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Air quality index

The Air Quality Index (AQI) is a standardized numerical scale designed to report daily ambient air quality by aggregating concentrations of major pollutants—such as particulate matter (PM2.5 and PM10), ground-level ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide—into a single value ranging from 0 (good) to 500 (hazardous), with color-coded categories indicating potential health risks from short-term exposure. Developed by the United States Environmental Protection Agency (EPA) in the 1970s following the Clean Air Act amendments, the AQI calculates sub-indices for each pollutant based on measured levels relative to national ambient air quality standards, then reports the highest sub-index value to prioritize the dominant health threat. This approach enables public advisories on protective actions, such as limiting outdoor activities during elevated pollution episodes, and has influenced similar systems worldwide, though calculations vary by country in pollutant weighting, breakpoint thresholds, and averaging periods—for instance, China's AQI emphasizes PM2.5 more heavily due to industrial sources, while the European Air Quality Index integrates real-time urban traffic data. While the US AQI aligns with empirical health effect thresholds derived from epidemiological studies, international variations reflect differing regulatory priorities and monitoring capabilities, sometimes leading to inconsistencies in cross-border comparisons; for example, the World Health Organization's stricter PM2.5 guidelines (annual mean of 5 μg/m³) exceed many national AQI breakpoints, highlighting debates over index sensitivity to long-term risks versus acute exposures. Early precursors, like Marvin Green's 1966 index focusing on and , laid groundwork, but the EPA's formalized method emphasized causal links between pollutants and respiratory/cardiovascular outcomes, prioritizing data from federal reference monitors for accuracy.

Definition and Purpose

Core Components and Scale

The Air Quality Index (AQI) in the United States, as defined by the Environmental Protection Agency (EPA), relies on measurements of five principal atmospheric pollutants to assess ambient air quality: (O3), (PM2.5 and PM10), (CO), (SO2), and (NO2). These criteria pollutants are selected based on their established associations with adverse health effects, as determined through epidemiological studies and toxicological research mandated under the Clean Air Act. Each pollutant's concentration is converted into a sub-index value using pollutant-specific breakpoints that map measured levels to health risk categories. Sub-indices are calculated for each via a piecewise linear interpolation formula. For a given concentration C_p falling between two breakpoints C_{low} and C_{high} (with corresponding index values I_{low} and I_{high}), the sub-index I_p is derived as: I_p = \frac{I_{high} - I_{low}}{C_{high} - C_{low}} \times (C_p - C_{low}) + I_{low} This formula ensures a continuous , with breakpoints calibrated to reflect increasing risks; for instance, PM2.5 breakpoints range from 0 μg/m³ (AQI 0) to over 500 μg/m³ (AQI 500+). The overall AQI is then taken as the maximum of these sub-indices, prioritizing the dominant contributing to poor air quality. The AQI scale spans from 0 to 500, segmented into six color-coded categories to signal health implications:
AQI RangeCategoryColorHealth Interpretation
0–50GoodAir quality satisfactory; minimal risk.
51–100ModerateYellowAcceptable; moderate concern for sensitive groups.
101–150Unhealthy for Sensitive GroupsOrangeUnhealthy for vulnerable populations.
151–200UnhealthyRedHealth effects possible for general public.
201–300Very UnhealthyPurpleSevere risk; emergency conditions for sensitive groups.
301–500HazardousMaroonLife-threatening; entire population affected.
These thresholds derive from concentration-response functions linking pollutant levels to morbidity and mortality data, such as ozone's role in respiratory irritation above 0.060 ppm (8-hour average) or PM2.5's cardiovascular impacts exceeding 12 μg/m³ (24-hour average). While the EPA scale serves as a foundational model, regional adaptations may incorporate additional pollutants like or adjust breakpoints based on local .

Health and Environmental Signaling

The Air Quality Index (AQI) functions primarily as a signaling mechanism, converting measured concentrations of key pollutants—such as (PM2.5 and PM10), , , , and —into a unified ranging from 0 to 500, where higher values indicate greater health risks. This employs color-coded categories to communicate immediate protective actions: green for "Good" (0-50), suitable for all activities with negligible effects; yellow for "Moderate" (51-100), acceptable but with potential concerns for sensitive individuals; orange for "Unhealthy for Sensitive Groups" (101-150), advising reduced exertion for children, elderly, and those with heart or disease; red for "Unhealthy" (151-200), where the general population may experience or exacerbated conditions; purple for "Very Unhealthy" (201-300), triggering health alerts for vulnerable groups to avoid outdoors; and maroon for "Hazardous" (301+), signaling emergency conditions with widespread severe effects like premature mortality risks. These categories derive from epidemiological and toxicological data linking pollutant exposures to adverse outcomes, including respiratory infections, cardiovascular events, and reduced lung function, with thresholds set by agencies like the U.S. Environmental Protection Agency (EPA) based on studies showing causal associations at specific concentrations. For instance, an AQI above 100 correlates with increased hospital admissions for in sensitive populations, while levels over 300 have been observed to elevate all-cause mortality rates during episodes. However, critiques note that PM2.5-related AQI guidance may not fully capture risks under contemporary profiles, potentially underestimating long-term cumulative effects. Environmentally, the AQI indirectly signals broader ecological stressors by highlighting pollutant loads that contribute to phenomena like vegetation damage from phytotoxicity, soil acidification from deposition, and aquatic ecosystem disruption via atmospheric inputs, though it emphasizes human health over dedicated environmental indices. High AQI readings thus prompt regulatory responses aimed at mitigating transboundary effects, such as forest decline or , with from events like the 2007 Greek wildfires demonstrating how sustained elevated indices correlate with regional .
AQI RangeColor CategoryPrimary Health Signaling
0–50Good (Green)Air quality poses little or no risk; active children and adults acceptable.
51–100Moderate (Yellow)Acceptable; sensitive individuals may experience minor effects.
101–150Unhealthy for Sensitive Groups ()Sensitive groups should limit outdoor exertion.
151–200Unhealthy ()General experiences effects; sensitive groups more serious.
201–300Very Unhealthy (Purple)Health alert; vulnerable avoid outdoors, others reduce activity.
301+Hazardous (Maroon)Emergency; all avoid outdoors, sensitive seek medical attention.

Historical Development

Origins in the 1960s-1970s

The first formalized air quality index emerged in 1966 with Marvin H. Green's Index, which aggregated measurements of and into a single numerical value to assess urban levels, primarily for public communication . This approach addressed the limitations of isolated readings by emphasizing overall risk, though it relied on limited parameters and lacked standardized thresholds. Legislative momentum built in the mid-1960s amid high-profile smog episodes, such as the 1966 New York City event that contributed to approximately 168 excess deaths from respiratory issues, prompting federal intervention. The Clean Air Act of 1963 authorized research into effects, followed by the 1967 Air Quality Act, which mandated states to designate air quality control regions and develop criteria for major pollutants like hydrocarbons, , and photochemical oxidants. These laws established a framework for systematic monitoring but did not yet prescribe a unified index, relying instead on disparate local metrics. The 1970 Clean Air Act Amendments marked a pivotal escalation, creating the Environmental Protection Agency (EPA) on December 2, 1970, and requiring (NAAQS) for six criteria pollutants by 1971. This spurred index development to translate complex data into actionable public alerts, culminating in the EPA's (PSI) adopted in 1976, which scaled pollution levels from 0 to 500 based on the highest sub-index among monitored pollutants, with categories signaling health risks. The PSI responded to congressional mandates for accessible reporting, drawing from earlier models like Green's while incorporating NAAQS breakpoints for uniformity across states. These origins reflected causal links between industrial emissions, vehicular exhaust, and acute health events, prioritizing empirical pollutant concentrations over qualitative assessments, though early indices faced criticism for oversimplifying synergistic effects among pollutants. By the late , the facilitated daily forecasting in major cities, laying groundwork for broader adoption despite variations in local implementation.

Standardization in the 1980s-1990s

The U.S. Environmental Protection Agency (EPA) formalized the () in 1979 as a uniform tool for daily public reporting of levels, scaling concentrations of criteria pollutants against () to categorize health risks from "good" to "hazardous." During the , this index achieved nationwide standardization as the EPA mandated its use by states for forecasting and disseminating air quality data, enabling consistent comparisons across regions and facilitating public awareness amid ongoing NAAQS revisions, such as those for in 1979 and lead in 1987. The 's sub-index approach, aggregating individual pollutant metrics into an overall score, emphasized the highest contributor to promote actionable alerts without overcomplicating interpretation. In the 1990s, standardization efforts intensified with the Clean Air Act Amendments of 1990, which expanded monitoring requirements and public notification obligations, prompting evaluations of the PSI's adequacy for emerging pollutants like fine particulate matter (PM2.5). These amendments indirectly supported index refinement by prioritizing real-time data integration and health-based thresholds. By 1999, the EPA promulgated a final rule revising the PSI: breakpoints were adjusted to align more closely with health effects evidence, PM2.5 was incorporated as a reportable pollutant with sub-indices calibrated to NAAQS levels (e.g., 55 μg/m³ for the 100 index value), and the index was renamed the Air Quality Index (AQI) to better reflect its comprehensive scope, effective October 30, 1999. This update addressed limitations in the original PSI, such as inconsistent sensitivity to short-term peaks, while maintaining backward compatibility for trend analysis. Internationally, parallel standardization emerged through the World Health Organization's (WHO) first Air Quality Guidelines for in , which established evidence-based threshold values for pollutants like (SO2, 50 μg/m³ annual mean) and (NO2, 200 μg/m³ 1-hour), influencing index-like frameworks in by linking concentrations to outcomes without a unified numerical scale. These guidelines, updated regionally in the , promoted causal linkages between exposure and respiratory/cardiovascular risks, aiding nascent European efforts toward harmonized reporting under early directives (e.g., 1980 lead standard, 1992 sulfur directive precursors). Unlike the U.S. PSI/AQI's public-facing index, WHO focused on guideline values for policy, but contributed to global convergence on empirical pollutant metrics.

Post-2000 Evolutions and Global Spread

Following the 1999 revision of the United States Environmental Protection Agency's (EPA) Air Quality Index (AQI) to incorporate fine particulate matter (PM2.5), subsequent updates aligned the index with evolving (NAAQS). In 2012, the EPA revised the annual PM2.5 NAAQS to 12 µg/m³, prompting adjustments to AQI breakpoints to reflect heightened health risks from lower concentrations. Further refinements occurred in 2024, updating AQI reporting for PM to include 24-hour averages and enhancing public communication of daily values based on the latest scientific evidence. These changes emphasized real-time monitoring and forecasting, facilitated by expanded networks and digital platforms like AirNow, which by the integrated satellite data for broader coverage. The AQI concept spread globally post-2000 amid rising awareness of transboundary pollution and health impacts, particularly in rapidly industrializing regions. China's Ministry of Environmental Protection introduced a national AQI in 2012, adapting the U.S. model to include PM2.5 alongside criteria pollutants like , NO2, , and O3, with breakpoints calibrated to local conditions and WHO guidelines. This marked a shift from earlier opacity-based indices, driven by following U.S. Embassy PM2.5 reporting since 2008, and enabled nationwide monitoring across 113 key cities by 2013. India operationalized its National Air Quality Index (NAQI) in October 2014, with Prime Minister Narendra Modi launching it for 10 major cities in April 2015; the index aggregates eight pollutants, prioritizing PM2.5 and PM10, and uses color-coded categories similar to the U.S. system to alert populations in high-pollution areas like Delhi. By the mid-2010s, over 100 countries had adopted or adapted AQI frameworks, supported by international efforts like the World Health Organization's 2005 and 2021 air quality guideline updates, which informed breakpoint thresholds for health protection. Global databases, such as AQICN's historical AQI records starting around 2012, standardized comparisons across borders, revealing disparities like worsening PM2.5 inequality from 2000 to 2020. Technological advancements post-2000, including low-cost sensors and mobile apps, accelerated AQI dissemination, enabling contributions and policy responses in urban centers worldwide. For instance, Europe's Common Air Quality Index (CAQI) evolved in parallel, but the U.S.-inspired models dominated in , where emissions from and vehicles drove adoption to mitigate events like the 2007 Greek wildfires and ongoing smog. Despite variations in pollutant weighting and scales, these indices consistently prioritized empirical concentration data over subjective perceptions, fostering causal links between exposure and outcomes like respiratory diseases.

Technical Foundations

Key Pollutants and Metrics

The key pollutants assessed in most air quality indices (AQIs) are those with documented causal links to respiratory, cardiovascular, and other health impairments, as established through longitudinal cohort studies and controlled exposure research. These primarily consist of fine particulate matter (PM2.5), inhalable particulate matter (PM10), (O3), (NO2), (SO2), and (CO). Lead (Pb) is occasionally included in criteria pollutant monitoring but rarely features in real-time AQI due to its longer-term deposition patterns from legacy sources like industrial emissions and gasoline additives phased out by regulations such as the U.S. Clean Air Act amendments of 1990. Metrics for these pollutants emphasize ambient concentration levels, normalized to standard units and averaging periods that align with peak human exposure risks and dose-response thresholds derived from toxicological data. 2.5 and 10 are measured in micrograms per cubic meter (μg/m³), reflecting mass accumulation from , , and secondary formation; 2.5 typically uses a 24-hour average to capture daily variability from traffic and heating sources. employs by volume (ppb) over an 8-hour period to account for photochemical reactions peaking midday, while NO2 and SO2 use 1-hour ppb averages due to their acute irritant effects from vehicle exhaust and , respectively. is quantified in parts per million (ppm) via 1-hour or 8-hour averages, targeting incomplete products that bind and reduce oxygen delivery. The following table summarizes the standard metrics for principal AQI pollutants, based on U.S. Environmental Protection Agency (EPA) conventions that influence global indices:
PollutantSymbolUnitTypical Averaging Period
Fine particulate matterPM2.5μg/m³24 hours
Inhalable particulate matterPM10μg/m³24 hours
O3ppb8 hours
NO2ppb1 hour
SO2ppb1 hour
COppm8 hours or 1 hour
These metrics prioritize empirical thresholds where pollutant levels correlate with increased hospital admissions and mortality rates, as quantified in meta-analyses of urban monitoring data from networks like the EPA's Air Quality System, which logged over 10,000 stations by 2023. Variations exist internationally; for instance, the European Union's index emphasizes NO2 hourly peaks from diesel traffic, while India's AQI incorporates metrics adjusted for monsoon-influenced dispersion. Source credibility in pollutant selection favors regulatory agencies over advocacy groups, given the former's reliance on peer-reviewed exposure-response models rather than modeled projections prone to overestimation in activist literature.

