Long-term Concentrations of Nitrogen Dioxide and Mortality: A Meta-analysis of Cohort Studies

Challenging unverified assumptions in causal claims: Do gas stoves increase risk of pediatric asthma?

The use of unverified models for risk estimates and policy recommendations can be highly misleading, as their predictions may not reflect real-world health impacts. For example, a recent article states that NO2 from gas stoves "likely causes ∼50,000 cases of current pediatric asthma from long-term NO2 exposure alone" annually in the United States. This explicitly causal claim, which is contrary to several methodology and review articles published in this journal, among others, reflects both (a) An unverified modeling assumption that pediatric asthma burden is approximately proportional to NO2; and (b) An unverified causal assumption that the assumed proportionality between exposure and response is causal. The article is devoid of any causal analysis showing that these assumptions are likely to be true. It does not show that reducing NO2 exposure from gas stoves would reduce pediatric asthma risk. Its key references report no significant associations - let alone causation - between NO2 and pediatric asthma. Thus, the underlying data suggests that the number of pediatric asthma cases caused by gas stoves in the United States is indistinguishable from zero. This highlights the need to rigorously validate modeling assumptions and causal claims in public health risk assessments to ensure scientifically sound foundations for policy decisions.

Long-term exposure to ambient air pollution and risk of lung cancer - A comparative analysis of incidence and mortality in four administrative cohorts in the ELAPSE study

BACKGROUND

Studies have linked air pollution to lung cancer incidence and mortality, but few have compared these associations, which may differ due to cancer survival variations. We aimed to evaluate the association between long-term air pollution exposure and lung cancer incidence and compare findings with previous lung cancer mortality analyses within the same cohorts.

METHODS

We analyzed four population-based administrative cohorts in Denmark (2000-2015), England (2011-2017), Norway (2001-2016) and Rome (2001-2015). We assessed residential exposure to annual average fine particulate matter (PM2.5), nitrogen dioxide (NO₂), black carbon (BC), and warm-season ozone (O3) using Europe-wide land use regression models. We used Cox proportional hazard models to evaluate cohort-specific hazard ratios (HRs) and 95% confidence intervals (CIs) for lung cancer incidence identified using hospital admission records (English and Roman cohorts) or cancer registries (Danish and Norwegian cohorts). We evaluated the associations at low exposure levels using subset analyses and natural cubic splines. Cohort-specific HRs were pooled using random-effects meta-analyses, separately for incidence and mortality.

RESULTS

Over 93,733,929 person-years of follow-up, 111,949 incident lung cancer cases occurred. Incident lung cancer was positively associated with PM2.5, NO2 and BC, and negatively associated with O3. The negative O3 association became positive after adjustment for NO2. Associations were almost identical or slightly stronger for lung cancer incidence than mortality in the same cohorts, with respective meta-analytic HRs (95% CIs) of 1.14 (1.06, 1.22) and 1.12 (1.02, 1.22) per 5 μg/m3 increase in PM2.5, and 1.10 (1.04, 1.16) and 1.09 (1.02, 1.16) per 10 μg/m3 increase in NO2. Positive associations persisted for both incidence and mortality at low pollution levels with similar magnitude.

CONCLUSIONS

We found similarly elevated risks of lung cancer incidence and mortality in association with residential exposure to PM2.5, NO2 and BC in meta-analyses of four European administrative cohorts, which persisted at low pollution levels.

Controlled human exposures: a review and comparison of the health effects of diesel exhaust and wood smoke

One of the most pressing issues in global health is air pollution. Emissions from traffic-related air pollution and biomass burning are two of the most common sources of air pollution. Diesel exhaust (DE) and wood smoke (WS) have been used as models of these pollutant sources in controlled human exposure (CHE) experiments. The aim of this review was to compare the health effects of DE and WS using results obtained from CHE studies. A total of 119 CHE-DE publications and 25 CHE-WS publications were identified for review. CHE studies of DE generally involved shorter exposure durations and lower particulate matter concentrations, and demonstrated more potent dysfunctional outcomes than CHE studies of WS. In the airways, DE induces neutrophilic inflammation and increases airway hyperresponsiveness, but the effects of WS are unclear. There is strong evidence that DE provokes systemic oxidative stress and inflammation, but less evidence exists for WS. Exposure to DE was more prothrombotic than WS. DE generally increased cardiovascular dysfunction, but limited evidence is available for WS. Substantial heterogeneity in experimental methodology limited the comparison between studies. In many areas, outcomes of WS exposures tended to trend in similar directions to those of DE, suggesting that the effects of DE exposure may be useful for inferring possible responses to WS. However, several gaps in the literature were identified, predominantly pertaining to elucidating the effects of WS exposure. Future studies should strongly consider performing head-to-head comparisons between DE and WS using a CHE design to determine the differential effects of these exposures.

Plant-based diet indices and their interaction with ambient air pollution on the ovarian cancer survival: A prospective cohort study

BACKGROUND

Ambient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions.

METHODS

The present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales.

RESULTS

Throughout a median follow-up of 37.60 (interquartile: 24.77-50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend < 0.01), whereas no significant associations were found between either overall PDI or hPDI and OC survival. Higher APS (HR for per interquartile range = 1.27, 95 % CI = 1.01, 1.60) was significantly associated with worse OC survival, and the association was exacerbated by adherence to uPDI. Notably, an additive interaction was identified between combined air pollution and uPDI (P < 0.005 for high APS and high uPDI). We also found that adherence to overall PDI aggravated associations of air pollution with OC survival (P-interaction = 0.006).

CONCLUSIONS

Joint exposure to various ambient air pollutants was significantly associated with lower survival among patients with OC, particularly for those who predominantly consumed unhealthy plant-based foods.

Evaluating air pollution exposure among cyclists: Real-time levels of PM2.5 and NO2 and POI impact

Although cycling has numerous health benefits, the increased breathing volume and lack of protection from exposure to the environment while cycling poses health risks that cannot be disregarded. Previous studies evaluating the exposure of cyclists to air pollution have typically focused on assessing exposure to a single pollutant or exposure concentrations on specific urban routes, and have not performed a comprehensive assessment considering the distribution of cyclists. The present study used bicycle-sharing big data to conduct a more comprehensive and refined real-time population weighted exposure risk assessment of pileless bike sharing riders in Beijing. We quantified the spatial distribution of high exposure areas at different times and found that the exposure risk during the evening peak period was significantly higher than that during the morning peak and early morning periods, particularly in the city center and its environs. By establishing stepwise regression models, we identified the significant impact of various urban points of interest (POIs) on exposure risk, with sports venues, public toilets, educational institutions, scenic spots, and financial entities particularly influential at different time periods. Medical institutions and shopping venues have a significant negative impact on the exposure levels of PM2.5 and NO2 among cyclists in most cases. These findings emphasize the need for targeted pollution control strategies. The aim of this study is to mitigate the impact of air pollution on cyclists and create a healthier cycling environment. The research results can provide new ideas for urban health planning and support scientific decision-making for sustainable urban development.

Exploring the nexus of urban form, transport, environment and health in large-scale urban studies: A state-of-the-art scoping review

BACKGROUND

As the world becomes increasingly urbanised, there is recognition that public and planetary health relies upon a ubiquitous transition to sustainable cities. Disentanglement of the complex pathways of urban design, environmental exposures, and health, and the magnitude of these associations, remains a challenge. A state-of-the-art account of large-scale urban health studies is required to shape future research priorities and equity- and evidence-informed policies.

OBJECTIVES

The purpose of this review was to synthesise evidence from large-scale urban studies focused on the interaction between urban form, transport, environmental exposures, and health. This review sought to determine common methodologies applied, limitations, and future opportunities for improved research practice.

METHODS

Based on a literature search, 2958 articles were reviewed that covered three themes of: urban form; urban environmental health; and urban indicators. Studies were prioritised for inclusion that analysed at least 90 cities to ensure broad geographic representation and generalisability. Of the initially identified studies, following expert consultation and exclusion criteria, 66 were included.

RESULTS

The complexity of the urban ecosystem on health was evidenced from the context dependent effects of urban form variables on environmental exposures and health. Compact city designs were generally advantageous for reducing harmful environmental exposure and promoting health, with some exceptions. Methodological heterogeneity was indicative of key urban research challenges; notable limitations included exposure and health data at varied spatial scales and resolutions, limited availability of local-level sociodemographic data, and the lack of consensus on robust methodologies that encompass best research practice.

