Search for: All records

Annual U.S. production of bioethanol, primarily produced from corn starch in the U.S. Midwest, rose to 57 billion liters in 2021, which fulfilled the required conventional biofuel target set forth by the Energy Independence and Security Act (EISA) of 2007. At the same time, the U.S. fell short of the cellulosic or advanced biofuel target of 79 billion liters. The growth of bioenergy grasses (e.g., Miscanthus and switchgrass) across the Central and Eastern U.S. has the potential to feed enhanced cellulosic bioethanol production and, if successful, increase renewable fuel volumes. However, water consumption and climate change and its extremes are critical concerns in corn and bioenergy grass productivity. These concerns are compounded by the demands on potentially productive land areas and water devoted to producing biofuels. This is a fundamental Food-Energy-Water System (FEWS) nexus challenge. We apply a computational framework to estimate potential bioenergy yield and conversion to bioethanol yield across the U.S., based on crop field studies and conversion technology analysis for three crops—corn, Miscanthus, and two cultivars of switchgrass (Cave-in-Rock and Alamo). The current study identifies regions where each crop has its highest yield across the Center and Eastern U.S. While growing bioenergy grasses requires more water than corn, one advantage they have as a source of bioethanol is that they control nitrogen leaching relative to corn. Bioenergy grasses also maintain steadily high productivity under extreme climate conditions, such as drought and heatwaves in the year 2012 over the U.S. Midwest, because the perennial growing season and the deeper and denser roots can ameliorate the soil water stress. While the potential ethanol yield could be enhanced using energy grasses, their practical success in becoming a potential source of ethanol yield remains limited by socio-economic and operational constraints and concerns regarding competition with food production. 

The rate and extent of anthropogenic alteration of the global nitrogen cycle over the past four decades has been extensive, resulting in cascading negative impacts on riverine and coastal water quality. In this paper, we investigate the individual effects of a set of management, technology, and policy mechanisms that alter total reactive nitrogen (TN) flux through rivers, using a modified, spatially detailed SPARROW TN model, between 1980 and 2019 in the Northeast (NE) and Midwest (MW) of the United States. Using the recalibrated model, we simulate and validate a historical baseline, to which we compare a set of climate and non-climate single factor experiments (SFEs) in which individual factors are held at 1980s levels while all other factors change dynamically. We evaluate SFE performance in terms of differences in TN flux and willingness to pay. The largest effect on TN flux are related to reduction in cropland area and atmospheric nitrogen deposition. Multi-factor experiments (MFEs) suggest that increasingly efficient corn cultivars had a larger influence than increasing fertilizer application rate, while population growth has a larger influence than wastewater treatment. Extreme climate SFEs suggest that persistent wet conditions increase TN flux throughout the study region. Meanwhile, persistent hot years result in reduced TN flux. The persistent dry climate SFE leads to increased TN flux in the NE and reduced TN flux in the MW. We find that the potential for TN removal through aquatic decay is greatest in MW, due to the role of long travel time of rivers draining into the Lower Mississippi River. This paper sheds light on how a geographically and climatologically diverse region would respond to a representative selection of management options. 

Forests provide several critical ecosystem services that help to support human society. Alteration of forest infrastructure by changes in land use, atmospheric chemistry, and climate change influence the ability of forests to provide these ecosystem services and their sensitivity to existing and future extreme climate events. Here, we explore how the evolving forest infrastructure of the Midwest and Northeast United States influences carbon sequestration, biomass increment (i.e., change in vegetation carbon), biomass burning associated with fuelwood and slash removal, the creation of wood products, and runoff between 1980 and 2019 within the context of changing environmental conditions and extreme climate events using a coupled modeling and assessment framework. For the 40-year study period, the region’s forests functioned as a net atmospheric carbon sink of 687 Tg C with similar amounts of carbon sequestered in the Midwest and the Northeast. Most of the carbon has been sequestered in vegetation (+771 Tg C) with more carbon stored in Midwestern trees than in Northeastern trees to provide a larger resource for potential wood products in the future. Runoff from forests has also provided 4,651 billion m 3 of water for potential use by humans during the study period with the Northeastern forests providing about 2.4 times more water than the Midwestern forests. Our analyses indicate that climate variability, as particularly influenced by heat waves, has the dominant effect on the ability of forest ecosystems to sequester atmospheric CO 2 to mitigate climate change, create new wood biomass for future fuel and wood products, and provide runoff for potential human use. Forest carbon sequestration and biomass increment appear to be more sensitive to heat waves in the Midwest than the Northeast while forest runoff appears to be more sensitive in the Northeast than the Midwest. Land-use change, driven by expanding suburban areas and cropland abandonment, has enhanced the detrimental heat-wave effects in Midwestern forests over time, but moderated these effects in Northeastern forests. When developing climate stabilization, energy production and water security policies, it will be important to consider how evolving forest infrastructure modifies ecosystem services and their responses to extreme climate events over time. 

