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

该项目由NSF科学、工程和教育促进可持续发展研究员(SEE FERLOS)计划支持，目标是帮助实现必要的发现，为导致环境、能源和社会可持续发展的行动提供信息，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领域，它解决了在不损害环境、不牺牲子孙后代满足其需求的能力的情况下满足人类需求的挑战。一支强大的科学队伍需要接受跨学科研究和思维方面的教育和培训，特别是在可持续发展科学领域。在SEES奖学金的支持下，该项目将使一位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地图。这项工作最终将在劳伦斯伯克利国家实验室(LBNL)班车车队上部署一个小规模的原型网络。SEES研究员将把收集的数据与大气模型以及辅助气象学、卫星和交通测量相结合，以在加州大学伯克利分校和LBNL校园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的大都市规模的网络奠定基础，该网络随后可以作为了解和减少城市地区交通来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以自我报告的数据为基础的，存在很大的不确定性，而且历来一直被系统性地少报。此外，地区政府越来越多地承诺减少温室气体排放，但目前还没有办法核实拟议的政策变化是否具有预期的效果。这项研究计划承诺为建立排放清单提供一种独立的方法，基于直接的大气采样。拟议的方法将进一步提供比以往任何方法所实现的更高的空间和时间分辨率清单。迫切需要强有力的国家政策和国际协议来减轻气候变化的影响。信任但核实是未来监管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，可用于提供二氧化碳排放的经验验证。此外，该项目还扩大了研究员的学术专长，超越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、大气传输和数据科学工具(包括大气数据的数据同化的统计方法)方面的新技能。与地区政府组织的定期互动将增进她对政治决策过程及其与与政策有关的科学衡量的关系的了解。劳伦斯·伯克利国家实验室的Tom Kirschstetter博士和加州大学伯克利分校的Inez Fung教授是这位研究员在这项工作中的主要导师。

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.