Showing papers by "Susan C. Anenberg published in 2020"
TL;DR: It is found that meteorological patterns were especially favorable for low NO2 in much of the U.S. in spring 2020, complicating comparisons with spring 2019.
Abstract: TROPOMI satellite data show substantial drops in nitrogen dioxide (NO2) during COVID-19 physical distancing. To attribute NO2 changes to NOX emissions changes over short timescales, one must account for meteorology. We find that meteorological patterns were especially favorable for low NO2 in much of the U.S. in spring 2020, complicating comparisons with spring 2019. Meteorological variations between years can cause column NO2 differences of ~15% over monthly timescales. After accounting for sun angle and meteorological considerations, we calculate that NO2 drops ranged between 9.2 - 43.4% among twenty cities in North America, with a median of 21.6%. Of the studied cities, largest NO2 drops (>30%) were in San Jose, Los Angeles, and Toronto, and smallest drops (<12%) were in Miami, Minneapolis, and Dallas. These normalized NO2 changes can be used to highlight locations with greater activity changes and better understand the sources contributing to adverse air quality in each city.
148 citations
TL;DR: If synergistic effects between heat and air pollution are confirmed with additional research, the health impacts from climate change-driven increases in air pollution and heat exposure may be larger than previously estimated in studies that consider these risk factors individually.
Abstract: Exposure to heat, air pollution, and pollen are associated with health outcomes, including cardiovascular and respiratory disease. Studies assessing the health impacts of climate change have considered increased exposure to these risk factors separately, though they may be increasing simultaneously for some populations and may act synergistically on health. Our objective is to systematically review epidemiological evidence for interactive effects of multiple exposures to heat, air pollution, and pollen on human health. We systematically searched electronic literature databases (last search, April 29, 2019) for studies reporting quantitative measurements of associations between at least two of the exposures and mortality from any cause and cardiovascular and respiratory morbidity and mortality specifically. Following the Navigation Guide systematic review methodology, we evaluated the risk of bias of individual studies and the overall quality and strength of evidence. We found 56 studies that met the inclusion criteria. Of these, six measured air pollution, heat, and pollen; 39 measured air pollution and heat; 10 measured air pollution and pollen; and one measured heat and pollen. Nearly all studies were at risk of bias from exposure assessment error. However, consistent exposure-response across studies led us to conclude that there is overall moderate quality and sufficient evidence for synergistic effects of heat and air pollution. We concluded that there is overall low quality and limited evidence for synergistic effects from simultaneous exposure to (1) air pollution, pollen, and heat; and (2) air pollution and pollen. With only one study, we were unable to assess the evidence for synergistic effects of heat and pollen. If synergistic effects between heat and air pollution are confirmed with additional research, the health impacts from climate change-driven increases in air pollution and heat exposure may be larger than previously estimated in studies that consider these risk factors individually.
74 citations
TL;DR: A modelling framework implemented in the Low Emissions Analysis Platform - Integrated Benefits Calculator (LEAP-IBC) tool is applied in Bangladesh to evaluate the air quality and climate change benefits from implementation of Bangladesh's Nationally Determined Contribution (NDC) and National Action Plan to reduce SLCPs.
31 citations
University of Washington1, Emory University2, Wellcome Trust3, George Washington University4, University of London5, Yale University6, Rockefeller Foundation7, Ritsumeikan University8, World Health Organization9, Colorado School of Public Health10, University of Basel11, Swiss Tropical and Public Health Institute12, University of Oxford13, Peking University14, Tsinghua University15, George Mason University16, University of Otago17, University College London18, National Institute for Environmental Studies19, Nagasaki University20, University of Tsukuba21, Northwestern University22, Lamont–Doherty Earth Observatory23, Seoul National University24, Boston University25, Université Félix Houphouët-Boigny26, Natural Resources Defense Council27, Max Planck Society28, University of Surrey29, Columbia University30, Princeton University31, Pompeu Fabra University32, International Institute for Applied Systems Analysis33, University of California, Berkeley34, University of Waterloo35, Harvard University36, Duke University37, The Nature Conservancy38, University of Exeter39, Netherlands Environmental Assessment Agency40, University of North Carolina at Chapel Hill41, University of Cambridge42, University of Auckland43, Beihang University44, University of Sydney45
TL;DR: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers to inform evidence-based decision making and practice.
Abstract: BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.
30 citations
25 Mar 2020
TL;DR: The explosion of low‐cost air monitors has allowed researchers to build dense air quality sensing networks to capture ephemeral and local releases of harmful materials, building on other developments in personal exposure sensing.
