Computational Model Based on Grey Systems to Determine Air Quality in a Maritime Industry

Air quality is a real problem around the world, specifically in Peru there are many social problems about the air pollution impact, specifically contaminants as PM10, SO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, NO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, or CO, due to diverse economic activities, such as mining industry, maritime industry, or manufacturing industry. In this work, a computational model based on grey systems theory, specifically the center-point triangular wight functions (CTWF), was applied. In turn, a case study on a maritime industry in Peru, was conducted. In the case study were analyzed four parameters of air quality: PM10, SO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, NO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, and CO), during two periods: during and after the COVID pandemic. The results showed that during the COVID pandemic the air quality level was lower than after the COVID pandemic. In addition, the SO2 parameter showed more variability during both periods. The results of this work could help local or national government make the best decision on air quality management.