DatalytIQs Academy

“How Temperature, Humidity, and Pollution Interact in the Global Atmosphere”

Written by

Collins Odhiambo

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Weather is a delicate system of balance where heat, moisture, and particles constantly interact to shape the air we breathe.
Using the Kaggle Global Daily Weather Dataset (2023–2024), we examined how five critical atmospheric variables — temperature, humidity, PM2.5, PM10, and UV index– correlate across global capital cities.
The findings reveal a fascinating picture of interdependence between meteorological and environmental factors and how they define climate experience on a planetary scale.

Correlation Summary

Variable Pair Correlation (r) Relationship Insight
Temperature ↔ Humidity −0.35 Warmer air tends to coincide with lower humidity — characteristic of arid and desert climates.
Temperature ↔ UV Index +0.48 Clearer skies and stronger sunlight raise both UV intensity and surface heat.
Temperature ↔ PM2.5 / PM10 +0.04 / +0.11 Weak links — temperature alone doesn’t drive particulate pollution.
Humidity ↔ PM2.5 / PM10 −0.18 / −0.23 Humid air helps trap or wash out particles, slightly improving air quality.
PM2.5 ↔ PM10 +0.65 Strongly correlated — polluted air contains both fine and coarse particulates.
Humidity ↔ UV Index −0.57 Moisture and cloud cover significantly reduce UV penetration.

Interpretation of Relationships

  1. Heat and Dryness Go Hand in Hand
    The −0.35 correlation confirms that high temperatures often correspond to low humidity — seen across desert belts such as the Arabian Peninsula, North Africa, and Central Asia.

  2. The Sun–Heat Connection
    A +0.48 correlation between temperature and UV index indicates that the clearest skies also bring the highest solar radiation levels — valuable insight for UV risk forecasting and solar power planning.

  3. Humidity as a Natural Filter
    Negative correlations with PM2.5, PM10, and UV show that moist air serves as an atmospheric moderator, suppressing both pollution dispersion and radiation intensity.

  4. Pollution’s Internal Unity
    PM2.5 and PM10 move together (+0.65), signaling shared sources — industrial emissions, construction dust, and vehicle exhaust — a universal pattern in urban air dynamics.

Key Climate Insights

Observation Implication
Hotter regions are generally drier Higher evaporative demand, less precipitation
Humidity suppresses pollution Moisture enables deposition and particle clumping
UV peaks in clear, arid conditions Greater exposure risk in low-humidity zones
PM2.5 and PM10 share origins Air quality interventions must target both simultaneously

Environmental and Policy Implications

  • ☀️ Public Health: Correlations help identify UV-exposure risk zones and regions prone to pollution-induced respiratory illness.

  • 🌱 Urban Sustainability: Insights support smart city air-quality planning and heat-mitigation initiatives (tree planting, cool roofs).

  • ⚡ Energy Strategy: High-UV, low-humidity areas offer ideal solar potential but require adaptation for dust management.

  • 🌡️ Climate Research: Quantitative relationships strengthen predictive climate models linking weather and pollution feedback loops.

Acknowledgment

Dataset Source: Kaggle — Global Daily Weather Data (2023–2024)
Analysis and Visualization: Climate and Environmental Analytics Unit, DatalytIQs Academy (2025)

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