skip to main content


Search for: All records

Creators/Authors contains: "Jain, Atul K."

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. 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. 
    more » « less
  2. 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. 
    more » « less
  3. 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. 
    more » « less
  4. 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. 
    more » « less
  5. Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO 2 enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle. 
    more » « less
  6. Abstract

    A land process model, Integrated Science Assessment Model, is extended to simulate contemporary soybean and maize crop yields accurately and changes in yields over the period 1901–2100 driven by environmental factors (atmospheric CO2level ([CO2]) and climate), and management factors (nitrogen input and irrigation). Over the twentieth century, each factor contributes to global yield increase; increasing nitrogen fertilization rates is the strongest driver for maize, and increasing [CO2] is the strongest for soybean. Over the 21st century, crop yields are projected under two future scenarios, RCP4.5‐SSP2 and RCP8.5‐SSP5; the warmer temperature drives yields lower, while rising [CO2] drives yields higher. The adverse warmer temperature effect of maize and soybean is offset by other drivers, particularly the increase in [CO2], and resultant changes in the phenological events due to climate change, particularly planting dates and harvesting times, by 2090s under both scenarios. Global yield for maize increases under RCP4.5‐SSP2, which experiences continued growth in [CO2] and higher nitrogen input rates. For soybean, yield increases at a similar rate. However, in RCP8.5‐SSP5, maize yield declines because of greater climate warming, extreme heat stress conditions, and weaker nitrogen fertilization than RCP4.5‐SSP2, particularly in tropical and subtropical regions, suggesting that application of advanced technologies, and stronger management practices, in addition to climate change mitigation, may be needed to intensify crop production over this century. The model also projects spatial variations in yields; notably, the higher temperatures in tropical and subtropical regions limit photosynthesis rates and reduce light interception, resulting in lower yields, particularly for soybean under RCP8.5‐SSP5.

     
    more » « less
  7. Abstract. Evapotranspiration (ET) is critical in linking global water, carbon andenergy cycles. However, direct measurement of global terrestrial ET is notfeasible. Here, we first reviewed the basic theory and state-of-the-artapproaches for estimating global terrestrial ET, including remote-sensing-based physical models, machine-learning algorithms and land surfacemodels (LSMs). We then utilized 4 remote-sensing-based physical models,2 machine-learning algorithms and 14 LSMs to analyze the spatial andtemporal variations in global terrestrial ET. The results showed that theensemble means of annual global terrestrial ET estimated by these threecategories of approaches agreed well, with values ranging from 589.6 mm yr−1(6.56×104 km3 yr−1) to 617.1 mm yr−1(6.87×104 km3 yr−1). For the period from 1982 to 2011, boththe ensembles of remote-sensing-based physical models and machine-learningalgorithms suggested increasing trends in global terrestrial ET (0.62 mm yr−2 with a significance level of p<0.05 and 0.38 mm yr−2 with a significance level of p<0.05,respectively). In contrast, the ensemble mean of the LSMs showed nostatistically significant change (0.23 mm yr−2, p>0.05),although many of the individual LSMs reproduced an increasing trend.Nevertheless, all 20 models used in this study showed that anthropogenicEarth greening had a positive role in increasing terrestrial ET. Theconcurrent small interannual variability, i.e., relative stability, found inall estimates of global terrestrial ET, suggests that a potentialplanetary boundary exists in regulating global terrestrial ET, with the value of this boundary beingaround 600 mm yr−1. Uncertainties among approaches were identified inspecific regions, particularly in the Amazon Basin and arid/semiaridregions. Improvements in parameterizing water stress and canopy dynamics,the utilization of new available satellite retrievals and deep-learning methods,and model–data fusion will advance our predictive understanding of globalterrestrial ET. 
    more » « less