The application of a multi-channel sensor network to decompose the local and background sources and quantify their contributions. (15th February 2023)

• Record Type: Journal Article
• Authors: Qin, Xiaoliang; Wei, Peng; Ghadikolaei, Meisam Ahmadi; Gali, Nirmal Kumar; Wang, Ya; Ning, Zhi
• Is Part Of: Building and environment. Volume 230(2023)
• Publication Date: 2023-02-15
• Subjects: Construction dust -- Multi-channel sensor network -- Iterative discrete wavelet transform -- Particle size distribution -- Source attribution; Buildings -- Environmental engineering -- Periodicals; Building -- Research -- Periodicals; Constructions -- Technique de l'environnement -- Périodiques; Electronic journals; 696
• DOI: 10.1016/j.buildenv.2023.110005
• Languages: English
• ISSNs: 0360-1323

Abstract

Abstract: The construction site is one of the typical sources of anthropogenic dust and profoundly responsible for generating a high concentration of particles in the surrounding air. To assess the detailed attribution of construction dust to the environment, it is necessary to distinguish the emissions and underlying pollution levels from the measurements. This study demonstrated the feasibility of using multi-channel particulate matter (PM) sensors to measure the concentration of PM in different sizes at a near-source site in real time. A total of five sensors were placed at different locations throughout the construction site for the intensive air quality monitoring from April 12 to April 26, 2021, during the extensive construction activities. Meanwhile, iterative discrete wavelet transform (IDWT) was used to decompose pollutant time series into different components based on low/high frequency filtering. Overall, baseline component was closely related to regional background concentration, showing mild diurnal variation, while the emission component showed a significant increase during working hours from 8:00 to 18:00, especially for coarse particles. The baseline and long-period emission components were mainly from the rapid accumulation of fine particles, but when the particle size was larger than 2.5 μm, the short-period emissions still increased rapidly. The correlation matrix clustering supports the conclusion that the different components were mainly determined by three potential sources. Our results may help to understand the profiles of different-sized PM in construction sites and identify potential source attributions. Highlights: A multi-channel sensor network was developed for different-sized PM monitoring. Baseline and emissions were extracted from high time resolution measurements. Short-period emission was the main source of PM in construction site. Three clusters were identified regarding the PM governed by different generations.