HTAP2 multi-model estimates of premature human mortality due to intercontinental transport of air pollution and emission sectors

Synergies of air pollution control policies: A review

Air pollution control necessitates the implementation of multiple policy instruments in a coordinated manner. However, the enforcement of different policy combinations may generate complementary or offsetting synergistic effects, thereby influencing policy effectiveness. Nevertheless, the direction of synergy and the mechanisms of action among heterogeneous policies is undefined in existing academic research. This study systematically reviewed 773 articles from 1998 to 2023 and, for the first time, integrated four primary domains of air pollution control policies: policy synergy and integration, collaborative governance for pollution and carbon mitigation, joint control of multiple pollutants, and cross-regional cooperative governance. This study revealed the directions and mechanisms of air policy synergy and provided empirical evidence for cross-regional comparisons in global environmental governance, with the ultimate goal of enhancing the effectiveness of air pollution control policies. Specifically, the mechanisms underlying policy synergy suggest that the cumulative impact of policies leads to the synergistic effects of multiple policies being superior to the effects of implementing a single policy. Furthermore, due to market price signals or the characteristics of specific technologies, the concurrent application of multiple policies may occasionally yield negative synergistic outcomes. Despite these advancements, gaps remain particularly in broadening the scope of policy integration, refining the assessment of synergistic effects, developing control strategies, and enhancing stakeholder engagement. Further research is necessary to address these gaps and enhance air policy effectiveness.

Daily high-resolution surface PM2.5 estimation over Europe by ML-based downscaling of the CAMS regional forecast

Fine particulate matter (PM2.5) is a key air quality indicator due to its adverse health impacts. Accurate PM2.5 assessment requires high-resolution (e.g., atleast 1 km) daily data, yet current methods face challenges in balancing accuracy, coverage, and resolution. Chemical transport models such as those from the Copernicus Atmosphere Monitoring Service (CAMS) offer continuous data but their relatively coarse resolution can introduce uncertainties. Here we present a synergistic Machine Learning (ML)-based approach called S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) for estimating daily surface PM2.5 over Europe at 1 km spatial resolution and demonstrate its performance for the years 2021 and 2022. The approach enhances and downscales the CAMS regional ensemble 24 h PM2.5 forecast by training a stacked XGBoost model against station observations, effectively integrating satellite-derived data and modeled meteorological variables. Overall, against station observations, S-MESH (mean absolute error (MAE) of 3.54 μg/m3) shows higher accuracy than the CAMS forecast (MAE of 4.18 μg/m3) and is approaching the accuracy of the CAMS regional interim reanalysis (MAE of 3.21 μg/m3), while exhibiting a significantly reduced mean bias (MB of -0.3 μg/m3 vs. -1.5 μg/m3 for the reanalysis). At the same time, S-MESH requires substantially less computational resources and processing time. At concentrations >20 μg/m3, S-MESH outperforms the reanalysis (MB of -7.3 μg/m3 and -10.3 μg/m3 respectively), and reliably captures high pollution events in both space and time. In the eastern study area, where the reanalysis often underestimates, S-MESH better captures high levels of PM2.5 mostly from residential heating. S-MESH effectively tracks day-to-day variability, with a temporal relative absolute error of 5% (reanalysis 10%). Exhibiting good performance at high pollution events coupled with its high spatial resolution and rapid estimation speed, S-MESH can be highly relevant for air quality assessments where both resolution and timeliness are critical.

Attribution of fine particulate matter and ozone health impacts in Canada to domestic and US emission sources

Exposure to ambient air pollution is associated with a wide range of adverse health effects such as respiratory symptoms, cardiovascular events, and premature mortality. Canada and the United States (US) have worked collaboratively for decades to address transboundary air pollution and its impacts across their shared border. To inform transboundary air quality considerations, we conducted modelling to attribute health impacts from ambient PM2.5 and O3 exposure in Canada to Canadian and US emission sources. We employed emissions, chemical transport, and health impacts modelling for 2015, 2025, and 2035 using a brute-force modelling approach whereby anthropogenic domestic and US emissions were reduced separately by 20 % or 100 %, and the resulting changes in health impacts were estimated across Canada. We find that transboundary PM2.5 and O3 related health impacts vary widely by region, with >80 % of impacts occurring in Central Canada, and most health impacts occurring within 200-300 km of the Canada-US border. The relative contribution of US sources to O3 in Canada is larger than for PM2.5, yet we find that the health impacts from transboundary PM2.5 exceeded those from transboundary O3. Nationally, we estimate that roughly one in five PM2.5 deaths in Canada is attributable to US sources (2000 deaths in 2015) and more than one in two O3 deaths are attributable to US sources (roughly 800 to 1200 deaths in 2015). We project health impacts from domestic and US sources to increase from 2025 to 2035 in Canada. Our results suggest that there are substantial benefits to be gained by domestic and international strategies to reduce PM2.5 in the Canada-US transboundary region.

