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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.

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.

Understanding and projecting income distributions within countries and regions is important to understanding consumption trends and the distributional consequences of climate impacts and responses. Several global, country-level projections of income distribution are available but most project only the Gini coefficient (a summary statistic of the distribution) or utilize the Gini along with the assumption of a lognormal distribution. We test the lognormal assumption and find that it typically underestimates income in the highest deciles and over-estimates it in others. We find that a new model based on two principal components of national time series data for income distribution provides a better fit to the data for all deciles, especially for the highest and lowest. We also construct a projection model in which the first principal component is driven by the Gini coefficient and the second captures deviations from this relationship. We use the model to project income distribution by decile for all countries for the five shared socioeconomic pathways. We find that inequality is consistently higher than projections based on the Gini and the lognormal functional form, with some countries reaching ratios of the highest to lowest income deciles that are almost three times their value using the lognormal assumption.

Income and its distribution profile are important determinants of residential energy demand and carry direct implications for human well-being and climate. We explore the sensitivity of residential energy systems to income growth and distribution across shared socioeconomic pathway-representative concentration pathways scenarios using a global, integrated, multisector dynamics model, Global Change Analysis Model, which tracks national/regional household energy services and fuel choice by income decile. Nation/region energy use patterns across deciles tend to converge over time with aggregate income growth, as higher-income consumers approach satiation levels in floorspace and energy services. However, in some regions, existing within-region inequalities in energy consumption persist over time due to slow income growth in lower income groups. Due to continued differences in fuel types, lower income groups will have higher exposure to household air pollution, despite lower contributions to greenhouse gas emissions. We also find that the share of income dedicated to energy is higher for lower deciles, with strong regional differences.

Income distributions are a growing area of interest in the examination of equity impacts brought on by climate change and its responses. Such impacts are especially important at subnational levels, but projections of income distributions at these levels are scarce. Here, we project U.S. state-level income distributions for the Shared Socioeconomic Pathways (SSPs). We apply a non-parametric approach, specifically a recently developed principal components algorithm to generate net income distributions for deciles across 50 U.S. states and the District of Columbia. We produce these projections to 2100 for three SSP scenarios in combination with varying projections of GDP per capita to represent a wide range of possible futures and uncertainties. In the generation of these scenarios, we also generated tax adjusted historical deciles by U.S. states, which we used for validating model performance. Our method thus produces income distributions by decile for each state, reflecting the variability in state income, population, and tax regimes. Our net income projections by decile can be used in both emissions- and impact-related research to understand distributional effects at various income levels and identify economically vulnerable populations.

Most studies assessing climate impacts on agriculture have focused on average changes in market-mediated responses (e.g. changes in land use, production, and consumption). However, the response of global agricultural markets to interannual variability (IAV) in climate and biophysical shocks is poorly understood and not well represented in global economic models. Here we show a strong transmission of IAVs in climate-induced biophysical yield shocks to agriculture markets, which is further magnified by endogenous market fluctuations generated due to producers’ imperfect expectations of market and weather conditions. We demonstrate that the volatility of crop prices and consumption could be significantly underestimated (i.e. on average by 55% and 41%, respectively) by assuming perfect foresight, a standard assumption in the economic equilibrium modeling, compared with the relatively more realistic adaptive expectations. We also find heterogeneity in IAV across crops and regions, which is considerably mediated by international trade. Studying IAV provides fundamentally new insights on measuring and understanding climate impacts on global agriculture, and our framework lays the foundation for further investigating the full range of climate impacts on biophysical and human systems.

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.

Issue Title: A Multi-Model Framework to Achieve Consistent Evaluation of Climate Change Impacts in the United States

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.

Issue Title: Climatic Change Letters | Edited by Michael Oppenheimer | pages 615-641 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.[PUBLICATION ABSTRACT]