This is metadata documentation for the Quality Assurance Tracking System - R7, an EPA Region 7 resource that tracks information on quality assurance reviews. Also called the QA Tracking System-R7 or QATS-R7. The reviews are completed under the Environmental Services (ENSV) Divsion at EPA Region 7.

The U.S. Geological Survey (USGS), in cooperation with the U.S. Fish and Wildlife Service (USFWS) and the U.S. Environmental Protection Agency (EPA), identified the occurrence of contaminants of emerging concern (CECs) in water and bottom sediments collected in 2013 at 57 sites throughout the Great Lakes Basin. The 2013 effort is part of a long-term study that began in 2010. Included in this directory are collection methods, references to or descriptions of analytical methods used, data for samples collected in 2013, and associated quality-assurance data. Samples were collected from April through October 2013 by USGS, USFWS, and/or EPA personnel. Study sites include tributaries to the Great Lakes located near Duluth, Minnesota; Kewaunee, Wisconsin; Appleton, Wisconsin; Detroit, Michigan; Grand Rapids, Michigan; St Clair, Michigan; Cleveland, Ohio; Wanakena, New York; and Potsdam, New York (see "2013 Site List"). During this study, 93 environmental samples and 6 field replicate sample pairs of surface water, 3 field blank water samples, and 3 laboratory-matrix spike water samples were collected or prepared. Additionally, 49 environmental samples, 4 field replicate sample pairs, and two laboratory-matrix spike samples of bottom sediment were collected or prepared. Water and bottom-sediment samples were analyzed at the USGS National Water Quality Laboratory in Denver, Colorado, for a broad suite of CECs.

Overview The Quality Assurance Oversight Team (QAOT) is responsible for providing guidance on, and evaluating the implementation of, the Comprehensive Everglades Restoration Plan (CERP) Quality Systems through the Quality Assurance Systems Requirements (QASR) and CERP Guidance Memorandum (CGMs). This responsibility includes developing and providing guidance on procedures, QA/QC requirements and data validation for CERP monitoring activities. The QAOT is the forum to develop consistency regarding data quality and QA/QC processes among the various entities involved with hydrological, meteorological, water quality, and biological monitoring activities for CERP. Purpose This memorandum provides guidance to the staff of the Jacksonville District, U.S. Army Corps of Engineers (USACE), South Florida Water Management District (SFWMD), members of the Program [including REstoration, COordination, and VERification (RECOVER)] and Project Delivery Teams (PDTs) on the establishment and administration of a Quality Assurance (QA)/Quality Control (QC) and Data Validation program for Comprehensive Everglades Restoration Plan (CERP) environmental data. In addition to providing guidance, other responsibilities of the QAOT include: Develop and implement data review criteria and quality assessment procedures. Standardize electronic data deliverables. Establish Standard Operating Procedures (SOPs) when they do not exist. Oversee the approval process for alternative procedures for sampling and analysis as described in the QASR. Implement a QA audit program for CERP monitoring activities. Oversee the laboratory and field comparison studies program to assess consistency and comparability among agencies involved in CERP monitoring activities. Produce a QA report on CERP monitoring activities on a biennial basis, evaluating whether the QASR is being implemented by CERP projects and programs and/or their contractors. Review and provide guidance in the development of QA/QC procedures in Scopes of Work and Monitoring Plans for CERP projects and programs. Review program and project-level monitoring plans and scopes of work to ensure all required QA/QC protocols are addressed. Familiarize Project Delivery Teams (PDTs) and programs (such as RECOVER) with the requirements of the QASR. Provide guidance, if requested, for data quality objectives to PDTs and programs. Coordinate and/or Facilitate Relevant Workshops, Meetings and Coordination Activities Prepare and Update the Program Management Plan Provide a Link between QAOT and DCT QAOT Document Control QASR Preparation and Updates CGM Development and Updates Related to QAOT

