Open Source Energy System Modeling Using Break-Even Costs to Inform State-Level Policy: A North Carolina Case Study.

Rigorous model-based analysis can help inform state-level energy and climate policy. In this study, we utilize an open-source energy system optimization model and publicly available data sets to examine future electricity generation, CO emissions, and CO abatement costs for the North Carolina electric power sector through 2050. Model scenarios include uncertainty in future fuel prices, a hypothetical CO cap, and an extended renewable portfolio standard.

Evaluation of optimal model parameters for prediction of methane generation from selected U.S. landfills.

In practice, methane generation at U.S. landfills is typically predicted by using the EPA's Landfill Gas Emissions Model (LandGEM), which includes two parameters, the methane production potential (L, m CH Mg wet waste) and the first-order decay rate constant (k, yr).

Solid Waste Management Policy Implications on Waste Process Choices and Systemwide Cost and Greenhouse Gas Performance.

Solid waste management (SWM) is a key function of local government and is critical to protecting human health and the environment. Development of effective SWM strategies should consider comprehensive SWM process choices and policy implications on system-level cost and environmental performance. This analysis evaluated cost and select environmental implications of SWM policies for Wake County, North Carolina using a life-cycle approach.

US Energy-Related Greenhouse Gas Emissions in the Absence of Federal Climate Policy.

The planned US withdrawal from the Paris Agreement as well as uncertainty about federal climate policy has raised questions about the country's future emissions trajectory. Our model-based analysis accounts for uncertainty in fuel prices and energy technology capital costs and suggests that market forces are likely to keep US energy-related greenhouse gas emissions relatively flat or produce modest reductions: in the absence of new federal policy, 2040 greenhouse gas emissions range from +10% to -23% of the baseline estimate. Natural gas versus coal utilization in the electric sector represents a key trade-off, particularly under conservative assumptions about future technology innovation.

Evaluation of Externality Costs in Life-Cycle Optimization of Municipal Solid Waste Management Systems.

The development of sustainable solid waste management (SWM) systems requires consideration of both economic and environmental impacts. Societal life-cycle costing (S-LCC) provides a quantitative framework to estimate both economic and environmental impacts, by including "budget costs" and "externality costs". Budget costs include market goods and services (economic impact), whereas externality costs include effects outside the economic system (e.

Systematic Evaluation of Industrial, Commercial, and Institutional Food Waste Management Strategies in the United States.

New regulations and targets limiting the disposal of food waste have been recently enacted in numerous jurisdictions. This analysis evaluated selected environmental implications of food waste management policies using life-cycle assessment. Scenarios were developed to evaluate management alternatives applicable to the waste discarded at facilities where food waste is a large component of the waste (e.

Characterization of uncertainty in estimation of methane collection from select U.S. landfills.

Methane is a potent greenhouse gas generated from the anaerobic decomposition of waste in landfills. If captured, methane can be beneficially used to generate electricity. To inventory emissions and assist the landfill industry with energy recovery projects, the U.

Analysis of material recovery facilities for use in life-cycle assessment.

Insights derived from life-cycle assessment of solid waste management strategies depend critically on assumptions, data, and modeling at the unit process level. Based on new primary data, a process model was developed to estimate the cost and energy use associated with material recovery facilities (MRFs), which are responsible for sorting recyclables into saleable streams and as such represent a key piece of recycling infrastructure. The model includes four modules, each with a different process flow, for separation of single-stream, dual-stream, pre-sorted recyclables, and mixed-waste.

Systematic exploration of efficient strategies to manage solid waste in U.S. municipalities: perspectives from the solid waste optimization life-cycle framework (SWOLF).

Solid waste management (SWM) systems must proactively adapt to changing policy requirements, waste composition, and an evolving energy system to sustainably manage future solid waste. This study represents the first application of an optimizable dynamic life-cycle assessment framework capable of considering these future changes. The framework was used to draw insights by analyzing the SWM system of a hypothetical suburban U.

How much do electric drive vehicles matter to future U.S. emissions?

Hybrid, plug-in hybrid, and battery electric vehicles--known collectively as electric drive vehicles (EDVs)--may represent a clean and affordable option to meet growing U.S. light duty vehicle (LDV) demand.

Using observed data to improve estimated methane collection from select U.S. landfills.

The anaerobic decomposition of solid waste in a landfill produces methane, a potent greenhouse gas, and if recovered, a valuable energy commodity. Methane generation from U.S.

The influence of large-scale wind power on global climate.

Large-scale use of wind power can alter local and global climate by extracting kinetic energy and altering turbulent transport in the atmospheric boundary layer. We report climate-model simulations that address the possible climatic impacts of wind power at regional to global scales by using two general circulation models and several parameterizations of the interaction of wind turbines with the boundary layer. We find that very large amounts of wind power can produce nonnegligible climatic change at continental scales.