Predictive Statistical Models For Meteorological Parameters And Average Environmental Temperature

Abstract

The objective of this study is to examine the influence of temperature variability on air pollution levels in an urban environment. Seasonal variation causes temperature shifts, which subsequently affect meteorological parameters such as wind speed, humidity, and air pressure—factors that are considered temperature-dependent. Using data collected over the past eight years for each month from January to December in the city of Kathmandu, Nepal, we have established and analyzed the relationship between these meteorological factors and average temperature. Linear and power models and correlation analyses were applied to analyze the statistical relationship among them.