Air and Water Quality - Case Studies
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Kurnool, a major city in Andhra Pradesh, faces growing air pollution due to rapid urbanization, industrial expansion, and increasing vehicle emissions, which release pollutants like Nitrogen Dioxides (NO2), Sulphur Dioxide (SO2), Ozone (O3), and Particulate Matter (PM2. and PM ). Additionally, construction activities, contribute to worsening air quality. This issue not only affects public health but also impacts the environment and overall quality of life. Air quality in cities varies based on factors such as industrialization levels, population density, and meteorological conditions. Artifici...
Kurnool, a major city in Andhra Pradesh, faces growing air pollution due to rapid urbanization, industrial expansion, and increasing vehicle emissions, which release pollutants like Nitrogen Dioxides (NO2), Sulphur Dioxide (SO2), Ozone (O3), and Particulate Matter (PM2. and PM ). Additionally, construction activities, contribute to worsening air quality. This issue not only affects public health but also impacts the environment and overall quality of life. Air quality in cities varies based on factors such as industrialization levels, population density, and meteorological conditions. Artificial intelligence models have been widely used for the prediction of air pollutants, especially ANN (Artificial Neural Networks) and ANFIS (Adaptive Neuro-Fuzzy Inference Systems). These models have proven to be suitable for the prediction of air pollutants, especially in cities where there are monitoring networks to measure the pollutant concentrations and the meteorological variables. Air pollution poses significant risks to public health and the environment, with pollutants like NO2, SO2, O3, PM2.5 and PM10 being key contributors to respiratory and cardiovascular diseases.
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