Simulation of the Environmental Impact of Industries in Smart Cities
Amira Ragab, Aya Osama, Amna Ramzy
Abstract
Life Cycle Assessment (LCA) is commonly used as an environmental assessment for products, services or activities; however, LCA is a process that facilitates optimal design and decision making. By combining LCA with artificial intelligence and machine learning, many uncertainties in early stages of design can be prevented which directly contributes to the performance assessment of smart cities environmentally, socially and economically. The aim of this study is to demonstrate the use of Environmental life cycle assessment (E-LCA) in three different well-established industries of three different volumes namely: food, glass and plastics industries. Material and Energy Flow Analysis (MEFA) using Umberto Efficiency + was carried out initially prior to LCA using Umberto LCA + to establish the inventory. The LCA has been conducted according to ISO 14040/14044 standards. Cradle-to-Gate system boundary was set considering the transportation of raw materials, energy and waste handling. Each case study is regarded as a sample representing the industry’s environmental burden respectively. The case studies are chosen with different production scale categorized under small and medium-sized enterprises (SMEs). The case representing the food industry which is considered a Small Enterprise proved to have a higher equivalent carbon footprint than the Medium Enterprise concerned with plastics recycling which points out the importance of performing LCA on all industrial scales.