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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
Biotic ligand models for calculation of watertype-specific no effect concentrations are recognized as a major improvement in risk assessment of metals in surface waters. Model complexity and data requirement, however, hamper the regulatory implementation. To facilitate regulatory use, biotic ligand models (BLM) for the calculation of Ni, Cu, and Zn HC5 values were simplified to linear equations with an acceptable level of accuracy, requiring a maximum of 3 measured water chemistry parameters. In single-parameter models, dissolved organic carbon (DOC) is the only significant parameter with an accuracy of 72%-75% to predict HC5s computed by the full BLMs. In 2-parameter models, Mg, Ca, or pH are selected by stepwise multiple regression for Ni, Cu, and Zn HC5, respectively, and increase the accuracy to 87%-94%. The accuracy is further increased by addition of a third parameter to 88%-97%. Three-parameter models have DOC and pH in common, the third parameter is Mg, Ca, or Na for HC5 of Ni, Cu, and Zn, respectively. Mechanisms of chemical speciation and competitive binding to the biotic ligand explain the selection of these parameters. User-defined requirements, such as desired level of reliability and the availability of measured data, determine the selection of functions to predict HC5.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1002/ieam.1298 | DOI Listing |
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