Fine particle air pollution and lung cancer risk: Extending the long list of health risks.

Exposures to fine particulate matter (PM2.5) concentrations above the WHO guidelines affect 99% of the world population. In a recent issue of Nature, Hill et al. dissect the tumor promotion paradigm orchestrated by PM2.5 inhalation exposures in lung carcinogenesis, supporting the hypothesis that PM2.5 can increase your risk of lung carcinoma without ever smoking.

Adopting electric school buses in the United States: Health and climate benefits.

Electric school buses have been proposed as an alternative to reduce the health and climate impacts of the current U.S. school bus fleet, of which a substantial share are highly polluting old diesel vehicles. However, the climate and health benefits of electric school buses are not well known. As they are substantially more costly than diesel buses, assessing their benefits is needed to inform policy decisions. We assess the health benefits of electric school buses in the United States from reduced adult mortality and childhood asthma onset risks due to exposure to ambient fine particulate matter (PM2.5). We also evaluate climate benefits from reduced greenhouse-gas emissions. We find that replacing the average diesel bus in the U.S. fleet in 2017 with an electric bus yields $84,200 in total benefits. Climate benefits amount to $40,400/bus, whereas health benefits amount to $43,800/bus due to 4.42*10-3 fewer PM2.5-attributable deaths ($40,000 of total) and 7.42*10-3 fewer PM2.5-attributable new childhood asthma cases ($3,700 of total). However, health benefits of electric buses vary substantially by driving location and model year (MY) of the diesel buses they replace. Replacing old, MY 2005 diesel buses in large cities yields $207,200/bus in health benefits and is likely cost-beneficial, although other policies that accelerate fleet turnover in these areas deserve consideration. Electric school buses driven in rural areas achieve small health benefits from reduced exposure to ambient PM2.5. Further research assessing benefits of reduced exposure to in-cabin air pollution among children riding buses would be valuable to inform policy decisions.

Climate and health benefits of a transition from gas to electric cooking.

Household electrification is thought to be an important part of a carbon-neutral future and could also have additional benefits to adopting households such as improved air quality. However, the effectiveness of specific electrification policies in reducing total emissions and boosting household livelihoods remains a crucial open question in both developed and developing countries. We investigated a transition of more than 750,000 households from gas to electric cookstoves-one of the most popular residential electrification strategies-in Ecuador following a program that promoted induction stoves and assessed its impacts on electricity consumption, greenhouse gas emissions, and health. We estimate that the program resulted in a 5% increase in total residential electricity consumption between 2015 and 2021. By offsetting a commensurate amount of cooking gas combustion, we find that the program likely reduced national greenhouse gas emissions, thanks in part to the country's electricity grid being 80% hydropower in later parts of the time period. Increased induction stove uptake was also associated with declines in all-cause and respiratory-related hospitalizations nationwide. These findings suggest that, when the electricity grid is largely powered by renewables, gas-to-induction cooking transitions represent a promising way of amplifying the health and climate cobenefits of net-carbon-zero policies.

Location-specific strategies for eliminating US national racial-ethnic [Formula: see text] exposure inequality.

Air pollution levels in the United States have decreased dramatically over the past decades, yet national racial-ethnic exposure disparities persist. For ambient fine particulate matter ([Formula: see text]), we investigate three emission-reduction approaches and compare their optimal ability to address two goals: 1) reduce the overall population average exposure ("overall average") and 2) reduce the difference in the average exposure for the most exposed racial-ethnic group versus for the overall population ("national inequalities"). We show that national inequalities in exposure can be eliminated with minor emission reductions (optimal: ~1% of total emissions) if they target specific locations. In contrast, achieving that outcome using existing regulatory strategies would require eliminating essentially all emissions (if targeting specific economic sectors) or is not possible (if requiring urban regions to meet concentration standards). Lastly, we do not find a trade-off between the two goals (i.e., reducing overall average and reducing national inequalities); rather, the approach that does the best for reducing national inequalities (i.e., location-specific strategies) also does as well as or better than the other two approaches (i.e., sector-specific and meeting concentration standards) for reducing overall averages. Overall, our findings suggest that incorporating location-specific emissions reductions into the US air quality regulatory framework 1) is crucial for eliminating long-standing national average exposure disparities by race-ethnicity and 2) can benefit overall average exposures as much as or more than the sector-specific and concentration-standards approaches.

