emitted by a sanitary landfill and the surrounding area. We evaluated the influence of environmental conditions in the occurrence of A.R.B. and biological risk assessment. Antibiotic resistance found in the bacteria aerosols was compared with the AWaRE consumption classification. We used the BIOGAVAL method to assess the workers' occupational exposure to antibiotic-resistant bacterial bioaerosols in the landfill. This study confirmed the multi-antibiotic resistant in bacterial bioaerosol in a landfill and in the surrounding area. Obtained mean concentrations of bacterial bioaerosols, as well as antibiotic-resistant in bacterial bioaerosol (A.R.B.), were high, especially for fine particles that may be a threat for human health. Results suggest the possible risk of antibiotic-resistance interchange between pathogenic and non-pathogenic species in the landfill facilities, thus promoting antibiotic multi-resistance genes spreading into the environment.

Commentary: Using potential outcomes causal methods to assess whether reductions in PM2.5 result in decreased mortality

Causal inference regarding exposures to ambient fine particulate matter (PM2.5) and mortality estimated from observational studies is limited by confounding, among other factors. In light of a variety of causal inference frameworks and methods that have been developed over the past century to specifically quantify causal effects, three research teams were selected in 2016 to evaluate the causality of PM2.5-mortality association among Medicare beneficiaries, using their own selections of causal inference methods and study designs but the same data sources. With a particular focus on controlling for unmeasured confounding, two research teams adopted an instrumental variables approach under a quasi-experiment or natural experiment study design, whereas one team adopted a structural nested mean model under the traditional cohort study design. All three research teams reported results supporting an estimated counterfactual causal relationship between ambient PM2.5 and all-cause mortality, and their estimated causal relationships are largely of similar magnitudes to recent epidemiological studies based on regression analyses with omitted potential confounders. The causal methods used by all three research teams were built upon the potential outcomes framework. This framework has marked conceptual advantages over regression-based methods in addressing confounding and yielding unbiased estimates of average treatment effect in observational epidemiological studies. However, potential violations of the unverifiable assumptions underlying each causal method leave the results from all three studies subject to biases. We also note that the studies are not immune to some other common sources of bias, including exposure measurement errors, ecological study design, model uncertainty and specification errors, and irrelevant exposure windows, that can undermine the validity of causal inferences in observational studies. As a result, despite some apparent consistency of study results from the three research teams with the wider epidemiological literature on PM2.5-mortality statistical associations, caution seems warranted in drawing causal conclusions from the results. A possible way forward is to improve study design and reduce dependence of conclusions on untested assumptions by complementing potential outcomes methods with structural causal modeling and information-theoretic methods that emphasize empirically tested and validated relationships.

Application of the Bayesian spline method to analyze real-time measurements of ultrafine particle concentration in the Parisian subway

BACKGROUND

Air pollution in subway environments is a growing concern as it often exceeds WHO recommendations for indoor air quality. Ultrafine particles (UFP), for which there is still no regulation nor a standardized exposure monitoring method, are the strongest contributor to this pollution when the number concentration is used as exposure metric.

OBJECTIVES

We aimed to assess the real-time UFP number concentration in the personal breathing zone (PBZ) of three types of underground Parisian subway professionals and analyze it using a novel Bayesian spline approach. Consecutively, we investigated the effect of job, week day, subway station, worker location, and some further events on UFP number concentrations.

METHODS

The data collection procedure originated from a longitudinal study and lasted for a total duration of 6 weeks (from October 7 to November 15, 2019, i.e. two weeks per type of subway professionals). Time-series were built from the real-time particle number concentration (PNC) measured in the PBZ of professionals during their work-shifts. Complementarily, contextual information expressed as Station, Environment, and Event variables were extracted from activity logbooks completed for every work-shift. A Bayesian spline approach was applied to model the PNC within a Bayesian framework as a function of the mentioned contextual information.

