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Open Access Publications from the University of California

Scholarly Works (3 results)

  • Thesis
  • Peer Reviewed
UC Irvine Electronic Theses and Dissertations (2018)

This dissertation proposes a methodology applicable worldwide to assess key health, climate and electricity system impacts of high penetrations of variable renewable energy (VRE), such as wind and solar energy, in the production of electricity. Three primary questions are addressed: (1) what are the health benefits and control costs of tightening emission standards for particulate matter (PM); (2) what are the health, climate and electricity grid impacts of high penetrations of VRE; and (3) is a 100% Renewable Portfolio Standard (RPS) electricity grid technically feasible in Northeast (NE) Brazil, and what are the associated health and climate benefits? The methodology I developed to answer these questions combines highly resolved spatial and temporal electricity grid simulation (via Plexos), atmospheric dispersion of power plant emissions (via CALPUFF), and human health impacts estimation (via BenMAP). The methodology is validated extensively over detailed case studies in NE Brazil, a region that has exceptionally high VRE and hydroelectric potential. Results for Question (1) indicate that when tightening emission standards, the health benefits outweigh the control costs by at least 50 times, even in a relatively clean region. Results for Question (2) show that health and climate benefits exceed US$267 million/yr and US$1.2 billion/yr respectively if NE Brazil transitions to a 45% VRE instead of a 30% VRE penetration in 2030. For Question (3), I find that a 100% RPS is not feasible using only wind, solar PV and hydroelectric resources in NE Brazil unless ~13% of demand can be flexibly imported and ~23% of generation can be flexibly exported; otherwise additional types of generation, storage and load balancing technology would need to be deployed. For this case, the health and climate benefits are at least US$433 million/yr and US$2.4 billion/yr respectively if NE Brazil transitions to a 100% RPS instead of a 30% VRE penetration in 2030.

    Cover page: Health, Climate and Electricity Grid Impacts of High Penetrations of Variable Renewable Energy
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2019)
    Exposure to ambient particulate matter (PM) caused an estimated 4.2 million deaths worldwide in 2015. However, PM emission standards for power plants vary widely. To explore if the current levels of these standards are sufficiently stringent in a simple cost-benefit framework, we compared the health benefits (avoided monetized health costs) with the control costs of tightening PM emission standards for coal-fired power plants in Northeast (NE) Brazil, where ambient PM concentrations are below World Health Organization (WHO) guidelines. We considered three Brazilian PM10 (PMx refers to PM with a diameter under x micrometers) emission standards and a stricter U.S. EPA standard for recent power plants. Our integrated methodology simulates hourly electricity grid dispatch from utility-scale power plants, disperses the resulting PM2.5, and estimates selected human health impacts from PM2.5 exposure using the latest integrated exposure-response model. Since the emissions inventories required to model secondary PM are not available in our study area, we modeled only primary PM so our benefit estimates are conservative. We found that tightening existing PM10 emission standards yields health benefits that are over 60 times greater than emissions control costs in all the scenarios we considered. The monetary value of avoided hospital admissions alone is at least four times as large as the corresponding control costs. These results provide strong arguments for considering tightening PM emission standards for coal-fired power plants worldwide, including in regions that meet WHO guidelines and in developing countries.
      Cover page: Health benefits and control costs of tightening particulate matter emissions standards for coal power plants - The case of Northeast Brazil
      • Article
      • Peer Reviewed
      LBL Publications (2022)
      In recent years, Earth system sciences are urgently calling for innovation on improving accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in many subdomains amid the exponentially accumulated datasets and the promising artificial intelligence (AI) revolution in computer science. This paper presents work led by the NASA Earth Science Data Systems Working Groups and ESIP machine learning cluster to give a comprehensive overview of AI in Earth sciences. It holistically introduces the current status, technology, use cases, challenges, and opportunities, and provides all the levels of AI practitioners in geosciences with an overall big picture and to “blow away the fog to get a clearer vision” about the future development of Earth AI. The paper covers all the majorspheres in the Earth system and investigates representative AI research in each domain. Widely used AI algorithms and computing cyberinfrastructure are briefly introduced. The mandatory steps in a typical workflow of specializing AI to solve Earth scientific problems are decomposed and analyzed. Eventually, it concludes with the grand challenges and reveals the opportunities to give some guidance and pre-warnings on allocating resources wisely to achieve the ambitious Earth AI goals in the future.
        Cover page: A review of Earth Artificial Intelligence
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