Anthropogenic emissions of air pollutants have resulted in local to global-scale changes ranging from altered global radiative energy balances to regional to local impacts on human health and ecosystems. Emissions data are necessary inputs to atmospheric models from weather to climate scales. This talk will discuss our on-going work to produce improved emissions data for global modeling efforts. We discuss current work focused on extending our data series to the lastest full year and the production of uncertainty ensembles. We will also be organizing a multi-model sensitivity study (Emiss-MIP) that aims to to determine what aspects of emissions data are most important to global models, including both ESMs and CTMs. Potential future directions for making emissions data more useful for near- and long-term modeling will be discussed.
Dr. Steven Smith is a senior scientist at the Joint Global Change Research Institute at the Pacific Northwest National Laboratory and the Department of Atmospheric and Oceanic Science, University of Maryland (College Park, MD). Much of Smith's research has focused on the interactions between air pollution and climate including future emission scenarios, the potential near-term role of short-lived climate forcers (e.g., methane, black carbon), and quantifying past and future aerosol forcing. Smith is co-lead of the EMF (Energy Modeling Form)-30 integrated model inter-comparison project focusing on short-lived climate forcers and also principal investigator of the project that produced the historical air pollutant emissions (1750-2014) used in the Coupled Model Inter-comparison Project phase 6 (CMIP6). Smith was one of the developers of the Global Change Assessment Model (GCAM), which he and collaborators are currently using to examine multi-sector interactions between the energy system and air-pollutant emissions from global to regional (India, US states) scales. Other recent work includes examination of the temporal and spatial impacts of black carbon emissions on the Arctic and the Globe, and an assessment of forcing uncertainty impacts on Arctic temperature change.
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