THIS DATA ASSET NO LONGER ACTIVE: This is metadata documentation for the Region 7 Air Compliance Complaint Database (ACCD) which logs all air pollution complaints received by Region 7. It contains information about the complaint along with how the complaint was addressed. The Air and Waste Management Division is the primary managing entity for this database. This work falls under objectives for EPA's 2003-2008 Strategic Plan (Goal 1) for Clean Air & Global Climate Change, which are to achieve healthier outdoor air.

Air pollution has a significant impact on human health and the economy. Air quality in Sydney is usually very good by international standards. For more information about air quality in Sydney, how our ventilation systems work to manage air quality within and outside the tunnels, and what has contributed to improve vehicle emissions visit the [Air Quality Portal](https://v2.communityanalytics.com.au/rms/air-quality/#). This dataset provides standardised measures of: * Carbon Monoxide * Nitrogen dioxide * Nitrogen oxides * Ozone * Sulfur dioxide * Particles < 10μm diameter * Particles < 2.5μm diameter * BTEX * Methane * Non-Methane Hydrocarbons * THC The data captured is from 01/01/2004 - 31/12/2017 and only includes sites where RMS had access to the monitor's data. More information about the sites covered can be found in the Report and associated data files.

Ambient monitoring measures the status of air quality throughout the state to assess trends, compliance with federal and state air quality standards, effectiveness of control strategies and attainment plans, health effects and environmental damage; respond to citizen complaints; evaluate specific geographic or hot-spot air quality concerns; and create environmental indicators. Emission inventory is the cataloging of sources of air pollution and the emissions from those sources. Inventory data are critical to the understanding of the causes of air pollution problems and creation of appropriate solutions. Meteorological forecasting and dispersion modeling of air pollutants are essential to understanding the movement and buildup of air pollution; the carrying capacity of airsheds; the interaction of pollutants; and the location of maximum impact of sources of pollution. As of September 26, 2005 there are no longer any areas of Washington designated as "NONATTAINMENT."

Tacoma-Pierce County Nonattainment Area (a.k.a. Wapato Hills-Puyallup River Valley PM2.5 Nonattainment Area)

Ambient monitoring measures the status of air quality throughout the state to assess trends, compliance with federal and state air quality standards, effectiveness of control strategies and attainment plans, health effects and environmental damage; respond to citizen complaints; evaluate specific geographic or hot-spot air quality concerns; and create environmental indicators. Emission inventory is the cataloging of sources of air pollution and the emissions from those sources. Inventory data are critical to the understanding of the causes of air pollution problems and creation of appropriate solutions. Meteorological forecasting and dispersion modeling of air pollutants are essential to understanding the movement and buildup of air pollution; the carrying capacity of airsheds; the interaction of pollutants; and the location of maximum impact of sources of pollution. As of September 26, 2005 there are no longer any areas of Washington designated as "NONATTAINMENT."

**This information is provided by Liverpool City Council** Air Quality sensors were installed across the Liverpool CBD through the Liverpool Smart Pedestrian Project in 2018. The project was co-funded by Council and the Australian Government Smart Cities and Suburbs Grant. The sensors were designed by University of Wollongong, a partner on the project. They measure PM2.5 and PM10. Use the Go to Resource to view the data source.

Every day the Air Quality Index (AQI) tells you how clean or polluted your outdoor air is, along with associated health effects that may be of concern. The AQI translates air quality data into numbers and colors that help people understand when to take action to protect their health.

The tool is designed to assist Environmental Health Practitioners and Technical Officers in the assessment of the hazard of Excess Cold in UK dwellings.

