Water availability is a growing concern globally (UN, 2012). Many countries are affected by water scarcity and quality issues (Postel, 2000). The United States (U.S.) is no exception, with the Colorado and the Rio Grande rivers so severely exploited that they often do not reach the oceans. The exploitation of U.S. water resources is the consequence of growing population and economic activity, and lack of conservation measures. Under the threat of climate change and consequently a change in water resources, water issues are even more pressing. To investigate the issue of water allocation and scarcity for the U.S., we use a computable general equilibrium (CGE) model to drive water requirements in an integrated assessment framework. Specifically, we apply a specially tailored version of the Integrated Global System Model – Water Resource System (IGSM-WRS) model (Strzepek et al., 2012), which draws on the water system module (WSM) developed by the International Food Policy Research Institute (Rosegrant et al. 2008). WRS allows the linkage of WSM with the IGSM (Sokolov et al. 2005). This integrated assessment framework facilitates evaluation of both the direct (via a geophysical model) and indirect (thanks to a CGE model) impacts of climate policy on water scarcity. Taking advantage of data available for the U.S., we model water at a 99-basin level (instead of the 14 regions in the global WRS model). Detailed economic inputs are supplied by the 11-region U.S. Regional Economic Policy (USREP) model (Rausch et al. 2009). This CGE model also provides detailed energy demand which allows a better estimation of water requirements for mining and thermoelectric power generation.

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45oN and polewards) for the period 1900–2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.

© 2012 The Authors

We examine the sensitivity of the biogeography of nitrogen fixers to a warming climate and increased aeolian iron deposition in the context of a global earth system model. We employ concepts from the resource-ratio theory to provide a simplifying and transparent interpretation of the results. First we demonstrate that a set of clearly defined, easily diagnosed provinces are consistent with the theory. Using this framework we show that the regions most vulnerable to province shifts and changes in diazotroph biogeography are the equatorial and South Pacific, and central Atlantic. Warmer and dustier climates favor diazotrophs due to an increase in the ratio of supply rate of iron to fixed nitrogen. We suggest that the emergent provinces could be a standard diagnostic for global change models, allowing for rapid and transparent interpretation and comparison of model predictions and the underlying mechanisms. The analysis suggests that monitoring of real world province boundaries, indicated by transitions in surface nutrient concentrations, would provide a clear and easily interpreted indicator of ongoing global change.

© 2014 the authors.

Historically, electricity consumption has been largely insensitive to short term spot market conditions, requiring the equating of supply and demand to occur almost exclusively through changes in production. Large scale entry of demand response, however, is rapidly changing this paradigm in the electricity market located in the mid-Atlantic region of the US, called PJM. Greater demand side participation in electricity markets is often considered a low cost alternative to generation and an important step towards decreasing the price volatility driven by inelastic demand. Recent experience in PJM, however, indicates that demand response in the form of a peaking product has the potential to increase energy price level and volatility.

Currently, emergency demand response comprises the vast majority of demand side participation in PJM. This is a peaking product dispatched infrequently and only during periods of scarcity when thermal capacity is exhausted. While emergency demand response serves as a cheaper form of peaking resource than gas turbines, it has recently contributed to increases in energy price volatility by setting price at the $1,800/MWh price cap, substantially higher than the marginal cost of most thermal generation. Additionally, the entry of demand response into the PJM capacity market is one of primary drivers for capacity prices declining by over fifty percent. This study investigates the large penetration of emergency demand response in PJM and the implications for the balance between energy and capacity prices and energy price volatility. A novel model is developed that dynamically simulates generation entry and exit over a long term horizon based on endogenously determined energy and capacity prices. The study finds that, while demand response leads to slight reductions in total generation cost, it shifts the bulk of capacity market revenues into the energy market and also vastly increases energy price volatility.

This transition towards an energy only market will send more accurate price signals to consumers as costs are moved out of the crudely assessed capacity charge and into the dynamic energy price. However, the greater volatility will also increase the risk faced by many market participants. The new market paradigm created by demand response will require regulators to balance the importance of sending accurate price signals to consumers against creating market conditions that decrease risk and foster investment.