RESULTS

Overall, the Bayesian spline method suited a real-time personal PNC data modeling approach. The model enabled estimating the differences in UFP exposure between subway professionals, stations, and various locations. Our results suggest a higher PNC closer to the subway tracks, with the highest PNC on subway station platforms. Studied event and week day variables had a lesser influence.

CONCLUSION

It was shown that the Bayesian spline method is suitable to investigate individual exposure to UFP in underground subway settings. This method is informative for better documenting the magnitude and variability of UFP exposure, and for understanding the determinants in view of further regulation and control of this exposure.

Toward practical causal epidemiology

Population attributable fraction (PAF), probability of causation, burden of disease, and related quantities derived from relative risk ratios are widely used in applied epidemiology and health risk analysis to quantify the extent to which reducing or eliminating exposures would reduce disease risks. This causal interpretation conflates association with causation. It has sometimes led to demonstrably mistaken predictions and ineffective risk management recommendations. Causal artificial intelligence (CAI) methods developed at the intersection of many scientific disciplines over the past century instead use quantitative high-level descriptions of networks of causal mechanisms (typically represented by conditional probability tables or structural equations) to predict the effects caused by interventions. We summarize these developments and discuss how CAI methods can be applied to realistically imperfect data and knowledge - e.g., with unobserved (latent) variables, missing data, measurement errors, interindividual heterogeneity in exposure-response functions, and model uncertainty. We recommend that CAI methods can help to improve the conceptual foundations and practical value of epidemiological calculations by replacing association-based attributions of risk to exposures or other risk factors with causal predictions of the changes in health effects caused by interventions.

Particle and metal exposure in Parisian subway: Relationship between exposure biomarkers in air, exhaled breath condensate, and urine

Subway particulate toxicity results from in vitro and in vivo studies diverge and call for applied human research on outcomes from chronic exposures and potential exposure biomarkers. We aimed to (1) quantify airborne particulate matter (PM) concentrations (mass and number) and metal concentrations in exhaled breath condensate (EBC), urine, and PM; (2) investigate their associations (EBC vs. PM vs. urine); and (3) assess the relevance of EBC in biomonitoring. Nine subway workers in three jobs: station agents, locomotive operators and security guards were monitored during their 6-h shifts over two consecutive weeks. Six-hour weighed average mass concentrations expressed as PM10, PM2.5 and their metal concentrations were determined. Urine and EBC samples were collected pre- and post-shift. Ultrafine particle (UFP) number concentrations were quantified in PM and EBC samples. Metal concentrations in urine and EBC were standardized by creatinine and EBC volume, respectively, and log-transformed. Associations were investigated using Pearson correlation and linear mixed regression models, with participant's ID as random effect. PM concentrations were below occupational exposure limits (OEL) and varied significantly between jobs. Locomotive operators had the highest exposure (189 and 137 μg/m³ for PM10 and PM2.5, respectively), while station agents had the highest UFP exposure (1.97 × 10⁴ particles/cm³). Five metals (Al, Fe, Zn, Cu, and Mn) in PM2.5 and three (Al, Fe, and Zn) in PM10 were above the limit of quantification (LOQ). Fe, Cu, Al and Zn were the most abundant by mass fraction in PM. In EBC, the metal concentrations in decreasing order were: Zn > Cu > Ni > Ba > Mn. Security guards had the highest EBC metal concentrations, and in particular Zn and Cu. Urinary metal concentrations in decreasing order were: Si > Zn > Mo > Ti > Cu > Ba ≈ Ni > Co. All urinary metal concentrations from the subway workers were similar to concentrations found in the general population. A statistically significant relationship was found for ultrafine particle number concentrations in PM and in EBC. Zn and Cu concentrations in post-shift EBC were associated with Zn and Cu concentrations in PM10 and with post-shift urinary Zn and Cu concentrations. Therefore, EBC appears a relevant matrix for assessing exposure to UFP in human biomonitoring when inhalation is a primary route of exposure. We found different temporal variation patterns between particle and metal exposures in three matrices (PM, urine, EBC) quantified daily over two full weeks in subway workers. These patterns might be related to metal oxidation, particulates' solubility and size as well as their lung absorption capabilities, which need to be further explored in toxicological research. Further research should also focus on understanding possible influences of low chronic exposures to subway particulates on health in larger cohorts.

