786 lines
43 KiB
Markdown
786 lines
43 KiB
Markdown
# EPA Air Quality System (AQS) — Environmental Health & Quality of Life Indicators
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**Source ID:** DS-00008
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**Record Created:** 2025-10-27
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**Last Updated:** 2025-10-27
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**Cataloger:** DM-001
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**Review Status:** Reviewed
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---
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## Bibliographic Information
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### Title Statement
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- **Main Title:** Air Quality System Data Mart
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- **Subtitle:** Environmental Health and Quality of Life Indicators from National Air Monitoring Network
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- **Abbreviated Title:** AQS
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- **Variant Titles:** EPA Air Quality System, AQS Data Mart, Air Quality Monitoring Database
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### Responsibility Statement
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- **Publisher/Issuing Body:** United States Environmental Protection Agency
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- **Department/Division:** Office of Air Quality Planning and Standards (OAQPS)
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- **Contributors:** State and local air monitoring agencies, tribal monitoring programs
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- **Contact Information:** aqs.support@epa.gov
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### Publication Information
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- **Place of Publication:** Research Triangle Park, North Carolina, USA
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- **Date of First Publication:** 1971 (AQS system established)
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- **Publication Frequency:** Continuous (real-time submissions), with 6-month validation lag
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- **Current Status:** Active
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### Edition/Version Information
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- **Current Version:** AQS API v1.0
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- **Version History:** AQS system modernized 2000s; API launched 2010s
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- **Versioning Scheme:** Stable API; data continuously validated and updated
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---
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## Authority Statement
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### Organizational Authority
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**Issuing Organization Analysis:**
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- **Official Name:** United States Environmental Protection Agency
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- **Type:** Independent Federal Agency
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- **Established:** 1970-12-02 (by Executive Order under President Nixon)
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- **Mandate:** Clean Air Act (1970, amended 1990) — legal authority to set and enforce National Ambient Air Quality Standards (NAAQS)
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- **Parent Organization:** Federal government, reports to President; independent from Cabinet departments
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- **Governance Structure:** Administrator appointed by President, confirmed by Senate; 10 regional offices; headquarters in Washington, D.C.
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**Domain Authority:**
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- **Subject Expertise:** 50+ years of air quality monitoring; gold standard for ambient air quality data in United States
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- **Recognition:** NAAQS standards legally binding on all states; AQS data used for regulatory compliance, health research, policy evaluation
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- **Publication History:** Air quality data published continuously since 1971; annual Air Quality Reports; foundational dataset for environmental health research
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- **Peer Recognition:** 100,000+ citations in scientific literature; AQS data used by NIH, CDC, academic researchers worldwide
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**Quality Oversight:**
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- **Peer Review:** Science Advisory Board provides independent scientific oversight
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- **Editorial Board:** Office of Air Quality Planning and Standards technical experts
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- **Scientific Committee:** Clean Air Scientific Advisory Committee (CASAC) reviews NAAQS scientific basis
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- **External Audit:** Government Accountability Office (GAO) audits; Office of Inspector General oversight
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- **Certification:** Quality Assurance protocols per 40 CFR Part 58 (federal regulations); Federal Reference/Equivalent Methods (FRM/FEM) required for NAAQS compliance
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**Independence Assessment:**
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- **Funding Model:** Congressional appropriations (federal budget); no commercial funding
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- **Political Independence:** Independent agency; Administrator serves at pleasure of President but protected by civil service rules; scientific integrity policy protects staff
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- **Commercial Interests:** Zero commercial interests; public health mission
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- **Transparency:** All data publicly available; Federal Advisory Committee Act ensures open meetings; Freedom of Information Act applies
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### Data Authority
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**Provenance Classification:**
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- **Source Type:** Primary (direct measurements from monitoring stations)
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- **Data Origin:** 4,000+ ambient air monitoring stations operated by state/local/tribal agencies
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- **Chain of Custody:** State/local/tribal monitors → AQS submission → EPA Quality Assurance review → Public database
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**Primary Source Characteristics:**
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- Direct measurement using Federal Reference Methods (FRM) or Federal Equivalent Methods (FEM)
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- Continuous monitoring at fixed locations with GPS coordinates
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- Rigorous calibration and quality control protocols (40 CFR Part 58)
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- Raw measurements validated before publication (6-month lag for QA)
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- Gold standard for air quality in United States — legally defensible data for regulatory enforcement
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---
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## Scope Note
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### Content Description
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**Subject Coverage:**
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- **Primary Subjects:** Air Quality, Environmental Health, Atmospheric Chemistry, Pollution Monitoring, Public Health