Prior to the use of the Cerro Colorado Landfill, the City of Albuquerque, Bernalillo County and private landowners operated several other landfills in and around Albuquerque. Though these landfills are now closed and have not accepted trash for some time, there is still a great deal of action taking place onsite. Landfills located in arid climates such as Albuquerque’s can create landfill gas for decades after being closed. These gases along with other products of decomposing landfills are potentially explosive and can impact water quality and health in addition to creating strong odors. The Environmental Services Division within the Environmental Health Department monitors these older landfills for gas generation, gas migration and groundwater contamination. Additionally, the Environmental Services Division recommends safety measures for development on and near these closed landfills (see Interim Guidelines for Development near Landfills). The Environmental Services Division works with the City of Albuquerque Planning Department to ensure that areas near old landfills are developed safely according to the guidelines. The Environmental Services Division also initiates remediation work for landfills that pose a risk. Some of these remediation measures include groundwater treatment and landfill gas collection. The map below provides locations of all known closed landfills in the Albuquerque metro area. The map also provides the buffer zones for all of these landfills. Each individual landfill can be selected for more information about the selected landfill. Contact information is provided for landfills that are not managed by the City of Albuquerque, Environmental Health Department.

This feature class represents the historical (1970-1999) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the mid-century (2030-2059) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the end-of-century (2070-2099) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the historical (1970-1999) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the mid-century (2030-2059) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the end-of-century (2070-2099) scenario for bull trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields BT_0BRK - BT_100BRK indicate the probabilities of bull trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the historical (1970-1999 scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields CT_0BRK - CT_100BRK indicate the probabilities of cutthroat trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the mid-century (2030-2059) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields CT_0BRK - CT_100BRK indicate the probabilities of cutthroat trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the end-of-century (2070-2099) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields CT_0BRK - CT_100BRK indicate the probabilities of cutthroat trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the historical (1970-1999) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields CT_0BRK - CT_100BRK indicate the probabilities of cutthroat trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the mid-century (2030-2059) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields CT_0BRK - CT_100BRK indicate the probabilities of cutthroat trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

This feature class represents the end-of-century (2070-2099) scenario for cutthroat trout, derived from the Climate Shield fish distribution models. These models provide stream-specific probabilistic predictions about the occurrence of juvenile bull trout and cutthroat trout in association with three different scenarios for climate change and brook trout invasions. These datasets indicate all potential cold-water habitats less than 11 degrees Celsius. The attribute fields CT_0BRK - CT_100BRK indicate the probabilities of cutthroat trout occurrence within a cold-water habitat based on the prevalence of brook trout at 0%, 25%, 50%, 75%, or 100% of the sites within a habitat. The probabilities were predicted using the Climate Shield native trout models developed from known species occurrence in greater than 500 cold-water streams. The stream centerlines were based on the National Hydrography Dataset (NHD) but were modified for purposes of modeling and cross-walking to other datasets.

The new 2010 Dietary Guidelines for Americans focus on balancing calories with physical activity, and encourage Americans to consume more healthy foods like vegetables, fruits, whole grains, fat-free and low-fat dairy products, and seafood, and to consume less sodium, saturated and trans fats, added sugars, and refined grains.

The Drinking Water Treatability Database (TDB) presents referenced information on the control of contaminants in drinking water. It allows drinking water utilities, first responders to spills or emergencies, treatment process designers, research organizations, regulators and others to access referenced information gathered from thousands of literature sources on regulated and unregulated contaminants.

EHSS Web Services (AUWS) provides for the maintenance of content for EHSS information on Energy.Gov, Powerpedia and the EHSS intranet.

The Eating & Health (EH) Module of the American Time Use Survey (ATUS) collects data to analyze relationships among time use patterns and eating patterns, nutrition, and obesity; food and nutrition assistance programs; and grocery shopping and meal preparation.