Abstract: Pollution from multiple sources causes significant disease and death worldwide. Some sources are legacy, such as heavy metals accumulated in soils, and some are current, such as particulate matter. Because the global burden of disease from pollution is so high, it is important to identify legacy and current sources and to develop and implement effective techniques to reduce human exposure. But many limitations exist in our understanding of the distribution and transport processes of pollutants themselves, as well as the complicated overprint of human behavior and susceptibility. New approaches are being developed to identify and eliminate pollution in multiple environments. Community-scale detection of geogenic arsenic and fluoride in Bangladesh is helping to map the distribution of these harmful elements in drinking water. Biosensors such as bees and their honey are being used to measure heavy metal contamination in cities such as Vancouver and Sydney. Drone-based remote sensors are being used to map metal hot spots in soils from former mining regions in Zambia and Mozambique. The explosion of low-cost air monitors has allowed researchers to build dense air quality sensing networks to capture ephemeral and local releases of harmful materials, building on other developments in personal exposure sensing. And citizen science is helping communities without adequate resources measure their own environments and in this way gain agency in controlling local pollution exposure sources and/or alerting authorities to environmental hazards. The future of GeoHealth will depend on building on these developments and others to protect a growing population from multiple pollution exposure risks.
24 citations
George Washington University1, University of Wisconsin-Madison2, University of British Columbia3, Institute for Health Metrics and Evaluation4, Pan American Health Organization5, Goddard Space Flight Center6, Lamont–Doherty Earth Observatory7, Pure Earth8, University of Colorado Boulder9, University of Washington10, Harvard University11, Boston University12, Emory University13, Environmental Defense Fund14, George Mason University15, Health Effects Institute16, University College London17, University of North Carolina at Chapel Hill18
TL;DR: Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality.
Abstract: The 2018 NASA Health and Air Quality Applied Science Team (HAQAST) "Indicators" Tiger Team collaboration between NASA-supported scientists and civil society stakeholders aimed to develop satellite-derived global air pollution and climate indicators. This Commentary shares our experience and lessons learned. Together, the team developed methods to track wildfires, dust storms, pollen counts, urban green space, nitrogen dioxide concentrations and asthma burdens, tropospheric ozone concentrations, and urban particulate matter mortality. Participatory knowledge production can lead to more actionable information but requires time, flexibility, and continuous engagement. Ground measurements are still needed for ground truthing, and sustained collaboration over time remains a challenge.
20 citations
17 Jun 2020
TL;DR: In this article, the authors investigated the capabilities of the Tropospheric Monito to observe the spatial heterogeneities of NO2 air pollution, which is an important first step in quantifying NOx emissions and exposures.
Abstract: Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOx emissions and exposures. This study investigates the capabilities of the Tropospheric Monito...
14 citations
TL;DR: In this paper, the effect of spatial resolution of exposure and population data on estimated NO2 attributable pediatric asthma incidence was investigated, and the authors concluded that 1km spatial resolution balances accuracy and computational efficiency in estimating NO2-attributable asthma burdens at national and urban levels.
Abstract: Nitrogen dioxide (NO2) is a major urban air pollutant and is associated with new onset asthma among children worldwide. Since NO2 concentrations are spatially heterogeneous and correlated with population, the spatial resolution of concentration estimates and disease burden calculations could strongly influence the magnitude and spatial distribution of estimated NO2-attributable pediatric asthma cases. Here, we investigate the effect of spatial resolution of exposure and population data on estimated NO2 attributable pediatric asthma incidence. We use epidemiologically-derived health impact functions to estimate NO2-attribtuable asthma incidence for the U.S. and India, two countries with different degrees of urbanicity. As inputs to the health impact function, we use population and NO2 concentration estimates at 100m resolution and aggregated to coarser spatial resolutions: 500m, 1km, 10km, and 100km. Estimated NO2-attributable pediatric asthma burdens differ by <1% for resolutions of 100m up to 1km for both countries. However, performing the analysis at 10km and 100km results in 5% and 17% fewer new asthma cases among children in India and 6% and 32% fewer in the U.S., respectively. We perform a similar analysis for the 500 most populated cities at 1km and 10km resolution, finding that the coarser resolution leads to lower estimated NO2-attributable asthma incidence in nearly all cities, especially for cities with smaller land areas. We conclude that 1km spatial resolution balances accuracy and computational efficiency in estimating NO2-attributable asthma burdens at national and urban levels, and that coarser resolutions may result in underestimates.
12 citations