Calculation Formulas and Sub-Indices

The Air Quality Index (AQI) is derived as the maximum value among sub-indices computed for principal air pollutants, ensuring the index reflects the most concerning pollutant at a given time. Each sub-index quantifies the health risk posed by a specific pollutant's concentration, scaled to a uniform 0–500 range where higher values indicate greater potential for adverse effects. This approach prioritizes empirical concentration data over aggregated metrics, with sub-indices calculated independently before selecting the highest to represent overall air quality. Sub-indices are computed for the six criteria pollutants defined under U.S. : (O₃), fine (PM₂.₅), inhalable coarse (PM₁₀), (CO), (SO₂), and (NO₂). Averaging periods vary by pollutant to align with observed health impacts: 8-hour for O₃ and CO, 24-hour for PM₂.₅ and PM₁₀, and 1-hour for SO₂ and NO₂. For each pollutant p, the sub-index Ip is determined via piecewise linear interpolation between predefined breakpoints, which map concentration thresholds to AQI levels based on toxicological and epidemiological evidence of health thresholds. The core formula for a sub-index, when the measured concentration Cp lies between adjacent breakpoints Clow and Chigh (with corresponding index values Ilow and Ihigh), is: Ip = Ilow + [( IhighIlow ) / ( ChighClow )] × ( CpClow ) This interpolation assumes linearity within segments, derived from air quality standards linking concentrations to health outcomes such as respiratory irritation or mortality risk increases. For concentrations below the lowest breakpoint, Ip = 0; above the highest (typically yielding AQI 500), extrapolation may apply but is rare in practice. Breakpoints differ by pollutant—for instance, PM₂.₅ 24-hour breakpoints start at 0–12.0 μg/m³ for AQI 0–50 and extend to 250.4–500 μg/m³ for 300–500, updated in 2024 to reflect revised fine particle standards. In real-time reporting, sub-indices incorporate NowCast algorithms to estimate current concentrations from recent hourly data, weighting recent observations more heavily to capture short-term fluctuations without relying solely on full averaging periods. This method, formalized by the U.S. Environmental Protection Agency, uses a weighted average of the most recent hours, with weights decreasing exponentially backward in time, ensuring sub-indices respond to acute events like wildfires. While the EPA framework emphasizes causal links between pollutants and health via controlled studies, adaptations in other regions adjust breakpoints for local , though the sub-index maximization principle remains consistent.

Breakpoints and Categorization

Breakpoints in the Air Quality Index (AQI) represent the concentration thresholds for criteria air pollutants that demarcate the transitions between AQI numerical ranges, enabling the derivation of pollutant-specific sub-indices via . These thresholds are calibrated to (NAAQS) and epidemiological evidence linking pollutant levels to adverse health outcomes, such as respiratory irritation or cardiovascular risks. The U.S. Environmental Protection Agency (EPA) defines breakpoints separately for each pollutant— (O₃), fine particulate matter (PM₂.₅), inhalable particulate matter (PM₁₀), (CO), (SO₂), and (NO₂)—accounting for averaging times like 1-hour, 8-hour, or 24-hour periods. Categorization segments the AQI scale from 0 to 500 into six discrete levels, each tied to escalating concerns, standardized color codes for visual alerts, and behavioral guidance. This prioritizes communication of relative risks, with lower categories indicating minimal population-level impacts and higher ones signaling widespread effects, particularly for vulnerable groups like children, the elderly, and those with preexisting conditions. The categories remain consistent across pollutants, but the dominant (highest) sub-index determines the overall AQI category.
AQI RangeCategoryColorHealth Effects Description
0–50GoodGreenAir pollution poses little or no risk; satisfactory for all activities.
51–100ModerateYellowAcceptable, but unusually sensitive individuals may experience minor effects from certain pollutants.
101–150Unhealthy for Sensitive GroupsSensitive populations (e.g., asthmatics) may suffer effects; general public unlikely impacted.
151–200UnhealthyGeneral public may experience symptoms; sensitive groups face aggravated effects.
201–300Very UnhealthyEntire population at heightened risk; sensitive groups severely affected.
301+HazardousEmergency conditions; widespread serious effects expected across all groups.
Sub-index calculation employs a piecewise linear formula: for a concentration C_p between adjacent breakpoints C_{low} and C_{high} (mapping to AQI values I_{low} and I_{high}), the sub-index is I_p = I_{low} + \frac{I_{high} - I_{low}}{C_{high} - C_{low}} \times (C_p - C_{low}), rounded to the nearest integer. Breakpoints are periodically revised; for example, 2024 PM₂.₅ updates lowered the upper "Good" breakpoint for 24-hour averages from 35.4 μg/m³ (AQI 100) to align with tightened NAAQS, reflecting evidence of risks at lower exposures, while upper-tier thresholds for "Unhealthy" (151–200) shifted from 55.4–150.4 μg/m³ to 35.5–55.4 μg/m³ in the sensitive range and higher for severe categories. Similar adjustments apply to other pollutants, ensuring breakpoints reflect current health data without altering the core categorical framework.

Variations by Region

North America

In North America, air quality indices are implemented separately by national agencies, with the (EPA) maintaining the Air Quality Index (AQI) and (ECCC) overseeing the Air Quality Health Index (AQHI). These systems monitor common pollutants such as fine particulate matter (PM2.5), (O3), and (NO2), but diverge in scale, pollutants considered, and emphasis: the U.S. AQI prioritizes a broader set of criteria pollutants aligned with (NAAQS), while the Canadian AQHI focuses explicitly on health risks using a narrower set of metrics. Both indices provide daily forecasts and real-time data to inform responses, particularly during events like wildfires, which have driven elevated PM2.5 levels across the continent; for instance, in , Canadian PM2.5 peaks were linked to widespread wildfires. Harmonization efforts are limited, though some Canadian regions report dual metrics for cross-border comparability, and discrepancies in scaling can lead to differing public perceptions of risk during transboundary pollution episodes.

United States

The U.S. EPA's AQI is a dimensionless index ranging from 0 to 500+, where values of 0–50 indicate good air quality with minimal health risks, 51–100 moderate conditions suitable for most activities, and higher tiers escalating to unhealthy (101–150 for sensitive groups, 151–200 general population), very unhealthy (201–300), and hazardous (301+). It aggregates sub-indices for six criteria pollutants—PM2.5, PM10, O3, (CO), (SO2), and NO2—using segmented linear formulas tied to NAAQS breakpoints; for example, PM2.5 concentrations of 35.5–55.4 μg/m³ correspond to an AQI of 101–150. The overall AQI reflects the highest sub-index value, reported hourly via networks like AirNow, which disseminates color-coded forecasts (green to maroon) to guide actions such as limiting outdoor exertion. Implementation is decentralized, with states operating monitoring stations under EPA oversight; annual summaries track days exceeding 100 AQI, as in the 2024 report noting maximum values and category counts. During wildfire seasons, temporary adjustments incorporate smoke-specific PM thresholds, though critics note the index's reliance on short-term averages may understate exposure risks from non-criteria pollutants.

Canada

Canada's AQHI, managed by ECCC, scales from 1 (low risk) to 10+ (very high risk), calculated as the sum of sub-indices for , , and , each derived from depurated hourly concentrations relative to health effect thresholds; for instance, an AQHI of 7–10 signals high risk prompting reduced outdoor activity for sensitive groups. Unlike the U.S. AQI, it excludes , , and , prioritizing acute impacts over comprehensive coverage, and incorporates forecasts up to 24–48 hours via provincial networks. Rolled out nationally starting in 2007–2010 across provinces, the AQHI replaced or supplemented the U.S.-style AQI in many areas to better convey relative risks, with low-risk days (1–3) comprising most monitoring periods despite spikes, such as the 2018 peaks. Public messaging escalates with risk levels—e.g., avoiding strenuous activity above 10—and data are accessible via weather.gc.ca, though cross-border events like U.S. can yield lower AQHI readings than equivalent U.S. AQI values due to scaling differences. Provincial variations exist, such as Ontario's integration of real-time alerts, but national standards ensure consistency in -focused reporting.

United States

The Air Quality Index (AQI), managed by the Environmental Protection Agency (EPA), provides a standardized numerical scale from 0 to 500 to communicate daily outdoor levels and associated health risks to the public. Initially established as the (PSI) in 1976 under requirements of the Clean Air Act to enable episode reporting and public alerts, it was updated and renamed the AQI in 1999 to include fine particulate matter (PM2.5) as a core pollutant, expand the scale to better reflect extreme events, and enhance health risk communication through color coding. The index draws from ambient monitoring data across a national network of over 5,000 stations, prioritizing the highest sub-index value among monitored pollutants to determine the reported AQI. The AQI incorporates six criteria pollutants: ground-level ozone (O3, 8-hour average), PM2.5 (24-hour average), PM10 (24-hour average), (CO, 8-hour average), (SO2, 1-hour average), and (NO2, 1-hour average). Sub-indices for each pollutant are calculated by mapping measured concentrations to predefined breakpoints—concentration thresholds linked to levels—via :
I_p = \frac{I_{high} - I_{low}}{C_{high} - C_{low}} \times (C_p - C_{low}) + I_{low}
where I_p is the sub-index, C_p the pollutant concentration, and low/high subscripts denote the bracketing breakpoints and corresponding AQI values (e.g., 0–50, 51–100). Breakpoints are derived from (NAAQS) and epidemiological evidence, with the overall AQI reflecting the most concerning pollutant. Categories and colors guide public response:
AQI RangeCategoryColor
0–50GoodGreen
51–100ModerateYellow
101–150Unhealthy for Sensitive GroupsOrange
151–200UnhealthyRed
201–300Very UnhealthyPurple
301–500HazardousMaroon
In May 2024, EPA updated PM2.5 breakpoints in the AQI to align with revised NAAQS, lowering the "Good" to "Moderate" threshold from 12.1 to 9.0 μg/m³ annually, reflecting evidence of health risks at lower exposures without altering the core . The system supports via AirNow, integrating nowcasting algorithms for predictions, and mandates alerts for values exceeding 100 to inform vulnerable populations like children, the elderly, and those with respiratory conditions. State and local agencies report data to EPA's Air Quality System (AQS), ensuring uniformity while allowing for supplemental indices like those for wildfires.

Canada

In Canada, the Air Quality Health Index (AQHI) serves as the primary metric for communicating the health risks associated with short-term exposure to ambient air pollution, differing from the United States' pollutant-specific Air Quality Index by providing a single, health-focused value. The AQHI ranges from 1 (lowest risk) to 10 or higher (very high risk), with categories defined as low risk (1–3), moderate risk (4–6), high risk (7–10), and very high risk (10+), where higher values indicate greater relative health impacts, particularly for vulnerable populations such as children, the elderly, and those with respiratory conditions. It is calculated hourly using three-hour rolling averages of three key pollutants: ground-level ozone (O₃), fine particulate matter (PM₂.₅), and nitrogen dioxide (NO₂), selected based on their established associations with acute health effects like respiratory irritation and cardiovascular strain. The AQHI's development stemmed from a 2001 collaboration between and to create an index grounded in epidemiological data linking to short-term mortality risks, rather than arbitrary concentration thresholds. The formula derives from estimates, summing the excess risks from each pollutant (expressed as log-linear associations without assumed thresholds) and scaling the result to the 1–10+ range to reflect population-level health burdens, such as an estimated increase in hospital admissions or premature deaths during high-pollution episodes. Forecasts extend this model using predicted concentrations of PM₂.₅ and O₃, incorporating meteorological factors like wind and temperature, though NO₂ forecasts rely on historical patterns. Nationally coordinated by , the AQHI is reported in real-time and forecasted for over 100 monitoring stations across provinces, with data accessible via weather.gc.ca and provincial portals; for instance, provides automated readings via a toll-free line updated every hour. Provincial adaptations exist, such as 's version, which aligns with the national formula but integrates local monitoring networks managed by Alberta Environment and Protected Areas, emphasizing the same three pollutants while occasionally adjusting for regional sources like emissions. similarly computes the AQHI provincially, factoring in smoke events that can elevate PM₂.₅ levels and push indices into high-risk categories during summer seasons. This unified yet adaptable framework prioritizes empirical health correlations over economic or industrial considerations in threshold setting.

Europe

Air quality indices in Europe emphasize comparability across urban and regional scales, guided by the (EEA). The Common Air Quality Index (CAQI), implemented since 2006, targets real-time urban monitoring to enable cross-city comparisons. In 2017, the EEA introduced the European Air Quality Index (EAQI), expanding coverage with data from over 3,500 stations across the continent for pollutants including PM₂.₅, PM₁₀, NO₂, O₃, and SO₂. The EAQI computes sub-indices for each pollutant relative to EU limit values, assigning an overall index as the maximum sub-index value on a scale from 1 (good) to 5 (very poor), or occasionally 6 for extreme conditions. EU air quality directives establish concentration limits—such as 25 μg/m³ annual mean for PM₂.₅ (pre-2024 revision)—that underpin index breakpoints, with 2024 amendments accelerating alignment to stricter WHO guidelines by 2030.

Common Air Quality Index (CAQI)

The CAQI aggregates hourly measurements of NO₂, PM₁₀, O₃ (primary for urban sites), and optionally PM₂.₅, , SO₂, applying a NowCast method to forecast immediate concentrations from recent data. It uses a from 0 to over 100, divided into bands: very low (≤25), low (26-50), moderate (51-75), high (76-100), and very high (>100), where higher values indicate greater health risks and reduced suitability for sensitive activities. Originally focused on traffic and background urban stations, the index was updated in 2013 to include PM₂.₅ sub-indices, enhancing sensitivity to fine . Breakpoints derive from EU health-based thresholds, with the overall CAQI taken as the highest sub-index to reflect the dominant pollutant. This design prioritizes simplicity for public communication while supporting policy evaluation in cities.

National Adaptations

European countries adapt the common framework to local monitoring networks and health messaging, though many adhere closely to CAQI or EAQI structures. The Kingdom's Quality Index (DAQI), managed by the Department for Environment, Food & Rural Affairs (DEFRA), rates overall air quality from 1 (low) to 10 (very high) based on sub-indices for PM₂.₅, PM₁₀, NO₂, SO₂, and O₃, with band-specific advice like avoiding strenuous exercise above band 7. DAQI calculations weight pollutants by projected health impacts, differing from the max-sub-index approach in CAQI by incorporating forecasts up to 24 hours. In alignment with standards, national indices inform compliance reporting, but variations in pollutant emphasis—such as greater focus on PM₂.₅ in —reflect regional emission sources like traffic and heating. and , for example, integrate CAQI into urban apps while customizing alerts to national exceedance data.

Common Air Quality Index (CAQI)

The Common Air Quality Index (CAQI) serves as a standardized metric for assessing and comparing air quality across European cities in real time. Developed within the framework of the European CITEAIR projects, it was first implemented in 2006 to address inconsistencies in national indices and facilitate cross-border evaluations of pollution levels. An update in 2013 incorporated PM₂.₅ measurements to reflect finer , enhancing its relevance to impacts from and urban emissions. The index emphasizes dynamic hourly reporting via platforms like airqualitynow.eu, prioritizing pollutants prevalent in European urban environments such as from vehicles and from photochemical reactions. CAQI calculations distinguish between urban background stations, which average concentrations of NO₂ (1-hour), O₃ (1-hour), and PM₁₀ (1-hour), and traffic stations, which apply a formula weighting NO₂ more heavily: CAQI = max(urban background index, (NO₂ index × 1.2) + 25). When available, PM₂.₅ (1-hour), CO (1-hour), and SO₂ (1-hour) contribute sub-indices, with the overall value determined by linear interpolation between predefined concentration breakpoints for each pollutant and selection of the highest sub-index. Daily CAQI aggregates 24 hourly values but caps at the maximum hourly index to highlight peak exposures. Breakpoints are calibrated to EU limit values, such as NO₂ thresholds at 40–200 μg/m³ corresponding to index rises from 25 to 100, ensuring sensitivity to exceedances without overemphasizing rare high events. The scale ranges from 0 to 100 (extendable beyond for extreme events), categorized into five levels: very low (0–25, green, minimal health risk), low (26–50, , acceptable), medium (51–75, , sensitive groups advised caution), high (76–100, , general population reduce exposure), and very high (>100, , all avoid outdoors). This color-coded system aligns with public communication standards, promoting uniform advisories across adopting cities like , , and . Adoption varies, with some nations adapting it nationally while others retain bespoke indices; its design avoids over-reliance on less-measured pollutants like SO₂, reflecting empirical urban data where NO₂ and dominate health burdens.

