Search

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.

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.

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.

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 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.

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.

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.

Current ozone (O3) concentration levels entail significant damages in crop yields around the world. The reaction of the emitted precursors (mostly methane and nitrogen oxides) with solar radiation contribute to O3 levels that exceed established thresholds for crop damage. This paper shows current and projected (up to 2080) relative yield losses (RYLs) driven by O3 exposure for different crops and the associated economic damages applying dynamic crop production and prices that are calculated per region and period. We adjust future crop yields in the Global Change Assessment Model (GCAM) to reflect the RYLs and analyze the effects on agricultural markets. We find that the changes (generally reductions) in O3 precursor emissions in a reference scenario would reduce the agricultural damages, compared to present, for most of the regions, with a few exceptions including India, where higher future O3 concentrations have large negative impacts on crop yields. The annual economic impact of O3 driven losses from 2010 to 2080 are, in billion US dollars at 2015 prices ($B), 5.0 6.0, 9.8 18.8, 6.7 10.6 and 10.4 12.5 for corn, soybeans, rice and wheat, respectively, with the large losses for wheat and soybeans driven by their comparatively high responses to O3. When O3 effects are explicitly modelled as exogenous yield shocks in future periods, there is a direct impact in future agricultural markets. Therefore, the aggregated net present value (NPV) of crop production would be reduced around by $90.8 B at a global level. However, these changes are not distributed evenly across regions, and the net present market value of the crops would increase by up to $118.2 B (India) or decrease by up to $59.2 B (China). © 2020 Elsevier Ltd This research is supported by Basque Government through the BERC 2018–2021 and the Spanish Government through María de Maeztu excellence accreditation MDM-2017-0714. This research is also supported in part by US Environmental Protection Agency , under Interagency Agreement DW08992459801 . Jon Sampedro, Dirk-Jan van de Ven and Iñaki Arto acknowledge financial support from the Ministry of Economy, Industry and Competitiveness of Spain ( RTI2018-099858-A-100 and RTI2018-093352-B-I00 ). Jon Sampedro acknowledge financial support from the Basque Government ( PRE_2017_2_0139 ). Iñaki Arto acknowledge financial support from the European Union's Horizon 2020 research and innovation program under grant agreement no. 821105 ( LOCOMOTION project). Agustin del Prado is financed by the programme Ramon y Cajal from the Spanish Ministry of Economy, Industry and Competitiveness ( RYC-2017-22143 )