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Article summary:
1. This study introduced a spatial distribution - principal component analysis (SD-PCA) model to assess soil pollution of heavy metals in the Lintong District, a typical multi-source urban area in Northwest China.
2. The SD-PCA model combines the spatial attributes of soil pollution with linear data transformation by the eigenvector-based principal component analysis to identify potential sources of heavy metals more easily.
3. Agriculture was found to be the largest source of soil pollution, contributing 65.5 %, while traffic and natural pollution sources contributed 17.9 % and 11.1 % respectively.
Article analysis:
The article “A spatial distribution – Principal component analysis (SD-PCA) model to assess pollution of heavy metals in soil” is an informative and well-structured piece that provides an overview of the SD-PCA model for assessing soil pollution of heavy metals in the Lintong District, a typical multi-source urban area in Northwest China. The article is written in a clear and concise manner, making it easy to understand for readers with varying levels of knowledge on the subject matter.
The article is reliable and trustworthy as it provides detailed information on the methods used for sampling and analysis, as well as evaluation methods for assessing soil pollution by heavy metals such as single factor index method, geo-accumulation index method, Nemerow pollution index method and potential ecological hazard index method. Furthermore, it also provides information on how these methods are used to classify different levels of soil contamination based on standards set by Chinese authorities.
The article does not appear to have any biases or one-sided reporting as it presents both sides equally and objectively without any promotional content or partiality towards either side. It also does not make any unsupported claims or missing points of consideration that could lead to misinterpretation or misunderstanding by readers. Additionally, all evidence presented is supported by relevant research studies which adds credibility to the article’s claims and arguments made throughout its entirety.
In conclusion, this article is reliable and trustworthy due to its comprehensive coverage on the topic at hand as well as its objective presentation without any biases or unsupported claims that could lead to misinterpretation or misunderstanding by readers.