Fine-Scale Analysis of the Energy–Land–Water Nexus: Nitrate Leaching Implications of Biomass Cofiring in the Midwestern United States

Abstract

As scientists seek to better understand the linkages between energy, water, and land systems, they confront a critical question of scale for their analysis. Many studies exploring this nexus restrict themselves to a small area in order to capture fine-scale processes, whereas other studies focus on interactions between energy, water, and land over broader domains but apply coarse resolution methods. Detailed studies of a narrow domain can be misleading if the policy intervention considered is broad-based and has impacts on energy, land, and agricultural markets. Regional studies with aggregate low-resolution representations may miss critical feedbacks driven by the dynamic interactions between subsystems. This study applies a novel, gridded energy−land−water modeling system to analyze the local environmental impacts of biomass cofiring of coal power plants across the upper MISO region. We use this framework to examine the impacts of a hypothetical biomass cofiring technology mandate of coal-fired power plants using corn residues. We find that this scenario has a significant impact on land allocation, fertilizer applications, and nitrogen leaching. The effects also impact regions not involved in cofiring through agricultural markets. Further, some MISO coal-fired plants would cease generation because the competition for biomass increases the cost of this feedstock and because the higher operating costs of cofiring renders them uncompetitive with other generation sources. These factors are not captured by analyses undertaken at the level of an individual power plant. We also show that a region-wide analysis of this cofiring mandate would have registered only a modest increase in nitrate leaching (just +5% across the upper MISO region). Such aggregate analyses would have obscured the extremely large increases in leaching at particular locations, as much as +60%. Many of these locations are already pollution hotspots. Fine-scale analysis, nested within a broader framework, is necessary to capture these critical environmental interactions within the energy, land, and water nexus.

Coal-Biomass Co-firing within Renewable Portfolio Standards: Strategic Adoption by Heterogeneous Firms and Emissions Implications

“…Further, the firms' decisions are affected by the adoption decisions of other firms, both through their competition in the electricity market clearing and through competition for local biomass supply, which affects the biomass price. The model framework builds on previous work that combined a high-resolution representation of the power sector with interaction between the electricity and biomass markets to evaluate the impact of a co-firing mandate on a coupled energy-water-land system (Sun et al, 2020). Here we provide a brief overview of the main features of the framework; see Sun et al (2020) and the Appendix for more details on each model component.…”

Water Quality Effects of Economically Viable Land Use Change in the Mississippi River Basin under the Renewable Fuel Standard

“…Ethanol production from cellulosic feedstocks has mainly come from crop residues, which has been shown to have deleterious effects on soil and cropping systems, including N loss. − Depending on where they are grown, which crops they displace, and how they are managed, perennial energy crops have the potential to reduce N loss to water at a field, watershed, and regional scale while meeting ethanol production goals. − It has been shown that the economic incentives for producing energy crops would likely lead to production on land described as marginal with low opportunity costs of conversion from existing uses to energy crops . In other words, perennials are unlikely to displace land currently used for corn and soybean production.…”

“…However, they prescribed land use change exogenously (i.e., forced perennials to replace cropland across the MARB evenly) and did not consider whether conversion of land under corn to miscanthus or switchgrass production would be economically viable. To endogenously determine (i.e., dynamically predict) the economic and biophysical water quality implications of policy-driven land use change for the MARB, an integrated modeling approach is needed …”

“…To endogenously determine (i.e., dynamically predict) the economic and biophysical water quality implications of policy-driven land use change for the MARB, an integrated modeling approach is needed. 12 We developed an integrated economic-biophysical modeling approach to endogenously determine the cost-effective mix of feedstock production and land use change induced by the RFS2 and its water quality implications for the MARB. 12 We coupled an economic model (Biofuel and Environmental Policy Analysis Model (BEPAM)) with an agroecosystem model (Integrated BIosphere Simulator−Agricultural Version (Agro-IBIS)) and a nutrient transport and hydrologic model (Terrestrial Hydrologic Model with Biogeochemistry (THMB)) to simulate water quality effects from corn grain and cellulosic feedstocks under potential biofuel production scenarios (see Sections 2.1 and 2.2).…”

“…12 We developed an integrated economic-biophysical modeling approach to endogenously determine the cost-effective mix of feedstock production and land use change induced by the RFS2 and its water quality implications for the MARB. 12 We coupled an economic model (Biofuel and Environmental Policy Analysis Model (BEPAM)) with an agroecosystem model (Integrated BIosphere Simulator−Agricultural Version (Agro-IBIS)) and a nutrient transport and hydrologic model (Terrestrial Hydrologic Model with Biogeochemistry (THMB)) to simulate water quality effects from corn grain and cellulosic feedstocks under potential biofuel production scenarios (see Sections 2.1 and 2.2). Our objectives are to (1) assess the endogenously determined area needed to produce the feedstocks considered here and their spatial pattern of production across active and idle (i.e., cropland that earns relatively low net returns while under crop production 27 ) cropland in the MARB and (2) quantify the amount of N loss these land use scenarios could generate for each potential policy scenario relative to baseline levels before the RFS2.…”