Four Years of Active Sampling and Measurement of Atmospheric Polycyclic Aromatic Hydrocarbons and Oxygenated Polycyclic Aromatic Hydrocarbons in Dronning Maud Land, East Antarctica.

Antarctica, protected by its strong polar vortex and sheer distance from anthropogenic activity, was always thought of as pristine. However, as more data on the occurrence of persistent organic pollutants on Antarctica emerge, the question arises of how fast the long-range atmospheric transport takes place. Therefore, polycyclic aromatic hydrocarbons (PAHs) and oxygenated (oxy-)PAHs were sampled from the atmosphere and measured during 4 austral summers from 2017 to 2021 at the Princess Elisabeth station in East Antarctica. The location is suited for this research as it is isolated from other stations and activities, and the local pollution of the station itself is limited. A high-volume sampler was used to collect the gas and particle phase (PM10) separately. Fifteen PAHs and 12 oxy-PAHs were quantified, and concentrations ranging between 6.34 and 131 pg m3 (Σ15PAHs-excluding naphthalene) and between 18.8 and 114 pg m3 (Σ13oxy-PAHs) were found. Phenanthrene, pyrene, and fluoranthene were the most abundant PAHs. The gas-particle partitioning coefficient log(Kp) was determined for 6 compounds and was found to lie between 0.5 and -2.5. Positive matrix factorization modeling was applied to the data set to determine the contribution of different sources to the observed concentrations. A 6-factor model proved a good fit to the data set and showed strong variations in the contribution of different air masses. During the sampling campaign, a number of volcanic eruptions occurred in the southern hemisphere from which the emission plume was detected. The FLEXPART dispersion model was used to confirm that the recorded signal is indeed influenced by volcanic eruptions. The data was used to derive a transport time of between 11 and 33 days from release to arrival at the measurement site on Antarctica.

Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep.

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

Urban Air-Quality Estimation Using Visual Cues and a Deep Convolutional Neural Network in Bengaluru (Bangalore), India.

Mobile monitoring provides robust measurements of air pollution. However, resource constraints often limit the number of measurements so that assessments cannot be obtained in all locations of interest. In response, surrogate measurement methodologies, such as videos and images, have been suggested. Previous studies of air pollution and images have used static images (e.g., satellite images or Google Street View images). The current study was designed to develop deep learning methodologies to infer on-road pollutant concentrations from videos acquired with dashboard cameras. Fifty hours of on-road measurements of four pollutants (black carbon, particle number concentration, PM2.5 mass concentration, carbon dioxide) in Bengaluru, India, were analyzed. The analysis of each video frame involved identifying objects and determining motion (by segmentation and optical flow). Based on these visual cues, a regression convolutional neural network (CNN) was used to deduce pollution concentrations. The findings showed that the CNN approach outperformed several other machine learning (ML) techniques and more conventional analyses (e.g., linear regression). The CO2 prediction model achieved a normalized root-mean-square error of 10-13.7% for the different train-validation division methods. The results here thus contribute to the literature by using video and the relative motion of on-screen objects rather than static images and by implementing a rapid-analysis approach enabling analysis of the video in real time. These methods can be applied to other mobile-monitoring campaigns since the only additional equipment they require is an inexpensive dashboard camera.

The synergy effect of energy security and carbon-haze collaborative management: From the perspective of biased technological progress.

It is important to ensure energy security and achieve carbon-haze collaborative management for sustainable development. Reducing imported energy dependence is necessary to maintain energy security, while its impact on environmental quality remains unclear. From the perspective of biased technological progress, this paper estimates the level of biased technological progress towards self-sufficient energy by a heterogeneous stochastic frontier analysis (SFA) function, and then empirically examines whether self-sufficient energy biased technological progress has a dampening effect on haze pollution and carbon emissions. It is found that: (1) Self-sufficient energy biased technological progress can effectively reduce haze pollution and carbon emissions, achieving a synergistic effect between energy security and carbon-haze collaborative management. (2) "Efficiency enhancement" and "quality improvement" are the essential mechanisms for the synergistic effect. (3) Environmental regulation, abundant resource and technology endowments can enhance the haze reduction effect. And the lower dependence on foreign trade and stable global economic policy environment are more conducive to achieving carbon-haze collaborative control. (4) In the Eastern and Western regions, self-sufficient energy biased technology can be sped up to alleviate haze pollution. The findings can enrich the research exploring pollution control from the perspective of biased technological progress, and provide policy recommendations for promoting high-quality development.

