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Data on income distributions within and across countries are becoming increasingly important to inform analysis of income inequality and to understand the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same income concept and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the GINI coefficient. For the imputation, we use a recently developed principal components-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions and the world as a whole. Our aggregation method takes into account both within-country and across-country income inequality when aggregating to the regional level. This dataset will enable more robust analysis of income distribution at multiple scales.

Methane directly contributes to air pollution, as an ozone precursor, and to climate change, generating physical and economic damages to different systems, namely agriculture, vegetation, energy, human health, or biodiversity. The methane-related damages to climate, measured as the Social Cost of Methane, and to human health have been analyzed by different studies and considered by government rulemaking in the last decades, but the ozone-related damages to crop revenues associated to methane emissions have not been incorporated to policy agenda. Using a combination of the Global Change Analysis Model and the TM5-FASST Scenario Screening Tool, we estimate that global marginal agricultural damages range from ~ 423 to 556 $2010/t-CH4, of which 98 $2010/t-CH4 occur in the USA, which is the most affected region due to its role as a major crop producer, followed by China, EU-15, and India. These damages would represent 39–59% of the climate damages and 28–64% of the human health damages associated with methane emissions by previous studies. The marginal damages to crop revenues calculated in this study complement the damages from methane to climate and human health, and provides valuable information to be considered in future cost-benefits analyses. © 2023, The Author(s). JS and SW were supported by the U.S. Environmental Protection Agency, under Interagency Agreement DW-089-92459801. The views expressed in this article are purely those of the authors and do not, under any circumstances, represent the views or policies of the U.S. Environmental Protection Agency or the European Commission. JS and SW were supported by the U.S. Environmental Protection Agency, under Interagency Agreement DW-089-92459801. The views expressed in this article are purely those of the authors and do not, under any circumstances, represent the views or policies of the U.S. Environmental Protection Agency or the European Commission.

Mitigating greenhouse gas emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production. However, certain mitigation measures may generate unintended consequences to food availability and food access due to both land use competition and economic burden of mitigation. Integrated assessment models (IAM) are generally used to evaluate these policies; however, currently these models may not capture the importance of income and food prices for hunger and overall economic wellbeing. Here, we implement a measure of food security that captures the nutritional and economic aspects as the total expenditures on staple foods divided by income and weighted by total caloric consumption in an IAM, the global change analysis model (GCAM4.0). We then project consumer prices and our measure of food security along the shared socioeconomic pathways. Sustained economic growth underpins increases in caloric consumption and lowering expenditures on staple foods. Strict conservation policies affect food accessibility in a larger number of developing countries, whereas the negative effects of pricing terrestrial emissions are more concentrated on the poor in Sub-Saharan Africa, by substantially replacing their cropland with forests and affecting the production of key staples.The online version contains supplementary material available at 10.1007/s10669-022-09860-4.

In passing the Bipartisan Budget Act of 2018, Congress reformed and strengthened a section of the tax code, 45Q, which provides tax credits of up to $35/ton CO(2) for the capture and utilization of CO(2) in qualifying applications such as enhanced oil recovery (EOR) and up to $50/ton CO(2) for CO(2) that is captured and permanently stored in a geologic repository. Earlier versions of the tax credit with lower credit values generated limited interest. This change to the tax code could potentially alter U.S. energy systems. This paper examines the effect of the increased 45Q credits on CO(2) capture, utilization and storage (CCUS) deployment in the United States and on petroleum and power production. A range of potential outcomes is explored using five modeling tools. The paper goes on to explore the potential impact of possible modifications of the current tax credit including extension of its availability in time, the period over which 45Q tax credits can be utilized for any given asset and increases in the value of the credit as well as interactions with technology availability and carbon taxation. The paper concludes that 45Q tax credits could stimulate additional CCUS beyond that which is already underway.

