INFEWS: U.S.-China: An Integrated Technology-Environment-Economic Modeling Platform for FEW Systems in Arid Regions

从全球角度来看，粮食-能源-水(少数)联系包含紧密相连的粮食、能源和水资源系统。随着世界人口到2050年预计将达到90亿，人们将迫切需要在这三个系统之间平衡不同的资源，以实现不同的用户目标，而不会给提供这些资源的生态系统带来不必要的压力。该研究项目将利用湿废物转化和可再生能源(如风能和太阳能)发电，以收集和过滤用于作物灌溉的咸水，并在通常不用于此类目的的土壤中生产藻类。该项目的目标是创建一个新的建模平台，利用来自伊利诺伊大学香槟分校(UIUC)和中国农业大学(CAU)两个不同团队的研究投入，将技术、环境和经济学融为一体。这一新平台可能被用来确定利用未得到充分利用的资源和可再生能源生产粮食的备选方案，特别是在干旱地区的少数几个系统(AR-FEWS)。PIS计划测试这样一种假设，即在获得可再生能源的干旱地区，为高价值作物灌溉收集非传统来源的水资源将具有成本效益和环境可行性。如果成功，这项研究可以通过确定在经济和环境上可行的技术来生产粮食和能源，同时节约水资源，从而加强美国和其他干旱地区的少数几个系统。该项目将利用美国和中国团队的研究投入，开发一个无缝的系统建模工具，集成技术、环境和经济成分，对AR-FEWS进行整体定量分析。将把重点特别放在拥有边际土地和水以及丰富的可再生能源的干旱地区，在这些地区可以加强资源生产和使用方面的协同增效作用。PIS将确定综合系统的关键参数，以开发基于过程的模型，包括对湿生物废物和藻类的水热液化(HTL)转化的优化，藻类生物质和水培食品生产所需的废水处理方法，以及用废水水培生产食品的特性。这些过程模型将与区域范围内的环境和经济分析相结合，以确定利用边际资源和可再生能源的潜力在干旱地区生产粮食的技术解决办法和政策选择。集成建模工具将在中国西北部的干旱地区进行测试。该项目将与美国国家科学基金会正在进行的INFEWS项目(INFEWS#1739788，通过营养循环的综合技术-环境-经济建模促进玉米带的少数系统弹性)保持一致，以开发一个通用的建模工具，用于为可持续和有弹性的少数系统确定稳健的最佳解决方案，并评估在区域范围内采用技术的可行性。该奖项反映了国家科学基金会的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The Food-Energy-Water (FEW) Nexus, from a global perspective, contains closely interconnected resource systems of food, energy, and water. As the world's population expands to an expected 9 billion by 2050, there will be an urgent demand to balance different resources across these three systems to achieve different user goals without putting undue strain on the ecosystems that provide these resources. This research project will utilize both wet waste conversion and renewable energy sources, such as wind and solar, to produce electricity for harvesting and filtering saline water for crop irrigation and algae production in soils not normally used for such purposes. The goal of the project is to create a new modeling platform that ingrates technology, environment, and economics using research inputs from two different teams in this collaboration - one from the University of Illinois at Urban-Champaign (UIUC) and one from the China Agricultural University (CAU). This new platform could potentially be used to identify options for harnessing underutilized resources and renewable energy to produce food, particularly in arid region FEW systems (AR-FEWS). The PIs plan to test the hypothesis that harvesting non-conventional sources of water for high-value crop irrigation will be cost effective and environmentally feasible in arid regions with access to renewable energy sources. If successful, this research could strengthen FEW systems in the US and other countries in under-used arid regions by identifying economically and environmentally viable technologies to produce food and energy while conserving water resources.Using research inputs from the U.S. and China teams, this project will develop a seamless system modeling tool that integrates technological, environmental, and economic components to conduct holistic quantitative analysis of AR-FEWS. A particular focus will be put on arid regions with marginal land and water and plentiful renewable energy sources where the synergies in resources production and use can be enhanced. The PIs will define key parameters of the integrated system to develop process-based models, including optimization for hydrothermal liquefaction (HTL) conversion of wet biowaste and algae, wastewater treatment methods needed for algal biomass and hydroponic food production, and characteristics of food produced hydroponically with wastewater. The process models will be integrated with environmental and economic analyses at the regional scale to identify technological solutions and policy options for harnessing the potential of marginal resources and renewable energy to produce food in arid regions. The integrated modeling tool will be tested in arid areas in Northwestern China. This project will be aligned with an ongoing NSF-funded INFEWS project (INFEWS #1739788, Advancing FEW System Resilience in the Corn Belt by Integrated Technology-Environment-Economics Modeling of Nutrient Cycling) to develop a generic modeling tool that will be used to identify robust optimal solutions for sustainable and resilient FEW systems and assess the feasibility of technology adoption at regional scales.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.