H. Scott Matthews

Cost-Effectiveness of Green Roofs

Life-cycle assessment was used to evaluate the widespread installation of green roofs in a typical urban mixed-use neighborhood. Market prices of materials, construction, energy conservation, storm-water management, and greenhouse gas (GHG) emission reductions were used to evaluate private and social costs and benefits. Results suggest green roofs are currently not cost effective on a private cost basis, but multifamily and commercial building green roofs are competitive when social benefits are included. Multifamily and commercial green roofs are also competitive alternatives for reducing greenhouse gases and storm-water runoff. However, green roofs are not the most competitive energy conservation techniques. GHG impacts are dominated by the material production and use phases. Energy impacts are dominated by the use phase, with urban heat island (UHI) impacts being an order of magnitude higher than direct building impacts. The quantification of private and social costs and benefits should help guide green roof policy. Results should encourage green roof enthusiasts to set appropriate life-cycle assessment boundaries, including construction material impacts and UHI effects.

Thinking Outside 'the Box': Designing a Packaging Take-Back System

This article details the planning/implementation, and assessment of a worldwide electronics packaging take-back system by a key supply chain partner. The take-back system was a financial and environmental tradeoff between reducing cardboard packaging against increased use of ground and water transportation. Through Internetenabled life cycle analysis, the new system was shown to significantly reduce waste as well as energy and environmental impacts. If such methods were introduced more formally in the electronics industry,

Using input‐output analysis for corporate benchmarking

150 million as well as billions of pounds of waste could be saved per year.

Disaggregating the Power Generation Sector for Input-Output Life Cycle Assessment

In recent years, cost‐effective protection of the environment has become a more important goal for many businesses. Companies have been striving to reduce the environmental impacts of their products and packaging, while not incurring costs that put them at a competitive disadvantage. A key to accomplishing this goal is by benchmarking their performance against other companies. Benchmarking can be expensive, time consuming, or problematic because detailed benchmarking requires detailed, specific data that are generally confidential. A screening level benchmark can accomplish much of the goal quickly and cheaply. Focuses on a tool to make quick, screening level benchmarks of US industrial environmental performance and discusses how it can be used to evaluate a plants environmental performance. Mentions other tools, notes its relationship to them, and discusses how it can be more broadly used. Finally, suggests ways that this type of benchmarking information can be used broadly within a firm for accounting and decision‐making purposes.

Methods and Apparatuses for Monitoring Energy Consumption and Related Operations

The electric power industry plays a critical role in the economy and the environment, and it is important to examine the economic, environmental, and policy implications of current and future power generation scenarios. However, the tools that exist to perform the life cycle assessments are either too complex or too aggregated to be useful for these types of activities. In this work, we build upon the framework of existing input‐output (I‐O) models by adding data about the electric power industry and disaggregating this single sector into additional sectors, each representing a specific portion of electric power industry operations. For each of these disaggregated sectors, we create a process‐specific supply chain and a set of emission factors that allow calculation of the environmental effects of that sectors output. This new model allows a much better fit for scenarios requiring more specificity than is possible with the current I‐O model.