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2021
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The who, why and where of Norway's CO
We present emissions from Norway’s tourist travel by the available transport modes, i.e., aviation, maritime (ferries and cruises) and land-based transport (road and railways). Our study includes detailed information on both domestic and international tourist travel within, from and to Norway. We have coupled statistics from several large surveys with detailed emission data to allow us to separate the purpose of the travel (holiday or business).
Total transport emissions for tourists in 2018 were estimated to be 8 530 kt, equivalent to 19% of the reported Norwegian national emissions. Of these emissions, international tourists visiting Norway were responsible for 3 273 kt , whereas travel by Norwegians accounted for 4 875 kt , most of which occur outside Norway’s reporting obligations. Aviation and maritime transport were found to be the largest emission sources, responsible for 71% and 21% of total emissions, respectively. The reduction due to the COVID-19 pandemic was approximately 60% in 2020, and was sustained throughout the year.
Our study shows that officially reported emissions, as limited to the countries territory, are not suitable for accurate evaluation of transport emissions related to tourism. A consumer or tourist-based calculation gives a marked redistribution of emission responsibility. Our results indicate that emissions from Norwegian residents travelling abroad are 1 602 kt higher than those from tourists coming to Norway. This is driven by frequent trips to popular tourist destinations such as Spain, Thailand, Turkey and Greece. Globally consumer based calculations would shift the responsibility of emissions by tourists to the large wealthy nations, with the most international tourists. The understanding of emission distributed by population group or market support in addition the developing of marketing strategies to attract low emission tourist markets and create awareness among the nations with higher shares of international tourist.
Elsevier
2021
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Beregning av luftkvalitet ved Bjørnheimveien 26
Prem Partners II A/S has commissioned NILU to evaluate the extent of air quality zones for the present situation concerning a possible new residential building in Bjørnheimveien 26. A Gaussian dispersion model for line sources has been applied (Hiway-2). The road E6 is in this area running over a bridge. If the elevation of E6 and the terrain around Bjørnheimveien is considered, the calculations show a significant reduction in the extend of red and yellow air quality zones at ground level. The effect of shielding existing houses from air pollution by the new building is marginal. The calculations show agreement with the current air quality map for the area when the default assumption of flat terrain is applied.
NILU
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Dimethyl Sulfide-Induced Increase in Cloud Condensation Nuclei in the Arctic Atmosphere
American Geophysical Union (AGU)
2021
Monitoring of long-range transported air pollutants in Norway. Annual Report 2020.
Denne rapporten omhandler resultater fra overvåkningsprogrammet for langtransportert forurenset luft og nedbør og atmosfæriske tilførsler i 2020. Rapporten presenterer målinger av uorganiske hovedkomponentene i luft og nedbør, partikulært karbonholdig materiale, partikkelmasse og bakkenært ozon. Forurensningsnivået i 2020 var generelt lavt noe som delvis kan forklares med spesielle værforhold de første månedene med hovedsakelig ren, marin luft fra vest. De omfattende restriksjonene på menneskelig aktivitet i forbindelse med pandemien i Europa, har trolig også bidratt til lavere nivåer av luftforurensninger på de norske bakgrunnsstasjonene. I 2020 ble det observert en uvanlig omfattende episode med høye konsentrasjoner av luftforurensing på alle stasjoner.
NILU
2021
Introducing a nested multimedia fate and transport model for organic contaminants (NEM)
Some organic contaminants, including the persistent organic pollutants (POPs), have achieved global distribution through long range atmospheric transport (LRAT). Regulatory efforts, monitoring programs and modelling studies address the LRAT of POPs on national, continental (e.g. Europe) and/or global scales. Whereas national and continental-scale models require estimates of the input of globally dispersed chemicals from outside of the model domain, existing global-scale models either have relatively coarse spatial resolution or are so computationally demanding that it limits their usefulness. Here we introduce the Nested Exposure Model (NEM), which is a multimedia fate and transport model that is global in scale yet can achieve high spatial resolution of a user-defined target region without huge computational demands. Evaluating NEM by comparing model predictions for PCB-153 in air with measurements at nine long-term monitoring sites of the European Monitoring and Evaluation Programme (EMEP) reveals that nested simulations at a resolution of 1° × 1° yield results within a factor of 1.5 of observations at sites in northern Europe. At this resolution, the model attributes more than 90% of the atmospheric burden within any of the grid cells containing an EMEP site to advective atmospheric transport from elsewhere. Deteriorating model performance with decreasing resolution (15° × 15°, 5° × 5° and 1° × 1°), manifested by overestimation of concentrations across most of northern Europe by more than a factor of 3, illustrates the effect of numerical diffusion. Finally, we apply the model to demonstrate how the choice of spatial resolution affect predictions of atmospheric deposition to the Baltic Sea. While we envisage that NEM may be used for a wide range of applications in the future, further evaluation will be required to delineate the boundaries of applicability towards chemicals with divergent fate properties as well as in environmental media other than air.