Reporting units of sample results [where 1 picoCurie (pCi) = 1 trillionth (1E-12) Curie (Ci)]: • Air Samples are reported in pCi/m³. Data Quality Disclaimer: This database is for informational use and is not a controlled quality database. Efforts have been made to ensure accuracy of data in the database; however, errors and omissions may occur. Examples of potential errors include: • Data entry errors. • Lab results not reported for entry into the database. • Missing results due to equipment failure or unable to retrieve samples due to lost or environmental hazards. • Translation errors – the data has been migrated to newer data platforms numerous times, and each time there have been errors and data losses. Error results are the calculated uncertainty for the sample measurement results and are reported as +/-. Environmental Sample Records are from the year 1998 until present. Prior to 1998 results were stored in hardcopy, in a non-database format. Requests for results from samples taken prior to 1998 or results subject to quality assurance are available from archived records and can be made through the DEEP Freedom of Information Act (FOIA) administrator at deep.foia@ct.gov. Information on FOIA requests can be found on the DEEP website. FOIA Administrator Office of the Commissioner Department of Energy and Environmental Protection 79 Elm Street, 3rd Floor Hartford, CT 06106

A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.

As part of the Glassmeyer et al., (2023) review for the journal GeoHealth, the data from 84 journal articles was summarized. One of the metrics captured in the summary was the different types of quality assurance/ quality control parameters mentioned in each paper (see Data Template tab). The types of QA/QC parameters were: field blank, laboratory reagent blank, laboratory fortified blank (LFB- aka laboratory spike), laboratory fortified matrix sample (LFM- aka matrix spike) and duplicate sample. Also logged was if no QA/QC was mentioned, and if it was a review paper that summarized multiple studies (and therefore had no independent QA/QC). This dataset is that QA/QC summary.

Additional file 3: Example of report formatting request to send to the lab.

IntroductionWhile crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented.MethodsWith a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (

ADBNet is an online database tracking Iowa's water quality assessments. These assessments are prepared under guidance provided by the US EPA under Section 305b of the Clean Water Act. The assessments are intended to estimate the extent to which Iowa's waterbodies meet the goals of the Clean Water Act and attain state water quality standards, and share this information with planners, citizens and other partners in basin planning and watershed management activities. Water quality in Iowa is measured by comparisons of recent monitoring data to the Iowa Water Quality Standards. Results of recent water quality monitoring, special water quality studies, and other assessments of the quality of Iowa's waters are used to determine the degree to which Iowa's rivers, streams, lakes, and wetlands support the beneficial uses for which they are designated in the Iowa Water Quality Standards (for example, aquatic life (fishing), swimming, and/or use as a source of a public water supply). Other information from water quality monitoring and studies that are up to five years old are also used to expand the coverage of assessments in the report. Waters assessed as impaired (that is, either partially supporting or not supporting their designated uses) form the basis for the state's list of impaired waters as required by Section 303(d) of the Clean Water Act.

Minnesota Pollution Control Agency (MPCA) surface water monitoring station locations, including lake, stream, biological and discharge. Locations of United States Geological Survey (USGS) stream flow stations are also included. This data set was created as part of MPCA's Environmental Data Access project, which was designed to provide internet access to MPCA's surface water monitoring data. The data set contains locational data and limited attributes for all MPCA stream chemistry stations, MPCA lake monitoring stations, MPCA stream biology stations, MPCA permitted dischargers [National Pollutant Discharge Elimination System (NPDES) permits], and (locations only) of USGS stream flow stations. MPCA lake and stream monitoring stations are the same stations found in MPCA's EQuIS database.

Reporting units of sample results [where 1 picoCurie (pCi) = 1 trillionth (1E-12) Curie (Ci)]: • Other samples are reported in pCi/g. Data Quality Disclaimer: This database is for informational use and is not a controlled quality database. Efforts have been made to ensure accuracy of data in the database; however, errors and omissions may occur. Examples of potential errors include: • Data entry errors. • Lab results not reported for entry into the database. • Missing results due to equipment failure or unable to retrieve samples due to lost or environmental hazards. • Translation errors – the data has been migrated to newer data platforms numerous times, and each time there have been errors and data losses. Error Results are the calculated uncertainty for the sample measurement results and are reported as (+/-). Environmental Sample Records are from the year 1998 until present. Prior to 1998 results were stored in hardcopy, in a non-database format. Requests for results from samples taken prior to 1998 or results subject to quality assurance are available from archived records and can be made through the DEEP Freedom of Information Act (FOIA) administrator at deep.foia@ct.gov. Information on FOIA requests can be found on the DEEP website. FOIA Administrator Office of the Commissioner Department of Energy and Environmental Protection 79 Elm Street, 3rd Floor Hartford, CT 06106

This is metadata documentation for the Quality Assurance Training Tracking System (QATTS) which tracks Quality Assurace training given by R7 QA staff to in-house staff and external partners.

