EPA ECHO Facility Search

Search the official EPA ECHO service for regulated US facilities by state, ZIP code, name, NAICS code, environmental program, or violation status. Export normalized compliance, inspection, and penalty fields without an API key. Set max_items before each run to keep output and cost predictable.

What data can I extract?

160 flat columns per facility, straight from the official EPA ECHO service. Nested values are flattened into scalar columns, so a CSV export needs no post-processing.

• Identity and location - registry ID, name, address, county, FIPS, latitude and longitude, plus the coordinate accuracy, collection method and reference point so you can tell a surveyed point from a geocoded address.
• Jurisdiction - EPA region, congressional district, census block group, HUC8 and HUC12 watershed codes and names, Indian country flag and nearby tribes.
• Program participation - one Y/N column per program (Clean Air Act, NPDES water, Safe Drinking Water, RCRA hazardous waste, Toxics Release Inventory, greenhouse gas reporting, Superfund) and the matching program IDs, which are the join keys into EPA's other public datasets.
• Compliance - overall status plus per-program status, significant non-compliance and high priority violator flags, and the quarter-by-quarter compliance history strings for each program.
• Inspections and enforcement - counts and latest dates, split by program and by whether EPA or the state carried the action out.
• Penalties - totals, counts, latest amounts and dates, broken out per program and for federal enforcement cases.
• Emissions - Toxics Release Inventory on-site releases and off-site transfers in pounds, and greenhouse gas CO2 equivalent in metric tons.
• Environmental justice - percent minority, percent people of colour, percent low income and population density around the site, plus nonattainment-area status and the pollutants involved.
• Permits and demographics (optional, include_details) - permit expiration dates, permit statutes, universes and areas, and the ACS demographic block around the site.

Every result is written to the default dataset and can be downloaded as JSON, CSV, Excel, or XML.

All 160 columns

Identity — air_ids, federal_agency_name, federal_case_ids, ghg_ids, name, npdes_ids, rcra_ids, registry_id, rmp_ids, sdwa_ids, superfund_ids, tri_ids, watershed_huc12_name, watershed_huc8_name

Status — active, caa_permit_types, caa_status, compliance_status, cwa_permit_types, cwa_status, rcra_permit_types, rcra_status, sdwa_status, sdwa_system_types

Dates — caa_last_formal_action_date, caa_last_penalty_date, cwa_last_formal_action_date, cwa_last_penalty_date, federal_last_case_date, last_formal_action_date, last_formal_action_date_epa, last_formal_action_date_state, last_informal_action_date, last_informal_action_date_epa, last_informal_action_date_state, last_inspection_date, last_inspection_date_epa, last_inspection_date_state, last_penalty_date, permit_expiration_dates, rcra_last_formal_action_date, rcra_last_penalty_date

Location — city, congressional_district, county, epa_region, fips_code, in_indian_country, latitude, longitude, state, zip

Money — acs_percent_below_low_income, acs_persons_below_low_income, caa_last_penalty_amount, caa_penalties, cwa_last_penalty_amount, cwa_penalties, federal_case_penalties, last_penalty_amount, penalty_count, percent_below_low_income, rcra_last_penalty_amount, rcra_penalties, total_penalties

Contact — url

Counts and measures — caa_evaluation_count, caa_formal_action_count, caa_informal_count, cwa_formal_action_count, cwa_informal_count, cwa_inspection_count, federal_case_count, formal_action_count, informal_action_count, inspection_count, permit_count, rcra_formal_action_count, rcra_informal_count, rcra_inspection_count, sdwa_formal_action_count, sdwa_informal_count

Other detail — acs_households, acs_households_public_assistance, acs_housing_units, acs_minors, acs_percent_below_poverty, acs_persons_below_poverty, acs_population, acs_radius_miles, acs_seniors, caa_compliance_history_3yr, caa_days_last_evaluation, caa_high_priority_violator, caa_quarters_in_noncompliance, census_block_group, compliance_history_3yr, coordinate_accuracy_meters, coordinate_collection_method, coordinate_reference_point, current_violation, currently_significant_violation, cwa_compliance_history_13qtrs, cwa_compliance_tracking, cwa_days_last_inspection, cwa_effluent_exceedances_13qtrs, cwa_qncr_codes, cwa_quarters_in_noncompliance, cwa_significant_noncompliance, days_since_inspection, discharges_to_impaired_water, epcra_inspections_5yr, federal_facility, fifra_inspections_5yr, formal_action_last_5yr, ghg_co2_releases_tons, had_violation_3yr, in_air_program, in_drinking_water_program, in_greenhouse_gas_reporting, in_hazardous_waste_program, in_nonattainment_area, in_superfund_program, in_toxics_release_inventory, in_water_program, informal_action_last_5yr, inspected_last_5yr, latest_permit_expiration, major_facility, naics_codes, nearby_tribes, nonattainment_categories, nonattainment_pollutants, percent_minority, percent_people_of_color, permit_areas, permit_statutes, permit_universes, population_density, programs_with_snc, quarters_in_noncompliance, rcra_compliance_history_3yr, rcra_days_last_evaluation, rcra_quarters_in_noncompliance, rcra_significant_noncompliance, sdwa_compliance_history_3yr, sdwa_inspections_5yr, sdwa_quarters_in_noncompliance, sdwa_significant_noncompliance, sic_codes, significant_noncompliance, street, tri_off_site_transfers_lbs, tri_on_site_releases_lbs, tri_releases_transfers_lbs, tri_reporter, tri_reporter_in_past, tsca_inspections_5yr, watershed_huc12, watershed_huc8