Transport for NSW provides projections of employment at the small area (Travel Zone or TZ) level for NSW. The latest version is Travel Zone Projections 2022 (TZP22), released November 2022. This new version TZP22 is an update on the previously published [TZP19](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/77e880c1-0073-42bd-850a-ddf974e26cd6) and aligns with the [NSW Government Common Planning Assumptions](https://www.treasury.nsw.gov.au/information-public-entities/common-planning-assumptions). TZP22 Employment Projections are for employed persons by place of work. They are provided by Industry using two breakdowns: * 33 industry categories (equivalent to the ABS 1-digit Australia and New Zealand Standard Industrial Classification (ANZSIC) codes with the exception of Manufacturing which is at 2-digit level). * 4 Broad Industry Categories (groupings of the above) The projections in this release, TZP22 are presented annually 2016 to 2026 and five-yearly from 2026 to 2066 and are in TZ16 geography. Please note, TZP22 is based on best available data as at early to mid 2022. It includes the impacts from the Covid-19 pandemic and does not include results from the ABS 2021 Census as the relevant data had not been released at the time of TZP22 production. **Key Data Inputs used:** * TZP22 Workforce Projections * Census Journey to Work 2016 dataset by Destination Zone - ABS * State-level Employment projections – NSW Treasury * Employment by industry projections - Victoria University * Future Employment Development Database (FEDD) - a custom dataset compiled by TfNSW in late 2019 and updated in mid-2022, that presents the number of jobs expected from major projects based on publicly available documents. For a summary of the TZP22 Projections method please refer to the [TZP22 Factsheet](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/cabdece8-98a2-4004-b2bc-30e4d153a2da) For more detail on the projection process please refer to the [TZP22 Technical Guide](https://opendata.transport.nsw.gov.au/dataset/employment-projections/resource/ca2fcd4d-fcaf-412a-b761-e5c86af6f570) Additional land use information for [population](https://opendata.transport.nsw.gov.au/dataset/population-projections) and [workforce](https://opendata.transport.nsw.gov.au/dataset/workforce-projections) as well as [Travel Zone boundaries for NSW](https://opendata.transport.nsw.gov.au/dataset/travel-zones-2016) are also available for download on the Open Data Hub. A visualisation of the employment projections is available on the Transport for NSW Website under [Reference Information.](https://www.transport.nsw.gov.au/data-and-research/reference-information/travel-zone-explorer-visualisation) **Cautions** The TZP22 dataset represents one view of the future aligned with the NSW Government Common Planning Assumptions and population and economic projections. The projections are not based on specific assumptions about future new transport infrastructure, but do take into account known land-use developments underway or planned, and strategic plans. * TZP22 is a strategic state-wide dataset and caution should be exercised when considering results at detailed breakdowns. * The TZP22 outputs represent a point in time set of projections (as at early to mid 2022). * The projections are not government targets. * Travel Zone (TZ) level outputs are projections only and should be used as a guide. As with all small area data, aggregating of travel zone projections to higher geographies leads to more robust results. * As a general rule, TZ-level projections are illustrative of a possible future only. * More specific advice about data reliability for the specific variables projected is provided in the “Read Me” page of the Excel format summary spreadsheets on the TfNSW Open Data Hub. * Caution is advised when comparing TZP22 with the previous set of projections (TZP19) due to addition of new data sources for the most recent years, and adjustments to methodology. **Further cautions and notes can be found in the TZP22 Technical Guide.**

The NMEDB is a publicly available application that consolidates New Mexico's environmental and public health data in an interactive map of the state. The NMEDB allows agencies, the public, private industry, and conservation practitioners to obtain a comprehensive view of what's happening on New Mexico's landscapes to enable data-driven decisions and minimize negative impacts to human health, plants, animals, land, air, and water.

Food environment factors--such as store/restaurant proximity, food prices, food and nutrition assistance programs, and community characteristics--interact to influence food choices and diet quality. Research is beginning to document the complexity of these interactions, but more is needed to identify causal relationships and effective policy interventions. The objectives of the Atlas are to assemble statistics on food environment indicators to stimulate research on the determinants of food choices and diet quality, and to provide a spatial overview of a community's ability to access healthy food and its success in doing so.

Find the calorie content of any food or beverage using the Food-a-pedia, looking at the Nutrition Facts label, or checking product or restaurant websites

The Air Quality API allows you to request air quality data for a specific location including: more than 70 AQ indexes, pollutants, and health recommendations. It covers over 100 countries with a resolution of 500 x 500 meters. Use of the API requires registration on the Google Cloud platform and is charged according to the volume of requests. At the time of writing (October 2023), there is no free tier.

Explore Saudi Arabia's government final consumption expenditure dataset with detailed information on sectors such as education, health, defense, and more. Gain insights into the country's social service spending and economic services. Other Community & Social Services, Education, Other Purposes, Economic Services, Social Security & Welfare Services, Total, Housing & Community Amenities, Defence, Health, General Public Service, housing, education, health, Defence, social, service, economic, SAMA Annual Saudi Arabia Follow data.kapsarc.org for timely data to advance energy economics research..2020: Provisional 

The Great Lakes Initiative Toxicity Data Clearinghouse is a central location for information on criteria, toxicity data, exposure parameters and other supporting documents used in developing water quality standards in the Great Lakes Watershed.