Soil erosion and sediment deposition are relevant to multiple important ecosystem services essential for natural and human systems. The present study aims to project future soil erosion and sediment deposition in the Upper Mississippi River Basin (UMRB) using climate projections by five Global Circulation Models (GCMs) under the Representative Concentrations Pathway (RCP) 8.5 scenario. To understand the importance of freeze-thaw cycles (FTCs) for soil erosion and sediment deposition estimation with climate change, this study compared two Soil and Water Assessment Tool (SWAT) models with different representations of the FTCs, with the standard SWAT using a simple regression method and SWAT-FT employing a physically based method. Modeling results show that future climate change can pronouncedly intensify soil erosion and increase sediment deposition, and the impacts are sensitive to how FTCs are represented in the model. The standard SWAT projected an increase in soil erosion by nearly 40% by the end of the 21st century, which is much lower than the projected over 65% increase in soil erosion by SWAT-FT. For sediment deposition, the projected percent changes by the standard SWAT and SWAT-FT also deviate from each other (i.e., about 70% by the standard SWAT vs about 120% by SWAT-FT). Overall, these results demonstrate the important roles of FTCs in projecting future soil erosion and sediment deposition and underline the need to consider the effects of conservation practices on FTCs to realistically assess the effectiveness of those measures.

The Paris Agreement of 2015 uses Nationally Determined Contributions (NDCs) to achieve its goal to limit climate change to well below 2°C. Article 6 allows countries to cooperatively implement NDCs provided they do not double-count mitigation. We estimate that economic efficiency gains from cooperative implementation of existing NDC goals using Article 6 could reduce the cost of achieving NDC goals in 2030 to all parties by [Formula: see text]$[Formula: see text], which if reinvested in additional emissions mitigation could add 9 billion tons CO2/year mitigation, beyond the 8 billion tons CO2/year currently pledged in 2030. We estimate that more than half of the 2030 gains could come from nature-based measures, but long-term potential for nature-based measures is more limited. How much or even if this economic potential can be realized is uncertain and will depend on both the rules and their implementation.

Agricultural production is highly sensitive to changes in climate and weather patterns. The focus of the great majority of studies assessing climate impacts on agriculture has been on mean changes in agricultural responses. However, the manner in which global agricultural markets respond to the interannual variability of the climate and biophysical shocks is poorly understood. Here we show a strong transmission of interannual variations in climate-induced biophysical yield shocks to agriculture markets, which is magnified further by endogenous market fluctuations. We demonstrate the importance of imperfect versus perfect expectations of market and weather in generating the market fluctuations that play a key role in transferring the interannual variations to markets. We find that the volatility of market prices and consumption could be potentially reduced on average by 55% and 41%, respectively, with improved expectations, where agricultural producers make better decisions to adapt to climate and biophysical variability. We also find much heterogeneity in interannual variability across crops and regions, which is considerably mediated by trade as part of the economic response. Our study provides new insights on climate impacts on agricultural market variability and lays a foundation for further investigating the full range of climate impacts on biophysical and human systems.

Climate change can have substantial impacts on nitrogen runoff, which is a major cause of eutrophication, harmful algal blooms, and hypoxia in freshwaters and coastal regions. We examined responses of nitrate loading to climate change in the Upper Mississippi River Basin (UMRB) with an enhanced Soil and Water Assessment Tool with physically based Freeze-Thaw cycle representation (SWAT-FT), as compared with the original SWAT model that employs an empirical equation. Driven by future climate projections from five General Circulation Models (GCMs) from 1960 to 2099 under the Representative Concentrations Pathways (RCP) 8.5 scenario, we analyzed changes in riverine nitrate loadings, as well as terrestrial surface and subsurface contributions of the UMRB in the 21st century relative to the baseline period of 1960-1999. By the end of the 21st century, the original SWAT model predicted about a 50% increase in riverine nitrate loadings which is nearly twice as much as that estimated by SWAT-FT (ca. 25%). Such a large difference in projected nitrate changes can potentially mislead mitigation strategies that aim to reduce nitrogen runoff from the UMRB. Further analysis shows that the difference between the original SWAT model and SWAT-FT led to substantial discrepancies in the spatial distribution of surface and subsurface nitrate loadings in the UMRB. In general, SWAT-FT predicted more nitrate leaching for northwestern parts of the UMRB which are more sensitive to freeze-thaw cycle, mainly because SWAT-FT simulated less frequent frozen soils. This study highlights the importance of using physically based freeze-thaw cycle representation in water quality modeling. Design of future nitrogen runoff reduction strategies should include careful assessment of effects that land management has on the freeze-thaw cycles to provide reliable projection of water quality under climate change.

