(162c) Electricity Planning for Ecosystems and Society: A Spatial-Temporal Approach Considering Cost, Societal Benefit and Environmental Justice

Recent years have seen an increase in both the frequency and severity of extreme weather events such as heatwaves, floods, and freezing conditions¹, with climate change and greenhouse gas (GHG) emissions playing a significant role. Emissions Gap Report 2023 by UN Environmental Programme (UNEP) emphasizes the urgent need for global actions to meet the Paris Agreement goals: by 2030 the predicted GHG emissions must decrease by 28% for the 2 ËšC pathway². Furthermore, according to data from World Health Organization (WHO), hazardous air pollutants are contributing to high mortality rates of around 7 million per year, and almost 99% of people in the world live in places that do not meet the WHO air quality guidelines levels³. These facts highlight the pressing importance of implementing environmental health and safety measures. Among all the sources of GHG emissions and air pollutants, fossil fuel electricity power plants are one of the top contributors^4,5. Studies show that some minority groups such as people of color, people with lower income, and places with high unemployment rate, are more likely to be vulnerable and exposed to worse air conditions, which leads to environmental injustice^6–8. Therefore, our work is motivated by these facts and focuses on finding solutions to improve air quality and consider the needs of people. Previous work related to sustainable electricity planning^9,10 only focused on minimizing economic costs, and they rely on imposing environmental constraints and traditional equipment as ways to control the emissions. Our work is inspired by nature’s ability of removing pollutants and we include ecosystems as unit operations to work in synergy with engineering technologies to improve air quality, and this method is called Techno-Ecological Synergy (TES)¹¹. Studies in this area design ecosystems and quantify their capacity in purifying air or water quality to achieve harmony between engineering systems and nature^12,13, however, TES has not been applied to electricity generation planning. Quantifying societal costs and environmental justice have also been mostly ignored. In this work, we develop a spatial-temporal model that integrates hourly electricity generation planning and strategic design of reforestation locations over time. Moreover, this model will consider societal cost and environmental justice as important factors in decision-making.

We employ the Techno-Ecological Synergy (TES) framework that integrates traditional emission control equipment with natural ecosystem processes to remove carbon dioxide and hazardous air pollutants emitted by power plants. In this work, four traditional emission control technologies are considered: selective catalytic reducer, flue gas desulfurization, baghouse filter, and aqueous monoethanolamine (MEA) solution for removal of NO₂, SO₂, PM₁₀, and CO₂, respectively. Trees are considered as an ecological unit operation in this work. The capacity of trees is quantified by dry deposition flux which is related to vegetation parameters. Air pollution modeling performed by CALPUFF version 7, an advanced non-steady-state meteorological and air quality modeling system, was utilized to obtain the spatial concentration and dry deposition maps for NO₂, SO₂, and PM₁₀ before and after land use change from original to tree covers. Besides, we used i-Tree Canopy to calculate carbon sequestration by trees, and the growth dynamics of trees were calculated by Forest Vegetation Simulator (FVS). To quantify societal costs, we obtain spatial social impact maps from BenMAP-CE, an open-source software tool designed to estimate the number of fatalities and illnesses attributable to air pollution. For incorporating environmental justice considerations, the block group level demographic index (calculated based on the average of five socioeconomic indicators; low-income, unemployment, limited English, less than high school education, and low life expectancy) was retrieved from EJScreen, an Environmental Protection Agency (EPA)'s tool for mapping and screening environmental justice concerns. This data was then integrated with our case study's specific geographic units using QGIS, ensuring a comprehensive analysis that aligns with our defined parameters. We conducted a case study over the region of Louisville, KY with nine power plants that utilize a mix of energy sources including coal, natural gas, and hydroelectric power. The optimization problem was formulated as a multi-objective mixed-integer linear program (MILP) and was solved in Julia by Gurobi solver to minimize engineering costs, societal costs, and environmental injustice. We explored three different scenario groups including conventional, techno-centric, and TES to find the best solution to balance the three objectives above and emission goals.

This work incorporates hourly electricity planning, emission control technologies, and spatial-temporal landscape design, in which the engineering systems work with nature in synergy to achieve both air quality and people-positive targets. The findings reveal that Techno-Ecological Synergy (TES) scenario groups demonstrate superior performance over time with lower overall costs. As trees become mature, their capacity to remove carbon dioxide and air pollutants will be higher than the demand of power plants, achieving greater environmental benefits by taking up additional carbon and emissions emitted by other sources. Furthermore, the cost of planting trees will be much less than traditional technologies. With the presence of more tree cover, electricity power plants will have more flexibility in running without the burden of worsening air quality during high-demand days. We also find out by setting additional objectives of social cost and environmental justice index, the results of time and location for tree planting can be very different: these objectives will prioritize reforestation at locations with high population densities and high percentages of minority groups and in the meantime start to plant trees at earlier years. From the Pareto front, we notice there are trade-offs between (1) engineering costs & social costs; (2) engineering costs & environmental justice index. The reason could be these locations have a relatively low dry deposition flux after land-use change according to air pollution modeling, so more trees and technologies are needed which makes the ecological and technological costs higher. However, people-positive is essential and our results show the necessity to consider it in decision-making. In summary, this work optimizes hourly electricity schedules, emission control technologies usage, time and locations for reforestation. It highlights the benefits of including trees as unit operations to improve air quality and emphasizes the significance of considering societal and minority groups in design strategies. Our aim is to foster a sustainable, nature-positive, and people-positive world, demonstrating how environmental solutions can be beneficial to both nature and diverse human communities .

Reference

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