Assessment of Relationship Between Meteorological Parameters and Air Quality Index of Kota, Rajasthan, India

Meteorological parameters extremely influence the air quality of metropolitan cities worldwide. This study analyses the impact of meteorological variables on the quality of air for the Kota metropolis of Rajasthan (India) from 2018 to 2021 for four years. Wind speed and direction, relative humidity, precipitation, and temperature are the meteorological parameters selected to statistically determine the effect of meteorological variables on the AQI (air quality index). The AQIs are evaluated through PM 10 , PM 2.5 , NO 2 , and SO 2 . The average concentration of PM 10 was 122.59 ± 44.11 µg/m 3 , PM 2.5 was 56.83 ± 24.89 µg/m 3 , NO 2 was 24.91 ± 4.99 µg/m 3 , and SO 2 was 7.39 ± 1.38 µg/m 3 during the observation period. The average temperature varied between 18-38 °C in 2018, 15.7-34.8 °C in 2019, 15.5-35.1 °C in 2020, and 16.8-32.4 °C. Total rainfall in 2018, 2019, 2020, and 2021 was 685 mm, 1637 mm, 514 mm, and 1338 mm, respectively. The average wind speed in the city were 1.39, 1.30, 1.26, and 1.22 m/s in 2018, 2019, 2020, and 2021, respectively. The relative humidity ranged from 17-78 % in 2018, 22-84 % in 2019, 40-90 % in 2020, and 24-82 % in 2021. The annual average AQI of Kota was 139, 118, 101, and 142 in 2018, 2019, 2020, and 2021, respectively. There is a statistically significant correlation between temperature and AQI (p<0.05), rainfall and AQI (p<0.05), and wind speed and AQI (p<0.05), which show a significant impact on the air quality of the Kota metropolis. At the same time, there is a statistically insignificant correlation between relative humidity and AQI (p>0.05), which shows an insignificant impact on air quality. The formulated equation for predicting AQI through meteorological parameters has wide scope utility in air pollution management and control


Introduction
The presence of air pollutants in the ambient air is a versatile global issue in metropolitan areas due to its adverse effects on the environment and humans. 1,2[17][18][19][20] Oxides of sulphur and nitrogen are the principal cause of acid rain.Acid fog and clouds with very low pH levels damage the fauna on the earth's surface. 9,21The plant's ability to extract soil nutrition is seriously decreased due to acidification.Sulphates, nitrogen oxides, and dust are responsible for visibility impairment.[24] The primary layer near to the ground level of Earth is the planetary boundary layer (PBL), and this layer exchange heat, moisture, and momentum with the earth's surface.The atmospheric stability significantly affects the dispersion of air pollutants in this layer. 36][27][28][29][30] These conditions (stable weather) close to the ground surface inhibited air pollutants' vertical diffusion.In contrast, an unstable atmosphere is associated with abundant precipitation and stronger winds when the pollution decreases.Unstable conditions of weather near the ground surface encouraged air pollutants' vertical diffusion. 3,4,317][38][39] These meteorological parameters significantly affect the air pollutant dispersion process and removal mechanisms. 40,41Rainfall is an additional factor that removes gaseous pollution and particulate matter deposition through the atmospheric chemical processes. 25,26,42,43veral studies worldwide indicate the potential influence of meteorological variables on the quality of ambient air.The present study determines the impact of meteorological variables on AQI during observation period of four years (2018-2021) for the Kota metropolis.Wind speed and direction, relative humidity, precipitation, and temperature are the meteorological variables selected to determine the impact of meteorological factors on the AQI.The parameters chosen for evaluating the AQI are PM 10 , NO 2 , PM 2.5 , and SO 2 , and the CPCB prescribed method is used to determine AQI.Past studies on the Kota metropolis did not quantify the effect of meteorological parameters on the city. 44,45Hence, a prediction model has been developed using multiple regression analysis with a confidence level of 95%.This study may be beneficial for stakeholders and policymakers to consider the effect of meteorological factors on the ambient air of Kota city to make new policies and rules to curb air pollution.

