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.

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The most important transition of the energy matrix in Peru was characterized by an economic bonanza between the years 2009 - 2011 and, whose energy intensity (I.E) was reflected by the accelerated growth of the GDP; which, caused an exponential increase in the energy demand of Peru and, whose multiplying effect was produced by the energy exchange of the predominance of Hydroelectric Energy towards the development of Natural Gas with the Camisea Gas Megaproject, however, it was not considered the impact of other factors. In this sense, the present study requires contextualizing the Energy Trilemma: 1) the country's energy security; through an energy efficiency policy in response to meeting demand in line with GDP growth, 2) energy equity, for the access of quality energy and accessible prices to more vulnerable populations with a diversified energy matrix; 3) environmental sustainability, to describe the Environmental Commitments of Peru with the COP24. The methodology is based on a macroeconomic-energetic model, whose architecture begins with historical information between the years 1970-2016 with respect to GDP vs. primary energy consumption; to then calculate the annual energy intensity of Peru and its CO2 emission according to the polluting factor of each primary matter. Followed, using projections of the GDP from 2017 to the year 2035 (3.8% per year - Conservative case with information from the World Bank) and 3 scenarios of decrease in energy intensity of 1%, 1.5% and 2% per year, may increase energy efficiency and reduce the emission of CO2 in the proportion of 10.4%, 15.2% and 19.6% respectively between 2017-2035. As a result, the total energy consumption will be estimated up to the year 2035 in Millions of TOE, according to each scenario of variation in energy intensity (ΔI. E). and with the forecasts in the distribution of the energy matrix of the years 2025 and 2035 through the BAU methodology, its forecasts of each primary material will be known (Natural Gas, Oil, Coal, Hydroelectric, Renewable Energy, others) until the year 2035 This will allow us to know the forecast of CO2 emissions based on each pollution factor of the primary sources and energy intensity levels predicted with respect to the base case (Δ IE = 0). Finally, Peru's commitment to COP24 will be evaluated based on the per capita correlation of the country / world population in the estimation of the cumulative maximum emission limit of 2.13 GtCO2 between 2017-2035 for Peru, if the temperature is not increased more than 2 ° C for the year 2100 and guarantee the demand of Peru under an optimized Energy Trilemma.