National Adaptations

While the Common Air Quality Index (CAQI) promotes standardization across , individual member states have implemented national adaptations to align with domestic monitoring networks, pollutant priorities, and public communication strategies. These variations often incorporate local health thresholds or emphasize specific pollutants prevalent in regional contexts, such as higher weighting for in urbanized areas. For instance, the United Kingdom's system diverges by using a 1-10 banding for daily forecasts, prioritizing over the CAQI's continuous 0-100 scale. In the , the Daily Air Quality Index (DAQI), managed by the Department for Environment, Food & Rural Affairs (DEFRA), assesses five key pollutants—PM2.5, PM10, (O3), (NO2), and (SO2)—with sub-indices aggregated to report the highest value. Bands range from 1-3 (low pollution, minimal health effects) to 10 (very high, serious impacts on sensitive groups), providing tailored health advice like reducing outdoor activity at levels 7 and above. This index, operational since 2000 and updated in 2013 to include PM2.5, supports localized forecasting via the and regional agencies. France employs the ATMO index, coordinated by Atmo France, which evaluates PM10, PM2.5, O3, NO2, and on a 1-10 scale (1: very low pollution; 10: extremely high), with regional associations like Atmo providing granular data. Introduced in the early 2000s, it emphasizes real-time urban monitoring and integrates EU directives while adapting breakpoints for French exceedance limits, such as O3 thresholds reflecting southern photochemical smog patterns. The index informs public alerts, with levels 7-10 triggering recommendations for vulnerable populations to limit exposure. Germany's national air quality index, overseen by the Federal Environment Agency (Umweltbundesamt), focuses on four primary pollutants—PM10 or PM2.5, NO2, O3, and —displayed at over 400 monitoring stations with color-coded levels and behavioral guidance. Unlike the CAQI's flow-based emphasis, it prioritizes limit value compliance under the Federal Immission Control Act, using hourly averages and annual means; for example, PM2.5 breakpoints align with stricter national targets of 10 µg/m³ yearly averages. This system, digitized since the , enables station-specific indices rather than broad regional aggregates. Other nations, such as , rely on regional agencies (e.g., in ) for indices often harmonized with the CAQI but customized via pollutant weighting for Mediterranean O3 episodes, reporting via platforms like the National System for Environmental Integrated Protection (SNPA). These adaptations reflect causal factors like varying industrial emissions and , ensuring indices remain empirically grounded in verifiable measurements while addressing national policy variances.

Asia

China and Hong Kong

China's national Air Quality Index, established under the 2012 Ambient Air Quality (GB 3095-2012), evaluates six pollutants: PM₂.₅, PM₁₀, SO₂, NO₂, O₃, and CO. The index ranges from 0 to over 500, with breakpoints defining categories such as 0-50 (excellent), 51-100 (good), 101-150 (lightly polluted), 151-200 (moderately polluted), 201-300 (heavily polluted), and above 300 (severely polluted). For PM₂.₅, the excellent range spans 0-35 μg/m³, exceeding WHO annual guidelines of 5 μg/m³ by a factor of seven, prioritizing feasibility over stricter global health benchmarks. Sub-indices use piecewise linear functions, with the overall AQI taking the maximum value; daily averages are reported via the China National Environmental Monitoring Center, though enforcement varies regionally due to industrial emission controls. Hong Kong's Air Quality Health Index (AQHI), implemented by the Environmental Protection Department in 2013, shifts from concentration thresholds to aggregated health risks. It computes sub-indices for NO₂, O₃, and PM₂.₅, summing them on a 1-10+ scale: 1-3 (low risk), 4-6 (moderate), 7 (high), 8-10 (very high), and 10+ (serious). Hourly updates reflect short-term exposure effects, drawing on local epidemiological data linking pollutants to respiratory and cardiovascular outcomes, differing from mainland China's pollution-focused metric.

India

India's National Air Quality Index (NAQI), rolled out by the Central Pollution Control Board (CPCB) on October 17, 2014, standardizes monitoring across 131 cities initially, expanding nationwide. It assesses eight pollutants—PM₁₀, PM₂.₅, NO₂, SO₂, CO, O₃, NH₃, and Pb—but emphasizes PM₂.₅ and PM₁₀ due to dominant biomass and vehicular sources. Sub-indices employ segmented linear formulas with breakpoints like PM₂.₅ 0-30 μg/m³ for good (AQI 0-50), up to 250-500 μg/m³ for severe (401-500); overall AQI is the highest sub-index. Categories include good (0-50), satisfactory (51-100), moderate (101-200), poor (201-300), very poor (301-400), and severe (401+), with real-time dissemination via CPCB's portal and SAFAR system, aiding alerts during events like Diwali stubble burning yielding AQI spikes over 400 in Delhi. This framework, adapted for South Asian dust and tropical meteorology, imposes stricter PM thresholds than U.S. EPA equivalents in lower ranges, though enforcement gaps persist amid rapid urbanization.

Japan and South Korea

lacks a unified national composite AQI, instead regulating under the 1968 Air Pollution Control Act with enforceable standards for individual pollutants: SO₂ (0.02-0.04 hourly), NO₂ (0.04-0.06 ), (PM₁₀ proxy, 100 μg/m³ daily), and photochemical oxidants triggering alerts above 0.06 . The Ministry of the Environment publishes hourly data and issues warnings during high-ozone episodes, common in summer; public tools often convert to U.S. EPA AQI for comparability, reflecting annual PM₂.₅ averages of 8-15 μg/m³ in , sustained by stringent vehicle emission rules since the 1970s. South Korea's Comprehensive Air-quality Index (CAI), managed by AirKorea since 1995 and updated for PM₂.₅ in 2015, integrates PM₁₀, PM₂.₅, SO₂, NO₂, , and O₃ via sub-indices mirroring U.S. categories: good (0-50), moderate (51-100), unhealthy for sensitive groups (101-150), unhealthy (151-200), very unhealthy (201-300), hazardous (301+). Emphasis on fine dust stems from domestic coal use and transboundary inflows, with 24-hour PM₂.₅ standards at 35 μg/m³; real-time maps and forecasts address public concerns, as Seoul's winter averages exceed 25 μg/m³ annually despite mitigation efforts.

China and Hong Kong

's national Air Quality Index (AQI), established under the technical guideline HJ 633–2012 issued by the Ministry of Environmental Protection in 2012, evaluates based on six criteria pollutants: (SO₂), (NO₂), inhalable (PM₁₀), fine (PM₂.₅), (CO), and (O₃, using an 8-hour average). The AQI value, ranging from 0 to 500, is computed as the maximum of individual sub-indices for each pollutant, where concentrations are mapped to sub-index values via segmented linear functions with country-specific breakpoints that generally allow higher pollutant levels before reaching elevated AQI categories compared to guidelines. For instance, the annual PM₂.₅ standard underlying the system is 35 μg/m³, exceeding the WHO's recommended 10 μg/m³ limit, which has drawn for potentially understating health risks in densely polluted urban areas. The index categorizes air quality into six levels—excellent (0–50), good (51–100), lightly polluted (101–150), moderately polluted (151–200), heavily polluted (201–300), and severely polluted (above 300)—with daily and real-time reporting mandated for over 300 cities since 2013 to support advisories and policy enforcement. In contrast, Hong Kong operates the Air Quality Health Index (AQHI), implemented by the Environmental Protection Department in December 2013 as a departure from traditional concentration-based indices toward a health-outcome-oriented metric. The AQHI aggregates the percentage excess risks of short-term exposure to four key pollutants— (NO₂), (O₃), fine (PM₂.₅) or PM₁₀ (whichever poses the greater risk), and (SO₂)—derived from epidemiological models linking 3-hour concentrations to increased daily hospital admissions for respiratory and cardiovascular causes. This sum yields a scale from 1 (low risk) to 10+ (serious risk), divided into five categories: low (1), moderate (2–4), high (5–6), very high (7–9), and serious (10+), emphasizing cumulative health impacts over isolated pollutant thresholds. Unlike mainland China's AQI, which prioritizes the worst single pollutant, Hong Kong's AQHI incorporates synergistic effects and uses tighter alignment with international health benchmarks, reflecting the region's exposure to cross-border pollution from the while providing actionable, real-time forecasts updated hourly. The divergence between the two systems stems from differing regulatory priorities: mainland China's AQI facilitates nationwide monitoring under centralized environmental laws but has been noted for breakpoints that tolerate higher PM₂.₅ and NO₂ levels before triggering warnings, potentially delaying public responses in industrial hubs like and . Hong Kong's AQHI, influenced by Canadian models, prioritizes morbidity risks and has prompted more frequent advisories during regional events, though both territories face challenges from transboundary , with Hong Kong's levels often mirroring mainland trends due to meteorological patterns.

India

The National Air Quality Index (AQI) in , administered by the (CPCB) under the Ministry of Environment, Forest and Climate Change, was launched on 17 October 2014 to deliver simplified, real-time air quality information from monitoring stations nationwide. The system converts concentrations of multiple pollutants into a single numerical value, emphasizing public awareness and health advisories through color-coded categories and associated impacts. It draws on data from Continuous Ambient Air Quality Monitoring Stations (CAAQMS), with over 1,000 stations operational by 2024, primarily in urban areas. The Indian AQI evaluates eight pollutants: PM2.5, PM10, , , , , , and . Sub-indices are computed for each using pollutant-specific breakpoints and formulas, with the overall AQI determined by the highest sub-index value. Breakpoints are calibrated to reflect health thresholds derived from national standards, such as those under the of 2009, though PM2.5 often drives the index due to its prevalence in biomass burning, vehicular emissions, and industrial sources. AQI values range from 0 to 500, divided into six categories with defined health implications:
AQI RangeCategoryHealth Implications
0–50GoodAir quality satisfactory; minimal health risk for all.
51–100Generally acceptable; minor effects possible for sensitive individuals.
101–200Moderately PollutedUncomfortable for sensitive groups; asthmatics may experience symptoms.
201–300PoorRespiratory issues for susceptible people; general public advised to limit exertion.
301–400Very PoorHealthy individuals may experience effects; vulnerable groups face serious risks.
401–500SevereAffects even healthy people; entire population urged to avoid outdoor activities.
Data is updated hourly via the CPCB portal, enabling city rankings and comparisons, though coverage remains uneven, with northern cities like frequently exceeding 300 during winter due to burning and meteorological stagnation.

Japan and South Korea

Japan's air quality monitoring system, overseen by the Ministry of the Environment, does not utilize a unified numerical air quality index akin to those in other countries; instead, it relies on standards (EQS) for individual pollutants, with public reporting focused on measured concentrations and status. Key monitored pollutants include (SO₂, daily average ≤0.04 ppm, hourly ≤0.1 ppm), (CO, daily ≤10 ppm, 8-hour ≤20 ppm), (NO₂, daily 0.04–0.06 ppm), suspended (SPM, daily ≤100 μg/m³), photochemical oxidants (hourly ≤0.06 ppm), and PM₂.₅ (annual ≤15 μg/m³, 24-hour 98th percentile ≤35 μg/m³). Data are disseminated through the Atmospheric Environmental Regional Observation System (AEROS), which provides real-time and historical concentrations from over 1,000 monitoring stations nationwide, enabling assessments of standard attainment rates—such as 99.8% for PM₂.₅ in 2022 across designated areas. Advisories are issued for elevated risks, including PM₂.₅ "attention" calls when 24-hour forecasts reach or exceed 70 μg/m³, recommending reduced outdoor activity for vulnerable groups, and photochemical warnings based on oxidant levels triggering eye irritation alerts. In contrast, employs the Comprehensive Air-quality Index (CAI), administered by the Ministry of Environment via AirKorea, to provide a singular numerical indicator of ambient air quality ranging from 0 to 500. The CAI incorporates sub-indices for six pollutants—SO₂ (1-hour), (1-hour), O₃ (1-hour), NO₂ (1-hour), PM₁₀ (24-hour), and PM₂.₅ (24-hour)—calculated using between breakpoints, with the overall index determined by the highest sub-index value, augmented by 50 or 75 points if two or three pollutants respectively fall into unhealthy or worse categories. Categories are defined as Good (0–50, blue), Moderate (51–100, green), Unhealthy (101–250, yellow), and Very Unhealthy (251–500, red), with health advisories escalating from minimal concern in Good conditions to avoidance of outdoor exertion for all in Very Unhealthy levels. This system, updated hourly or daily based on monitoring networks exceeding 300 stations, reflects influences like transboundary PM from continental , contributing to frequent Unhealthy readings in urban areas such as , where annual PM₂.₅ averages have hovered around 20–25 μg/m³ in recent years.
CAI RangeCategoryColorHealth Implications
0–50GoodBlueAir pollution poses little or no risk.
51–100ModerateGreenAcceptable, but sensitive individuals may experience minor effects.
101–250UnhealthyYellowUnhealthy for sensitive groups; general public may notice symptoms with prolonged exposure.
251–500Very UnhealthyRedHealth alerts for everyone; avoid outdoor activities.
Both nations' approaches emphasize PM₂.₅ due to its prevalence from vehicle emissions, industry, and imported dust—Japan's standards align closely with WHO guidelines for annual PM₂.₅, while South Korea's CAI breakpoints for PM₂.₅ (e.g., 101–250 corresponding to 51–76 μg/m³ 24-hour) reflect a more precautionary scaling amid higher baseline pollution from regional sources.

Other Regions

employs a national Air Quality Index (AQI) framework, with implementation varying by state and territory to monitor pollutants including (PM10 and PM2.5), (NO2), (O3), and (SO2). The index categorizes air quality on a scale where 0-33 indicates very good conditions suitable for all activities, 34-66 good, 67-99 fair (with precautions for sensitive groups), 100-149 poor, and 150+ very poor, prompting reduced outdoor activities. Calculations rely on hourly averages, with the highest sub-index among pollutants determining the overall AQI to reflect the dominant . State-level reporting, such as in , integrates real-time data from monitoring stations to inform advisories, particularly during bushfire seasons when PM2.5 levels can spike significantly.

Latin America (e.g., Mexico)

In Mexico, air quality monitoring centers on the Metropolitan Air Quality Index (IMECA) for Mexico City and surrounding areas, which evaluates PM2.5, PM10, O3, NO2, SO2, and CO using 24-hour or hourly concentrations. The scale ranges from 0-50 (good, green), 51-100 (acceptable, yellow), 101-150 (bad, orange), 151-200 (very bad, red), to over 200 (extremely bad, black), with recommendations escalating from unrestricted activities to emergency measures as levels worsen. This system, managed by local environmental authorities, addresses chronic pollution from traffic, industry, and topography trapping emissions in valleys, where annual PM2.5 averages often exceed 20 µg/m³ in urban centers. Broader Latin American countries vary, with some like Chile using a similar multi-pollutant index aligned to WHO guidelines, but Mexico's IMECA exemplifies region-specific adaptations prioritizing ozone and particulates amid high-altitude urban challenges.

