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Analysis of U.S. Water Resources under Climate Change

The MIT Integrated Global System Model (IGSM) framework, extended to include a Water Resource System (WRS) component, is applied to an integrated assessment of effects of alternative climate policy scenarios on U.S. water systems. Climate results are downscaled to yield estimates of surface runoff at 99 river basins of the continental U.S., with an exploration of climate patterns that are relatively wet and dry over the region. These estimates are combined with estimated groundwater supplies. An 11-region economic model (USREP) sets conditions driving water requirements estimated for five use sectors, with detailed sub-models employed for analysis of irrigation and electric power. The water system of the interconnected basins is operated to minimize water stress. Results suggest that, with or without climate change, U.S. average annual water stress is expected to increase over the period 2041 to 2050, primarily because of an increase in water requirements, with the largest water stresses projected in the South West. Policy to lower atmospheric greenhouse gas concentrations has a beneficial effect, reducing water stress intensity and variability in the concerned basins.

Analysis of variability and correlation in long-term economic growth rates

Quantifying the uncertainty in future climate change is an important input into policy decisions. Two important sources of uncertainty are economic growth and technological change, which in turn contribute to uncertainty in future emissions. In this paper, we focus on uncertainty in one type of technical change: productivity growth. Estimates of uncertainty in future growth must necessarily include expert judgment, since the future will not necessarily look like the past. But previous uncertainty studies have taken expert judgments based on annual national growth rates, and applied them to models with regional aggregations and multi-year time steps, and often have made crude assumptions about the correlation between regions. This paper analyzes data on the variability and covariability of historical economic productivity growth rates, and investigates the effect of spatial and temporal aggregation on variance. The results are intended to inform participants in expert elicitation exercises on future economic growth uncertainty. © 2006 Elsevier

Analysis of Visible/SWIR surface reflectance ratios for aerosol retrievals from satellite in Mexico City urban area

The surface reflectance ratio between the visible (VIS) and shortwave infrared (SWIR) radiation is an important quantity for the retrieval of the aerosol optical depth (τa) from the MODIS sensor data. Based on empirically determined VIS/SWIR ratios, MODIS τa retrieval uses the surface reflectance in the SWIR band (2.1 µm), where the interaction between solar radiation and the aerosol layer is small, to predict the visible reflectances in the blue (0.47 µm) and red (0.66 µm) bands. Therefore, accurate knowledge of the VIS/SWIR ratio is essential for achieving accurate retrieval of aerosol optical depth from MODIS. We analyzed the surface reflectance over some distinct surface covers in and around the Mexico City metropolitan area (MCMA) using MODIS radiances at 0.66 µm and 2.1 µm. The analysis was performed at 1.5 km×1.5 km spatial resolution. Also, ground-based AERONET sun-photometer data acquired in Mexico City from 2002 to 2005 were analyzed for aerosol depth and other aerosol optical properties. In addition, a network of hand-held sun-photometers deployed in Mexico City, as part of the MCMA-2006 Study during the MILAGRO Campaign, provided an unprecedented measurement of τa in 5 different sites well distributed in the city. We found that the average RED/SWIR ratio representative of the urbanized sites analyzed is 0.73±0.06 for scattering angles <140° and goes up to 0.77±0.06 for higher ones. The average ratio for non-urban sites was significantly lower (approximately 0.55). In fact, this ratio strongly depends on differences in urbanization levels (i.e. relative urban to vegetation proportions and types of surface materials). The aerosol optical depth retrieved from MODIS radiances at a spatial resolution of 1.5 km×1.5 km and averaged within 10×10 km boxes were compared with collocated 1-h τa averaged from sun-photometer measurements. The use of the new RED/SWIR ratio of 0.73 in the MODIS retrieval over Mexico City led to a significant improvement in the agreement between the MODIS and sun-photometer AOD results; with the slope, offset, and the correlation coefficient of the linear regression changing from (τaMODIS=0.91τa sun-photometer+0.33, R2=0.66) to (τaMODIS=0.96 τa sun-photometer−0.006, R2=0.87). Indeed, an underestimation of this ratio in urban areas lead to a significant overestimation of the AOD retrieved from satellite. Therefore, we strongly encourage similar analyses in other urban areas to enhance the development of a parameterization of the surface ratios accounting for urban heterogeneities.

Analysis on Energy-Water Nexus by Sankey diagram: the Case of Beijing

We visualize water utilization in Beijing from source to service and onwards to destination using Sankey diagram to analyze the energy–water nexus at the city level. First, we describe the methodology, def�nition, and data and apply the Sankey diagram approach. Beijing faces highly constrained water resources and relies heavily on water that is energy-intensive to supply (such as underground water or water that must be conveyed over long distances. We f�nd that the electricity required for water supply, treatment, utilization, and post-use utilization comprised about 5–7% of total electricity consumption in Beijing in 2009. We further f�nd that water used in the energy-related sub-sectors accounted for about one-fourth of the water used in the whole industrial sector and about of 3% of the total fresh water used in Beijing in 2009. Among the energy related sub-sectors, the electricity sub-sector was found to be the largest contributor.