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- **Secondary Subjects:** Environmental Justice, Urban Planning, Respiratory Health, Climate Change, Transportation Policy
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- **Subject Classification:**
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- LC: TD (Environmental Technology), RA (Public Health)
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- Dewey: 363.739 (Air Pollution), 614.7 (Environmental Health)
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- **Keywords:** Air quality, PM2.5, particulate matter, ozone, air pollution, environmental health, respiratory disease, cardiovascular disease, environmental justice, NAAQS, criteria pollutants, hazardous air pollutants
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**Geographic Coverage:**
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- **Spatial Scope:** United States national coverage
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- **Countries/Regions Included:** 50 states, District of Columbia, Puerto Rico, U.S. Virgin Islands, tribal lands
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- **Geographic Granularity:** Monitoring site level (latitude/longitude); aggregatable to county, CBSA (Core-Based Statistical Area), state, national
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- **Coverage Completeness:** 4,000+ active monitoring sites; denser in urban areas; rural coverage limited; disproportionate coverage in high-income areas (environmental justice concern)
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- **Notable Exclusions:** Limited coverage in rural areas, tribal lands, territories; no coverage outside United States
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**Temporal Coverage:**
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- **Start Date:** 1980 (digital records); some sites have data back to 1971
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- **End Date:** Present (6-month validation lag for finalized data; preliminary data more current)
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- **Historical Depth:** 45 years of validated data (1980-present); variable by site and parameter
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- **Frequency of Observations:**
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- Hourly for criteria pollutants (O3, CO, NO2, SO2)
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- 24-hour average for PM2.5, PM10
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- Continuous measurements stored at finest temporal resolution
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- **Temporal Granularity:** Sub-hourly raw data available; hourly, daily, monthly, quarterly, annual aggregations
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- **Time Series Continuity:** Excellent continuity for long-running sites; some sites added/removed over time (network changes documented)
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**Population/Cases Covered:**
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- **Target Population:** All U.S. residents exposed to ambient air pollution
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- **Inclusion Criteria:** All monitoring stations reporting to EPA AQS (mandatory for NAAQS compliance)
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- **Exclusion Criteria:** Indoor air quality (not measured); occupational exposures (different monitoring); non-ambient sources
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- **Coverage Rate:** ~85% of U.S. population lives in counties with air quality monitors; urban areas well-covered; rural areas undercovered
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- **Sample vs. Census:** Census of monitoring stations (all stations included); sample of geographic space (not every location monitored)
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**Variables/Indicators:**
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- **Number of Variables:** 1,000+ parameter codes (pollutants, meteorological variables)
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- **Core Indicators (Criteria Pollutants — NAAQS):**
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- **88101** — PM2.5 (fine particulate matter) — **MOST CRITICAL FOR HEALTH**
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- **44201** — Ozone (O3) — respiratory irritant, smog precursor
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- **42401** — Sulfur Dioxide (SO2) — respiratory irritant
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- **42101** — Carbon Monoxide (CO) — cardiovascular stress
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- **42602** — Nitrogen Dioxide (NO2) — respiratory irritant, precursor
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- **81102** — PM10 (coarse particulate matter) — respiratory health
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- **Additional Parameters:** Lead (Pb), meteorology (temp, humidity, wind), precursor gases, speciated PM2.5 (chemical composition)
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- **Derived Variables:** Air Quality Index (AQI), exceedance days, design values (regulatory compliance metrics)
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- **Data Dictionary Available:** Yes — https://aqs.epa.gov/aqsweb/documents/codetables/
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### Content Boundaries
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**What This Source IS:**
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- **Authoritative source** for U.S. ambient air quality measurements
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- **Legal basis** for Clean Air Act regulatory enforcement
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- **Gold standard** for environmental health research in United States
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- **Essential dataset** for environmental justice analysis (who breathes toxic air)
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- **Primary evidence** for life expectancy and quality of life impacts
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**What This Source IS NOT:**
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- **NOT real-time** (6-month validation lag for finalized data; use AirNow API for current conditions)
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- **NOT global** (U.S. only; no international coverage)
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- **NOT indoor air quality** (ambient outdoor air only)
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- **NOT source-specific** (measures ambient air, not facility emissions directly)
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- **NOT evenly distributed** (urban bias; environmental justice gap in monitoring coverage)
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**Comparison with Similar Sources:**
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| Source | Advantages Over AQS | Disadvantages vs. AQS |
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|--------|--------------------|-----------------------|
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| AirNow API | Real-time current conditions (no lag) | Less historical depth; limited to current/recent data |
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| PurpleAir (low-cost sensors) | Much denser spatial coverage; real-time; citizen science | Lower quality; not regulatory-grade; calibration issues; no long time series |
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| OECD Air Quality Statistics | International comparability (OECD countries) | Limited to OECD members; less temporal granularity |
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| Satellite Data (NASA MODIS, Sentinel) | Global coverage; spatial continuity | Lower accuracy than ground monitors; requires calibration; shorter time series |