Study Area and Research Methodology
The rapid and fast-growing city of Rajasthan, Kota, has been chosen to study the effects of meteorological variables on the quality of ambient air in the city.It is situated on the banks of the Chambal river and comes under the category of smart cities. Rapid urbanisation, vigorous population growth, unplanned development, increased vehicles, dynamic construction and demolition work, and lack of awareness among people had several detrimental impacts on the city's air quality. 22,45The air quality of Kota city is determined through the CPCB method of air quality index (AQI) with the help of four pollutants, namely, PM 10 , PM 2.5 , SO 2 , and NO 2 .Meteorological parameters selected for the study are wind speed and direction, relative humidity, precipitation, and temperature.The correlation study with the significance level between each meteorological parameter and AQI is performed separately.A multiple regression analysis based AQI prediction model is also formulated using temperature, wind speed, and relative humidity through M.S. Excel software.The meteorological and air parameters data are collected for four years (2018-2021) from different government agencies such as CPCB and RSPCB.The study area is shown in Figure 1, and the GPS coordinates of the selected air monitor locations are tabulated in Table 1.
Where, BP HI = Higher breakpoint concentration of pollutant, BP LO = Lower breakpoint concentration of pollutant, I HI = AQI corresponding to BP HI , I LO = AQI corresponding to BP LO , and P C = concentration of air pollutants.
The maximum operator system is used to obtain the subindex of each pollutant, as shown in equation 2.
used when independent variables are greater than one (1), and the general equation for this method is as follows. 37 Where C is the regression constant, and X is the regression coefficient.The determination coefficient (R 2 ) analysis has been done to define its predictive ability (goodness).The value of R 2 varies between 0 to 1.The accuracy of predicted values derived from the regression line is measured through standard error.The t-statistic test (CI:95%) and one-way ANOVA test (α=5%) have been used as the test of significance.

Observed Data
The observation period for the study is four years, from 2018 to 2021.Total rainfall and average temperature with standard deviation are tabulated in Table 3, while Table 4 and Table 5 exhibit average relative humidity and wind speed, respectively.The highest, lowest and average concentrations of pollutants, along with standard deviation, are shown in Table 6 for each air quality monitoring site in Kota during the observation of four years.The variation in the monthly average concentrations of PM 10 , PM 2.5 , NO 2 , and SO 2 are shown in Figure 2.

Multiple Linear Regression Analysis
The stepwise multiple linear regression method is employed to determine the relationship between the selected variables of this study.This method is   The concentration of each parameter goes down in the rainy season due to precipitation in the southwest monsoon season.The highest concentrations of air quality parameters were observed in Winter, followed by Summer and Rainy seasons, except in 2020, as the lockdown restriction prevails this year.This variation in the concentration of air quality parameters majorly depends on the meteorological parameters in these seasons.
The stable atmospheric conditions prevail in the winters, while unstable atmospheric conditions in the summers and rainy seasons. 44,45The difference between stable and unstable conditions in Kota may be understood with the help of Table 7 Note: Data is unavailable for air quality monitoring station S AQ6 (Sewage Treatment Plant, Balita) for 2020 and 2021.The obtained AQI values suggest that AQI varies continuously from month to month, season to season, year to year, and station to station.The lowest values of AQI levels for each monitoring site were obtained in the rainy season, followed by the summer and winter seasons.The reason was temperature, rainfall, relative humidity, and wind speed because AQI is based on pollutant concentration, and pollutant concentration is considerably affected by meteorological conditions. 31,43,46The AQI varies between 73-297 in 2018, 36-335 in 2019, 38-267 in 2020, and 49-339 in 2021.Another factor that reduced AQI values in 2020 was the lockdown restriction due to Covid-19.