Agricultural crop yields are susceptible to changes in future temperature, precipitation, and other Earth system factors. Future changes to these physical Earth system attributes and their effects on agricultural crop yields are highly uncertain. United States agricultural producers will be affected by such changes whether they occur domestically or internationally through international commodity markets. Here we present a replication study of previous investigations (with different models) showing that potential direct domestic climate effects on crop yields in the U.S. have financial consequences for U.S. producers on the same order of magnitude but opposite in sign to indirect financial impacts on U.S. producers from climate effects on crop yields elsewhere in the world. We conclude that the analysis of country-specific financial climate impacts cannot ignore indirect effects arising through international markets. We find our results to be robust across a wide range of potential future crop yield impacts analyzed in the multi-sector dynamic global model GCAM.

A number of countries – including major economies such as the UK, Canada, France, China, and Japan – have announced net-zero emissions pledges generally consistent with the IPCC's guidelines for 1.5 °C. As countries design strategies to achieve these pledges, decision-makers are faced with questions and issues related to the role of Carbon Dioxide Removal (CDR). This perspective highlights three issues. First, the scale of CDR deployment will determine the level of emission mitigation in the energy system and vice versa. Second, CDR will interact with societal priorities beyond climate. Finally, the location of CDR could have implications for the country-level pledges, and emissions trading. While these issues have been discussed in the literature in other contexts, this perspective highlights their importance for net-zero emissions strategies.

Agricultural yields are highly susceptible to changes in weather system patterns, including annual and sub-annual changes in temperature and precipitation. The impacts of future meteorological variable changes on crop yields have been widely studied in both empirical and process-based models. These changes in future yields can be used in economic models to adjust future crop yields or production functions to reflect the effects of changing weather conditions. This work presents an econometric approach that combines historical weather data with the biophysical growth cycles of maize, winter wheat, and soybean to predict the year-to-year weather-driven yield shocks for rainfed crops. Temperature and modeled soil moisture are taken as predictors, allowing testing of the fitted rainfed model’s ability to predict shocks to irrigated yields by assuming irrigation produces the yield-maximizing level of soil moisture. This approach enables prediction of the potential impacts of changing weather patterns on irrigated crops in areas that are currently primarily rainfed. We present the results of the empirical model, fitted with rainfed data; out-of-sample validation on irrigated crops; and projections of yield shocks under multiple future climate scenarios. Under a bias-corrected GFDL RCP8.5 scenario, this approach predicts the average of annual weather-induced yield shocks, relative to the average of 2006–2020 annual yield shocks, across U.S. counties in the 2040–2060 period of −17% and −13% for rainfed and irrigated maize, −19% and −18% for rainfed and irrigated soybean, and −4% and −2% for rainfed and irrigated winter wheat. Predicted changes in the 2070–2090 period are −30% and −29% for rainfed and irrigated maize, −33% for both rainfed and irrigated soybean, and −7% and −5%for rainfed and irrigated winter wheat. The annual yield shocks presented here will enable modeling of the economic consequences of extreme weather events and potential for irrigation to mitigate such events.