CONCLUSION

Future urban environmental health research for evidence-informed urban planning and policies requires a multi-faceted approach. Advances in geospatial and AI-driven techniques and urban indicators offer promising developments; however, there remains a wider call for increased data availability at local-levels, transparent and robust methodologies of large-scale urban studies, and greater exploration of urban health vulnerabilities and inequities.

Neighborhood-Level Nitrogen Dioxide Inequalities Contribute to Surface Ozone Variability in Houston, Texas

In Houston, Texas, nitrogen dioxide (NO2) air pollution disproportionately affects Black, Latinx, and Asian communities, and high ozone (O3) days are frequent. There is limited knowledge of how NO2 inequalities vary in urban air quality contexts, in part from the lack of time-varying neighborhood-level NO2 measurements. First, we demonstrate that daily TROPOspheric Monitoring Instrument (TROPOMI) NO2 tropospheric vertical column densities (TVCDs) resolve a major portion of census tract-scale NO2 inequalities in Houston, comparing NO2 inequalities based on TROPOMI TVCDs and spatiotemporally coincident airborne remote sensing (250 m × 560 m) from the NASA TRacking Aerosol Convection ExpeRiment-Air Quality (TRACER-AQ). We further evaluate the application of daily TROPOMI TVCDs to census tract-scale NO2 inequalities (May 2018-November 2022). This includes explaining differences between mean daily NO2 inequalities and those based on TVCDs oversampled to 0.01° × 0.01° and showing daily NO2 column-surface relationships weaken as a function of observation separation distance. Second, census tract-scale NO2 inequalities, city-wide high O3, and mesoscale airflows are found to covary using principal component and cluster analysis. A generalized additive model of O3 mixing ratios versus NO2 inequalities reproduces established nonlinear relationships between O3 production and NO2 concentrations, providing observational evidence that neighborhood-level NO2 inequalities and O3 are coupled. Consequently, emissions controls specifically in Black, Latinx, and Asian communities will have co-benefits, reducing both NO2 disparities and high O3 days city wide.

Combination of toxicological and epidemiological approaches for estimating the health impact of atmospheric pollutants. A proof of concept for NO2

BACKGROUND

Regular monitoring of the air pollutant nitrogen dioxide (NO2), an indicator for traffic-related emissions, is a priority in urban environments. The health impacts associated with NO2 exposure are the result of a combination of factors, including concentration, duration of exposure, and interactions with other pollutants. WHO has established air quality guidelines based on epidemiological studies.

OBJECTIVE

This study develops a new concept "Health Impact Pathways (HIPs)" using adversity as a probabilistic indicator of health effects. For this purpose, it integrates available toxicological and epidemiological information, using Adverse Outcome Pathways (AOPs), in order to understand chemical-biological interactions and their consequences on health.

METHODS

Literature review and meta-analysis of toxicological data supported by expert judgment were performed to establish: a) adversity pathways, b) quantitative criteria for scoring the observed toxicological effects (adversity indicators), c) NO2 exposure - adversity relationship for both long-term (1-36 months) and shortterm (1-7 days). The NO2 daily concentrations from January 2001 to December 2022, were obtained from Madrid city Air Quality network monitoring database. Adversity levels were compared with relative risk levels for all-cause and respiratory mortality estimated using linear equations from WHO 2021 guidelines.

RESULTS

Non-linear relations were obtained for all long- and short-term NO2 related adversity indicators; for long-term effects, the best fitting was obtained with a modified Haber's law model with an exponential coefficient for the exposure time of 0.25. Estimations are presented for a set of case studies for Madrid city, covering temporal and spatial variability. A clear improvement trend along the two decades was observed, as well as high inter- and intra-station variability; the adversity indicators provided integrated information on the temporal and spatial evolution of population level risk.

DISCUSSION

The proposed HIP conceptual approach offers promising advances for integrating experimental and epidemiological data. The next step is linking the concentration-adversity relationship with population health impacts through probability estimations, the preliminary estimations confirm the need for assessing independently different population groups.

Health impact assessment of port-sourced air pollution in Barcelona

INTRODUCTION

Air pollution is a major health risk factor. Ports might be an understudied source of air pollution.

METHODS

We conducted a spatial health impact assessment (HIA) of port-sourced air pollution for Barcelona for 2017 at the neighbourhood level. Total NO2 and PM10 and port-sourced NO2, PM10 and PM2.5 concentrations were available through the ADMS-Urban model. Population data, mortality and morbidity data, and risk estimates were obtained. We followed standard HIA methodologies and calculated relative risks and impact fractions for 1.35 million adults living in 73 neighbourhoods.

RESULTS

The city-wide mean total NO2 and PM10 concentrations were 37.88 μg/m3 (range: 19.61-52.17 μg/m3) and 21.68 μg/m3 (range: 17.33-26.69 μg/m3), respectively, of which 7% (range: 2-36%) and 1% (range: 0-7%) were port-sourced, respectively. The mean port-sourced PM2.5 concentration was 0.19 μg/m3 (range: 0.06-1.38 μg/m3). We estimated that 1,123 (PI: 0-3,060) and 1,230 (95% CI: 0-2,566) premature deaths were attributable to total NO2 and PM10, respectively, of which 8.1% (91; PI: 0-264) and 1.1% (13; 95% CI 0-29) were attributable to port-sourced NO2 and PM10, respectively. 20 (95% CI: 15-26) premature deaths were attributable to port-sourced PM2.5. Additionally, a considerable morbidity burden and losses in life expectancy were attributable to port-sourced air pollution. Neighbourhoods closest to the port in the south-east were most adversely affected, gradually decreasing towards the north-west.

CONCLUSIONS

The port is an understudied air pollution source in Barcelona with strong health impacts. Cities need local insight into health risk factors, their sources, attributable burdens and distributions for defining targeted policies.

A hybrid model for enhanced forecasting of PM2.5 spatiotemporal concentrations with high resolution and accuracy

Forecasting concentrations of PM2.5 is important due to its known impacts on public health and environment. However, PM2.5 concentrations can vary significantly over short distances and time, which can be influenced by local emissions and short-term weather patterns. This spatiotemporal variability makes accurate PM2.5 forecasting an inherently complex and challenging task. This study presented novel methodologies for short-term PM2.5 concentration forecast by combining the atmospheric chemistry transport model Community Multiscale Air Quality Modeling System (CMAQ) with data-driven machine learning methods, namely long short-term memory (LSTM) and random forest (RF) models. The combined model system forecast PM2.5 with 1 h, 1km × 1 km spatiotemporal resolution. The LSTM system forecast time-dependent PM2.5 concentrations at observation sites with a maximum root mean square error (RMSE) of 3.66 μg/m3 for 1-hr forecast and 23.75 μg/m3 for 72-hr forecast, leveraging results obtained from the atmospheric transport model with RMSE of 45.81 μg/m3. Wavelet transform in the LSTM system allowed learning and prediction of PM2.5 concentrations at different frequencies, capturing temporal variability of PM2.5 at various time scales. The RF model predicted distributions of PM2.5 concentrations by learning LSTM results and integrating crucial features such as CMAQ results, meteorological and topographical information. The feature significance of CMAQ results was the highest among the input features in RF models. Overall, the hybrid model could help with managing and mitigating the adverse effects of air pollution by enabling informed decision-making at the individual, community and policy levels.

Excess deaths and loss of life expectancy attributed to long-term NO2 exposure in the Chinese elderly

BACKGROUND

Evidence linking nitrogen dioxide (NO2) air pollution to life span of high-vulnerability older adults is extensively scarce in low- and middle-income countries. This study seeks to quantify mortality risk, excess deaths, and loss of life expectancy (LLE) associated with long-term exposure to NO2 among elderly individuals in China.

METHODS

A nationwide dynamic cohort of 20352 respondents ≥65 years old were enrolled from the China Longitudinal Health and Longevity Survey during 2005-2018. Residential exposures to NO2 and co-pollutants were assessed by well-validated spatiotemporal prediction models. A Cox regression model with time-dependent covariates was utilized to quantify the association of all-cause mortality with NO2 exposure, controlling for confounders such as demographics, lifestyle, health status, and ambient temperature. NO2-attributable deaths and LLE were evaluated for the years 2010 and 2020 based on the pooled NO2-mortality relation derived from multi-national cohort investigations. Decomposition analyses were conducted to dissociate net shift in NO2-related deaths between 2010 and 2020 into four primary contributing factors.