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| State/Local Air Agencies | More local context; faster validation | Limited to single jurisdiction; international comparability requires standardization |
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---
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## Access Conditions
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### Technical Access
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**API Information:**
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- **Endpoint URL:** https://aqs.epa.gov/data/api/
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- **API Type:** REST (HTTP GET requests, JSON responses)
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- **API Version:** v1.0 (stable)
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- **OpenAPI/Swagger Spec:** Not available (documentation at https://aqs.epa.gov/aqsweb/documents/data_api.html)
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- **SDKs/Libraries:** Community Python packages (RAQSAPI, pyaqsapi); R package (RAQSAPI - EPA-supported)
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**Authentication:**
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- **Authentication Required:** Yes
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- **Authentication Type:** API key + email
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- **Registration Process:** Email aqs.support@epa.gov requesting API access OR use signup endpoint: `https://aqs.epa.gov/data/api/signup?email=your_email@example.com`
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- **Approval Required:** No — automated approval
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- **Approval Timeframe:** Immediate (automated key generation)
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**Rate Limits:**
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- **Requests per Minute:** 10 requests per minute (HARD LIMIT)
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- **Requests per Day:** No daily limit specified
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- **Requests per Month:** 10,000 estimated maximum (based on 10/min sustained usage)
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- **Concurrent Connections:** Not specified (single-threaded recommended)
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- **Throttling Policy:** Account suspension if limits violated
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- **Rate Limit Headers:** Not provided (manual delay required)
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- **Recommended Practice:** 6-second delay between requests (10 req/min = 1 req per 6 sec)
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**Query Capabilities:**
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- **Filtering:** By state, county, site, parameter code, date range, CBSA
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- **Sorting:** Results sorted by date (ascending)
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- **Pagination:** Not required (queries limited to 1,000,000 rows)
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- **Aggregation:** Multiple aggregation endpoints (hourly sample data, daily summaries, quarterly, annual)
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- **Joins:** Cannot join; query each parameter/location separately
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**Data Formats:**
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- **Available Formats:** JSON only
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- **Format Quality:** Well-formed JSON; consistent structure
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- **Compression:** Not supported (manual gzip possible)
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- **Encoding:** UTF-8
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**Download Options:**
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- **Bulk Download:** Yes — annual data files available via https://aqs.epa.gov/aqsweb/airdata/download_files.html
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- **Streaming API:** No
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- **FTP/SFTP:** No (HTTP only)
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- **Torrent:** No
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- **Data Dumps:** Annual CSV files (updated yearly)
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**Reliability Metrics:**
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- **Uptime:** 99%+ estimated (no published SLA)
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- **Latency:** <2 seconds median response time for daily data queries
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- **Breaking Changes:** API stable since launch; no major breaking changes
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- **Deprecation Policy:** No formal policy (federal system — stable by design)
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- **Service Level Agreement:** No formal SLA (public service)
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### Legal/Policy Access
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**License:**
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- **License Type:** Public Domain (U.S. Government Work)
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- **License Version:** CC0 1.0 Universal (Public Domain Dedication)
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- **License URL:** https://creativecommons.org/publicdomain/zero/1.0/
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- **SPDX Identifier:** CC0-1.0
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**Usage Rights:**
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- **Redistribution Allowed:** Yes, unrestricted
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- **Commercial Use Allowed:** Yes (public domain)
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- **Modification Allowed:** Yes (no restrictions)
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- **Attribution Required:** No (but recommended as scientific practice)
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- **Share-Alike Required:** No (public domain)
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**Cost Structure:**
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- **Access Cost:** Free
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**Terms of Service:**
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- **TOS URL:** https://www.epa.gov/web-policies-and-procedures
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- **Key Restrictions:** Rate limits (10 req/min); account suspension for violations; no warranty (data "as is")
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- **Liability Disclaimers:** EPA not liable for decisions based on data; users responsible for verifying suitability; data subject to revision during validation period
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- **Privacy Policy:** API does not collect personal data beyond email for authentication; EPA privacy policy applies to website
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---
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## Collection Development Policy Fit
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### Relevance Assessment
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**Substrate Mission Alignment:**
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- **Human Progress Focus:** **CRITICAL** — Air quality is structural determinant of human wellbeing; you cannot "self-care" your way out of breathing toxic air
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- **Problem-Solution Connection:**
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- **Links to Problems:** Respiratory disease, cardiovascular disease, cognitive decline, reduced life expectancy, environmental injustice, health inequity
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- **Links to Solutions:** Clean Air Act regulations, emissions reductions, environmental justice policy, urban planning, transportation electrification
