The Social Cost of Ozone-Related Mortality Impacts From Methane Emissions.

Atmospheric methane directly affects surface temperatures and indirectly affects ozone, impacting human welfare, the economy, and environment. The social cost of methane (SC-CH4) metric estimates the costs associated with an additional marginal metric ton of emissions. Current SC-CH4 estimates do not consider the indirect impacts associated with ozone production from changes in methane. We use global model simulations and a new BenMAP webtool to estimate respiratory-related deaths associated with increases in ozone from a pulse of methane emissions in 2020. By using an approach consistent with the current SC-CH4 framework, we monetize and discount annual damages back to present day values. We estimate that the methane-ozone mechanism is attributable to 760 (95% CI: 330-1200) respiratory-related deaths per million metric tons of methane globally, for a global net present damage of $1800/mT (95% CI: $760-$2800/Mt CH4; 2% Ramsey discount rate); this would double the current SC-CH4 if included. These physical impacts are consistent with recent studies, but comparing direct costs is challenging. Economic damages are sensitive to uncertainties in the exposure and health risks associated with tropospheric ozone, assumptions about future projections of NOx emissions, socioeconomic conditions, and mortality rates, monetization parameters, and other factors. Our estimates are highly sensitive to uncertainties in ozone health risks. We also develop a reduced form model to test sensitivities to other parameters. The reduced form tool runs with a user-supplied emissions pulse, as well as socioeconomic and precursor projections, enabling future integration of the methane-ozone mechanism into the SC-CH4 modeling framework.

Regional temperature-ozone relationships across the U.S. under multiple climate and emissions scenarios.

The potential effects of 21st century climate change on ozone (O3) concentrations in the United States are investigated using global climate simulations to drive higher-resolution regional meteorological and chemical transport models. Community Earth System Model (CESM) and Coupled Model version 3 (CM3) simulations of the Representative Concentration Pathway 8.5 scenario are dynamically downscaled using the Weather Research and Forecasting model, and the resulting meteorological fields are used to drive the Community Multiscale Air Quality model. Air quality is modeled for five 11-year periods using both a 2011 air pollutant emission inventory and a future projection accounting for full implementation of promulgated regulatory controls. Across the U.S., CESM projects daily maximum temperatures during summer to increase 1-4°C by 2050 and 2-7°C by 2095, while CM3 projects warming of 2-7°C by 2050 and 4-11°C by 2095. The meteorological changes have geographically varying impacts on O3 concentrations. Using the 2011 emissions dataset, O3 increases 1-5 ppb in the central Great Plains and Midwest by 2050 and more than 10 ppb by 2095, but it remains unchanged or even decreases in the Gulf Coast, Maine, and parts of the Southwest. Using the projected emissions, modeled increases are attenuated while decreases are amplified, indicating that planned air pollution control measures ameliorate the ozone climate penalty. The relationships between changes in maximum temperature and changes in O3 concentrations are examined spatially and quantified to explore the potential for developing an efficient approach for estimating air quality impacts of other future climate scenarios.Implications: The effects of climate change on ozone air quality in the United States are investigated using two global climate model simulations of a high warming scenario for five decadal periods in the 21st century. Warming summer temperatures simulated under both models lead to higher ozone concentrations in some regions, with the magnitude of the change increasing with temperature over the century. The magnitude and spatial extent of the increases are attenuated under a future emissions projection that accounts for regulatory controls. Regional linear regression relationships are developed as a first step toward development of a reduced form model for efficient estimation of the health impacts attributable to changes in air quality resulting from a climate change scenario.

A temperature binning approach for multi-sector climate impact analysis.

Characterizing the future risks of climate change is a key goal of climate impacts analysis. Temperature binning provides a framework for analyzing sector-specific impacts by degree of warming as an alternative or complement to traditional scenario-based approaches in order to improve communication of results, comparability between studies, and flexibility to facilitate scenario analysis. In this study, we estimate damages for nine climate impact sectors within the contiguous United States (US) using downscaled climate projections from six global climate models, at integer degrees of US national warming. Each sector is analyzed based on socioeconomic conditions for both the beginning and the end of the century. The potential for adaptive measures to decrease damages is also demonstrated for select sectors; differences in damages across adaptation response scenarios within some sectors can be as much as an order of magnitude. Estimated national damages from these sectors based on a reactive adaptation assumption and 2010 socioeconomic conditions range from $600 million annually per degree of national warming for winter recreation to $8 billion annually per degree of national warming for labor impacts. Results are also estimated per degree of global temperature change and for 2090 socioeconomic conditions.

Improving reduced complexity model assessment and usability.

Reduced complexity climate models are useful tools with practical policy applications, yet evaluation of their performance and application is nascent. We call for stakeholder-driven development and assessment to address user needs, including provision of open-source code and guidance to inform model selection and application.

