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Quality Assurance

At Stone Environmental, we know how data quality impacts environmental decisions and project results. That’s why we require all projects be conducted professionally, with a high degree of integrity and ethics. Our in-house Quality Assurance Unit (QAU) sets standards for our team members, provides training, and maintains a comprehensive Quality Management System to deliver results of the highest quality.

Stone requires all environmental data operations collect data of known and documented quality, suitable for its intended use and in compliance with all applicable regulatory and contractual requirements. Our QAU staff has substantial experience with a range of compliance requirements backed by an understanding of analytical methodologies, method validation, data assessment, and data validation.

Our Quality Assurance Capabilities

Regulatory Support Items

Stone has extensive experience working within the context of many regulatory requirements, including:

  • Expert Testimony / Legal Assistance
  • State Regulatory Support
  • Threatened and Endangered Species
  • Army Corps of Engineers 401/404
  • Comprehensive Environmental Response Compensation and Liability Act (CERCLA)
  • Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA)
  • Food Quality Protection Act (FQPA)
  • National Environmental Policy Act (NEPA)
  • Resource Conservation and Recovery Act (RCRA)
  • Total Maximum Daily Load (TMDL) and Clean Water Act Compliance
  • Toxic Substances Control Act (TSCA)

For Stone, environmental data include information collected directly from measurements, standard analyses, produced from models, and compiled from other sources such as databases and/or literature. Acquired data are data or information used for project implementation or decision making which meet the following criteria:

  • are compiled from other sources;
  • were originally collected another purpose; or
  • are obtained from non-measurement sources, such as, computer databases, programs, literature files, and historical databases.