Severity: Warning
Message: file_get_contents(https://...@remsenmedia.com&api_key=81853a771c3a3a2c6b2553a65bc33b056f08&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
Identifying the influencing factors of soil heavy metal content changes is the basis for reducing or preventing soil heavy metal pollution. Taking an agricultural experimental field in Changping District of Beijing as an example, the heavy metal content changes in As, Cr, Cu, Ni, Pb, and Zn from 2012 to 2022 were firstly analyzed. Secondly, the influencing factors of the heavy metal content changes were detected based on the geographical detector at the single-target and multi-target levels, respectively. Finally, comparative experiments with the correlation analysis method and existing studies were set up to evaluate the effectiveness of the identification method of influencing factors developed in this study. The results showed that human activity factors have exacerbated the changes in soil heavy metal content in the study area as follows: ① At the single-target level, the land use type was the main influencing factor on the changes in Cr, Cu, and Zn contents, and the annual deposition flux influenced the changes in As. The results of the interaction detection showed that there was an enhancement effect among the factors, and the interaction of the human activity factors dominated for the factor identification. ② The results of the multi-target level detection covered the results of the single-target level detection, which could identify more influencing factors. The land use type affected the changes in Cu, Zn, Cr, Ni, and As, and the changes in As and Zn were influenced by the annual deposition fluxes. ③ The multi-target identification method coupled with geographical detector and principal component analysis could effectively identify the influencing factors of soil heavy metal content changes, which was much more effective than the single soil heavy metal correlation method. The developed multi-target identification method for influencing factors of heavy metal content changes can provide technical support for the regional pollution monitoring and macro-management of soil heavy metals.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.13227/j.hjkx.202308194 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!