Evolution of surface ozone pollution pattern in eastern China and its relationship with different intensity heatwaves

With climate warming, eastern China has experienced a significant increase in temperature accompanied by intensified ozone pollution. We aimed to investigate the spatiotemporal patterns and relationships between ozone levels and temperature in eastern China using observation-based ozone data from 418 air quality monitoring stations and temperature data from ERA5. The summer maximum temperature and annual ozone concentration in eastern China increased significantly between 2015 and 2022, with increases rate of 10% and 2.84 μg/m3 yr-1, respectively. The baseline ozone concentration was increasing over time. The average difference in MDA8 O3 concentration in spring, summer, and autumn decreased, with more ozone pollution spreading into spring and autumn, indicating a trend of prolonging the ozone season. During the June-July-August (JJA) period of 2015-2022, heatwaves increased significantly in eastern China. The frequency of heatwave events >10 days played a vital role in exacerbating ozone pollution. During the JJA period, the increase rate in MDA8 O3 concentration was 9.31 μg/m3 yr-1 during heatwave periods, significantly higher than that during non-heatwave periods (4.01 μg/m3 yr-1). The correlation between MDA8 O3 concentration and temperature was as high as 0.99, indicating that temperature was vital in ozone formation during the JJA period in eastern China. This study suggests that more stringent actions are needed to control ozone-precursor compounds during frequent summertime heatwaves in eastern China.

Predictability of fossil fuel CO2 from air quality emissions

Quantifying the coevolution of greenhouse gases and air quality pollutants can provide insight into underlying anthropogenic processes enabling predictions of their emission trajectories. Here, we classify the dynamics of historic emissions in terms of a modified Environmental Kuznets Curve (MEKC), which postulates the coevolution of fossil fuel CO₂ (FFCO₂) and NOx emissions as a function of macroeconomic development. The MEKC broadly captures the historic FFCO₂-NO_x dynamical regimes for countries including the US, China, and India as well as IPCC scenarios. Given these dynamics, we find the predictive skill of FFCO2 given NO_x emissions constrained by satellite data is less than 2% error at one-year lags for many countries and less than 10% for 4-year lags. The proposed framework in conjunction with an increasing satellite constellation provides valuable guidance to near-term emission scenario development and evaluation at time-scales relevant to international assessments such as the Global Stocktake.

Sources of PM2.5-Associated Health Risks in Europe and Corresponding Emission-Induced Changes During 2005-2015

We present a newly developed approach to characterize the sources of fine particulate matter (PM2.5)-related premature deaths in Europe using the chemical transport model GEOS-Chem and its adjoint. The contributions of emissions from each individual country, species, and sector are quantified and mapped out at km scale. In 2015, total PM2.5-related premature death is estimated to be 449,813 (257,846-722,138) in Europe, 59.0% of which were contributed by domestic anthropogenic emissions. The anthropogenic emissions of nitrogen oxides, ammonia, and organic carbon contributed most to the PM2.5-related health damages, making up 29.6%, 23.2%, and 16.8%, respectively of all domestic anthropogenic contributions. Residential, agricultural, and ground transport emissions are calculated to be the largest three sectoral sources of PM2.5-related health risks, accounting for 23.5%, 23.0%, and 19.4%, respectively, of total anthropogenic contributions within Europe. After excluding the influence of extra-regional sources, we find eastern European countries suffered from more premature deaths than their emissions caused; in contrast, the emissions from some central and western European regions contributed premature deaths exceeding three times the number of deaths that occurred locally. During 2005-2015, the first decade of PM2.5 regulation in Europe, emission controls reduced PM2.5-related health damages in nearly all European countries, resulting in 63,538 (46,092-91,082) fewer PM2.5-related premature deaths. However, our calculation suggests that efforts to reduce air pollution from key sectors in some countries can be offset by the lag in control of emissions in others. International cooperation is therefore vitally important for tackling air pollution and reducing corresponding detrimental effects on public health.