Southeast Asia (e.g., Singapore, Vietnam)

Singapore utilizes the Pollutant Standards Index (PSI), a 24-hour average metric incorporating PM2.5, PM10, O3, NO2, SO2, and CO, with bands from 0-50 (good), 51-100 (moderate), 101-200 (unhealthy), up to over 400 (hazardous), triggering advisories like mask-wearing during haze episodes from regional fires. The National Environment Agency updates PSI hourly, emphasizing PM2.5 due to transboundary haze, where levels can surge to unhealthy ranges exceeding 100 during dry seasons. In Vietnam, monitoring employs a standard AQI akin to international scales, focusing on PM2.5 and PM10 in cities like Hanoi and Ho Chi Minh City, where 2022 averages reached 40-50 µg/m³ PM2.5, classifying much of the urban air as moderate to unhealthy. Local agencies report via apps and websites, but data gaps persist in rural areas, with pollution driven by traffic, construction, and biomass burning; Singapore's PSI provides a model for subregional consistency amid varying enforcement.

Australia

Australia employs a decentralized approach to air quality indexing, with monitoring and public reporting conducted primarily by state and territory agencies, under the overarching National Environment Protection (Ambient Air Quality) Measure (NEPM) established in 1998 and revised as recently as 2022. The NEPM defines national ambient air quality standards for six criteria pollutants: (CO), (O3), (SO2), (NO2), coarse (PM10), and fine (PM2.5), with lead standards also included until phased out in reporting by 2010 due to declining emissions from unleaded . These standards specify averaging periods, such as 8-hour maxima for CO and O3, 1-hour for SO2 and NO2, and 24-hour for PM10 and PM2.5, aiming to protect by limiting exceedances to no more than one day per year on average over five years. Air quality indices (AQI) in are calculated at individual monitoring stations by determining sub-indices for each pollutant based on measured concentrations relative to NEPM thresholds, then taking the maximum sub-index as the site's overall AQI. This method aligns with practices in other jurisdictions, segmenting air quality into five to six categories—typically Good (green, low health risk), Fair/Moderate (yellow, minimal concern for sensitive groups), Poor (orange, advisory for vulnerable populations), Very Poor (red, reduce outdoor activity), and Hazardous (purple/maroon, emergency measures)—with numerical ranges varying slightly by state but generally scaling from 0 (pristine) to over 200 (extreme). For instance, in , PM2.5 concentrations of 0–25 μg/m³ correspond to Good, escalating to Hazardous above 300 μg/m³, reflecting acute risks from events like bushfires. and similarly use color-coded categories tied to 1-hour or 24-hour averages, with real-time data disseminated via state portals for public advisories on activity restrictions. While national aggregation occurs through reports like the Australia State of the Environment, which assesses compliance by comparing exceedance percentages against NEPM criteria across capital cities, there is no unified federal AQI dashboard; instead, states maintain independent networks, leading to minor methodological variations in breakpoint definitions or pollutant weighting. Overall compliance with NEPM standards has been high, with PM2.5 and O3 occasionally exceeding in urban areas due to traffic, industry, and seasonal wildfires—such as the 2019–2020 Black Summer fires that drove widespread Hazardous readings—but long-term population-weighted PM2.5 averages remain below 8 μg/m³ annually in most regions. This state-led system prioritizes localized data accuracy over standardization, enabling tailored responses to episodic pollution from prescribed burns or dust storms, though critics note potential inconsistencies in cross-jurisdictional comparisons.

Latin America (e.g., )

In , air quality monitoring systems often incorporate national adaptations of international standards, with indices calculated from pollutants such as PM2.5, PM10, , and oxides, though coverage remains uneven due to limited station density in rural areas. 's IMECA (Índice Metropolitano de la Calidad del Aire) serves as a prominent example, applied across the metropolitan zone encompassing the city and surrounding municipalities. The IMECA index, computed hourly by the Mexico City Environment Secretariat, aggregates sub-indices for six criteria pollutants—ozone (O3), (NO2), (SO2), (CO), inhalable particulate matter (PM10), and fine particulate matter (PM2.5)—using Mexican Official Standards (NOM) as breakpoints, such as NOM-025-SSA1 for PM2.5 at 45 μg/m³ for 24-hour averages. It produces a dimensionless value from 0 to over 200, categorized as bueno (good, 0-50), regular (fair, 51-100), mala (poor, 101-150), muy mala (very poor, 151-200), or extremadamente mala (extremely poor, >200), with thresholds triggering vehicle restrictions and industrial halts during contingencies. This system, operational since 1992, relies on over 30 automated stations reporting real-time data via public dashboards. Public engagement with IMECA is moderate; a 2018 population-based survey of 1,061 adults found 61.4% familiarity in versus 43.9% in the adjacent , correlating with higher adoption of protective actions like reduced outdoor time on poor air days among aware respondents. Air quality has improved over decades through measures like unleaded mandates and emissions controls, dropping 's global ranking to 88th by 2015 from prior notoriety, though PM2.5 episodes persist, averaging 20-30 μg/m³ annually in recent reports. Similar localized indices exist elsewhere, such as Brazil's IQA (Índice de Qualidade do Ar), which scales 0-500 based on PM10, , , O3, and NO2 against national thresholds, with values above 100 prompting alerts in urban centers like . Regional efforts, including satellite-assisted modeling, aim to enhance cross-border comparability amid challenges like burning and urban growth.

Southeast Asia (e.g., Singapore, Vietnam)

Singapore's National Environment Agency (NEA) operates the Pollutant Standards Index (PSI), a composite air quality metric derived from real-time and 24-hour average concentrations of six pollutants: fine particulate matter (PM2.5), inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ground-level ozone (O3), and carbon monoxide (CO). The PSI scale ranges from 0 to 500+, categorized as good (0-50), moderate (51-100), unhealthy (101-200), very unhealthy (201-300), and hazardous (301+), with the overall reading determined by the highest sub-index among the pollutants. NEA updates the 3-hour PSI hourly for immediate public guidance, especially during transboundary haze events from peat fires in Indonesia, which have historically driven PSI levels above 400 in September 2015 and October 2019, prompting school closures and outdoor activity restrictions. Singapore benchmarks PSI thresholds against World Health Organization air quality guidelines while maintaining national standards that prioritize PM2.5 due to its prevalence from regional biomass burning and urban sources. Vietnam's Ministry of Natural Resources and Environment oversees air quality monitoring through a network of stations in major cities, reporting an Air Quality Index (AQI) aligned with international scales that sub-index PM2.5, PM10, NO2, , , and O3 on a 0-500 linear scale, where 0-50 denotes good air quality and values exceeding 150 signal unhealthy conditions for the general population. Hanoi and routinely exhibit AQI readings in the moderate (51-100) to unhealthy (101-150) range, with 2023 annual PM2.5 averages of 38 µg/m³ in —over seven times the WHO guideline of 5 µg/m³—and episodic spikes to hazardous levels (AQI >300) from emissions, activity, and dust. Vietnam's system emphasizes PM2.5 as the primary driver, reflecting localized sources rather than uniform regional haze, though data gaps persist in rural areas due to limited station coverage. Across , AQI implementations vary but converge on multi-pollutant aggregation, with Thailand's Pollution Control Department using an AQI that prioritizes PM10 and PM2.5 (scale 0-500, good to hazardous) amid sugarcane burning seasons pushing Bangkok's readings above 200 in March 2024, and Malaysia's Department of Environment applying the Air Pollutant Index (API), similar to Singapore's PSI, which spiked to 150+ during 2019 haze episodes. Indonesia relies on a nascent AQI framework focused on PM2.5 from forest fires, often exceeding 300 in and , contributing to regional exceedances under agreements for haze mitigation. These indices highlight transboundary challenges, as wind patterns distribute pollutants, elevating AQI uniformly during El Niño-induced dry periods, with 37 of the world's 40 most polluted cities in 2023 located in the region per PM2.5 data.

Limitations and Criticisms

Measurement Accuracy and Sensor Reliability

Official air quality indices rely on data from reference-grade monitoring instruments, such as Federal Reference Method (FRM) and Federal Equivalent Method (FEM) analyzers certified by the U.S. Environmental Protection Agency, which measure criteria pollutants including (PM2.5 and PM10), , , , and with high precision under controlled conditions. These instruments undergo rigorous protocols, including daily calibrations and audits, achieving measurement uncertainties typically below 10-15% for PM2.5 concentrations in the range of 10-100 μg/m³, though errors can arise from instrument drift, incomplete combustion interferences in gas analyzers, or improper siting that fails to capture representative ambient conditions. Reliability of these monitors is maintained through federal performance standards requiring 90% data completeness and corrective actions for failures, yet operational issues like power outages or mechanical breakdowns can lead to data gaps, as documented in EPA Air Quality System reports where up to 20% of monitors experience downtime annually in some networks. Low-cost sensors, often electrochemical or optical devices costing under $500, have proliferated for supplemental AQI reporting via networks like PurpleAir, but exhibit lower accuracy and reliability compared to reference monitors, with studies reporting errors (RMSE) exceeding 10 μg/m³ for PM2.5 and coefficients (R²) below 0.7 without site-specific . These sensors suffer from cross-sensitivities to humidity, temperature, and co-pollutants, leading to overestimations during high relative humidity events by up to 50% for PM measurements, and baseline drift requiring frequent recalibration—often every few months—to mitigate systematic biases. Evaluations of commercial low-cost units, such as those from AirVisual and PurpleAir, reveal inter-unit variability where colocated devices differ by 20-30% in reported concentrations, undermining their use for regulatory AQI without correction algorithms. Calibration efforts for low-cost sensors frequently employ models like random forests or Gaussian processes to align readings with reference data, reducing errors by 30-50% in controlled deployments, though generalizability remains limited due to sensor-to-sensor inconsistencies and environmental variability. In practice, discrepancies between low-cost networks and official AQI sources can exceed a factor of two during episodic events like wildfires, as seen in comparisons where PurpleAir reported higher PM2.5 levels than AirNow, prompting debates over for advisories. Overall, while reference monitors provide the backbone for standardized AQI with quantifiable accuracy, the integration of uncalibrated low-cost sensors risks propagating unreliable data, necessitating hybrid approaches with rigorous validation to enhance spatial coverage without compromising precision.

Failure to Capture Cumulative Effects

The Air Quality Index (AQI) calculates an overall value by selecting the highest sub-index from individual pollutants such as PM2.5, , or , thereby emphasizing the dominant short-term risk without aggregating contributions from co-occurring pollutants. This single-pollutant maximum approach overlooks additive or synergistic interactions, where mixtures of pollutants can amplify health effects beyond those predicted by isolated assessments; for instance, epidemiological studies indicate that combined exposure to PM2.5 and NO2 yields stronger associations with respiratory outcomes than either alone. In regions with frequent multi-pollutant exceedances, such as parts of , AQI values have been shown to underestimate comprehensive health risks from the six criteria pollutants compared to alternative indices that incorporate joint effects. Furthermore, AQI reporting focuses on hourly or daily concentrations to guide immediate public actions, but it does not reflect cumulative over weeks, months, or years, during which low-level accrues significant harm. Long-term studies link sustained to fine particulate matter with increased risks of and mortality, effects driven by total inhaled dose rather than episodic peaks captured by AQI. This disconnect is evident in cases like lead, whose exclusion from standard AQI reflects its inherently cumulative unsuitable for daily indexing, yet similar dynamics apply to other pollutants where repeated sub-threshold exposures compound damage without triggering high AQI alerts. Critics argue this limitation fosters incomplete , as AQI "good" or "moderate" days may mask ongoing multi- burdens, particularly in or areas where synergistic stressors like exacerbate outcomes. Empirical models incorporating interactions, such as indices, reveal elevated hazards during co-exceedance events that AQI rates as acceptable, underscoring the need for supplementary metrics to address these gaps.

Overemphasis on Certain Pollutants and Potential Alarmism

The Air Quality Index (AQI) calculation often emphasizes a limited set of criteria pollutants—primarily (PM2.5), , , , and —by deriving the overall index from the maximum sub-index value among them, which can overshadow contributions from other atmospheric components or synergistic interactions. This methodology, as outlined in U.S. Environmental Protection Agency (EPA) technical documents, prioritizes the single most elevated pollutant without weighting for cumulative exposures, potentially amplifying the perceived dominance of PM2.5 or ozone in urban or wildfire-affected areas where these routinely exceed thresholds. Critics contend this structure neglects less-regulated factors like volatile organic compounds (VOCs), ultrafine particles below 0.1 micrometers, or bioaerosols, which may pose comparable or additive health risks but fall outside standard monitoring. The piecewise linear scaling for PM2.5 in AQI computations, featuring arbitrary breakpoints such as 12 μg/m³ (annual standard influence) and 35.4 μg/m³ (24-hour average), lacks direct physiological grounding and blends short- and long-term exposure metrics inconsistently, leading some analysts to argue it inflates index values relative to verifiable acute hazards. For example, an AQI exceeding 100—triggering "unhealthy for sensitive groups" warnings—can result from PM2.5 levels as low as 35.5 μg/m³ over 24 hours, even though epidemiological associations at such concentrations are confounded by factors like , , and urban confounders, with causation for mortality not firmly established below historical highs. Independent reviews highlight that EPA attributions of tens of thousands of annual U.S. deaths to PM2.5 rely on linear no-threshold models extrapolated from high-exposure cohorts (e.g., industrial areas), potentially overstating risks in modern contexts where ambient levels have declined over 50% since 1990 despite stable life expectancies. This emphasis contributes to potential alarmism, as color-coded AQI alerts (e.g., orange for 101–150) prompt broad behavioral advisories like reduced outdoor activity, which may induce undue public anxiety disproportionate to empirical harms for the general population. Regulatory thresholds, influenced by precautionary models from agencies like the EPA and WHO, have tightened iteratively—e.g., the U.S. primary PM2.5 annual standard reduced from 15 μg/m³ in 2006 to 9 μg/m³ in 2024—yielding frequent "moderate" or worse readings (51+ AQI) in compliant regions, correlating with media amplification of transient spikes from natural sources like wildfires or pollen without distinguishing drivers. Skeptics from non-governmental analyses note that such standards yield diminishing marginal returns, with cost-benefit ratios exceeding $100 million per life-year saved at lower levels, suggesting policy-driven stringency over evidence-based calibration; mainstream institutional sources, often aligned with environmental advocacy, underplay these debates in favor of consensus narratives. Healthy adults experience negligible acute effects below AQI 150 from short-term PM2.5 dominance, per controlled studies, yet advisories rarely qualify risks by individual factors like fitness or acclimation.

Recent Advances and Future Directions

Integration of Low-Cost Sensors and Data Sources

Low-cost sensors, typically electrochemical or optical devices costing between $100 and $2,500, have enabled the deployment of dense, community-driven networks that supplement traditional regulatory monitoring stations for air quality index (AQI) calculations, providing higher spatial and data. These sensors primarily measure (PM2.5 and PM10) and select gases like and , allowing for real-time AQI estimates in areas underserved by sparse government stations. Hybrid systems combining low-cost sensor (LCS) data with reference-grade instruments address gaps in conventional networks, as demonstrated by recommendations for their use in enhancing global monitoring coverage. Prominent examples include the PurpleAir network, which aggregates data from thousands of user-deployed sensors to generate EPA-standard AQI maps, integrated into the U.S. Agency's (EPA) AirNow Fire and Smoke Map since 2020 for wildfire-related pollution tracking. In 2025, the EPA expanded this by approving Clarity Movement sensors for the same platform, marking a milestone in incorporating calibrated for indicative monitoring during high-pollution events. Such integrations have supported responses, with studies showing LCS networks improving AQI granularity in urban and rural settings, though data from these sources remain supplementary due to regulatory requirements for Federal Reference or Equivalent Methods. Despite benefits, LCS integration faces challenges in accuracy, with raw readings prone to biases from environmental factors like and , often requiring site-specific against co-located reference monitors. Advances in machine learning-based corrections, including models that adjust for sensor drift and meteorological variables, have improved reliability; for instance, calibrated LCS can achieve correlations exceeding 0.9 with regulatory instruments under controlled conditions. A 2025 U.S. report highlights ongoing EPA efforts to validate LCS for broader AQI applications, emphasizing hybrid to mitigate variability while expanding coverage. These developments, including remote protocols, position LCS as viable for predictive AQI modeling, though full regulatory equivalence demands standardized validation protocols to counter inherent sensor limitations.

