Author : Paniz Mohammadpour
Release : 2023
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Maximizing Human-Environmental Security by Analyzing the Food, Energy and Water Interconnections - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Maximizing Human-Environmental Security by Analyzing the Food, Energy and Water Interconnections write by Paniz Mohammadpour. This book was released on 2023. Maximizing Human-Environmental Security by Analyzing the Food, Energy and Water Interconnections available in PDF, EPUB and Kindle. Food, energy, and water (FEW) are among the essential resources for living on the earth. However, accelerating global population growth, increasing food, energy, water resource consumption, climate change, and uneven distribution of resources have limited FEW availability and accessibility, endangering both human life and the environment. Therefore, to balance human-environmental security, the sustainable usage and management of these three vital resources are necessary. Through this dissertation, my main goal is to use the FEW Nexus as a framework to quantify social and environmental security by investigating food, energy, and water resources systems and their interlinkages across scales with the final goal of informing decision-makers and development actors to develop new solutions to maximize the synergies among resources and optimize their social-environmental impacts. In that regard, I utilized and developed FEW nexus models to inform regional management decisions that enhances FEW resources security with the focus on 1) human access to enough and safe resources and 2) environmental quality induced by food production and consumption. With this dissertation, I presented an approach to quantify FEW security at regional scale and highlighted cases in Ecuador, Peru, and Bolivia where national statistics leave out important regional variation. The outcome was an integrated approach to quantify security measures that can be implemented at multiple spatial scales and institutional levels. This approach can not only provide insight into FEW security in Ecuador, Peru, and Bolivia but can also be an effective tool for assessing multiple development priorities simultaneously throughout the world. In support of the Chesapeake Bay Watershed restoration and water quality improvement, I focused on the food and agricultural system as the primary source of nitrogen pollution in the watershed and a main driver of water quality degradation in the Bay. In this regard, I created a mass flow model of nitrogen embedded in the food production chain throughout the Chesapeake Bay Watershed that separates phases of the production and consumption processes for crops, live animals, and animal products and considers commodity trade at each phase by combining aspects of both nitrogen footprint and nitrogen budget models. Also, by tracking nitrogen embedded in products imported and exported in these processes, I distinguished between direct nitrogen pollution and nitrogen pollution externalities (displaced N pollution from other regions) from outside of the Bay. Using the developed model, I determined the spatiotemporal drivers of nitrogen loss to the environment from the food chain within the watershed. I also show that at the watershed scale, trade has reduced the food chain nitrogen loss by about 40 million metric tons. The model's ability to distinguish between nitrogen loss from local and non-local (due to trade) sources makes it a potential tool to optimize regional domestic production and trade to meet local watershed's human protein needs while minimizing the resulting nitrogen loss. Overall, this model has the potential to quantify the effect of various decision scenarios, including trade, dietary choices, production patterns, and agricultural practices, on the food production chain nitrogen loss at multiple scales and so as a metric to evaluate environmental protection futures. Using the nitrogen flow model of Chesapeake Bay Watershed, I completed scenario analysis to investigate the effects of simulated future agricultural changes and management scenarios on agricultural N loss in the Chesapeake Bay Watershed, focusing on the food production chain's most influential factors (drivers of N loss). I tested the effects of future scenarios, including crop and animal production in 2050, management scenarios focusing on crop and animal production efficiency improvement in 2020, and a combined scenario of these two scenarios in 2050 on agricultural N loss reduction. Through this work, I concluded that, considering both future and management scenarios (combined scenario), N loss from food production chain will drop compared to the baseline scenario, implying that despite an increase in the future N loss due to the projected agriculture intensification, we can still reduce the N loss if we improve the controlling factors for the efficiency of crops and animals. The results can improve water quality in the Bay by informing targeted management decisions at croplands and livestock farms to diminish N loss inputs in the watershed.