RESULTS

A total of 14313 deaths were recorded during follow-up of approximately 100 hundred person-years (median 3.6 years). We observed an approximately linear relationship (nonlinear P = 0.882) of NO2 exposure with all-cause death across a broad range from 6.6 to 95.7 μg/m3. Every 10-μg/m3 rise in yearly average NO2 concentration was linked to a hazard ratio (HR) of 1.045 (95% confidence interval [CI]: 1.031-1.059). In the updated meta-analysis of this study and 9 existing cohorts, we estimated a pooled HR of 1.043 (95% CI: 1.023-1.063) for each 10-μg/m3 growth in NO2. Reaching a 10-μg/m3 counterfactual target of NO2 concentration in China could avoid 0.33 (95% empirical CI: 0.19-0.49) million premature deaths and an LLE of 0.40 (95% empirical CI: 0.23-0.59) years in 2010, which greatly dropped to 0.24 (95% empirical CI: 0.14-0.36) million deaths and 0.21 (95% empirical CI: 0.12-0.31) years of LLE in 2020. The net fall in NO2-attributable deaths (-26.8%) between 2010 and 2020 was primarily driven by the declines in both NO2 concentration (-41.6%) and mortality rate (-27.1%) under population growth (+41.0%) and age structure transition (+0.9%).

CONCLUSIONS

Our findings provide national evidence for increased risk of premature death and loss of life expectancy attributed to later-life NO2 exposure among the elderly in China. In an accelerated aging society, strengthened clean air actions should be formulated to minimize the health burden and regional inequality in NO2-attributable mortality.

Source Attribution of Health Burdens From Ambient PM2.5, O3, and NO2 Exposure for Assessment of South Korean National Emission Control Scenarios by 2050

We quantify anthropogenic sources of health burdens associated with ambient air pollution exposure in South Korea and forecast future health burdens using domestic emission control scenarios by 2050 provided by the United Nations Environment Programme (UNEP). Our health burden estimation framework uses GEOS-Chem simulations, satellite-derived NO2, and ground-based observations of PM2.5, O3, and NO2. We estimate 19,000, 3,300, and 8,500 premature deaths owing to long-term exposure to PM2.5, O3, and NO2, respectively, and 23,000 NO2-associated childhood asthma incidences in 2016. Next, we calculate anthropogenic emission contributions to these four health burdens from each species and grid cell using adjoint sensitivity analysis. Domestic sources account for 56%, 38%, 87%, and 88% of marginal emission contributions to the PM2.5-, O3-, and NO2-associated premature deaths and the NO2-associated childhood asthma incidences, respectively. We project health burdens to 2050 using UNEP domestic emission scenarios (Baseline and Mitigation) and population forecasts from Statistics Korea. Because of population aging alone, there are 41,000, 10,000, and 20,000 more premature deaths associated with PM2.5, O3, and NO2 exposure, respectively, and 9,000 fewer childhood asthma incidences associated with NO2. The Mitigation scenario doubles the NO2-associated health benefits over the Baseline scenario, preventing 24,000 premature deaths and 13,000 childhood asthma incidences by 2050. It also slightly reduces PM2.5- and O3-associated premature deaths by 9.9% and 7.0%, unlike the Baseline scenario where these pollutants increase. Furthermore, we examine foreign emission impacts from nine SSP/RCP-based scenarios, highlighting the need for international cooperation to reduce PM2.5 and O3 pollution.

Temporal Trends in Air Pollution Exposure across Socioeconomic Groups in The Netherlands

Air pollution exposure has been linked to detrimental health outcomes. While cross-sectional studies have demonstrated socioeconomic disparities in air pollution exposure, longitudinal evidence on these disparities remains limited. The current study investigates trends in residential air pollution exposure across socioeconomic groups in the Netherlands from 2014 to 2019. Our dataset includes over 12.5 million individuals, aged 18 years and above, who resided in the Netherlands between 2014 and 2019, using Statistics Netherlands data. The address-level air pollution concentrations were estimated by dispersion models of the National Institute of Public Health and the Environment. We linked the exposure estimations of particulate matter < 10 or <2.5 μm (PM10, PM2.5) and nitrogen dioxide (NO2) to household-level socioeconomic data. In highly urbanized areas, individuals from both the lowest and highest socioeconomic groups were exposed to higher air pollution concentrations. Individuals from the lowest socioeconomic group were disproportionally located in highly urbanized and more polluted areas. The air pollution concentrations of PM10, PM2.5, and NO2 decreased between 2014 and 2019 for all the socioeconomic groups. The decrease in the annual average air pollution concentrations was the strongest for the lowest socioeconomic group, although differences in exposure between the socioeconomic groups remain. Further research is needed to define the health and equity implications.

Surrogate-Assisted and Filter-Based Multiobjective Evolutionary Feature Selection for Deep Learning

Feature selection (FS) for deep learning prediction models is a difficult topic for researchers to tackle. Most of the approaches proposed in the literature consist of embedded methods through the use of hidden layers added to the neural network architecture that modify the weights of the units associated with each input attribute so that the worst attributes have less weight in the learning process. Other approaches used for deep learning are filter methods, which are independent of the learning algorithm, which can limit the precision of the prediction model. Wrapper methods are impractical with deep learning due to their high computational cost. In this article, we propose new attribute subset evaluation FS methods for deep learning of the wrapper, filter and wrapper-filter hybrid types, where multiobjective and many-objective evolutionary algorithms are used as search strategies. A novel surrogate-assisted approach is used to reduce the high computational cost of the wrapper-type objective function, while the filter-type objective functions are based on correlation and an adaptation of the reliefF algorithm. The proposed techniques have been applied in a time series forecasting problem of air quality in the Spanish south-east and an indoor temperature forecasting problem in a domotic house, with promising results compared to other FS techniques used in the literature.

Geospatial artificial intelligence for estimating daytime and nighttime nitrogen dioxide concentration variations in Taiwan: A spatial prediction model

Nitrogen dioxide (NO2) is a major air pollutant primarily emitted from traffic and industrial activities, posing health risks. However, current air pollution models often underestimate exposure risks by neglecting the bimodal pattern of NO2 levels throughout the day. This study aimed to address this gap by developing ensemble mixed spatial models (EMSM) using geo-artificial intelligence (Geo-AI) to examine the spatial and temporal variations of NO2 concentrations at a high resolution of 50m. These EMSMs integrated spatial modelling methods, including kriging, land use regression, machine learning, and ensemble learning. The models utilized 26 years of observed NO2 measurements, meteorological parameters, geospatial layers, and social and season-dependent variables as representative of emission sources. Separate models were developed for daytime and nighttime periods, which achieved high reliability with adjusted R2 values of 0.92 and 0.93, respectively. The study revealed that mean NO2 concentrations were significantly higher at nighttime (9.60 ppb) compared to daytime (5.61 ppb). Additionally, winter exhibited the highest NO2 levels regardless of time period. The developed EMSMs were utilized to generate maps illustrating NO2 levels pre and during COVID restrictions in Taiwan. These findings could aid epidemiological research on exposure risks and support policy-making and environmental planning initiatives.

Nitrogen dioxide exposure, health outcomes, and associated demographic disparities due to gas and propane combustion by U.S. stoves

Gas and propane stoves emit nitrogen dioxide (NO2) pollution indoors, but the exposures of different U.S. demographic groups are unknown. We estimate NO2 exposure and health consequences using emissions and concentration measurements from >100 homes, a room-specific indoor air quality model, epidemiological risk parameters, and statistical sampling of housing characteristics and occupant behavior. Gas and propane stoves increase long-term NO2 exposure 4.0 parts per billion volume on average across the United States, 75% of the World Health Organization's exposure guideline. This increased exposure likely causes ~50,000 cases of current pediatric asthma from long-term NO2 exposure alone. Short-term NO2 exposure from typical gas stove use frequently exceeds both World Health Organization and U.S. Environmental Protection Agency benchmarks. People living in residences <800 ft2 in size incur four times more long-term NO2 exposure than people in residences >3000 ft2 in size; American Indian/Alaska Native and Black and Hispanic/Latino households incur 60 and 20% more NO2 exposure, respectively, than the national average.

Insights from Explainable Artificial Intelligence of Pollution and Socioeconomic Influences for Respiratory Cancer Mortality in Italy

Respiratory malignancies, encompassing cancers affecting the lungs, the trachea, and the bronchi, pose a significant and dynamic public health challenge. Given that air pollution stands as a significant contributor to the onset of these ailments, discerning the most detrimental agents becomes imperative for crafting policies aimed at mitigating exposure. This study advocates for the utilization of explainable artificial intelligence (XAI) methodologies, leveraging remote sensing data, to ascertain the primary influencers on the prediction of standard mortality rates (SMRs) attributable to respiratory cancer across Italian provinces, utilizing both environmental and socioeconomic data. By scrutinizing thirteen distinct machine learning algorithms, we endeavor to pinpoint the most accurate model for categorizing Italian provinces as either above or below the national average SMR value for respiratory cancer. Furthermore, employing XAI techniques, we delineate the salient factors crucial in predicting the two classes of SMR. Through our machine learning scrutiny, we illuminate the environmental and socioeconomic factors pertinent to mortality in this disease category, thereby offering a roadmap for prioritizing interventions aimed at mitigating risk factors.