Five new scenarios, or Shared Socioeconomic Pathways (SSPs), have been developed, spanning a range of challenges to mitigation and challenges to adaptation. The Shared Socioeconomic Pathway 4 (SSP4), “Inequality” or “A Road Divided,” is one of these scenarios, characterized by low challenges to mitigation and high challenges to adaptation. We describe, in quantitative terms, the SSP4 as implemented by the Global Change Assessment Model (GCAM), the marker model for this scenario. We use demographic and economic assumptions, in combination with technology and non-climate policy assumptions to develop a quantitative representation of energy, land-use and land-cover, and emissions consistent with the SSP4 narrative. The scenario is one with stark differences within and across regions. High-income regions prosper, continuing to increase their demand for energy and food. Electrification increases in these regions, with the increased generation being met by nuclear and renewables. Low-income regions, however, stagnate due to limited economic growth. Growth in total consumption is dominated by increases in population, not increases in per capita consumption. Due to failures in energy access policies, these regions continue to depend on traditional biofuels, leading to high pollutant emissions. Declining dependence on fossil fuels in all regions means that total radiative forcing absent the inclusion of mitigation or impacts only reaches 6.4 W m−2 in 2100, making this a world with relatively low challenges to mitigation. We explore the effects of mitigation effort on the SSP4 world, finding that the imposition of a carbon price has a varied effect across regions. In particular, the SSP4 mitigation scenarios are characterized by afforestation in the high-income regions and deforestation in the low-income regions. Furthermore, we find that the SSP4 is a world with low challenges to mitigation, but only to a point due to incomplete mitigation of land-related emissions.

In passing the Bipartisan Budget Act of 2018, Congress reformed and strengthened a section of the tax code, 45Q, which provides tax credits of up to $35/ton CO2 for the capture and utilization of CO2 in qualifying applications such as enhanced oil recovery (EOR) and up to $50/ton CO2 for CO2 that is captured and permanently stored in a geologic repository. Earlier versions of the tax credit with lower credit values generated limited interest. This change to the tax code could potentially alter U.S. energy systems. This paper examines the effect of the increased 45Q credits on CO2 capture, utilization and storage (CCUS) deployment in the United States and on petroleum and power production. A range of potential outcomes is explored using five modeling tools. The paper goes on to explore the potential impact of possible modifications of the current tax credit including extension of its availability in time, the period over which 45Q tax credits can be utilized for any given asset and increases in the value of the credit as well as interactions with technology availability and carbon taxation. The paper concludes that 45Q tax credits could stimulate additional CCUS beyond that which is already underway.

Analyses of the future impacts of changing crop yields on agricultural production, prices, food security, and GDP growth using Integrated Assessment models require country-level yield shocks due to changing weather conditions, for a wide range of crops and warming scenarios. We characterize impacts of different climate futures on crop yields for individual countries and years. We use historical crop yield and weather data to empirically estimate annual crop yield responses to temperature and precipitation, constructing reduced-form statistical models that are then coupled with earth system model outputs for the same variables to project future yields. Our main result is a panel of annual shocks to yields of 12 crops (cassava, cotton, maize, potatoes, rice, sorghum, soybean, sugar beet, sugarcane, sunflower, and winter and spring wheat) for 58–136 countries, depending on the crop, through 2099, under moderate and vigorous warming scenarios. We find that global yield impacts by century’s end (2086–2095) are − 2%, − 19%, − 14%, and − 1%, without the CO2 fertilization effect (CFE), for maize, rice, soybean, and wheat, respectively, with similar global values with CFE. However, the global and decadal averages mask regional and year-to-year differences that may have large economic consequences, which IAMs could more fully address by representing agricultural yield impacts through the parameters supplied by our study.

This paper describes GCAM v5.1, an open source model that represents the linkages between energy, water, land, climate, and economic systems. GCAM is a market equilibrium model, is global in scope, and operates from 1990 to 2100 in five-year time steps. It can be used to examine, for example, how changes in population, income, or technology cost might alter crop production, energy demand, or water withdrawals, or how changes in one region's demand for energy affect energy, water, and land in other regions. This paper describes the model, including its assumptions, inputs, and outputs. We then use eleven scenarios, varying socioeconomic and climate policy assumptions, to illustrate the results from the model. The resulting scenarios illustrate a wide range of potential future energy, water, and land uses. We compare the results from GCAM v5.1 to historical data and to future scenario simulations from earlier versions of GCAM and from other models. Finally, we provide information on how to obtain the model.

