Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
This study addresses the limited understanding of factors affecting the efficiency of water treatment plants in reducing trihalomethane (THM) formation through total organic carbon (TOC) removal, highlighting significant challenges in improving treatment effectiveness. The aim of this study was to examine the influence of water quality on the efficiency of water treatment plants to remove TOC and reduce THM formation. Linear regression and correlation analyses were conducted to examine the relationship between water quality parameters and THM concentrations. The results showed that there was a negative relationship between turbidity, metals, and TOC concentration with TOC removal efficiency. Positive correlations were found between parameters and the formation of THMs in water. Of these parameters, water temperature was observed to have relatively less influence on THM formation. It was observed that seasonal variations in water quality affect the efficiency of TOC removal and THM content in treated water. THM levels in chlorinated water were found to be within the permissible range of the World Health Organization's drinking water quality guidelines. However, it is still important to maintain continuous monitoring and take measures to reduce THMs. The model demonstrated a strong correlation (R = 0.906) between predicted and measured THM values.
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Source |
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http://dx.doi.org/10.2166/wh.2024.276 | DOI Listing |
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