https://ijitis.org/index.php/EIL <p><em><strong>Environmental Industry Letters (EIL)</strong> is an <strong>open-access </strong>and <strong>free-of-charge</strong> journal which offers both an environmental perspective on the current industries and a practical approach to the development of environmental industries. Both developed and developing nations may need to address this issue. It should be noted that by introducing this new viewpoint into scientific societies, it may result in a more limited understanding of how industry and the environment are related. Last but not least, it should be noted that environment, industry, sustainable development, circular economy, and green economy are among this journal's most crucial keywords.</em></p> TULTECH en-US Environmental Industry Letters 2806-2965 https://ijitis.org/index.php/EIL/article/view/196 <p>Numerous water supply utilities around the world face challenges in successfully distributing water in distribution networks due to increased urbanization, population growth, and climate change. The age of the water supply facilities is a particular issue, which is aggravated by their inadequate maintenance and operation. Due of this, many water utilities have recently adopted integrated and intelligent water supply solutions that leverage information technology, artificial intelligence, big data, and IOT (Internet of Things) to handle water supply system issues. In this study, a smart dashboard of water distribution network operation was developed to improve the effectiveness of Tehran, Iran's water delivery system. In order to properly manage water resources, the article proposes adopting knowledge management systems in Tehran's municipal water distribution and transmission networks.</p> Amirhossein Kiyan Mohammad Gheibi Reza Moezzi Kourosh Behzadian Copyright (c) 2022 Environmental Industry Letters 2023-03-14 2023-03-14 1 1 46 63 10.15157/EIL.2023.1.1.46-63 https://ijitis.org/index.php/EIL/article/view/191 <p>Controlling air pollution in megacities is crucial from both a health and environmental perspective. Air pollution is a pervasive problem in these densely populated cities and must be effectively managed to promote sustainability. This study presents a framework for the intelligent management of air pollution control systems in developing nations. The framework was developed through the use of an expert agreement model involving five managers from Tehran. The results indicate that the Decision Support System (DSS) is equipped with calibrated sensors for monitoring air quality. Additionally, the concentration of air pollutants can be determined through the application of machine learning algorithms and the analysis of historical data. Rapid response methods are then applied to mitigate the acute and chronic effects of air pollution. The DSS also incorporates citizens' feedback to evaluate the effectiveness of air pollution control measures. Implementing this model in developing nations' smart cities can help achieve several of the United Nations' Sustainable Development Goals (SDGs), such as good health and well-being, sustainable cities and communities, climate action, and life on land.</p> Amirhossein Kiyan Mohammad Gheibi Mehran Akrami Reza Moezzi Kourosh Behzadian Copyright (c) 2022 Environmental Industry Letters 2023-02-19 2023-02-19 1 1 10 27 10.15157/EIL.2023.1.1.10-27 https://ijitis.org/index.php/EIL/article/view/192 <p>By locating useful characteristics and determining the perfect circumstances to meet ideal water quality criteria, this study seeks to improve the operation of a water treatment facility. The research comprises gathering data from personnel and exposure to system events, as well as from explicit and tacit knowledge sources. The problem at hand is a multi-objective, multi-criteria problem with many variables in spatial and temporal dimensions, requiring the use of powerful tools for analysis. All engineering problems have an objective function consisting of smaller sub-functions, typically in the form of cost or error minimization. To solve such problems, optimization methods based on natural patterns have been introduced, including genetic algorithms, evolutionary algorithms, and particle mass optimization. By optimizing the operation process of the water treatment plant, the quality of the water provided can be improved to meet standards set by organizations such as Iran 1053, WHO, and EPA. The study's findings could be used to implement changes to the plant's management and operation processes to achieve more ideal water quality conditions. Ultimately, the optimization of water treatment plant processes could have significant positive impacts on public health and well-being, as well as the environment.</p> Amirhossein Kiyan Mohammad Gheibi Mehran Akrami Reza Moezzi Kourosh Behzadian Hadi Taghavian Copyright (c) 2022 Environmental Industry Letters 2023-02-22 2023-02-22 1 1 28 45 10.15157/EIL.2023.1.1.28-45 https://ijitis.org/index.php/EIL/article/view/190 <p>Filtration is a crucial step in the water treatment process, typically preceding disinfection. Filters trap microorganisms and suspended solids, reducing their amount in the environment. The latest technology in filtration is ceramic filters, and in this study, the performance of silicon carbide ceramic filters (SIC) is evaluated. These filters were installed at three different locations within a water treatment plant (entrance storage, raw water, and backwash water), and changes in physical and chemical water parameters were measured. Results indicate high efficiency in turbidity removal, effectively clarifying volatile suspended solids (VSS) and fixed suspended solids (FSS). The turbidity removal efficiency was 99% for entrance storage and 65% for raw water. The SWOT (Strengths, Weaknesses, Opportunities, and Threats) matrix was used to analyse the results of the SIC and highlight its strengths, weaknesses, opportunities, and threats.</p> Mohammad Gheibi Benyamin Chahkandi Kourosh Behzadian Mehran Akrami Reza Moezzi Copyright (c) 2022 Environmental Industry Letters 2023-02-17 2023-02-17 1 1 1 9 10.15157/EIL.2023.1.1.1-9