SAMPLING, ANALYSIS, AND DATA COLLECTION Sample Clauses

SAMPLING, ANALYSIS, AND DATA COLLECTION. To ensure that all DQOs are met, a summary table of sampling, analysis, and data collection was formulated and is presented in Table 6. Figure 4 identifies the location of treatment system components and physical sample locations for the Northeast Plume Optimization Project. The air stripper effluent sample point for performance monitoring of TCE removal efficiency is in the same general location inside both the C-765 (servicing EW234 and shown in Figure 4) and C-765-A (servicing EW235) TUs. Figure 4 identifies that CERCLA Outfall 001 is the sample collection point for compliance with ARARs that occurs prior to comingling with other waters. Refer to Section 6 and Figures 6 and 7 of the RAWP for additional information (DOE 2018a). Decision Rule (refer to Table 3) Table 6. Summary of Sampling, Analysis, and Data Collection Sample point(s) Parameters Frequencya Pumping Rates Daily EW234 and EW235 #1 TCE Monthly Water Level Weekly MWs (see Table 5 for MW numbers) TCE, Tc-99, and Water Level Quarterly or Semiannually (see Table 5) #2 Air Stripper Liquid Effluent TCE Weekly Flow; Total Suspended Solids; Oil and Grease;
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Related to SAMPLING, ANALYSIS, AND DATA COLLECTION

  • DATA COLLECTION AND ANALYSIS The goal of this task is to collect operational data from the project, to analyze that data for economic and environmental impacts, and to include the data and analysis in the Final Report. Formulas will be provided for calculations. A Final Report data collection template will be provided by the Energy Commission. The Recipient shall: • Develop data collection test plan. • Troubleshoot any issues identified. • Collect data, information, and analysis and develop a Final Report which includes: o Total gross project costs. o Length of time from award of bus(es) to project completion. o Fuel usage before and after the project.

  • Data Analysis In the meeting, the analysis that has led the College President to conclude that a reduction- in-force in the FSA at that College may be necessary will be shared. The analysis will include but is not limited to the following: ● Relationship of the FSA to the mission, vision, values, and strategic plan of the College and district ● External requirement for the services provided by the FSA such as accreditation or intergovernmental agreements ● Annual instructional load (as applicable) ● Percentage of annual instructional load taught by Residential Faculty (as applicable) ● Fall Full-Time Student Equivalent (FFTE) inclusive of dual enrollment ● Number of Residential Faculty teaching/working in the FSA ● Number of Residential Faculty whose primary FSA is the FSA being analyzed ● Revenue trends over five years for the FSA including but not limited to tuition and fees ● Expenditure trends over five years for the FSA including but not limited to personnel and capital ● Account balances for any fees accounts within the FSA ● Cost/benefit analysis of reducing all non-Residential Faculty plus one Residential Faculty within the FSA ● An explanation of the problem that reducing the number of faculty in the FSA would solve ● The list of potential Residential Faculty that are at risk of layoff as determined by the Vice Chancellor of Human Resources ● Other relevant information, as requested

  • Statistical Sampling Documentation a. A copy of the printout of the random numbers generated by the “Random Numbers” function of the statistical sampling software used by the IRO.

  • Data Collection Some downloaded software included in the Materials may generate and collect information about the software and usage and transmit it to Intel to help improve Intel’s products and services. This collected information may include product name, product version, time of event collection, license type, support type, installation status, hardware and software performance, and use. 9.

  • Random Drug Testing All employees covered by this Agreement shall be subject to random drug testing in accordance with Appendix D.

  • Statistical Analysis 31 F-tests and t-tests will be used to analyze OV and Quality Acceptance data. The F-test is a 32 comparison of variances to determine if the OV and Quality Acceptance population variances 33 are equal. The t-test is a comparison of means to determine if the OV and Quality Acceptance 34 population means are equal. In addition to these two types of analyses, independent verification 35 and observation verification will also be used to validate the Quality Acceptance test results.

  • Test Samples The Contractor is responsible for providing Samples of sufficient size for test purposes and for coordinating such tests with the Work Progress Schedule to avoid delay.

  • Disturbance Analysis Data Exchange The Parties will cooperate with one another and the NYISO in the analysis of disturbances to either the Large Generating Facility or the New York State Transmission System by gathering and providing access to any information relating to any disturbance, including information from disturbance recording equipment, protective relay targets, breaker operations and sequence of events records, and any disturbance information required by Good Utility Practice.

  • Study An application for leave of absence for professional study must be supported by a written statement indicating what study or research is to be undertaken, or, if applicable, what subjects are to be studied and at what institutions.

  • Data Collection and Reporting 1. Grantee shall develop and use a local reporting unit that will provide an assigned location for all clients served within the Hospital. This information shall also be entered into Client Assignment and Registration (CARE)when reporting on beds utilized at the Hospital.

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