M
Michael A. McNeil
Researcher at Lawrence Berkeley National Laboratory
Publications - 72
Citations - 2799
Michael A. McNeil is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Efficient energy use & Energy consumption. The author has an hindex of 28, co-authored 72 publications receiving 2530 citations.
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Using learning curves on energy-efficient technologies to estimate future energy savings and emission reduction potentials in the U.S. iron and steel industry:
TL;DR: In this article, the authors propose a novel approach to solve the problem of homonymity in homonym-based homonym identification.1 Chapter 1, Section 3.1.
Superefficient Refrigerators: Opportunities and Challenges for Efficiency Improvement Globally
TL;DR: In this paper, the authors present the results of a technical analysis done for refrigerators in support of the Super-efficient Equipment and Appliance Deployment (SEAD) initiative.
Journal ArticleDOI
Methodology for the National Water Savings Models- Indoor Residential and Commercial/Institutional Products, and Outdoor Residential Products.
Jonah Schein,Peter Chan,Yuting Chen,Camilla Dunham,Heidi L. Fuchs,Virginie Letschert,Michael A. McNeil,Moya Melody,Sarah Price,Hannah Stratton,Alison Williams +10 more
TL;DR: The National Water Savings (NWS) model tracks the water and consumer monetary savings of WaterSense-labeled products for residential and commercial water use both indoors and out.
What do India's transport energy data tell us? A bottom-up assessment of energy demand in India transportation sector
TL;DR: In this article, the authors developed a data base on all transport modes including passenger air and water, and freight in order to facilitate the development of energy scenarios and assess signifi cance of technology potential in a global climate change model.
ReportDOI
DSM Electricity Savings Potential in the Buildings Sector in APP Countries
TL;DR: In this paper, the authors present a first estimate of the savings potential of DSM programs in Asia Pacific Partnership (APP) countries through the year 2030, based on detailed end-use data, which is worth keeping in mind that more work is needed to overcome limitation in data at this time of the project.