A new combination of Bayesian methods for studying the role of DOM in water quality and greenhouse gases

This method is not a traditional Bayesian network; instead, it innovatively integrates Bayesian network analysis into environmental analysis, allowing for the examination of how DOM and water quality influence greenhouse gas emissions while distinguishing between direct and indirect effects. The resulting probability table makes it possible to observe changes in greenhouse gas emissions under specific conditions in a more intuitive way. (Similarly, this approach can be applied to scenarios in which multiple independent variables affect a single dependent variable.) The method also employs a novel analytical framework, which gives it greater practical significance than traditional Bayesian methods. For further details, please refer to the paper and its methodological description.