Machine Learning and Predictive Modeling

Machine learning techniques have been increasingly applied to predict Air Quality Index (AQI) values by analyzing historical pollutant concentrations, meteorological variables such as , , , and temporal patterns. These models enable short-term forecasting, often from hours to days ahead, aiding in alerts and emission control strategies. methods like and variants, including , , and , dominate due to their ability to handle nonlinear relationships and feature interactions among pollutants like PM2.5, PM10, NO2, , , and O3. Deep learning approaches, particularly (LSTM) networks, excel in capturing temporal dependencies in time-series AQI data, outperforming traditional statistical models in scenarios with sequential events. For instance, a study on , , using achieved an R² score of 0.9998 and RMSE of 0.76 when predicting AQI from , gaseous pollutants, and meteorological inputs. Similarly, models have reported accuracies exceeding 99% in evaluations on Indian datasets, though such figures reflect training set performance and may not generalize across diverse climates or sources. Support Vector Regression and Regression have also demonstrated over 96% accuracy in simplified models relying on core pollutants like PM2.5, PM10, and . Recent advancements from 2023 to 2025 emphasize frameworks combining tree-based ensembles with neural networks for improved explainability and applicability, incorporating Explainable (XAI) to interpret feature importance, such as the dominant role of PM2.5 in AQI variance. Integration with sensors and satellite data enhances , enabling city-scale predictions; one 2025 framework fused multimodal environmental data for dynamic forecasting, reducing prediction errors by addressing spatial correlations. However, model reliability depends on , with challenges in handling missing values or regime shifts from events like wildfires, underscoring the need for robust validation beyond lab-reported metrics. These predictive tools support policy decisions but require ongoing calibration to maintain causal accuracy in varying emission landscapes.

Harmonization Efforts for Global Comparability

Differing national air quality index (AQI) methodologies, including variations in monitored pollutants, breakpoint concentrations, and sub-index aggregation formulas, hinder direct comparisons of air quality across borders. For instance, the United States Environmental Protection Agency's AQI emphasizes criteria pollutants like ozone and particulate matter with breakpoints aligned to health effects, while China's AQI prioritizes PM2.5 due to prevalent sources, resulting in divergent index values for identical pollutant levels. These discrepancies complicate global assessments of pollution trends and health risks, prompting initiatives to standardize reporting. The (WHO) has advanced harmonization indirectly through its Global Air Quality Guidelines, updated on September 22, 2021, which establish health-based interim targets and recommended limits for key pollutants such as PM2.5 (annual mean of 5 μg/m³), PM10, NO2, O3, , and . These guidelines enable countries to align national standards and derive comparable indices, with 194 countries inventoried in a 2017 study revealing widespread adoption gaps, as many retain looser thresholds influenced by economic feasibility over stringent health protections. WHO's ambient air quality database further supports comparability by compiling ground-level measurements from global sources, though it focuses on raw concentrations rather than aggregated indices. Data aggregation platforms like OpenAQ, launched in 2016, harmonize raw air quality measurements from over 100 countries into a unified , facilitating cross-national analysis without altering local indices. Complementing this, the World Air Quality Index (WAQI) project, initiated in by aqicn.org, converts diverse national AQIs to a common scale based on the U.S. EPA 2016 standard, enabling real-time global mapping and alerts for over 10,000 stations. Research efforts propose explicit global indices, such as a 2023 Air Quality Health Index (AQHI) derived from WHO guidelines, weighting pollutants by relative health risks to yield comparable health impact scores across regions, validated against excess mortality data. A 2005 European assessment compared the U.S. EPA AQI with indices from nations like the UK and Japan, recommending breakpoint alignments for better interoperability. Despite these advances, full standardization remains elusive, as national AQIs often reflect local emission profiles and regulatory priorities, potentially understating risks in high-pollution areas when viewed through harmonized lenses.

Societal and Policy Impacts

Public Awareness and Behavioral Responses

Public awareness of the Air Quality Index (AQI) varies by region and demographic, with surveys indicating that while a may recognize air quality alerts, fewer actively consider them in daily decisions. For instance, analysis of U.S. survey from to found that 54% of respondents were aware of air quality alerts, but only 29% reported frequent consideration of air quality in their routines. Awareness is often heightened through mobile applications, reports, and public , which disseminate AQI to inform individuals of potential risks. However, perceptions of air quality frequently diverge from measured levels, influenced by factors such as , , and coverage rather than objective AQI metrics. Exposure to AQI information prompts various averting behaviors aimed at reducing of pollutants, particularly during episodes of unhealthy air. Empirical studies document reduced outdoor , with individuals cutting running distances by approximately 0.50 km (7.5%) on days with elevated levels when informed via AQI alerts or apps. Vulnerable populations, including children and those with respiratory conditions, exhibit stronger responses, such as staying indoors or limiting exertion, in line with EPA guidelines recommending avoidance of outdoor activity when AQI exceeds moderate thresholds. In regions like , high AQI readings correlate with increased defensive expenditures, including a 54.5% rise in general mask consumption and 70.6% for specialized anti-PM2.5 masks per 100-point AQI increase. The dissemination of AQI data through digital tools has demonstrated potential to drive preventive actions, with randomized trials showing that app usage linking pollution levels to health risks encourages behavior changes like shortened commutes or indoor alternatives to exercise. Protective behaviors induced by air pollution risk information, including mask-wearing and activity restriction, have been estimated to avert 5.7% of PM2.5-related premature deaths annually in informed populations. Nonetheless, the effectiveness of these responses depends on accurate communication; misleading reports of good air quality can lower perceived risks and diminish protective actions. Overall, while AQI serves as a key tool for public engagement, gaps in sustained awareness and equitable access to information limit broader behavioral shifts.

Regulatory Enforcement and Compliance

Regulatory enforcement of air quality standards, which underpin AQI calculations, involves monitoring compliance with pollutant thresholds set by national or supranational bodies, with AQI serving as a public-facing metric to trigger escalated actions during exceedances. In the United States, the Agency (EPA) enforces the Clean Air Act through state implementation plans (SIPs) requiring areas to meet (NAAQS), where persistent high AQI levels designate non-attainment zones subject to stricter permitting, emissions controls, and federal oversight. Violations can result in civil penalties up to $118,678 per day per violation as adjusted for in 2025, with EPA conducting inspections, audits, and settlements that recovered over $1 billion in penalties in fiscal year 2021 alone. In the , the Ambient Air Quality Directive mandates member states to monitor pollutants and maintain levels below limits, using AQI-like indices for alerts; non-compliance prompts infringement proceedings by the , potentially leading to fines imposed by the . The revised Directive 2024/2881, effective December 10, 2024, introduces stricter PM2.5 and NO2 limits aligned closer to WHO guidelines, with enhanced enforcement requiring national authorities to develop air quality plans and report exceedances, emphasizing accountability for persistent violations. China employs AQI to enforce national standards through centralized campaigns, including the 2017 shutdown of over 28,000 factories in northern provinces to curb winter , alongside ongoing inspections by the that impose production halts and fines for emitters exceeding limits. These measures, often tied to AQI thresholds above 200, have reduced violations but faced criticism for selective enforcement favoring economic priorities in local jurisdictions. In , the (CPCB) uses AQI to activate the Graded Response (GRAP) in Delhi-NCR, imposing measures like construction bans and vehicle restrictions when AQI surpasses 300; however, compliance remains uneven, with studies indicating over 60% of small industries violating emission norms due to limited regulatory capacity and selective inspections. interventions, such as in October 2024 declaring pollution-free air a fundamental right, have pushed for stricter accountability, yet enforcement gaps persist amid resource constraints and political influences. Globally, while AQI facilitates rapid response, effective compliance hinges on robust monitoring, deterrent penalties, and insulation from economic or local biases, with developing nations often lagging due to institutional weaknesses.

Economic Trade-Offs and Cost-Benefit Analyses

Cost-benefit analyses of air quality regulations, often informed by AQI thresholds for triggering interventions, reveal substantial health and economic gains from pollution reductions, though implementation imposes direct compliance burdens on industries and indirect costs from activity restrictions. The U.S. Environmental Protection Agency's retrospective study of the Clean Air Act from 1990 to 2020 estimated that benefits, primarily from averted premature deaths and morbidity, totaled approximately $2 trillion in the central estimate, exceeding compliance costs of about $65 billion by a factor of more than 30 to 1. Independent analyses, such as one by the Natural Resources Defense Council, corroborated net benefits ranging from $1.9 trillion to $3.8 trillion over the same period, attributing gains to reduced and exposure tracked via AQI metrics. These valuations rely heavily on the value of a statistical life, estimated at around $10 million per avoided death, which some economists critique for overstating benefits due to assumptions about willingness-to-pay in diverse populations. In developing economies with volatile AQI levels, trade-offs are starker, as stringent controls based on high AQI episodes can disrupt economic activity while itself erodes productivity. In , attributable economic losses reached $26.5 annually as of recent estimates, varying up to fivefold across states, with national impacts equivalent to 3% of GDP from lost output, healthcare, and premature mortality. Measures like Delhi's odd-even vehicle rationing and school closures during AQI exceedances of 400+ have curbed emissions but incurred short-term costs in reduced and , estimated in billions of dollars per severe episode, though long-term health savings from lower PM2.5 levels are projected to outweigh these by reducing morbidity burdens of $8 billion yearly. Similarly, in , pre-2018 costs hit 6.6% of GDP, prompting AQI-driven crackdowns that improved air quality in cities like , yielding health expenditure reductions and economic rebounds via cleaner industrial transitions, with benefits surpassing abatement costs in 70% of global studies reviewed. Market-based approaches, such as systems calibrated to AQI improvement targets, mitigate trade-offs by achieving reductions at lower costs than command-and-control mandates. Pilot programs in , like Surat's emissions market, demonstrated 25-fold health benefits over costs by incentivizing firm-level efficiencies without broad shutdowns. However, in high-AQI contexts, over-reliance on restrictive alerts can amplify economic drags, as evidenced by reduced (1.3% drop in , or $22 billion in 2019) from pollution-induced behavioral changes, underscoring the need for targeted policies that weigh localized AQI data against sector-specific impacts. Critics of overly stringent AQI thresholds argue they impose disproportionate burdens on manufacturing-heavy regions, potentially slowing GDP growth by 0.5-1% annually in affected areas, though empirical data from phased implementations show net positive returns after 5-10 years through avoided externalities.

