Anand Gopal

Bio: Anand Gopal is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Electric vehicle & Biofuel. The author has an hindex of 16, co-authored 31 publications receiving 861 citations. Previous affiliations of Anand Gopal include University of California, Berkeley.

Life-Cycle Assessment of Electric Power Systems

Abstract: The application of life-cycle assessment (LCA) to electric power (EP) technologies is a vibrant research pursuit that is likely to continue as the world seeks ways to meet growing electricity demand with reduced environmental and human health impacts. Although LCA is an evolving methodology with a number of barriers and challenges to its effective use, LCA studies to date have improved our understanding of the life-cycle energy, greenhouse gas emissions, air pollutant emissions, and water-use implications of EP technologies. With continued progress, LCA offers promise for assessing and comparing EP technologies in an analytically thorough and environmentally holistic manner for more robust deployment decisions. This article summarizes (a) current challenges in applying LCA to EP technologies, (b) LCA results to date on various impacts of EP technologies, and (c) opportunities for improving LCAs of EP technologies.

Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area

Abstract: Emerging technologies and services stand poised to transform the transportation system, with large implications for energy use and mobility. The degree and speed of these impacts depend largely on who adopts these innovations and how quickly. Leveraging data from a novel survey of San Francisco Bay Area residents, we analyze adoption patterns for shared mobility, electrified vehicle technologies, and vehicle automation. We find that ride-hailing and adaptive cruise control have penetrated the market more extensively than have electrified vehicles or car-sharing services. Over half of respondents have adopted or expressed interest in adopting all levels of vehicle automation. Overall, there is substantial potential for market growth for the technologies and services we analyzed. Using county fixed effects regressions, we investigate which individual and location-level factors correlate to adoption and interest. We find that, although higher-income people are disproportionately represented among current adopters of most new technologies and services, low- to middle-income people are just as likely to have adopted pooled ride-hailing. Younger generations have high interest in automated and electrified vehicles relative to their current adoption of these technologies, suggesting that young people could contribute substantially to future market growth—as they are doing for ride-hailing. We find no evidence that longer commutes present a barrier to plug-in electric vehicle adoption. Finally, women are less likely than men to adopt and/or be interested in adopting most new transportation technologies, with the exception of ride-hailing; designing or marketing technologies with women’s preferences in mind could contribute to future market expansion.

The ecoinvent database version 3 (part I): overview and methodology

Abstract: Purpose Good background data are an important requirement in LCA. Practitioners generally make use of LCI databases for such data, and the ecoinvent database is the largest transparent unit-process LCI database worldwide. Since its first release in 2003, it has been continuously updated, and version 3 was published in 2013. The release of version 3 introduced several significant methodological and technological improvements, besides a large number of new and updated datasets. The aim was to expand the content of the database, set the foundation for a truly global database, support regionalized LCIA, offer multiple system models, allow for easier integration of data from different regions, and reduce maintenance efforts. This article describes the methodological developments.

Dewatering of microalgal cultures : a major bottleneck to algae-based fuels

Abstract: Microalgae dewatering is a major obstruction to industrial-scale processing of microalgae for biofuel prodn. The dil. nature of harvested microalgal cultures creates a huge operational cost during dewatering, thereby, rendering algae-based fuels less economically attractive. Currently there is no superior method of dewatering microalgae. A technique that may result in a greater algal biomass may have drawbacks such as a high capital cost or high energy consumption. The choice of which harvesting technique to apply will depend on the species of microalgae and the final product desired. Algal properties such as a large cell size and the capability of the microalgae to autoflocculate can simplify the dewatering process. This article reviews and addresses the various technologies currently used for dewatering microalgal cultures along with a comparative study of the performances of the different technologies.