LSPA Continuing Education Seminar

Environmental Data Analysis and MCP Risk Assessment Statistics with ProUCL

Instructors: 

• Bernard J. Morzuch, PhD, Department of Resource Economics, University of Massachusetts
• Harrison Roakes, PE, Project Manager, Sanborn, Head & Associates, Inc.
• Stephen Zemba, PhD, PE, Project Director, Sanborn, Head & Associates, Inc.

View Instructor Biographies

This course has been approved by the LSP Board of Registration for 8.0 LSP technical continuing education credits (#1518B). This is a repeat course and was last offered in 2019. This course will also be submitted for CT LEP, NY PE and NY PG credits. On-site registration opens at 7:30 AM; the course will begin at 8:00 AM and end at 5:00 PM. Continental breakfast, lunch and refreshments will be provided.

Available Credits: 
8.0 Technical LSP Credits (#1518B)
8.0 CT LEP Credits (#CTLEP-479b)
8.0 NY PE Credits (#20229147)
8.0 NY PG Credits (#20229147)

Course Description: 
The Massachusetts Contingency Plan (MCP) defines an Exposure Point Concentration (EPC) as the concentration of oil or hazardous material (OHM) in a specific medium that may be contacted by human or environmental receptors. Calculating EPCs, however, is not necessarily straightforward. Under the MCP, a data set’s maximum concentration level, its arithmetic average, or an upper confidence limit (UCL) of the population mean can be used to estimate an EPC. In many cases, the 1995 MCP risk characterization guidance allows for the use of arithmetic average (mean) concentrations in estimating chronic and subchronic exposures, but Section 310 CMR 40.0926 of the 2019 draft amendments to the MCP requires “a conservative estimate of the mean.”

It is important for site practitioners to have practical knowledge of statistics to support and justify the calculation of EPCs.  To help prepare you for addressing the enhanced requirements involved in estimating EPCs and to familiarize you with statistics such as UCLs, this course will include: 1) EPC regulatory and guidance context; 2) core statistical concepts and applications; 3) hands-on instruction and use of the USEPA ProUCL software; and 4) case studies that deal with common environmental data challenges. Additionally, a discussion of using statistical tests to identify OHM present at background levels will also be covered.  Please click here to review the course syllabus.

The course presents approaches to common challenges encountered with environmental data sets, such as small sample sizes, censored or non-detect data, and fitting data distributions. The course will include hands-on analyses of data using the ProUCL software. ProUCL is freely available for download from the USEPA (Version 5.2). A ProUCL user guide and technical guide are also available from the USEPA.

Participants should bring a laptop with ProUCL installed. Please note that ProUCL installation may require administrator permissions for installation, and ProUCL may be available for only certain operating systems (e.g., Windows 10).

Course Prerequisites:
It is helpful but not required that participants have a working knowledge of key descriptive statistics such as mean, median, mode, range, variance, and standard deviation. Familiarity with the z-table and t-table for the purpose of calculating probabilities is desirable. Familiarity with the Central Limit Theorem is desirable but not expected.