This data was taken from 2010-2012. It was taken with the YSI meter, the professional plus series, with the quatro sensors. This data is presented as a list of each data repatition entry taken at each site during each visit. The data is up loaded with excel 2010. Each excel data set, sheet 1 is "QAPP DATA" and sheet 2 "NON QAPP DATA". The "QAPP DATA" is what is listed in the Native Village of White Mountain's Quality Assurance Program Plan (QAPP). The "NON QAPP DATA" is other data collected by the YSI meter which is not listed in the NVWM's QAPP. You will notice the data for Dissolved Oxygen mg/L has dropped significantly in 2012 from previous years. We believe this data to be inaccurate because of sensor malfunction.

The importance of long-term environmental monitoring and research for detecting and understanding changes in ecosystems and human impacts on natural systems is widely acknowledged. Over the last decades a number of critical components for successful long-term monitoring have been identified. One basic component is quality assurance/quality control protocols to ensure consistency and comparability of data. In Norway, the authorities require environmental monitoring of the impacts of the offshore petroleum industry on the Norwegian continental shelf, and in 1996 a large-scale regional environmental monitoring program was established. As a case study, we used a sub-set of data from this monitoring to explore concepts regarding best practices for long-term environmental monitoring. Specifically, we examined data from physical and chemical sediment samples and benthic macro-invertebrate assemblages from 11 stations from six sampling occasions during the period 1996-2011. Despite the establis...

Analysis of ‘Environmental Monitoring Results for Radiation’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/53a59ab0-444f-45ba-ab3c-fe6de6eb6a7a on 26 January 2022.

--- Dataset description provided by original source is as follows ---

• Reporting unit of monitoring results is millirem [where 1 millirem = 1 thousandth (10-3) of a Rem] as defined in Regulations of Connecticut State Agencies Section 19-24-4.
• Monitoring results below the minimum measurable quantity for the monitoring period are recorded as “M.”
• Quarterly results reflect total integrated gamma exposure received within a calendar 3-month time frame.
• Environmental monitoring results are reported on a calendar quarterly basis: • 1st Quarter: January, February, March • 2nd Quarter: April, May, June • 3rd Quarter: July, August, September • 4th Quarter: October, November, December
• Data Quality Disclaimer: This database is for informational use and is not a controlled quality database. Efforts have been made to ensure accuracy of data in the database; however, errors and omissions may occur. Examples of potential errors include: • Data entry errors. • Monitoring results not reported for entry into the database. • Missing results due to equipment failure or unable to retrieve monitors due to lost or environmental hazards. • Translation errors – the data has been migrated to a newer data platform, and there have been errors and data losses.
• Environmental Monitoring Records are from the year 2008 until present. Prior to 2008 results are stored in hardcopy, in a non-database format. Requests for monitor results prior to 2008 or results subject to quality assurance are available from archived records and can be made through the DEEP Freedom of Information Act (FOIA) administrator at deep.foia@ct.gov. Information on FOIA requests can be found on the DEEP website (https://portal.ct.gov/deep) FOIA Administrator Office of the Commissioner Department of Energy and Environmental Protection 79 Elm Street, 3rd Floor Hartford, CT 06106

