ProUCL is a statistical software package developed by the USEPA using many of the concepts found in the RCRA Unified Guidance. Originally developed to evaluate concerns at a specific Superfund site, the USEPA has, after considerable feedback from the remediation community, continued to update the software with additional features and tools.
Various types of environmental data may be generated during Site investigation and characterization. Often, our goals may be to determine the current risk to human health at the Site based on this data and attempt to evaluate what the risk may be moving forward.
For soil, this risk may be associated with someone contacting or inhaling/ingesting the soil. Therefore, it may be important to know how site soils compare to background values in the area, as well as a representative soil contaminant concentration for an area or the totality of the site for various exposure pathways (exposure point concentration). ProUCL has the functionality to calculate these values, as well as any outliers within the dataset.
For groundwater, specifically routine monitoring wells, we are likely more concerned with how the contaminant concentrations are trending over time. ProUCL can be used to determine whether there is statistical evidence of increasing or decreasing trends in these datasets and can provide both numerical and graphical outputs. Knowing whether the concentrations are decreasing, increasing, or not statistically trending in either direction can provide us with valuable decision-making ammunition.
ProUCL can also be used in other comparative ways. Sediment datasets, for example, can be evaluated using many of the same tools listed above for soil. One additional tool that may be helpful for these datasets is population comparison tests, or t-tests. ProUCL can be utilized to compare the means of background and site sediment sample populations, to determine if the mean of the site dataset is statistically similar or different than the mean of the background dataset. This is a useful aid in determining if site use has contributed to sediment contamination in a meaningful way.
The ease-of-use of the software, requiring no formal statistics education, as well as the comprehensive function of the software, allowing for both detect and non-detect data, makes the software a vital tool for evaluating environmental datasets.