First measurements of ambient aerosol over an ecologically sensitive zone in Central India: Relationships between PM2.5 mass, its optical properties, and meteorology.

PM2.5 mass and its optical properties were measured over an ecologically sensitive zone in Central India between January and December, 2012. Meteorological parameters including temperature, relative humidity, wind speed, wind direction, and barometric pressure were also monitored. During the study period, the PM2.5 (fine PM) concentration ranged between 3.2μgm(-3) and 193.9μgm(-3) with a median concentration of 31.4μgm(-3). The attenuation coefficients, βATN at 370nm, 550nm, and 880nm had median values of 104.5Mm(-1), 79.2Mm(-1), and 59.8Mm(-1), respectively. Further, the dry scattering coefficient, βSCAT at 550nm had a median value of 17.1Mm(-1) while the absorption coefficient βABS at 550nm had a median value of 61.2Mm(-1). The relationship between fine PM mass and attenuation coefficients showed pronounced seasonality. Scattering, absorption, and attenuation coefficient at different wavelengths were all well correlated with fine PM mass only during the post-monsoon season (October, November, and December). The highest correlation (r(2)=0.81) was between fine PM mass and βSCAT at 550nm during post-monsoon season. During this season, the mass scattering efficiency (σSCAT) was 1.44m(2)g(-1). Thus, monitoring optical properties all year round, as a surrogate for fine PM mass was found unsuitable for the study location. In order to assess the relationships between fine PM mass and its optical properties and meteorological parameters, multiple linear regression (MLR) models were fitted for each season, with fine PM mass as the dependent variable. Such a model fitted for the post-monsoon season explained over 88% of the variability in fine PM mass. However, the MLR models were able to explain only 31 and 32% of the variability in fine PM during pre-monsoon (March, April, and May) and monsoon (June, July, August, and September) seasons, respectively. During the winter (January and February) season, the MLR model explained 54% of the PM2.5 variability.