--- Original source retains full ownership of the source dataset ---

This United States Environmental Protection Agency (US EPA) feature layer represents monitoring site data, updated hourly concentrations and Air Quality Index (AQI) values for the latest hour received from monitoring sites that report to AirNow.Map and forecast data are collected using federal reference or equivalent monitoring techniques or techniques approved by the state, local or tribal monitoring agencies. To maintain "real-time" maps, the data are displayed after the end of each hour. Although preliminary data quality assessments are performed, the data in AirNow are not fully verified and validated through the quality assurance procedures monitoring organizations used to officially submit and certify data on the EPA Air Quality System (AQS).This data sharing, and centralization creates a one-stop source for real-time and forecast air quality data. The benefits include quality control, national reporting consistency, access to automated mapping methods, and data distribution to the public and other data systems. The U.S. Environmental Protection Agency, National Oceanic and Atmospheric Administration, National Park Service, tribal, state, and local agencies developed the AirNow system to provide the public with easy access to national air quality information. State and local agencies report the Air Quality Index (AQI) for cities across the US and parts of Canada and Mexico. AirNow data are used only to report the AQI, not to formulate or support regulation, guidance or any other EPA decision or position.About the AQIThe Air Quality Index (AQI) is an index for reporting daily air quality. It tells you how clean or polluted your air is, and what associated health effects might be a concern for you. The AQI focuses on health effects you may experience within a few hours or days after breathing polluted air. EPA calculates the AQI for five major air pollutants regulated by the Clean Air Act: ground-level ozone, particle pollution (also known as particulate matter), carbon monoxide, sulfur dioxide, and nitrogen dioxide. For each of these pollutants, EPA has established national air quality standards to protect public health. Ground-level ozone and airborne particles (often referred to as "particulate matter") are the two pollutants that pose the greatest threat to human health in this country.A number of factors influence ozone formation, including emissions from cars, trucks, buses, power plants, and industries, along with weather conditions. Weather is especially favorable for ozone formation when it’s hot, dry and sunny, and winds are calm and light. Federal and state regulations, including regulations for power plants, vehicles and fuels, are helping reduce ozone pollution nationwide.Fine particle pollution (or "particulate matter") can be emitted directly from cars, trucks, buses, power plants and industries, along with wildfires and woodstoves. But it also forms from chemical reactions of other pollutants in the air. Particle pollution can be high at different times of year, depending on where you live. In some areas, for example, colder winters can lead to increased particle pollution emissions from woodstove use, and stagnant weather conditions with calm and light winds can trap PM2.5 pollution near emission sources. Federal and state rules are helping reduce fine particle pollution, including clean diesel rules for vehicles and fuels, and rules to reduce pollution from power plants, industries, locomotives, and marine vessels, among others.How Does the AQI Work?Think of the AQI as a yardstick that runs from 0 to 500. The higher the AQI value, the greater the level of air pollution and the greater the health concern. For example, an AQI value of 50 represents good air quality with little potential to affect public health, while an AQI value over 300 represents hazardous air quality.An AQI value of 100 generally corresponds to the national air quality standard for the pollutant, which is the level EPA has set to protect public health. AQI values below 100 are generally thought of as satisfactory. When AQI values are above 100, air quality is considered to be unhealthy-at first for certain sensitive groups of people, then for everyone as AQI values get higher.Understanding the AQIThe purpose of the AQI is to help you understand what local air quality means to your health. To make it easier to understand, the AQI is divided into six categories:Air Quality Index(AQI) ValuesLevels of Health ConcernColorsWhen the AQI is in this range:..air quality conditions are:...as symbolized by this color:0 to 50GoodGreen51 to 100ModerateYellow101 to 150Unhealthy for Sensitive GroupsOrange151 to 200UnhealthyRed201 to 300Very UnhealthyPurple301 to 500HazardousMaroonNote: Values above 500 are considered Beyond the AQI. Follow recommendations for the Hazardous category. Additional information on reducing exposure to extremely high levels of particle pollution is available here.Each category corresponds to a different level of health concern. The six levels of health concern and what they mean are:"Good" AQI is 0 to 50. Air quality is considered satisfactory, and air pollution poses little or no risk."Moderate" AQI is 51 to 100. Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people. For example, people who are unusually sensitive to ozone may experience respiratory symptoms."Unhealthy for Sensitive Groups" AQI is 101 to 150. Although general public is not likely to be affected at this AQI range, people with lung disease, older adults and children are at a greater risk from exposure to ozone, whereas persons with heart and lung disease, older adults and children are at greater risk from the presence of particles in the air."Unhealthy" AQI is 151 to 200. Everyone may begin to experience some adverse health effects, and members of the sensitive groups may experience more serious effects."Very Unhealthy" AQI is 201 to 300. This would trigger a health alert signifying that everyone may experience more serious health effects."Hazardous" AQI greater than 300. This would trigger a health warnings of emergency conditions. The entire population is more likely to be affected.AQI colorsEPA has assigned a specific color to each AQI category to make it easier for people to understand quickly whether air pollution is reaching unhealthy levels in their communities. For example, the color orange means that conditions are "unhealthy for sensitive groups," while red means that conditions may be "unhealthy for everyone," and so on.Air Quality Index Levels of Health ConcernNumericalValueMeaningGood0 to 50Air quality is considered satisfactory, and air pollution poses little or no risk.Moderate51 to 100Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution.Unhealthy for Sensitive Groups101 to 150Members of sensitive groups may experience health effects. The general public is not likely to be affected.Unhealthy151 to 200Everyone may begin to experience health effects; members of sensitive groups may experience more serious health effects.Very Unhealthy201 to 300Health alert: everyone may experience more serious health effects.Hazardous301 to 500Health warnings of emergency conditions. The entire population is more likely to be affected.Note: Values above 500 are considered Beyond the AQI. Follow recommendations for the "Hazardous category." Additional information on reducing exposure to extremely high levels of particle pollution is available here.

