**If this course has Remote Live Attendance -- USA as the location, it is a live stream remote course. You will need a computer and an internet connection.
In this course, attendees will learn the role of quality assurance and quality control in developing environmental programs for site investigations, remediation, and monitoring at contaminated sites. Participants will become comfortable with concepts, tools, and the basic statistical methods needed for designing and implementing a field program, and will gain knowledge regarding how to work with a laboratory to ensure the right chemical analyses are performed on the right samples. There will be empahsis on how to plan for and then evaluate data produced to achieve the greatest usability.
Upon completion of the course, attendees will come away with tools for deciding how to assess environmental laboratory data, how to maximize data defensibility, and when an independent data validator is needed. The extensive hands-on exercises include working through a Quality Assurance Project Plan and setting up Excel worksheets to perform efficient assessments for standard analytical data.
This course is intended for environmental professionals who need a good grounding in the concepts and framework of quality assurance for environmental data.
Basic college chemistry and modest familiarity with environmental site work will be helpful but not necessary in getting the most out of this course.
a. Quality Assurance Overview
b. Quality Management Planning and Implementation
i. Setting Data Quality Objectives
ii. Regulatory Compliance
iii. Identifying Responsible Personnel
c. Systematic Project Planning:
i. Quality Management Plan (QMP)
ii. Quality Assurance Project Plan (QAPP)
iii. Field Sampling Plan (FSP); Work Plan (WP); Sampling and Analysis Plan (SAP)
iv. Coordination of laboratory and field sampling activities
d. Issues in Field Sampling
i. Preparation
ii. Implementation/Communication
iii. Corrective Action
iv. Post-Sampling Review
e. Data Quality Indicators
i. Precision
ii. Accuracy
iii. Representativeness
iv. Reproducibility
v. Completeness
f. Data Quality Assessment I: Statistical Methods
g. Data Quality Assessment II: Data Verification and Data Validation
h. Data Quality for Decision-making and Defensibility
Attendees will receive a course manual containing workshop proceedings and reference material.
A personal laptop with Excel and a pen or pencil and paper if you prefer not to write in your course manual.