References

  1. [1]
    Air Data Basic Information | US EPA
    Nov 20, 2024 · The AQI is an index for reporting daily air quality. It tells how clean or polluted the air is, and what associated health effects might be a ...
  2. [2]
    Patient Exposure and the Air Quality Index | US EPA
    May 23, 2025 · The AQI tells the public how clean or polluted the air is and how to avoid health effects associated with poor air quality. The AQI focuses on ...
  3. [3]
    What Is the Air Quality Index? - NRDC
    Sep 27, 2023 · The AQI is a scale that provides real-time information on the amount of pollution in the air. The US Environmental Protection Agency (EPA) developed the index.Aqi Reference Chart · The Clean Air Act 101 · Why Does Air Quality Change...
  4. [4]
    [PDF] The Air Quality Index (AQI) in historical and analytical perspective a ...
    In particular, the 1970 amendment provided directions in developing air quality standards for each of the criteria pollutants; this would become the. National ...
  5. [5]
    Standards for Air Quality Indices in Different Countries (AQI)
    Nov 28, 2023 · The AQHI is reported on a scale from 1 to 10 and 10+, and is divided into five categories: low, moderate, high, very high, and serious.<|separator|>
  6. [6]
  7. [7]
    What are the WHO Air quality guidelines?
    Sep 22, 2021 · The WHO Air quality guidelines recommend levels and interim targets for common air pollutants: PM, O3, NO2, and SO2. Recommended 2021 AQG ...
  8. [8]
    What is the difference between the US AQI and WHO air quality ...
    Oct 12, 2016 · The WHO's annual mean exposure guideline of 5 μg/m3 guideline is broadly referred to as the authoritative global guideline for PM2.5 exposure.
  9. [9]
    A Review of Chronological Evolution of Air Quality Indexing Systems ...
    Dec 9, 2021 · Green's Index is the first air Quality Index developed in 1966 by Marvin H. Green. This pollution index is based on only two parameters: i.
  10. [10]
    The Air Quality Index (AQI) in historical and analytical perspective a ...
    Jan 15, 2024 · In this paper, we provide a historical overview of the Air Quality Index, the Federal Reference Methods (FRMs) vs. Federal Equivalent Methods (FEMs) for ...
  11. [11]
    Air Quality Index (AQI) Basics - AirNow.gov
    For example, an AQI value of 50 or below represents good air quality, while an AQI value over 300 represents hazardous air quality. For each pollutant an AQI ...Indiana · Alaska · Using
  12. [12]
    Criteria Air Pollutants | US EPA
    Aug 25, 2025 · The Clean Air Act requires EPA to set National Ambient Air Quality Standards (NAAQS) for six commonly found air pollutants known as criteria ...NAAQS Table · Hazardous Air · Air Emissions Inventories · Information by PollutantMissing: core scale
  13. [13]
    How is the AQI calculated? | US EPA
    Jul 15, 2025 · Refer to the AQI Technical Assistance Document for equations on how to calculate the AQI from pollutant concentration.
  14. [14]
    [PDF] Technical Assistance Document for the Reporting of Daily Air Quality
    Using Table 5, find the two breakpoints that contain the concentration. c. Using Equation 1, calculate the index. d. Round the index to the nearest integer.
  15. [15]
    United States of America - AQI Hub
    The following piecewise linear function is used to calculate the sub-index AQI values using each pollutant's breakpoint concentration: A Q I P = I H I − I ...
  16. [16]
    Air Quality Index | American Lung Association
    Sep 18, 2024 · When AQI values are above 100, air quality is unhealthy. The higher the number, the more people are at risk of health harm. What Can You Do ...
  17. [17]
    Managing Air Quality - Human Health, Environmental and Economic ...
    Feb 13, 2025 · Hazardous (or toxic) air pollutants may cause cancer or other serious health effects, such as reproductive effects or birth defects. Specific ...
  18. [18]
    Air Pollution and Your Health
    It can be inhaled deeply into lung tissue and contribute to serious health problems. PM 2.5 accounts for most health effects due to air pollution in the U.S.
  19. [19]
    Public Health Relevance of US EPA Air Quality Index Activity ...
    Apr 8, 2024 · These findings suggest that existing PM 2.5 AQI activity recommendations are of questionable public health relevance in present-day conditions.
  20. [20]
    How is air quality measured? - UNEP
    Sep 22, 2022 · The database prioritizes PM2.5 readings and applies artificial intelligence to calculate nearly every country's population exposure to air ...
  21. [21]
    Air pollution in NYC led to creation of the EPA's Air Quality Index
    Jun 15, 2023 · By 1976, with a mandate from Congress to share air quality data, the EPA created the “Pollutant Standards Index,” which provided information ...
  22. [22]
    Evolution of the Clean Air Act | US EPA
    This page describes how the Clean Air Act and its subsequent amendments in 1977 and 1990 evolved from the Air Pollution Control Act on 1955.
  23. [23]
    History of the Air District
    In 1979, the Pollutant Standards Index (forerunner of the Air Quality Index, or AQI) was introduced by the EPA to give the public easily understandable ...<|separator|>
  24. [24]
    Timeline of Ozone National Ambient Air Quality Standards (NAAQS)
    In 1971, the standard was 0.08 ppm for 1 hour. In 1979, it was 0.12 ppm for 1 hour. In 1997, it was 0.08 ppm for 8 hours. In 2015, it was 0.070 ppm for 8 hours.Missing: 1980s | Show results with:1980s
  25. [25]
    Guideline for public reporting of daily air quality: Pollutant Standards ...
    Aug 1, 1976 · The guideline suggests the use of an air quality index for those local and state air pollution control agencies wishing to report an air quality index on a ...Missing: rule 1999
  26. [26]
    Clean Air Act: A Summary of the Act and Its Major Requirements
    Sep 13, 2022 · It provides a very brief history of federal involvement in air quality regulation and of the provisions added by legislation in 1970, 1977, and ...
  27. [27]
    [PDF] Federal Register/Vol. 64, No. 149/Wednesday, August 4, 1999 ...
    Aug 4, 1999 · The. EPA has determined that the revisions to air quality index reporting in this final rule would not have an annual effect on the economy ...
  28. [28]
    Air Quality Index Reporting - Federal Register
    Aug 4, 1999 · Air Quality Index Reporting. A Rule by the Environmental Protection Agency on 08/04/1999. New folder; My Clipboard. Published Document: 99-19433 ...Missing: final PSI
  29. [29]
    Air quality guidelines for Europe, 2nd edition
    Jan 1, 2000 · The first edition of the WHO Air quality guidelines for Europe was published in 1987. Since then new data have emerged and new developments ...
  30. [30]
    Reconsideration of the National Ambient Air Quality Standards for ...
    Jan 27, 2023 · In so doing, the EPA proposes to revise the AQI value of 50 within the range of 9.0 and 10.0 µg/m3 and proposes to retain the AQI values of 100 ...
  31. [31]
    [PDF] Final Updates to the Air Quality Index (AQI) for Particulate Matter - EPA
    Feb 7, 2024 · The updated reporting requirement applies for all AQI pollutants. • The previous requirement was issued in 1999. It required the daily AQI to be ...
  32. [32]
    Using Air Quality Index | AirNow.gov
    Use the Air Quality Index (AQI) to learn more about your local air quality and the best times for your outdoor activities.
  33. [33]
    Development of the National Air Quality Health Index — China, 2013 ...
    This report introduced the method of calculating the Chinese AQHI. This AQHI was established based on daily PM 2.5 , O 3 , NO 2 , and SO 2 concentration of 769 ...
  34. [34]
    How the U.S. State Department started a Chinese environmental ...
    Rating 5.0 (5) Apr 14, 2025 · In April 2008, just months before the Beijing Olympics, the U.S. Embassy in Beijing installed a regulatory-grade air quality monitor and began ...
  35. [35]
    National Air Quality Index (AQI) launched by the Environment ... - PIB
    Oct 17, 2014 · The Minister for Environment, Forests & Climate Change Shri Prakash Javadekar today launched 'The National Air Quality Index' (AQI) in New Delhi.
  36. [36]
    PM Narendra Modi launches National Air Quality Index
    Apr 6, 2015 · The AQI has been at present launched for 10 cities -- Delhi, Agra, Kanpur, Lucknow, Varanasi, Faridabad, Ahmedabad, Chennai, Bangalore and ...
  37. [37]
    A chronology of global air quality - Journals
    Sep 28, 2020 · Sporadic measurements of air quality began in the late nineteenth century, especially by Robert Angus Smith in the UK [7], the first scientist ...Introduction · The development of laws to... · 1750–1950 Urban air quality...
  38. [38]
    World Air Quality Historical Database
    The database provides individual pollutant AQI data since ~2012, converted from raw concentrations, but is not fully verified and not for official use.Missing: developments | Show results with:developments
  39. [39]
    Global air quality inequality over 2000–2020 - ScienceDirect
    The global PM2.5 Gini Index rose from 0.30 in 2000 to 0.35 in 2020, exceeding levels of income inequality in many countries. Air quality inequality is mostly ...
  40. [40]
    Development of an aggregate Air Quality Index for an urban ...
    This early index is based on five pollutants, namely O3, NO2, CO, SO2 and PM10. In June, 2000, EPA improved PSI and renamed it to Air Quality Index (AQI).<|separator|>
  41. [41]
    Air quality index variation before and after the onset of COVID-19 ...
    Dec 5, 2021 · The purpose of this study was to investigate the changes in the air quality indexes (AQI) in industrial, densely populated and capital cities in different ...
  42. [42]
    NAAQS Table | US EPA
    Jul 31, 2025 · Units of measure for the standards are parts per million (ppm) by volume, parts per billion (ppb) by volume, and micrograms per cubic meter of ...
  43. [43]
    Ambient (outdoor) air pollution - World Health Organization (WHO)
    Oct 24, 2024 · Pollutants · Particulate matter (PM) PM is a common proxy indicator for air pollution. · Carbon monoxide (CO) · Ozone (O3) · Nitrogen dioxide (NO2)<|separator|>
  44. [44]
    National Air Quality: Status and Trends of Key Air Pollutants | US EPA
    Aug 28, 2025 · EPA sets national air quality standards for six common air pollutants. Each year EPA tracks the levels of these air pollutants in the air.National Summary · Design Values · Previous Air Quality Trends... · Ozone Trends
  45. [45]
    Air Pollutants | Air Quality - CDC
    Feb 16, 2024 · The six criteria air pollutants · Carbon monoxide · Lead · Nitrogen oxides · Ozone · Particulate matter · Sulfur dioxide.
  46. [46]
    Air Quality Standards - World Health Organization (WHO)
    May 19, 2025 · This database is a comprehensive resource that compiles national air quality standards for criteria pollutants and other airborne toxics from countries ...
  47. [47]
    About Air Data Reports | US EPA
    Mar 20, 2025 · The AirData Air Quality Index Summary Report displays an annual summary of Air Quality Index (AQI) values for counties or core based statistical areas (CBSA).<|separator|>
  48. [48]
    40 CFR Appendix G to Part 58 - Uniform Air Quality Index (AQI) and ...
    If the concentration is between two breakpoints, then calculate the index of that pollutant with equation 1. It should also be noted that in some areas, the AQI ...<|control11|><|separator|>
  49. [49]
    How to Calculate AQI and NowCast Indices - Met One Instruments
    The PM2.5 AQI is computed from the following formula where Ip = AQI: 24 1-hour measured PM values from midnight to midnight are needed to compute the Air ...
  50. [50]
    [PDF] A Guide to Air Quality and Your Health - AirNow.gov
    What do the AQI values mean? 151 to 200 Unhealthy Red 201 to 300 Very Unhealthy Purple 301 to 500 Hazardous Maroon 2 Page 4 Air Quality Index Each category ...Missing: categorization | Show results with:categorization
  51. [51]
    Air Quality Health Index - Canada.ca
    Jun 9, 2025 · The Air Quality Health Index is a public information tool providing local conditions, forecasts, and health risks, including air pollution and ...Air quality · About the Air Quality Health... · Air quality and weather · Use
  52. [52]
    Air quality - Canada.ca
    Jun 26, 2025 · Canada's key air pollutants are PM2.5, O3, NO2, SO2, and VOCs. PM2.5 had high peak in 2018 due to wildfires. Average and peak trends are ...
  53. [53]
    How we measure air quality and what the numbers mean | CBC News
    Jun 26, 2023 · Canada uses what's called the Air Quality Health Index (AQHI), a measurement designed to make it easier for the public to understand the level of risk involved.
  54. [54]
    Difference between Air Quality Health Index and Air ... - Canada.ca
    Nov 14, 2018 · This webpage describes both the Air Quality Index and Air Quality Health Index. It compares and contrasts both indices.
  55. [55]
  56. [56]
    US EPA PM2.5 Air Quality Standards Interactive Map by PurpleAir
    The US EPA PM2.5 Air Quality Index (AQI) is a number used by US government agencies to communicate to the public how polluted the air currently is.
  57. [57]
    AirNow.gov
    Air Quality Index Scale ; 0 - 50. Good ; 51 - 100. Moderate ; 101 - 150. Unhealthy for Sensitive Groups (USG) ; 151 - 200. Unhealthy.Air Quality Index (AQI) Basics · Air Quality Index (AQI) · Maps and Data · AQI Basics
  58. [58]
    Air Quality Index Report | US EPA
    Mar 28, 2025 · This report provides Air Quality Index annual summary information, including maximum AQI values and the count of days in each AQI category.
  59. [59]
    Public Health Relevance of US EPA Air Quality Index Activity ... - NIH
    Apr 8, 2024 · This cross-sectional study assesses the public health relevance of air quality index (AQI) activity guidance for exposure to fine particulate matter air ...
  60. [60]
    Air Quality Health Index Messages - Environment Canada
    Aug 6, 2025 · Very High Risk, Above 10, Avoid strenuous activities outdoors. Children and the elderly should also avoid outdoor physical exertion.
  61. [61]
    Air Quality Health Index (AQHI)
    AQHI readings and forecasts are also available on Environment and Climate Change Canada website. You can also get AQHI readings from recorded telephone messages ...Air quality alerts · Map · Toronto West · Ottawa Downtown<|separator|>
  62. [62]
    Local Air Quality Health Index - Environment Canada
    This table shows a summary of the most recent forecast values of the Air Quality Health Index for many Canadian cities.Ontario · Edmonton · Alberta · British Columbia
  63. [63]
    UO study compares US, Canadian wildfire smoke air quality indexes
    Jul 25, 2024 · The American Air Quality Index, or AQI, is based on a scale from zero to 500+. The Canadian Air Quality Health Index, or AQHI, has a scale from ...<|separator|>
  64. [64]
    Air Quality | US EPA
    The US Air Quality Index is EPA's index for reporting air quality. Every day the AQI tells you how clean or polluted your outdoor air is.
  65. [65]
    Federal Register, Volume 64 Issue 149 (Wednesday, August 4, 1999)
    Aug 4, 1999 · ). In addition, EPA is changing the name of the index from the Pollutant Standards Index (PSI) to the Air Quality Index (AQI). This document ...
  66. [66]
    Air Quality System (AQS) | US EPA
    Aug 28, 2025 · The Air Quality System (AQS) is EPA's repository of ambient air quality data. AQS stores data from over 10000 monitors, 5000 of which are ...Obtaining AQS Data · AQS Code List · AQS Manuals and Guides · AQS Java Memo<|separator|>
  67. [67]
    Air Quality Data Collected at Outdoor Monitors Across the US - EPA
    Sep 2, 2025 · This site provides air quality data collected at outdoor monitors across the United States, Puerto Rico, and the U. S. Virgin Islands.Air Quality Index Report · Download Daily Data · Interactive Map · AQI Plot
  68. [68]
    About the Air Quality Health Index - Canada.ca
    Apr 28, 2021 · The Air Quality Health Index or "AQHI" is a scale designed to help you understand what the air quality around you means to your health.
  69. [69]
    Assessment of the Air Quality Health Index (AQHI) and four alternate ...
    Jul 8, 2019 · The AQHI is calculated based on a formula that includes the concentrations of three common air pollutants known to affect human health: ground- ...
  70. [70]
    The Air Quality Health Index and Asthma Morbidity - EHP Publishing
    Health Canada and Environment Canada began a collaboration in 2001 to develop a new index named the Air Quality Health Index (AQHI), which was derived based on ...
  71. [71]
    The construction of the air quality health index (AQHI) and a validity ...
    It was calculated by estimating the short-term mortality risks of selected air pollution, which assumes a non-threshold log-linear association between air ...
  72. [72]
    AQI Hub Canada (AQHI)
    A calculation method based on the AQHI formula is used to forecast the AQHI, however it only accounts for predicted concentrations of PM2.5 and O3. The air ...
  73. [73]
    Air Quality Health Index – Calculation | Alberta.ca
    The formula developed to calculate the national Air Quality Health Index (AQHI) is based on research conducted by Health Canada using health and air quality ...Missing: method | Show results with:method
  74. [74]
    [PDF] Air Quality Health Index Variation across British Columbia - Gov.bc.ca
