Smart solutions for clean air: An AI-guided approach to sustainable industrial pollution control in coal-fired power plant

Lim JY 1 , Teng SY 2 , How BS 3 , Loy ACM 4 , Heo S 5 , Jansen J 6 Show all authors , Show PL 7 , Yoo CK 8

Affiliations 

  • 1 Integrated Engineering, Dept. of Environmental Science and Engineering, College of Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-Si, Gyeonggi-do, 17104, Republic of Korea; Korea Biochar Research Center, APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering, Korea University, Seoul, 02841, Republic of Korea
  • 2 Radboud University, Institute for Molecules and Materials, P.O. Box 9010, 6500 GL, Nijmegen, the Netherlands; Department of Circular Chemical Engineering (CCE), Faculty of Science and Engineering, Maastricht University, Urmonderbaan 22, 6162, Geleen, The Netherlands
  • 3 Research Centre for Sustainable Technologies, Faculty of Engineering, Computing and Science, Swinburne University of Technology, Jalan Simpang Tiga, 93350, Kuching, Sarawak, Malaysia
  • 4 Department of Chemical and Biological Engineering, Monash University, Clayton, Victoria, 3800, Australia
  • 5 Integrated Engineering, Dept. of Environmental Science and Engineering, College of Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-Si, Gyeonggi-do, 17104, Republic of Korea
  • 6 Radboud University, Institute for Molecules and Materials, P.O. Box 9010, 6500 GL, Nijmegen, the Netherlands
  • 7 Department of Chemical Engineering, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates; Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500, Semenyih, Selangor Darul Ehsan, Malaysia
  • 8 Integrated Engineering, Dept. of Environmental Science and Engineering, College of Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-Si, Gyeonggi-do, 17104, Republic of Korea. Electronic address: ckyoo@khu.ac.kr
Environ Pollut, 2023 Oct 15;335:122335.
PMID: 37558197 DOI: 10.1016/j.envpol.2023.122335

Abstract

Conventional fossil fuels are relied on heavily to meet the ever-increasing demand for energy required by human activities. However, their usage generates significant air pollutant emissions, such as NOx, SOx, and particulate matter. As a result, a complete air pollutant control system is necessary. However, the intensive operation of such systems is expected to cause deterioration and reduce their efficiency. Therefore, this study evaluates the current air pollutant control configuration of a coal-powered plant and proposes an upgraded system. Using a year-long dataset of air pollutants collected at 30-min intervals from the plant's telemonitoring system, untreated flue gas was reconstructed with a variational autoencoder. Subsequently, a superstructure model with various technology options for treating NOx, SOx, and particulate matter was developed. The most sustainable configuration, which included reburning, desulfurization with seawater, and dry electrostatic precipitator, was identified using an artificial intelligence (AI) model to meet economic, environmental, and reliability targets. Finally, the proposed system was evaluated using a Monte Carlo simulation to assess various scenarios with tightened discharge limits. The untreated flue gas was then evaluated using the most sustainable air pollutant control configuration, which demonstrated a total annual cost, environmental quality index, and reliability indices of 44.1 × 106 USD/year, 0.67, and 0.87, respectively.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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