Economic Valuation of Coccidioidomycosis (Valley Fever) Projections in the United States in Response to Climate Change.

Coccidioidomycosis, or valley fever, is an infectious fungal disease currently endemic to the southwestern United States. Symptoms of valley fever range in severity from flu-like illness to severe morbidity and mortality. Warming temperatures and changes in precipitation patterns may cause the area of endemicity to expand northward throughout the western United States, putting more people at risk for contracting valley fever. This may increase the health and economic burdens from this disease. We developed an approach to describe the relationship between climate conditions and valley fever incidence using historical data and generated projections of future incidence in response to both climate change and population trends using the Climate Change Impacts and Risk Analysis (CIRA) framework developed by the U.S. Environmental Protection Agency. We also developed a method to estimate economic impacts of valley fever that is based on case counts. For our 2000-15 baseline time period, we estimated annual medical costs, lost income, and economic welfare losses for valley fever in the United States were $400,000 per case, and the annual average total cost was $3.9 billion per year. For a high greenhouse gas emission scenario and accounting for population growth, we found that total annual costs for valley fever may increase up to 164% by year 2050 and up to 380% by 2090. By the end of the twenty-first century, valley fever may cost $620,000 per case and the annual average total cost may reach $18.5 billion per year. This work contributes to the broader effort to monetize climate change-attributable damages in the United States.

City-level vulnerability to temperature-related mortality in the USA and future projections: a geographically clustered meta-regression.

BACKGROUND: Extreme heat exposure can lead to premature death. Climate change is expected to increase the frequency, intensity, and duration of extreme heat events, resulting in many additional heat-related deaths globally, as well as changing the nature of extreme cold events. At the same time, vulnerability to extreme heat has decreased over time, probably due to a combination of physiological, behavioural, infrastructural, and technological adaptations. We aimed to account for these changes in vulnerability and avoid overstated projections for temperature-related mortality. We used the historical observed decrease in vulnerability to improve future mortality estimates. METHODS: We used historical mortality and temperature data from 208 US cities to quantify how observed changes in vulnerability from 1973 to 2013 affected projections of temperature-related mortality under various climate scenarios. We used geographically structured meta-regression to characterise the relationship between temperature and mortality for these urban populations over the specified time period. We then used the fitted relationships to project mortality under future climate conditions. FINDINGS: Between Oct 26, 2018, and March 9, 2020, we established that differences in vulnerability to temperature were geographically structured. Vulnerability decreased over time in most areas. US mortalities projected from a 2°C increase in mean temperature decreased by more than 97% when using 2003-13 data compared with 1973-82 data. However, these benefits declined with increasing temperatures, with a 6°C increase showing only an 84% decline in projected mortality based on 2003-13 data. INTERPRETATION: Even after accounting for adaptation, the projected effects of climate change on premature mortality constitute a substantial public health risk. Our work suggests large increases in temperature will require additional mitigation to avoid excess mortality from heat events, even in areas with high air conditioning coverage in place. FUNDING: The US Environmental Protection Agency and Abt Associates.

Associations Between Simulated Future Changes in Climate, Air Quality, and Human Health.

Importance: Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 µm (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. Objective: To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. Design, Setting, and Participants: This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. Main Outcomes and Measures: The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. Results: The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21 000 (95% CI, 14 000-28 000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15 000 (95% CI, 10 000-20 000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. Conclusions and Relevance: These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.

Impact of South Asian brick kiln emission mitigation strategies on select pollutants and near-term Arctic temperature responses.

The brick kiln industrial sector in South Asia accounts for large amounts of short-lived climate forcer (SLCF) emissions, namely black carbon (BC), organic carbon (OC), and sulfur dioxide (SO2; the precursor to atmospheric sulfate [SO4]). These SLCFs are air pollutants and have important impacts on both human health and the Arctic, a region currently experiencing more than double the rate of warming relative to the global average. Using previously derived Arctic equilibrium temperature response factors, we estimate the contribution to Arctic temperature impacts from previously reported emissions of BC, OC, and SO2 from four prevalent South Asian brick kiln types (Bull's Trench [BTK], Down Draught [DDK], Vertical Shaft [VSBK], and Zig-zag). Net annual BC (115 gigagrams [Gg]), OC (17 Gg), and SO2 (350 Gg) baseline emissions from all four South Asian kiln types resulted in 3.36 milliKelvin (mK) of Arctic surface warming. Given these baseline emissions and Arctic temperature responses, we estimate the current and maximum potential emission and temperature mitigation considering two kiln type conversions. Assuming no change in brick production, baseline emissions have been reduced by 17% when considering current BTK to Zig-zag conversions and have the potential to decrease by 82% given a 100% future conversion rate. This results in a 25% and 119% reduction in Arctic warming, respectively. Replacing DDKs with VSBKs increases baseline SLCF emissions by 28% based on current conversions and has the potential to increase by 131%. This conversion still reduces baseline warming by 31% and 149%, respectively. These results show that brick kiln conversions can have different impacts on local air quality and Arctic climate. When considering brick kiln emissions mitigation options, regional and/or local policy action should consider several factors, including local air quality, worker health and safety, cost, quality of bricks, as well as global climate impacts.

