153 research outputs found

    Benefits of greenhouse gas mitigation on the supply, management, and use of water resources in the United States

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    Climate change impacts on water resources in the United States are likely to be far-reaching and substantial because the water is integral to climate, and the water sector spans many parts of the economy. This paper estimates impacts and damages from five water resource-related models addressing runoff, drought risk, economics of water supply/demand, water stress, and flooding damages. The models differ in the water system assessed, spatial scale, and unit of assessment, but together provide a quantitative and descriptive richness in characterizing water sector effects that no single model can capture. The results, driven by a consistent set of greenhouse gas (GHG) emission and climate scenarios, examine uncertainty from emissions, climate sensitivity, and climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, broad conclusions can be drawn regarding patterns of change and benefits of GHG mitigation. Four key findings emerge: 1) GHG mitigation substantially reduces hydro-climatic impacts on the water sector; 2) GHG mitigation provides substantial national economic benefits in water resources related sectors; 3) the models show a strong signal of wetting for the Eastern US and a strong signal of drying in the Southwest; and 4) unmanaged hydrologic systems impacts show strong correlation with the change in magnitude and direction of precipitation and temperature from climate models, but managed water resource systems and regional economic systems show lower correlation with changes in climate variables due to non-linearities created by water infrastructure and the socio-economic changes in non-climate driven water demand

    The Impact of Water Scarcity on Food, Bioenergy and Deforestation

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    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)

    The Future Water Risks Under Global Change in Southern and Eastern Asia: Implications of Mitigation

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    Understanding and predicting the future vulnerability of freshwater resources is a major challenge with important societal implications. Many studies have identified Asia as a hotspot of severe water stress in the coming decades, and also highlighted the large uncertainty associated with water resource assessment based on limited multi-model projections. Here we provide a more comprehensive risk-based assessment of water use and availability in response to future climate change, socioeconomic growth, and their combination in Southern and Eastern Asia. We employ a large ensemble of scenarios that capture the spectrum of regional climate response as well as a range of economic projections and climate policies in a consistent, integrated modeling framework. We show that economic growth increases water stress ubiquitously. The climate-only and combined climate-growth effects on water stress remain largely negative in China and Indus Basin, but largely positive in India, Indochina, and Ganges Basin. However, climate poses substantially large uncertainty in water stress changes than socioeconomic growth. By 2050, socioeconomic growth alone can lead to an additional 650 million people living under at least “heavy” water stress, with most of these located in India, Indus Basin, and China. The combined effects of socioeconomic growth and climate change reduce people under water stress to an additional 200 million, attributed mainly to the beneficial climate in India that moves its heavily-stressed condition into the slightly or moderately‑stressed conditions. These 200 million people primarily reside in Indus Basin and China under at least overly exploited water conditions— where total water requirements will consistently exceed surface water supply. Climate mitigation helps alleviating the risks of increasing water scarcity by midcentury, but to a limited extent. Therefore, adaptive measures need to be taken to meet these surface water shortfalls, or a combination of both approaches may be most effective.This work was supported by the Department of Energy under An Integrated Framework for Climate Change Assessment (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

    Water Body Temperature Model for Assessing Climate Change Impacts on Thermal Cooling

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    We develop and test a physically based semi-Lagrangian water body temperature model to apply climatological data and thermal pollution from river-based power plants to historical river flow data in order to better understand climate change impacts on surface water temperature and thermal power plant withdrawal allowances. The model is built for rapid assessment and use in Integrated Assessment Models. We first test the standalone model on a 190km river reach, the Delaware River, where we have detailed flow and temperature data. An R2 of 0.88 is obtained on hourly data for this initial test. Next, we integrate the standalone temperature model into a series of models—rainfall-runoff model, water demand model, water resource management model, and power plant uptake and release model—for the contiguous USA (CONUS), with about 19,000 segments total. With this system in place, we then validate the standalone water temperature model within the system for 16 river stations throughout the CONUS, where we have measured daily temperature data. The model performs reasonably well with a median R2 of 0.88. A variety of climate and emissions scenarios are then applied to the model to test regions of higher vulnerability to river temperature environmental violations, making use of output from two GCMs and six emissions scenarios focusing on projections out to 2050. We find that the two GCMs project significantly different impacts to water temperature, driven largely by the resulting changes in streamflow from the two models. We also find significantly different impacts on the withdrawal allowed by thermal power plants due to environmental regulations. Potential impacts on generation are between +3% and -4% by 2050 for the unconstrained emissions case and +3.5% to -2% for the stringent GHG mitigation policy (where 1% is equivalent to 32 TWh, or about 3 billion USD/year using 2005 electricity prices). We also find that once-through cooling plants are most vulnerable to climate change impacts, with summer impacts ranging from -0.8% to -6% for the unconstrained emissions case and +2.1% to -3.7% for the stringent GHG emissions case

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

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    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