Information consumption city and carbon emission efficiency: Evidence from China's quasi-natural experiment.

The transformation of public consumption patterns has become a burning question, but there are few studies on public consumption patterns. Therefore, evaluating the impact of Information consumption city (ICC) policy on carbon emission efficiency holds significant implications. This study settles on 104 pilot cities in China from 2006 to 2020 to assess the impact and the response mechanism of ICC policy on carbon emission efficiency through the time-vary Difference-in-Difference (DID) model. The result shows that: (1) ICC policy significantly promotes the local carbon emission efficiency, which remains robust after a battery of sensitivity tests. (2) It improves carbon emission efficiency through production factors agglomeration effect, industrial structural changing effect, innovation promotion effect, and environmental attention effect; (3) The direct impact of ICC policy on carbon emission efficiency varies across regions with different information consumption and carbon emission base. (4) ICC can improve carbon emission efficiency through the joint implementation of smart city (SC), new urbanization (NU), ecological civilization city construction (EC), Belt and Road Initiative (BR), Broadband China (BC), low-carbon city pilot policy (LCC), and air quality standards (AQS) policy.

A comprehensive review and perspective research in technology integration for the treatment of gaseous volatile organic compounds.

Volatile organic compounds (VOCs) are harmful pollutants emitted from industrial processes. They pose a risk to human health and ecosystems, even at low concentrations. Controlling VOCs is crucial for good air quality. This review aims to provide a comprehensive understanding of the various methods used for controlling VOC abatement. The advancement of mono-functional treatment techniques, including recovery such as absorption, adsorption, condensation, and membrane separation, and destruction-based methods such as natural degradation methods, advanced oxidation processes, and reduction methods were discussed. Among these methods, advanced oxidation processes are considered the most effective for removing toxic VOCs, despite some drawbacks such as costly chemicals, rigorous reaction conditions, and the formation of secondary chemicals. Standalone technologies are generally not sufficient and do not perform satisfactorily for the removal of hazardous air pollutants due to the generation of innocuous end products. However, every integration technique complements superiority and overcomes the challenges of standalone technologies. For instance, by using catalytic oxidation, catalytic ozonation, non-thermal plasma, and photocatalysis pretreatments, the amount of bioaerosols released from the bioreactor can be significantly reduced, leading to effective conversion rates for non-polar compounds, and opening new perspectives towards promising techniques with countless benefits. Interestingly, the three-stage processes have shown efficient decomposition performance for polar VOCs, excellent recoverability for nonpolar VOCs, and promising potential applications in atmospheric purification. Furthermore, the review also reports on the evolution of mathematical and artificial neural network modeling for VOC removal performance. The article critically analyzes the synergistic effects and advantages of integration. The authors hope that this article will be helpful in deciding on the appropriate strategy for controlling interested VOCs.

Co-benefits and influencing factors exploration of air pollution and carbon reduction in China: Based on marginal abatement costs.

This study addresses the pressing need for cost-effective emission reduction strategies that maximize co-benefits in terms of air pollution and carbon emissions. Our research contributes to the literature by accurately measuring these co-benefits, thereby facilitating their prompt realization in different regions. We employ an input-output framework that integrates carbon emissions and air pollution, allowing us to calculate marginal abatement costs using the shadow price of undesired output. Through this approach, we quantify the co-benefits and analyze the factors influencing them at both spatiotemporal and factor levels using spatial kernel density and geographical detectors. Our findings reveal several key insights: (1) under joint emission reduction efforts, we observe average annual reduction rates of 6.46% for marginal pollution and 6.10% for carbon reduction costs. Importantly, we document an increase in co-benefits from 0.50 to 0.86, characterized by an initial fluctuation followed by a linear increase. (2) the marginal cost difference for carbon emission and pollution reduction in western China was 179.45 and 155.08 respectively, compared to 321.51 and 124.70 in the Northeast, highlighting the crucial role of regional differences in shaping co-benefit outcomes. (3) we identify a negative spatial spillover effect between provinces, which diminishes over time, leading to heterogeneous effects when local provincial co-benefits exceed a threshold of 0.9. (4) during the adjustment period, we find that the industrial structure exerts significant single and interactive effects on co-benefits. Additionally, we highlight the critical role of environmental governance investment and government intervention as drivers of co-benefits in the current era. By offering the quantification of co-benefits under the marginal abatement costs, our study provides valuable scientific insights for planning and implementing effective synergy strategies.

