Air Quality Index Calculation Formula Cpcb

Use this interactive calculator to estimate AQI using the Central Pollution Control Board methodology. Enter pollutant concentrations, compare sub-index values, identify the dominant pollutant, and visualize how each parameter contributes to the final AQI score.

CPCB AQI Formula Calculator

This calculator applies the CPCB breakpoint interpolation method for major pollutants used in India’s National Air Quality Index framework. Fill in concentration values in the appropriate units. The overall AQI is the maximum sub-index among available pollutants.

Expert Guide to the Air Quality Index Calculation Formula CPCB

The phrase air quality index calculation formula cpcb refers to the method used by the Central Pollution Control Board of India to translate pollutant concentration data into a single, understandable air quality score. This score is widely used across Indian cities to communicate whether the air is clean, acceptable, unhealthy, or hazardous to public health. While AQI is often presented as a simple number, the mathematical logic behind it is systematic, policy-driven, and closely tied to health-based breakpoints.

At its core, the CPCB AQI framework works by calculating a sub-index for each pollutant and then selecting the highest of those sub-indices as the overall AQI. This approach reflects the idea that public health risk is governed by the worst relevant pollutant in the air at a given time. If PM2.5 is very high but NO2 and SO2 are moderate, then PM2.5 will dominate the AQI outcome.

What is the CPCB AQI formula?

The CPCB uses a breakpoint interpolation formula. For each pollutant concentration, the measured value is located within a predefined concentration range. That range corresponds to an AQI category interval. The formula then interpolates proportionally within that interval.

AQI sub-index formula: I = [(IHI – ILO) / (BPHI – BPLO)] × (C – BPLO) + ILO, where C is the observed pollutant concentration, BPLO and BPHI are concentration breakpoints, and ILO and IHI are the corresponding AQI breakpoints.

In simple terms, the formula answers this question: if the pollutant concentration falls somewhere between two concentration breakpoints, where should its AQI sub-index fall between the matching AQI breakpoints? The process is linear within each interval.

Why does CPCB use sub-indices instead of one combined pollution average?

A simple arithmetic average of pollutants would hide acute risk. For example, a city could have low SO2 and low NH3, but dangerous PM2.5. If all pollutants were averaged together, the severe fine particulate exposure might appear less serious than it really is. The CPCB framework avoids this problem by assigning each pollutant its own health-linked sub-index and then using the maximum. That makes the AQI more protective, easier to communicate, and better suited to issuing public advisories.

Main pollutants covered in the CPCB AQI framework

• PM2.5 – Fine particles that can penetrate deep into the lungs and even enter the bloodstream.
• PM10 – Coarser inhalable particulate matter, often linked to road dust, construction, and mechanical abrasion.
• NO2 – Nitrogen dioxide, commonly associated with traffic and combustion sources.
• SO2 – Sulfur dioxide, often linked to industrial fuel burning and power generation.
• CO – Carbon monoxide, measured under 8-hour averaging in AQI systems because of its short-term exposure relevance.
• O3 – Ground-level ozone, a secondary pollutant formed in sunlight from precursor emissions.
• NH3 – Ammonia, relevant in agriculture, waste handling, and secondary particulate formation.
• Pb – Lead, included because of toxic health impacts despite relatively lower ambient values in many regions.

How the calculation works step by step

1. Collect measured pollutant concentrations from validated monitoring data.
2. Find the breakpoint interval for each pollutant concentration.
3. Apply the interpolation formula to obtain that pollutant’s sub-index.
4. Repeat for all available pollutants with valid data.
5. Select the highest sub-index as the overall AQI.
6. Assign the matching health category such as Good, Satisfactory, Moderate, Poor, Very Poor, or Severe.

For example, suppose PM2.5 is 86 µg/m³. In the CPCB system, that concentration falls within the Moderate interval for PM2.5, which spans 61 to 90 µg/m³ and maps to AQI 201 to 300. Interpolation places 86 near the upper end of that AQI band. If the resulting PM2.5 sub-index is around 283 and all other pollutants produce lower values, then the final AQI is approximately 283 and the category remains Moderate.

CPCB AQI categories and public meaning

AQI Range	Category	General Interpretation	Public Health Meaning
0 to 50	Good	Minimal pollution load	Little or no risk for the general population.
51 to 100	Satisfactory	Acceptable ambient air quality	Minor breathing discomfort possible for unusually sensitive individuals.
101 to 200	Moderate	Elevated pollution levels	Discomfort possible for people with lung disease, asthma, or heart conditions.
201 to 300	Poor	Unhealthy conditions developing	Breathing discomfort possible for many people on prolonged exposure.
301 to 400	Very Poor	Serious air quality deterioration	Respiratory illness risk increases on prolonged exposure.
401 to 500	Severe	Emergency-level air quality	May affect healthy people and seriously affect those with existing disease.

Real-world concentration breakpoints commonly used for CPCB AQI interpolation

The precise pollutant breakpoints define how concentration is converted into AQI. Below is a practical summary of commonly cited CPCB AQI concentration bands used for calculation in India.

