AQI Calculator


Calculate Air Quality Index.


Given pollutants as input to the Machine Learning model, predict the Air Quality Index.
The kNN model is trained on 4 stations in Gurugram on 147K rows that has 83.5% accuracy (R-Squared).

Calculate AQI now.

Concentration in µg/m3 (except for CO)
PM2.5 NO

NO2 NOx

SO2 CO


Note: If you do not have value for any field, input it as 0.

AQI Scale

AQI Associated Health Impacts
0-50 (Good) Minimal Impact
51-100 (Satisfactory) May cause minor breathing discomfort to sensitive people
101-200 (Moderate) May cause breathing discomfort to people with lung diseases (such as asthma) and discomfort to people with heart diseases, children, and older adults
201-300 (Poor) May cause breathing discomfort to people on prolonged exposure and discomfort to people with heart disease with short exposure
301-400 (Very Poor) May cause respiratory illness in people on prolonged exposure. The effect may be more pronounced in people with lung and heart diseases
401-500 (Severe) May cause respiratory effects even on healthy people and serious health impacts on people with lung/heart diseases. The health impacts may be experienced even during light physical activity

Gurugram - Historical Daily AQI

FAQs

The Air Quality Index (AQI) is a numerical scale used to communicate the quality of air in a specific location. It takes into account various air pollutants, such as
  • Particulate matter (PM2.5 and PM10)
  • Nitrogen dioxide (NO2)
  • Sulfur Dioxide (SO2)
  • Carbon Monoxide (CO)
  • Ozone (O3)
to provide an overall assessment of air quality.

  • In India, the AQI is measured based on the concentrations of major air pollutants.
  • Each pollutant is assigned an individual Air Quality Index
  • The overall AQI is determined by the highest index value among them
  • The AQI is categorized into different levels, ranging from "Good" to "Severe" indicating the potential health impacts associated with the air quality.

  • Limit outdoor activities, especially strenuous ones.
  • Use N95 masks to reduce inhalation of pollutants.
  • Keep windows and doors closed.
  • Plant good quality indoor trees.
  • Use air purifiers indoors.
  • Stay informed about air quality levels and take necessary precautions.

  • The AQI for your area can be checked through various sources, including government websites, mobile apps, and online platforms. Many cities in India have dedicated air quality monitoring stations, and their data is often accessible in real-time.
  • However, if you are in Gurugram, you can check the AQI and the next 5 day's forecast at the top of this page.

Government initiatives may include
  • Implementing stricter emission standards
  • Promoting public transportation
  • Encouraging the use of cleaner energy sources
  • Imposing regulations on industries contributing to air pollution
Additionally, awareness campaigns and citizen participation are crucial components of improving air quality.

  • Individuals can contribute by using public transportation.
  • Reducing the use of personal vehicles, minimizing the use of fossil fuels, planting trees.
  • Participating in community initiatives to raise awareness about air quality issues.
These FAQs provide a basic understanding of the Air Quality Index and its relevance in the context of India. It's important to stay informed and take necessary actions to protect personal and public health during varying air quality conditions.

Indoor plants can help improve air quality by absorbing pollutants and releasing oxygen. Here are some indoor plants known for their air-purifying qualities:
  • Spider Plant (Chlorophytum comosum): Effective in removing pollutants like formaldehyde and xylene. Easy to care for and adapts well to different conditions.
  • Snake Plant (Sansevieria trifasciata): Known for its ability to filter out formaldehyde, benzene, and other pollutants. Requires minimal light and water.
  • Peace Lily (Spathiphyllum spp.): Excellent in removing common indoor pollutants, including ammonia and benzene. Adds a touch of elegance to indoor spaces.
  • Aloe Vera (Aloe barbadensis miller): Known for its ability to clear formaldehyde and benzene. Requires bright, indirect sunlight.
  • Boston Fern (Nephrolepis exaltata): Effective in removing pollutants like formaldehyde and xylene. Thrives in high humidity and indirect light.
  • Rubber Plant (Ficus elastica): Removes pollutants such as formaldehyde. Tolerant of low light conditions.
  • Areca Palm (Dypsis lutescens): Effective in removing formaldehyde, benzene, and trichloroethylene. Adds a tropical touch to indoor spaces.
  • Dracaena (Dracaena spp.): Different varieties (e.g., Dracaena marginata, Dracaena reflexa) are effective in removing pollutants. Adaptable to different light conditions.
  • Bamboo Palm (Chamaedorea seifrizii): Excellent in removing benzene and trichloroethylene. Well-suited for indoor environments.
  • Golden Pothos (Epipremnum aureum): Known for its air-purifying abilities, particularly in removing formaldehyde. Low-maintenance and can thrive in various light conditions.
Remember that while indoor plants can contribute to improved air quality, they are not a substitute for proper ventilation and addressing the root causes of indoor air pollution. Regularly ventilate your living space, minimize the use of synthetic materials, and keep the area clean to create a healthier indoor environment.

Forecast AQI now.


Want to know AQI forecast? Then, checkout my another project
AirCast - https://AirCastAQI.netlify.app/

Architecture & more...

AQI Calculator

  • The Story:
    • After learning the concepts of ML, writing blogs/posts, hustling on Kaggle,
    • I wanted to build my first end-to-end project that too with a good team & environment.
    • So, I joined Omdena & started this project.
    • Here, I learned the skills first, then did the project.
  • Input & Output: Given pollutants as input to the Machine Learning model, predict the Air Quality Index.
  • Collaborated with Omdena, worked with people across the globe, and led a team of 5 people in Data Collection, Exploratory Data Analysis, Model Training & Project Documentation.
  • Algorithm: k Nearest Neighbors (k = 5)
  • Data collected from: CPCB
  • Dataset type & frequency: Hourly Time Series data with target column as AQI
  • Dataset size: 147531 rows x 31 columns
  • Model metrics:
    • R-Squared: 0.835
    • Mean Absolute Error (MAE): 30.75
  • Timelines: March 2023 - May 2023
  • Tech stack: Python, Pandas, Scikit-learn, Matplotlib, Seaborn, Plotly, Flask
  • Certificate