Mobile Measurements of Particulate Matter Concentrations in Urban Area
Adnan Masic,Boran Pikula,Dzevad Bibic +2 more
- pp 0452-0456
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The article was published on 2017-12-18 and is currently open access. It has received 5 citations till now. The article focuses on the topics: Particulates & Urban area.read more
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Vertical Distribution of Particulate Matter and its Relationship with Planetary Boundary Layer Structure in Shenyang, Northeast China
TL;DR: In this article, the authors investigated the characteristics of the vertical distribution of particulate matter (PM1, PM2.5, and PM10) mass concentrations and their relationship with PBL structures in Shenyang, a provincial capital city in Northeast China, using balloon sounding data collected during an intensive observation period in November 2018.
Hotspot identification with portable low-cost particulate matter sensor
Csongor Báthory,Arpad B. Palotas +1 more
TL;DR: In this article, a low-cost particulate matter (PM) sensor and GPS receiver based portable device was developed to determine the atmospheric PM concentration and distribution, hotspots can be identified, the air quality characteristics of crawled areas and routes can be determined.
Journal ArticleDOI
Ultra-Light Airborne Measurement System for Investigation of Urban Boundary Layer Dynamics
TL;DR: In this paper, the performance of an UAV-based measurement system developed for investigation of urban boundary layer dynamics was evaluated by comparing the results of temperature, relative humidity, wind speed and particulate matter fraction with aerodynamic diameter below 10 μm (PM10) concentration vertical profiles obtained using this system with two reference meteorological stations: Jagiellonian University Campus (JUC) and radio transmission tower (RTCN), located in the urban area of Krakow city, Southern Poland.
Journal ArticleDOI
Self-Powered Wireless Sensor Matrix for Air Pollution Detection with a Neural Predictor
TL;DR: This paper presents an approach based on Deep Learning networks, which does not use Bayesian sub-predictors, and shows the applied data feature extraction method, embedded in the proposed algorithm, allows for such feature clustering.
Journal ArticleDOI
The Use of the Novel Optical Method SEZO AM (WiRan Ltd.) for Measurements of Particulate Matter (PM10–2.5) in Port Areas-Case Study for Port of Gdynia (Poland)
TL;DR: In this paper , a comparison of two SEZOAM devices to a higher-class TSI OPS3330 reference in a measurement dust chamber showed a fit between 79% and 86% for the PM2.5 and 80% and 81% for PM10.