Dataset contains information on New York City air quality surveillance data. Air pollution is one of the most important environmental threats to urban populations and while all people are exposed, pollutant emissions, levels of exposure, and population vulnerability vary across neighborhoods. Exposures to common air pollutants have been linked to respiratory and cardiovascular diseases, cancers, and premature deaths. These indicators provide a perspective across time and NYC geographies to better characterize air quality and health in NYC. Data can also be explored online at the Environment and Health Data Portal: http://nyc.gov/health/environmentdata.

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.

An estimated 63,600 deaths were attributable to air pollution in the United States in 2021. The annual number of deaths attributable to air pollution in the United States has dropped significantly since 1990. The decline in deaths has coincided with improved air quality, with PM2.5 levels in the U.S. falling more than 40 percent since the turn of the century.

API operated by Louisville Metro that returns AQI information from local sensors operated by APCD. Shows the latest hourly data in a JSON feed.The Air Quality Index (AQI) is an easy way to tell you about air quality without having to know a lot of technical details. The “Metropolitan Air Quality Index” shows the AQI from the monitor in Kentuckiana that is currently detecting the highest level of air pollution. See: https://louisvilleky.gov/government/air-pollution-control-district/servi...See the air quality map (Louisville Air Watch) for more details: airqualitymap.louisvilleky.gov/#Read the FAQ for more information about the AQI data: https://louisvilleky.gov/government/air-pollution-control-district/louis...If you'd prefer air quality forecast data (raw data, maps, API) instead, please see AIRNow: https://www.airnow.gov/index.cfm?action=airnow.local_city&zipcode=40204&...See the Data Dictionary section below for information about what the AQI numbers mean, their corresponding colors, recommendations, and more info and links.To download daily snapshots of AQI for the last 25 years, visit the EPA website, set your year range, and choose, Louisville KY. Then download with the CSV link at the bottom of the page.IFTTT integration trigger that fires and after retrieving air quality from Louisville Metro air sensors via the APIGives a forecast instead of the current conditions, so you can take action before the air quality gets bad.The U.S. EPA AirNow program (www.AirNow.gov) protects public health by providing forecast and real-time observed air quality information across the United States, Canada, and Mexico. AirNow receives real-time air quality observations from over 2,000 monitoring stations and collects forecasts for more than 300 cities.Sign up for a free account and get started using the RSS data feed for Louisville. https://docs.airnowapi.org/feedsAir Quality Forecast via AirNowAQI Level - Value and Related Health Concerns LegendGood 0-50 GreenAir quality is considered satisfactory, and air pollution poses little or no risk.Moderate 51-100 YellowAir 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 Groups 101-150 OrangeMembers of sensitive groups may experience health effects. The general public is not likely to be affected.Unhealthy 151-200 RedEveryone may begin to experience health effects; members of sensitive groups may experience more serious health effects.Very Unhealthy 201-300 PurpleHealth alert: everyone may experience more serious health effects.Hazardous > 300 Dark PurpleHealth warnings of emergency conditions. The entire population is more likely to be affected.Here are citizen actions APCD recommends on air quality alert days, that is, days when the forecast is for the air quality to reach or exceed the “unhealthy for sensitive groups” (orange) level:Don’t idle your car. (Recommended all the time; see the second link below.)Put off mowing grass with a gas mower until the alert ends.“Refuel when it’s cool” (pump gasoline only in the evening or night).Avoid driving if possible. Share rides or take TARC.Check on neighbors with breathing problems.Here are some links in relation to the recommendations:KAIRE, www.helptheair.org/Idle Free Louisville, www.helptheair.org/idle-freeTARCTicket to Ride, tickettoride.org/Lawn Care for Cleaner Air (rebates)Contact:Bryan FrazerBryan.Frazar@louisvilleky.gov

According to the monitoring data from the Embassy of the United States, there was on average 39 micrograms of PM2.5 particles per cubic meter to be found in the air in Beijing during 2023. The air quality has improved considerably since 2013.

