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More than a decade of satellite observations offers global information about the trend and magnitude of human exposure to fine particulate matter (PM2.5). In this study, we developed improved global exposure estimates of ambient PM2.5 mass and trend using PM2.5 concentrations inferred from multiple satellite instruments. We combined three satellite-derived PM2.5 sources to produce global PM2.5 estimates at about 10 km × 10 km from 1998 through 2012. For each source, we related total column retrievals of aerosol optical depth to near-ground PM2.5 using the GEOS-Chem chemical transport model to represent local aerosol optical properties and vertical profiles. We collected 210 global ground-based PM2.5 observations from the literature to evaluate our satellite-based estimates with values measured in areas other than North America and Europe. We estimated that global population-weighted ambient PM2.5 concentrations increased 0.55 μg/m3/year (95% CI: 0.43, 0.67) (2.1%/year; 95% CI: 1.6, 2.6) from 1998 through 2012. Increasing PM2.5 in some developing regions drove this global change, despite decreasing PM2.5 in some developed regions. The estimated proportion of the population of East Asia living above the World Health Organization (WHO) Interim Target-1 of 35 μg/m3 increased from 51% in 1998-2000 to 70% in 2010-2012. In contrast, the North American proportion above the WHO Air Quality Guideline of 10 μg/m3 fell from 62% in 1998-2000 to 19% in 2010-2012. We found significant agreement between satellite-derived estimates and ground-based measurements outside North America and Europe (r = 0.81; n = 210; slope = 0.68). The low bias in satellite-derived estimates suggests that true global concentrations could be even greater. Satellite observations provide insight into global long-term changes in ambient PM2.5 concentrations. Satellite-derived estimates and ground-based PM2.5 observations from this study are available for public use.

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health(1–9) . A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-19(10–20). Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

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. Ambient fine particulate matter (PM 2.5 ) is one of the most important environmental health risk factors in many regions. Here, the authors present an assessment of PM 2.5 emission sources and the related health impacts across global to sub-national scales and find that over 1 million deaths were avoidable in 2017 by eliminating PM 2.5 mass associated with fossil fuel combustion emissions.

Emerging evidence suggests that living near major roads might adversely affect cognition. However, little is known about its relationship with the incidence of dementia, Parkinson's disease, and multiple sclerosis. We aimed to investigate the association between residential proximity to major roadways and the incidence of these three neurological diseases in Ontario, Canada. In this population-based cohort study, we assembled two population-based cohorts including all adults aged 20–50 years (about 4·4 million; multiple sclerosis cohort) and all adults aged 55–85 years (about 2·2 million; dementia or Parkinson's disease cohort) who resided in Ontario, Canada on April 1, 2001. Eligible patients were free of these neurological diseases, Ontario residents for 5 years or longer, and Canadian-born. We ascertained the individual's proximity to major roadways based on their residential postal-code address in 1996, 5 years before cohort inception. Incident diagnoses of dementia, Parkinson's disease, and multiple sclerosis were ascertained from provincial health administrative databases with validated algorithms. We assessed the associations between traffic proximity and incident dementia, Parkinson's disease, and multiple sclerosis using Cox proportional hazards models, adjusting for individual and contextual factors such as diabetes, brain injury, and neighbourhood income. We did various sensitivity analyses, such as adjusting for access to neurologists and exposure to selected air pollutants, and restricting to never movers and urban dwellers. Between 2001, and 2012, we identified 243 611 incident cases of dementia, 31 577 cases of Parkinson's disease, and 9247 cases of multiple sclerosis. The adjusted hazard ratio (HR) of incident dementia was 1·07 for people living less than 50 m from a major traffic road (95% CI 1·06–1·08), 1·04 (1·02–1·05) for 50–100 m, 1·02 (1·01–1·03) for 101–200 m, and 1·00 (0·99–1·01) for 201–300 m versus further than 300 m (p for trend=0·0349). The associations were robust to sensitivity analyses and seemed stronger among urban residents, especially those who lived in major cities (HR 1·12, 95% CI 1·10–1·14 for people living <50 m from a major traffic road), and who never moved (1·12, 1·10–1·14 for people living <50 m from a major traffic road). No association was found with Parkinson's disease or multiple sclerosis. In this large population-based cohort, living close to heavy traffic was associated with a higher incidence of dementia, but not with Parkinson's disease or multiple sclerosis. Health Canada (MOA-4500314182).

Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM 2.5 exposure. Here we interpret satellite-derived PM 2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM 2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM 2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 μg/m 3 ) to a peak in 2011 (38.9 μg/m 3 ) and decreased steadily afterwards (34.7 μg/m 3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM 2.5 -attributable mortality and increasing health benefits per µg/m 3 marginal reduction in exposure, implying increasing urgency and benefits of PM 2.5 mitigation with aging population and cleaner air. Global fine particulate matter air pollution recently pivots from increase to decrease as inferred from satellite observations, driven by unprecedented exposure reduction in China and slowed exposure growth in South Asia, the Middle East and Africa.

