Primary Convener:
Yuzhou Wang, University of California Berkeley

Convener:
Srinidhi Balasubramanian, Indian Institute of Technology Bombay
Christopher Tessum, University of Illinois at Urbana Champaign
Yuqiang Zhang, Shandong University

Early Career Convener:
Yuzhou Wang, University of California Berkeley

Chair:
Yuzhou Wang, University of California Berkeley
Srinidhi Balasubramanian, University of Illinois at Urbana Champaign
Christopher Tessum, University of Illinois at Urbana Champaign
Yuqiang Zhang, Shandong University

Air pollution is one of the largest environmental risks to human health worldwide. It originates from diverse sources, and pollution levels are unevenly distributed across countries, regions, cities, and communities. Given the highly heterogeneous nature of air pollution, it is important to have a toolkit of models and methods to accurately and efficiently quantify the source contributions and ambient pollutant concentrations for developing effective and equitable policy solutions. This session seeks to highlight research from across the globe that focuses on the development and deployment of computational methods for high-resolution exposure assessment and source attribution across local to global spatial scales. Featured tools will include data-driven frameworks with a focus on satellite-based approaches, models that integrate low-cost sensors and mobile monitoring, chemical transport model-derived tools, reduced-form models, machine-learning models, and other hybrid approaches.

Index Terms
0305 Aerosols and particles
0345 Pollution: urban and regional
0545 Modeling
1952 Modeling

Co-Sponsored Sessions:
ISEE： International Society of Environmental Epidemiology

Suggested Itineraries:
Climate Change and Global Policy
Machine Learning and AI
Global Impacts‚ Solutions‚ & Policies
Environmental Justice

Cross-Listed:
A - Atmospheric Sciences
GC - Global Environmental Change

Neighborhoods:
1. Science Nexus