The Social Costs of Hydrofluorocarbons and the Large Climate Benefits from their Expedited Phasedown.

Hydrofluorocarbons are a potent greenhouse gas, yet there remains a lack of quantitative estimates of their social cost. The present study addresses this gap by directly calculating the social cost of hydrofluorocarbons (SC-HFCs) using perturbations of exogenous inputs to integrated assessment models. We first develop a set of direct estimates of the SC-HFCs using methods currently adopted by the United States Government, and then derive updated estimates that incorporate recent advances in climate science and economics. We compare our estimates with commonly used social cost approximations based on global warming potentials to show that the latter is a poor proxy for direct calculation of hydrofluorocarbon emissions impacts using IAMs. Applying our SC-HFCs to the Kigali Amendment, a global agreement to phase down HFCs, we estimate that it provides $37 trillion (2020USD) in climate benefits over its lifetime. Expediting the phasedown could increase the estimated climate benefits to $41 trillion (2020USD).

Advancing the estimation of future climate impacts within the United States.

Evidence of the physical and economic impacts of climate change is a critical input to policy development and decision-making. In addition to the magnitude of potential impacts, detailed estimates of where, when, and to whom those damages may occur; the types of impacts that will be most damaging; uncertainties in these damages; and the ability of adaptation to reduce potential risks are all interconnected and important considerations. This study utilizes the reduced-complexity model, the Framework for Evaluating Damages and Impacts (FrEDI), to rapidly project economic and physical impacts of climate change across 10 000 future scenarios for multiple impact sectors, regions, and populations within the contiguous United States (US). Results from FrEDI show that net national damages increase overtime, with mean climate-driven damages estimated to reach USD 2.9 trillion (95 % confidence interval (CI): USD 510 billion to USD 12 trillion) annually by 2090. Detailed FrEDI results show that for the analyzed sectors the majority of annual long-term (e.g., 2090) damages are associated with climate change impacts to human health, including mortality attributable to climate-driven changes in temperature and air pollution (O3 and PM2.5) exposure. Regional results also show that annual long-term climate-driven damages vary geographically. The Southeast (all regions are as defined in Fig. 5) is projected to experience the largest annual damages per capita (mean: USD 9300 per person annually; 95 % CI: USD 1800-USD 37 000 per person annually), whereas the smallest damages per capita are expected in the Southwest (mean: USD 6300 per person annually; 95 % CI: USD 840-USD 27 000 per person annually). Climate change impacts may also broaden existing societal inequalities, with, for example, Black or African Americans being disproportionately affected by additional premature mortality from changes in air quality. Lastly, FrEDI projections are extended through 2300 to estimate the net present climate-driven damages within US borders from marginal changes in greenhouse gas emissions. Combined, this analysis provides the most detailed illustration to date of the distribution of climate change impacts within US borders.

Comprehensive evidence implies a higher social cost of CO2.

The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit-cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44-$413 per tCO2: 5%-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government's current value of $51 per tCO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.

A Market for Snow: Modeling Winter Recreation Patterns Under Current and Future Climate.

Throughout the winter months across the globe, mountain communities and snow-enthusiasts alike anxiously monitor ever-changing snowpack conditions. We model the behavioral response to this climate amenity by pairing a unique panel of 12 million short-term property rental transactions with daily local weather, daily local snowpack, and daily local snowfall in every major ski resort market across the United States. Matching the spatial and temporal variation in the level of the amenity with that of related market transactions, we derive market-specific demand elasticities, explicitly accounting for substitution, to model recreation patterns throughout a typical season. Lastly, we combine downscaled projections of local snowpack under future climate scenarios to estimate within and across season trends in visitation during mid and late-century conditions. Our model predicts reductions in snow-related visitation of -40% to -60%, almost twice as large as previous estimates suggest. This translates to a lower-bound on the annual willingness to pay to avoid reductions in snowpack between $1.23 billion (RCP4.5) and $2.05 billion (RCP8.5) by the end of the century.

Benefits of the fire mitigation ecosystem service in The Great Dismal Swamp National Wildlife Refuge, Virginia, USA.

The Great Dismal Swamp (GDS) National Wildlife Refuge delivers multiple ecosystem services, including air quality and human health via fire mitigation. Our analysis estimates benefits of this service through its potential to reduce catastrophic wildfire related impacts on the health of nearby human populations. We used a combination of high-frequency satellite data, ground sensors, and air quality indices to determine periods of public exposure to dense emissions from a wildfire within the GDS. We examined emergency department (ED) visitation in seven Virginia counties during these periods, applied measures of cumulative Relative Risk to derive the effects of wildfire smoke exposure on ED visitation rates, and estimated economic losses using regional Cost of Illness values established within the US Environmental Protection Agency BenMAP framework. Our results estimated the value of one avoided catastrophic wildfire in the refuge to be $3.69 million (2015 USD), or $306 per hectare of burn. Reducing the frequency or severity of extensive, deep burning peatland wildfire events has additional benefits not included in this estimate, including avoided costs related to fire suppression during a burn, carbon dioxide emissions, impacts to wildlife, and negative outcomes associated with recreation and regional tourism. We suggest the societal value of the public health benefits alone provides a significant incentive for refuge mangers to implement strategies that will reduce the severity of catastrophic wildfires.