Quantification for photochemical loss of volatile organic compounds upon ozone formation chemistry at an industrial city (Zibo) in North China Plain.

Volatile organic compounds (VOCs) are consumed by photochemical reactions during transport, leading to inaccuracies in estimating the local ozone (O3) formation mechanism and its subsequent strategy for O3 attainment. To comprehensively quantify the deviations in O3 formation mechanism by consumed VOCs (C-VOCs), a 5-month field campaign was conducted in a typical industrial city in Northern China over incorporating a 0-D box model (implemented with MCMv3.3.1). The averaged C-VOCs concentration was 6.8 ppbv during entire period, and Alkenes accounted for 62% dominantly. Without considering C-VOCs, the relative incremental reactivity (RIR) of anthropogenic VOCs (AVOC, overestimated by 68%-75%) and NOx (underestimated by 137%-527%) demonstrated deviations at multiple scenarios, and the RIR deviations for precursors in High-O3-periods (HOP) were lower than Low-O3-periods (LOP). The RIR deviations from individual species involved C-VOCs calculation did not impact the identification for the high-ranking-RIR AVOC species but non-negligible. Monthly comparisons showed that higher C-VOCs concentrations would lead to higher RIR deviations. The daily maximum of net Ox production rate (P(Ox)) and the regional transport Ox (Trans(Ox)) without C-VOCs were underestimated by 56%-194% and 81%-243%, respectively. After considering C-VOCs, the contribution of HO2+NO for Ox gross production (G(Ox)) decreased by 7% (LOP) and 7% (HOP), but OH + NO2 for Ox destruction (D(Ox)) decreased by 16% (LOP) and 23% (HOP), and alkenes + O3 increased for D(Ox) by 12% (LOP) and 22% (HOP). This implies that VOCs-NOx-O3 sensitivity was deviated between with/without C-VOCs, and severe O3 pollution rendered deviations in O3 formation, especially via NOx-driving chemistry. Based on RIR(NOx)/RIR(AVOC) with/without C-VOCs, the sensitivity regime shifted from VOCs-limited (-0.93) to transition (1.38) at LOP, and from VOCs-limited (0.19) to NOx-limited (3.79) at HOP. Our results reflected that the NOx limitation degree was underestimated without constraint C-VOCs, especially HOP, and provided implication to more precise O3 pollution control strategies.

Association between exposure to heavy metals in atmospheric particulate matter and sleep quality: A nationwide data linkage study.

BACKGROUND: Recent studies have demonstrated that long-term exposure to particulate matter (PM) is associated with poor sleep quality. However, no studies have linked PM constituents, particularly heavy metals, to sleep quality. OBJECTIVE: This study investigated the association between exposure to heavy metals in PM and sleep quality. METHODS: We obtained nationwide data from the Korean Community Health Survey conducted in 2018 among adults aged 19-80 years. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as PSQI ≥5. One-year and three-month average concentrations of heavy metals (lead, manganese, cadmium, and aluminum) in PM with diameter ≤10 µm were obtained from nationwide air quality monitoring data and linked to the survey data based on individual district-level residential addresses. Logistic regression analyses were performed after adjusting for age, gender, education level, marital status, smoking status, alcohol consumption, history of hypertension, and history of diabetes mellitus. RESULTS: Of 32,050 participants, 17,082 (53.3%) reported poor sleep quality. Increases in log-transformed one-year average lead (odds ratio, 1.14; 95% confidence interval, 1.08-1.20), manganese (1.31; 1.25-1.37), cadmium (1.03; 1.00-1.05), and aluminum concentrations (1.17; 1.10-1.25) were associated with poor sleep quality. Increases in log-transformed three-month average manganese (odds ratio, 1.13; 95% confidence interval, 1.09-1.17) and aluminum concentrations (1.28; 1.21-1.35) were associated with poor sleep quality. CONCLUSION: We showed for the first time that exposure to airborne lead, manganese, cadmium, and aluminum were associated with poor sleep quality. This study may be limited by self-reported sleep quality and district-level exposure data.