    The AQHI is a function of the hourly ambient concentrations of nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3). It is calculated each ...Missing: method | Show results with:method
  75. [75]
    CAQI Common Air Quality Index — Update with PM2.5 and ...
    Aug 1, 2014 · The CAQI or Common Air Quality Index was proposed to facilitate the comparison of air quality in European cities in real-time.
  76. [76]
    European Air Quality Index
    The European Air Quality Index allows users to understand more about air quality where they live, work or travel. Displaying up-to-date information for ...
  77. [77]
    Air pollution | In-depth topics | European Environment Agency (EEA)
    Aug 20, 2025 · Since the 1980s, the EU has adopted strict policies on air quality ... The European Air Quality Index provides information on the current air ...European city air quality viewer · National air pollutant · Environmental health risk<|separator|>
  78. [78]
    European Air Quality Index Calculation — CAMS Training
    The index ranges from 1 (good) to 6 (extremely poor). For each pollutant, the index is calculated separately according to the concentrations; the higher the ...Missing: Union | Show results with:Union
  79. [79]
    EU air quality standards - Environment - European Commission
    The EU air quality standards and objectives are summarised in the table below. These apply over different periods of time.
  80. [80]
    European Union and United States Update Air Quality Standards
    Feb 7, 2024 · The new rules aim to establish stricter EU air quality standards for 2030, which will be more in line with World Health Organization (WHO) guidelines.
  81. [81]
    Air Quality Index - Documentation
    To estimate the Common Air Quality Index (CAQI), it is calculated the average concentration for NO₂, PM₁₀, O₃, PM₂.₅, CO, and SO₂ using the NowCast algorithm ...
  82. [82]
    Air Quality Map - Check air pollution in your area - Airly
    The air quality index used in Europe, CAQI, has five ranges, with the values presented on a scale from 0 (very low) to >100 (very high). It is a relative ...
  83. [83]
    European Air Quality Index Calculation | Climate & Clean Air Coalition
    Apr 22, 2025 · This notebook provides you a practical introduction to the calculation and interpretation of the Air Quality Index (AQI) in Europe.Missing: CAQI | Show results with:CAQI
  84. [84]
    European Union - Air Quality Index Hub
    The European Union has established the European Air Quality Index, accounting for five pollutants: PM2.5, PM10, O3, NO2, and SO2. An hourly AQI value is ...
  85. [85]
    Daily Air Quality Index - DEFRA UK Air - GOV.UK
    The Daily Air Quality Index (DAQI) tells you about levels of air pollution and provides recommended actions and health advice.Menu · PM2.5 Particles · PM10 Particles · Sulphur Dioxide
  86. [86]
    Eu Air Quality Index (AQI) and France Air Pollution | IQAir
    Eu Air Quality Index (AQI) is now Good. Get real-time, historical and forecast PM2.5 and weather data. Read the air pollution in Eu, France with AirVisual.Missing: CAQI | Show results with:CAQI
  87. [87]
    CAQI Common Air Quality Index — Update with PM2.5 and ...
    The CAQI has 5 index classes ranging from very low to very high air pollution. It uses a long scale (1–100) to assure a dynamic picture of the air quality. This ...
  88. [88]
    [PDF] CAQI Air quality index
    The calculation is based on three pollutants of major concern: PM10, NO2,. O3. It can also take the pollutants PM2.5, CO and SO2 into account if these data are ...
  89. [89]
    Air Quality Index – CAQI and AQI. How to Calculate Them? - Airly
    Read our article to find out the differences between CAQI and AQI. And how the different air pollution indicators are calculated!<|control11|><|separator|>
  90. [90]
    What is the Daily Air Quality Index? - DEFRA UK Air - GOV.UK
    The DAQI (1-10) indicates air pollution levels and provides health advice. It is used for forecasts and monitoring, based on five pollutants.PM2.5 Particles · PM10 Particles · Nitrogen Dioxide · Sulphur Dioxide
  91. [91]
    Daily Air Quality Index (DAQI)
    The DAQI is a 1-10 index, using five pollutants, to show air pollution levels, similar to the sun or pollen index.
  92. [92]
    Atmo France: Un air sain pour tous
    La qualité de l'air près de chez vous · Très faible · Faible · Modéré · Élevé · Très élevé · Extrêmement élevé · Indisponible.Carte France Indice ATMO et... · Les valeurs d'Atmo France · France · Air extérieur
  93. [93]
  94. [94]
    Air data - Umweltbundesamt
    The air quality index based on four pollutants shows at a glance how good the air is at each monitoring station. It further provides conduct recommendations ...
  95. [95]
    Rome Air Pollution: Real-time Air Quality Index (AQI)
    Rome Air Pollution: Real-time Air Quality Index (AQI) ; PM2.5 AQI. 46, Arenula, Roma, Lazio, Italy PM25 (fine particulate matter) measured by ARAP ; PM10 AQI. 26 ...<|control11|><|separator|>
  96. [96]
    China: Air Quality Standards | Transport Policy - TransportPolicy.net
    Ambient air quality has been regulated in China since 1982, when initial limits were set for TSP (Total Suspended Particulates), SO2, NO2, lead, and BaP (Benzo( ...Missing: introduction date
  97. [97]
    China Air Quality Index (AQI) and Air Pollution information | IQAir
    China has a standard figure of 35 µg/m³ to which it tries to adhere to, whereas the recommended limit as suggested by the World Health Organisation is 10 µg/m³.
  98. [98]
    China - AQI Hub
    China's Air Quality Index accounts for six primary pollutants: PM 2.5, PM 10, CO, O 3, NO 2 and SO 2. A daily and real-time AQI is reported, along with a ...
  99. [99]
    EPD AQHI : What's AQHI
    The AQHI informs you of the short-term health risk of air pollution and helps you take precautionary measures to protect your health.
  100. [100]
    Air Quality Health Index - GovHK
    The Air Quality Health Index (AQHI) compiled by the Environmental Protection Department (EPD) informs the public of the short-term health risk of air pollution ...
  101. [101]
    Update of Air Quality Health Index (AQHI) and harmonization of ...
    Jun 1, 2024 · In 2014, Hong Kong introduced a risk-based Air Quality Health Index (AQHI) to replace the earlier concentration-based air pollution index ...
  102. [102]
    National Air Quality Index - CPCB | Central Pollution Control Board
    Sep 9, 2024 · National Air Quality IndexUpdated On : 09 Sep 2024 · National Air Quality Index (NAQI) · About NAQI · How AQI is Calculated · National Real Time ...
  103. [103]
    Air Quality Index - SAFAR - India
    Air Quality Index ; AQI Category(Range) ; I low. I high ; Good. 0. 50 ; Satisfactory. 50. 100 ; Moderate. 100. 200.
  104. [104]
    Overview of India's National Air Quality Index
    May 15, 2015 · India's NAQI, created by CPCB, is adapted to Asian dust, is stricter than US EPA, and has a range from Good to Severe.<|separator|>
  105. [105]
    Japan Air Quality Index (AQI) and Air Pollution information | IQAir
    At the beginning of 2021, Japan was enjoying relatively good quality air with a US AQI reading of 47 which classified it in the “Good” category according to ...Air quality in Japan · Tokyo · Luftqualität in Japan · Kualitas udara di Japan
  106. [106]
    Japan Air Quality Index | What Are Tokyo's Pollution Stats?
    Apr 26, 2023 · Based on historical data from 2018-2022, Japan ranks 97th in the worst countries for air quality, out of a total of 131 countries listed.
  107. [107]
    AirKorea
    What's CAI ... The CAI is an index of reporting air quality. It tells you how clean or polluted air is and what health eff-ects might be caused by air pollution.
  108. [108]
    South Korea Air Quality Index (AQI) and Air Pollution information
    In 2019, the annual average air quality in South Korea was classified as being "Moderate" with a reading of 78 US AQI. The PM2.5 level was twice the recommended ...Seoul · Daegu · Gyeonggi-do · Chungcheongbuk-do
  109. [109]
    Is Air Quality in China a Social Problem? - ChinaPower Project
    Beijing's average AQI in February 2020, for example, reached 155, while it was a moderate 73 in September. Daily AQI averages can climb to much higher levels.Missing: date | Show results with:date<|separator|>
  110. [110]
    Hong Kong - Air Quality Health Index (AQHI) - AQI Hub
    The Air Quality Health Index (AQHI) accounts for 4 criteria pollutants: PM, O3, NO2 and SO2. For PM, both PM2.5 and PM10 are considered, however only the PM ...
  111. [111]
    How is the AQHI calculated?
    AQHIs are calculated based on the cumulative health risk attributable to the 3-hour moving average concentrations of four air pollutants.
  112. [112]
  113. [113]
    Real time Air Quality Index from various locations
    The real-time data as collected from the field instruments is displayed live without human intervention from CPCB. It is likely that the live data may display ...
  114. [114]
    [PDF] About National Air Quality Index - CPCB
    AQ sub-index and health breakpoints are evolved for eight pollutants (PM10, PM2. 5, NO2, SO2, CO, O3, NH3, and Pb) for which short-term (upto 24-hours) ...
  115. [115]
    National Air Quality Index
    National Air Quality Index. Central Pollution Control Board, Ministry of Environment, Forests and Climate Change; Color Codes; City Rankings; Compare Cities ...
  116. [116]
    Environmental Quality Standards in Japan | Air & Transportation
    The annual standard for PM2.5 is less than or equal to 15.0 μg/m3. The 24 hour standard, which means the annual 98th percentile values at designated monitoring ...
  117. [117]
    Introduction to the CAI - AirKorea
    The CAI describes air quality based on health risk, calculated from six pollutants, with values from 0-500, ranging from good to very unhealthy.Missing: CAQI | Show results with:CAQI<|separator|>
  118. [118]
    Australia Air Quality Index (AQI) and Air Pollution information | IQAir
    Lower AQI numbers represent better air quality, from 0-33 representing “Very good”, up to 150+ representing “Very poor” air quality.1 When multiple pollutants ...Air quality in Australia · Air quality in Sydney · Western Australia · South Australia
  119. [119]
    Air quality index - Department of Water and Environmental Regulation
    The Air Quality Index (AQI) for nitrogen dioxide (NO2), ozone (O3) sulfur dioxide (SO2) and particles (PM10 and PM2.5) are based on clock hour averages ...
  120. [120]
    Smoke and Air Quality Information - BoM
    Smoke and air quality information ; Australia wide. Air Pollution in Australia: Real-time Air Quality Index Visual Map · Air Quality Australia ; New South Wales.
  121. [121]
    Mexico City Air Quality Index (AQI) and Mexico Air Pollution | IQAir
    Mexico City Air Quality Index (AQI) is now --. Get real-time, historical and forecast PM2.5 and weather data. Read the air pollution in Mexico City, Mex...Ciudad de Mexico44 · Mexico City53 · Air quality in Toluca · Air quality in Coyoacan
  122. [122]
    Mexico-city Air Pollution: Real-time Air Quality Index (AQI)
    Mexico-city Air Pollution: Real-time Air Quality Index (AQI) · 31 · 37 · 48 · 41 · 23 · 18 · 22 · 28, 34, 36, 40, 28, 17, 13, 20 ...
  123. [123]
    Haze - Singapore
    Latest Update · Haze Situation Update · Air Quality · Hotspots · Satellite Images · Health Advisory · What's New · Our Related Sites.Readings over the last 24 hours · Air Quality · Portable Air Cleaners · Who We Are
  124. [124]
    Central, Singapore Air Pollution: Real-time Air Quality Index (AQI)
    Central, Singapore Air Pollution: Real-time Air Quality Index (AQI) · 93 · 80 · 85 · 84 · 63 · 59 · 77 · 79, 79, 82, 85, 76, 58, 56, 75 ...East, Singapore · Singapore Air Quality Forecast · North, Singapore · 55
  125. [125]
    Vietnam Air Quality Index (AQI) and Air Pollution information | IQAir
    Ho Chi Minh City which is a large city in the south ranked as the cleanest with a US AQI figure of 79. The average annual US AQI figure was 97.Ho Chi Minh City · Air quality in Hanoi · Air quality in Tinh Bac Giang · Da Nang
  126. [126]
    Air Pollution in Vietnam: Real-time Air Quality Index Visual Map
    Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to ...
  127. [127]
    National Environment Protection (Ambient Air Quality) Measure | nepc
    Oct 25, 2022 · The National Environment Protection (Ambient Air Quality) Measure aims to achieve national standards for air quality, protecting human health ...
  128. [128]
    Australia: Air Quality Standards | Transport Policy - TransportPolicy.net
    The policy set national standards for six criteria air pollutants: CO, O3, SO2, NO2, lead, and particulate matter (PM10).
  129. [129]
    Glossary of air quality terms - Environment and Heritage
    Jul 5, 2024 · The AAQ NEPM has set the 24-hour national standard for PM2.5 as 25 µg/m3, defined as a calendar day 24-hour average. Concentrations of PM10 and ...<|separator|>
  130. [130]
    Live air data | Environment, land and water | Queensland Government
    Five colour-coded air quality categories are used, being 'Good' (green), 'Fair' (yellow), 'Poor' (orange), 'Very poor' (red) or 'Extremely poor' (dark red).
  131. [131]
    Air Quality NSW
    Health advice. Air quality categories use 5 colours to show pollution levels. Use the Activity guide to gauge how current air quality impacts your health.Air quality concentration data · Air quality in my area · Air quality data services
  132. [132]
    Approach | Australia state of the environment 2021
    The state and trends of Australia's air quality reported here can be directly compared across years. The AQI takes each pollutant measurement.
  133. [133]
    [PDF] Australia state of the environment 2021: air quality
    Australia generally has good air quality, but events and industries can impact it. PM2.5 levels are above standards in capital cities, and peak ozone levels ...
  134. [134]
    AQI Hub Australia (AQC)
    Methods. Each state in Australia appears to set their own threshold values and averaging periods for the pollutants considered in the air quality categories.<|control11|><|separator|>
  135. [135]
    Ambient fine particulate matter in Latin American cities
    In conclusion, we found that 58% of residents in the Latin American cities examined live in areas that exceed WHO guidelines for PM2.5. We also found ...
  136. [136]
    Dirección de Monitoreo Atmosférico
    Índice de calidad del aire, índice UV e información meteorológica. Aquí encontrarás los reportes más recientes sobre el estado de la calidad del aire, ...Índice UV · Índice AIRE Y SALUD · Índice de calidad del aire · Boletín MeteorológicoMissing: oficial | Show results with:oficial
  137. [137]
    [PDF] NADF-009-AIRE-2017
    Feb 28, 2007 · En la Ciudad de México la metodología para el cálculo del Índice de Calidad del Aire, utiliza las Normas Oficiales. Mexicanas en materia de ...
  138. [138]
    [PDF] GACETA OFICIAL DEL DISTRITO FEDERAL - Sedema
    Nov 3, 2006 · 4.13 Índice Metropolitano de la Calidad del Aire (IMECA). Escala adimensional que sirve para calificar la calidad del aire con respecto a ...
  139. [139]
    Assessing air quality index awareness and use in Mexico City - PMC
    Apr 23, 2018 · Note the increased awareness of IMECA among individuals living in Mexico City (61.4%) compared to the State of Mexico (43.9%).
  140. [140]
    [PDF] HISTORICAL ANALYSIS OF POPULATION HEALTH BENEFITS ...
    Oct 30, 2015 · Mexico City is no longer the most polluted city in the world, not even in the country, ranking now in the position 88 of the World Health.
  141. [141]
    AQI Hub Brazil (IQA)
    A lower IQA value (e.g., 50 or below) suggests clean air with minimal health risks, while values above 300 reflect severe pollution levels that pose serious ...
  142. [142]
    Using Satellite Data for Air Quality and Health Applications in Latin ...
    Developing national air quality modeling systems for Latin America; Conducting trainings and overall capacity building to support the applications of aerosol ...
  143. [143]
    Air and Coastal Water Quality Monitoring - NEA
    Sep 2, 2025 · NEA benchmarks Singapore's air quality against the World Health Organisation Air Quality Guidelines (WHO AQG), while keeping a watching brief on ...
  144. [144]
    Vietnam Air Quality Index (AQI) and Air Pollution information | IQAir
    Ho Chi Minh City which is a large city in the south ranked as the cleanest with a US AQI figure of 79. The average annual US AQI figure was 97. One of the worst ...Air quality in Vietnam · Air quality in Hanoi · Air quality in Tinh Ca Mau · Da Nang
  145. [145]
    Southeast Asian Cities Have Some of the Most Polluted Air in the ...
    Nov 28, 2023 · 37 out of the 40 most polluted cities in the world are located in Southeast Asia, cutting average life expectancy in the region by 1.5 years.
  146. [146]
    South Asian Air Quality Scales: Malaysia and Thailand
    May 2, 2015 · As concerns the scale for Thailand, there is a very clear explaination available on aqmthai.com. And again, just like for Malaysia, the ...
  147. [147]
    Air Sensor Toolbox | US EPA
    Sep 16, 2025 · Comparing sensors and reference monitors to understand the accuracy of the data produced. Explore Air Sensor Collocation. Understanding Sensor ...Air Sensor Guidebook · Sensor Use and Study Design · Sensor Performance and...Missing: reliability | Show results with:reliability