The transboundary health impacts of air pollution associated with the international trade of goods and services are greater than those associated with long-distance atmospheric pollutant transport. The international air pollution trade Air quality and mortality are affected by local air pollution, but not all local air pollution comes from local emissions. It is also fed by atmospheric transport of pollutants from distant sources, and some of the pollution in one region is due to the production of goods for consumption in another. This study investigates the effect of these two remote pollution sources on premature mortality linked to fine particulate matter pollution. Qiang Zhang et al . find that, in 2007, about 12 per cent of premature deaths related to fine particulate matter were attributed to air pollutants from distant sources and about 22 per cent were associated with goods and services produced in one region for consumption in another. The findings suggest that the health impacts of pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport. Millions of people die every year from diseases caused by exposure to outdoor air pollution 1 , 2 , 3 , 4 , 5 . Some studies have estimated premature mortality related to local sources of air pollution 6 , 7 , but local air quality can also be affected by atmospheric transport of pollution from distant sources 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 . International trade is contributing to the globalization of emission and pollution as a result of the production of goods (and their associated emissions) in one region for consumption in another region 14 , 19 , 20 , 21 , 22 . The effects of international trade on air pollutant emissions 23 , air quality 14 and health 24 have been investigated regionally, but a combined, global assessment of the health impacts related to international trade and the transport of atmospheric air pollution is lacking. Here we combine four global models to estimate premature mortality caused by fine particulate matter (PM 2.5 ) pollution as a result of atmospheric transport and the production and consumption of goods and services in different world regions. We find that, of the 3.45 million premature deaths related to PM 2.5 pollution in 2007 worldwide, about 12 per cent (411,100 deaths) were related to air pollutants emitted in a region of the world other than that in which the death occurred, and about 22 per cent (762,400 deaths) were associated with goods and services produced in one region for consumption in another. For example, PM 2.5 pollution produced in China in 2007 is linked to more than 64,800 premature deaths in regions other than China, including more than 3,100 premature deaths in western Europe and the USA; on the other hand, consumption in western Europe and the USA is linked to more than 108,600 premature deaths in China. Our results reveal that the transboundary health impacts of PM 2.5 pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport.

Growing evidence suggests that fine particulate matter (PM2.5) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO₃⁻), sulfate (SO₄2−), ammonium (NH₄⁺), and soil dust (DUST). To investigate the impact of long-term exposure to PM2.5 constituents on incident all-cause dementia and Alzheimer’s disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration–response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM2.5 and its major constituents. An interquartile range increase in PM2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM2.5 constituents, associations remained significant for BC, OM, SO₄2−, and NH₄⁺ for both end points (even after adjustments of other constituents), among which BC and SO₄2− showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM2.5 is significantly associated with higher rates of incident dementia and AD and that SO₄2−, BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

In a globalized economy, production of goods can be disrupted by trade disputes. Yet the resulting impacts on carbon dioxide emissions and ambient particulate matter (PM 2.5 ) related premature mortality are unclear. Here we show that in contrast to a free trade world, with the emission intensity in each sector unchanged, an extremely anti-trade scenario with current tariffs plus an additional 25% tariff on each traded product would reduce the global export volume by 32.5%, gross domestic product by 9.0%, carbon dioxide by 6.3%, and PM 2.5 -related mortality by 4.1%. The respective impacts would be substantial for the United States, Western Europe and China. A freer trade scenario would increase global carbon dioxide emission and air pollution due to higher levels of production, especially in developing regions with relatively high emission intensities. Global collaborative actions to reduce emission intensities in developing regions could help achieve an economic-environmental win-win state through globalization. Carbon dioxide emissions and air pollution are often assessed on a national or regional level, but little is known about the role of trade structures. Here, a combination of models shows that trade restrictions can lead to massive reduction of gross domestic product in most countries, but also to a reduction of emissions and pollution.

BACKGROUND: Epidemiologie and health impact studies of fine particulate matter with diameter < 2.5 um (PM₂.₄) are limited by the lack of monitoring data, especially in developing countries. Satellite observations offer valuable global information about PM₂.₄ concentrations. OBJECTIVE: In this study, we developed a technique for estimating surface PM₂.₄ concentrations from satellite observations. METHODS: We mapped global ground-level PM₂.₄ concentrations using total column aerosol optical depth (AOD) from the MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multiangle Imaging Spectroradiometer) satellite instruments and coincident aerosol vertical profiles from the GEOS-Chem global chemical transport model. RESULTS: We determined that global estimates of long-term average (1 January 2001 to 31 December 2006) PM₂.₄ concentrations at approximately 10 km x 10 km resolution indicate a global population-weighted geometric mean PM2.5 concentration of 20 ug/m³. The World Health Organization Air Quality PM₂.₄ Interim Target-1 (35 Hg/m 3 annual average) is exceeded over central and eastern Asia for 38% and for 50% of the population, respectively. Annual mean PM₂.₄ concentrations exceed 80 ug/m 3 over eastern China. Our evaluation of the satellite-derived estimate with ground-based in situ measurements indicates significant spatial agreement with North American measurements (r = 0.77; slope = 1.07; n= 1057) and with noncoincident measurements elsewhere (r = 0.83; slope = 0.86; n = 244). The 1 SO of uncertainty in the satellite-derived PM₂.₄ is 25%, which is inferred from the AOD retrieval and from aerosol vertical profile errors and sampling.The global population-weighted mean uncertainty is 6.7 ug/m³. CONCLUSIONS: Satellite-derived total-column AOD, when combined with a chemical transport model,provides estimates of global long-term average PM₂.₄ concentrations.

Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5∘ × 0.5∘) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).