© 2013 Balaban Desalination Publications

Analyzing Methane-Emitting Activities: Longitudinal Data, Emissions Coefficients, and Spatial Distributions

We assemble a longitudinal data set for analyzing methane-emitting activities within the MIT Integrated Global System Model (IGSM). It is an earth system model of intermediate complexity that, for forward simulations, is driven by anthropogenic emissions as projected by the Emissions Prediction and Policy Analysis (EPPA) model. We develop initial estimates of emissions coefficients for each of the main methane-emitting activities along with corresponding uncertainty estimates to be utilized as "priors" in inverse calculations. In addition, baseline maps for the spatial distribution of methane emissions by individual activities are coded to EPPA regions for later use with emissions coefficient estimates produced by these inverse calculations.

Analyzing the Regional Impact of a Fossil Energy Cap in China

Decoupling fossil energy demand from economic growth is crucial to China’s sustainable development. In addition to energy and carbon intensity targets enacted under the Twelfth Five-Year Plan (2011–2015), a coal or fossil energy cap is under discussion as a way to constrain the absolute quantity of energy used. Importantly, implementation of such a cap may be compatible with existing policies and institutions. We evaluate the efficiency and distributional implications of alternative energy cap designs using a numerical general equilibrium model of China’s economy, built on the 2007 regional input-output tables for China and the Global Trade Analysis Project global data set. We find that a national cap on fossil energy implemented through a tax on final energy products and an energy saving allowance trading market is the most costeffective design, while a regional coal-only cap is the least cost-effective design. We further find that a regional coal cap results in large welfare losses in some provinces. Capping fossil energy use at the national level is found to be nearly as cost effective as a national CO2 emissions target that penalizes energy use based on carbon content.

Annex I Differentiation Proposals: Implications for Welfare, Equity and Policy

Drawing upon a variety of different criteria, many nations have introduced proposals to differentiate the reductions in carbon emissions that would be required of industrialized nations in the short to medium term. This paper considers the relationship of these proposals to their underlying conceptions of equity, and to the self-interest of the nations proposing them. The MIT Emissions Prediction and Policy Assessment (EPPA) model is used to analyze the welfare implications of several prominent proposals, considering both cases where nations must carry out all emissions reductions domestically, and situations where trading in emissions permits is allowed. The consequences of applying two prominent differentiation measures to a global regime using a zero-based allocation of emissions rights is also explored. One conclusion is that a trading regime can yield important benefits in reducing potential conflict within developed nations, and help avoid complicated and divisive negotiations over burden-sharing formulas.

Antarctic ice sheet fertilises the Southern Ocean

Southern Ocean (SO) marine primary productivity (PP) is strongly influenced by the availability of iron in surface waters, which is thought to exert a significant control upon atmospheric CO2 concentrations on glacial/interglacial timescales. The zone bordering the Antarctic Ice Sheet exhibits high PP and seasonal plankton blooms in response to light and variations in iron availability. The sources of iron stimulating elevated SO PP are in debate. Established contributors include dust, coastal sediments/upwelling, icebergs and sea ice. Subglacial meltwater exported at the ice margin is a more recent suggestion, arising from intense iron cycling beneath the ice sheet. Icebergs and subglacial meltwater may supply a large amount of bioavailable iron to the SO, estimated in this study at 0.07–0.2 Tg yr−1. Here we apply the MIT global ocean model (Follows et al., 2007) to determine the potential impact of this level of iron export from the ice sheet upon SO PP. The export of iron from the ice sheet raises modelled SO PP by up to 40%, and provides one plausible explanation for seasonally very high in situ measurements of PP in the near-coastal zone. The impact on SO PP is greatest in coastal regions, which are also areas of high measured marine PP. These results suggest that the export of Antarctic runoff and icebergs may have an important impact on SO PP and should be included in future biogeochemical modelling.

© 2014 the authors.

Application of Probabilistic Collocation Method for Uncertainty Analysis of a Simple Ocean Model

This paper presents the probabilistic collocation method as a computationally efficient method for performing uncertainty analysis on large complex models such as those used in global climate change research. The collocation method is explained, and then the results of its application to a box model of ocean thermohaline circulation are presented. A comparison of the results of the collocation method with a traditional Monte Carlo simulation show that the collocation method gives a better approximation for the probability density function of the model's response with less than 20 model runs as compared with a Monte Carlo simulation of 5000 model runs.

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