Affiliations 

  • 1 Department of Biology, Faculty of Science and Technology, Universitas Airlangga, Kampus C UNAIR, Jalan Mulyorejo, Surabaya 60115, Indonesia
  • 2 Department of Environmental Engineering, Institut Teknologi Adhi Tama Surabaya, Jalan Arif Rahman Hakim No. 100, Surabaya 60117, Indonesia
  • 3 Department of Industrial & System Engineering, Institut Teknologi Sepuluh Nopember, Kampus ITS-Keputih Sukolilo, Surabaya 60111, Indonesia
  • 4 Department of Environmental Engineering, Institut Teknologi Sepuluh Nopember, Kampus ITS-Keputih Sukolilo, Surabaya 60111, Indonesia
  • 5 Department of Chemical and Process Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600, UKM Bangi, Selangor, Malaysia
  • 6 Department of Civil Engineering Engineering, Faculty of Civil and Built Environment, Universiti Tun Hussein Onn, 86400, Parit Raja, Batu Pahat, Johor, Malaysia
Heliyon, 2020 Sep;6(9):e04967.
PMID: 33015386 DOI: 10.1016/j.heliyon.2020.e04967

Abstract

In a slow sand filter, a biological layer consisting of alluvial mud and various types of microorganisms grows and attaches to the sand media and forms a matrix called schmutzdecke. Changes to several factors, including the quality of raw water, filtration speed, and the addition of media, affect the performance of the slow sand filter unit in producing treated water. Geotextiles can be equipped to improve the performance of a slow sand filter in removing pollutants. The selection of several factors that affect slow sand filter performance can be used as a starting point for the engineering system to determine the best pattern of performance behavior. This approach was carried out by looking at the dynamic behavior patterns of slow sand filter system performance in treating raw water. This research has not yet been conducted extensively. The dynamic behavior pattern approach to the performance of the slow sand filter unit was used to obtain the behavior model for the schmutzdecke layer on the filter. The system dynamic approach focused on treatment scenarios that can determine the behavior of the slow sand filter system. Several factors were assessed, including temperature, turbidity, nutrient concentration, algal concentration, bacteria and dissolved oxygen. Model simulation results show that the comparison of C: N: P values affected the performance of the schmutzdecke layer in removing total coli. The slow sand filter unit was capable of producing treated water with a total amount of coli equal to 0 on the C: N: P values of 85: 5.59: 1.25, respectively, and a 9 cm geotextile thickness.

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