A national-scale simulation-optimization model was created to generate estimates of economic impacts associated with changes in water supply and demand as influenced by climate change. Water balances were modeled for the 99 assessment sub-regions, and are presented for 18 water resource regions in the United States. Benefit functions are developed for irrigated agriculture, municipal and domestic water use, commercial and industrial water use, and hydroelectric power generation. Environmental flows below minimal levels required for environmental needs are assessed a penalty. As a demonstration of concept for the model, future climate is projected using a climate model ensemble for two greenhouse gas (GHG) emissions scenarios: a business-as-usual (BAU) scenario in which no new GHG controls are implemented, and an exemplary mitigation policy (POL) scenario in which future GHG emissions are mitigated. Damages are projected to grow less during the 21st century under the POL scenario than the BAU scenario. The largest impacts from climate change are projected to be on non-consumptive uses (e.g., environmental flows and hydropower) and relatively lower-valued consumptive uses (e.g., agriculture), as water is reallocated during reduced water availability conditions to supply domestic, commercial, and industrial uses with higher marginal values. Lower GHG concentrations associated with a mitigation policy will result in a smaller rise in temperature and thus less extensive damage to some water resource uses. However, hydropower, environmental flow penalty, and agriculture were shown to be sensitive to the change in runoff as well.

© 2013 the authors

Decoupling fossil energy demand from economic growth is crucial for China's sustainable development, especially for addressing severe local air pollution and global climate change. An absolute cap on coal or fossil fuel consumption has been proposed as a means to support the country's energy and climate policy objectives. We evaluate potential energy cap designs that differ in terms of target fuel, point of control, and national versus regional allowance trading using a global numerical general equilibrium model that separately represents 30 provinces in China. First, we simulate a coal cap and find that relative to a cap on all fossil fuels, it is significantly more costly and results in high localized welfare losses. Second, we compare fossil energy cap designs and find that a national cap on downstream fossil energy use with allowance trading across provinces is the most cost effective. Third, we find that a national fossil energy cap with trading is nearly as cost effective as a national CO₂ emissions trading system that penalizes energy use based on carbon content. As a fossil energy cap builds on existing institutions in China, it offers a viable intermediate step toward a full-fledged CO₂ emissions trading system.

The marked-based emission trading system is regarded as a cost effective way to facilitate emission abatement and is expected to play an essential role in international cooperation for global climate mitigation. The European Union Emissions Trading System (EU-ETS) has been fully operation since 2007. In 2012, Australia announced its intention to link to the EU-ETS starting in 2015. This research considers the implications of expanding these linkages further to include China and (or) the United States. We simulate an extended international emission market, beginning by analysing the implications of the EU-Australia/New Zealand (NZ) linkage (assuming New Zealand links to the Australian market) based on currently announced policy targets. We then extend the system to include China, and compare it to an Australia/NZ-EU-US linkage in terms of the impact on greenhouse gas (GHG) emissions at the global, national and sectoral level, the carbon-equivalent price by region (or for the ETS linked regions), and primary energy use at the global sectoral level, with attention to quantifying any leakage effects.

We employ the China-in-Global Energy Model (CGEM) for this analysis. The CGEM is a multi-regional, multi-sector, recursive-dynamic computable general equilibrium (CGE) model of the global economy that separately represents 19 regions and 18 sectors. For this work, we use the Global Trade Analysis Project 2007 data set (GTAP 8), which was released in the spring of 2012. To analyse the individual and combined impact of including China and US in an integrated global emissions trading market, we develop several scenarios, including a No-ETS scenario to serve as a baseline “No Policy” scenario, and a “reference” scenario that imposes emissions trading in each region without linkages. These scenarios include: EU-Australia/NZ, EU-Australia/NZ-China, EU-Australia/NZ-US, and EU-Australia-China-US. Other scenarios involve simulating the these cap-and-trade policies...

Emission controls that provide incentives for maximizing reductions in emissions of ozone precursors on days when ozone concentrations are highest have the potential to be cost-effective ozone management strategies. Conventional prescriptive emissions controls or cap-and-trade programs consider all emissions similarly regardless of when they occur, despite the fact that contributions to ozone formation may vary. In contrast, a time-differentiated approach targets emissions reductions on forecasted high ozone days without imposition of additional costs on lower ozone days. This work examines simulations of such dynamic air quality management strategies for NOx emissions from electric generating units. Results from a model of day-specific NOx pricing applied to the Pennsylvania–New Jersey–Maryland (PJM) portion of the northeastern U.S. electrical grid demonstrate (i) that sufficient flexibility in electricity generation is available to allow power production to be switched from high to low NOx emitting facilities, (ii) that the emission price required to induce EGUs to change their strategies for power generation are competitive with other control costs, (iii) that dispatching strategies, which can change the spatial and temporal distribution of emissions, lead to ozone concentration reductions comparable to other control technologies, and (iv) that air quality forecasting is sufficiently accurate to allow EGUs to adapt their power generation strategies.

© 2012 American Chemical Society