Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Acidic partial nitritation (PN) is a promising technology to achieve low-cost and energy-efficient shortcut nitrogen removal from wastewater. However, a comprehensive understanding of the acidic PN under dynamic changes of pH in a sequencing batch reactor (SBR) is still lacking. In this study, we successfully established acidic PN (NO accumulation ratio >80%) under dynamic pH variation from 7.0 to 4.5 in a lab-scale SBR. By accumulating free nitrous acid (FNA) generation based on the dynamic pH change, acidic PN maintained stability even at a low NH concentration of 100 mg N L. The microbial community analysis revealed that two ammonium-oxidizing bacteria (AOB) genera, and , successfully coexisted and cooperated during acidic PN. None of the species of nitrite-oxidizing bacteria (NOB) showed adaptation to intermittent inhibition of FNA even under high DO conditions (>4.0 mg O L). Furthermore, we innovatively incorporated the classic nitrification model with the growth and decay of different nitrifying bacterial species and their inhibition by pH, FNA, and free ammonia (FA) to predict the nitrifying microbial communities shifting for establishing acidic PN. The extended model was calibrated by using short-term batch experiments and was validated by using long-term dynamic data of the nitrifying microbial community during SBR operation. The validated model was further used to identify feasible influent conditions for the SBR PN process, including influent HCO concentration, NH concentration and molar ratio (HCO/NH). Outcomes from this study support the optimal design of acidic PN-based short-cut nitrogen removal processes for future application.
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http://dx.doi.org/10.1021/acs.est.3c01282 | DOI Listing |