Night markets are attractive tourist sites in Asian cities. However, the outdoor activities produce different types of pollutants. Air pollution and solid waste in night markets have received much attention, but wastewater pollution from night markets has rarely been examined. The untreated wastewater are discharged into roadside gutters and might contaminate receiving waterbodies. In this study, night markets in Taipei city, Taiwan, were surveyed to clarify the characteristics of wastewater. The sampled wastewater showed high levels of organic substances, oil and grease, and phosphorous but low levels of nitrogen compounds. In addition, the unit pollution loads in night market stalls was obtained. The BOD load of each stall in the night markets was 2,509 g/day, which is higher than the sewage emissions of 50 people. In order to know the impacts of night market wastewater on receiving waterbody, a water quality model, the Water Quality Analysis Simulation Program (WASP), was used in the studied river, Keelung river. If night market wastewater could be collected (not discharged), the BOD concentration could be reduced by 9.8%, but the NH3-N and DO concentration could be reduced by less than 1%.
In this study, the Hydrological Simulation Programme‐FORTRAN (HSPF) and the Water Quality Analysis Simulation Programme (WASP), were adopted as a combined tool. The long Feitsui impounding reservoir located in Taiwan was used as a case study. The combined model helped illustrate the total phosphorus (TP) mass balance. Approximately 51.4% of the TP flowed out from the reservoir, while 16.2% of the TP remained in the waterbody and 32.2% of the TP was deposited. The reservoir was divided into five sections along its length for a quality analysis. The exceedance probability (the probability of exceeding the eutrophic level, i.e., TP = 24 μg/L) was 9.7% in the upstream section. If the TP load increased by 20%, the eutrophication exceedance probability could increase to 25.5%. This study demonstrated the usage of the combined model tool and the exceedance probability method in the data analysis, which could guide effective catchment management and eutrophication risk prevention.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.