Indoor Air Quality Strategies for Air-Conditioning and Ventilation Systems with the Spread of the Global Coronavirus (COVID-19) Epidemic: Improvements and Recommendations

The coronavirus has come to the world and spread with great wide among the countries of the world and has resulted in numerous infections that exceeded 167,181,023 million patients and are close to 3.5 deaths by September 2021. It also brought with it panic and fear, halted many activities, and led to the decline of the global economy. It changed human behavior and forced people to change their lifestyles to avoid infection. One of the most sectors that must be taken into consideration through pandemic coronavirus (COVID-19) around the globe is the air conditioning systems. The HVAC systems depend on the air as a heat transfer medium. The air contains a group of pollutants, viruses, and bacteria, and it affects and destroys human life. The air filter plays a major role as an important component in the air conditioning systems. Thus, it requires more effort by researchers to improve its design to prevent the ultra-size of particles loaded with coronavirus (COVID-19). This paper provides insight into the design of existing combined air-conditioners on their suitability and their impact on the spread of the hybrid coronavirus epidemic and review efforts to obtain a highly efficient air filter to get rid of super-sized particles for protection against epidemic infection. In addition, important guideline recommendations have been made to limit the spread of the COVID-19 virus and to obtain indoor air quality in air-conditioned places.

Air Pollution: A Neglected Risk Factor for Dementia in Latin America and the Caribbean

The risk of dementia and Alzheimer's disease in Latin America and the Caribbean (LAC) rises with increasing age and polluted air. Currently, at least 172 million people breathe unhealthy levels of air pollution in LAC countries. Several cohort studies have indicated that air pollution increases the risk of developing dementia and neurodegenerative diseases, but the mechanisms underlying the association are still not clear. Air pollution causes and aggravates five established risk factors for dementia (obesity, hypertension, stroke, diabetes mellitus, and heart diseases) and is linked to three other risk factors (physical inactivity, cognitive inactivity, and depression). Some of these risk factors could be mediating the association between air pollution and dementia. Reducing the risks for dementia is crucial and urgently needed in LAC countries. There is room for improving air quality in many urban areas in the LAC region and other low- and middle-income countries (LMICs), a routealready explored by many urban areas in developing regions. Moreover, reducing air pollution has proved to improve health outcomes before. In this article, we propose that despite the ongoing and valid scientific discussion, if air pollution can or cannot directly affect the brain and cause or aggravate dementia, we are ready to consider air pollution as a potentially modifiable risk factor for dementia in LAC and possibly in other LMICs. We suggest that controlling and reducing current air pollution levels in LAC and other LMIC regions now could strongly contribute.

The effect of COVID-19 pandemic on human mobility and ambient air quality around the world: A systematic review

We conducted this systematic review to identify and appraise studies investigating the coronavirus disease 2019 (COVID-19) effect on ambient air pollution status worldwide. The review of studies was conducted using determined search terms via three major electronic databases (PubMed, Web of Science, and Scopus) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. A total of 26 full-text studies were included in our analysis. The lockdown measures related to COVID-19 pandemic caused significant decreases in the concentrations of PM2.5, NO2, PM10, SO2 and CO globally in the range of 2.9%-76.5%, 18.0%-96.0%, 6.0%-75.0%, 6.8%-49.0% and 6.2%-64.8%, respectively. However, O3 concentration increased in the range of 2.4%-252.3%. The highest decrease of PM2.5 was found in 16 states of Malaysia (76.5%), followed by Zaragoza (Spain) with 58.0% and Delhi (India) with 53.1%. The highest reduction of NO2 was found in Salé city (Morocco) with 96.0%, followed by Mumbai (India) with 75.0%, India with 70.0%, Valencia (Spain) with 69.0%, and São Paulo (Brazil) with 68.0%, respectively. The highest increase of O3 was recorded for Milan (Italy) with 252.3% and 169.9% during the first and third phases of lockdown measures, and for Kolkata (India) with 87% at the second phase of lockdown measures. Owing to the lockdown restrictions in the studied countries and cities, driving and public transit as a proxy of human mobilities and the factors affecting emission sources of ambient air pollution decreased in the ranges of 30-88% and 45-94%, respectively. There was a considerable variation in the reduction of ambient air pollutants in the countries and cities as the degree of lockdown measures had varied there. Our results illustrated that the COVID-19 pandemic had provided lessons and extra motivations for comprehensive implementing policies to reduce air pollution and its health effects in the future.