Accurately characterizing the emissions implications of bioenergy is increasingly important to the design of regional and global greenhouse gas mitigation policies. Market-based policies, in particular, often use information about carbon intensity to adjust relative deployment incentives for different energy sources. However, the carbon intensity of bioenergy is difficult to quantify because carbon emissions can occur when land use changes to expand production of bioenergy crops rather than simply when the fuel is consumed as for fossil fuels. Using a long-term, integrated assessment model, this paper develops an approach for computing the carbon intensity of bioenergy production that isolates the marginal impact of increasing production of a specific bioenergy crop in a specific region, taking into account economic competition among land uses. We explore several factors that affect emissions intensity and explain these results in the context of previous studies that use different approaches. Among the factors explored, our results suggest that the carbon intensity of bioenergy production from land use change (LUC) differs by a factor of two depending on the region in which the bioenergy crop is grown in the United States. Assumptions about international land use policies (such as those related to forest protection) and crop yields also significantly impact carbon intensity. Finally, we develop and demonstrate a generalized method for considering the varying time profile of LUC emissions from bioenergy production, taking into account the time path of future carbon prices, the discount rate and the time horizon. When evaluated in the context of power sector applications, we found electricity from bioenergy crops to be less carbon-intensive than conventional coal-fired electricity generation and often less carbon-intensive than natural-gas fired generation.

Methane is a greenhouse gas that oxidizes to form ground-level ozone, itself a greenhouse gas and a health-harmful air pollutant. Reducing methane emissions will both slow anthropogenic climate change and reduce ozone-related mortality. We estimate the benefits of reducing methane emissions anywhere in the world for ozone-related premature mortality globally and for eight geographic regions. Our methods are consistent with those used by the US Government to estimate the social cost of carbon (SCC). We find that the global short- and long-term premature mortality benefits due to reduced ozone production from methane mitigation are (2011) $790 and $1775 per tonne methane, respectively. These correspond to approximately 70 and 150 % of the valuation of methane’s global climate impacts using the SCC after extrapolating from carbon dioxide to methane using global warming potential estimates. Results for monetized benefits are sensitive to a number of factors, particularly the choice of elasticity to income growth used when calculating the value of a statistical life. The benefits increase for emission years further in the future. Regionally, most of the global mortality benefits accrue in Asia, but 10 % accrue in the United States. This methodology can be used to assess the benefits of methane emission reductions anywhere in the world, including those achieved by national and multinational policies.

In the future, the land system will be facing new intersecting challenges. While food demand, especially for resource-intensive livestock based commodities, is expected to increase, the terrestrial system has large potentials for climate change mitigation through improved agricultural management, providing biomass for bioenergy, and conserving or even enhancing carbon stocks of ecosystems. However, uncertainties in future socio-economic land use drivers may result in very different land-use dynamics and consequences for land-based ecosystem services. This is the first study with a systematic interpretation of the Shared Socio-Economic Pathways (SSPs) in terms of possible land-use changes and their consequences for the agricultural system, food provision and prices as well as greenhouse gas emissions. Therefore, five alternative Integrated Assessment Models with distinctive land-use modules have been used for the translation of the SSP narratives into quantitative projections. The model results reflect the general storylines of the SSPs and indicate a broad range of potential land-use futures with global agricultural land of 4900 mio ha in 2005 decreasing by 743 mio ha until 2100 at the lower (SSP1) and increasing by 1080 mio ha (SSP3) at the upper end. Greenhouse gas emissions from land use and land use change, as a direct outcome of these diverse land-use dynamics, and agricultural production systems differ strongly across SSPs (e.g. cumulative land use change emissions between 2005 and 2100 range from −54 to 402 Gt CO2). The inclusion of land-based mitigation efforts, particularly those in the most ambitious mitigation scenarios, further broadens the range of potential land futures and can strongly affect greenhouse gas dynamics and food prices. In general, it can be concluded that low demand for agricultural commodities, rapid growth in agricultural productivity and globalized trade, all most pronounced in a SSP1 world, have the potential to enhance the extent of natural ecosystems, lead to lowest greenhouse gas emissions from the land system and decrease food prices over time. The SSP-based land use pathways presented in this paper aim at supporting future climate research and provide the basis for further regional integrated assessments, biodiversity research and climate impact analysis.

