Catalyzing virtuous cycles of climate action: an empirical model of polycentric climate governance

催化气候行动的良性循环：多中心气候治理的经验模型

• 批准号: 2216592
• 负责人: Angel Hsu
• 金额: $ 50.38万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2216592&HistoricalAwards=false
• 关键词: Catalyzing; virtuous; cycles; climate; action

Nations and international governing bodies are traditionally viewed as the primary actors working to mitigate global climate change. Yet subnational jurisdictions, such as states and cities, and non-state entities, such as businesses and civic organizations, have become increasingly important actors in efforts to reduce climate-warming greenhouse gas emissions and stem climate impacts. This research project uses new data science methods to answer essential questions about this emerging diverse climate landscape, analyzing which subnational government climate policies and strategies translate to measurable emissions reductions; determining where and how these policies and initiatives perform regarding emissions; isolating the conditions that allow urban climate actions to create virtuous cycles of interaction and raise ambition nationally and internationally. This research also creates new data science methodologies and informational frameworks that strengthen the scientific basis of non-state and subnational contributions to global climate governance and help answer fundamental questions regarding the efficacy of current frameworks to address climate change. Subnational (i.e., cities and states) and private actors’ engagement in international processes and frameworks devoted to mitigate climate change (e.g., the 2015 Paris Agreement) represents a shift in the global climate governance paradigm from a predominantly top-down, nation-state centric approach to a polycentric network of actors. Subnational and non-state actors’ ability to catalyze and enhance climate actions towards global goals is unknown, largely due to a lack of relevant empirical data. This research project produces new evidence describing subnational actors’ contributions to global climate mitigation and governance, lending empirical bases for multi-level, polycentric climate governance theories that are so far untested. Three broad questions are examined: what subnational government climate policies and strategies translate to measurable emissions reductions? Where and how are these policies and initiatives performing, considering the total value (i.e., upstream and downstream) and embedded carbon chains? What conditions enhance urban climate actions’ ability to create virtuous cycles of interaction and raise ambition nationally and internationally? The project develops large-scale, spatially-explicit, open datasets using innovative Machine Language techniques to collect policy data and earth observation (EO)—the practice of collecting data on Earth's biological, physical and chemical processes typically through the use of satellite remote sensing technologies. The new data on climate change policies and practices and emission reductions used to estimate the effect of subnational governments and organizations seeking to mitigate the climate effects of emissions; only limited similar data currently exists, and that which does tends to neglect the Global South. Special considerations are given so that methods and models are scalable, reproducible, and adaptable to various locales and political contexts. Each research component incorporates equity and justice considerations, with continuing evaluation of where each dataset, case study, and model may not be attuned to policy inclusiveness and promoting equity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

传统上，国家和国际理事机构被视为致力于减缓全球气候变化的主要行为体。然而，州和城市等地方管辖区以及企业和民间组织等非国家实体已成为减少气候变暖温室气体排放和遏制气候影响的努力中越来越重要的行为体。该研究项目使用新的数据科学方法来回答有关这一新兴的多样化气候景观的基本问题，分析哪些地方政府气候政策和战略转化为可衡量的减排;确定这些政策和举措在排放方面的表现以及如何表现;隔离允许城市气候行动创造良性互动循环的条件，并在国内和国际上提高雄心。这项研究还创建了新的数据科学方法和信息框架，加强了非国家和国家以下各级对全球气候治理贡献的科学基础，并有助于回答有关当前框架应对气候变化的有效性的基本问题。国家以下一级（即，城市和国家）以及私营部门参与专门缓解气候变化的国际进程和框架（例如，2015年《巴黎协定》）代表了全球气候治理范式的转变，从主要的自上而下、以民族国家为中心的方法转变为多中心的行动者网络。国家以下一级和非国家行为者催化和加强气候行动以实现全球目标的能力尚不清楚，这主要是由于缺乏相关的经验数据。该研究项目提供了新的证据，说明国家以下一级行为体对全球气候减缓和治理的贡献，为迄今未经检验的多层次、多中心气候治理理论提供了经验基础。三个广泛的问题进行审查：什么地方政府的气候政策和战略转化为可衡量的减排？考虑到总价值（即，上游和下游）和嵌入式碳链？哪些条件可以增强城市气候行动创造良性互动循环和提高国家和国际目标的能力？该项目使用创新的机器语言技术开发大规模、空间明确的开放数据集，以收集政策数据和地球观测（EO）-通常通过使用卫星遥感技术收集地球生物、物理和化学过程数据的做法。 关于气候变化政策和实践以及减排的新数据用于估计国家以下各级政府和组织寻求减轻排放的气候影响的影响;目前只有有限的类似数据，并且倾向于忽视全球南方。特别考虑，使方法和模型是可扩展的，可复制的，并适应各种地区和政治背景。每个研究部分都包含公平和正义的考虑，并持续评估每个数据集，案例研究和模型可能不适合政策包容性和促进公平。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。