In 2018, groundwater samples were collected from aquifers in the Williston Basin in parts of eastern Montana, western North Dakota, and northwestern South Dakota. This dataset includes quality-control data for volatile organic compounds that include data for source-solution blanks and field blanks. The dataset also includes data for sulfur hexafluoride in environmental samples of groundwater.

Reporting unit of monitoring results is millirem [where 1 millirem = 1 thousandth (10-3) of a Rem] as defined in Regulations of Connecticut State Agencies Section 19-24-4. Monitoring results below the minimum measurable quantity for the monitoring period are recorded as “M.” Quarterly results reflect total integrated gamma exposure received within a calendar 3-month time frame. Environmental monitoring results are reported on a calendar quarterly basis: • 1st Quarter: January, February, March • 2nd Quarter: April, May, June • 3rd Quarter: July, August, September • 4th Quarter: October, November, December Data Quality Disclaimer: This database is for informational use and is not a controlled quality database. Efforts have been made to ensure accuracy of data in the database; however, errors and omissions may occur. Examples of potential errors include: • Data entry errors. • Monitoring results not reported for entry into the database. • Missing results due to equipment failure or unable to retrieve monitors due to lost or environmental hazards. • Translation errors – the data has been migrated to a newer data platform, and there have been errors and data losses. Environmental Monitoring Records are from the year 2008 until present. Prior to 2008 results are stored in hardcopy, in a non-database format. Requests for monitor results prior to 2008 or results subject to quality assurance are available from archived records and can be made through the DEEP Freedom of Information Act (FOIA) administrator at deep.foia@ct.gov. Information on FOIA requests can be found on the DEEP website (https://portal.ct.gov/deep) FOIA Administrator Office of the Commissioner Department of Energy and Environmental Protection 79 Elm Street, 3rd Floor Hartford, CT 06106

Analysis of ‘Environmental Monitoring Results for Radioactivity: Other Samples’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a4163daf-e45a-4339-ab2d-0e41787ccfd8 on 27 January 2022.

--- Dataset description provided by original source is as follows ---

• Reporting units of sample results [where 1 picoCurie (pCi) = 1 trillionth (1E-12) Curie (Ci)]: • Other samples are reported in pCi/g.

• Data Quality Disclaimer: This database is for informational use and is not a controlled quality database. Efforts have been made to ensure accuracy of data in the database; however, errors and omissions may occur.

Examples of potential errors include: • Data entry errors. • Lab results not reported for entry into the database. • Missing results due to equipment failure or unable to retrieve samples due to lost or environmental hazards. • Translation errors – the data has been migrated to newer data platforms numerous times, and each time there have been errors and data losses.

• Error Results are the calculated uncertainty for the sample measurement results and are reported as (+/-).

• Environmental Sample Records are from the year 1998 until present. Prior to 1998 results were stored in hardcopy, in a non-database format.

Requests for results from samples taken prior to 1998 or results subject to quality assurance are available from archived records and can be made through the DEEP Freedom of Information Act (FOIA) administrator at deep.foia@ct.gov. Information on FOIA requests can be found on the DEEP website.

FOIA Administrator Office of the Commissioner Department of Energy and Environmental Protection 79 Elm Street, 3rd Floor Hartford, CT 06106

--- Original source retains full ownership of the source dataset ---

The Environmental Protection Department released the national manual monitoring data for fine particulate matter (PM2.5). The manual monitoring of PM2.5 is based on the standard testing method, with sampling conducted every three days and continuous sampling for 24 hours to obtain the measurement. As monitoring data requires on-site sampling, laboratory testing and analysis, as well as data quality assurance and quality control procedures, it usually takes 20 days to provide the data.