Nutraceuticals with anti-inflammatory and anti-oxidant properties as intervention for reducing the health effects of fine particulate matter: Potential and Prospects

Air pollution, especially particulate matter pollution adversely affects human health. A growing pool of evidence has emerged which underscores the potential of individual-level nutritional interventions in attenuating the adverse health impact of exposure to PM2.5. Although controlling emission and reducing the overall levels of air pollution remains the ultimate objective globally, the sustainable achievement of such a target and thus consequent protection of human health will require a substantial amount of time and concerted efforts worldwide. In the meantime, smaller-scale individual-level interventions that can counter the inflammatory or oxidative stress effects triggered by exposure to particulate matter may be utilized to ameliorate the health effects of PM2.5 pollution. One such intervention is incorporation of nutraceuticals in the diet. Here, we present a review of the evidence generated from various in vitro, in vivo and human studies regarding the effects of different anti-inflammatory and antioxidant nutraceuticals in ameliorating the health effects of particulate matter air pollution. The studies discussed in this review suggest that these nutraceuticals when consumed as a part of the diet, or as additional supplementation, can potentially negate the cellular level adverse effects of exposure to particulate pollution. The potential benefits of adopting a non-pharmacological diet-based approach to air pollution-induced disease management have also been discussed. We argue that before a nutraceuticals-based approach can be used for widespread public adoption, further research, especially human clinical trials, is essential to confirm the beneficial action of relevant nutraceuticals and to explore the safe limits of human supplementation and the risk of side effects. Future research should focus on systematically translating bench-based knowledge regarding nutraceuticals gained from in-vitro and in-vivo studies into clinically usable nutritional guidelines.

COVID-19 mitigation measures and nitrogen dioxide - A quasi-experimental study of air quality in Munich, Germany

BACKGROUND

In response to the COVID-19 pandemic, the Bavarian State government announced several COVID-19 mitigation measures beginning on March 16, 2020, which likely led to a reduction in traffic and a subsequent improvement in air quality. In this study, we evaluated the short-term effect of COVID-19 mitigation measures on NO₂ concentrations in Munich, Germany.

METHODS

We applied two quasi-experimental approaches, a controlled interrupted time-series (c-ITS) approach and a synthetic control (SC) approach. Each approach compared changes occurring in 2020 to changes occurring in 2014-2019, and accounted for weather-related and other potential confounders. We hypothesized that the largest reductions in NO₂ concentrations would be observed at traffic sites, with smaller reductions at urban background sites, and even small reductions, if any, at background sites. All hypotheses, as well as the main and additional analyses were defined a priori. We also conducted post-hoc analyses to ensure that observed effects were not due to factors other than the intervention.

RESULTS

Main analyses largely supported our hypotheses. Specifically, at the two traffic sites, using the c-ITS approach we observed reductions of 9.34 μg/m³ (95% confidence interval: -23.58; 4.90) and 10.02 μg/m³ (-19.25; -0.79). Using the SC approach we observed reductions of 15.65 μg/m³ (-27.58; -4.09) and 15.1 μg/m³ (-24.82; -9.83) at these same sites. We observed effects ranging from smaller in magnitude to no effect at urban background and background sites. Additional analyses showed that the effect was largest in the first two weeks following introduction of measures, and that a 3-day lagged intervention time also showed a larger effect. Post-hoc analyses suggested that at least some of the observed effects may have been attributable to changes in air quality occurring before the intervention, as well as unusually high concentrations in January 2020.

