SEES Fellows: Be-Agile: A Mobile Network for Measuring Urban CO2 Emissions

SEES 研究员：Be-Agile：用于测量城市二氧化碳排放的移动网络

• 批准号: 1415404
• 负责人: Holly Maness
• 金额: $ 41.75万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1415404&HistoricalAwards=false
• 关键词: SEES; Fellows; Agile; Mobile; Network

The project is supported under the NSF Science, Engineering and Education for Sustainability Fellows (SEES Fellows) program, with the goal of helping to enable discoveries needed to inform actions that lead to environmental, energy and societal sustainability while creating the necessary workforce to address these challenges. Sustainability science is an emerging field that addresses the challenges of meeting human needs without harm to the environment, and without sacrificing the ability of future generations to meet their needs. A strong scientific workforce requires individuals educated and trained in interdisciplinary research and thinking, especially in the area of sustainability science. With the SEES Fellowship support, this project will enable a promising early career researcher to establish herself in an independent research career related to sustainability. This project focuses on developing a low-cost, mobile network capable of mapping CO2 greenhouse gas concentrations in urban environments with unprecedented spatial and temporal resolution. The work would culminate in the deployment of a small-scale prototype network on the fleet of Lawrence Berkeley National Laboratory (LBNL) shuttle buses. The SEES Fellow would integrate the collected data with an atmospheric model and ancillary meteorology, satellite, and traffic measurements to produce high spatial and temporal resolution surface carbon emissions maps in the vicinity of the UC Berkeley and LBNL campuses. This research project would lay the groundwork for deploying a future metropolitan-scale network which could then serve as a much needed policy tool for understanding and reducing emissions from traffic sources in urban areas, and thereby promoting global sustainability. Current inventories of greenhouse gas emissions are based on self-reported data, are subject to large uncertainties, and have historically been systematically under-reported. Moveover, regional governments are increasingly making commitments to greenhouse gas emission reductions, but presently there is no means of verifying whether the proposed policy changes have the intended effect. This research program promises to provide an independent method for constructing emissions inventories, based on direct atmospheric sampling. The proposed method would further provide higher spatial and temporal resolution inventories than have previously been achieved by any method. Strong national policy and international agreements are urgently needed to mitigate the impacts of climate change. Trust-but-verify is a necessary component for future treaties regulating greenhouse gases. This project establishes a scalable approach that can be used to provide empirical verification of CO2 emissions.In addition, this SEES Fellowship broadens the Fellow's academic expertise beyond her disciplinary training in physics to include new skills in systems engineering, traffic emissions modeling, analytic chemistry, atmospheric transport, and the tools of data science, including the statistical method of data assimilation for atmospheric data. Regular interaction with regional government organizations will enhance her understanding of the political decision-making process and its relationship to policy-relevant scientific measurements. Dr. Tom Kirschstetter (Lawrence Berkeley National Lab) and Professor Inez Fung (University of California, Berkeley) serve as the Felow's principal mentors in this endeavor.

该项目得到了NSF科学，工程和教育可持续发展研究员（SEES研究员）计划的支持，其目标是帮助实现所需的发现，为导致环境，能源和社会可持续性的行动提供信息，同时创造必要的劳动力来应对这些挑战。可持续发展科学是一个新兴的领域，它解决了在不损害环境的情况下满足人类需求的挑战，并且不牺牲后代满足其需求的能力。一个强大的科学队伍需要在跨学科研究和思维方面受过教育和培训的个人，特别是在可持续发展科学领域。在SEES奖学金的支持下，该项目将使一个有前途的早期职业研究人员能够在与可持续发展相关的独立研究生涯中确立自己的地位。该项目的重点是开发一个低成本的移动的网络，能够以前所未有的空间和时间分辨率绘制城市环境中的二氧化碳温室气体浓度。这项工作最终将在劳伦斯伯克利国家实验室（LBNL）穿梭巴士车队上部署一个小规模的原型网络。SEES研究员将把收集到的数据与大气模型和辅助气象学、卫星和交通测量相结合，在加州大学伯克利分校和LBNL校区附近制作高空间和时间分辨率的地表碳排放地图。这一研究项目将为部署未来大都市规模的网络奠定基础，该网络可作为了解和减少城市地区交通源排放的迫切需要的政策工具，从而促进全球可持续性。目前的温室气体排放清单是基于自我报告的数据，存在很大的不确定性，而且历来都是系统性地少报的。此外，区域政府越来越多地承诺减少温室气体排放，但目前没有办法核实拟议的政策变化是否产生了预期的效果。这项研究计划承诺提供一个独立的方法来构建排放清单，基于直接大气采样。所提出的方法将进一步提供比以前任何方法所实现的更高的空间和时间分辨率的清单。迫切需要强有力的国家政策和国际协定，以减轻气候变化的影响。“信任但要核查”是未来控制温室气体条约的必要组成部分。该项目建立了一种可扩展的方法，可用于提供CO2排放的经验验证。此外，该SEES奖学金拓宽了研究员的学术专长，超出了她在物理学方面的学科培训，包括系统工程，交通排放建模，分析化学，大气运输和数据科学工具的新技能，包括大气数据同化的统计方法。与区域政府组织的定期互动将提高她对政治决策过程及其与政策相关科学计量的关系的理解。Tom Kirschstetter博士（劳伦斯伯克利国家实验室）和伊内兹冯教授（加州大学伯克利分校）担任Felow在这奋进的主要导师。