**Author details**

Pb, Cd, Hg, Cr, are frequently found in water, sediment, soil, and particle, showing

The unsupervised machine learning algorithm, including principal component analysis, factor analysis, positive matrix fractionation is mostly used. The PCA is used in water is to find contamination source of trace element, and sometimes water inrush in coal mines. In the air particle researches, PCA and PMF are frequently used to trace the source of PM 2.5 and PM 10, and the TEs source in the particle sources. Some supervised algorithm, including discrimination analysis, Bayesian network, artificial neural network, decision tree is used when the data are labeled. Generally speaking, the most popular methods used to apportion the source of trace elements as contaminants are unsupervised ML techniques, especially the principal component analysis. In a wider scope, supervised ML is a big tool box for investigations and researches, which is frequently applied and implemented in the areas of science and society. The supervised ML usually gives more accuracy and robust result than the unsupervised ML. In the area of trace element apportionment, some factors constrain the implementation of supervised ML techniques, as the sources are usually not known. However, some techniques are promising to treat the issues of trace element apportionment. First, the supervised ML methods could be implemented more frequently. The unsupervised ML methods are used in the first step. With the intensive research, as some sources have been identified, the supervised ML methods could be used. For example, water inrush is sometimes a threaten in some Chinese coal mines. As the potential source of inrush can be identified, supervised ML method, discriminant analysis is used to determine the water type of inrush, then the corresponding technologies to deal with the threaten or accidents could be implemented. At this stage, some other supervised ML method could also be used. However, the discriminant analysis was mostly used. Second, semi supervised ML may be used implemented more. This method is a series of relative novel techniques. Once more data is obtained in an investigation or research, the semi-supervised ML may be used. In a sense, this method combines the unsupervised and supervised techniques in one implementation. Third, the machine learning method could be combined with geochemical method together. Two technique system have their advantages and disadvantages, the combination

high mobility and contaminating potential on environment.

*Trace Metals in the Environment - New Approaches and Recent Advances*

may achieve its maximum consequences and efficiency.

Our study is funded by the Fundamental Research Funds for the Central Universities (3142014005), the Colleges and Universities in Hebei Province Science and Technology Research Project (ZD2016204), and the National Natural Science

**Acknowledgements**

**Conflict of interest**

**22**

Foundation of China (51674119).

The authors declare no conflict of interest.

Yao Shan\* and Jianjun Shi School of Safety Engineering, North China Institute of Science and Technology, Yanjiao, China

\*Address all correspondence to: 9106350@qq.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