Reasons for air pollution in Beijing

China’s capital city Beijing is one of the most populous cities in China with over 20 million inhabitants. Over the past 20 years, Beijing’s GDP has increased tenfold. With the significant growth of vehicles and energy consumption in the country, Beijing’s air quality is under great pressure from the economic development. In the past, the city had a high level of coal consumption. Especially in winter, in which coal consumption increased due to heating, the air quality could get extremely bad on the days without wind. In spring, the wind from the north would bring sand from Mongolian deserts, resulting in severe sandstorms in Beijing. The bad air quality also affected the air visibility and threatened people’s health. On days with very bad air quality, people wearing masks for protection can be seen on the streets in the city.

Methods to improve air quality in Beijing

Over the past years, the government has implemented various methods to improve the air quality in Northern China. Sandstorms, which were quite common 15 years ago, are now rarely seen in Beijing’s spring thanks to afforestation projects on China’s northern borders. The license-plate lottery system was introduced in Beijing to restrict the growth of private vehicles. Large trucks were not allowed to enter certain areas in Beijing. Above all, the coal consumption in Beijing has been restricted by shutting down industrial sites and improving heating systems. Beijing’s efforts to improve air quality has also been highly praised by the UN as a successful model for other cities. However, there is also criticism pointing out that the improvement of Beijing’s air quality is based on the sacrifice of surrounding provinces (including Hebei), as many factories were moved from Beijing to other regions. Besides air pollution, there are other environmental problems like water pollution that China is facing. The industrial transformation is the key to China’s environmental improvement.

The study population included live births from the National Center for Health Statistics (NCHS) for the entire United States for the years 2000–2005 for all 3141 counties. Domain-specific EQIs were used to represent environmental exposure at the county-level for the entire U.S. over the 2000–2005 time period. The EQI includes variables representing five environmental domains: air, water, land, built, and sociodemographic (2). The domain-specific indices include both beneficial and detrimental environmental factors. The air domain includes 87 variables representing criteria and hazardous air pollutants. The water domain includes 80 variables representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination. The land domain includes 26 variables representing agriculture, pesticides, contaminants, facilities, and radon. The built domain includes 14 variables representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment. The sociodemographic environment includes 12 variables representing socioeconomics and crime. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files. This dataset is associated with the following publication: Grabich, S., K. Rappazzo, C. Gray, J. Jagai, Y. Jian, L. Messer, and D. Lobdell. Additive interaction between heterogeneous environmental quality domains (air, water, land, sociodemographic and built environment) on preterm birth. Frontiers in Public Health. Frontiers, Lausanne, SWITZERLAND, 4: 232, (2016).

Data is CMAQ (Community Multiscale Air Quality) air quality modeling data contained in 12km grids (covering the eastern US) and 36 km grids (covering the entire US) for the years 2004, 2005, and 2006. Each CMAQ grid contains a concentration value for an air pollutant (fine particulate matter - PM2.5), and this concentration value can be used to determine the impact of air pollution concentrations on hospital emergency department admissions for asthma, and hospital inpatient admissions for asthma, myocardial infraction (MI), and heart failure (HF) in Baltimore Maryland. CMAQ data is in both .IOAPI (Input/Output Applications Programming Interface) format and .csv (comma-separated value) format. Health data was used in this analysis, but the health data cannot be released because it contains personally identifiable information (PII) on living individuals, and is protected by the Privacy Act of 1974 (as amended), the Health Insurance Portability and Accountability Act (HIPPA) of 1996 (as amended), and is exempt from Freedom of Information Act (FOIA) requests. The health dataset contains information about human research subjects, and access to it was limited by the Institutional Review Board (IRB) decision of 19 February 2014 (Protocol #13-76), and updated on 8 December 2016. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The following folder has been set aside to access this (CMAQ_Data-only) data: ftp://newftp.epa.gov/EPADataCommons/ORD/NERL_SED/EHCAB/Hall_ORD-028187/. Format: Data is CMAQ (Community Multiscale Air Quality) air quality modeling data contained in 12km grids (covering the eastern US) and 36 km grids (covering the entire US) for the years 2004, 2005, and 2006. Each CMAQ grid contains a concentration value for an air pollutant (fine particulate matter - PM2.5), and this concentration value can be used to determine the impact of air pollution concentrations on hospital emergency department admissions for asthma, and hospital inpatient admissions for asthma, myocardial infraction (MI), and heart failure (HF) in Baltimore Maryland. CMAQ data is in both .IOAPI (Input/Output Applications Programming Interface) format and .csv (comma-separated value) format. Health data was used in this analysis, but the health data cannot be released because it contains personally identifiable information (PII) on living individuals, and is protected by the Privacy Act of 1974 (as amended), the Health Insurance Portability and Accountability Act (HIPPA) of 1996 (as amended), and is exempt from Freedom of Information Act (FOIA) requests. The health dataset contains information about human research subjects, and access to it was limited by the Institutional Review Board (IRB) decision of 19 February 2014 (Protocol #13-76), and updated on 8 December 2016. This dataset is associated with the following publication: Braggio, J., E. Hall, S. Weber, and A. Huff. Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland. ATMOSPHERE. MDPI AG, Basel, SWITZERLAND, 11(2): 209, (2020).