CONCLUSION

We applied two quasi-experimental approaches in assessing the impact of the COVID-19 mitigation measures on NO₂ concentrations in Munich. Taking the 2020 pre-intervention average concentrations as a reference, we observed reductions in NO₂ concentrations of approximately 15-25% and 24-36% at traffic sites, suggesting that reducing traffic may be an effective measure to reduce NO₂ concentrations in heavily trafficked areas by margins which could translate to public health benefits.

Cross-Regional Highway Built through a City Centre as an Example of the Sustainable Development of Urban Transport

Sustainable development requires ensuring the mobility of residents and must not cause deterioration of the quality of the environment in the selected area. The purpose of this study is to verify if the construction of a cross-regional highway through the city centre affected air quality in the neighbourhood of a newly built road. Air quality was assessed based on measurements of concentrations of nitrogen dioxide, which is considered to be typical for automotive sources air pollution. The spectrophotometric method with passive sampling was used in the 24 h NO2 measurements. The calculated mean NO2 concentrations in the periods before and after road construction were within the ranges of 23.2–31.9 μg/m3 and 22.3–28.9 μg/m3, respectively. The relative NO2 concentrations determined in the study for 10 out of 11 sampling points were lower than the unity, including 5 points markedly lower (0.82–0.89). The obtained results indicate that the construction of the new artery by the city centre, using appropriate technical solutions and traffic organization (tunnel, noise barriers, roundabouts, speed limit) likely contributed to an overall reduction in NO2 concentrations. The presented solution may serve as an example for other cities struggling with problems of low air quality associated with inefficient transportation systems.

Implications for air quality management of changes in air quality during lockdown in Auckland (New Zealand) in response to the 2020 SARS-CoV-2 epidemic

The current changes in vehicle movement due to 'lockdown' conditions (imposed in cities worldwide in response to the COVID-19 epidemic) provide opportunities to quantify the local impact of 'controlled interventions' on air quality and establish baseline pollution concentrations in cities. Here, we present a case study from Auckland, New Zealand, an isolated Southern Hemisphere city, which is largely unaffected by long-range pollution transport or industrial sources of air pollution. In this city, traffic flows reduced by 60-80% as a result of a government-led initiative to contain the virus by limiting all transport to only essential services. In this paper, ambient pollutant concentrations of NO₂, O₃, BC, PM_2.5, and PM₁₀ are compared between the lockdown period and comparable periods in the historical air pollution record, while taking into account changes in the local meteorology. We show that this 'natural experiment' in source emission reductions had significant but non-linear impacts on air quality. While emission inventories and receptor modelling approaches confirm the dominance of traffic sources for NO_x (86%), and BC (72%) across the city, observations suggest a consequent reduction in NO₂ of only 34-57% and a reduction in BC of 55-75%. The observed reductions in PM_2.5 (still likely to be dominated by traffic emissions), and PM₁₀ (dominated by sea salt, traffic emissions to a lesser extent, and affected by seasonality) were found to be significantly less (8-17% for PM_2.5 and 7-20% for PM₁₀). The impact of this unplanned controlled intervention shows the importance of establishing accurate, local-scale emission inventories, and the potential of the local atmospheric chemistry and meteorology in limiting their accuracy.

NO2 levels after the COVID-19 lockdown in Ecuador: A trade-off between environment and human health

The negative effects on human health, along with the fatalities caused by the new coronavirus, have led governments worldwide to take strict measures. However, a reduction in air pollution has been found in many regions on a global scale. This study is focused on how the COVID-19 pandemic is impacting on the air quality in Ecuador, one of the most alarming cases of COVID-19 contagion in Latin America, occupying the first place as regards deaths per capita. The spatio-temporal variations in NO2 concentrations in 12 highly populated cities were evaluated by comparing the NO2 tropospheric concentrations before (2019) and after (2020) the COVID-19 lockdown. The atmospheric data was collected from the TROPOMI on the Sentinel-5P satellite of the European Space Agency. A reduction in NO2 concentrations (-13%) was observed as a consequence of the COVID-19 lockdown in Ecuador. However, this reduction occurred to the greatest extent in the cases of Guayaquil (-23.4%) and Quito (-22.4%), the two most highly populated cities. Linking NO2 levels to confirmed cases/deaths of COVID-19, a strong correlation between air NO2 concentrations and the cases/mortality caused by coronavirus (r = 0.91; p<0.001) was observed. This work highlights the crucial role played by air quality as regards human health.