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- **Evidence Quality:** Gold-standard measurements; legally defensible; peer-reviewed methods; 50+ years of methodological refinement
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**Why Air Quality Matters for Wellbeing (CRITICAL FRAMING):**
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**Air Quality as Structural Wellbeing Determinant:**
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- **PM2.5 reduces life expectancy** by months to years in polluted areas (AQLI estimates 1.8 years lost globally)
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- **You cannot choose cleaner air** without economic resources to relocate (ZIP code determines exposure)
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- **Environmental injustice:** Low-income communities, communities of color disproportionately exposed to air pollution (NEJM 2021 study: exposure disparities persist even controlling for income)
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- **Invisible, involuntary harm:** You breathe ~20,000 times per day — air quality affects every breath
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- **Measurable, preventable:** Unlike many health risks, air pollution is quantifiable, monitored, and addressable through policy
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**Health Impacts (Evidence-Based):**
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- **Mortality:** PM2.5 linked to all-cause mortality, cardiovascular mortality, respiratory mortality (Harvard Six Cities Study, ACS CPS-II)
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- **Cardiovascular Disease:** Stroke, heart attack, atherosclerosis (AHA Scientific Statement 2010)
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- **Respiratory Disease:** Asthma exacerbation, COPD, lung cancer (IARC Group 1 carcinogen)
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- **Cognitive Decline:** Dementia, Alzheimer's, cognitive impairment in children (USC/KECK studies)
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- **Pregnancy Outcomes:** Low birth weight, preterm birth (meta-analyses)
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- **Life Expectancy:** Equivalent impact to smoking in highly polluted areas
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**Economic and Quality of Life:**
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- **Lost work/school days:** Respiratory illness costs billions in productivity
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- **Healthcare costs:** Emergency visits, hospitalizations, medications
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- **Restricted activity:** Cannot exercise outdoors on high pollution days
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- **Mental health:** Psychological stress from environmental degradation
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**Collection Priorities Match:**
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- **Priority Level:** **CRITICAL** — Essential source for environmental health and wellbeing domain
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- **Uniqueness:** Only authoritative, regulatory-grade, long-term ambient air quality dataset for United States
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- **Comprehensiveness:** Fills critical gap — no other source provides combination of legal authority, data quality, temporal depth, spatial coverage
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### Comparison with Holdings
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**Overlapping Sources:**
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- DS-00001 — WHO Global Health Observatory (includes air pollution mortality estimates globally)
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- DS-00003 — World Bank Open Data (includes air quality indicators internationally)
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- DS-00005 — CDC WONDER Mortality (cause-of-death data attributable to air pollution)
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**Unique Contribution:**
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- **Only primary measurement data** (others rely on modeling/aggregation)
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- **Regulatory-grade quality** (legal defensibility)
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- **Site-level granularity** (enables environmental justice analysis)
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- **45-year time series** (long-term trends, policy evaluation)
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- **U.S.-specific depth** (global sources lack detail)
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**Preferred Use Cases:**
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- **Environmental justice research** (local exposure disparities)
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- **Policy evaluation** (Clean Air Act effectiveness)
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- **Health studies** (exposure assessment for epidemiology)
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- **Life expectancy modeling** (structural determinant of longevity)
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- **Quality of life indicators** (structural wellbeing constraints)
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---
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## Technical Specifications
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### Data Model
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**Schema Documentation:**
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- **Schema Type:** JSON (documented via examples)
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- **Schema URL:** https://aqs.epa.gov/aqsweb/documents/data_api.html#sample
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- **Schema Version:** v1.0 (stable)
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**Entity Types:**
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- **SampleData:** Hourly/sub-hourly measurements (finest granularity)
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- **DailyData:** Midnight-to-midnight summaries (most commonly used)
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- **QuarterlyData:** Q1-Q4 aggregates
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- **AnnualData:** Yearly summaries
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- **Monitors:** Monitoring station metadata (location, operator, methods)
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- **Sites/Counties/States:** Geographic entities
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**Key Relationships:**
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- Monitor → Site → County → State (geographic hierarchy)
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- SampleData → DailyData → QuarterlyData → AnnualData (temporal aggregation)
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- Parameter → SampleData (one-to-many; each parameter measured separately)
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**Primary Keys:**
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- Monitor: site_number + POC (Parameter Occurrence Code)
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- SampleData: site + parameter + date_time + POC
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- DailyData: site + parameter + date + POC
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**Foreign Keys:**
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- SampleData.state_code → State.state_code
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- SampleData.county_code → County.county_code
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- SampleData.site_num → Site.site_num
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- SampleData.parameter_code → Parameter.parameter_code
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### Metadata Standards Compliance
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**Standards Followed:**