Healthy Access Locator map can be used to view schools that have received a Healthier US Schools Challenge Award (HUSSC). To get started, click on Search Awards and enter your search criteria. When the information displays on the map, you can click a star for additional details or see a summary of your results below the map. You can also use the Data Layers feature to display different data layers on obesity and diabetes prevalence, SNAP Participation Rates, and SNAP Outreach Plans by states. (HUSSC Awards as of May 30, 2013).

The Human Exposure Database System (HEDS) provides public access to data sets, documents, and metadata from EPA on human exposure. It is primarily intended for scientists involved in human exposure studies or work requiring such data.

Environmental concerns surrounding drilling for gas are intense due to expansion of shale gas drilling operations. Controversy surrounding the impact of drilling on air and water quality has pitted industry and lease - holders against individuals and groups concerned with environmental protection and public health. Because animals often are exposed continually to air, soil, and groundwater and have more frequent reproductive cycles, animals can be used as sentinels to monitor impacts to human health. This study involved interviews with animal owners who live near gas drilling operations. The findings illustrate which aspects of the drilling process may lead to health problems and suggest modifications that would lessen but not eliminate impacts. Complete evidence regarding health impacts of gas drilling cannot be obtained due to incomplete testing and disclosure of chemicals, and nondisclosure agreements. Without rigorous scientific studies, the gas drilling boom sweeping the world will remain an uncontrolled health experiment on an enormous scale.

This study is the fourth in a series that uses the National Health and Nutrition Examination Survey data to examine the relationship between SNAP participation and indicators of diet quality, nutrition, and health. As in previous studies, this study compares SNAP participants with income-eligible and higher income nonparticipants, by age and gender.

EPA?s Integrated Risk Information System (IRIS) is a compilation of electronic reports on specific substances found in the environment and their potential to cause human health effects.

MyPyramid Food Data provides information on the total calories; calories from solid fats, added sugars, and alcohol (extras); MyPyramid food group and subgroup amounts; and saturated fat content of over 1,000 commonly eaten foods with corresponding commonly used portion amounts. This information is key to help consumers meet the recommendations of the Dietary Guidelines for Americans and manage their weight by understanding how many calories are consumed from "extras." CNPP has created an interactive tool from this data set available on the web at MyFood-a-pedia.gov. A mobile version is coming soon to provide consumers with assistance on-the-go.

This site is part of pilot effort at the US Department of Energy (DOE) - Office of NEPA Policy and Compliance to evaluate providing IT web services as a shared service, hosted on the cloud, and using only Free and Open Source Software (FOSS). The site is a collaborative data and document sharing platform, data is made publically available both as a downloadable file in multiple Open Standard formats or as a web service using Open Geospatial Construtium (OGC) Open Standard services (WMS/WFS/WCS).

People drink and use water every day. Therefore, the environmental health impacts of drinking water are extremely important. The majority of New Mexicans are provided high quality drinking water. About 90% of people in New Mexico get their water from a Community Drinking Water system. The US Environmental Protection Agency (EPA) sets regulations for treating and monitoring drinking water delivered by community water systems. There are water quality standards and monitoring requirements for over 90 contaminants. The New Mexico Environmental Public Health Tracking works closely with community, state, and federal organizations to explore connections between drinking water and health outcomes. In addition our Biomonitoring Program program looks at arsenic and Contaminants in urine and drinking water.

Find out more about how the environment may be affecting your health with this easy to use tool that lets you see health and environmental information in one place. Learn about environmental health issues in your community and what you can do to protect yourself and your family. Use this website to answer questions about air quality, drinking water, cancer, and a wide variety of other topics.

National Training Center provides for the infrastructure and applications necessary to develop and deliver safety and security training courses across the department.

