Air quality and health impacts in Nepal’s urban valley: PM_2.5 pollution patterns and public health risks

The Kathmandu Valley exemplifies how monsoon climate dynamics create deceptive pollution patterns that mask persistent public health threats. Seasonal PM_2.5 variability suggests that the monsoon "relief" pollution, but even the cleanest periods pose severe health risks. We analyzed 1,710 daily PM_2.5 observations spanning 2020-2024 using machine learning and advanced statistical methods, developing predictive models, identifying meteorological thresholds, and assessing health risks across Nepal's five distinct seasons. PM_2.5 measurements were obtained using a BAM-1020 Beta Attenuation Monitor with rigorous quality control procedures ensuring 97.3 % data completeness. Extreme seasonal variability was observed, ranging from 51.5 ± 30.5 μg/m³ during the monsoon to 146.7 ± 27.3 μg/m³ in winter; however, across all seasons, the values were 3.4-9.8 times higher. Temperature exhibited the strongest PM_2.5 control (r = -0.710, p < 0.001), while Random Forest models achieved superior prediction accuracy (R² = 0.941, RMSE = 12.04 μg/m³, MAPE = 10.3 %) compared to linear regression (R² = 0.572) following systematic hyperparameter optimization across 18 parameter combinations using 5-fold cross validation (CV R² = 0.933 ± 0.017). Critical meteorological thresholds were identified: rainfall exceeding 15.9 mm/day and wind speed exceeding 5.8 m/s reduce pollution, but not sufficiently for safety. Concentrations show a systematic annual increase of 6.7 μg/m³ (p < 0.001), with all vulnerable populations facing year-round health risks (hazard quotients >1), and people with asthma experiencing the highest risks (HQ = 4.4 in winter). Multi-year patterns demonstrate that monsoon washing effects, while substantial, cannot compensate for extreme baseline pollution levels, revealing the urgent need for emission controls that transcend seasonal pollution management approaches.