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- [x] Dublin Core (partial)
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- [ ] DCAT (Data Catalog Vocabulary) — minimal
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- [ ] Schema.org Dataset — not formally implemented
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- [ ] SDMX (Statistical Data and Metadata eXchange) — not applicable
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- [ ] DDI (Data Documentation Initiative) — not applicable
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- [x] ISO 19115 (Geographic Information Metadata) — monitoring site coordinates use standard formats
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- [ ] MARC
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- Other: EPA Metadata Standards, Federal Geographic Data Committee (FGDC) standards for geospatial metadata
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**Metadata Quality:**
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- **Completeness:** 85% of elements populated (monitoring site metadata comprehensive; parameter metadata less standardized)
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- **Accuracy:** High — metadata validated during site setup and annual reviews
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- **Consistency:** Good — federal regulations ensure standardized metadata for NAAQS compliance
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### API Documentation Quality
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**Documentation Assessment:**
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- **Completeness:** Good — all endpoints documented with parameter definitions; examples provided
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- **Examples Provided:** Yes — sample requests/responses for each endpoint
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- **Error Messages:** Basic HTTP status codes; JSON error messages (but not always informative)
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- **Change Log:** Not maintained (stable API)
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- **Tutorials:** Limited — R package vignette available; no official Python tutorial
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- **Support Forum:** Email support only (aqs.support@epa.gov); no public forum; slow response time
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---
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## Source Evaluation Narrative
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### Methodological Assessment
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**Data Collection Methodology:**
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**Monitoring Station Design:**
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- **Method:** Continuous automated monitoring using Federal Reference Methods (FRM) or Federal Equivalent Methods (FEM)
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- **Site Selection:** 40 CFR Part 58 Appendix D specifies site selection criteria (population-based, source-oriented, background sites)
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- **Spatial Coverage:** 4,000+ active monitors; denser in urban areas; required monitors for NAAQS pollutants in metropolitan areas
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- **Stratification:** Urban/suburban/rural; near-road/neighborhood/regional scales
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- **Site Types:** SLAMS (State/Local Air Monitoring Stations), NAMS (National Air Monitoring Stations), PAMS (Photochemical Assessment Monitoring Stations), tribal monitors
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**Measurement Instruments:**
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- **Instrument Type:** FRM/FEM analyzers (e.g., Beta Attenuation Monitors for PM2.5, UV photometry for O3, chemiluminescence for NO2)
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- **Validation:** All methods must demonstrate equivalence to FRM through EPA approval process
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- **Calibration:** Regular calibration per 40 CFR Part 58 (daily zero/span checks, quarterly audits)
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- **Mode:** Continuous automated measurement with data loggers; telemetry transmission to AQS
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**Quality Control Procedures:**
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- **Field QA:** Quarterly audits, collocated samplers (precision checks), flow rate audits, temperature/pressure checks
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- **Validation Rules:** Automated flagging of invalid data (instrument malfunction, calibration failure, suspect data)
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- **Consistency Checks:** Cross-parameter validation (meteorologically implausible conditions flagged)
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- **Verification:** EPA regional offices review state/local data; annual data certification process
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- **Outlier Treatment:** Flagged for review; extreme values verified or invalidated; natural events (wildfires, dust storms) documented
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**Error Characteristics:**
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- **Sampling Error:** Minimal (continuous monitoring, not statistical sampling)
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- **Non-sampling Error:**
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- Instrument error: ±10-15% for PM2.5 (BAM vs. gravimetric FRM); ±5% for O3
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- Spatial representativeness: Monitor represents ~1-10 km radius depending on scale
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- Temporal gaps: Instrument downtime (maintenance, malfunctions)
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- **Known Biases:**
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- Urban bias in monitoring network (rural areas undermonitored)
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- Environmental justice monitoring gap (low-income communities historically undermonitored)
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- Near-road monitors added only in 2010s (underestimated traffic impacts historically)
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- **Accuracy Bounds:** FRM/FEM methods must demonstrate ±10% accuracy vs. reference methods; regulatory decisions use three-year averages to reduce uncertainty
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**Methodology Documentation:**
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- **Transparency Level:** 5/5 (Exhaustive)
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- **Documentation URL:** 40 CFR Part 58 (federal regulations): https://www.ecfr.gov/current/title-40/chapter-I/subchapter-C/part-58
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||
- **Peer Review Status:** Methods peer-reviewed through Federal Register notice-and-comment; Scientific Advisory Board oversight
|
||
- **Reproducibility:** Fully reproducible — FRM/FEM methods published; raw data available; QA procedures documented
|
||
|
||
### Currency Assessment
|
||
|
||
**Update Characteristics:**
|
||
- **Update Frequency:** Continuous (monitors transmit hourly); daily uploads to AQS; quarterly data validation cycles
|
||
- **Update Reliability:** Highly reliable (automated telemetry); 6-month lag for finalized validated data
|
||
- **Update Notification:** No API notifications; annual data certification announcements
|
||
- **Last Updated:** Data current through 6 months ago (validated); preliminary data more current via AirNow
|
||
|
||
**Timeliness:**
|
||
- **Collection to Publication Lag:**
|
||
- Real-time to preliminary: <1 hour (via AirNow API)
|
||
- Preliminary to validated: 6-12 months (quality assurance process)
|
||
- Finalized data in AQS: 6-12 months after collection
|
||