Royal Society of Chemistry (RSC)
2021
Modeling study of the impact of SO2 volcanic passive emissions on the tropospheric sulfur budget
Well constrained volcanic emissions inventories in chemistry transport models are necessary to study the impacts induced by these sources on the tropospheric sulfur composition and on sulfur species concentrations and depositions at the surface. In this paper, the changes induced by the update of the volcanic sulfur emissions inventory are studied using the global chemistry transport model MOCAGE (MOdèle de Chimie Atmosphérique à Grande Échelle). Unlike the previous inventory (Andres and Kasgnoc, 1998), the updated one (Carn et al., 2016, 2017) uses more accurate information and includes contributions from both passive degassing and eruptive emissions. Eruptions are provided as daily total amounts of sulfur dioxide (SO2) emitted by volcanoes in the Carn et al. (2016, 2017) inventories, and degassing emissions are provided as annual averages with the related mean annual uncertainties of those emissions by volcano. Information on plume altitudes is also available and has been used in the model. We chose to analyze the year 2013, for which only a negligible amount of eruptive volcanic SO2 emissions is reported, allowing us to focus the study on the impact of passive degassing emissions on the tropospheric sulfur budget. An evaluation against the Ozone Monitoring Instrument (OMI) SO2 total column and MODIS (Moderate-Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) observations shows the improvements of the model results with the updated inventory. Because the global volcanic SO2 flux changes from 13 Tg yr−1 in Andres and Kasgnoc (1998) to 23.6 Tg yr−1 in Carn et al. (2016, 2017), significant differences appear in the global sulfur budget, mainly in the free troposphere and in the tropics. Even though volcanic SO2 emissions represent 15 % of the total annual sulfur emissions, the volcanic contribution to the tropospheric sulfate aerosol burden is 25 %, which is due to the higher altitude of emissions from volcanoes. Moreover, a sensitivity study on passive degassing emissions, using the annual uncertainties of emissions per volcano, also confirmed the nonlinear link between tropospheric sulfur species content with respect to volcanic SO2 emissions. This study highlights the need for accurate estimates of volcanic sources in chemistry transport models in order to properly simulate tropospheric sulfur species.
2021
The increased availability of commercially-available low-cost air quality sensors combined with increased interest in their use by citizen scientists, community groups, and professionals is resulting in rapid adoption, despite data quality concerns. We have characterized three out-the-box PM sensor systems under different environmental conditions, using field colocation against reference equipment. The sensor systems integrate Plantower 5003, Sensirion SPS30 and Alphasense OCP-N3 PM sensors. The first two use photometry as a measuring technique, while the third one is an optical particle counter. For the performance evaluation, we co-located 3 units of each manufacturer and compared the results against optical (FIDAS) and gravimetric (KFG) methods for a period of 7 weeks (28 August to 19 October 2020). During the period from 2nd and 5th October, unusually high PM concentrations were observed due to a long-range transport episode. The results show that the highest correlations between the sensor systems and the optical reference are observed for PM1, with coefficients of determination above 0.9, followed by PM2.5. All the sensor units struggle to correctly measure PM10, and the coefficients of determination vary between 0.45 and 0.64. This behavior is also corroborated when using the gravimetric method, where correlations are significantly higher for PM2.5 than for PM10, especially for the sensor systems based on photometry. During the long range transport event the performance of the photometric sensors was heavily affected, and PM10 was largely underestimated. The sensor systems evaluated in this study had good agreement with the reference instrumentation for PM1 and PM2.5; however, they struggled to correctly measure PM10. The sensors also showed a decrease in accuracy when the ambient size distribution was different from the one for which the manufacturer had calibrated the sensor, and during weather conditions with high relative humidity. When interpreting and communicating air quality data measured using low-cost sensor systems, it is important to consider such limitations in order not to risk misinterpretation of the resulting data.
MDPI
2021
Black Carbon Emission Reduction Due to COVID-19 Lockdown in China
American Geophysical Union (AGU)
2021