An Analysis of Costs and Health Co-Benefits for a U.S. Power Plant Carbon Standard

Reducing carbon dioxide (CO2) emissions from power plants can have important “co-benefits” for public health by reducing emissions of air pollutants. Here, we examine the costs and health co-benefits, in monetary terms, for a policy that resembles the U.S. Environmental Protection Agency’s Clean Power Plan. We then examine the spatial distribution of the co-benefits and costs, and the implications of a range of cost assumptions in the implementation year of 2020. Nationwide, the total health co-benefits were $29 billion 2010 USD (95$2.3 to $68 billion), and net co-benefits under our central cost case were$12 billion (95% CI: -$15 billion to$51 billion). Net co-benefits for this case in the implementation year were positive in 10 of the 14 regions studied. The results for our central case suggest that all but one region should experience positive net benefits within 5 years after implementation

Ancillary health effects of climate mitigation scenarios as drivers of policy uptake: a review of air quality, transportation and diet co-benefits modeling studies

Background: Significant mitigation efforts beyond the Nationally Determined Commitments (NDCs) coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2 °C above pre-industrial temperatures. Health co-benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term before the beneficial impacts of those policies on the magnitude of climate change are evident. The diversity of approaches to modeling mitigation options and their health effects inhibits meta-analyses and syntheses of results useful in policy-making. Methods/Design: We evaluated the range of methods and choices in modeling health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration that could better inform policy-making. We reviewed studies quantifying the health co-benefits of climate change mitigation related to air quality, transportation, and diet published since the 2009 Lancet Commission 'Managing the health effects of climate change' through January 2017. We documented approaches, methods, scenarios, health-related exposures, and health outcomes. Results/Synthesis: Forty-two studies met the inclusion criteria. Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determined policy relevance. More recent studies tended to use more sophisticated methods to address complexity in the relevant policy system. Discussion: Most studies indicated significant, nearer term, local ancillary health benefits providing impetus for policy uptake and net cost savings. However, studies were more suited to describing the interaction of climate policy and health and the magnitude of potential outcomes than to providing specific accurate estimates of health co-benefits. Modeling the health co-benefits of climate policy provides policy-relevant information when the scenarios are reasonable, relevant, and thorough, and the model adequately addresses complexity. Greater consistency in selected modeling choices across the health co-benefits of climate mitigation research would facilitate evaluation of mitigation options particularly as they apply to the NDCs and promote policy uptake

Population allocation at the housing unit level: estimates around underground natural gas storage wells in PA, OH, NY, WV, MI, and CA

Background Spatially accurate population data are critical for determining health impacts from many known risk factors. However, the utility of the increasing spatial resolution of disease mapping and environmental exposures is limited by the lack of receptor population data at similar sub-census block spatial scales. Methods Here we apply an innovative method (Population Allocation by Occupied Domicile Estimation – ABODE) to disaggregate U.S. Census populations by allocating an average person per household to geospatially-identified residential housing units (RHU). We considered two possible sources of RHU location data: address point locations and building footprint centroids. We compared the performance of ABODE with the common proportional population allocation (PPA) method for estimating the nighttime residential populations within 200 m radii and setback areas (100 – 300 ft) around active underground natural gas storage (UGS) wells (n = 9834) in six U.S. states. Results Address location data generally outperformed building footprint data in predicting total counts of census residential housing units, with correlations ranging from 0.67 to 0.81 at the census block level. Using residentially-sited addresses only, ABODE estimated upwards of 20,000 physical households with between 48,126 and 53,250 people living within 200 m of active UGS wells – likely encompassing the size of a proposed UGS Wellhead Safety Zone. Across the 9834 active wells assessed, ABODE estimated between 5074 and 10,198 more people living in these areas compare to PPA, and the difference was significant at the individual well level (p = < 0.0001). By either population estimation method, OH exhibits a substantial degree of hyperlocal land use conflict between populations and UGS wells – more so than other states assessed. In some rare cases, population estimates differed by more than 100 people for the small 200 m2 well-areas. ABODE’s explicit accounting of physical households confirmed over 50% of PPA predictions as false positives indicated by non-zero predictions in areas absent physical RHUs. Conclusions Compared to PPA – in allocating identical population data at sub-census block spatial scales –ABODE provides a more precise population at risk (PAR) estimate with higher confidence estimates of populations at greatest risk. 65% of UGS wells occupy residential urban and suburban areas indicating the unique land use conflicts presented by UGS systems that likely continue to experience population encroachment. Overall, ABODE confirms tens of thousands of homes and residents are likely located within the proposed UGS Wellhead Safety Zone – and in some cases within state’s oil and gas well surface setback distances – of active UGS wells