Evaluating the sensitivity of mortality attributable to pollution to modeling Choices: A case study for Colorado

We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or using racial/ethnic group specific CRFs from the same epidemiologic study, 3) assigning exposure to residents based on home, instead of home and work locations for the state of Colorado. We found that the spatial scale of the analysis influences the magnitude of NO2, but not PM2.5, attributable deaths. Using county-level predictions instead of 1 km2 predictions of NO2 resulted in a lower estimate of mortality attributable to NO2 by ∼ 50 % for all of Colorado for each year between 2000 and 2020. Using an all-population CRF instead of racial/ethnic group specific CRFs results in a 130 % higher estimate of annual mortality attributable for the white population and a 40 % and 80 % lower estimate of mortality attributable to PM2.5 for Black and Hispanic residents, respectively. Using racial/ethnic group specific CRFs did not result in a different estimation of NO2 attributable mortality for white residents, but led to ∼ 50 % lower estimates of mortality for Black residents, and 290 % lower estimate for Hispanic residents. Using NO2 based on home instead of home and workplace locations results in a smaller estimate of annual mortality attributable to NO2 for all of Colorado by 2 % each year and 0.3 % for PM2.5. Our results should be interpreted as an exercise to make methodological recommendations for future health impact assessments of pollution.

The impact of air quality on cardiovascular health: A state of the art review

Air pollution is a global health challenge, increasing the risk of cardiovascular diseases such as heart disease, stroke, and arrhythmias. Particulate matter (PM), particularly PM2.5 and ultrafine particles (UFP), is a key contributor to the adverse effects of air pollution on cardiovascular health. PM exposure can lead to oxidative stress, inflammation, atherosclerosis, vascular dysfunction, cardiac arrhythmias, and myocardial injury. Reactive oxygen species (ROS) play a key role in mediating these effects. PM exposure can also lead to hypertension, a significant risk factor for cardiovascular disease. The COVID-19 pandemic resulted in a significant reduction of air pollutants, leading to a decline in the incidence of heart attacks and premature deaths caused by cardiovascular diseases. This review highlights the relationship between environmental air quality and cardiovascular health, elucidating the pathways through which air pollutants affect the cardiovascular system. It also emphasizes the need for increased awareness, collective efforts to mitigate the adverse effects of air pollution, and strategic policies for long-term air quality improvement to prevent the devastating effects of air pollution on global cardiovascular health.

Long-term NO2 exposure and mortality: A comprehensive meta-analysis

In response to the World Health Organization's (WHO) revised annual mean nitrogen dioxide (NO2) standard from 40 μg/m3 to 10 μg/m3, reflecting the growing evidence linking long-term exposure to ambient NO2 and excess mortality, we conducted a comprehensive meta-analysis incorporating 11 new studies published since the WHO analysis. Our investigation involved a systematic search of three major databases (PubMed, Web of Science, and Scopus) for articles published until July 1, 2022. We employed random effects models to calculate summarized risk ratios (RR) along with 95% confidence intervals (CIs) for overall and subgroup analyses. Sensitivity analyses were conducted to assess result robustness, and publication bias was evaluated using funnel plots and Egger's linear regression. Out of 2799 identified articles, 56 were included in our meta-analysis. The findings indicate a heightened risk of all-cause, cardiovascular, and respiratory mortality associated with long-term exposure to ambient NO2, with pooled RR values of 1.03 (95% CI: 1.02, 1.05), 1.07 (95% CI: 1.04, 1.10), and 1.03 (95% CI: 1.02, 1.05) per 10 μg/m3 increase, respectively. Substantial heterogeneity (I2 = 84%-96%) among studies was observed. Subgroup analysis revealed significantly elevated RR values in Asia and Oceania (p-value <0.05). The aggregated values for all-cause and cardiovascular mortality were slightly larger than those reported in previous studies. Our study emphasizes the imperative to develop more patient cohorts and conduct age-refined analyses to explore the impact of existing chronic diseases on these associations. Further, additional cohorts in Asia and Oceania are essential to fortify evidence in these regions. Lastly, we recommend using fused multi-source data with higher spatiotemporal resolution for individual exposure representation to minimize heterogeneity among studies in future research.

Reconstructing individual-level exposures in cohort analyses of environmental risks: an example with the UK Biobank

Recent developments in linkage procedures and exposure modelling offer great prospects for cohort analyses on the health risks of environmental factors. However, assigning individual-level exposures to large population-based cohorts poses methodological and practical problems. In this contribution, we illustrate a linkage framework to reconstruct environmental exposures for individual-level epidemiological analyses, discussing methodological and practical issues such as residential mobility and privacy concerns. The framework outlined here requires the availability of individual residential histories with related time periods, as well as high-resolution spatio-temporal maps of environmental exposures. The linkage process is carried out in three steps: (1) spatial alignment of the exposure maps and residential locations to extract address-specific exposure series; (2) reconstruction of individual-level exposure histories accounting for residential changes during the follow-up; (3) flexible definition of exposure summaries consistent with alternative research questions and epidemiological designs. The procedure is exemplified by the linkage and processing of daily averages of air pollution for the UK Biobank cohort using gridded spatio-temporal maps across Great Britain. This results in the extraction of exposure summaries suitable for epidemiological analyses of both short and long-term risk associations and, in general, for the investigation of temporal dependencies. The linkage framework presented here is generally applicable to multiple environmental stressors and can be extended beyond the reconstruction of residential exposures. IMPACT: This contribution describes a linkage framework to assign individual-level environmental exposures to population-based cohorts using high-resolution spatio-temporal exposure. The framework can be used to address current limitations of exposure assessment for the analysis of health risks associated with environmental stressors. The linkage of detailed exposure information at the individual level offers the opportunity to define flexible exposure summaries tailored to specific study designs and research questions. The application of the framework is exemplified by the linkage of fine particulate matter (PM2.5) exposures to the UK Biobank cohort.

Air pollution mortality benefits of sustained COVID-19 mobility restrictions in Australian cities

OBJECTIVES

Emissions from road traffic, power generation and industry were substantially reduced during pandemic lockdown periods globally. Thus, we analysed reductions in traffic-related air pollution in Australian capital cities during March-April 2020 and then modelled the mortality benefits that could be realised if similar reductions were sustained by structural policy interventions.

STUDY DESIGN

Satellite, air pollution monitor and land use observations were used to estimate ground-level nitrogen dioxide (NO2) concentrations in all Australian capital cities during: (a) a typical year with no prolonged air pollution events; (b) a hypothetical sustained reduction in NO2 equivalent to the COVID-19 lockdowns.

METHODS

We use the WHO recommended NO2 exposure-response coefficient for mortality (1.023, 95 % CI: 1.008-1.037, per 10 μg/m3 annual average) to assess gains in life expectancy and population-wide years of life from reduced exposure to traffic-related air pollution.

RESULTS

We attribute 1.1 % of deaths to anthropogenic NO2 exposures in Australian cities, corresponding to a total of 13,340 years of life lost annually. Although COVID-19-related reductions in NO2 varied widely between Australian cities during April 2020, equivalent and sustained reductions in NO2 emissions could reduce NO2-attributable deaths by 27 %, resulting in 3348 years of life gained annually.

CONCLUSIONS

COVID-19 mobility restrictions reduced NO2 emissions and population-wide exposures in Australian cities. When sustained to the same extent by policy interventions that reduce fossil fuel consumption by favouring the uptake of electric vehicles, active travel and public transport, the health, mortality and economic benefits will be measurable in Australian cities.

Environmental health impacts and inequalities in green space and air pollution in six medium-sized European cities

BACKGROUND

The GoGreenRoutes project aims to introduce co-created nature-based solutions (NBS) to enhance environmental quality in six medium-sized cities (Burgas, Lahti, Limerick, Tallinn, Umeå, and Versailles). We estimated the mortality and economic impacts attributed to suboptimal exposure to green space and air pollution, economic impacts, and the distribution thereof the adult population by socioeconomic status.

METHODS

We retrieved data from publicly accessible databases on green space (NDVI and % Green Area), air pollution (NO2 and PM2.5) and population (≥20 years, n = 804,975) at a 250m × 250m grid-cell level, and mortality for each city for 2015. We compared baseline exposures at the grid-cell to World Health Organization's recommendations and guidelines. We applied a comparative risk assessment to estimate the mortality burden attributable to not achieving the recommendations and guidelines. We estimated attributable mortality distributions and the association with income levels.