This layer includes contains air quality and meteorologic measurements from air monitoring stations in Michigan that is sourced from AirNow. The data begins on March 3rd, 2024 and is updated hourly. Note that this data is preliminary and is subject to validation and changes.

Field Name

Alias

Description

OBJECTID

N/A

N/A

StationID

Station ID

The station ID assigned by EGLE

StationName

Station Name

Station name of the air monitoring station. StationType

Station TypeThe type of air monitoring station. The value 'Permanent' indicates the station is a fixed, long-term installation.

StationStatus

Station Status

Activity status of the station.

LastObservation

Last Observation

Date and time of the most recent recorded observation.

shape

shape

ESRI geometry field.

WD_DEGREES

Wind Direction

Wind direction for current observation expressed in degrees.

WS_MS

Wind Speed

Wind speed measured in meters per second.

TEMP_CTemperatureTemperature measure in degrees Celsius.

PM25_UGM3

PM 2.5

Concentration of particulate matter ≤ 2.5 micrometers (PM2.5) measured in micrograms per cubic meter (µg/m³).

OZONE_PPBOzone

Concentration of ozone (O3) measured in parts per billion (ppb).

NO2_PPB

NO2

Concentration of nitrogen dioxide (NO₂) measured in parts per billion (ppb).

SO2_PPB

SO2Concentration of sulfur dioxide (SO₂) measured in parts per billion (ppb).

CO_PPM

CO

Concentration of carbon monoxide (CO) measured in parts per million (ppm).

NO_PPB

NOConcentration of nitrogen monoxide (NO) measured in parts per billion (ppb).

PM10_UGM3

PM 10

Concentration of particulate matter ≤ 10 micrometers (PM10) measured in micrograms per cubic meter (µg/m³). NOX_PPB

NOxConcentration of nitrogen oxides (NOx) measured in parts per billion (ppb).RWD_DEGREESResultant Wind Direction The average wind direction expressed in degrees. NOY_PPB

NOy

Concentration of total reactive nitrogen (NOy) measured in parts per billion (ppb). RWS_KNOTS

Resultant Wind Speed

The average wind speed measured in knots.

If you have questions related to air quality, please reach out to Susan Kilmer (KilmerS@Michigan.gov or 517-242-2655). If you have map suggestions or functionality issues, please reach out to EGLE-Maps@Michigan.gov.From US EPA AirNow: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. Visit Michigan.gov/EGLE for more information about air monitoring in Michigan.

Context

Air Pollution is a major environmental concern that demands immediate attention. A data-centric approach can help better understand the problem, identify highly impacted areas and target solutions appropriately. The data collected under the NATIONAL AIR QUALITY MONITORING PROGRAMME (N.A.M.P.) is available in the form of a PDF, a nightmare for Data Scientists. Fortunately, it has been converted into a usable CSV format, and every record has been cross-verified to ensure data integrity.