How informal environmental regulations constrain carbon dioxide emissions under pollution control and carbon reduction: Evidence from China.

Exploring whether informal environmental regulations (INER) can achieve carbon reduction in the context of pollution reduction and carbon reduction, as well as how to achieve carbon reduction, can help solve the dual failures of the market and government in environmental protection. Based on the polycentric governance theory and considering the characteristics of social subject environmental participation, the Stackelberg game is used to demonstrate the impact mechanism of INER on CO2. In addition, using the panel data of China's 30 provinces from 2003 to 2018, this paper validates the effectiveness of INER by Pooled Ordinary Least Square (POLS) and threshold panel model. Then, the mediating effect model is used to test the mechanism of INER's effect on carbon reduction. The results show that corruption is not conducive to CO2 reduction. The reduction effect of INER on CO2 exhibits heterogeneity with changes in other non-greenhouse gas pollutants. While INER effectively reduces local corruption, its more substantial indirect impact on CO2 reduction is prominent when levels of other pollutants are lower. Comparative analysis reveals that there are still biased governance behaviors to cope with INER's pressure in some regions nowadays. The findings show that for countries facing the dual task of pollution control and carbon reduction, the key to leveraging the supervisory role of INER should be focused on mitigating information asymmetry caused by the characteristics of CO2. Therefore, in the process of environmental protection, the public environmental participation system should be improved, and the process of disclosing polluters' carbon information should be accelerated.

Governance effects of pollution reduction and carbon mitigation of carbon emission trading policy in China.

China's carbon emission trading policy plays a crucial role in achieving both its "3060" dual carbon objectives and the United Nations Sustainable Development Goal 13 (SDG 13) on climate action. The policy's effectiveness in reducing pollution and mitigating carbon emissions holds significant importance. This paper investigated whether China's carbon emission trading policy affects pollution reduction (PM2.5 and SO2) and carbon mitigation (CO2) in pilot regions, using panel data from 30 provinces and municipalities in China from 2005 to 2019 and employing a multi-period difference-in-differences (DID) model. Furthermore, it analyzed the heterogeneity of carbon market mechanisms and regional variations. Finally, it examined the governance pathways for pollution reduction and carbon mitigation from a holistic perspective. The results indicate that: (1) China's carbon emission trading policy has reduced CO2 emissions by 18% and SO2 emissions by 36% in pilot areas, with an immediate impact on the "carbon mitigation" effect, while the "pollution reduction" effect exhibits a time lag. (2) Higher carbon trading prices lead to stronger "carbon mitigation" effect, and larger carbon market scales are associated with greater "pollution reduction" effects on PM2.5. Governance effects on pollution reduction and carbon mitigation vary among pilot regions: Carbon markets of Beijing, Chongqing, Shanghai, and Tianjin show significant governance effects in both "pollution reduction" and "carbon mitigation", whereas Guangdong's carbon market exhibits only a "pollution reduction" effect, and Hubei's carbon market demonstrates only a "carbon mitigation" effect. (3) Currently, China's carbon emission trading policy achieves pollution reduction and carbon mitigation through "process management" and "end-of-pipe treatment". This study could provide empirical insights and policy implications for pollution reduction and carbon mitigation, as well as for the development of China's carbon emission trading market.

When the smoke gets in your lungs: short-term effects of Indonesia's 2015 forest fires on health care use.