Nitrogen deposition from aviation emissions

Excess nitrogen deposition from anthropogenic sources of atmospheric emissions, such as agriculture and transportation, can have negative effects on natural environments. Designing effective conservation efforts requires knowledge of the contribution of individual sectors. This study utilizes a global atmospheric chemistry-transport model to quantify, for the first time, the contribution of global aviation NO_x emissions to nitrogen deposition for 2005 and 2019. We find that aviation led to an additional 1.39 Tg of nitrogen deposited globally in 2019, up 72 % from 2005, with 67 % of each year's total occurring through wet deposition. In 2019, aviation was responsible for an average of 0.66 %, 1.13 %, and 1.61 % of modeled nitrogen deposition from all sources over Asia, Europe, and North America, respectively. These impacts are spatially widespread, with 56 % of deposition occurring over water. Emissions during the landing, taxi and takeoff (LTO) phases of flight are responsible for 8 % of aviation's nitrogen deposition impacts on average globally, and between 16 and 32 % over most land in regions with high aviation activity. Despite currently representing less than 1.2 % of nitrogen deposition globally, further growth of aviation emissions would result in increases in aviation's contribution to nitrogen deposition and associated critical loads.

A Source Apportionment and Emission Scenario Assessment of PM2.5- and O3-Related Health Impacts in G20 Countries

Exposure to air pollution is a leading risk factor for premature death globally; however, the complexity of its formation and the diversity of its sources can make it difficult to address. The Group of Twenty (G20) countries are a collection of the world's largest and most influential economies and are uniquely poised to take action to reduce the global health burden associated with air pollution. We present a framework capable of simultaneously identifying regional and sectoral sources of the health impacts associated with two air pollutants, fine particulate matter (PM_2.5) and ozone (O₃) in G20 countries; this framework is also used to assess the health impacts associated with emission reductions. This approach combines GEOS-Chem adjoint sensitivities, satellite-derived data, and a new framework designed to better characterize the non-linear relationship between O₃ exposures and nitrogen oxides emissions. From this approach, we estimate that a 50% reduction of land transportation emissions by 2040 would result in 251 thousand premature deaths avoided in G20 countries. These premature deaths would be attributable equally to reductions in PM_2.5 and O₃ exposure which make up 51% and 49% of the potential benefits, respectively. In our second application, we estimate that the energy generation related co-benefits associated with G20 countries staying on pace with their net-zero carbon dioxide targets would be 290 thousand premature deaths avoided in 2040; action by India (47%) would result in the most benefits of any country and a majority of these avoided deaths would be attributable to reductions in PM_2.5 exposure (68%).

Analysis and forecasting of air quality index based on satellite data

OBJECTIVE

The air quality index (AQI) forecasts are one of the most important aspects of improving urban public health and enabling society to remain sustainable despite the effects of air pollution. Pollution control organizations deploy ground stations to collect information about air pollutants. Establishing a ground station all-around is not feasible due to the cost involved. As an alternative, satellite-captured data can be utilized for AQI assessment. This study explores the changes in AQI during various COVID-19 lockdowns in India utilizing satellite data. Furthermore, it addresses the effectiveness of state-of-the-art deep learning and statistical approaches for forecasting short-term AQI.

MATERIALS AND METHODS

Google Earth Engine (GEE) has been utilized to capture the data for the study. The satellite data has been authenticated against ground station data utilizing the beta distribution test before being incorporated into the study. The AQI forecasting has been explored using state-of-the-art statistical and deep learning approaches like VAR, Holt-Winter, and LSTM variants (stacked, bi-directional, and vanilla).

RESULTS

AQI ranged from 100 to 300, from moderately polluted to very poor during the study period. The maximum reduction was recorded during the complete lockdown period in the year 2020. Short-term AQI forecasting with Holt-Winter was more accurate than other models with the lowest MAPE scores.

CONCLUSIONS

Based on our findings, air pollution is clearly a threat in the studied locations, and it is important for all stakeholders to work together to reduce it. The level of air pollutants dropped substantially during the different lockdowns.

Present-day and future PM2.5 and O3-related global and regional premature mortality in the EVAv6.0 health impact assessment model

We used the EVAv6.0 system to estimate the present (2015) and future (2015-2050) global PM_2.5 and O₃-related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM_2.5-related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM_2.5-related premature deaths, contributing by 35% globally. Both long-term and short-term O₃-related premature deaths are estimated to be around 1 million, globally. Overall, PM_2.5 and O₃-related premature mortality leads to 5.3-5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM_2.5 relative risk as recommended by the WHO leads to an increase of PM_2.5-related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM_2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM_2.5-related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM_2.5 and O₃-related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems.