Content

Acknowledgements

NAMP data - Source Image Credits - Veeterzy on Unsplash

We conducted an unmatched case-control study of 5,992 infant mortality cases and 60,000 randomly selected controls from a North Carolina Birth Cohort (2003-2015). PM2.5 during critical exposure periods (trimesters, pregnancy, first month alive) were estimated using residential address and a national spatiotemporal model at census block centroid. Here we describe data sources for outcome (i.e., infant mortality) and exposure (i.e., PM2.5) data. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The North Carolina Birth Cohort data are not publicly available as it contains personal identifiable information. Data may be requested through the NCDHHS, Division of Public Health with proper approvals. Air pollutant concentrations for PM2.5 from the national spatiotemporal model are available upon request and may require a processing fee. Air monitoring data questions can be directed to Ms. Amanda Gassett at the University of Washington. Format: Birth certificate data from the State Center for Health Statistics of the NC Department of Health and Human Services linked with data from the Birth Defects Monitoring Program (NC BDMP) to create a birth cohort of all infants born in NC between 2003-2015. The NC BDMP is an active surveillance system that follows NC births to obtain birth defect diagnoses up to 1 year after the date of birth as well as identify infant deaths during the first year of life and include relevant information from the death certificate. A national spatiotemporal model provided data on predicted PM2.5 concentrations over critical prenatal and postnatal time periods. The prediction model used data from research and regulatory monitors as well as a large (>200) array of geographic covariates to create fine scale spatial and temporal predictions. The model has a cross-validated R2 of 0.89 for PM2.5. Concentrations were predicted for every 2 weeks in the study period at the centroid of each 2010 census block in NC. This dataset is associated with the following publication: Jampel, S., J. Kaufman, D. Enquobahrie, A. Wilkie, A. Gassett, and T. Luben. Association between fine particulate matter (PM2.5) and infant mortality in a North Carolina Birth Cohort (2003-2015). Environmental Epidemiology. Wolters Kluwer, Alphen aan den Rijn, NETHERLANDS, 8(6): e350, (2024).

The Texas Birth Defects Registry (TBDR) of the Texas Department of State Health Services (TDSHS) is an active surveillance system that maintains information on infants with structural and chromosomal birth defects born to mothers residing in Texas at the time of birth (Texas Department of State Health Services, 2019). TBDR staff review medical records to identify and abstract relevant case information, which then undergoes extensive quality checks (Texas Department of State Health Services, 2019). All diagnoses are made prenatally or within one year after delivery (Texas Department of State Health Services, 2019). Data on cases was obtained from the TBDR. Information on live births for the denominators and on covariates for cases and denominators was obtained from the Texas Department of State Health Services Center for Health Statistics. This research was approved by the Texas Department of State Health Services Institutional Review Board and US EPA Human Subjects Review.

The Environmental Quality Index (EQI) estimates overall county-level environmental quality for the entire US for 2006-2010. The construction of the EQI is described elsewhere (United States Environmental Protection Agency, 2020). Briefly, the national data was compiled to represent simultaneous, cumulative environmental quality across each of the five domains: air (43 variables) representing criteria and hazardous air pollutants; water (51 variables), representing overall water quality, general water contamination, recreational water quality, drinking water quality, atmospheric deposition, drought, and chemical contamination; land (18 variables), representing agriculture, pesticides, contaminants, facilities, and radon; built (15 variables), representing roads, highway/road safety, public transit behavior, business environment, and subsidized housing environment; and sociodemographic (12 variables), representing socioeconomics and crime. The variables in each domain specific index were reduced using principal component analysis (PCA), with the first component retained as that domain’s index value. The domain specific indices were valence corrected to ensure that the directionality of the variables was consistent with higher values suggesting poorer environmental quality. The domain specific indices were then processed through a second PCA and the first index retained as the overall EQI. The overall and domain specific EQI indices are publicly available through the US EPA (United States Environmental Protection Agency: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Human health data are not available publicly. EQI data are available at: https://edg.epa.gov/data/Public/ORD/NHEERL/EQI. Format: Data are stored as csv files.