The Climate Change Impacts and Risk Analysis (CIRA) modeling exercise is a unique contribution to the scientific literature on climate change impacts, economic damages, and risk analysis that brings together multiple, national-scale models of impacts and damages in an integrated and consistent fashion to estimate climate change impacts, damages, and the benefits of greenhouse gas (GHG) mitigation actions in the United States. The CIRA project uses three consistent socioeconomic, emissions, and climate scenarios across all models to estimate the benefits of GHG mitigation policies: a Business As Usual (BAU) and two policy scenarios with radiative forcing (RF) stabilization targets of 4.5 W/m2 and 3.7 W/m2 in 2100. CIRA was also designed to specifically examine the sensitivity of results to uncertainties around climate sensitivity and differences in model structure. The goals of CIRA project are to 1) build a multi-model framework to produce estimates of multiple risks and impacts in the U.S., 2) determine to what degree risks and damages across sectors may be lowered from a BAU to policy scenarios, 3) evaluate key sources of uncertainty along the causal chain, and 4) provide information for multiple audiences and clearly communicate the risks and damages of climate change and the potentialmore » benefits of mitigation. This paper describes the motivations, goals, and design of the CIRA modeling exercise and introduces the subsequent papers in this special issue.« less

The increasing data requirements of complex models demand robust, reproducible, and transparent systems to track and prepare models’ inputs. Here we describe version 1.0 of the gcamdata R package that processes raw inputs to produce the hundreds of XML files needed by the GCAM integrated human-earth systems model. It features extensive functional and unit testing, data tracing and visualization, and enforces metadata, documentation, and flexibility in its component data-processing subunits. Although this package is specific to GCAM, many of its structural pieces and approaches should be broadly applicable to, and reusable by, other complex model/data systems aiming to improve transparency, reproducibility, and flexibility. Funding statement: Primary support for this work was provided by the U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program. Additional support was provided by the U.S. Department of Energy Offices of Fossil Energy, Nuclear Energy, and Energy Efficiency and Renewable Energy and the U.S. Environmental Protection Agency.

A common feature of model inter-comparison efforts is that the base year numbers for important parameters such as population and GDP can differ substantially across models. This paper explores the sources and implications of this variation in Asian countries across the models participating in the Asian Modeling Exercise (AME). Because the models do not all have a common base year, each team was required to provide data for 2005 for comparison purposes. This paper compares the year 2005 information for different models, noting the degree of variation in important parameters, including population, GDP, primary energy, electricity, and CO2 emissions. It then explores the difference in these key parameters across different sources of base-year information. The analysis confirms that the sources provide different values for many key parameters. This variation across data sources and additional reasons why models might provide different base-year numbers, including differences in regional definitions, differences in model base year, and differences in GDP transformation methodologies, are then discussed in the context of the AME scenarios. Finally, the paper explores the implications of base-year variation on long-term model results.

The social cost of carbon (SCC) is a monetized metric for evaluating the benefits associated with marginal reductions in carbon dioxide (CO2) emissions. It represents the expected welfare loss from the future damages caused by the release of one tonne of CO2 in a given year, expressed in consumption equivalent terms. It is intended to be a comprehensive measure, taking into account changes in agricultural productivity, human health risks, loss of ecosystem services and biodiversity, and the frequency and severity of flooding and storms, among other possible impacts. Estimating the SCC requires long-term modeling of global economic activity, the climate system, and the linkages between the two through anthropogenic greenhouse gas (GHG) emissions and the effects of changing climatic conditions on economic activity and human well-being. The United States government currently uses the SCC in regulatory benefit-cost analyses to assess the welfare effects of changes in CO2 emissions. Consistent application of the SCC to federal rulemaking analyses began in 2009-2010 with the development of a set of global SCC estimates that employed three prominent integrated assessment models (IAMs) -- DICE, FUND, and PAGE. The U.S. government report identified a number of limitations associated with SCC estimates in general and itsmore » own assumptions in particular: an incomplete treatment of damages, including potential “catastrophic” impacts; uncertainty regarding the extrapolation of damage functions to high temperatures; incomplete treatment of adaptation and technological change; and the evaluation of uncertain outcomes in a risk-neutral fashion. External experts have identified other potential issues, including how best to model long-term socio-economic and emissions pathways, oversimplified physical climate and carbon cycle modeling within the IAMs, and an inconsistency between non-constant economic growth scenarios and constant discount rates. The U.S. government has committed to updating the estimates regularly as modeling capabilities and scientific and economic knowledge improves. To help foster further improvements in estimating the SCC, the U.S. Environmental Protection Agency and the U.S. Department of Energy hosted a pair of workshops on “Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis.” The first focused on conceptual and methodological issues related to integrated assessment modeling and the second brought together natural and social scientists to explore methods for improving damage assessment for multiple sectors. These two workshops provide the basis for the 13 papers in this special issue.« less