Meteorological Parameters Affecting Air Quality
The air quality of a particular location varies tremendously daily, even at constant daily emissions due to meteorological parameters.The air quality of a region is significantly affected by these above-mentioned meteorological parameters.The relationship between AQI and Meteorological variables are shown in Figure 4.The coefficient of correlation between rainfall and air quality index (AQI) was -0.42 [significance level (P) < 5%], which confirms a negative correlation between rainfall and air quality index (AQI), i.e., as the amount of precipitation increases, the air quality of the city gets improves or vice versa.The effect of rainfall on air quality is shown in Figure 5.

Conclusion
This study concludes that PM 10 and PM 2.5 are the main reasons behind the continuous deterioration in the city's air quality, as both continuously violated the Indian standards prescribed by the CPCB.The annual average concentrations of NO 2 and SO 2 were well under the prescribed Indian limits and couldn't be considered air pollutants.The highest AQIs were observed in Winter, followed by summer and rainy seasons, except in 2020, as the lockdown restriction prevails this year.This variation in the concentration of air quality parameters majorly depends on the meteorological parameters in these seasons.The lowest AQI values show the low concentration of air pollutants in ambient air throughout the rainy season as high temperature, intense wind speed, and wind direction work together to increase the dispersion of air pollutants in the atmosphere, while rainfall acts as the cleansing agent to wash out air pollutants from the atmosphere.This study attempts to statistically analyse the meteorological variable's impact on the air quality index of Kota city.A negative correlation was found between AQI and Temperature, AQI and Rainfall, AQI and relative humidity, and AQI and wind speed.
The developed AQI prediction model is advantageous for stakeholders and researchers in the air pollution field.However, anthropogenic activities significantly affect meteorological activities and, ultimately, the accumulation of air pollutants near the ground surface, causing increased air pollution scenarios in Kota city.It may be used as the baseline study to help policymakers and stakeholders make rules, regulations and management/prevention plans for different aspects of air pollution in the city.

Fig. 1 :
Fig. 1: Positions of air quality monitoring stations in the study area (Kota).

Fig. 3 :
Fig. 3: Variation in the air quality index for Kota city during the study period.

Fig. 5 :Fig. 6 :
Fig. 5: Effect of rainfall and temperature on air quality during the study period.

Results and Discussion Variability in the concentration of PM 10 , PM 2.5 , NO 2 , and SO 2
The annual average concentration of PM 10 was 153 ± 32 µg/m 3 , 119 ± 40 µg/m 3 , 97 ± 23 µg/m 3 , The PM 2.5 concentration range was 14-119 µg/m 3 in 2018, 17-165 µg/m 3 in 2019, 19-110 µg/m 3 in 2020, and 27-170 µg/m 3 in 2021.The annual permissible limits for PM 10 and PM 2.5 are 60 and 40, respectively, as per CPCB guidelines.PM 10 and PM 2.5 are the main reasons behind the continuous deterioration in the city's air quality, as both were continuously violating the Indian standards prescribed by the CPCB.Vehicular emissions, construction, and demolition works, power plant emissions, cement plant, stone cutting industries, open burning, stubble burning, and natural dust, significantly contribute to particulate matter pollution in the city.

Table 7 : Variations in relative humidity, temperature, wind speed, and rainfall for Winter, Summer, and Rainy seasons.
.

Table 8 : Evaluated AQI Values for all ambient air quality monitoring stations.
air quality parameters, one of which should be PM 10 or PM 2.5 .A sub-index is calculated for these pollutants depending upon their measured concentration in the ambient atmosphere.AQI values on a monthly and seasonal basis for each monitoring location for 2018, 2019, 2020, and 2021 are shown in Table8 and Table 9, respectively.The variation in the air quality index from 2018 to 2021 is graphically shown in Figure3.

Table 9 : Stationwise Air Quality Index for Air Monitoring Stations, Kota (India) on seasonal and annual basis.
value) is 0.632, i.e., 63.2% of the total variations in AQI are determined through the linear relationship between AQI and meteorological parameters.The significance level (α) for all meteorological parameters was ≤ 0.05, which validates the significant relationship between AQI and selected meteorological variables.This equation holds good for wind speed ≥ 1.2 m/s.This equation does not consider rainfall as it only occurs in the monsoon period.