This dataset is associated with the following publication: Krajewski, A., K. Rappazzo, P. Langlois, L. Messer, and D. Lobdell. Associations between cumulative environmental quality and ten selected birth defects in Texas. Birth Defects Research. John Wiley & Sons, Inc., Hoboken, NJ, USA, 113(2): 161-172, (2020).

Abstract

MEJ aims to create easy-to-use, publicly-available maps that paint a holistic picture of intersecting environmental, social, and health impacts experienced by communities across the US.

With guidance from the residents of impacted communities, MEJ combines environmental, public health, and demographic data into an indicator of vulnerability for communities in every state. MEJ’s goal is to fill an existing data gap for individual states without environmental justice mapping tools, and to provide a valuable tool for advocates, scholars, students, lawyers, and policy makers.

Methodology

The negative effects of pollution depend on a combination of vulnerability and exposure. People living in poverty, for example, are more likely to develop asthma or die due to air pollution. The method MEJ uses, following the method developed for CalEnviroScreen, reflects this in the two overall components of a census tract’s final “Cumulative EJ Impact”: population characteristics and pollution burden. The CalEnviroScreen methodology was developed through an intensive, multi-year effort to develop a science-backed, peer-reviewed tool to assess environmental justice in a holistic way, and has since been replicated by several other states.

CalEnviroScreen Methodology:

• Population characteristics are a combination of socioeconomic data (often referred to as the social determinants of health) and health data that together reflect a populations' vulnerability to pollutants. Pollution burden is a combination of direct exposure to a pollutant and environmental effects, which are adverse environmental conditions caused by pollutants, such as toxic waste sites or wastewater releases. Together, population characteristics and pollution burden help describe the disproportionate impact that environmental pollution has on different communities.

• Every indicator is ranked as a percentile from 0 to 100 and averaged with the others of the same component to form an overall score for that component. Each component score is then percentile ranked to create a component percentile. The Sensitive Populations component score, for example, is the average of a census tract’s Asthma, Low Birthweight Infants, and Heart Disease indicator percentiles, and the Sensitive Populations component percentile is the percentile rank of the Sensitive Populations score.

• The Population Characteristics score is the average of the Sensitive Populations component score and the Socioeconomic Factors component score. The Population Characteristics percentile is the percentile rank of the Population Characteristics score.

• The Pollution Burden score is the average of the Pollution Exposure component score and one half of the Environmental Effects component score (Environmental Effects may have a smaller effect on health outcomes than the indicators included the Exposures component so are weighted half as much as Exposures). The Pollution Burden percentile is the percentile rank of the Pollution Burden score.

• The Populaton Characteristics and Pollution Burden scores are then multiplied to find the final Cumulative EJ Impact score for a census tract, and then this final score is percentile-ranked to find a census tract's final Cumulative EJ Impact percentile.

• Census tracts with no population aren't given a Population Characteristics score.

• Census tracts with an indicator score of zero are assigned a percentile rank of zero. Percentile rank is then only calculated for those census tracts with a score above zero.

• Census tracts that are missing data for more than two indicators don't receive a final Cumulative EJ Impact ranking.

