LEED Green Associate Study Guide

This review presents the developments in artificial intelligence technologies for environmental pollution controls. A number of AI approaches, which start with the reliable mapping of nonlinear behavior between inputs and outputs in chemical and biological processes in  terms of prediction models to the emerging optimization and control algorithms that study the  pollutants removal processes and intelligent control systems, have been developed for environmental clean-ups. The characteristics, advantages and limitations of AI methods, including single and hybrid AI methods, were overviewed. Hybrid AI methods exhibited synergistic effects, but with computational heaviness.

Introduction: Sustainable water and wastewater services are critical to providing the American public with clean and safe water and helping ensure the environmental, economic, and social sustainability of the communities that utilities serve. Utilities across the country face tremendous challenges, such as aging infrastructure, an aging workforce, increasing mandates, and competing priorities within the communities they serve. The purpose of this document is to assist utility leaders with implementing proven and effective practices over time to improve their operations and move toward sustainability, at a pace consistent with their needs and the needs of their communities. It provides utility leaders with a cohesive structure to help them address various challenges proactively and with confidence. The practices described in this document reflect the lessons learned and the practical experience utilities have derived as they have improved their operations. A utility can use this document to identify specific opportunities for improvement and draw on the example practices to create an individualized “roadmap” to more sustainable operations.

Water resources management should be assessed under climate change conditions, as historic data cannot replicate future climatic conditions. - Climate change impacts on water resources are bound to affect all water uses, i.e., irrigated agriculture, domestic and industrial water supply, hydropower generation, and environmental flow (of streams and rivers) and water level (of lakes). - Bottom-up approaches, i.e., the forcing of hydrologic simulation models with climate change models’ outputs, are the most common engineering practices and considered as climate-resilient water management approaches. - Hydrologic simulations forced by climate change scenarios derived from regional climate models (RCMs) can provide accurate assessments of the future water regime at basin scales.