SODAR Based Meteorological Sensor Network for Air Pollution Monitoring in Northern India

Abstract

The atmospheric boundary layer (ABL) plays a significant role in defining the air-quality index of an environment. It determines the environmental capacity for the diffusion of atmospheric pollutants. The air-quality in a designated area is influenced by the local air pollution as well as the transported pollutants from remote locations. Estimation of mixing-height helps to determine the volume space in which the emitted pollutants are dispersed. The continuous and effective monitoring of mixing-height in real-time is a major concern for the research community. Sonic Detection and Ranging (sodar) is crucial for real-time and continuous determination of mixing-height. This paper proposes a novel Sodar-based meteorological sensor network (SMSN) with the Internet of Things (IoT) capability. In the SMSN, the temperature, relative humidity, and wind sensors are integrated with sodar and deployed to seven locations in Northern India. The sensors with IoT work as sensor nodes and provide accessibility to users for air-quality monitoring in real-time. The IoT-enabled SMSN displayed impressive standard uncertainty for data packet losses across all the sites and parameters. Additionally, correlation analysis is performed between the SMSN parameters and key air-pollutants of each sensor node. The correlation analysis shows good relevance between the regional parameters and Delhi's parameters. The integration of IoT with sodar and meteorological parameters is important for improving the overall decision-making and planning of Delhi's air quality.

Determining hotspots of gaseous criteria air pollutants in Delhi airshed and its association with stubble burning

“…Since gaseous air pollutants and their association with stubble burning are sparingly explored in literature, the study further investigates the role of stubble burning and meteorological factors (wind direction, air temperature, and planetary boundary height) on the seasonal contribution hotspots for the gaseous pollutants using weighted Concentrated Weighted Trajectory (WCWT) analysis. The study uses Copernicus Atmosphere Monitoring Service (CAMS) global reanalysis product to assess pollutant trajectories from 100 to 1500 m AGL, corresponding to the area’s mixing height 32 . These results are further compared to ground-level data (100 m AGL) for the same period to justify the adoption of a modeled dataset.…”