  148. [148]
    Air pollution measurement errors: is your data fit for purpose? - AMT
    Jul 13, 2022 · All measurements suffer from errors, with the degree to which these errors impact the accuracy of the final data often determined by our ability ...
  149. [149]
    Evaluating the Performance of Low-Cost Air Quality Monitors ... - NIH
    In this work, we explore the performance and calibration of 12 commercial low-cost sensors co-located at a regulatory (reference) air quality monitoring site in ...
  150. [150]
    Can data reliability of low-cost sensor devices for indoor air ...
    Oct 1, 2022 · The performance evaluation results showed poor detection of particulates in classrooms by the low-cost devices compared to the reference. The on ...
  151. [151]
    Evaluation of Nine Low-cost-sensor-based Particulate Matter Monitors
    Feb 1, 2020 · This study assessed the performance of nine low-cost PM monitors (AirVisual, Alphasense, APT, Awair, Dylos, Foobot, PurpleAir, Wynd, and Xiaomi)
  152. [152]
    Enhancing accuracy of air quality sensors with machine learning to ...
    Dec 27, 2024 · The study reveals the best-performing ML model for correcting PM2.5 sensor data, enhancing the accuracy of air quality monitoring systems.
  153. [153]
    Discrepancies with AirNow - General - PurpleAir Community
    Aug 7, 2023 · Has anyone looked into discrepancies between AirNow's AQI readings and Purple Air's readings? I have yet to purchase a Purple Air device but ...
  154. [154]
    Investigating Use of Low-Cost Sensors to Increase Accuracy and ...
    Low-cost sensors (LCS) are increasingly being used by the public to fill in the gaps in AQ monitoring; however, LCS are not as accurate as EPA monitors.
  155. [155]
    [PDF] Lung-Association-Cumulative-Impacts-Assessment-Criteria-Air ...
    Dec 17, 2024 · This maximum value single-pollutant AQI paradigm does not capture the cumulative health impacts of co-pollutants or other non-chemical stressors ...
  156. [156]
    Synergistic or Antagonistic Health Effects of Long- and Short-Term ...
    [101] observed that the short-term effects of PM2.5 on health were greater than those of NO2. However, the long-term effects of NO2 were greater than PM2.5.
  157. [157]
    Characterization of multi-pollutant air quality in China using health ...
    Sep 15, 2025 · Our analysis indicates that the AQI underestimates health risks in regions with simultaneous exceedances of multiple pollutants, particularly in ...
  158. [158]
    Characterization of air pollution and associated health risks in ...
    Jun 26, 2024 · The results indicated that AQI system undervalued the comprehensive health risk impact of the six criteria pollutants compared with the other three indices.
  159. [159]
    Health Impacts of Air Pollution - World Health Organization (WHO)
    Whereas long-term or chronic exposure to fine particulate matter increases a person's risk for diseases with a longer onset, like some noncommunicable diseases ...Missing: failure | Show results with:failure
  160. [160]
    Impact of a long‐term air pollution exposure on the case fatality rate ...
    Our results indicate that long‐term exposure to severe air pollution is associated with higher CFR of COVID‐19 patients.
  161. [161]
    The interaction between air pollution, weather conditions, and health ...
    Both weather and air pollution can harm public health. However, the evidence on the synergistic effects of both remains inconclusive. Therefore, the aim of ...Missing: criticisms AQI
  162. [162]
    The Air Quality Index doesn't make any sense - Chris Said
    Jun 19, 2023 · The second thing to know about AQI is that it aggregates levels from different pollutants in an unusual way. There are separate AQIs for PM2.5 ( ...
  163. [163]
    Skepticism about EPA's PM2.5 Rule Is Healthy
    Apr 14, 2023 · The present post discusses the weakness of the EPA's core scientific premise that fine particle pollution kills tens of thousands of Americans every year.
  164. [164]
    Rethinking Air Quality Regulation | Cato Institute
    Jul 15, 2025 · However, since particulate matter was first monitored and regulated there has been considerable disagreement about its actual health effects.
  165. [165]
    Reconsideration of the National Ambient Air Quality Standards for ...
    Mar 6, 2024 · The EPA is revising the primary annual PM 2.5 standard by lowering the level from 12.0 μg/m 3 to 9.0 μg/m 3.
  166. [166]
    [PDF] Low-cost sensors (LCS) for monitoring air quality | EANET
    Monitors (FRMs/FEMs), LCS are smaller, cheaper, and easier to use: $100 to $2500 compared to $20,000+ for a regulatory station. US EPA does not accept sensor ...
  167. [167]
    EPA Research Improves Air Quality Information for the Public on the ...
    Jul 5, 2022 · The AirNow Fire and Smoke Map showing the national network of PurpleAir sensors reporting air quality data. Air sensors, more portable and ...
  168. [168]
    Low-cost sensors can improve air quality monitoring and people's ...
    Jun 13, 2024 · Low-cost sensor systems (LCS) represent a key tool for filling gaps in existing global and local air quality monitoring networks and ...
  169. [169]
    Clarity Approved for EPA's Fire and Smoke Map: A Major Milestone ...
    Jul 23, 2025 · Until now, PurpleAir devices were the only low-cost sensors publicly displayed on the Fire and Smoke Map. Their inclusion in 2020 followed a ...Missing: examples | Show results with:examples
  170. [170]
    [PDF] GAO-24-106393, Air Quality Sensors
    Mar 19, 2024 · Rural communities have used sensors to help fill data gaps between reference monitors, and to advocate for improvements in local air quality.<|separator|>
  171. [171]
    Low-Cost Air Quality Sensors: Biases, Corrections and Challenges ...
    For the purpose of low-cost ambient AQ sensor calibration, RF is used to predict the measurement value from a set of inputs, including the sensor output and ...
  172. [172]
    Challenges and Opportunities in Calibrating Low-Cost ... - NIH
    Jun 5, 2024 · Calibration is challenging for low-cost sensors due to the variability in sensing materials, transducer designs, and environmental conditions.
  173. [173]
  174. [174]
    A predictive study on the indian coastal city of Visakhapatnam
    To predict the AQI, we employed five machine-learning algorithms including LightGBM, Random Forest, Catboost, Adaboost, and XGboost. These models demonstrate ...
  175. [175]
    Prognosis of air quality index and air pollution using machine ...
    Jul 17, 2025 · This study proposes a simplified machine learning approach to predict AQI using only three main pollutants—PM2.5, PM10, and CO—derived from real ...
  176. [176]
    Air Quality Forecasting Using Machine Learning: Comparative ...
    May 14, 2025 · A comprehensive comparison of ten machine learning regression models XGBoost, LightGBM, Random Forest, Gradient Boosting, CatBoost, Support Vector Regression ( ...
  177. [177]
    Predict Air Quality with Machine Learning | Science Project
    In this project, you will collect air quality data from a location of your choice and train three LSTM models to predict AQI one week, four weeks, and one year ...Abstract · Summary · Introduction · Experimental Procedure
  178. [178]
    [PDF] Evaluation of Machine Learning Algorithms for Air Quality Index (AQI ...
    Six machine learning algorithms were evaluated for AQI prediction. Random Forest and Decision Tree achieved 99% accuracy. The study used Python and five years ...
  179. [179]
    Explainable forecasting of air quality index using a hybrid random ...
    Jul 18, 2025 · Two popular algorithms in Machine Learning that are utilized in predicting Air Quality Index (AQI) values effectively are the Random Forest ...
  180. [180]
    Machine learning-driven framework for realtime air quality ... - Nature
    Aug 6, 2025 · Real-time pollutant behaviour and health risks are provided by predictive models that integrate environmental, temporal, and spatial data.
  181. [181]
    Advanced air quality prediction using multimodal data and dynamic ...
    Jul 30, 2025 · Advanced methodologies facilitate the ongoing modeling of temporal air quality variations, enhancing comprehension of spatial interactions, ...
  182. [182]
    AirNet: predictive machine learning model for air quality forecasting ...
    Oct 9, 2024 · The proposed research uses various machine learning models to predict air quality, including Random Forest (100%), Logistic Regression (79%), ...
  183. [183]
    [PDF] Air Quality Prediction Model for Monitoring AQI
    Recent improvements in AQI forecasting represent a shift toward more interpretable and scalable models: Explainable AI (XAI): Incorporating XAI approaches, such ...
  184. [184]
    Air Quality Index (AQI): Historical Origins, Legal Frameworks ...
    Mar 11, 2025 · Air Quality Index (AQI): Historical Origins, Legal ... Introduced by the EPA in the 1970s, AQI has now become a widely used global tool.Missing: 1960s | Show results with:1960s
  185. [185]
    Time to harmonize national ambient air quality standards
    Feb 27, 2017 · We compiled an inventory of ambient air quality standards for 194 countries worldwide for six air pollutants: PM 2.5, PM 10, ozone, nitrogen dioxide, sulphur ...
  186. [186]
    Air quality database - World Health Organization (WHO)
    The WHO Ambient Air Quality Database compiles data on ground measurements of annual mean concentrations of nitrogen dioxide (NO 2 ), particulate matter.
  187. [187]
    Beijing Air Pollution: Real-time Air Quality Index
    Beijing Air Pollution: Real-time Air Quality Index (AQI) ; PM10 AQI. 7, Beijing PM10 (respirable particulate matter) measured by Beijing Environmental Protection ...AQI Scale and Color Legend · 114 Shanghai · Click to view the detailed... · HereMissing: standard | Show results with:standard
  188. [188]
    A New Global Air Quality Health Index Based on the WHO Air ... - NIH
    Oct 23, 2023 · This study developed an Air Quality Health Index (AQHI) based on global scientific evidence and applied it to data from Cape Town, South Africa.Missing: post- | Show results with:post-
  189. [189]
    Air Quality Perceptions, Awareness, and Associated Behaviors ...
    An analysis of survey data from 2016 to 2018 reported that although 54% of respondents were aware of air quality alerts, only 29% reported thinking or were ...
  190. [190]
    What matters in public perception and awareness of air quality ...
    Sep 7, 2020 · This study aims to understand how people perceive air quality apart from the measured levels of airborne pollutants using internet search volume data from ...
  191. [191]
    The Impact of Air Pollution Information on Individuals' Exercise ...
    Sep 10, 2024 · Our results show that individuals exhibit a reduction of running exercise behaviors by about 0.50 km (or 7.5%; P<.001) during instances of ...Missing: wearing | Show results with:wearing
  192. [192]
    Air pollution and defensive expenditures: Evidence from particulate ...
    The daily model shows that a 100-point increase in Air Quality Index (AQI) increases the consumption of all masks by 54.5 percent and anti-PM2.5 masks by 70.6 ...
  193. [193]
    Air quality app influences behavior by linking health to environment
    Jul 15, 2019 · Air quality mobile applications could mitigate these health risks by educating people and promoting preventive behavioral changes, a UCLA study found.
  194. [194]
    Health benefits from risk information of air pollution in China - Nature
    Sep 18, 2023 · The protective behavior led by air pollution risk information reduces 5.7% PM2.5-related premature deaths per year. With a 1% increase in ...
  195. [195]
    Misleading air quality reports lower the public's perception ... - Nature
    Aug 22, 2025 · Media analysis reveals a negative correlation between the accuracy of air pollution reports and the air quality index. Behavioral experiments ...
  196. [196]
    Public engagement with air quality data: using health behaviour ...
    Jun 28, 2022 · We examine the health behaviour theoretical steps linking air quality data with reduced air pollution exposure and (consequently) improved public health.
  197. [197]
    Compliance-Enforcement in Air Quality Management Process - EPA
    Compliance involves actions and programs designed to ensure that environmental laws and regulations are followed.
  198. [198]
    Regulatory and Guidance Information by Topic: Air | US EPA
    May 20, 2025 · The Clean Air Act (CAA) requires all areas of the country to meet or strive to comply with the National Ambient Air Quality Standards (NAAQS).
  199. [199]
    Fact Sheet: EPA's Civil Enforcement Program | US EPA
    Jul 24, 2025 · Breaking the law on purpose may bring criminal enforcement actions, which can result in jail time, fines, and/or restitution by the violator.Missing: AQI | Show results with:AQI
  200. [200]
    Legal enforcement - Environment - European Commission
    The European Commission ensures that all EU countries properly apply EU environmental law and launches infringement procedures when this is not the case.
  201. [201]
    Analysis of the new Air Quality Directive (EU) 2024/2881 - Kunak
    Apr 11, 2025 · The new European air quality regulation, adopted on 23 October 2024, aims to significantly cut air pollution and take a major step towards the ambitious goal ...<|separator|>
  202. [202]
    China Shuts Down Thousands of Factories To Battle Pollution
    Oct 23, 2017 · The Chinese government temporarily shut down tens of thousands of factories in an effort to improve air quality throughout the country.
  203. [203]
    Changing Patterns in China's Environmental Enforcement
    Jun 8, 2023 · In 2019, the Hebei Steel Industry association publicly decried the MEE's use of “sudden stop” shutdowns to temporarily improve air quality.
  204. [204]
    In the midst of an air pollution crisis, there's another way India can ...
    May 6, 2025 · Research in Gujarat documented that over 60% of small industries were in violation of pollution limits, and regulators were selective in ...
  205. [205]
    [PDF] Report on Environmental Compliance and Enforcement in India
    The report recommends more resources, policies for compliance, using self-monitoring as evidence, and developing national guidance on inspector training.
  206. [206]
    Living pollution-free is a 'fundamental right,' India's top court says
    Oct 24, 2024 · Living in a pollution-free environment is a fundamental right, India's Supreme Court said as it urged officials to address deteriorating air ...
  207. [207]
    [PDF] China's Air Pollution Rules: Compliance and Enforcement Lessons ...
    In this Article, we will discuss air pollution reduction efforts through compliance and enforcement of national laws and regulations in one of the world's ...
  208. [208]
    Benefits and Costs of the Clean Air Act 1990-2020, the Second ...
    May 15, 2025 · Our central benefits estimate exceeds costs by a factor of more than 30 to one, and the high benefits estimate exceeds costs by 90 times.
  209. [209]
    [PDF] The Benefits and Costs of US Air Pollution Regulations | NRDC
    As described in further detail below, this analysis finds that the Clean Air Act. Amendments have led to net benefits ranging from $1.9 trillion to $3.8 ...
  210. [210]
    Economic Incentives | US EPA
    Jul 22, 2025 · Economic incentive or market-based policies that rely on market forces to correct for producer and consumer behavior.Hybrid Approaches · Key Considerations · The Nature Of The...Missing: offs | Show results with:offs
  211. [211]
    Health and economic impact of air pollution in the states of India
    The per-capita economic loss due to air pollution in India was $26·5 (19·7–34·3), and varied 5·4 times across the states; this economic loss per capita was ...
  212. [212]
    India's killer smog is piling on the costs to citizens, the economy
    Nov 24, 2024 · Experts say the costs of India's air pollution crisis to its economy is as much as 3 per cent of GDP.<|control11|><|separator|>
  213. [213]
    How is India Trying to Address Air Pollution? - World Bank
    Jun 5, 2024 · Lost output from premature deaths and morbidity attributable to air pollution accounted for economic losses of US$28.8 billion and $8 billion, ...Missing: restrictions | Show results with:restrictions
  214. [214]
    The costs, health and economic impact of air pollution control ...
    Aug 21, 2024 · Nearly 70% of the reviewed studies reported that the economic benefits of implementing air pollution control strategies outweighed the relative costs.
  215. [215]
    Emissions Markets to Reduce Air Pollution
    Jul 9, 2025 · A pilot market in the city of Surat reduced air pollution and was highly cost-effective, with projected health benefits surpassing costs by at least 25 times.
  216. [216]
    [PDF] Air Pollution and Its Impact on Business - Clean Air Fund
    Air pollution diminishes India's strength of being a large consumer economy by reducing consumer spending by 1.3%, costing USD 22 bn. in 2019. As air pollution ...Missing: restrictions | Show results with:restrictions
  217. [217]
    The False Trade-Off Between Economic Growth and Environmental ...
    May 23, 2016 · The World Health Organization's report indicates that public policy and economic choices can lead to higher or lower levels of pollution.