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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
2018
Duration and decay of Arctic stratospheric vortex events in the ECMWF seasonal forecast model
John Wiley & Sons
2018
2018
A complete rethink is needed on how greenhouse gas emissions are quantified for national reporting
Elsevier
2018
2018
2018
2018
Understanding the bioaccumulation mechanisms of per- and polyfluoroalkyl substances (PFASs) across different chain-lengths, isomers and functional groups represents a monumental scientific challenge with implications for chemical regulation. Here, we investigate how the differential tissue distribution and bioaccumulation behavior of 25 PFASs in crucian carp from two field sites impacted by point sources can provide information about the processes governing uptake, distribution and elimination of PFASs. Median tissue/blood ratios (TBRs) were consistently <1 for all PFASs and tissues except bile which displayed a distinct distribution pattern and enrichment of several perfluoroalkyl sulfonic acids. Transformation of concentration data into relative body burdens (RBBs) demonstrated that blood, gonads, and muscle together accounted for >90% of the amount of PFASs in the organism. Principal component analyses of TBRs and RBBs showed that the functional group was a relatively more important predictor of internal distribution than chain-length for PFASs. Whole body bioaccumulation factors (BAFs) for short-chain PFASs deviated from the positive relationship with hydrophobicity observed for longer-chain homologues. Overall, our results suggest that TBR, RBB, and BAF patterns were most consistent with protein binding mechanisms although partitioning to phospholipids may contribute to the accumulation of long-chain PFASs in specific tissues.
2018
Sudden Stratospheric Warmings (SSW) affect the chemistry and dynamics of the middle atmosphere. Major warmings occur roughly every second winter in the Northern Hemisphere (NH), but has only been observed once in the Southern Hemisphere (SH), during the Antarctic winter of 2002. Observations by the Global Ozone Monitoring by Occultation of Stars (GOMOS, an instrument on board Envisat) during this rare event, show a 40% increase of ozone in the nighttime secondary ozone layer at subpolar latitudes compared to non-SSW years. This study investigates the cause of the mesospheric nighttime ozone increase, using the National Center for Atmospheric Research (NCAR) Whole Atmosphere Community Climate Model with specified dynamics (SD-WACCM). The 2002 SH winter was characterized by several reductions of the strength of the polar night jet in the upper stratosphere before the jet reversed completely, marking the onset of the major SSW. At the time of these wind reductions, corresponding episodic increases can be seen in the modelled nighttime secondary ozone layer. This ozone increase is attributed largely to enhanced upwelling and the associated cooling of the altitude region in conjunction with the wind reversal. This is in correspondence to similar studies of SSW induced ozone enhancements in NH. But unlike its NH counterpart, the SH secondary ozone layer appeared to be impacted less by episodic variations in atomic hydrogen. Seasonally decreasing atomic hydrogen plays however a larger role in SH compared to NH.
Elsevier
2018
2018
2018
Atmospheric monitoring and inverse modelling for verification of greenhouse gas inventories
Publications Office of the European Union
2018