RESULTS

We found high variability in air pollution and green spaces levels. Around 60% of the population lacked green space and 90% were exposed to harmful air pollution. Overall, we estimated age-standardized mortality rates varying from 10 (Umeå) to 92 (Burgas) deaths per 100,000 persons attributable to low NDVI levels; 3 (Lahti) to 38 (Burgas) per 100,000 persons to lack of % Green Area; 1 (Umeå) to 88 (Tallinn) per 100,000 persons to exceedances of NO2 guidelines; and 1 (Umeå) to 206 (Burgas) per 100,000 persons to exceedances of PM2.5 guidelines. Lower income associated with higher or lower mortality impacts depending on whether deprived populations lived in the densely constructed, highly-trafficked city centre or greener, less polluted outskirts.

CONCLUSIONS

We attributed a considerable mortality burden to lack of green spaces and higher air pollution, which was unevenly distributed across different social groups. NBS and health-promoting initiatives should consider socioeconomic aspects to regenerate urban areas while providing equally good environments.

The built environment and cardiovascular disease: an umbrella review and meta-meta-analysis

AIMS

To provide a comprehensive overview of the current evidence on objectively measured neighbourhood built environment exposures in relation to cardiovascular disease (CVD) events in adults.

METHODS AND RESULTS

We searched seven databases for systematic reviews on associations between objectively measured long-term built environmental exposures, covering at least one domain (i.e. outdoor air pollution, food environment, physical activity environment like greenspace and walkability, urbanization, light pollution, residential noise, and ambient temperature), and CVD events in adults. Two authors extracted summary data and assessed the risk of bias independently. Robustness of evidence was rated based on statistical heterogeneity, small-study effect, and excess significance bias. Meta-meta-analyses were conducted to combine the meta-analysis results from reviews with comparable exposure and outcome within each domain. From the 3304 initial hits, 51 systematic reviews were included, covering 5 domains and including 179 pooled estimates. There was strong evidence of the associations between increased air pollutants (especially PM2.5 exposure) and increased residential noise with greater risk of CVD. Highly suggestive evidence was found for an association between increased ambient temperature and greater risk of CVD. Systematic reviews on physical activity environment, food environment, light pollution, and urbanization in relation to CVD were scarce or lacking.

CONCLUSION

Air pollutants, increased noise levels, temperature, and greenspace were associated with CVD outcomes. Standardizing design and exposure assessments may foster the synthesis of evidence. Other crucial research gaps concern the lack of prospective study designs and lack of evidence from low-to-middle-income countries (LMICs).

REGISTRATION

PROSPERO: CRD42021246580.

The Long-Term Mortality Effects Associated with Exposure to Particles and NOx in the Malmö Diet and Cancer Cohort

In this study, the long-term mortality effects associated with exposure to PM10 (particles with an aerodynamic diameter smaller than or equal to 10 µm), PM2.5 (particles with an aerodynamic diameter smaller than or equal to 2.5 µm), BC (black carbon), and NOx (nitrogen oxides) were analyzed in a cohort in southern Sweden during the period from 1991 to 2016. Participants (those residing in Malmö, Sweden, born between 1923 and 1950) were randomly recruited from 1991 to 1996. At enrollment, 30,438 participants underwent a health screening, which consisted of questionnaires about lifestyle and diet, a clinical examination, and blood sampling. Mortality data were retrieved from the Swedish National Cause of Death Register. The modeled concentrations of PM10, PM2.5, BC, and NOx at the cohort participants' home addresses were used to assess air pollution exposure. Cox proportional hazard models were used to estimate the associations between long-term exposure to PM10, PM2.5, BC, and NOx and the time until death among the participants during the period from 1991 to 2016. The hazard ratios (HRs) associated with an interquartile range (IQR) increase in each air pollutant were calculated based on the exposure lag windows of the same year (lag0), 1-5 years (lag1-5), and 6-10 years (lag6-10). Three models were used with varying adjustments for possible confounders including both single-pollutant estimates and two-pollutant estimates. With adjustments for all covariates, the HRs for PM10, PM2.5, BC, and NOx in the single-pollutant models at lag1-5 were 1.06 (95% CI: 1.02-1.11), 1.01 (95% CI: 0.95-1.08), 1.07 (95% CI: 1.04-1.11), and 1.11 (95% CI: 1.07-1.16) per IQR increase, respectively. The HRs, in most cases, decreased with the inclusion of a larger number of covariates in the models. The most robust associations were shown for NOx, with statistically significant positive HRs in all the models. An overall conclusion is that road traffic-related pollutants had a significant association with mortality in the cohort.

Health impact assessment for air pollution in the presence of regional variation in effect sizes: The implications of using different meta-analytic approaches

The estimated health effects of air pollution vary between studies, and this variation is caused by factors associated with the study location, hereafter termed regional heterogeneity. This heterogeneity raises a methodological question as to which studies should be used to estimate risks in a specific region in a health impact assessment. Should one use all studies across the world, or only those in the region of interest? The current study provides novel insight into this question in two ways. Firstly, it presents an up-to-date analysis examining the magnitude of continent-level regional heterogeneity in the short-term health effects of air pollution, using a database of studies collected by Orellano et al. (2020). Secondly, it provides in-depth simulation analyses examining whether existing meta-analyses are likely to be underpowered to identify statistically significant regional heterogeneity, as well as evaluating which meta-analytic technique is best for estimating region-specific estimates. The techniques considered include global and continent-specific (sub-group) random effects meta-analysis and meta-regression, with omnibus statistical tests used to quantify regional heterogeneity. We find statistically significant regional heterogeneity for 4 of the 8 pollutant-outcome pairs considered, comprising NO2, O3 and PM2.5 with all-cause mortality, and PM2.5 with cardiovascular mortality. From the simulation analysis statistically significant regional heterogeneity is more likely to be identified as the number of studies increases (between 3 and 30 in each region were considered), between region heterogeneity increases and within region heterogeneity decreases. Finally, while a sub-group analysis using Cochran's Q test has a higher median power (0.71) than a test based on the moderators' coefficients from meta-regression (0.59) to identify regional heterogeneity, it also has an inflated type-1 error leading to more false positives (median errors of 0.15 compared to 0.09).

Pulmonary, inflammatory, and oxidative effects of indoor nitrogen dioxide in patients with COPD

Introduction

Indoor nitrogen dioxide (NO2) sources include gas heating, cooking, and infiltration from outdoors. Associations with pulmonary function, systemic inflammation, and oxidative stress in patients with chronic obstructive pulmonary disease (COPD) are uncertain.

Methods

We recruited 144 COPD patients at the VA Boston Healthcare System between 2012 and 2017. In-home NO2 was measured using an Ogawa passive sampling badge for a week seasonally followed by measuring plasma biomarkers of systemic inflammation (C-reactive protein [CRP] and interleukin-6 [IL-6]), urinary oxidative stress biomarkers (8-hydroxy-2'deoxyguanosine [8-OHdG] and malondialdehyde [MDA]), and pre- and postbronchodilator spirometry. Linear mixed effects regression with a random intercept for each subject was used to assess associations with weekly NO2. Effect modification by COPD severity and by body mass index (BMI) was examined using multiplicative interaction terms and stratum-specific effect estimates.

Results

Median (25%ile, 75%ile) concentration of indoor NO2 was 6.8 (4.4, 11.2) ppb. There were no associations observed between NO2 with CRP, 8-OHdG, or MDA. Although the confidence intervals were wide, there was a reduction in prebronchodilator FEV1 and FVC among participants with more severe COPD (FEV1: -17.36 mL; -58.35, 23.60 and FVC: -28.22 mL; -91.49, 35.07) that was greater than in patients with less severe COPD (FEV1: -1.64 mL; -24.80, 21.57 and FVC: -6.22 mL; -42.16, 29.71). In participants with a BMI <30, there was a reduction in FEV1 and FVC.

Conclusions

Low-level indoor NO2 was not associated with systemic inflammation or oxidative stress. There was a suggestive association with reduced lung function among patients with more severe COPD and among patients with a lower BMI.