The impact of PM2.5 on acute otitis media in children (aged 0-3): A time series study

BACKGROUND

Experimental studies have reported that air pollution could make the middle ear more susceptible to infections. However, the associations between specific air pollutants and AOM were inconsistent in previous epidemiologic studies. This study aimed to investigate the association between PM_2.5 exposure and the AOM events in seven major cities in the Republic of Korea.

METHODS

We performed a nationwide time series analysis of children aged 0-3 years living in seven major Korean cities between 2008 and 2016. We used a quasi-Poisson regression to estimate the short-term association between incident AOM and the 5-day moving average of particulate matter smaller than 2.5 μm (PM_2.5) for each city. Then, we conducted a meta-analysis to combine the city-specific associations. The exposure unit was 10 μg/m³, and all models were adjusted for time, daily mean apparent temperature and day of the week.

RESULTS

A higher risk of incident AOM was significantly associated with higher 5-day moving PM_2.5 averages in five cities, except for Gwangju and Ulsan. The combined relative risk (RR) was 1.011 (95% confidence interval [CI]: 1.008, 1.014). In the subgroup analysis by season, PM_2.5 exposure was significantly associated with incident AOM in the warm season (RR: 1.016, 95% CI: 1.009, 1.022). In addition, among children with a URI history within 4 weeks, children with a more recent URI history were more sensitive to the impact of PM_2.5 exposure on incident AOM (RR for 1st week: 1.017, 95% CI: 1.011, 1.024; RR for 2nd week: 1.013, 95% CI: 1.008, 1.018; RR for 3rd week: 1.008, 95% CI: 1.003, 1.013; RR for 4th week: 1.005, 95% CI: 1.001, 1.009).

CONCLUSION

Higher PM_2.5 concentrations are associated with a higher risk of incident AOM, particularly in the warm season and children with recent URI history. Our findings could have important implications for preventing AOM in children.

Should air pollution health effects assumptions be tested? Fine particulate matter and COVID-19 mortality as an example

In the first half of 2020, much excitement in news media and some peer reviewed scientific articles was generated by the discovery that fine particulate matter (PM2.5) concentrations and COVID-19 mortality rates are statistically significantly positively associated in some regression models. This article points out that they are non-significantly negatively associated in other regression models, once omitted confounders (such as latitude and longitude) are included. More importantly, positive regression coefficients can and do arise when (generalized) linear regression models are applied to data with strong nonlinearities, including data on PM2.5, population density, and COVID-19 mortality rates, due to model specification errors. In general, statistical modeling accompanied by judgments about causal interpretations of statistical associations and regression coefficients - the current weight-of-evidence (WoE) approach favored in much current regulatory risk analysis for air pollutants - is not a valid basis for determining whether or to what extent risk of harm to human health would be reduced by reducing exposure. The traditional scientific method based on testing predictive generalizations against data remains a more reliable paradigm for risk analysis and risk management.

Impact of temporary traffic bans on the risk of acute coronary syndromes in a large metropolitan area

BACKGROUND

Strong epidemiologic evidence has highlighted the role of pollution, on top of adverse climate features, as a novel cardiovascular risk factor. However, mechanistic proof that reducing pollution may be beneficial to prevent atherothrombotic events is limited. We aimed at appraising the impact of temporary traffic bans in a large metropolitan area on the risk of acute coronary syndromes.

