Delhi Air Quality & Weather Analysis 2025: Key Pollution Trends, Hotspots, and Meteorological Insights

By abhishek.verma75000 · July 1, 2026

Air pollution patterns across Delhi were analyzed using a full year of 2025 environmental and weather data, uncovering important trends in AQI,…

Across 6 locations, pollutant levels vary significantly. Two bar charts were generated — one comparing PM2.5, PM10, and NO2 side by side, and another focusing on CO levels (which operates on a much larger scale). IGI Airport leads in particulate matter and NO2, while Anand Vihar has the highest CO concentration. Rohini is the cleanest location based on PM2.5 levels.

The analysis successfully produced visualizations showing how AQI and PM2.5 levels vary across different hours of the day in Delhi (2025). Two charts were generated: a line chart showing average AQI by hour and a bar chart showing average PM2.5 levels by hour, giving a comprehensive picture of daily pollution patterns.

The analysis identified the locations with the highest average AQI that require urgent intervention. IGI Airport, Dwarka, and Okhla Phase III are the most critical, all sharing an average AQI of 380.3 with a staggering peak of 2742. Anand Vihar and Connaught Place follow with an average AQI of 194.5. Two bar charts and supporting data tables were generated to visualize these findings.

Clear, calm weather conditions are overwhelmingly associated with hazardous AQI readings above 500. Out of 6,903 total hazardous readings, nearly 70% occurred under 'Clear sky' conditions, which is a striking finding — it suggests that poor air quality at these extreme levels is not driven by stormy or wet weather, but rather by stagnant, clear atmospheric conditions that trap pollutants. Two bar charts and scatter plots were generated to visualize these patterns.

The chart shows how average daily AQI has trended across the city throughout 2025. The light blue line shows daily fluctuations, while the red 7-day rolling average smooths out the noise to reveal the underlying seasonal pattern. Overall, the city averaged an AQI of 287 for the year, starting at 201 in January and ending at 209 in December — a modest increase of 8 points.

Three visualizations and data tables were generated showing how windspeed, humidity, and temperature relate to AQI and PM2.5 levels. Overall, temperature has the strongest influence on PM2.5, while humidity has the strongest link to AQI. Higher windspeed tends to disperse pollutants, slightly reducing PM2.5. Pollution is generally worse at lower temperatures, consistent with winter smog patterns, and tends to rise with higher humidity.

A full correlation matrix was computed across all 9 weather and pollution variables for Delhi 2025, and visualized as an annotated heatmap. The heatmap uses a red-blue color scale to clearly show the strength and direction of relationships between every variable pair. The strongest positive correlation is between AQI Index and PM10 (0.831), confirming that particulate matter is the primary driver of air quality levels. The strongest negative correlation is between temperature and pressure (-0.717), a well-known meteorological relationship. Among weather factors, humidity and windspeed show the most notable relationships with AQI — lower windspeed tends to trap pollutants while higher humidity can influence particulate concentration.

The dual-axis line chart shows how atmospheric pressure, humidity, and AQI evolved month-over-month across 2025. Pressure ranged from a low of 974.06 mb in July to a high of 991.24 mb in December, following a typical seasonal pattern. Humidity peaked in August at 82.26%, aligning with monsoon conditions. AQI was worst in May (582.76) and best in September (123.89), suggesting that pre-monsoon heat and stagnation drive poor air quality, while monsoon rains in September help clear pollutants.

Two histograms with KDE curves were generated for temperature and wind speed across all Delhi locations. Temperature (mean 25.02°C, median 26.50°C, std 7.62°C) follows an approximately symmetric, near-normal distribution with no extreme outliers detected by the IQR method. Wind speed (mean 6.57 kph, median 6.00 kph, std 3.48°C) is right-skewed, meaning most readings cluster at lower speeds with a tail of higher values — 650 data points (1.24%) were flagged as outliers, with the highest reaching 27.1 kph.

The analysis successfully broke down air quality metrics across all unique weather conditions. Two bar charts were generated: one showing average AQI per weather condition (ranked from most to least polluted using a red color scale), and a grouped bar chart comparing mean PM2.5, NO2, and windspeed across each condition type. Data tables were also produced with full details per condition category.