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
In this study, the operation parameters of a partial nitrification process (PN) treating saline wastewater were optimized using the Box-Behnken design via the response surface methodology (BBD-RSM). A novel strategy based on the control of the carbon/nitrogen ratio (C/N), alkalinity/ammonia ratio (K/A), and salinity in three stages was used to achieve PN in a sequence batch reactor. The results demonstrated that a high and stable PN was completed after 50 d with an ammonia removal efficiency (ARE) of 98.37 % and nitrite accumulation rate (NAR) of 85.93 %. Next, BBD-RSM was applied, where ARE and NAR were the responses. The highest responses from the confirmation experiment were 99.9 % ± 0.04 and 95.25 % ± 0.32 when the optimum C/N, K/A, and salinity were identified as 0.84, 2, and 5.5 (g/L), respectively. The results were higher than those for the nonoptimized reactor. The developed regression model adequately forecasts the PN performance under optimal conditions. Therefore, this study provides a promising strategy for controlling the PN process and shows how the BBD-RSM model can improve the PN performance.
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Source |
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http://dx.doi.org/10.1016/j.scitotenv.2022.160802 | DOI Listing |
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