METHODS

Aggregate and anonymized data from 15 tertiary cardiac care centers were obtained detailing precoronavirus disease 2019 (COVID-19) daily cases of ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), including those treated with percutaneous coronary intervention (PCI). Data on pollutants and climate were sought for the same days. Mixed level regression was used to compare the week before vs after the traffic ban (Fortnight analysis), the 3 days before vs. after (Weekly analysis) and the Sunday before vs. after (Sunday analysis).

RESULTS

A total of 8 days of temporary traffic bans were included, occurring between 2017 and 2020, totaling 802 STEMI and 1196 NSTEMI in the Fortnight analysis, 382 STEMI and 585 in the Weekly analysis, and 148 STEMI and 210 NSTEMI in the Sunday analysis.Fortnight and Sunday analyses did not disclose a significant impact of traffic ban on STEMI or NSTEMI (all P>0.05). Conversely, Weekly analysis showed non-significant changes for STEMI, but a significant decrease in daily NSTEMI when comparing the 3 days before the traffic ban with the ban day (P=0.043), as well as the 3 days before vs. the 3 days after the ban (P=0.025). No statistically significant effect of traffic ban was found at Fortnight, Weekly or Sunday analyses for daily mean concentrations of benzene, carbon monoxide, nitric oxide, nitrogen dioxide, ozone, sulfur dioxide, particulate matter (PM) <2.5 µm or PM <10 µm (all P>0.05). However, minimum daily concentrations showed a significant reduction of ozone during the ban in comparison to the week preceding it (P=0.034), nitric oxide during the ban in comparison to the 3 days preceding it (P=0.046), and an increase in benzene during the ban in comparison to the Sunday before (P=0.039).

CONCLUSIONS

Temporary traffic ban may favorably reduce coronary atherothrombotic events, and in particular NSTEMI, even if not globally and immediately impacting on environmental pollution. Further controlled studies are required to confirm and expand this hypothesis-generating results.

Real-world assessment of vehicle air pollutant emissions subset by vehicle type, fuel and EURO class: New findings from the recent UK EDAR field campaigns, and implications for emissions restricted zones

This paper reports upon and analyses vehicle emissions measured by the Emissions Detecting and Reporting (EDAR) system, a Vehicle Emissions Remote Sensing System (VERSS) type device, used in five UK based field campaigns in 2016 and 2017. In total 94,940 measurements were made of 75,622 individual vehicles during the five campaigns. The measurements are subset into vehicle type (bus, car, HGV, minibus, motorcycle, other, plant, taxi, van, and unknown), fuel type for car (petrol and diesel), and EURO class, and particulate matter (PM), nitric oxide (NO) and nitrogen dioxide (NO₂) are reported. In terms of recent EURO class emission trends, NO and NO_x emissions decrease from EURO 5 to EURO 6 for nearly all vehicle categories. Interestingly, taxis show a marked increase in NO₂ emissions from EURO 5 to EURO 6. Perhaps most concerningly is a marked increase in PM emissions from EURO 5 to EURO 6 for HGVs. Another noteworthy observation was that vans, buses and HGVs of unknown EURO class were often the dirtiest vehicles in their classes, suggesting that where counts of such vehicles are high, they will likely make a significant contribution to local emissions. Using Vehicle Specific Power (VSP) weighting we provide an indication of the magnitude of the on-site VERSS bias and also a closer estimate of the regulatory test/on-road emissions differences. Finally, a new 'EURO Updating Potential' (EUP) factor is introduced, to assess the effect of a range of air pollutant emissions restricted zones either currently in use or marked for future introduction. In particular, the effects of the London based Low Emission Zone (LEZ) and Ultra-Low Emissions Zone (ULEZ), and the proposed Birmingham based Clean Air Zone (CAZ) are estimated. With the current vehicle fleet, the impacts of the ULEZ and CAZ will be far more significant than the LEZ, which was introduced in 2008.