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LISTOS_Ground_OuterIsland_Data is the Long Island Sound Tropospheric Ozone Study (LISTOS) ground site data collected at the Outer Island ground site during the LISTOS field campaign. This product is a result of a joint effort across multiple agencies, including NASA, NOAA, the EPA Northeast States for Coordinated Air Use Management (NESCAUM), Maine Department of Environmental Protection, New Jersey Department of Environmental Protection, New York State Department of Environmental Conservation, and several research groups at universities. Data collection is complete. The New York City (NYC) metropolitan area (comprised of portions of New Jersey, New York, and Connecticut in and around NYC) is home to over 20 million people, but also millions of people living downwind in neighboring states. This area continues to persistently have challenges meeting past and recently revised federal health-based air quality standards for ground-level ozone, which impacts the health and well-being of residents living in the area. A unique feature of this chronic ozone problem is the pollution transported in a northeast direction out of NYC over Long Island Sound. The relatively cool waters of the Long Island Sound confine the pollutants in a shallow and stable marine boundary layer. Afternoon heating over coastal land creates a sea breeze that carries the air pollution inland from the confined marine layer, resulting in high ozone concentrations in Connecticut and, at times, farther east into Rhode Island and Massachusetts. To investigate the evolving nature of ozone formation and transport in the NYC region and downwind, Northeast States for Coordinated Air Use Management (NESCAUM) launched the Long Island Sound Tropospheric Ozone Study (LISTOS). LISTOS was a multi-agency collaborative study focusing on Long Island Sound and the surrounding coastlines that continually suffer from poor air quality exacerbated by land/water circulation. The primary measurement observations took place between June-September 2018 and include in-situ and remote sensing instrumentation that were integrated aboard three aircraft, a network of ground sites, mobile vehicles, boat measurements, and ozonesondes. The goal of LISTOS was to improve the understanding of ozone chemistry and sea breeze transported pollution over Long Island Sound and its coastlines. LISTOS also provided NASA the opportunity to test air quality remote sensing retrievals with the use of its airborne simulators (GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS), and Geostationary Trace gas and Aerosol Sensory Optimization (GeoTASO)) for the preparation of the Tropospheric Emissions; Monitoring of Pollution (TEMPO) observations for monitoring air quality from space. LISTOS also helped collaborators in the validation of Tropospheric Monitoring Instrument (TROPOMI) science products, with use of airborne- and ground-based measurements of ozone, NO2, and HCHO.

Data were collected in 70 detached houses built in 2011-2017 in compliance with the mechanical ventilation requirements of California’s building energy efficiency standards. Each home was monitored for a one-week period with windows closed and the central mechanical ventilation system operating. Pollutant measurements included time-resolved fine particulate matter (PM2.5) indoors and outdoors and formaldehyde and carbon dioxide (CO2) indoors. Time-integrated measurements were made for formaldehyde, NO2 and nitrogen oxides (NOX) indoors and outdoors. Operation of the cooktop, range hood and other exhaust fans was continuously recorded during the monitoring period. One-time diagnostic measurements included mechanical airflows and envelope and duct system air leakage. All homes met or were very close to meeting the ventilation requirements. On average the dwelling unit ventilation fan moved 50% more airflow than the minimum requirement. Pollutant concentrations were similar or lower than those reported in a 2006-2007 study of California new homes built in 2002-2005. Mean and median indoor concentrations were lower by 44% and 38% for formaldehyde and 44% and 54% for PM2.5. Ventilation fans were operating in only 26% of homes when first visited and the control switches in many homes did not have informative labels as required by building standards.

Methods Overview of HENGH Study

The HENGH study was conceived, designed and implemented for the purpose of evaluating impacts of residential mechanical ventilation equipment requirements that have been part of the California’s Building Energy Efficiency Standards since 2008. Starting in 2009, these standards have required bath and kitchen exhaust fans and dwelling unit mechanical ventilation with sizing and performance levels based on the residential ventilation standard (62.2) of the ASHRAE organization. The ventilation standards are intended to help maintain indoor air quality as homes are constructed with tighter shells to reduce uncontrolled outdoor air infiltration for energy efficiency.

The study was led by Lawrence Berkeley National Laboratory (LBNL). All study protocols involving interactions and collection of data from private individuals and monitoring in occupied homes were reviewed and approved by the LBNL Human Subjects Committee. Research Funding and technical contributions of collaborators are noted below in the acknowledgements.

The field study included the following data collection elements:

Homeowner survey about household demographics, ventilation practices, activities that can impact indoor air quality, and satisfaction with environmental conditions in the home.
Compilation of basic data about the houses (location, size, number of bedrooms, etc.) and gas appliances and mechanical ventilation equipment (technology type, make, model, etc.)
Measurements of air leakiness of the building envelope and forced air system ductwork.
Measurements of the following parameters over a weeklong monitoring period:

  Airflows of all mechanical ventilation equipment;
  Air pollutants and environmental parameters indoors and outdoors;
  Cooktop and oven surface temperatures to identify burner use.


