Martin’s research focuses on characterizing atmospheric composition to inform effective policies surrounding major environmental and public health challenges ranging from air quality to climate change. He leads a research group at the interface of satellite remote sensing and global modeling, with applications that include population exposure for health studies, top-down constraints on emissions, and analysis of processes that affect atmospheric composition. He serves as Co-Model Scientist for a leading global atmospheric model (GEOS-Chem), leads a global fine particulate matter network (SPARTAN) to evaluate and enhance satellite-based estimates of fine particulate matter, and on multiple science teams for satellite instruments including MAIA, TEMPO, and GEMS. Data from his group are relied upon for a large number of assessments including the OECD Regional Well-Being Index, for World Health Organization estimates of global mortality due to fine particulate matter, for the Global Burden of Disease Project to examine the risk factors affecting global public health, and for a wide range of health studies.