Modeling Coastal Flood Risk and Adaptation Response under Future Climate Conditions.

The National Coastal Property Model (NCPM) simulates flood damages resulting from sea level rise and storm surge along the contiguous U.S. coastline. The model also projects local-level investments in a set of adaptation measures under the assumption that these measures will be adopted when benefits exceed the costs over a 30-year period. However, it has been observed that individuals and communities often underinvest in adaptive measures relative to standard cost-benefit assumptions due to financial, psychological, sociopolitical, and technological factors. This study applies an updated version of the NCPM to incorporate improved cost-benefit tests and to approximate observed sub-optimal flood risk reduction behavior. The updated NCPM is tested for two multi-county sites: Virginia Beach, VA and Tampa, FL. Sub-optimal adaptation approaches slow the implementation of adaptation measures throughout the 100-year simulation and they increase the amount of flood damages, especially early in the simulation. The net effect is an increase in total present value cost of $1.1 to $1.3 billion (2015 USD), representing about a 10% increase compared to optimal adaptation approaches. Future calibrations against historical data and incorporation of non-economic factors driving adaptation decisions could prove useful in better understanding the impacts of continued sub-optimal behavior.

Combining the effects of increased atmospheric carbon dioxide on protein, iron, and zinc availability and projected climate change on global diets: a modelling study.

BACKGROUND: Increasing atmospheric concentrations of carbon dioxide (CO2) affect global nutrition via effects on agricultural productivity and nutrient content of food crops. We combined these effects with economic projections to estimate net changes in nutrient availability between 2010 and 2050. METHODS: In this modelling study, we used the International Model for Policy Analysis of Agricultural Commodities and Trade to project per capita availability of protein, iron, and zinc in 2050. We used estimated changes in productivity of individual agricultural commodities to model effects on production, trade, prices, and consumption under moderate and high greenhouse gas emission scenarios. Two independent sources of data, which used different methodologies to determine the effect of increased atmospheric CO2 on different key crops, were combined with the modelled food supply results to estimate future nutrient availability. FINDINGS: Although technological change, market responses, and the effects of CO2 fertilisation on yield are projected to increase global availability of dietary protein, iron, and zinc, these increases are moderated by negative effects of climate change affecting productivity and carbon penalties on nutrient content. The carbon nutrient penalty results in decreases in the global availability of dietary protein of 4·1%, iron of 2·8%, and zinc of 2·5% as calculated using one dataset, and decreases in global availability of dietary protein of 2·9%, iron of 3·9%, and zinc of 3·4% using the other dataset. The combined effects of projected increases in atmospheric CO2 (ie, carbon nutrient penalty, CO2 fertilisation, and climate effects on productivity) will decrease growth in the global availability of nutrients by 19·5% for protein, 14·4% for iron, and 14·6% for zinc relative to expected technology and market gains by 2050. The many countries that currently have high levels of nutrient deficiency would continue to be disproportionately affected. INTERPRETATION: This approach is an improvement in estimating future global food security by simultaneously projecting climate change effects on crop productivity and changes in nutrient content under increased concentrations of CO2, which accounts for a much larger effect on nutrient availability than CO2 fertilisation. Regardless of the scenario used to project future consumption patterns, the net effect of increasing concentrations of atmospheric CO2 will slow progress in decreasing global nutrient deficiencies. FUNDING: US Environmental Protection Agency, Consultative Group on International Agricultural Research (CIGAR) Research Program on Policies, Institutions and Markets (PIM), and the CGIAR Research Program on Climate Change and Food Security (CCAFS).

Informing Future Risks of Record-Level Rainfall in the United States.

The changing risk of extreme precipitation is difficult to project. Events are rare by definition, and return periods of heavy precipitation events are often calculated assuming a stationary climate. Furthermore, ensembles of climate model projections are not large enough to fully categorize the tails of the distribution. To address this, we cluster the contiguous United States into self-similar hydroclimates to estimate changes in the expected frequency of extremely rare events under scenarios of global mean temperature change. We find that, although there is some regional variation, record events are projected in general to become more intense, with 500-year events intensifying by 10-50% under 2 °C of warming and by 40-100% under 4 °C of warming. This analysis could provide information to inform regional prioritization of resources to improve the resilience of U.S. infrastructure.

A quantitative approach to evaluating the GWP timescale through implicit discount rates.