Participants were expected to complete a daily activity log. 

What is contained in this dataset?

The dataset contains the most relevant information collected about the 70 houses and their mechanical equipment, results of the participant survey, results of air leakage and airflow measurements at the homes, pollutant concentrations measured by time-integrated passive samplers inside and outside of the home, usage of cooktop and oven, external door open state, and time-series or air pollutants and environmental indicators measured within and outside of the houses.

Organization of Dataset

Airflow

  This folder contains time series data of monitored mechanical ventilation equipment, estimates of air infiltration rate, and overall air exchange rate. There is one csv file for each home. See HENGH_Airflow_ReadMe for more details. 


Ambient_PM

  This folder contains a summary of PM2.5 data reported by one or more ambient air monitoring stations nearest to each study home. There is one EXCEL file containing PM2.5 data reported from up to three closest regulatory monitoring sites. A composite estimate of ambient PM2.5 was calculated for each home using an inverse distance weighing method. 


Home_Equipment_Data

  This folder contains data about the house, including basic characteristics, air leakage test results, and measured airflow rates of mechanical ventilation equipment. There is one EXCEL file containing the data for all homes. The EXCEL file has ReadMe information about the data provided and a note about data quality issue concerning exhaust airflow measurements of over-the-range microwaves.  


IAQ_Monitoring

  This folder contains time-resolved air quality data, including estimated PM2.5 as measured by photometry (PM), carbon dioxide (CO2), nitrogen dioxide (NO2), formaldehyde (FRM), temperature (T), and relative humidity (RH). There is one csv file of 1-minute time-series data for each home. See HENGH_IAQ_Monitoring_ReadMe for data header definitions and data issues. 


IAQ_Sample

  This folder contains the results of time-integrated air quality samples, including passive measurements of formaldehyde, nitrogen dioxide and nitrogen oxides, and PM2.5 gravimetric filter measurements. There is one EXCEL file containing all data. Detail information about chemical analysis of air samples are provided elsewhere in the journal paper and report. 


Occupant_Activity

  This folder contains tabulated information provided by study participants from their daily activity logs. There is one EXCEL file containing data transcribed by a staff member, which was independently spot checked by another staff to confirm accuracy. The PDF file is the daily activity log used. 


Occupant_Survey

  This folder contains results of a survey about the occupants, their general activities related to ventilation and IAQ satisfaction, completed by study participants. There is one EXCEL file containing data transcribed by a staff member. Two homes did not complete surveys; these homes have "No survey" in each data file. Questions for the occupant surveys are provided in MS Word and PDF formats. 


State_Monitoring

  This folder contains time series data of cooking burners monitored with iButton temperature sensors and open/close status of external (mostly patio) doors monitored with state sensors. There is one csv file for each home. See HENGH_State_Monitoring_ReadMe for more details.

We assembled a retrospective, administrative cohort of singleton births in North Carolina from 2003-2015. We used US EPA EQUATES data to assign long-term SO2 gestational exposures to eligible births for the entire pregnancy and by trimester. We used multivariable generalized linear regression to estimate risk differences (RD (95%CI)) per 1-ppb increase in SO2, adjusted for gestational parent education, Medicaid status, marital status, and season of conception. Multi-pollutant models were additionally adjusted for other criteria air co-pollutants (O3, PM2.5, NO2). This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: The North Carolina Birth Cohort data are not publicly available as it contains personal identifiable information. Data may be requested through the NCDHHS, Division of Public Health with proper approvals. Data from EPA's CMAQ EQUATES model are publicly available. Format: Birth certificate data from the State Center for Health Statistics of the NC Department of Health and Human Services linked with data from the Birth Defects Monitoring Program (NC BDMP) to create a birth cohort of all infants born in NC between 2003-2015. The NC BDMP is an active surveillance system that follows NC births to obtain birth defect diagnoses up to 1 year after the date of birth as well as identify infant deaths during the first year of life and include relevant information from the death certificate. EPA's publicly available CMAQ EQUATES model provided data on predicted SO2 concentrations over critical windows of gestation. The model predicts daily 1-hour maximum SO2 concentrations for 12 km x 12 km grid cells across the study area. This dataset is associated with the following publication: Wilkie, A., T. Luben, K. Rappazzo, K. Foley, C. Woods, M. Serre, D. Richardson, and J. Daniels. Long-term ambient sulfur dioxide exposure during gestation and preterm birth in North Carolina, 2003-2015. ATMOSPHERIC ENVIRONMENT. Elsevier B.V., Amsterdam, NETHERLANDS, 333(September 15): 120669, (2024).