Association of short-term nitrogen dioxide exposure with hospitalization for urolithiasis in Xinxiang, China: a time series study

Urolithiasis accounts for the highest incidence of all urologic-associated hospitalizations. However, few studies have explored the effect of nitrogen dioxide (NO2) on hospitalizations for urolithiasis. We included 5956 patients with urolithiasis, collected daily meteorological and air pollution data between 2016 and 2021, and analyzed the associations between air pollutants and hospitalization, length of the hospital stay, and hospitalization costs attributable to urolithiasis. NO2 exposure was associated with an increased risk of hospitalization for urinary tract stones. For each 10-μg/m3 increase and 1-day lag of NO2, the maximum daily effect on the risk of hospitalization for urolithiasis was 1.020 (95% confidence interval [CI]: 1.001-1.039), and the cumulative effect peaked on lag day 4 (relative risk [RR]: 1.061; 95% CI: 1.003-1.122). Attribution scores and quantitative analysis revealed that the mean number of hospital days and mean hospital costs were 16 days and 21,164.39 RMB, respectively. Up to 5.75% of all urolithiasis hospitalizations were estimated to be attributable to NO2, and the cost of NO2-related urolithiasis hospitalizations reached approximately 3,430,000 RMB. Stratified analysis showed that NO2 had a more sensitive impact on urolithiasis hospitalizations in women and in those aged ≥65 years. Notably, men and those younger than 65 years of age (exclude people aged 65) incurred more costs for urolithiasis hospitalizations. In the population level, the association between NO2 and risk of urolithiasis hospitalization was more pronounced during the warm season. NO2 can increase hospitalizations for urolithiasis for Xinxiang City residents, and there is a cumulative lag effect. Focusing on air pollution may have practical significance in terms of the prevention and control of urolithiasis.

Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China

Background

Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk.

Methods

We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 μm (PM2.5), ≤10 μm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants.

Findings

During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM10 (mean [baseline]: 136.5 μg/m3), PM2.5 (mean [baseline]: 70.2 μg/m3), SO2 (mean [baseline]: 113.0 μg/m3) and NO2 (mean [baseline]: 39.2 μg/m3) were adversely and consistently associated with all mortality outcomes. A 10 μg/m3 increase in PM2.5 was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17-1.23), CVDs (1.23; 1.19-1.28), non-malignant RDs (1.37; 1.25-1.49) and lung cancer (1.14; 1.05-1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM2.5 consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO2 or PM10.

Interpretation

There was a strong and positive association of long-term individual and joint exposure to PM10, PM2.5, SO2, and NO2 with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM2.5 potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study.

Funding

National Key Research and Development Program of China, the China Scholarship Council, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province.

Linking Ambient NO2 Pollution Measures with Electronic Health Record Data to Study Asthma Exacerbations

Electronic health record (EHR)-derived data can be linked to geospatially distributed socioeconomic and environmental factors to conduct large-scale epidemiologic studies. Ambient NO2 is a known environmental risk factor for asthma. However, health exposure studies often rely on data from geographically sparse regulatory monitors that may not reflect true individual exposure. We contrasted use of interpolated NO2 regulatory monitor data with raw satellite measurements and satellite-derived ground estimates, building on previous work which has computed improved exposure estimates from remotely sensed data. Raw satellite and satellite-derived ground measurements captured spatial variation missed by interpolated ground monitor measurements. Multivariable analyses comparing these three NO2 measurement approaches (interpolated monitor, raw satellite, and satellite-derived) revealed a positive relationship between exposure and asthma exacerbations for both satellite measurements. Exposure-outcome relationships using the interpolated monitor NO2 were inconsistent with known relationships to asthma, suggesting that interpolated monitor data might yield misleading results in small region studies.

Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models

BACKGROUND

A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO₂. Assessing whether and to what extent air quality standards for NO₂ should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO₂ and related health risks, which have not been studied to date.

OBJECTIVE

We predicted ground NO₂ concentrations with high resolution in mainland China, explored exposure characteristics to NO₂ pollution, and assessed the mortality burden attributable to NO₂ exposure.

METHODS

Daily NO₂ concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO₂, population and area percentages with NO₂ exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO₂ exposure in China.

RESULTS

The cross-validation R²and root mean squared error of the NO₂ predicting model were 0.80 and 7.78 μg/m³, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO₂ exposure over 40 μg/m³ in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 μg/m³. NO₂ levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO₂ were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit.

CONCLUSION

In China, NO₂ pollution is associated with significant mortality burden. Spatial disparities exist in NO₂ pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO₂ pollution and exposure risk. Tightening the national standards for NO₂ is needed and will lead to significant health benefits.

Improved Performance of g-C3N4 for Optoelectronic Detection of NO2 Gas by Coupling Metal-Organic Framework Nanosheets with Coordinatively Unsaturated Ni(II) Sites

Sensitive and selective optoelectronic detection of NO₂ with g-C₃N₄ (CN) is critical, but it remains challenging to achieve ultralow concentration (ppb-level) detection. Herein, Ni metal-organic frameworks/CN nanosheet heterojunctions were successfully fabricated by the electrostatic induced assembly strategy and then treated by a post-alkali etching process for creating coordinatively unsaturated Ni(II) sites. The optimized heterojunction exhibits a record detection limitation of 1 ppb for NO₂, well below that observed on pristine CN, and an outstanding selectivity over other gases, along with long-time stability (120 days) at room temperature. The resulting superior detection performance benefits from the enhanced charge transfer and separation of the closely contacted heterojunction interface and the favorable adsorption of NO₂ by unsaturated Ni(II) as selective adsorption sites mainly by means of the time-resolved photoluminescence spectra and in situ X-ray photoelectron spectra. Moreover, the in situ Fourier transform infrared spectra and temperature-programmed desorption disclose that the promotion adsorption of NO₂ depends on the strengthened interaction between NO₂ and Ni(II) node sites at the aid of OH groups from unsaturated coordination. This work offers a versatile solution to develop promising CN-based optoelectronic sensors at room temperature.

Effectiveness of Mobility and Urban Sustainability Measures in Improving Citizen Health: A Scoping Review

BACKGROUND

The relationship between mobility and health has multiple dimensions, and the mobility model can be considered a public health intervention. Increasingly, mobility in cities is oriented towards incorporating sustainability criteria; however, there are many very diverse measures that cities carry out in terms of mobility and urban sustainability, and in many cases, these do not receive subsequent evaluation and/or study to analyse their effectiveness or impact. Currently, the literature does not offer any updated review of the measures applied in the different communities and countries.

AIM

To carry out a panoramic review of the measures implemented in the last 5 years to analyse which ones report a greater effectiveness and efficiency in health.

RESULTS

After applying the exclusion criteria of the study, a total of 16 articles were obtained for evaluation. The measures applied in terms of sustainability are grouped into four subgroups and their subsequent evaluation and possible impact on public health is analysed.

CONCLUSIONS

The present study found a large heterogeneous variety of sustainability measures in local settings around the world, which seem to reflect positive impacts on population health. However, subsequent evaluation of these measures is inconclusive in most cases. Further research and sharing across macro-communities are needed to establish universal criteria.

Traffic-Related Air Pollution and Breast Cancer Risk: A Systematic Review and Meta-Analysis of Observational Studies

Current evidence of an association of breast cancer (BC) risk with air pollution exposure, in particular from traffic exhaust, remains inconclusive, and the exposure assessment methodologies are heterogeneous. This study aimed to conduct a systematic review and meta-analysis on the association between traffic-related air pollution (TRAP) and BC incidence (PROSPERO CRD42021286774). We systematically reviewed observational studies assessing exposure to TRAP and BC risk published until June 2022, available on Medline/PubMed and Web of Science databases. Studies using models for assessing exposure to traffic-related air pollutants or using exposure proxies (including traffic density, distance to road, etc.) were eligible for inclusion. A random-effects meta-analysis of studies investigating the association between NO₂/NO_x exposure and BC risk was conducted. Overall, 21 studies meeting the inclusion criteria were included (seven case-control, one nested case-control, 13 cohort studies); 13 studies (five case-control, eight cohort) provided data for inclusion in the meta-analyses. Individual studies provided little evidence of an association between TRAP and BC risk; exposure assessment methods and time periods of traffic emissions were different. The meta-estimate on NO₂ exposure indicated a positive association (pooled relative risk per 10 µg/m³ of NO₂: 1.015; 95% confidence interval, CI: 1.003; 1.028). No association between NO_x exposure and BC was found (three studies). Although there was limited evidence of an association for TRAP estimated with proxies, the meta-analysis showed a significant association between NO₂ exposure, a common TRAP pollutant marker, and BC risk, yet with a small effect size. Our findings provide additional support for air pollution carcinogenicity.