Developing economy greenhouse gas emissions are growing rapidly relative to developed economy emissions (Boden et al. 2010) and developing economies as a group have greater emissions than developed economies. These developments are expected to continue (U.S. Energy Information Administration 2010), which has led some to question the effectiveness of emissions mitigation in developed economies without a commitment to extensive mitigation action from developing economies. One often heard argument against proposed U.S. legislation to limit carbon emissions to mitigate climate change is that, without participation from large developing economies like China and India, stabilizing temperature at 2 degrees Celsius above preindustrial (United Nations 2009), or even reducing global emissions levels, would be impossible (Driessen 2009; RPC Energy Facts 2009) or prohibitively expensive (Clarke et al. 2009). Here we show that significantly delayed action by rapidly developing countries is not a reason to forgo mitigation efforts in developed economies. This letter examines the effect of a scenario with no explicit international climate policy and two policy scenarios, full global action and a developing economy delay, on the probability of exceeding various global average temperature changes by 2100. This letter demonstrates that even when developing economies delay any mitigation efforts until 2050 the effect of action by developed economies will appreciably reduce the probability of more extreme levels of temperature change. This paper concludes that early carbon mitigation efforts by developed economies will considerably affect the distribution over future climate change, whether or not developing countries begin mitigation efforts in the near term.

Demand for agricultural products is an important problem in global change economics. Food consumption will shape and be shaped by global change through interactions with bioenergy and afforestation, two critical issues in meeting international goals. We develop a model of food demand for staple and nonstaple commodities that evolves with changing incomes and prices. The model addresses a long-standing issue in estimating food demands, the evolution of demand relationships across large changes in income and prices. We discuss the model, some of its properties and limitations. We estimate parameter values using pooled cross-sectional-time-series observations and Bayesian Monte Carlo method and cross-validate the model by estimating parameters using a subset of the observations and test its ability to project into the unused observations. Finally, we apply bias correction techniques borrowed from the Earth system modeling community and report results. We find that the demand for food rises rapidly as income initially increases from zero. Demand for staples peaks at under $1000 per person per capita. Nonstaple food demands increase steadily with income. While staples are an inferior good at per capita incomes greater than $1000, we see no evidence that there is a range of per capita income for which staples are Giffen goods.

We use FUND 3.5 to estimate the social cost of carbon dioxide, methane, nitrous oxide, and sulphur hexafluoride emissions. We show the results of a range of sensitivity analyses, focusing on the impact of carbon dioxide fertilization. Ignored in previous studies of the social cost of greenhouse gas emissions, carbon dioxide fertilization has a positive effect at the margin, but only for carbon dioxide. Because of this, the ratio of the social cost of a greenhouse gas to that of carbon dioxide (the global damage potential) is higher - that is, previous papers underestimated the importance of reducing non-carbon dioxide greenhouse gas emissions. When leaving out carbon dioxide fertilization, our estimate of the social cost of methane is comparable to previous estimates. Our estimate of the global damage potential of methane is close to the estimates of the global warming potential because discounting roughly cancels carbon dioxide fertilization. Our estimate of the social cost of nitrous oxide is higher than previous estimates, also when omitting carbon dioxide fertilization. This is because, in FUND, vulnerability to climate change falls over time (with development) while in the long run carbon dioxide is a more potent greenhouse gas than nitrous oxide. Our estimate of the global damage potential of nitrous oxide is larger than the global warming potential because of carbon dioxide fertilization, discounting, and rising atmospheric concentrations of both gases. Our estimate of the social cost of sulphur hexafluoride is similar to the one previous estimate. Its global damage potential is higher than the global warming potential because of carbon dioxide fertilization, discounting, and rising concentrations.

