Optimizing Wastewater Treatment for a Carbon-Neutral Future: A Data-Driven Approach

Abstract

The research explores the pivotal role of wastewater treatment plants (WWTPs) in addressing energy consumption and greenhouse gas (GHG) emissions to achieve carbon neutrality (CN) and the United Nations' Sustainable Development Goals (SDGs), notably promoting health, clean water, and sustainable energy while mitigating climate change impacts. In 2023, Thailand will have wastewater treatment plants capable of handling around 620 million cubic meters, or about 45% of wastewater produced, and data reveals that 3,621.574 thousand kg CO2 eq/year is emitted from wastewater treatment, highlighting the need for sustainable practices to reduce emissions. The objective of this research is to develop a framework that integrates structured query language (SQL) with life cycle inventory (LCI) methodologies to create a comprehensive database for WWTPs. This includes goal and scope determination in assessment to identify inputs, outputs, and emissions throughout the WWTPs process lifecycle. This framework aims to analyze energy consumption and reduce GHG emissions by examining the correlations between WWTPs operational parameters and electricity consumption, thereby contributing to carbon neutrality, and supporting the United Nations' Sustainable Development Goals (SDGs). These findings emphasize the critical importance of understanding the relationship between WWTP operational efficiency and energy consumption to effectively mitigation for enhance and optimize efficiency in reducing energy consumption and GHG emissions in WWTPs. Ultimately, this framework aims to enhance and optimize the efficiency of reducing energy consumption and GHG emissions in WWTPs, thereby contributing to CN and the SDGs.