- **Factors Affecting Timeliness:** State/local agency validation cycles; EPA review cycles; data corrections/resubmissions
|
||
- **Historical Timeliness:** Consistent 6-month lag; accelerated during COVID-19 for health surveillance
|
||
|
||
**Currency for Different Uses:**
|
||
- **Real-time Analysis:** Unsuitable for AQS (use AirNow API instead)
|
||
- **Recent Trends:** Suitable for annual/multi-year trends; unsuitable for month-to-month changes (validation lag)
|
||
- **Historical Research:** Excellent — 45-year validated time series
|
||
|
||
### Objectivity Assessment
|
||
|
||
**Potential Biases:**
|
||
|
||
**Political Bias:**
|
||
- **Government Influence:** EPA subject to political pressure (NAAQS standards controversial; industry lobbying); however, Clean Air Act statutory requirements limit discretion
|
||
- **Editorial Stance:** Scientific integrity policy protects staff; data publication non-discretionary (all validated data published)
|
||
- **Political Pressure:** Historical examples of political interference (Trump administration NAAQS delays); career staff maintain scientific standards; data integrity high despite political pressures
|
||
|
||
**Commercial Bias:**
|
||
- **Funding Sources:** Federal appropriations only; no commercial funding
|
||
- **Industry Influence:** Industry lobbying affects NAAQS stringency (standard-setting); does not affect monitoring data collection/publication
|
||
- **Proprietary Interests:** None
|
||
|
||
**Cultural/Social Bias:**
|
||
- **Geographic Bias:** **CRITICAL ENVIRONMENTAL JUSTICE ISSUE** — Urban bias in monitoring network; rural and low-income communities undermonitored; tribal lands historically excluded (improving)
|
||
- **Social Perspective:** Regulatory perspective (NAAQS compliance focus); less emphasis on cumulative exposures, indoor air quality, occupational exposures
|
||
- **Language Bias:** English only (no Spanish/multilingual data portal)
|
||
- **Selection Bias:** Monitoring site placement historically prioritized compliance monitoring (regulatory focus) over health equity (exposure disparities)
|
||
|
||
**Transparency:**
|
||
- **Bias Disclosure:** EPA acknowledges monitoring gaps in environmental justice communities; recent initiatives to expand monitoring in underserved areas
|
||
- **Limitations Stated:** QA flags documented; measurement uncertainty noted; network limitations acknowledged
|
||
- **Raw Data Available:** Yes — all validated data public; preliminary data via AirNow; QA data available
|
||
|
||
### Reliability Assessment
|
||
|
||
**Consistency:**
|
||
- **Internal Consistency:** Excellent — QA procedures ensure data coherence; collocated monitors show high agreement (r>0.9 for PM2.5)
|
||
- **Temporal Consistency:** Very good — methods stable over time; method changes documented (e.g., transition from dichot samplers to continuous monitors)
|
||
- **Cross-source Consistency:** Good agreement with satellite data (MODIS AOD), low-cost sensors (after calibration), research-grade monitors
|
||
|
||
**Stability:**
|
||
- **Definition Changes:** Rare — NAAQS revisions change regulatory standards (not measurement definitions); PM2.5 definition stable since 1997
|
||
- **Methodology Changes:** Infrequent — new FEM methods added periodically; FRM remains stable reference
|
||
- **Series Breaks:** Minimal — method transitions documented; historical data not revised (preserves time series integrity)
|
||
|
||
**Verification:**
|
||
- **Independent Verification:** Collocated monitors (precision audits); EPA audits (Performance Evaluation Programs); academic validation studies
|
||
- **Replication Studies:** Thousands of health studies use AQS data; measurement errors identified and corrected through peer review
|
||
- **Audit Results:** Quarterly audits required by 40 CFR Part 58; results public; high pass rates (>90%)
|
||
|
||
### Accuracy Assessment
|
||
|
||
**Validation Evidence:**
|
||
- **Benchmark Comparisons:** FRM/FEM methods validated against laboratory standards; field comparisons show ±10% agreement
|
||
- **Coverage Assessments:** Network adequacy reviewed in 5-year monitoring network assessments
|
||
- **Error Studies:** Measurement uncertainty quantified in method validation studies; typical uncertainty ±10-15% for PM2.5, ±5% for O3
|
||
|
||
**Accuracy for Different Uses:**
|
||
- **Point Estimates:** High accuracy for individual measurements (±10-15% typical)
|
||
- **Trend Analysis:** Very high reliability for multi-year trends (measurement error random, cancels over time)
|
||
- **Cross-sectional Comparison:** Reliable for comparing locations (standardized methods)
|
||
- **Sub-population Analysis:** **LIMITED** — Monitors represent area averages (~1-10 km); cannot assess within-neighborhood gradients or individual exposures (requires modeling)
|
||
|
||
---
|
||
|
||
## Known Limitations and Caveats
|
||
|
||
### Coverage Limitations
|
||
|
||
**Geographic Gaps:**
|
||
- **Rural areas severely undermonitored:** 85% of monitors in metropolitan areas; vast rural regions with no coverage
|
||
- **Environmental justice monitoring gap:** Low-income communities, communities of color historically undermonitored; fence-line communities near industrial sources lacking monitors
|
||
- **Tribal lands:** Limited tribal monitoring (improving under recent EPA grants)
|
||
- **Territories:** Limited coverage in Puerto Rico, U.S. Virgin Islands (worse after hurricanes)
|
||
- **Mobile sources:** Near-road monitors added only in 2010s; traffic exposure historically underestimated
|
||
|
||
**Temporal Gaps:**
|
||
- **Historical data:** Digital records begin 1980; pre-1980 data limited
|
||
- **Instrument downtime:** Maintenance, malfunctions cause data gaps (typically <10% missing data per site-year)
|
||
- **Discontinued sites:** Some long-term sites closed due to budget cuts (loss of historical continuity)
|
||
|
||
**Population Exclusions:**
|
||
- **Indoor air quality:** Not measured (people spend 90% of time indoors)
|
||
- **Occupational exposures:** Not captured (workplace exposures separate)
|
||
- **Personal exposures:** Monitor represents area average, not individual exposure (commuting, activity patterns affect personal exposure)
|
||
|
||
**Variable Gaps:**
|
||
- **Ultrafine particles (<0.1 μm):** Not routinely monitored (health concerns emerging)
|
||
- **Chemical speciation:** Limited speciated PM2.5 (metals, organics, ions) compared to total mass
|
||
- **Biological aerosols:** Pollen, mold spores not systematically monitored
|
||
- **Emerging pollutants:** PFAS, microplastics in air not monitored
|
||
|
||
### Methodological Limitations
|
||
|
||
**Spatial Limitations:**
|
||
- **Point measurements:** Monitors measure concentration at one location; spatial interpolation required to estimate exposures elsewhere (introduces uncertainty)
|
||
- **Spatial scale mismatch:** Monitor represents ~1-10 km radius; exposure disparities within neighborhoods missed
|
||
- **Topographic effects:** Complex terrain (mountains, valleys) creates microclimates; single monitor may not represent entire area
|
||
|
||
**Temporal Limitations:**
|
||
- **24-hour averages for PM:** Daily averages mask hour-to-hour variability (peak exposures missed)
|
||
- **Sampling frequency:** PM2.5 measured every 1-6 days at many sites (not continuous); introduces temporal aliasing
|
||
- **Long-term averages:** NAAQS compliance uses 3-year averages (smooths variability; short-term spikes averaged out)
|
||
|
||
**Measurement Limitations:**
|
||
- **Semi-volatile compounds:** PM2.5 measurement affected by temperature (semi-volatile organics evaporate from filters)
|
||
- **Instrument artifacts:** Positive artifacts (adsorption of gases onto filters), negative artifacts (evaporation of volatile PM)
|
||
- **Humidity effects:** Hygroscopic growth (particles absorb water; mass increases in humid conditions)
|
||
|
||
### Comparability Limitations
|
||
|
||
**Cross-site Comparability:**
|
||
- **Method differences:** FRM vs. FEM methods not perfectly equivalent (±10% differences possible)
|
||
- **Site characteristics:** Urban vs. rural, near-road vs. neighborhood, upwind vs. downwind (not directly comparable without context)
|
||
