Create your own ideas about Peace, Planet and Profit

DDL Receives National Science Foundation Grant To Develop an Empirical Model of Subnational Climate Action

39


Photo by Henning Witzel on Unsplash

Data-Driven EnviroLab’s Principal Investigator, Dr. Angel Hsu, has received a $503,819 grant from the National Science Foundation for a 3-year research project, “Catalyzing virtuous cycles of climate action: an empirical model of polycentric climate governance.”

The 2015 Paris Agreement formally recognized the value of non-state actors, including the efforts of cities and companies, as vital parts of global efforts to take action on climate change. These organizations’  climate policy pledges mark a structural shift in global climate governance from a top-down structure to a more widely distributed and localized approach.

However, the incorporation of non-state entities as essential pieces of global climate change policy drastically increases the number of players on the scene. Tracking environmental policy made by states, provinces, cities, counties and even private and non-profit organizations is a large undertaking in itself, let alone measuring the effectiveness of these policies and comparing them to one another. Due to these challenges, non-state climate actions’ impact on global goals is largely unknown. To evaluate their efforts, DDL intends to build an empirical foundation with the help of data science. 

In unmasking this multi-level, polycentric climate governing landscape, the project aims to answer the following questions:

  1. What subnational climate policies and strategies translate to measurable emission reductions?
  2. Where and how are these policies and initiatives performing in reducing emissions from the global supply chain?
  3. What conditions enhance the ability of urban climate actors to create virtuous cycles of interaction and raise ambition nationally and internationally?

Incorporating equity and justice considerations with a continuing evaluation of datasets, case studies and models, the new DDL project will develop large-scale, spatially-explicit, open datasets with scalable, reproducible, and adaptable methods and models. The project seeks to establish an empirical basis for evaluating the role of non-state and subnational actors in mitigating climate change. 

Overall, this project seeks to uncover what is and is not working in the current climate change mitigation landscape, while considering benefits to global environmental health and societal equity. With the goal of strengthening the scientific basis for non-state and subnational contributions to global climate governance, this research will help evaluate the efficacy of current frameworks in addressing climate change, as well as create data science methodologies and informational frameworks for assessing the efforts of non-state and subnational climate contributions.

Comments are closed.