Quantifying COVID-19's silver lining: Avoided deaths from air quality improvements in Bogotá

In cities around the world, COVID-19 lockdowns have significantly improved outdoor air quality. Even if only temporary, these improvements could have longer-lasting effects by making chronic air pollution more salient and boosting political pressure for change. To that end, it is important to develop objective estimates of both the air quality improvements associated with lockdowns and the benefits they generate. We use panel data econometric models to estimate the effect of Bogotá's 16-month lockdown on PM_2.5 and NO₂ pollution, epidemiological models to simulate the effect of reductions in these pollutants on long- and short-term mortality, and benefit transfer methods to value the avoided mortality. We find that on average, Bogotá's lockdown cut PM_2.5 pollution by 15% and NO₂ pollution by 21%. However, the magnitude of these effects varied considerably over time and across the city's neighborhoods. Equivalent permanent reductions in these pollutants would reduce long-term premature deaths from air pollution by 23% each year, a benefit valued at $1 billion annually. Finally, we estimate that if they occurred ceteris paribus, the temporary reductions in pollutant concentrations in 2020-2021 due to Bogotá's lockdown would have cut short-term deaths from air pollution by 19%, a benefit valued at $244 million.

Etiology of lung cancer: Evidence from epidemiologic studies

Lung cancer is one of the leading causes of cancer incidence and mortality worldwide. While smoking, radon, air pollution, as well as occupational exposure to asbestos, diesel fumes, arsenic, beryllium, cadmium, chromium, nickel, and silica are well-established risk factors, many lung cancer cases cannot be explained by these known risk factors. Over the last two decades the incidence of adenocarcinoma has risen, and it now surpasses squamous cell carcinoma as the most common histologic subtype. This increase warrants new efforts to identify additional risk factors for specific lung cancer subtypes as well as a comprehensive review of current evidence from epidemiologic studies to inform future studies. Given the myriad exposures individuals experience in real-world settings, it is essential to investigate mixture effects from complex exposures and gene-environment interactions in relation to lung cancer and its subtypes.

Disparities in Air Pollutants Across Racial, Ethnic, and Poverty Groups at US Public Schools

We investigate socioeconomic disparities in air quality at public schools in the contiguous US using high resolution estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations. We find that schools with higher proportions of people of color (POC) and students eligible for the federal free or reduced lunch program, a proxy for poverty level, are associated with higher pollutant concentrations. For example, we find that the median annual NO2 concentration for White students, nationally, was 7.7 ppbv, compared to 9.2 ppbv for Black and African American students. Statewide and regional disparities in pollutant concentrations across racial, ethnic, and poverty groups are consistent with nationwide results, where elevated NO2 concentrations were associated with schools with higher proportions of POC and higher levels of poverty. Similar, though smaller, differences were found in PM2.5 across racial and ethnic groups in most states. Racial, ethnic, and economic segregation across the rural-urban divide is likely an important factor in pollution disparities at US public schools. We identify distinct regional patterns of disparities, highlighting differences between California, New York, and Florida. Finally, we highlight that disparities exist not only across urban and non-urban lines but also within urban environments.

Daily Satellite Observations of Nitrogen Dioxide Air Pollution Inequality in New York City, New York and Newark, New Jersey: Evaluation and Application

Urban air pollution disproportionately harms communities of color and low-income communities in the U.S. Intraurban nitrogen dioxide (NO₂) inequalities can be observed from space using the TROPOspheric Monitoring Instrument (TROPOMI). Past research has relied on time-averaged measurements, limiting our understanding of how neighborhood-level NO₂ inequalities co-vary with urban air quality and climate. Here, we use fine-scale (250 m × 250 m) airborne NO₂ remote sensing to demonstrate that daily TROPOMI observations resolve a major portion of census tract-scale NO₂ inequalities in the New York City-Newark urbanized area. Spatiotemporally coincident TROPOMI and airborne inequalities are well correlated (r = 0.82-0.97), with slopes of 0.82-1.05 for relative and 0.76-0.96 for absolute inequalities for different groups. We calculate daily TROPOMI NO₂ inequalities over May 2018-September 2021, reporting disparities of 25-38% with race, ethnicity, and/or household income. Mean daily inequalities agree with results based on TROPOMI measurements oversampled to 0.01° × 0.01° to within associated uncertainties. Individual and mean daily TROPOMI NO₂ inequalities are largely insensitive to pixel size, at least when pixels are smaller than ∼60 km², but are sensitive to low observational coverage. We statistically analyze daily NO₂ inequalities, presenting empirical evidence of the systematic overburdening of communities of color and low-income neighborhoods with polluting sources, regulatory ozone co-benefits, and worsened NO₂ inequalities and cumulative NO₂ and urban heat burdens with climate change.

New sights on the impact of spatial composition of production factors for socioeconomic recovery in the post-epidemic era: a case study of cities in central and eastern China

The COVID-19 pandemic led to a sharp economic contraction. A comprehensive understanding of the relationship between the spatial composition of production factor (SCPF) and socioeconomic recovery is still missing. Here, we applied the contrasting status of nitrogen dioxide (NO₂) concentrations in cities in central and eastern China as natural laboratories. From the perspective of the spatial composition of land (SCL) and the dependence on the inflow population (DIP), four quantifiable indicators (resilience, impact, sensitivity, recovery speed) were used to analyze the adaptability of SCPF to the epidemic lockdown. The results indicate that appropriate SCPF is a prerequisite for a complete "land-population-industry" nexus. The built-up area proportion is below 74.38%, with higher adaptability to epidemic shocks. The range of rural built-up proportion conducive to economic recovery is 10.18%-15.18%. The proportions of various land types inside the city's defense unit should also be constrained. Similarly, DIP is advocated to be maintained below 17.5%. For urban-rural fringe areas, the response to epidemic prevention and socioeconomic recovery are rapid. This observation-driven study indicated that COVID-19 is a shocking reminder for policymakers, to improve the socioeconomic recovery ability from the spatial composition of production factor perspective in the post-COVID-19 era.

National Land Use Regression Model for NO2 Using Street View Imagery and Satellite Observations

Land use regression (LUR) models are widely applied to estimate intra-urban air pollution concentrations. National-scale LURs typically employ predictors from multiple curated geodatabases at neighborhood scales. In this study, we instead developed national NO₂ models relying on innovative street-level predictors extracted from Google Street View [GSV] imagery. Using machine learning (random forest), we developed two types of models: (1) GSV-only models, which use only GSV features, and (2) GSV + OMI models, which also include satellite observations of NO₂. Our results suggest that street view imagery alone may provide sufficient information to explain NO₂ variation. Satellite observations can improve model performance, but the contribution decreases as more images are available. Random 10-fold cross-validation R² of our best models were 0.88 (GSV-only) and 0.91 (GSV + OMI)─a performance that is comparable to traditional LUR approaches. Importantly, our models show that street-level features might have the potential to better capture intra-urban variation of NO₂ pollution than traditional LUR. Collectively, our findings indicate that street view image-based modeling has great potential for building large-scale air quality models under a unified framework. Toward that goal, we describe a cost-effective image sampling strategy for future studies based on a systematic evaluation of image availability and model performance.

Outdoor air quality and human health: An overview of reviews of observational studies

The epidemiological evidence supporting putative associations between air pollution and health-related outcomes continues to grow at an accelerated pace with a considerable heterogeneity and with varying consistency based on the outcomes assessed, the examined surveillance system, and the geographic region. We aimed to evaluate the strength of this evidence base, to identify robust associations as well as to evaluate effect variation. An overview of reviews (umbrella review) methodology was implemented. PubMed and Scopus were systematically screened (inception-3/2020) for systematic reviews and meta-analyses examining the association between air pollutants, including CO, NO_X, NO₂, O₃, PM₁₀, PM_2.5, and SO₂ and human health outcomes. The quality of systematic reviews was evaluated using AMSTAR. The strength of evidence was categorized as: strong, highly suggestive, suggestive, or weak. The criteria included statistical significance of the random-effects meta-analytical estimate and of the effect estimate of the largest study in a meta-analysis, heterogeneity between studies, 95% prediction intervals, and bias related to small study effects. Seventy-five systematic reviews of low to moderate methodological quality reported 548 meta-analyses on the associations between outdoor air quality and human health. Of these, 57% (N = 313) were not statistically significant. Strong evidence supported 13 associations (2%) between elevated PM_2.5, PM₁₀, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory or pregnancy/birth-related outcomes. Twenty-three (4%) highly suggestive associations were identified on elevated PM_2.5, PM₁₀, O₃, NO₂, and SO₂ concentrations and increased risk of cardiorespiratory, kidney, autoimmune, neurodegenerative, cancer or pregnancy/birth-related outcomes. Sixty-seven (12%), and 132 (24%) meta-analyses were graded as suggestive, and weak, respectively. Despite the abundance of research on the association between outdoor air quality and human health, the meta-analyses of epidemiological studies in the field provide evidence to support robust associations only for cardiorespiratory or pregnancy/birth-related outcomes.