Air pollution and health impacts of oil & gas production in the United States

Oil and gas production is one of the largest emitters of methane, a potent greenhouse gas and a significant contributor of air pollution emissions. While research on methane emissions from oil and gas production has grown rapidly, there is comparatively limited information on the distribution of impacts of this sector on air quality and associated health impacts. Understanding the contribution of air quality and health impacts of oil and gas can be useful for designing mitigation strategies. Here we assess air quality and human health impacts associated with ozone, fine particulate matter, and nitrogen dioxide from the oil and gas sector in the US in 2016, and compare this impact with that of the associated methane emissions. We find that air pollution in 2016 from the oil and gas sector in the US resulted in 410 000 asthma exacerbations, 2200 new cases of childhood asthma and 7500 excess deaths, with $77 billion in total health impacts. NO2 was the highest contributor to health impacts (37%) followed by ozone (35%), and then PM2.5 (28%). When monetized, these air quality health impacts of oil and gas production exceeded estimated climate impact costs from methane leakage by a factor of 3. These impacts add to the total life cycle impacts of oil and gas, and represent potential additional health benefits of strategies that reduce consumption of oil and gas. Policies to reduce oil and gas production emissions will lead to additional and significant health benefits from co-pollutant reductions that are not currently quantified or monetized

Public health impacts of the severe haze in Equatorial Asia in September-October 2015: demonstration of a new framework for informing fire management strategies to reduce downwind smoke exposure

In September–October 2015, El Niño and positive Indian Ocean Dipole conditions set the stage for massive fires in Sumatra and Kalimantan (Indonesian Borneo), leading to persistently hazardous levels of smoke pollution across much of Equatorial Asia. Here we quantify the emission sources and health impacts of this haze episode and compare the sources and impacts to an event of similar magnitude occurring under similar meteorological conditions in September–October 2006. Using the adjoint of the GEOS-Chem chemical transport model, we first calculate the influence of potential fire emissions across the domain on smoke concentrations in three receptor areas downwind—Indonesia, Malaysia, and Singapore—during the 2006 event. This step maps the sensitivity of each receptor to fire emissions in each grid cell upwind. We then combine these sensitivities with 2006 and 2015 fire emission inventories from the Global Fire Assimilation System (GFAS) to estimate the resulting population-weighted smoke exposure. This method, which assumes similar smoke transport pathways in 2006 and 2015, allows near real-time assessment of smoke pollution exposure, and therefore the consequent morbidity and premature mortality, due to severe haze. Our approach also provides rapid assessment of the relative contribution of fire emissions generated in a specific province to smoke-related health impacts in the receptor areas. We estimate that haze in 2015 resulted in 100 300 excess deaths across Indonesia, Malaysia and Singapore, more than double those of the 2006 event, with much of the increase due to fires in Indonesia's South Sumatra Province. The model framework we introduce in this study can rapidly identify those areas where land use management to reduce and/or avoid fires would yield the greatest benefit to human health, both nationally and regionally

Evaluation of the public health impacts of traffic congestion: a health risk assessment

Background: Traffic congestion is a significant issue in urban areas in the United States and around the world. Previous analyses have estimated the economic costs of congestion, related to fuel and time wasted, but few have quantified the public health impacts or determined how these impacts compare in magnitude to the economic costs. Moreover, the relative magnitudes of economic and public health impacts of congestion would be expected to vary significantly across urban areas, as a function of road infrastructure, population density, and atmospheric conditions influencing pollutant formation, but this variability has not been explored. Methods: In this study, we evaluate the public health impacts of ambient exposures to fine particulate matter (PM2.5) concentrations associated with a business-as-usual scenario of predicted traffic congestion. We evaluate 83 individual urban areas using traffic demand models to estimate the degree of congestion in each area from 2000 to 2030. We link traffic volume and speed data with the MOBILE6 model to characterize emissions of PM2.5 and particle precursors attributable to congestion, and we use a source-receptor matrix to evaluate the impact of these emissions on ambient PM2.5 concentrations. Marginal concentration changes are related to a concentration-response function for mortality, with a value of statistical life approach used to monetize the impacts. Results: We estimate that the monetized value of PM2.5-related mortality attributable to congestion in these 83 cities in 2000 was approximately $31 billion (2007 dollars), as compared with a value of time and fuel wasted of$60 billion. In future years, the economic impacts grow (to over $100 billion in 2030) while the public health impacts decrease to$13 billion in 2020 before increasing to $17 billion in 2030, given increasing population and congestion but lower emissions per vehicle. Across cities and years, the public health impacts range from more than an order of magnitude less to in excess of the economic impacts. Conclusions: Our analyses indicate that the public health impacts of congestion may be significant enough in magnitude, at least in some urban areas, to be considered in future evaluations of the benefits of policies to mitigate congestion

Air Quality and Health-Related Impacts of Traditional and Alternate Jet Fuels From Airport Aircraft Operations in the U.S.

