Found 10000 publications. Showing page 303 of 400:
2009
2015
NILU has carried out an investigation of contributions from small scale wood burning to PM concentrations in air in cities in Norway. In this project phase 2B the contributions to PM in Trondheim from small scale wood burning have been studied.
There were days with high PM concentrations in Trondheim that winter, up to and above 100 µg/m3 of PM10. On days with probable large contributions from wood burning particles, the PM2,5 and PM10 could be over 50 µg/m3 .
Due to analysis problems with the wood burning tracer component (an unexplained interference peak) the wood burning contribution could not be determined quantitatively.
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2019
2025
2014
PM10/PM2.5 comparison exercise in Oslo, Norway. Study in 2015-2016 and 2018.
The purpose of the comparison was to test for equivalence and establish calibration functions for automatic PM-analysers commonly used in Norway. The reference laboratory performed a field test at three different locations in Oslo during summer and winter conditions in the periods September 2015 to July 2016 and February to March 2018. Participating analysers were Palas Fidas 200, Grimm EDM 180, TEI TEOM 1405 DF, TEI FH 62 I-R, and R&P TEOM 1400AB.
The report proposes a system to carry out ongoing verification of equivalence in the Norwegian monitoring network and how to calibrate analyser data.
NILU
2021
PM2.5 Retrieval Using Aerosol Optical Depth, Meteorological Variables, and Artificial Intelligence
Particulate matter (PM) is one of the major air pollutants that has adverse impacts on human health. The aim of this study is to present an alternative approach for retrieving fine PM (particles with an aerodynamic diameter less than 2.5 μm, PM2.5) using artificial intelligence. Ground-based instruments, including a hand-held Microtops II sun photometer (for aerosol optical depth), a PurpleAir sensor (for PM2.5), and Rotronic sensors (for temperature and relative humidity), are used for the machine learning algorithm training. The retrieved PM2.5 reveals an adequate performance with an error of 0.08 μg m−3 and a Pearson correlation coefficient of 0.84.
2023
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