Outdoor air pollution and cancer: An overview of the current evidence and public health recommendations

Outdoor air pollution is a major contributor to the burden of disease worldwide. Most of the global population resides in places where air pollution levels, because of emissions from industry, power generation, transportation, and domestic burning, considerably exceed the World Health Organization's health-based air-quality guidelines. Outdoor air pollution poses an urgent worldwide public health challenge because it is ubiquitous and has numerous serious adverse human health effects, including cancer. Currently, there is substantial evidence from studies of humans and experimental animals as well as mechanistic evidence to support a causal link between outdoor (ambient) air pollution, and especially particulate matter (PM) in outdoor air, with lung cancer incidence and mortality. It is estimated that hundreds of thousands of lung cancer deaths annually worldwide are attributable to PM air pollution. Epidemiological evidence on outdoor air pollution and the risk of other types of cancer, such as bladder cancer or breast cancer, is more limited. Outdoor air pollution may also be associated with poorer cancer survival, although further research is needed. This report presents an overview of outdoor air pollutants, sources, and global levels, as well as a description of epidemiological evidence linking outdoor air pollution with cancer incidence and mortality. Biological mechanisms of air pollution-derived carcinogenesis are also described. This report concludes by summarizing public health/policy recommendations, including multilevel interventions aimed at individual, community, and regional scales. Specific roles for medical and health care communities with regard to prevention and advocacy and recommendations for further research are also described.

Effects of air pollutants on the transmission and severity of respiratory viral infections

Particulate matter, sulfur dioxide, nitrogen oxides, ozone, carbon monoxide, volatile organic compounds (VOCs) and polycyclic aromatic hydrocarbons (PAHs) are among the outdoor air pollutants that are major factors in diseases, causing especially adverse respiratory effects in humans. On the other hand, the role of respiratory viruses in the pathogenesis of severe respiratory infections is an issue of great importance. The present literature review was aimed at assessing the potential effects of air pollutants on the transmission and severity of respiratory viral infections. We have reviewed the scientific literature regarding the association of outdoor air pollution and respiratory viruses on respiratory diseases. Evidence supports a clear association between air concentrations of some pollutants and human respiratory viruses interacting to adversely affect the respiratory system. Given the undoubted importance and topicality of the subject, we have paid special attention to the association between air pollutants and the transmission and severity of the effects caused by the coronavirus named SARS-CoV-2, which causes the COVID-19. Although to date, and by obvious reasons, the number of studies on this issue are still scarce, most results indicate that chronic exposure to air pollutants delays/complicates recovery of patients of COVID-19 and leads to more severe and lethal forms of this disease. This deserves immediate and in-depth experimental investigations.

Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs

Despite the increased attention given to the health impact assessment of air pollution and to the strategies to control it in both scientific literature and concrete interventions, the results of the implementations, especially those involving traffic, have not always been satisfactory and there is still disagreement about the most appropriate interventions and the methods to assess their effectiveness. This state-of-the-art article reviews the recent interpretation of the concepts that concern the impact assessment, and compares old and new measurements of attributable risk and attributable fraction. It also summarizes the ongoing discussion about the designs and methods for assessing the air pollution impact with particular attention to improvements due to spatio-temporal analysis and other new approaches, such as studying short term effects in cohorts, and the still discussed methods of predicting the values of attributable risk (AR). Finally, the study presents the more recent analytic perspectives and the methods for directly assessing the effects of not yet implemented interventions on air quality and health, in accordance with the suggestion in the strategic plan 2020-2025 from the Health Effect Institute.

Direct assessment of health impacts on hospital admission from traffic intensity in Madrid

In this paper we establish the attributable risk on respiratory and cardiovascular disorders related to traffic intensity in Madrid. In contrast to previous related studies, the proposed approach directly associates road traffic counts to patient emergency admission rates instead of using primary air pollutants. By applying Shapley values over gradient boosting machines, a first selection step is performed among all traffic observation points based on their influence on patient emergency admissions at Gregorio Marañon hospital. A subsequent quantification of the relative risk associated to traffic intensity of the selected point is calculated via ARIMA and log-linear Poisson regression models. The results obtained show that 13% of respiratory cases are related to traffic intensity while, in the case of cardiovascular disorders, the percentage increases to 39%.