The Impact of Water Scarcity on Food, Bioenergy and Deforestation

We evaluate the impact of explicitly representing irrigated land and water scarcity in an economy-wide model on food prices, bioenergy production and deforestation both with and without a global carbon policy. The analysis develops supply functions of irrigable land from a water resource model resolved at 282 river basins and applies them within a global economy-wide model of energy and food production, land-use change and greenhouse gas emissions. The irrigable land supply curves are built on basin-level estimates of water availability, and the costs of improving irrigation efficiency and increasing water storage, and include other water requirements within each basin. The analysis reveals two key findings. First, explicitly representing irrigated land at has a small impact on food, bioenergy and deforestation outcomes. This is because this modification allows more flexibility in the expansion of crop land (i.e. irrigated and rainfed land can expand in different proportions) relative to when a single type of crop land is represented, which counters the effect of rising marginal costs for the expansion of irrigated land. Second, due to endogenous irrigation and storage responses, changes in water availability have small impacts on food prices, bioenergy production, land-use change and the overall economy, even with large scale (~150 exajoules) bioenergy production.Primary funding for this research was through a sponsored research agreement with BP. The authors also acknowledge support in the basic development of the Economic Projection and Policy Analysis model from the Joint Program on the Science and Policy of Global Change, which is funded by a consortium of industrial sponsors and Federal grants including core funding in support of basic research under U.S. Environmental Protection Agency (EPA‑XA‑83600001) and U.S. Department of Energy, Office of Science (DE‑FG02‑94ER61937). For a complete list of sponsors see for complete list see http://globalchange.mit.edu/sponsors/current.html)

A Framework for Analysis of the Uncertainty of Socioeconomic Growth and Climate Change on the Risk of Water Stress: a Case Study in Asia

The sustainability of future water resources is of paramount importance and is affected by many factors, including population, wealth and climate. Inherent in how these factors change in the future is the uncertainty of their prediction. In this study, we integrate a large ensemble of scenarios—internally consistent across economics, emissions, climate, and population—to develop a risk portfolio of water stress over a large portion of Asia that includes China, India, and Mainland Southeast Asia. We isolate the effects of socioeconomic growth from the effects of climate change in order to identify the primary drivers of stress on water resources. We find that water needs related to socioeconomic changes, which are currently small, are likely to increase considerably in the future, often overshadowing the effect of climate change on levels of water stress. As a result, there is a high risk of severe water stress in densely populated watersheds by 2050, compared to recent history. If socio-economic growth is unconstrained by global actions to limit greenhouse gas concentrations, water-stressed populations may increase from about 800 million to 1.7 billion in this region.The Joint Program on the Science and Policy of Global Change is funded by a consortium of industrial and foundation sponsors. For the complete list see http://globalchange.mit.edu/sponsors/all

Probabilistic projections of the future climate for the world and the continental USA

In this paper, we study possible impacts of anthropogenic greenhouse gas (GHG) emissions on the 21st century climate on the continental USA using the MIT Integrated Global System Model (IGSM) framework. Climate change simulations use an emissions scenario developed with the IGSM’s Economic Projection and Policy Analysis (EPPA) Model. The scenario represents a global emission path consistent with the current view on the trajectories of technological and economic development. The estimates of possible changes in climate are based on an ensemble of 400 simulations with the IGSM’s MIT Earth System Model (MESM), a model of intermediate complexity. Regional changes over the USA were obtained using statistical downscaling that incorporates results from the simulations with the CMIP5 Atmosphere-Ocean General Circulation Models (AOGCMs). The results show that under the considered emissions scenario, surface air temperature averaged over the continental USA increases by 2.6 to 4.4K by the last decade of the 21st century (90% probability interval) relative to pre-industrial temperatures, compare to 2.3 to 3.4K for the whole globe. Corresponding changes in precipitation are -0.65 to 0.34 mm/day and 0.13 to 0.22 mm/day, respectively. There is significant variation in the geographical distribution of those changes among the ensemble simulations.This work was supported by the U.S. Department of Energy under grant #DE-FG02-94ER61937 and other government, industry and foundation sponsors of the MIT Joint Program on the Science and Policy of Global Change. For a complete list of sponsors and U.S. government funding sources, see http://globalchange.mit.edu/sponsors