Pollutant	Good	Satisfactory	Moderate	Poor	Very Poor	Severe
PM2.5 (µg/m³)	0 to 30	31 to 60	61 to 90	91 to 120	121 to 250	251+
PM10 (µg/m³)	0 to 50	51 to 100	101 to 250	251 to 350	351 to 430	431+
NO2 (µg/m³)	0 to 40	41 to 80	81 to 180	181 to 280	281 to 400	401+
SO2 (µg/m³)	0 to 40	41 to 80	81 to 380	381 to 800	801 to 1600	1601+
CO (mg/m³)	0 to 1.0	1.1 to 2.0	2.1 to 10	10.1 to 17	17.1 to 34	34.1+
O3 (µg/m³)	0 to 50	51 to 100	101 to 168	169 to 208	209 to 748	749+
NH3 (µg/m³)	0 to 200	201 to 400	401 to 800	801 to 1200	1201 to 1800	1801+
Pb (µg/m³)	0 to 0.5	0.6 to 1.0	1.1 to 2.0	2.1 to 3.0	3.1 to 3.5	3.6+

What do real statistics say about AQI and pollution in India?

Air quality analysis becomes much more useful when tied to actual monitoring trends. According to the CPCB CAAQM dashboard, many large Indian urban centers experience seasonal AQI spikes, especially during winter when lower mixing heights, stagnant winds, local emissions, and transport of pollution combine to elevate particulate levels. PM2.5 and PM10 are frequently the dominant pollutants in northern Indian cities during post-monsoon and winter episodes.

The Ministry of Environment, Forest and Climate Change and affiliated policy publications have repeatedly highlighted the impact of transport, road dust, solid fuel use, industrial sources, and open burning. Academic work from institutions such as IIT Delhi has also emphasized that source contributions can vary by city, season, and meteorology, which is why AQI interpretation should always be paired with local source understanding.

As an illustrative benchmark, winter PM2.5 concentrations in Delhi frequently exceed the Indian National Ambient Air Quality Standard of 60 µg/m³ for 24-hour averages by a large margin. During intense episodes, citywide AQI values may enter the Very Poor or Severe categories. By contrast, coastal or high-wind cities may show lower particulate AQI on many days, though ozone or NO2 can still become relevant under photochemical or traffic-heavy conditions.

Common mistakes people make when calculating AQI

• Using the wrong units. CO is often entered in mg/m³, while most other pollutants are entered in µg/m³.
• Mixing averaging periods. O3 and CO are commonly interpreted on 8-hour exposure basis in AQI calculations, while PM is often based on 24-hour concentrations.
• Averaging pollutants together. CPCB AQI does not use a mean of pollutants; it uses the highest valid sub-index.
• Skipping breakpoint interpolation. A pollutant concentration does not jump to the category ceiling automatically; it is proportionally interpolated inside the category band.
• Ignoring incomplete data quality. AQI should reflect valid monitored values, not rough estimates of missing pollutants unless the method clearly states assumptions.

Why PM2.5 often dominates the AQI result

Fine particulate matter is one of the most health-relevant and persistent air quality concerns in many Indian cities. PM2.5 is small enough to bypass many of the body’s natural respiratory defenses, making it especially important for cardiovascular and pulmonary outcomes. It also tends to reflect multiple source pathways: vehicle exhaust, secondary aerosol formation, residential fuel use, industrial activity, dust resuspension chemistry, and biomass burning. Because concentrations can remain elevated over broad areas, PM2.5 often becomes the dominant sub-index in CPCB AQI calculations.

How to interpret AQI responsibly

The AQI is a communication tool, not a complete atmospheric science report. It simplifies complex environmental data into a single number so that schools, families, hospitals, city administrators, and workers can make faster decisions. However, a responsible interpretation asks additional questions:

• Which pollutant is dominating the AQI today?
• Is the event local, regional, or meteorology-driven?
• Are sensitive groups, such as children, older adults, and people with asthma, at greater immediate risk?
• Are short-term protective actions needed, such as reducing outdoor exertion or improving indoor filtration?

Using this calculator for practical analysis

The calculator above is designed for quick educational and planning use. You can enter measured concentrations for the CPCB pollutants and instantly obtain sub-indices and the dominant pollutant. The chart helps compare all pollutant contributions side by side, making it easier to understand whether your AQI is driven by particles, gases, or a mixed pollution profile.

For researchers, environmental consultants, journalists, and students, this kind of tool is especially useful when explaining why two locations with different pollutant mixes may still display similar AQI categories. For example, one site might be PM-dominated while another is driven by ozone. The final AQI may be similar, but the health messaging and source intervention strategies can differ.

Recommended authoritative sources

• CPCB Continuous Ambient Air Quality Monitoring Dashboard
• Ministry of Environment, Forest and Climate Change, Government of India
• United States Environmental Protection Agency AQI Resource

Final takeaway

Understanding the air quality index calculation formula cpcb is essential if you want to move beyond headline AQI numbers and understand what the air actually contains. The CPCB method is fundamentally a health-based interpolation system. It converts pollutant concentrations into pollutant-specific sub-indices and then uses the highest one as the overall AQI. Once you understand breakpoints, interpolation, and the role of the dominant pollutant, AQI becomes much more transparent and useful for decision-making. Whether you are tracking city pollution trends, comparing monitoring stations, or building educational content, the CPCB AQI framework provides a rigorous and practical basis for air quality interpretation.

Disclaimer: This calculator is intended for educational and informational use. For regulatory reporting, use official monitored data, approved averaging methods, and the latest CPCB guidance.