Smoke detectors face the challenges of increasing accuracy, sensitivity, and high reliability in complex use environments to ensure the timeliness, accuracy, and reliability of very early fire detection. The improvement in and innovation of the principle and algorithm of smoke particle concentration detection provide an opportunity for the performance improvement in the detector. This study is a new refinement of the smoke concentration detection principle based on capacitive detection of cell structures, and detection signals are processed by a multiscale smoke particle concentration detection algorithm to calculate particle concentration. Through experiments, it is found that the detector provides effective detection of smoke particle concentrations ranging from 0 to 10% obs/m; moreover, the detector can detect smoke particles at parts per million (PPM) concentration levels (at 2 and 5 PPM), and the accuracy of the detector can reach at least the 0.5 PPM level. Furthermore, the detector can detect smoke particle concentrations at better than 1 PPM accuracy even in an environment with 6% obs/m oil gas particles, 7% obs/m large dust interference particles, or 8% obs/m small dust interference particles.
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http://dx.doi.org/10.3390/s24051692 | DOI Listing |
Environ Pollut
January 2025
Pollution Prevention Unit, Spanish Ministry for the Ecological Transition, Madrid, Spain; Institute of Environmental Assessment and Water Research - Spanish Research Council (IDAEA-CSIC), Barcelona, Spain.
Changes in climate and land-use have significantly increased both the frequency and intensity of wildland fires globally, exacerbating the potential for hazardous impacts on human health. A better understanding of particle exposure concentrations and scenarios is crucial for developing mitigation strategies to reduce the health risks. Here, PM and black carbon (BC) concentrations were monitored during wildland fires between 2022-2024, in fire-prone areas in Catalonia (NE Spain), by means of personal monitors (AirBeam2 and Micro-aethalometers AE51 and MA200).
View Article and Find Full Text PDFMaterials (Basel)
December 2024
School of Materials Science and Engineering, Hainan University, Haikou 570228, China.
The use of traditional sealing materials in buildings poses a significant risk of fire and noise pollution. To address these issues, we propose a novel composite functional sealant designed to enhance fire safety and sound insulation. The sealant incorporates a unique four-component filler system consisting of carbon nanotubes (CNTs) decorated with layered double hydroxides (LDHs), ammonium dihydrogen phosphate (ADP), and artificial marble waste powder (AMWP), namely CLAA.
View Article and Find Full Text PDFJ Dent Res
January 2025
Oral and Maxillofacial Diseases, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Missing teeth have been linked to incident cardiovascular disease, diabetes, and all-cause mortality. Our previous study revealed that signs of oral infections and inflammatory conditions (i.e.
View Article and Find Full Text PDFSci Rep
December 2024
Division of Pulmonary and Critical Care, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095-1690, USA.
Electronic cigarettes (e-cigs) fundamentally differ from tobacco cigarettes in their generation of liquid-based aerosols. Investigating how e-cig aerosols behave when inhaled into the dynamic environment of the lung is important for understanding vaping-related exposure and toxicity. A ventilated artificial lung model was developed to replicate the ventilatory and environmental features of the human lung and study their impact on the characteristics of inhaled e-cig aerosols from simulated vaping scenarios.
View Article and Find Full Text PDFPLoS One
December 2024
Group of Atmospheric Optics (GOA-UVa), Universidad de Valladolid, Valladolid, Spain.
This work introduces CAECENET, a new system capable of automatically retrieving columnar and vertically-resolved aerosol properties running the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) algorithm using sun-sky photometer (aerosol optical depth, AOD; and sky radiance measurements) and ceilometer (range corrected signal; RCS) data as input. This method, so called GRASPpac, is implemented in CAECENET, which assimilates sun-sky photometers data from CÆLIS database and ceilometer data from ICENET database (Iberian Ceilometer Network). CAECENET allows for continuous and near-real-time monitoring of both vertical and columnar aerosol properties.
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