Plan Your Cleanup

Choosing a cleanup or monitoring strategy is difficult when site data are limited and contaminant behavior is uncertain. You need to understand what the evidence supports and which questions remain open.

Use ChemML to interpret your site data, investigate contaminant sources and movement, and compare remediation and site-management options.

ChemML combines machine learning with models of physical and chemical processes. Review sensitivity and uncertainty to see which inputs matter most before choosing your next step.

Representing interactions among many chemical species can require substantial model development and computing resources. The detail you can represent depends on the available data and the questions you need to answer.

Before relying on a prediction, examine how the model represents the processes that control contaminant movement and reactions. These choices can affect estimates of contamination impacts and remediation performance.

Bring your site data, process-informed models, and uncertainty analysis into the same evaluation with ChemML.

ChemML is designed for cloud delivery, with tools to manage and visualize site data and evaluate sensitivity, uncertainty, and decisions. Public and proprietary data connections, computing resources, licensing, and support can be scoped around your project. Where needed, results can be delivered through device and mobile interfaces.

Discuss your site, monitoring data, and remediation questions with our team to explore licensing and consulting options.