Found 9941 publications. Showing page 277 of 398:
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2018
Model development for high-resolution emissions from residential wood combustion
In this report, we describe the MetVed model developed to estimate emissions from residential wood combustion (RWC) at high spatial-temporal resolution. The model uses a downscaling method approach, which builds on bottom-up principles and derive a wood burning potential for each grid based on the housing type, size and heating technology, energy demand and outdoor temperature of each grid. The model builds on the combination of several databases with information at high level of detail. The databases contain geo-localised information about dwelling number and type, energy consumption statistics, fireplace and stove locations, and the available technology for residential heating. The datasets are combined and the dependencies between the different variables are analysed. MetVed includes the time variation for RWC based on the heating degree concept combined with time-variation from consumer statistics, and the vertical distribution based on the RWC shared in apartment buildings versus houses. The results from the MetVed-model have shown to improve the accuracy of dispersion modelling results when compared with predictions based on previous emission inventories.
NILU
2018
In this study we apply two methods for data collection that are relatively new in the field of atmospheric science. The two developed methods are designed to collect essential geo-localized information to be used as input data for a high resolution emission inventory for residential wood combustion (RWC). The first method is a webcrawler that extracts openly online available real estate data in a systematic way, and thereafter structures them for analysis. The webcrawler reads online Norwegian real estate advertisements and it collects the geo-position of the dwellings. Dwellings are classified according to the type (e.g., apartment, detached house) they belong to and the heating systems they are equipped with. The second method is a model trained for image recognition and classification based on machine learning techniques. The images from the real estate advertisements are collected and processed to identify wood burning installations, which are automatically classified according to the three classes used in official statistics, i.e., open fireplaces, stoves produced before 1998 and stoves produced after 1998. The model recognizes and classifies the wood appliances with a precision of 81%, 85% and 91% for open fireplaces, old stoves and new stoves, respectively. Emission factors are heavily dependent on technology and this information is therefore essential for determining accurate emissions. The collected data are compared with existing information from the statistical register at county and national level in Norway. The comparison shows good agreement for the proportion of residential heating systems between the webcrawled data and the official statistics. The high resolution and level of detail of the extracted data show the value of open data to improve emission inventories. With the increased amount and availability of data, the techniques presented here add significant value to emission accuracy and potential applications should also be considered across all emission sectors.
2018
Altitude-temporal behaviour of atmospheric ozone, temperature and wind velocity observed at Svalbard
Elsevier
2018
Duration and decay of Arctic stratospheric vortex events in the ECMWF seasonal forecast model
John Wiley & Sons
2018
2018
CO2-rensing Klemetsrud. Beregning av nitros- og nitraminer.
Beregning av spredning og dannelse av nitros- og nitramin er gjennomført for et potensielt aminbasert CO2-fangst-anlegg på Klemetsrud. Det er utført beregninger for tre ulike aminer. Beregningene viser makismal utslippskonsentrasjon for de ulike aminene for å sikre overholdelse av anbefalte grenseverdier for nitros- og nitraminer i luft og vann. Høyeste utslippskonsentrasjon som ikke gir overskridelser av grenseverdiene, er mellom 1,1 ppmV og 11 ppmV avhengig av hvilket amin som benyttes.
NILU
2018