A Data-Driven Approach to Assessing Spatially-Explicit Air Emissions of Biomass Feedstock Production | AIChE

A Data-Driven Approach to Assessing Spatially-Explicit Air Emissions of Biomass Feedstock Production

Authors 

Heath, G., National Renewable Energy Laboratory (NREL
Zhang, Y., National Renewable Energy Laboratory
Hanes, R., National Renewable Energy Laboratory
Increased demand for biomass feedstock for biofuel production could lead to additional emission sources and may impact air quality. The National Renewable Energy Laboratory’s Feedstock Production Emissions to Air Model (FPEAM) is a tool, which can be used to develop county-level emission inventories of direct air pollutant emissions produced by the biomass feedstock supply chain in the United States. Here we provide an overview of FPEAM functionality and discuss several applications based on the newly released model.

FPEAM is a modular model, in which each module contains calculations for an activity type, except for the feedstock transportation and on-farm equipment operation modules which connect to the U.S. Environmental Protection Agency’s Motor Vehicle Emissions Simulator (MOVES) and NONROAD models, respectively. User-defined model inputs (e.g., equipment horsepower) or default data for certain scenarios are used to calculate inventories of volatile organic compounds, particulate matter, ammonia, nitrogen oxides, sulfur oxides generated by each activity in the biomass production and supply chain. The data-driven aspect of FPEAM means that the input data for a scenario (e.g.,production scale) rather than the model itself drives the type and magnitude of the pollutants. Modules within FPEAM can be turned on or off manually to adjust the scenario scope. Default data packaged with the FPEAM code can be used to calculate inventories of aforementioned pollutants generated by agricultural and forestry equipment operation, chemical application, and feedstock transportation. User-defined data can be used in place of the default data to analyze scenarios with alternate feedstocks and supply chain activities.