Mortality Attributable to Ambient Air Pollution: A Review of Global Estimates

Since the publication of the first epidemiological study to establish the connection between long-term exposure to atmospheric pollution and effects on human health, major efforts have been dedicated to estimate the attributable mortality burden, especially in the context of the Global Burden of Disease (GBD). In this work, we review the estimates of excess mortality attributable to outdoor air pollution at the global scale, by comparing studies available in the literature. We find large differences between the estimates, which are related to the exposure response functions as well as the number of health outcomes included in the calculations, aspects where further improvements are necessary. Furthermore, we show that despite the considerable advancements in our understanding of health impacts of air pollution and the consequent improvement in the accuracy of the global estimates, their precision has not increased in the last decades. We offer recommendations for future measurements and research directions, which will help to improve our understanding and quantification of air pollution-health relationships.

Inequality in historical transboundary anthropogenic PM2.5 health impacts

Atmospheric transport of fine particulate matter (PM_2.5), the leading environmental risk factor for public health, is estimated to exert substantial transboundary effects at present. During the past several decades, human-produced pollutant emissions have undergone drastic and regionally distinctive changes, yet it remains unclear about the resulting global transboundary health impacts. Here we show that between 1950 and 2014, global anthropogenic PM_2.5 has led to 185.7 million premature deaths cumulatively, including about 14% from transboundary pollution. Among four country groups at different affluence levels, on a basis of per capita contribution to transboundary mortality, a richer region tends to exert severer cumulative health externality, with the poorest bearing the worst net externality after contrasting import and export of pollution mortality. The temporal changes in transboundary mortality and cross-regional inequality are substantial. Effort to reduce PM_2.5-related transboundary mortality should seek international collaborative strategies that account for historical responsibility and inequality.

Contribution of fine particulate matter to present and future premature mortality over Europe: A non-linear response

The World Health Organization estimates that around 7 million people die every year from exposure to fine particles (PM2.5) inpolluted air. Here, the number of premature deaths in Europe from different diseases associated to the ambient exposure to PM2.5 have here been studied both for present (1991-2010) and future periods (2031-2050, RCP8.5 scenario). This contribution combines different state-of-the-art approaches (use of high-resolution climate/chemistry simulations over Europe for providing air quality data; use of different baseline mortality data for specific European regions; inclusion of future population projections and dynamical changes for 2050 obtained from the United Nations (UN) Population Projections or use of non-linear exposure-response functions) to estimate the premature mortality due to PM2.5. The mortality endpoints included in this study are Lung Cancer (LC), Chronic Obstructive Pulmonary Disease (COPD), Cerebrovascular Disease (CEV), Ischemic Heart Disease (IHD), Lower Respiratory Infection (LRI) and other Non-Communicable Diseases (other NCDs). Different risk ratio and baseline mortalities for each disease end each age range have been estimated individually. The results indicate that the annual excess mortality rate from fine particulate matter in Europe is 904,000 [95% confidence interval (95% CI) 733,100-1,067,800], increasing by 73% in 2050s (1,560,000; 95% CI 1,260,000-1,840,000); meanwhile population decreases from 808 to 806 million according to the UN estimations. The results show that IHD is the main cause of premature mortality in Europe associated to PM2.5 (around 48%) both for the present and future periods. Despite several marked regional differences, premature deaths associated to all the endpoints included in this study will increase in the future period due to the climate penalty but especially because of changes in the population projected and its aging.

Source sector and fuel contributions to ambient PM2.5 and attributable mortality across multiple spatial scales

Ambient fine particulate matter (PM_2.5) is the world's leading environmental health risk factor. Reducing the PM_2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM_2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74-1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM_2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52-0.95] million deaths; 19.2%), industrial (0.45 [0.32-0.58] million deaths; 11.7%), and energy (0.39 [0.28-0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

Air Quality Response in China Linked to the 2019 Novel Coronavirus (COVID-19) Lockdown

Efforts to stem the spread of COVID-19 in China hinged on severe restrictions to human movement starting 23 January 2020 in Wuhan and subsequently to other provinces. Here, we quantify the ancillary impacts on air pollution and human health using inverse emissions estimates based on multiple satellite observations. We find that Chinese NOx emissions were reduced by 36% from early January to mid-February, with more than 80% of reductions occurring after their respective lockdown in most provinces. The reduced precursor emissions increased surface ozone by up to 16 ppb over northern China but decreased PM2.5 by up to 23 μg m-3 nationwide. Changes in human exposure are associated with about 2,100 more ozone-related and at least 60,000 fewer PM2.5-related morbidity incidences, primarily from asthma cases, thereby augmenting efforts to reduce hospital admissions and alleviate negative impacts from potential delayed treatments.