There is a rapidly growing need to communicate to the public and policymakers on the nature and impact of climate change and its associated extremes, which manifest themselves across essential Food-Energy-Water Systems (FEWS). The complexity of this nexus demands analytical tools that can capture the essence of FEWS with the climate system, which may be difficult to stage and implement from a computationally efficient point-of-view. Reduced Complexity Models (RCMs) can synthesize important facets of a system quickly and with less dependence on difficult-to-assign inputs. We report on the development of an RCM framework for the FEWS nexus, to serve as a basic research tool in facilitating parameter sensitivity experiments as well as a means to establish more insightful dialogue with stakeholders through joint scenario construction. Three stand-alone and coupled models at the basin scale have been configured using Stella Architect software to simulate: 1) major flows and storage of water, 2) power plant operations and subsequent impacts on river reaches; and 3) nitrogen (N) mobilization and transport from atmospheric and landmass sources to riverine receiving waters. The Delaware River Basin is chosen for a contemporary simulation test case. Modeled results are calibrated and validated using observed stream gauge data, indicating reliable model performance at the monthly and annual time steps (0.57 < NSE < 0.98). A set of single and multi-factor climate, technology, and policy experiments are then explored using the RCM framework. Basin-scale system sensitivities are investigated across a set of intensified climate extremes, revealing the crucial roles of sewage treatment and energy infrastructure for climate resilience, significant exacerbations as well as mitigations of thermal and N pollution under opposing climate extremes, and important tradeoffs between river temperature and electricity production that are explored with technology and policy scenarios. 

Change to global climate, including both its progressive character and episodic extremes, constitutes a critical societal challenge. We apply here a framework to analyze Climate-induced Extremes on the Food, Energy, Water System Nexus (C-FEWS), with particular emphasis on the roles and sensitivities of traditionally-engineered (TEI) and nature-based (NBI) infrastructures. The rationale and technical specifications for the overall C-FEWS framework, its component models and supporting datasets are detailed in an accompanying paper (Vörösmarty et al., this issue). We report here on initial results produced by applying this framework in two important macro-regions of the United States (Northeast, NE; Midwest, MW), where major decisions affecting global food production, biofuels, energy security and pollution abatement require critical scientific support. We present the essential FEWS-related hypotheses that organize our work with an overview of the methodologies and experimental designs applied. We report on initial C-FEWS framework results using five emblematic studies that highlight how various combinations of climate sensitivities, TEI-NBI deployments, technology, and environmental management have determined regional FEWS performance over a historical time period (1980–2019). Despite their relative simplicity, these initial scenario experiments yielded important insights. We found that FEWS performance was impacted by climate stress, but the sensitivity was strongly modified by technology choices applied to both ecosystems (e.g., cropland production using new cultivars) and engineered systems (e.g., thermoelectricity from different fuels and cooling types). We tabulated strong legacy effects stemming from decisions on managing NBI (e.g., multi-decade land conversions that limit long-term carbon sequestration). The framework also enabled us to reveal how broad-scale policies aimed at a particular net benefit can result in unintended and potentially negative consequences. For example, tradeoff modeling experiments identified the regional importance of TEI in the form wastewater treatment and NBI via aquatic self-purification. This finding, in turn, could be used to guide potential investments in point and/or non-point source water pollution control. Another example used a reduced complexity model to demonstrate a FEWS tradeoff in the context of water supply, electricity production, and thermal pollution. Such results demonstrated the importance of TEI and NBI in jointly determining historical FEWS performance, their vulnerabilities, and their resilience to extreme climate events. These infrastructures, plus technology and environmental management, constitute the “policy levers” which can actively be engaged to mitigate the challenge of contemporary and future climate change. 

Climate change continues to challenge food, energy, and water systems (FEWS) across the globe and will figure prominently in shaping future decisions on how best to manage this nexus. In turn, traditionally engineered and natural infrastructures jointly support and hence determine FEWS performance, their vulnerabilities, and their resilience in light of extreme climate events. We present here a research framework to advance the modeling, data integration, and assessment capabilities that support hypothesis-driven research on FEWS dynamics cast at the macro-regional scale. The framework was developed to support studies on climate-induced extremes on food, energy, and water systems (C-FEWS) and designed to identify and evaluate response options to extreme climate events in the context of managing traditionally engineered (TEI) and nature-based infrastructures (NBI). This paper presents our strategy for a first stage of research using the framework to analyze contemporary FEWS and their sensitivity to climate drivers shaped by historical conditions (1980–2019). We offer a description of the computational framework, working definitions of the climate extremes analyzed, and example configurations of numerical experiments aimed at evaluating the importance of individual and combined driving variables. Single and multiple factor experiments involving the historical time series enable two categories of outputs to be analyzed: the first involving biogeophysical entities (e.g., crop production, carbon sequestered, nutrient and thermal pollution loads) and the second reflecting a portfolio of services provided by the region’s TEI and NBI, evaluated in economic terms. The framework is exercised in a series of companion papers in this special issue that focus on the Northeast and Midwest regions of the United States. Use of the C-FEWS framework to simulate historical conditions facilitates research to better identify existing FEWS linkages and how they function. The framework also enables a next stage of analysis to be pursued using future scenario pathways that will vary land use, technology deployments, regulatory objectives, and climate trends and extremes. It also supports a stakeholder engagement effort to co-design scenarios of interest beyond the research domain.