Input example

{
  "state": "RI",
  "program": "A",
  "violations_only": true,
  "max_items": 10
}

The default input is deliberately bounded and produces a small, useful Store test. max_items is a hard output ceiling.

Output example

An abridged real record - the full row carries 160 columns:

{
  "registry_id": "110007019190",
  "name": "CNTRL LANDFILL RESOURCE RECOVERY PLANT",
  "street": "65 SHUN PIKE",
  "city": "JOHNSTON",
  "state": "RI",
  "zip": "02919",
  "county": "PROVIDENCE",
  "latitude": 41.808331,
  "longitude": -71.534719,
  "epa_region": "01",
  "congressional_district": "02",
  "watershed_huc8_name": "Narragansett",
  "naics_codes": "562212 999999 221119 22111 562111",
  "major_facility": "Y",
  "in_air_program": "Y",
  "in_water_program": "Y",
  "in_superfund_program": "Y",
  "npdes_ids": "RI0023442, RIR100390, RIR100645, RIR101096",
  "superfund_ids": "RID980520183",
  "caa_permit_types": "Major Emissions, Minor Emissions",
  "compliance_status": "Violation Identified",
  "caa_status": "Violation w/in 1 Year",
  "cwa_status": "Violation Identified",
  "current_violation": 1,
  "quarters_in_noncompliance": 10,
  "compliance_history_3yr": "SSSS_VVSS_VV",
  "inspection_count": 7,
  "last_inspection_date": "09/02/2026",
  "formal_action_count": 1,
  "last_penalty_date": "02/24/2020",
  "ghg_co2_releases_tons": 5354.0,
  "discharges_to_impaired_water": "Y",
  "in_nonattainment_area": "Y",
  "nonattainment_pollutants": "Ozone",
  "percent_people_of_color": 24.15,
  "percent_below_low_income": 19.21,
  "latest_permit_expiration": "03/31/2027",
  "url": "https://echo.epa.gov/detailed-facility-report?fid=110007019190"
}

compliance_history_3yr gives one character per quarter, oldest first: an underscore is a compliant quarter and a letter marks a violation, so a whole three-year trend reads at a glance.

Nullable fields remain explicit when the upstream source does not supply a value. latest_permit_expiration and the acs_* columns need include_details; they are returned as null otherwise, so the column set never changes between runs.

Common use cases

• Environmental due diligence
• Supplier and site compliance research
• Facility prospecting by industry
• Public-interest and enforcement analysis

Use with AI agents and MCP

Apify's MCP server can discover and call this Actor from an AI workflow. Example intent:

Find 10 Rhode Island Clean Air Act facilities currently flagged for violations.

Use the JSON from Input example as the tool arguments. The strict input schema rejects unsupported parameters, and the documented dataset schema tells the agent how to interpret each returned field.

Pricing and cost control

Output is billed per result at $0.003 per result (about $3.00 per 1,000 results), plus a $0.0005 Actor-start charge billed once per gigabyte of memory at run start. Use max_items to cap both output volume and charges. The price shown on the Apify Store listing is authoritative.

max_items limits both output volume and result-based charges. Start with 10 records, inspect them, and then scale deliberately.

Reliability

The Actor validates input, bounds pagination, retries transient upstream failures, writes structured records, and fails explicitly when the source cannot produce usable output. A production default-input canary is monitored by the fleet.

Limitations and responsible use

• ECHO status reflects EPA source systems and reporting schedules.
• A flagged record is a research lead, not a legal conclusion.
• Some fields are unavailable for some programs or facilities.
• This Actor does not bypass EPA limits or access nonpublic records.

Use the data lawfully, respect source terms, and independently validate records before making consequential decisions.

FAQ

Does it need my own API key?

No, the default workflow does not require a customer-supplied API key.

Can I export the results?

Yes. Download the default dataset as JSON, CSV, Excel, or XML, or retrieve it through the Apify API.

How do I control cost?

Set max_items to the most records you want returned. Begin with the bounded default input.

Can an AI agent call it?

Yes. The Actor has strict input and semantic output schemas and can be called through Apify's MCP tooling.

What happens when a source field is missing?

The relevant field is returned as null or an empty normalized value rather than being merged into another field.