The 100-year global warming potential (GWP) is the primary metric used to compare the climate impacts of emissions of different greenhouse gases (GHGs). The GWP relies on radiative forcing rather than damages, assumes constant future concentrations, and integrates over a timescale of 100 years without discounting; these choices lead to a metric that is transparent and simple to calculate, but have also been criticized. In this paper, we take a quantitative approach to evaluating the choice of time horizon, accounting for many of these complicating factors. By calculating an equivalent GWP timescale based on discounted damages resulting from CH4 and CO2 pulses, we show that a 100-year timescale is consistent with a discount rate of 3.3% (interquartile range of 2.7% to 4.1% in a sensitivity analysis). This range of discount rates is consistent with those often considered for climate impact analyses. With increasing discount rates, equivalent timescales decrease. We recognize the limitations of evaluating metrics by relying only on climate impact equivalencies without consideration of the economic and political implications of metric implementation.

Climate Benefits of U.S. EPA Programs and Policies That Reduced Methane Emissions 1993-2013.

The United States (U.S.) Environmental Protection Agency (EPA) has established voluntary programs to reduce methane (CH4) emissions, and regulations that either directly reduce CH4 or provide co-benefits of reducing CH4 emissions while controlling for other air pollutants. These programs and regulations address four sectors that are among the largest domestic CH4 emissions sources: municipal solid waste landfills, oil and natural gas, coal mining, and agricultural manure management. Over the 1993-2013 time period, 127.9 Tg of CH4 emissions reductions were attributed to these programs, equal to about 18% of the counterfactual (or potential) domestic emissions over that time, with almost 70% of the abatement due to landfill sector regulations. Reductions attributed to the voluntary programs increased nearly continuously during the study period. We quantified how these reductions influenced atmospheric CH4 concentration and global temperature, finding a decrease in concentration of 28 ppb and an avoided temperature rise of 0.006 °C by 2013. Further, we monetized the climate and ozone-health impacts of the CH4 reductions, yielding an estimated benefit of $255 billion. These results indicate that EPA programs and policies have made a strong contribution to CH4 abatement, with climate and air quality benefits.

Future Arctic temperature change resulting from a range of aerosol emissions scenarios.

The Arctic temperature response to emissions of aerosols-specifically black carbon (BC), organic carbon (OC), and sulfate-depends on both the sector and the region where these emissions originate. Thus, the net Arctic temperature response to global aerosol emissions reductions will depend strongly on the blend of emissions sources being targeted. We use recently published equilibrium Arctic temperature response factors for BC, OC, and sulfate to estimate the range of present-day and future Arctic temperature changes from seven different aerosol emissions scenarios. Globally, Arctic temperature changes calculated from all of these emissions scenarios indicate that present-day emissions from the domestic and transportation sectors generate the majority of present-day Arctic warming from BC. However, in all of these scenarios, this warming is more than offset by cooling resulting from SO2 emissions from the energy sector. Thus, long-term climate mitigation strategies that are focused on reducing carbon dioxide (CO2) emissions from the energy sector could generate short-term, aerosol-induced Arctic warming. A properly phased approach that targets BC-rich emissions from the transportation sector as well as the domestic sectors in key regions-while simultaneously working toward longer-term goals of CO2 mitigation-could potentially avoid some amount of short-term Arctic warming.

Projections of temperature-attributable premature deaths in 209 U.S. cities using a cluster-based Poisson approach.

BACKGROUND: A warming climate will affect future temperature-attributable premature deaths. This analysis is the first to project these deaths at a near national scale for the United States using city and month-specific temperature-mortality relationships. METHODS: We used Poisson regressions to model temperature-attributable premature mortality as a function of daily average temperature in 209 U.S. cities by month. We used climate data to group cities into clusters and applied an Empirical Bayes adjustment to improve model stability and calculate cluster-based month-specific temperature-mortality functions. Using data from two climate models, we calculated future daily average temperatures in each city under Representative Concentration Pathway 6.0. Holding population constant at 2010 levels, we combined the temperature data and cluster-based temperature-mortality functions to project city-specific temperature-attributable premature deaths for multiple future years which correspond to a single reporting year. Results within the reporting periods are then averaged to account for potential climate variability and reported as a change from a 1990 baseline in the future reporting years of 2030, 2050 and 2100. RESULTS: We found temperature-mortality relationships that vary by location and time of year. In general, the largest mortality response during hotter months (April - September) was in July in cities with cooler average conditions. The largest mortality response during colder months (October-March) was at the beginning (October) and end (March) of the period. Using data from two global climate models, we projected a net increase in premature deaths, aggregated across all 209 cities, in all future periods compared to 1990. However, the magnitude and sign of the change varied by cluster and city. CONCLUSIONS: We found increasing future premature deaths across the 209 modeled U.S. cities using two climate model projections, based on constant temperature-mortality relationships from 1997 to 2006 without any future adaptation. However, results varied by location, with some locations showing net reductions in premature temperature-attributable deaths with climate change.