The social cost of carbon (SCC) is a crucial tool for economic analysis of climate policies. The SCC estimates the dollar value of reduced climate change damages associated with a one-metric-ton reduction in carbon dioxide (CO2) emissions. Although the conceptual basis, challenges, and merits of the SCC are well established, its use in government cost-benefit analysis (CBA) is relatively new. In light of challenges in constructing the SCC, its newness in government regulation, and the importance of updating, we propose an institutional process for regular SCC review and revision when used in government policy-making and suggest how scientists might contribute to improved SCC estimates.

Climate change and armed civil conflict are both linked to socioeconomic development, although conditions that facilitate peace may not necessarily facilitate mitigation and adaptation to climate change. While economic growth lowers the risk of conflict, it is generally associated with increased greenhouse gas emissions and costs of climate mitigation policies. This study investigates the links between growth, climate change, and conflict by simulating future civil conflict using new scenario data for five alternative socioeconomic pathways with different mitigation and adaptation assumptions, known as the shared socioeconomic pathways (SSPs). We develop a statistical model of the historical effect of key socioeconomic variables on country-specific conflict incidence, 1960–2013. We then forecast the annual incidence of conflict, 2014–2100, along the five SSPs. We find that SSPs with high investments in broad societal development are associated with the largest reduction in conflict risk. This is most pronounced for the least developed countries—poverty alleviation and human capital investments in poor countries are much more effective instruments to attain global peace and stability than further improvements to wealthier economies. Moreover, the SSP that describes a sustainability pathway, which poses the lowest climate change challenges, is as conducive to global peace as the conventional development pathway. © 2016 IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence.

The authors estimate the growth rate of the social cost of carbon. This is an indication of the optimal rate of acceleration of greenhouse gas emission reduction policy over time. The authors find that the social cost of carbon increases by 1.3% to 3.9% per year, with a central estimate of 2.2%. Previous studies found an average rate of 2.3% and a range of 0.9 to 4.1%. The rate of increase of the social carbon depends on a range of factors, including the pure rate of time preference, the rate of risk aversion, equity weighting, the socioeconomic and emission scenarios, the climate sensitivity, dynamic vulnerability, and the curvature of the impact functions. Paper submitted to the special issue The Social Cost of Carbon

The social cost of carbon is an estimate of the benefit of reducing CO2 emissions by one ton today. As such it is a key input into cost-benefit analysis of climate policy and regulation. We provide a set of new estimates of the social cost of carbon from the integrated assessment model FUND 3.5 and present a regional and sectoral decomposition of our new estimate. China, Western Europe and the United States have the highest share of harmful impacts, with the precise order depending on the discount rate. The most important sectors in terms of impacts are agriculture and increased energy use for cooling. We present an extensive sensitivity analysis with respect to the discount rate, equity weights, different socio economic scenarios and values for the climate sensitivity parameter.

Climate sensitivity and climate-carbon cycle feedbacks interact to determine how global carbon and energy cycles will change in the future. While the science of these connections is well documented, their economic implications are not well understood. Here we examine the effect of climate change on the carbon cycle, the uncertainty in climate outcomes inherent in any given policy target, and the economic implications. We examine three policy scenarios—a no policy “Reference” (REF) scenario, and two policies that limit total radiative forcing—with four climate sensitivities using a coupled integrated assessment model. Like previous work, we find that, within a given scenario, there is a wide range of temperature change and sea level rise depending on the realized climate sensitivity. We expand on this previous work to show that temperature-related feedbacks on the carbon cycle result in more mitigation required as climate sensitivity increases. Thus, achieving a particular radiative forcing target becomes increasingly expensive as climate sensitivity increases.