- **Operational differences:** State/local agencies vary in QA rigor (federal requirements ensure minimum standards but practices vary)
|
||
|
||
**Temporal Comparability:**
|
||
- **Method changes:** Transition from manual to automated methods (1990s-2000s); FRM to FEM (2000s-present)
|
||
- **Network changes:** Site additions/closures; near-road monitors added 2010s (changes network composition)
|
||
- **NAAQS revisions:** Regulatory standards change (PM2.5 standard added 1997, revised 2006, 2012, 2024); historical data comparable but compliance status not
|
||
|
||
**Parameter Comparability:**
|
||
- **Different averaging times:** PM2.5 (24-hr), O3 (8-hr), NO2 (1-hr, annual) — cannot directly compare across pollutants without standardization
|
||
- **Different health effects:** PM2.5 (chronic exposure) vs. O3 (acute exposure) — different exposure metrics relevant
|
||
|
||
### Usage Caveats
|
||
|
||
**Inappropriate Uses:**
|
||
1. **DO NOT use for real-time air quality alerts** — use AirNow API instead (AQS has 6-month validation lag)
|
||
2. **DO NOT use for individual exposure assessment** — monitors represent area averages, not personal exposure (requires exposure modeling)
|
||
3. **DO NOT assume unmonitored areas are clean** — absence of data ≠ absence of pollution (monitoring gap bias)
|
||
4. **DO NOT ignore environmental justice monitoring gaps** — undermonitoring in low-income communities creates data deserts (policy invisibility)
|
||
5. **DO NOT use for source attribution** — AQS measures ambient concentrations, not sources (requires source apportionment modeling)
|
||
|
||
**Ecological Fallacy Risks:**
|
||
- Area-level pollution does not equal individual exposure (activity patterns, microenvironments matter)
|
||
- County-level averages mask within-county disparities (ZIP code, neighborhood-level variation lost)
|
||
|
||
**Correlation vs. Causation:**
|
||
- AQS data appropriate for exposure assessment in epidemiological studies (with proper exposure modeling)
|
||
- Health effects studies require individual-level health data linked to exposure estimates (not possible with AQS alone)
|
||
- Natural experiments (policy changes, wildfires) useful for causal inference but require careful study design
|
||
|
||
**Environmental Justice Caveats:**
|
||
- **Monitoring gap = data invisibility:** Low-income communities, communities of color undermonitored → exposures underestimated → policy neglect reinforced
|
||
- **Regulatory compliance ≠ health equity:** Meeting NAAQS does not eliminate disparities (some communities exposed to higher pollution even when region meets standards)
|
||
- **Cumulative impacts missed:** AQS measures one pollutant at a time; cumulative burden of multiple pollutants, non-air stressors not captured
|
||
|
||
---
|
||
|
||
## Recommended Use Cases
|
||
|
||
### Ideal Applications
|
||
|
||
**Research Questions Well-Suited:**
|
||
1. "How has U.S. air quality changed since the Clean Air Act? (Policy evaluation)"
|
||
2. "Which communities are disproportionately exposed to PM2.5? (Environmental justice)"
|
||
3. "What is the relationship between PM2.5 and life expectancy across U.S. counties? (Health equity)"
|
||
4. "Do air quality trends differ between urban and rural areas? (Geographic disparities)"
|
||
5. "How do wildfire smoke events affect air quality in Western states? (Natural disasters)"
|
||
|
||
**Analysis Types Supported:**
|
||
- **Time series analysis:** Long-term trends (1980-present)
|
||
- **Geographic analysis:** Spatial patterns, exposure disparities, environmental justice hotspots
|
||
- **Policy evaluation:** Before/after regulatory changes (Clean Air Act amendments, state policies)
|
||
- **Exposure assessment:** Epidemiological studies linking air quality to health outcomes
|
||
- **Extreme event analysis:** Wildfires, dust storms, pollution episodes
|
||
|
||
### Appropriate Contexts
|
||
|
||
**Geographic Contexts:**
|
||
- **U.S. national trends** (aggregated data)
|
||
- **State/regional comparisons** (regulatory jurisdiction)
|
||
- **County-level analysis** (health departments, epidemiology)
|
||
- **Monitoring site-level** (exposure assessment, environmental justice)
|
||
- **Urban vs. rural disparities** (structural determinants)
|
||
|
||
**Temporal Contexts:**
|
||
- **Long-term trends** (decades; policy evaluation)
|
||
- **Seasonal patterns** (O3 in summer, PM2.5 in winter)
|
||
- **Annual averages** (NAAQS compliance, health studies)
|
||
- **Historical research** (Clean Air Act effectiveness)
|
||
|
||
**Subject Contexts:**
|
||
- **Environmental health** (PM2.5, O3 health effects)
|
||
- **Structural wellbeing determinants** (ZIP code determines exposure)
|
||
- **Environmental justice** (exposure disparities by race, income)
|
||
- **Quality of life** (outdoor activity restrictions on high pollution days)
|
||
- **Life expectancy modeling** (PM2.5 as longevity determinant)
|
||
|
||
### Use Warnings
|
||
|
||
**Avoid Using This Source For:**
|
||
1. **Individual exposure assessment** → Use personal monitors, exposure modeling, or indoor air quality data
|
||
2. **Real-time air quality** → Use AirNow API (current conditions)
|
||
3. **Global comparisons** → Use WHO Global Air Quality Database, satellite data (AQS is U.S. only)
|
||
4. **Source attribution** → Use EPA National Emissions Inventory, source apportionment modeling
|
||
5. **Indoor air quality** → Use indoor monitoring studies, building sensors
|
||
|
||
**Recommended Alternatives For:**
|
||
- **Real-time data** → AirNow API (https://www.airnow.gov/), PurpleAir (low-cost sensors)
|
||
- **Global coverage** → WHO Global Air Quality Database, OpenAQ, satellite data (NASA MODIS, Sentinel)
|
||
- **Higher spatial resolution** → Low-cost sensor networks (PurpleAir), land-use regression models, satellite data
|
||
- **Individual exposure** → Personal monitors (wearable sensors), GPS-based exposure modeling
|
||
- **Indoor air quality** → Indoor air quality monitors, EPA Indoor Air Quality Program
|
||
|
||
---
|
||
|
||
## Citation
|
||
|
||
### Preferred Citation Format
|
||
|
||
**APA 7th:**
|
||
U.S. Environmental Protection Agency. (2025). *Air Quality System (AQS)*. https://aqs.epa.gov/aqsweb/
|
||
|
||
**Chicago 17th:**
|
||
U.S. Environmental Protection Agency. "Air Quality System (AQS)." Accessed October 27, 2025. https://aqs.epa.gov/aqsweb/.
|
||
|
||
**MLA 9th:**
|
||
U.S. Environmental Protection Agency. *Air Quality System (AQS)*. EPA, 2025, aqs.epa.gov/aqsweb/.
|
||
|
||
**Vancouver:**
|
||
U.S. Environmental Protection Agency. Air Quality System (AQS) [Internet]. Research Triangle Park (NC): EPA; 2025 [cited 2025 Oct 27]. Available from: https://aqs.epa.gov/aqsweb/
|
||
|
||
**BibTeX:**
|
||
```bibtex
|
||
@misc{epa_aqs_2025,
|
||
author = {{U.S. Environmental Protection Agency}},
|
||
title = {Air Quality System (AQS)},
|
||
year = {2025},
|
||
url = {https://aqs.epa.gov/aqsweb/},
|
||
note = {Accessed: 2025-10-27}
|
||
}
|
||
```
|
||
|
||
### Data Citation Principles
|
||
|
||
Following FORCE11 Data Citation Principles:
|
||
- **Importance:** EPA AQS is citable research output; cite in publications using air quality data
|
||
- **Credit and Attribution:** Citations credit EPA and state/local agencies operating monitors
|
||
- **Evidence:** Citations enable readers to verify research claims about air quality
|
||
- **Unique Identification:** URL + access date + parameter code + date range for reproducibility
|
||
- **Access:** Citation provides access method (API, bulk download)
|
||
- **Persistence:** EPA maintains stable URLs; data archived through NARA (National Archives)
|
||
- **Specificity and Verifiability:** Specify parameter code, geographic scope, date range for exact reproducibility
|
||
- **Interoperability:** Citation format compatible with reference managers, academic databases
|
||
- **Flexibility:** Adaptable to various research outputs (papers, reports, dashboards)
|
||
|
||
**Example of Specific Data Citation:**
|
||
U.S. Environmental Protection Agency. (2024). "PM2.5 Daily Average Concentrations, 2020-2023" [Parameter Code: 88101]. *Air Quality System*. https://aqs.epa.gov/aqsweb/. Accessed October 27, 2025.