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.

CTD, marine invertebrate pathology, benthic organisms, and marine toxic substances and pollutants data were collected using CTD, net casts, and other instruments from the SEA TRANSPORTER and other platforms in the Gulf of Mexico. Data were collected from 20 May 1978 to 15 January 1979. Data were submitted by the South West Research Institute in Houston with support from the Ocean Continental Shelf (OCS). Full format and format code descriptions are available at http://www.nodc.noaa.gov/General/NODC-datafmts.html.

The F022 format contains high-resolution data collected using CTD (conductivity-temperature-depth) and STD (salinity-temperature-depth) instruments. As they are lowered and raised in the oceans, these electronic devices provide nearly continuous profiles of temperature, salinity, and other parameters. Data values may be subject to averaging or filtering or obtained by interpolation and may be reported at depth intervals as fine as 1m. Cruise and instrument information, position, date, time and sampling interval are reported for each station. Environmental data at the time of the cast (meteorological and sea surface conditions) may also be reported. The data record comprises values of temperature, salinity or conductivity, density (computed sigma-t), and possibly dissolved oxygen or transmissivity at specified depth or pressure levels. Data may be reported at either equally or unequally spaced depth or pressure intervals. A text record is available for comments.

Marine Invertebrate Pathology (F063) contains data from examinations of diseased marine invertebrates. Although these data maybe from field observations, they derive primarily from laboratory analyses. Data include: catch statistics (e.g., total weight, number of individual, identity of disease and number of diseased individuals) by species for any number of species; and biological condition of selected specimens. The size location, and frequency of lesions may be reported for individual specimens. Specimens are identified by an NODC Taxonomic Code. A text record is available for comments.

The F0132 contains data from field sampling or surveys of bottom dwelling marine organisms. The data provide information on species abundance, distribution, and biomass; they may have been collected by point sampling (grab or core), by tow (dredge, trawl or net), by photographic surveys, or by other methods. Cruise information such as vessel, start and end dates, investigator, and institution/agency; station numbers, positions and times; and equipment and methods are reported for each survey. Environmental data reported at each sampling site may include meteorological and sea surface conditions; surface and bottom temperature, salinity and dissolved oxygen; and sediment characteristics. Number of individual organisms and total weight of organisms is reported for each species. A text record is available for comments.

This file contains data on ambient concentrations of toxic substances and other pollutants in the marine environment. The data derive from laboratory analyses of samples of water, sediment, or marine organisms. Samples may have been collected near marine discharge sites or during ocean monitoring surveys of large areas. Field observations of tar deposits on beaches may also be reported. Survey information includes platform type, start and end dates, and investigator and institution. If data are collected near a discharge site, discharge location, depth, distance to shore, average volume, and other characteristics are reported. Position, date, time and environmental conditions are reported for each sample station. Environmental data may include meteorological and sea surface conditions, tide stage and height, depth of the thermocline or mixed layer surface temperature and salinity, and wave height and periods. Sample characteristics, collection methods, and laboratory techniques are reported for each sample collected and analyzed. The data record comprises concentration values (or a code to indicate trace amounts) for each chemical substance analyzed. Chemical substances are identified by codes based on the registry numbers assigned by the Chemical Abstracts Service (CAS) of the American Chemical Society. Marine organisms from which samples have been taken are identified using the 12-digit NODC Taxonomic Code. A text record is available for optional comments.