13-C-AJFF-UNC-010, 012This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license https://creativecommons.org/licenses/by-nc-nd/4.0/. Please cite this article as: Calvin A. Arter, Jonathan J. Buonocore, Chowdhury Moniruzzaman, Dongmei Yang, Jiaoyan Huang, Saravanan Arunachalam, Air quality and health-related impacts of traditional and alternate jet fuels from airport aircraft operations in the U.S., Environment International, Volume 158, 2022, 106958, ISSN 0160-4120, https://doi.org/10.1016/j.envint.2021.106958.Aviation emissions from landing and takeoff operations (LTO) can degrade local and regional air quality leading to adverse health outcomes in populations near airports and downwind. In this study we aim to quantify the air quality and health-related impacts from commercial LTO emissions in the continental U.S. for two recent years\u2019 inventories, 2011 and 2016. We quantify the LTO-attributable PM2.5, O3, and NO2 concentrations and health outcomes for mortality and multiple morbidity health endpoints. We also quantify the impacts from two scenarios representing a nation-wide implementation of 5% or 50% blends of sustainable alternative jet fuels. We estimate 80 (68\u201393) and 88 (75\u2013100) PM2.5-attributable and 610 (310\u2013920) and 1,100 (570\u20131,700) NO2- attributable premature mortalities in 2011 and 2016, respectively. We estimate a net decrease of 28 (14\u201356) and 54 (27\u2013110) in O3-attributable premature mortalities across the U.S. in 2011 and 2016, respectively due to the large O3 titration effects near the airports. We also find that the asthma exacerbations due to NO2 exposures from LTO emissions increase from 100,000 (2,500\u2013200,000) in 2011 to 170,000 (4,400\u2013340,000) in 2016. Implementing a 5% or 50% blend of sustainable alternative jet fuel in 2016 results in a 1% or 18% reduction, respectively in PM2.5-attributable premature mortalities. Monetizing the value of avoided total premature mortalities, we find that a 50%-blended sustainable alternative jet fuel results in a 19% decrease in PM2.5 damages per ton of fuel burned and a 2% decrease in total damages per ton of fuel burned as compared to damages from traditional jet fuel. We also quantify health impacts by state and find California to be the most impacted by LTO emissions. We find that LTO-attributable PM2.5 and NO2 premature mortalities increase by 10% and 80%, respectively from 2011 to 2016 and that NO2-attributable premature mortalities are responsible for 91% of total LTO-attributable premature mortalities in both 2011 and 2016. And since we find LTO-attributable NO2 to be unaffected by the implementation of sustainable alternative jet fuels, additional approaches focused on NOX reductions in the combustor are needed to mitigate the air quality-related health impacts from LTO emissions

Health and climate benefits of offshore wind facilities in the Mid-Atlantic United States

Electricity from fossil fuels contributes substantially to both climate change and the health burden of air pollution. Renewable energy sources are capable of displacing electricity from fossil fuels, but the quantity of health and climate benefits depend on site-specific attributes that are not often included in quantitative models. Here, we link an electrical grid simulation model to an air pollution health impact assessment model and US regulatory estimates of the impacts of carbon to estimate the health and climate benefits of offshore wind facilities of different sizes in two different locations. We find that offshore wind in the Mid-Atlantic is capable of producing health and climate benefits of between $54 and$120 per MWh of generation, with the largest simulated facility (3000 MW off the coast of New Jersey) producing approximately $690 million in benefits in 2017. The variability in benefits per unit generation is a function of differences in locations (Maryland versus New Jersey), simulated years (2012 versus 2017), and facility generation capacity, given complexities of the electrical grid and differences in which power plants are offset. This work demonstrates health and climate benefits of offshore wind, provides further evidence of the utility of geographically-refined modeling frameworks, and yields quantitative insights that would allow for inclusion of both climate and public health in benefits assessments of renewable energy

Health and climate benefits of offshore wind facilities in the Mid-Atlantic United States

Publisher's PDFElectricity from fossil fuels contributes substantially to both climate change and the health burden of air pollution. Renewable energy sources are capable of displacing electricity from fossil fuels, but the quantity of health and climate benefits depend on site-specific attributes that are not often included in quantitative models. Here, we link an electrical grid simulation model to an air pollution health impact assessment model and US regulatory estimates of the impacts of carbon to estimate the health and climate benefits of offshore wind facilities of different sizes in two different locations. We find that offshore wind in the Mid-Atlantic is capable of producing health and climate benefits of between $54 and$120 per MWh of generation, with the largest simulated facility (3000 MW off the coast of New Jersey) producing approximately $690 million in benefits in 2017. The variability in benefits per unit generation is a function of differences in locations (Maryland versus New Jersey), simulated years (2012 versus 2017), and facility generation capacity, given complexities of the electrical grid and differences in which power plants are offset. This work demonstrates health and climate benefits of offshore wind, provides further evidence of the utility of geographically-refined modeling frameworks, and yields quantitative insights that would allow for inclusion of both climate and public health in benefits assessments of renewable energy.University of Delaware, College of Earth, Ocean and Environmen

The Influence of Traffic on Air Quality in an Urban Neighborhood: A Community–University Partnership

Objectives. We evaluated the spatial and temporal patterns of traffic-related air pollutants in an urban neighborhood to determine factors contributing to elevated concentrations and to inform environmental justice concerns