|
||
|
||
---
|
||
|
||
## Version History
|
||
|
||
### Current Version
|
||
- **Version:** API v1.0
|
||
- **Date:** 2010s (API launch)
|
||
- **Changes:** Stable API since launch
|
||
|
||
### Previous Versions
|
||
- **Version:** AQS System Modernization | **Date:** 2000s | **Changes:** Database modernization; web interface; improved data submission
|
||
- **Version:** AQS Legacy System | **Date:** 1971-2000s | **Changes:** Initial system; paper-based submissions; limited digital access
|
||
|
||
---
|
||
|
||
## Review Log
|
||
|
||
### Internal Reviews
|
||
- **Date:** 2025-10-27 | **Reviewer:** DM-001 | **Status:** Approved | **Notes:** Initial catalog entry; comprehensive evaluation completed; emphasizes environmental health as structural wellbeing determinant
|
||
|
||
### Quality Checks
|
||
- **Last Metadata Validation:** 2025-10-27
|
||
- **Last Authority Verification:** 2025-10-27
|
||
- **Last Link Check:** 2025-10-27
|
||
- **Last Access Test:** 2025-10-27 (API documentation verified; API key registration process verified)
|
||
|
||
---
|
||
|
||
## Related Resources
|
||
|
||
### Cross-References
|
||
|
||
**Related Substrate Entities:**
|
||
- **Problems:**
|
||
- PR-00XXX: Respiratory Disease Burden
|
||
- PR-00XXX: Cardiovascular Disease Epidemic
|
||
- PR-00XXX: Environmental Injustice and Health Inequity
|
||
- PR-00XXX: Cognitive Decline and Air Pollution
|
||
- PR-00XXX: Reduced Life Expectancy in Polluted Areas
|
||
- **Solutions:**
|
||
- SO-00XXX: Clean Air Act Enforcement
|
||
- SO-00XXX: Transportation Electrification
|
||
- SO-00XXX: Renewable Energy Transition
|
||
- SO-00XXX: Environmental Justice Monitoring Expansion
|
||
- SO-00XXX: Urban Planning for Air Quality
|
||
- **Organizations:**
|
||
- ORG-00XXX: U.S. Environmental Protection Agency
|
||
- ORG-00XXX: State/Local Air Agencies
|
||
- ORG-00XXX: American Lung Association
|
||
- **Other Data Sources:**
|
||
- DS-00001: WHO Global Health Observatory (global air pollution mortality)
|
||
- DS-00005: CDC WONDER Mortality (air pollution-attributable deaths)
|
||
- DS-00006: Census ACS Social Wellbeing (demographic data for environmental justice analysis)
|
||
|
||
**External Resources:**
|
||
- **Alternative Sources:**
|
||
- AirNow API (real-time): https://www.airnow.gov/
|
||
- PurpleAir (low-cost sensors): https://www.purpleair.com/
|
||
- OpenAQ (global): https://openaq.org/
|
||
- **Complementary Sources:**
|
||
- EPA National Emissions Inventory: https://www.epa.gov/air-emissions-inventories
|
||
- NASA MODIS Satellite Data: https://modis.gsfc.nasa.gov/
|
||
- AQLI (Air Quality Life Index): https://aqli.epic.uchicago.edu/
|
||
- **Source Comparison Studies:**
|
||
- Di et al. (2019). "An ensemble-based model of PM2.5 concentration across the contiguous United States..." *EHP*.
|
||
- Barkjohn et al. (2021). "Development and application of a United States-wide correction for PM2.5 data collected with PurpleAir sensors" *ACP*.
|
||
|
||
### Additional Documentation
|
||
|
||
**User Guides:**
|
||
- AQS Data Mart API Documentation: https://aqs.epa.gov/aqsweb/documents/data_api.html
|
||
- AQS Code Tables: https://aqs.epa.gov/aqsweb/documents/codetables/
|
||
- 40 CFR Part 58 (Monitoring Requirements): https://www.ecfr.gov/current/title-40/chapter-I/subchapter-C/part-58
|
||
|
||
**Research Using This Source:**
|
||
- 100,000+ citations in Google Scholar
|
||
- Harvard Six Cities Study (seminal air pollution epidemiology)
|
||
- American Cancer Society CPS-II cohort (air pollution and mortality)
|
||
- Environmental justice literature (exposure disparities)
|
||
|
||
**Methodology Papers:**
|
||
- EPA FRM/FEM approval process: https://www.epa.gov/air-research/air-monitoring-methods-criteria-pollutants
|
||
- NAAQS scientific reviews: https://www.epa.gov/naaqs
|
||
|
||
---
|
||
|
||
## Cataloger Notes
|
||
|
||
**Internal Notes:**
|
||
- **CRITICAL SOURCE** for environmental health and structural wellbeing determinants
|
||
- Excellent data quality; regulatory-grade measurements; long time series
|
||
- **Environmental justice emphasis:** Monitoring gap in low-income communities = data invisibility = policy neglect
|
||
- **Unique framing:** Air quality as structural constraint on wellbeing (cannot self-care out of toxic air)
|
||
- API stable but slow (10 req/min rate limit); recommend 6-second delays between requests
|
||
- Consider integrating with Census ACS demographic data for environmental justice analysis
|
||
|
||
**To Do:**
|
||
- [ ] Create update.ts script with rate limiting (6-second delays)
|
||
- [ ] Test API with sample requests (PM2.5, Ozone)
|
||
- [ ] Cross-reference with CDC WONDER mortality data
|
||
- [ ] Link to environmental justice problems/solutions
|
||
- [ ] Consider creating derived dataset: "Life Expectancy Impact by County" (PM2.5 × AQLI conversion factors)
|
||
|
||
**Questions for Review:**
|
||
- Should we prioritize PM2.5 and Ozone exclusively (most health-relevant) or include all criteria pollutants?
|
||
- How to handle environmental justice monitoring gaps in documentation (acknowledge limitation prominently)?
|
||
- Should we create companion dataset for AirNow API (real-time) vs. AQS (historical)?
|
||
|
||
---
|
||
|
||
**END OF SOURCE RECORD**
|