The Future of Coal in China

As the world’s largest consumer of total primary energy and energy from coal, and the largest emitter of carbon dioxide (CO2), China is now taking an active role in controlling CO2 emissions. Given current coal use in China, and the urgent need to cut emissions, ‘clean coal’ technologies are regarded as a promising solution for China to meet its carbon reduction targets while still obtaining a considerable share of energy from coal. Using an economy-wide model, this paper evaluates the impact of two existing advanced coal technologies—coal upgrading and ultra-supercritical (USC) coal power generation—on economic, energy and emissions outcomes when a carbon price is used to meet China’s CO2 intensity target out to 2035. Additional deployment of USC coal power generation lowers the carbon price required to meet the CO2 intensity target by more than 40% in the near term and by 25% in the longer term. It also increases total coal power generation and coal use. Increasing the share of coal that is upgraded leads to only a small decrease in the carbon price. As China’s CO2 intensity is set exogenously, additional deployment of the two technologies has a small impact on total CO2 emissions.The authors thank John Reilly for helpful comments and suggestions, and gratefully acknowledge the financial support for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial sponsors and Federal grants. For a complete list of sponsors see http://globalchange.mit.edu/sponsors

CLM-AG: An Agriculture Module for the Community Land Model version 3.5

It is estimated that 40% of all crops grown in the world today are grown using irrigation. As a consequence, shifting precipitation patterns due to climate change are viewed as a major threat to food security. This report presents the Community Land Model-Agriculture module (CLM-AG), which models crop growth and water stress. The CLM-AG model is a global generic crop model built in the framework of the Community Land Model version 3.5. This report describes the structure and main routines of the model. Two different evaluations of the model are then considered. First, at a global level, CLM-AG is run under a historic climatology and compared to the Global Agro-Ecological Zones, an existing model of irrigation need. Second, the irrigation need computed for the United States is compared to survey data from the United States Department of Agriculture. For both evaluations, CLM-AG results are comparable to either the model results or the surveyed data.Development of the IGSM applied in this research was supported by the U.S. Department of Energy, Office of Science (DE-FG02-94ER61937); the U.S. Environmental Protection Agency, EPRI, and other U.S. government agencies and a consortium of 40 industrial and foundation sponsors. For a complete list see http://globalchange.mit.edu/sponsors/current.htm

Costs of Climate Mitigation Policies

The wide range of cost estimates for stabilizing climate is puzzling to policy makers as well as researchers. Assumptions about technology costs have been studied extensively as one reason for these differences. Here, we focus on how policy timing and the modeling of economy-wide interactions affect costs. We examine these issues by restructuring a general equilibrium model of the global economy, removing elements of the model one by one. We find that delaying the start of a global policy by 20 years triples the needed starting carbon price and increases the macroeconomic cost by nearly 30%. We further find that including realistic details of the economy (e.g. sectoral and electricity technology detail; tax and trade distortions; capital vintaging) more than double net present discounted costs over the century. Inter-model comparisons of stabilization costs find a similar range, but it is not possible to isolate the structural causes behind cost differences. Broader comparisons of stabilization costs face the additional issue that studies of different vintages assume different policy starting dates, often dates that are no longer realistic given the pace of climate change negotiations. This study can aid in interpretation of estimates and give policymakers and researchers an idea of how to adjust costs upwards as the start of policy is delayed. It also illustrates that models that greatly simplify the realities of modern economies likely underestimate costs.We gratefully acknowledge the financial support for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial and foundation sponsors and Federal awards, including the U.S. Department of Energy, Office of Science under DE-FG02-94ER61937 and the U.S. Environmental Protection Agency under XA-83600001-1. For a complete list of sponsors and the U.S. government funding sources, please visit http://globalchange.mit.edu/sponsors/all

Transparency in the Paris Agreement

Establishing a credible and effective transparency system will be both crucial and challenging for the climate regime based on the pledge and review process established in the Paris Agreement. The Agreement provides for review of achievements under national pledges (Nationally Determined Contributions, or NDCs), but much of this information will become available only well after key steps in the launch of this latest attempt to control human influence on the climate. Still, in these early years, information and understanding of individual and collective performance, and of relative national burdens under the NDCs, will play an important role in the success or failure of the Agreement. However, because of the phasing of various steps in the 5-year cycles under the Agreement and the unavoidable delays of two or more years to produce and review government reports, the Climate Convention and other intergovernmental institutions are ill-suited to carry out timely analyses of progress. Consequently, in advance of formal procedures, academic and other non-governmental groups are going to provide analyses based on available data and their own methodologies. We explore this transparency challenge, using the MIT Economic Projection and Policy Analysis (EPPA) model, to construct sample analyses, and consider ways that efforts outside official channels can make an effective contribution to the success of the Agreement.We gratefully acknowledge the financial support for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial and foundation sponsors and Federal awards, including the U.S. Department of Energy, Office of Science under DE-FG02-94ER61937 and the U.S. Environmental Protection Agency under XA-83600001-1. For a complete list of sponsors and the U.S. government funding sources, please visit http://globalchange.mit.edu/sponsors/all