BACKGROUND: The forest fires that ravaged parts of Indonesia in 2015 were the most severely polluting of this century but little is known about their effects on health care utilization of the affected population. We estimate their short-term impact on visit rates to primary and hospital care with particular focus on visits for specific smoke-related conditions (respiratory disease, acute respiratory tract infection (ARTI) and common cold). METHOD: We estimate the short-term impact of the 2015 forest fire on visit rates to primary and hospital care by combining satellite data on Aerosol Optical Depth (AOD) with administrative records from Indonesian National Health Insurance Agency (BPJS Kesehatan) from January 2015-April  2016. The 16 months of panel data cover 203 districts in the islands of Sumatra and Kalimantan before, during and after the forest fires. We use the (more efficient) ANCOVA version adaptation of a fixed effects model to compare the trends in healthcare use of affected districts (with AOD value above 0.75) with control districts (AOD value below 0.75). Considering the higher vulnerability of children's lungs, we do this separately for children under 5 and the rest of the population adults (> 5), and for both urban and rural areas, and for both the period during and after the forest fires. RESULTS: We find little effects for adults. For young children we estimate positive effects for care related to respiratory problems in primary health care facilities in urban areas. Hospital care visits in general, on the other hand, are negatively affected in rural areas. We argue that these patterns arise because accessibility of care during fires is more restricted for rural than for urban areas. CONCLUSION: The severity of the fires and the absence of positive impact on health care utilization for adults and children in rural areas indicate large missed opportunities for receiving necessary care. This is particularly worrisome for children, whose lungs are most vulnerable to the effects. Our findings underscore the need to ensure ongoing access to medical services during forest fires and emphasize the necessity of catching up with essential care for children after the fires, particularly in rural areas.

Local- and regional-scale racial and ethnic disparities in air pollution determined by long-term mobile monitoring.

Disparity in air pollution exposure arises from variation at multiple spatial scales: along urban-to-rural gradients, between individual cities within a metropolitan region, within individual neighborhoods, and between city blocks. Here, we improve on existing capabilities to systematically compare urban variation at several scales, from hyperlocal (<100 m) to regional (>10 km), and to assess consequences for outdoor air pollution experienced by residents of different races and ethnicities, by creating a set of uniquely extensive and high-resolution observations of spatially variable pollutants: NO, NO2, black carbon (BC), and ultrafine particles (UFP). We conducted full-coverage monitoring of a wide sample of urban and suburban neighborhoods (93 km2 and 450,000 residents) in four counties of the San Francisco Bay Area using Google Street View cars equipped with the Aclima mobile platform. Comparing scales of variation across the sampled population, greater differences arise from localized pollution gradients for BC and NO (pollutants dominated by primary sources) and from regional gradients for UFP and NO2 (pollutants dominated by secondary contributions). Median concentrations of UFP, NO, and NO2 are, for Hispanic and Black populations, 8 to 30% higher than the population average; for White populations, average exposures to these pollutants are 9 to 14% lower than the population average. Systematic racial/ethnic disparities are influenced by regional concentration gradients due to sharp contrasts in demographic composition among cities and urban districts, while within-group extremes arise from local peaks. Our results illustrate how detailed and extensive fine-scale pollution observations can add new insights about differences and disparities in air pollution exposures at the population scale.

COVID-19 pandemic reveals persistent disparities in nitrogen dioxide pollution.

The unequal spatial distribution of ambient nitrogen dioxide ([Formula: see text]), an air pollutant related to traffic, leads to higher exposure for minority and low socioeconomic status communities. We exploit the unprecedented drop in urban activity during the COVID-19 pandemic and use high-resolution, remotely sensed [Formula: see text] observations to investigate disparities in [Formula: see text] levels across different demographic subgroups in the United States. We show that, prior to the pandemic, satellite-observed [Formula: see text] levels in the least White census tracts of the United States were nearly triple the [Formula: see text] levels in the most White tracts. During the pandemic, the largest lockdown-related [Formula: see text] reductions occurred in urban neighborhoods that have 2.0 times more non-White residents and 2.1 times more Hispanic residents than neighborhoods with the smallest reductions. [Formula: see text] reductions were likely driven by the greater density of highways and interstates in these racially and ethnically diverse areas. Although the largest reductions occurred in marginalized areas, the effect of lockdowns on racial, ethnic, and socioeconomic [Formula: see text] disparities was mixed and, for many cities, nonsignificant. For example, the least White tracts still experienced ∼1.5 times higher [Formula: see text] levels during the lockdowns than the most White tracts experienced prior to the pandemic. Future policies aimed at eliminating pollution disparities will need to look beyond reducing emissions from only passenger traffic and also consider other collocated sources of emissions such as heavy-duty vehicles.

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.