Premature mortality related to United States cross-state air pollution

Outdoor air pollution adversely affects human health and is estimated to be responsible for five to ten per cent of the total annual premature mortality in the contiguous United States^1-3. Combustion emissions from a variety of sources, such as power generation or road traffic, make a large contribution to harmful air pollutants such as ozone and fine particulate matter (PM_2.5)⁴. Efforts to mitigate air pollution have focused mainly on the relationship between local emission sources and local air quality². Air quality can also be affected by distant emission sources, however, including emissions from neighbouring federal states^5,6. This cross-state exchange of pollution poses additional regulatory challenges. Here we quantify the exchange of air pollution among the contiguous United States, and assess its impact on premature mortality that is linked to increased human exposure to PM_2.5 and ozone from seven emission sectors for 2005 to 2018. On average, we find that 41 to 53 per cent of air-quality-related premature mortality resulting from a state's emissions occurs outside that state. We also find variations in the cross-state contributions of different emission sectors and chemical species to premature mortality, and changes in these variations over time. Emissions from electric power generation have the greatest cross-state impacts as a fraction of their total impacts, whereas commercial/residential emissions have the smallest. However, reductions in emissions from electric power generation since 2005 have meant that, by 2018, cross-state premature mortality associated with the commercial/residential sector was twice that associated with power generation. In terms of the chemical species emitted, nitrogen oxides and sulfur dioxide emissions caused the most cross-state premature deaths in 2005, but by 2018 primary PM_2.5 emissions led to cross-state premature deaths equal to three times those associated with sulfur dioxide emissions. These reported shifts in emission sectors and emission species that contribute to premature mortality may help to guide improvements to air quality in the contiguous United States.

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent.

Long-term trends in the ambient PM2.5- and O3-related mortality burdens in the United States under emission reductions from 1990 to 2010

Concentrations of both fine particulate matter (PM2.5) and ozone (O3) in the United States (US) have decreased significantly since 1990, mainly because of air quality regulations. Exposure to these air pollutants is associated with premature death. Here we quantify the annual mortality burdens from PM2.5 and O3 in the US from 1990 to 2010, estimate trends and inter-annual variability, and evaluate the contributions to those trends from changes in pollutant concentrations, population, and baseline mortality rates. We use a fine-resolution (36 km) self-consistent 21-year simulation of air pollutant concentrations in the US from 1990 to 2010, a health impact function, and annual county-level population and baseline mortality rate estimates. From 1990 to 2010, the modeled population-weighted annual PM2.5 decreased by 39 %, and summertime (April to September) 1 h average daily maximum O3 decreased by 9 % from 1990 to 2010. The PM2.5-related mortality burden from ischemic heart disease, chronic obstructive pulmonary disease, lung cancer, and stroke steadily decreased by 54% from 123 700 deaths year-1 (95% confidence interval, 70 800-178 100) in 1990 to 58 600 deaths year-1 (24 900-98 500) in 2010. The PM2.5-related mortality burden would have decreased by only 24% from 1990 to 2010 if the PM2.5 concentrations had stayed at the 1990 level, due to decreases in baseline mortality rates for major diseases affected by PM2.5. The mortality burden associated with O3 from chronic respiratory disease increased by 13% from 10 900 deaths year-1 (3700-17 500) in 1990 to 12 300 deaths year-1 (4100-19 800) in 2010, mainly caused by increases in the baseline mortality rates and population, despite decreases in O3 concentration. The O3-related mortality burden would have increased by 55% from 1990 to 2010 if the O3 concentrations had stayed at the 1990 level. The detrended annual O3 mortality burden has larger inter-annual variability (coefficient of variation of 12%) than the PM2.5-related burden (4%), mainly from the inter-annual variation of O3 concentration. We conclude that air quality improvements have significantly decreased the mortality burden, avoiding roughly 35 800 (38%) PM2.5-related deaths and 4600 (27%) O3-related deaths in 2010, compared to the case if air quality had stayed at 1990 levels (at 2010 baseline mortality rates and population).