The data presented in this dataset is invaluable for monitoring the potential of the food supply to meet nutritional needs; for examining relationships between food supply nutrients and health; and for examining dietary trends of Americans. Additionally, food supply nutrient estimates reflect Federal enrichment and fortification standards and technological advances in the food industry and contribute to the Federal dietary guidance system. As such, these data are of interest to agricultural policymakers, economists, nutrition researchers, and nutrition and public health educators. Data are provided for the following nutrients and their food sources from the major food groups.

NOTE: This data product is no longer being updated. This data product identifies which countries, under APHIS phytosanitary rules, are eligible to export to the United States the fresh fruits and vegetables that are most important in the American diet. Increased trade in fresh fruits and vegetables provides U.S. consumers with a variety of benefits including the possibility of improved nutrition by making these products available year-round. Imports of these products are regulated by USDA's Animal and Plant Health and Inspection Service (APHIS) to reduce the risk of inadvertent entry of pests and diseases that could harm agriculture, public health, navigation, irrigation, natural resources, or the environment. This data product identifies which countries, under APHIS phytosanitary rules, are eligible to export to the United States the fresh fruits and vegetables that are most important in the American diet. Current data represent country eligibility as of June 2012. Previous data represent eligibility in June of 2008 through 2011 and in February of 2007. Data on the absolute and relative importance of these countries in international production and trade, individually and in aggregate, are also included. This data product supports the objectives of the Program for Research on the Economics of Invasive Species (PREISM) under which ERS funded research to improve the economic basis of decisionmaking concerning invasive species issues, policies, and programs between 2003 and 2008.

To further transparency and openness, DOE established a policy to document and post online all CX determinations involving classes of actions listed in Appendix B to Subpart D of the DOE NEPA regulations (10 CFR Part 1021). This raw data set contains CX determinations required to be posted under the policy, and also some for which documentation and posting are optional, i.e., determinations involving classes of actions listed in Appendix A or made before the policy's effective date of November 2, 2009. The data set includes information by state, CX applied, date range, DOE Program, Field, or Site Office, keyword, and whether the CX determination is for a project related to the American Recovery and Reinvestment Act (Recovery Act or ARRA) of 2009. The web address to the CX determination documents are provided. This data set will be updated approximately monthly. See www.gc.doe.gov/NEPA/categorical_exclusion_determinations.htm for information on DOE CX procedures. For further information on DOE's NEPA compliance program, see www.gc.energy.gov/nepa or email: askNEPA@hq.doe.gov.

The SuperTracker is an online tool that helps you track what you currently eat and drink, gives you a personalized plan for what you should eat and drink, and guides you to make better choices.

The Toxicity Reference Database (ToxRefDB) contains approximately 30 years and $2 billion worth of animal studies. ToxRefDB allows scientists and the interested public to search and download thousands of animal toxicity testing results for hundreds of chemicals that were previously found only in paper documents. Currently, there are 474 chemicals in ToxRefDB, primarily the data rich pesticide active ingredients, but the number will continue to expand.

To further transparency and openness, DOE established a policy to document and post online all CX determinations involving classes of actions listed in Appendix B to Subpart D of the DOE NEPA regulations (10 CFR Part 1021). The database contains CX determinations required to be posted under the policy, and also some for which documentation and posting are optional, i.e., determinations involving classes of actions listed in Appendix A or made before the policy's effective date of November 2, 2009. The database may be searched by state, CX applied, date range, DOE Program, Field, or Site Office, keyword, and whether the CX determination is for a project related to the American Recovery and Reinvestment Act (Recovery Act or ARRA) of 2009. Links to CX determination documents are provided. The database will be updated approximately monthly. See http://www.gc.doe.gov/NEPA/categorical_exclusion_determinations.htm for information on DOE CX procedures. For further information on DOE's NEPA compliance program, see http://www.gc.energy.gov/nepa or email: askNEPA@hq.doe.gov.

Find information using interactive applications to get statistics from multiple surveys.

This dataset contains 60-min locomotor response data for all control, chemical and particulate-extract-treated zebrafish. This dataset is associated with the following publication: Stevens, J., S. Padilla, D. DeMarini, D. Hunter, K. Martin, L. Thompson, I. Gilmour, M. Hazari, and A. Farraj. Zebrafish Locomotor Responses Reveal Irritant Effects of Fine Particulate Matter Extracts and a Role for TRPA1. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 161(2): 290-299, (2018).