Economic Projection with Non-homothetic Preferences: The Performance and Application of a CDE Demand System

In computable general equilibrium modeling, whether the simulation results are consistent to a set of valid own-price and income demand elasticities that are observed empirically remains a key challenge in many modeling exercises. To address this issue, the Constant Difference of Elasticities (CDE) demand system has been adopted by some models since the 1990s. However, perhaps due to complexities of the system, the applications of CDE systems in other models are less common. Furthermore, how well the system can represent the given elasticities is rarely discussed or examined in existing literature. The study aims at bridging these gaps by revisiting calibration details of the system, exploring conditions where the calibrated elasticities of the system can better match a set of valid target elasticities, and presenting strategies to incorporate the system into GTAP8inGAMS—a global computable general equilibrium model written in GAMS and MPSGE modeling languages. It finds that the calibrated elasticities can be matched to the target ones more precisely if the corresponding sectorial expenditure shares are lower, target own-price demand elasticities are lower, and target income demand elasticities are higher. It also verifies that for the GTAP8inGAMS with a CDE system, the model responses can successfully replicate the calibrated elasticities under various price and income shocks.The author gratefully acknowledges the financial support for this work provided by the MIT Joint Program on the Science and Policy of Global Change through a consortium of industrial and foundation sponsors and Federal awards, including the U.S. Department of Energy, Office of Science under DEFG02-94ER61937 and the U.S. Environmental Protection Agency under XA83600001-1. For a complete list of sponsors and the U.S. government funding sources, please visit http://globalchange.mit.edu/sponsors/all

Impact of Canopy Representations on Regional Modeling of Evapotranspiration using the WRF-ACASA Coupled Model

In this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model, to investigate the impact of canopy representation on regional evapotranspiration. The WRF-ACASA model uses a multilayer structure to represent the canopy, consequently allowing microenvironmental variables such as leaf area index (LAI), air and canopy temperature, wind speed and humidity to vary both horizontally and vertically. The improvement in canopy representation and canopy-atmosphere interaction allow for more realistic simulation of evapotranspiration on both regional and local scales. Accurate estimates of evapotranspiration (both potential and actual) are especially important for regions with limited water availability and high water demand, such as California. Water availability has been and will continue to be the most important issue facing California for years and perhaps decades to come. Terrestrial evapotranspiration is influenced by many processes and interactions in the atmosphere and the bio-sphere such as water, carbon, and momentum exchanges. The need to improve representation within of surface-atmosphere interactions remains an urgent priority within the modeling community.This work is supported in part by the National Science Foundation under Awards No.ATM-0619139 and EF-1137306. The Joint Program on the Science and Policy of Global Change is funded by a number of federal agencies and a consortium of 40 industrial and foundation sponsors. (For the complete list see http://globalchange.mit.edu/sponsors/current.html)

Estimating the potential of U.S. urban infrastructure albedo enhancement as climate mitigation in the face of climate variability

The climate mitigation potential of U.S. urban infrastructure albedo enhancement is explored using multidecadal regional climate simulations. Increasing albedo from 0.2 to 0.4 results in summer daytime surface temperature decreases of 1.5°C, substantial reductions in health-related heat (50% decrease in days with danger heat advisory) and decreases in energy demand for air conditioning (15% decrease in cooling degree days) over the U.S. urban areas. No significant impact is found outside urban areas. Most regional modeling studies rely on short simulations; here, we use multidecadal simulations to extract the forced signal from the noise of climate variability. Achieving a ±0.5°C margin of error for the projected impacts of urban albedo enhancement at a 95% confidence level entails using at least 5 simulation years. Finally, single-year higher-resolution simulations, requiring the same computing power as the multidecadal coarser-resolution simulations, add little value other than confirming the overall magnitude of our estimates.This work was supported by the Concrete Sustainability Hub at MIT, with sponsorship provided by the Portland Cement Association and the RMC Research & Education Foundation, and by the US Department of Energy, Office of Biological and Environmental Research, under grant DE-FG02-94ER61937. The MIT Joint Program on the Science and Policy of Global Change is funded by a number of federal agencies and a consortium of 40 industrial and foundation sponsors. For a complete list of sponsors, see http://globalchange.mit.edu