Version 1
: Received: 28 August 2024 / Approved: 29 August 2024 / Online: 29 August 2024 (12:25:01 CEST)
How to cite:
Asim, M. M.; Amjad, M. M.; Sarfaraz, A.; Ali, Z. Analysis and Monitoring of Air Quality through Discrete Time Markov Chai. Preprints2024, 2024082149. https://doi.org/10.20944/preprints202408.2149.v1
Asim, M. M.; Amjad, M. M.; Sarfaraz, A.; Ali, Z. Analysis and Monitoring of Air Quality through Discrete Time Markov Chai. Preprints 2024, 2024082149. https://doi.org/10.20944/preprints202408.2149.v1
Asim, M. M.; Amjad, M. M.; Sarfaraz, A.; Ali, Z. Analysis and Monitoring of Air Quality through Discrete Time Markov Chai. Preprints2024, 2024082149. https://doi.org/10.20944/preprints202408.2149.v1
APA Style
Asim, M. M., Amjad, M. M., Sarfaraz, A., & Ali, Z. (2024). Analysis and Monitoring of Air Quality through Discrete Time Markov Chai. Preprints. https://doi.org/10.20944/preprints202408.2149.v1
Chicago/Turabian Style
Asim, M. M., Amna Sarfaraz and Zaiwar Ali. 2024 "Analysis and Monitoring of Air Quality through Discrete Time Markov Chai" Preprints. https://doi.org/10.20944/preprints202408.2149.v1
Abstract
The term Air Quality (AQ) pertains to the standard of air, which has a direct impact on the health and well-being of individuals. It is crucial to maintain high Air Quality (AQ), for better health and productivity. Though most of people spend more time indoors nowadays, it is not to be overlooked that the pollutant concentration in indoor air is directly linked to the outdoor air quality. Due to the changes in occupancy patterns, outdated maintenance of ventilation systems, and structural flaws in buildings, the indoor air is significantly polluted; pollutants emitted outdoors enter indoor air through open windows, ventilation systems and infiltration. In this paper, we have proposed a new technique, DTMCPM (discrete-time Markov chain (DTMC) model for the analysis and forecasting of AQ, using the power method). Specialized sensors and equipment to measure different pollutants, such as particulate matter, ozone, nitrogen dioxide, sulfur dioxide, benzene and toluene, are used to collect data by the Institute of Pakistan Air Quality Monitor in various cities; the data is converted to US EPA standard for all pollutant species. This data is used to calculate the transition matrix, steady-state values and mean return rate for the analysis of IAQ. The calculated and actual return rates have been compared and the proposed model is found to have a low average prediction error of 2.356%.
Keywords
Air Quality (AQ); Discrete-Time Markov Chain (DTMC); Environmental Data Analysis; Indoor Air Quality (IAQ; Air Pollution Forecasting; Sensor Networks
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
