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SODAR Based Meteorological Sensor Network for Air Pollution Monitoring in Northern India
MAPAN ( IF 1 ) Pub Date : 2022-05-23 , DOI: 10.1007/s12647-022-00569-y
Parag Chourey , Nirbhow Jap Singh , Kirti Soni , Ravinder Agarwal

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.



中文翻译:

基于 SODAR 的印度北部空气污染监测气象传感器网络

大气边界层 (ABL) 在定义环境的空气质量指数方面发挥着重要作用。它决定了大气污染物扩散的环境容量。指定区域的空气质量受到当地空气污染以及从偏远地区输送的污染物的影响。混合高度的估计有助于确定排放污染物分散的体积空间。实时连续有效地监测混合高度是研究界关注的主要问题。声波探测和测距(声波雷达)对于实时和连续确定混合高度至关重要。本文提出了一种具有物联网 (IoT) 功能的新型基于 Sodar 的气象传感器网络 (SMSN)。在 SMSN 中,温度、相对湿度、和风传感器与声雷达集成并部署到印度北部的七个地点。带有物联网的传感器作为传感器节点工作,并为用户提供实时空气质量监测的可访问性。支持物联网的 SMSN 在所有站点和参数中显示出令人印象深刻的数据包丢失标准不确定性。此外,还对每个传感器节点的 SMSN 参数和关键空气污染物进行了相关性分析。相关性分析表明区域参数与德里的参数之间具有良好的相关性。物联网与声雷达和气象参数的集成对于改善德里空气质量的整体决策和规划非常重要。带有物联网的传感器作为传感器节点工作,并为用户提供实时空气质量监测的可访问性。支持物联网的 SMSN 在所有站点和参数中显示出令人印象深刻的数据包丢失标准不确定性。此外,还对每个传感器节点的 SMSN 参数和关键空气污染物进行了相关性分析。相关性分析表明区域参数与德里的参数之间具有良好的相关性。物联网与声雷达和气象参数的集成对于改善德里空气质量的整体决策和规划非常重要。带有物联网的传感器作为传感器节点工作,并为用户提供实时空气质量监测的可访问性。支持物联网的 SMSN 在所有站点和参数中显示出令人印象深刻的数据包丢失标准不确定性。此外,还对每个传感器节点的 SMSN 参数和关键空气污染物进行了相关性分析。相关性分析表明区域参数与德里的参数之间具有良好的相关性。物联网与声雷达和气象参数的集成对于改善德里空气质量的整体决策和规划非常重要。对每个传感器节点的 SMSN 参数和关键空气污染物进行相关性分析。相关性分析表明区域参数与德里的参数之间具有良好的相关性。物联网与声雷达和气象参数的集成对于改善德里空气质量的整体决策和规划非常重要。对每个传感器节点的 SMSN 参数和关键空气污染物进行相关性分析。相关性分析表明区域参数与德里的参数之间具有良好的相关性。物联网与声雷达和气象参数的集成对于改善德里空气质量的整体决策和规划非常重要。

更新日期:2022-05-24
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