Kassian T.T. Amesho1, Yuan-Chung Lin This email address is being protected from spambots. You need JavaScript enabled to view it.1,2, Zhou-Wei Gong1, Feng-Chih Chou1, Pei-Cheng Cheng1, Tsu-Nai Wang3, Pei-Shih Chen3, Kang-Shin Chen1, Ken-Lin Chang1, Chien-Hung Lee3 

1 Institute of Environmental Engineering, National Sun Yat-sen University, Kaohsiung 804, Taiwan
2 Center for Emerging Contaminants Research, National Sun Yat-Sen University, Kaohsiung 804, Taiwan
3 Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 807, Taiwan

Received: August 18, 2021
Revised: September 29, 2021
Accepted: October 6, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.4209/aaqr.210206  

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Cite this article:

Amesho, K.T.T., Lin, Y.C., Gong, Z.W., Chou, F.C., Cheng, P.C., Wang, T.N., Chen, P.S., Chen, K.S., Chang, K.L., Lee, C.H. (2021). Assessment of PM2.5 Chemical Composition and Air Quality Monitoring: Implications of Air Pollutants Emissions from a Night Market in Kaohsiung City, Taiwan. Aerosol Air Qual. Res. https://doi.org/10.4209/aaqr.210206


  • Air pollutants emissions from a night market was investigated.
  • Industrial Source Complex Short-Term (ISCST3) model for simulation of PM2.5.
  • Average concentration of 29–61 µg m3 for PM2.5 was recorded during opening hours.
  • Metallic elements concentrations in PM2.5 in an increasing order of Na > Fe > Al > Ca.
  • Traditional pollutants such as NOx, SO2, and CO are investigated.


There are around 300 night markets in Taiwan, and they have been drawing an increasing number of tourists in recent years. As a result, public awareness over air quality in the night markets has grown tremendously. In response to this, a specific night market in Kaohsiung City was chosen for this study in order to characterize the existing air quality in and around the night markets. In this present study, we employed an Industrial Source Complex Short-Term (ISCST3) air quality model for the simulation of PM2.5 diffusions. The model as a technique can simulate the pollutants emissions, diffusions, transportation, and pollution sources in specific areas and subsequently evaluate the influence between the source and the receiver. Therefore, we compared pollutants emissions data from several air quality monitoring stations with our sampling data of three different sampling sites in Kaohsiung City. The findings of this study showed that the average concentration of PM2.5 was in the range of 29-61 µg m-3 during opening hours of the night market, whereas the average concentration of PM2.5 range was between 22-38 µg m-3 before the night market opening hours. The concentration of metallic elements (ME) (Mg, Na, Cr, Mn, Fe, Cu, Al, Ba, Cd, Pb and Ca) was determined with the support of Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). During the night market opening hours, the result disclosed that the ME concentrations in PM2.5 was in an increasing order as follows: Na>Fe>Al>Ca. With respect to the concentration of carbonaceous species, our results showed that the highest total carbon (TC) concentration was found to be 6.52 µg m-3 during the downwind sampling interval. The highest elemental carbon (EC) and organic carbon (OC) concentration were found to be 6.53 µg m–3 and 2.70 µg m–3 of the PM2.5 concentration, respectively. This study’s findings have significant consequences for Taiwan policymakers and urban planners, particularly those responsible for coordinating environmental protection and economic development in cities. Therefore, police actions to abate urban air pollution can be attained on diverse governing echelons, resulting in synergistic effects such as a reduction in climate change impacts.

Keywords: Night market, PM2.5 emissions, Metallic elements concentrations, Air quality monitoring, Pollutants emissions, ISCST3 model

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