fugitive dust
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2021 ◽  
Vol 5 (1) ◽  
pp. 15
Author(s):  
Athanasios Triantafyllou ◽  
Ioannis Kapageridis ◽  
Stylianos Gkaras ◽  
Francis Pavloudakis

In surface mines, various activities (e.g., excavations, loading and unloading of material, moving vehicles on unpaved haul roads, etc.) represent significant sources of fugitive dust. The estimation of dust generation from each individual source is a basic step in planning and implementation decision-making systems regarding the air quality of the surrounding area. Typically, this can be obtained by using emission factor or prediction-type equations. A detailed study was carried out at four surface lignite mines to determine PM emission factors and to develop the prediction-type equations of various surface mining activities. In this work, the data, method and results referring to the stacker, one of and the significant fugitive dust emissions source in mining operations are presented and analyzed.


2021 ◽  
pp. 100765
Author(s):  
Katheryn R. Kolesar ◽  
Mark D. Schaaf ◽  
John W. Bannister ◽  
Maarten D. Schreuder ◽  
Mica H. Heilmann

2021 ◽  
Vol 11 (18) ◽  
pp. 8686
Author(s):  
Seungwon Cho ◽  
Muhammad Khan ◽  
Jaeho Pyeon ◽  
Chansik Park

In total, 44.3% of particle matter 10 (PM10) is fugitive dust, and one of the main sources of fugitive dust generation in Korea is construction work (22%). Construction sites account for 84% of the total business places that have reported fugitive dust generation. Currently, the concentration of fine dust at construction sites is being remotely monitored by government inspection agencies through IoT sensors, but it is difficult to trust that appropriate fine dust reduction measures are being taken, because contractors can avoid taking these measures by submitting false reports or photos. In addition, since the fine dust monitoring system under government management is not an open platform and centralized system, residents near construction sites encounter difficulties in accessing information about fine dust. Therefore, in this study, we designed and constructed a blockchain network model to transparently and reliably provide network participants with the information associated with IoT data and fine dust reduction measures. To operate the blockchain network, we designed the chaincode, DApp, and network architecture. In addition, information on fine dust concentration and reduction measure photos were shared with the participants via the blockchain search tool (Hyperledger Explorer). The proposed blockchain network is expected to form a trust protocol among contractors, government inspection agencies, and citizens.


2021 ◽  
Vol 52 ◽  
pp. 100724
Author(s):  
Horacio A. Petit ◽  
Cecilia I. Paulo ◽  
Oscar A. Cabrera ◽  
Edgardo F. Irassar

2021 ◽  
pp. 117521
Author(s):  
Tingkun Li ◽  
Xiaohui Bi ◽  
Qili Dai ◽  
Jianhui Wu ◽  
Yufen Zhang ◽  
...  

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