Impact of Environmental Parameters and Aerosol Concentration on Muon Flux Measured at DEASA, Agra

The objective of this study is to look at the impact of environmental parameters and aerosol concentration on muon flux, measured at Agra. The investigation describes how atmospheric conditions-pressure and temperature influence cosmic ray (CR) muons using data collected with portable muon detectors at the Dayalbagh Educational Institute, Agra (27.18° N, 78.01° E). The first dataset was recorded during August-November 2019 (pre-COVID-19), and the second during August-November 2022 (post-COVID-19). The effects of pressure (\((P)\)) and temperature (\((T = t + 273)\)) on cosmic muon flux, a simple correlation between muon flux and \((T/P)\) was derived using the relation: \((I = p_0 + p_1\left(\frac{T}{P}\right))\), where \((p_0)\) represents the baseline flux independent of atmospheric conditions, and \((p_1)\) is the temperature-pressure correlation parameter. The \((T/P)\) corrected muon flux was then correlated with average Air Quality Index (AQI) values for five major pollutants: PM\(({2.5})\), PM\(({10})\), NO\((_2)\), SO\((_2)\), and O\((_3)\). Linear regression analysis between muon flux and AQI-based pollutant data further quantified these relationships. For 2019, the raw data measured an intercept (\((p_0)\)) value varying from 0.62 \((\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) ( for PM10) to 1.33 \((\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\)(ozone). The T/P corrected data measured an intercept (\((p_0)\)) of minimum value 0.63 \((\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) for (PM10) and maximum value 1.36 \((\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) for (ozone). Secondly,the raw data measured slope (\((p_1)\)) with minimum value \((-0.000035 \pm 0.00240\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for PM\(({2.5})\) and maximum value \((0.031021 \pm 0.036383\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for SO\((_2)\) in the same period. The T/P corrected data measured slope (p\((_1)\)) of minimum value \((-0.000028 \pm 0.002456\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for PM\(({2.5})\) and maximum value \((0.031527 \pm 0.037221\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for SO\((_2)\).While in 2022 for the raw data, \((p_0)\) values decreased from \((0.37\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (ozone, SO\((_2)\)) to \((0.47\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) for PM\(({2.5})\). The T/P corrected data measured an intercept (p\((_0)\)) of minimum value 0.028 \((\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) for NO\((_2)\) and maximum value 0.48 \((\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) for PM\(({2.5})\). The raw data measured slope (\((p_1)\)) with minimum value \((-0.000217 \pm 0.000129\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for All AQI and maximum value \((0.023499 \pm 0.018200\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for SO\((_2)\) . The T/P corrected data measured slope (p\((_1)\)) of minimum value \((-0.00216 \pm 0.000120\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for All AQI and maximum value \((0.021636 \pm 0.017006\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) for SO\((_2)\).The 2022 \((T/P)\) corrected slopes showed consistently negative trends for PM\(({2.5})\) comes out to be \((-0.000512 \pm 0.00027\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)) and PM\(({10})\) value is \((-0.000337 \pm 0.00017\mathrm{min^{-1}\,cm^{-2}\,sr^{-1}})\) (\((\mu)\)g/m\((^3)\)), confirming a clear inverse dependence of muon intensity on particulate concentration. O\((_3)\) showed a weak positive slope, while NO\((_2)\) and SO\((_2)\) exhibited minor positive correlations due to their reactive atmospheric behaviour.These findings emphasize the necessity of accurate atmospheric corrections in cosmic ray studies and enhance our understanding of how environmental factors influence muon flux variations. The results also have implications for temperature inversion studies, urban air pollution dynamics, climate change projections, and sustainable land-use planning.