    Quantifying the Likelihood of Regional Cimate Change: A hybridized Approach

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    The growing need for risk-based assessments of impacts and adaptation to climate change calls for increased capability in climate projections: the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Herein, we present a technique that extends the latitudinal projections of the 2-D atmospheric model of the MIT Integrated Global System Model (IGSM) by applying longitudinally resolved patterns from observations, and from climate-model projections archived from exercises carried out for the 4th Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The method maps the IGSM zonal means across longitude using a set of transformation coefficients, and we demonstrate this approach in application to near-surface air temperature and precipitation, for which high-quality observational datasets and model simulations of climate change are available. The current climatology of the transformation coefficients is observationally based. To estimate how these coefficients may alter with climate, we characterize the climate models’ spatial responses, relative to their zonal mean, from transient increases in trace-gas concentrations and then normalize these responses against their corresponding transient global temperature responses. This procedure allows for the construction of meta-ensembles of regional climate outcomes, combining the ensembles of the MIT IGSM—which produce global and latitudinal climate projections, with uncertainty, under different global climate policy scenarios—with regionally resolved patterns from the archived IPCC climate-model projections. This approach also provides a hybridization of the climate-model longitudinal projections with the global and latitudinal patterns projected by the IGSM, and can be applied to any given state or flux variable that has the sufficient observational and model-based information.U.S. Department of Energy’s Abrupt Climate Change program, grant # DE-FG02-08ER64597

    Competition for water for the food system

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    Although the global agricultural system will need to provide more food for a growing and wealthier population in decades to come, increasing demands for water and potential impacts of climate change pose threats to food systems. We review the primary threats to agricultural water availability, and model the potential effects of increases in municipal and industrial (M&I) water demands, environmental flow requirements (EFRs) and changing water supplies given climate change. Our models show that, together, these factors cause an 18 per cent reduction in the availability of worldwide water for agriculture by 2050. Meeting EFRs, which can necessitate more than 50 per cent of the mean annual run-off in a basin depending on its hydrograph, presents the single biggest threat to agricultural water availability. Next are increases in M&I demands, which are projected to increase upwards of 200 per cent by 2050 in developing countries with rapidly increasing populations and incomes. Climate change will affect the spatial and temporal distribution of run-off, and thus affect availability from the supply side. The combined effect of these factors can be dramatic in particular hotspots, which include northern Africa, India, China, parts of Europe, the western US and eastern Australia, among others

    CliCrop: a Crop Water-Stress and Irrigation Demand Model for an Integrated Global Assessment Model Approach

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    http://globalchange.mit.edu/research/publications/2264This paper describes the use of the CliCrop model in the context of climate change general assessment modeling. The MIT Integrated Global System Model (IGSM) framework is a global integrated assessment modeling framework that uses emission predictions and economic outputs from the MIT Emission Prediction and Policy Analysis (EPPA) model and earth system modeling predictions from the IGSM to drive a land system component, a crop model (CliCrop) and a Water Resource System (WRS) model. The global Agriculture and Water System are dependant upon and interlinked with the global climate system. As irrigated agriculture provides 60% of grains and 40% of all crop production on 20% of global crop lands and accounts for 80% of global water consumption, it is crucial that the agricultural-water linkage be properly modeled. Crop models are used to predict future yields, irrigation demand and to understand the effect of crop and soil type on food productivity and soil fertility. In the context of an integrated global assessment, a crop water-stress and irrigation demand model must meet certain specifications that are different for other crop models; it needs to be global, fast and generic with a minimal set of inputs. This paper describes how CliCrop models the physical and biological processes of crop growth and yield production and its use within the MIT Integrated Global System Model (IGSM) framework, including the data inputs. This paper discusses the global data bases used as input to CliCrop and provides a comparison of the accuracy of CliCrop with the detailed biological-based crop model DSSAT as well as with measured crop yields over the U.S. at the country level using reanalyzed weather data. In both cases CliCrop performed well and the analysis validated its use for climate change impact assessment. We then show why correctly modeling the soil is important for irrigation demand calculation, especially in temperate areas. Finally, we discuss a method to estimate actual water withdrawal from modeled physical crop requirements using U.S. historical data.The initial funding for CliCrop was provided by USAID under a program on climate change adaptation in Niger. Further funding was provided by UN University World Institute for Development Economics Research for the Application and Development of CliCrop in Africa, the authors would like to particularly thank Prof. Finn Tarp, Prof. Channing Arndt and Dr. James Thurlow for their support. The authors also would like to thank Dr. Jawoo Koo of IFPRI for his review and contributions to the software development. The authors also gratefully acknowledge additional 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. 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

    Graphite crystallizer and its surface quality as a factor affecting the copper continuous casting process

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    Pure copper is one of the best conducting metals among known materials, making it the first choice for wires and microwires. However, before subjecting to metal working, the material is being manufactured in the continuous casting lines. The experimental study conducted in laboratory conditions proved that the external surface quality, and thus the contact quality with the cooling system is being responsible for the worsening or improving of the heat transfer and therefore the temperature of the crystallizer itself. The conducted study might function as sort of a guideline for the industrial process

    Graphite crystallizer and its surface quality as a factor affecting the copper continuous casting process

    Get PDF
    Pure copper is one of the best conducting metals among known materials, making it the first choice for wires and microwires. However, before subjecting to metal working, the material is being manufactured in the continuous casting lines. The experimental study conducted in laboratory conditions proved that the external surface quality, and thus the contact quality with the cooling system is being responsible for the worsening or improving of the heat transfer and therefore the temperature of the crystallizer itself. The conducted study might function as sort of a guideline for the industrial process
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