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.

Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort

BACKGROUND

The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort.

METHODS

Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants' baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise.

RESULTS

The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found.

CONCLUSIONS

We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise.

The impact of urban environmental exposures on health: An assessment of the attributable mortality burden in Sao Paulo city, Brazil

BACKGROUND

Currently, more than half of the global population lives in cities. Contemporary urban planning practices result in environmental risk factors (e.g. air pollution, noise, lack of green space, excess heat) that put health and well-being of city dwellers at risk and contribute to chronic diseases and premature death. Despite a growing body of evidence on adverse health impacts related to current urban and transport planning practices, especially for cities in the Global North, not much is known about associated health impacts in South American cities. Therefore, we estimated the mortality burden attributable to breaching internationally-recommended or locally-preferable exposure levels of urban planning related environmental exposures in Sao Paulo, Brazil.

METHODS

We carried out a health impact assessment study, following the comparative risk assessment framework, to assess preventable mortality impacts of breaching exposure recommendations for air pollution, green spaces and temperature at the census tract (CT) level (n = 18,363). We also assessed the distribution thereof by socioeconomic vulnerability.

RESULTS

We estimated that annually 11,372 (95% CI: 7921; 15,910) attributable deaths could be prevented by complying with recommended exposure levels. The largest proportion of preventable mortality was due to breaching air pollution limits (i.e. 8409 attributable deaths), followed by insufficient green space (i.e. 2593), and excess heat (i.e. 370). Adverse health impacts were larger in CTs of lower socioeconomic vulnerability, due to demographic profile, traffic density and residential area configurations.

DISCUSSION

Not complying with the health limits for air pollution, green space and temperature exposures resulted in a considerable preventable mortality burden (i.e. 17% of total expected deaths) in Sao Paulo. This burden can be reduced by improving current urban and transport planning practices.

An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations

Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.

Ambient air pollution and cardiovascular diseases: An umbrella review of systematic reviews and meta-analyses

The available evidence on the effects of ambient air pollution on cardiovascular diseases (CVDs) has increased substantially. In this umbrella review, we summarized the current epidemiological evidence from systematic reviews and meta-analyses linking ambient air pollution and CVDs, with a focus on geographical differences and vulnerable subpopulations. We performed a search strategy through multiple databases including articles between 2010 and 31 January 2021. We performed a quality assessment and evaluated the strength of evidence. Of the 56 included reviews, the most studied outcomes were stroke (22 reviews), all-cause CVD mortality, and morbidity (19). The strongest evidence was found between higher short- and long-term ambient air pollution exposure and all-cause CVD mortality and morbidity, stroke, blood pressure, and ischemic heart diseases (IHD). Short-term exposures to particulate matter <2.5 μm (PM2.5 ), <10 μm (PM10 ), and nitrogen oxides (NOx ) were consistently associated with increased risks of hypertension and triggering of myocardial infarction (MI), and stroke (fatal and nonfatal). Long-term exposures of PM2.5 were largely associated with increased risk of atherosclerosis, incident MI, hypertension, and incident stroke and stroke mortality. Few reviews evaluated other CVD outcomes including arrhythmias, atrial fibrillation, or heart failure but they generally reported positive statistical associations. Stronger associations were found in Asian countries and vulnerable subpopulations, especially among the elderly, cardiac patients, and people with higher weight status. Consistent with experimental data, this comprehensive umbrella review found strong evidence that higher levels of ambient air pollution increase the risk of CVDs, especially all-cause CVD mortality, stroke, and IHD. These results emphasize the importance of reducing the alarming levels of air pollution across the globe, especially in Asia, and among vulnerable subpopulations.

Modeling COVID-19 Impact on Consumption and Mobility in Europe: A Legacy Toward Sustainable Business Performance

This article has explored the impact of coronavirus disease 2019 (COVID-19)-induced decline in consumer durables and mobility on nitrogen dioxide (NO2) emission in Europe by providing empirical and graphical justifications based on consumer price index (CPI) and gross domestic product (GDP) deflator indexes. The empirical estimations show that carbon dioxide (CO2) and NOx emission along with other greenhouse gases drastically decreased in the wake of COVID-19-induced lockdowns and decrease in the demand of consumer goods in Europe. This means that COVID-19 improved environment in the European region. However, high cost (e.g., unemployment, loss of life, and social segregation) makes COVID-19 an unstable solution to environmental woes where positive impact of COVID-19 on environment achieved in short run cannot be guaranteed in the long run. Besides environment, COVID-19 drastically curtailed economic activities and exposed them to the risk of economic crisis particularly in case of Europe.

Air pollution at the residence of Danish adults, by socio-demographic characteristics, morbidity, and address level characteristics

BACKGROUND

Exposure to outdoor air pollution is associated with adverse health effects. Previous studies have indicated higher levels of air pollution in socially deprived areas.

AIM

To investigate associations between air pollution and socio-demographic variables, comorbidity, stress, and green space at the residence in Denmark.

METHODS

We included 2,237,346 persons living in Denmark, aged 35 years or older in 2017. We used the high resolution, multi-scale DEHM/UBM/AirGIS air pollution modelling system to calculate mean concentrations of air pollution with PM_2.5, elemental carbon, ultrafine particles and NO₂ at residences held the preceding five years. We used nationwide registries to retrieve information about socio-demographic indicators at the individual and neighborhood levels. We used general linear regression models to analyze associations between socio-demographic indicators and air pollution at the residence.

RESULTS

Individuals with high SES (income, higher white-collar worker and high educational level) and of non-Danish origin were exposed to higher levels of air pollution than individuals of low SES and of Danish origin, respectively. We found comparable levels of air pollution according to sex, stress events and morbidity. For neighborhood level SES indicators, we found high air pollution levels in neighborhoods with low SES measured as proportion of social housing, sole providers, low income and unemployment. In contrast, we found higher air pollution levels in neighborhoods with higher educational level and a low proportion of manual labor. People living in an apartment and/or with little green space had higher air pollution levels.

CONCLUSION

In Denmark, high levels of residential air pollution were associated with higher individual SES and non-Danish origin. For neighborhood-level indicators of SES, no consistent pattern was observed. These results highlight the need for analyzing many different socio-demographic indicators to understand the complex associations between SES and exposure to air pollution.

Vehicular Traffic in Urban Areas: Health Burden and Influence of Sustainable Urban Planning and Mobility

Vehicular traffic is one of the major sources of air pollution in European cities. This work aims to understand which characteristics of the urban environment could influence mobility-related air pollution, quantify the health impacts of exposure to traffic-derived PM2.5 and NO2 concentrations, and assess the potential health benefits expected from traffic interventions. The health benefits modeled are intended to provide a set of comparable data to support decision-makers and encourage informed decision-making to design healthier cities. Targeting a large geographical coverage, 12 European cities from 9 countries were comparatively assessed in terms of mean daily traffic volume/area, the number of public transport stops/area, and the percentage of green and outdoor leisure areas, among other urban indicators. This was implemented using an open-source data mining tool, which was seen as a useful engine to identify potential strategies to improve air quality. The comparison of urban indicators in the selected cities evidenced two trends: (a) cities with the most heterogeneous distribution of public transport stops, as an indicator of poor accessibility, are also those with the lowest proportion of km dedicated to cycleways and footways, highlighting the need in these cities for more sustainable mobility management; and (b) the percentage of green and outdoor leisure areas may influence the share of journeys by bicycle, pointing out that promoting the perception of green routes is relevant to enhance the potential of active transport modes. Socioeconomic factors can be key determinants of the urban indicators and would need further consideration. For the health impact assessment (HIA), two baseline scenarios were evaluated and compared. One is based on mean annual traffic contributions to PM2.5 concentrations in each target city (ranging between 1.9 and 13 µg/m3), obtained from the literature, and the second is grounded on mean annual NO2 concentrations at all available traffic and urban background stations within each city (17.2–83.5 µg/m3), obtained from the European Environment Agency database. The intervention scenarios modeled were designed based on traffic mitigation strategies in the literature, and set to ranges of 6–50% in traffic-derived PM2.5 concentrations and of 4–12.5% in NO2 concentrations. These scenarios could result in only a 1.7% (0.6–4%) reduction in premature mortality due to exposure to traffic-derived PM2.5, and 1.0% (0.4–2%) due to exposure to NO2, as the mean for all the cities. This suggests that more ambitious pollution abatement strategies should be targeted.