46 research outputs found

    Global assessment of marine plastic exposure risk for oceanic birds

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    Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species

    Global assessment of marine plastic exposure risk for oceanic birds

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    Plastic pollution is distributed patchily around the world's oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species.B.L.C., C.H., and A.M. were funded by the Cambridge Conservation Initiative’s Collaborative Fund sponsored by the Prince Albert II of Monaco Foundation. E.J.P. was supported by the Natural Environment Research Council C-CLEAR doctoral training programme (Grant no. NE/S007164/1). We are grateful to all those who assisted with the collection and curation of tracking data. Further details are provided in the Supplementary Acknowledgements. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Peer reviewe

    Global assessment of marine plastic exposure risk for oceanic birds

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    Plastic pollution is distributed patchily around the world’s oceans. Likewise, marine organisms that are vulnerable to plastic ingestion or entanglement have uneven distributions. Understanding where wildlife encounters plastic is crucial for targeting research and mitigation. Oceanic seabirds, particularly petrels, frequently ingest plastic, are highly threatened, and cover vast distances during foraging and migration. However, the spatial overlap between petrels and plastics is poorly understood. Here we combine marine plastic density estimates with individual movement data for 7137 birds of 77 petrel species to estimate relative exposure risk. We identify high exposure risk areas in the Mediterranean and Black seas, and the northeast Pacific, northwest Pacific, South Atlantic and southwest Indian oceans. Plastic exposure risk varies greatly among species and populations, and between breeding and non-breeding seasons. Exposure risk is disproportionately high for Threatened species. Outside the Mediterranean and Black seas, exposure risk is highest in the high seas and Exclusive Economic Zones (EEZs) of the USA, Japan, and the UK. Birds generally had higher plastic exposure risk outside the EEZ of the country where they breed. We identify conservation and research priorities, and highlight that international collaboration is key to addressing the impacts of marine plastic on wide-ranging species

    Modellerade kvÀve och svavelnedfall över Europa 1980-2011

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    The Eulerian Transport and Chemistry model MATCH (Robertson et al. 1999) has been used to estimate the deposition over Europe from 1980 to 2011. In data to the model is meteorology from ERA-Interim (Dee et al. 2011) and emissions from EMEP (The European Monitor and Evaluation Programme, http://www.ceip.at/webdeb-emission-database). The MATCH model has been set up with 22 vertical layers and the top height is 6 km. The thickness of the lowest layer is 20 m. Results of the modelled nitrate deposition over Sweden have been published in the IVL-report “Trender i kvĂ€venedfall över Sverige 1955-2011” (Hansen et al. 2013 in Swedish). The available data are modelled gridded data, for the years 1980-2011, of the diurnal mean atmospheric concentrations in the lowest model layer, and dry and wet deposition of: ammonium nitrate (NH4NO3), other nitrate, ammonium sulfate ((NH4)2SO4), other sulfate, NO, NO2, SO2 and ozone (O3). The netcdf-files also includes gridpoint latitude and longitude. A sample of the data are available here for year 1980. The full dataset can be obtained by contacting the Principal investigator. References: Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., 
 Vitart, F. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553–597. https://doi.org/10.1002/qj.828 Robertson, L., Langner, J., & Engardt, M. (1999). An Eulerian Limited-Area Atmospheric Transport Model. Journal of Applied Meteorology, 38(2), 190–210. https://doi.org/10.1175/1520-0450(1999)0382.0.co;2.Den eulerianska transport- och kemimodellen MATCH (Robertson et al. 1999) har anvĂ€nts för att uppskatta avsĂ€ttning över Europa frĂ„n 1980 till 2011. Data omfattar meteorologi frĂ„n ERA-Interim (Dee et al. 2011) och utslĂ€pp frĂ„n EMEP (The European Monitor and Evaluation Programme, http://www.ceip.at/webdeb-emission-database). En MATCH-modell sattes upp med 22 vertikala lager och med en maximal höjd pĂ„ 6 km. Tjockleken pĂ„ det lĂ€gsta lagret Ă€r 20 m. Resultatet frĂ„n modellerat nitratnedfall över Sverige har publicerats i IVL-rapporten “Trender i kvĂ€venedfall över Sverige 1955-2011” (Hansen et al. 2013). Data utgörs av modellerat rutnĂ€t för Ă„ren 1980-2011, för dagliga atmosfĂ€riska medelkoncentrationer i det nedersta modellagret, och torr- samt vĂ„tdeposition av: ammoniumnitrat (NH4NO3), andra nitrater, ammoniumsulfat ((NH4)2SO4), andra sulfater, NO, NO2, SO2 och ozon (O3). FIlerna innehĂ„ller ocksĂ„ longitud/latitud för varje ruta i rutnĂ€ten. HĂ€r tillhandahĂ„lls data för Ă„ret 1980. Hela datasetet kan Ă„terfĂ„s genom att kontakta ansvarig forskare. Referenser: Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., 
 Vitart, F. (2011). The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society, 137(656), 553-597. https://doi.org/10.1002/qj.828 Robertson, L., Langner, J., & Engardt, M. (1999). An Eulerian Limited-Area Atmospheric Transport Model. Journal of Applied Meteorology, 38(2), 190-210. https://doi.org/10.1175/1520-0450(1999)0382.0.co;2

    A regional model for surface ozone in Southeast Asia

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    Underlag för reviderade ASEK-vÀrden för luftföroreningar

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    I Trafikverkets Analysmetod och samhÀllsekonomiska kalkylvÀrden för transportsektorn (ASEK) ingÄr ett antal kalkylvÀrden som anvÀnds i transportsektorns samhÀllsekonomiska analyser för att i sÄdana analyser kunna vÀrdera exempelvis utslÀpp av föroreningar och trafiksÀkerhetsrisker ekonomiskt. Kapitel 11 i version 6.1 av ASEK redovisar de kalkylvÀrden som för nÀrvarande anvÀnds för luftföroreningar förutom vÀxthusgaser (Trafikverket, 2018). Tidigare studier har indikerat att det finns brister med de nuvarande kalkylvÀrdena och att det dÀrför finns ett stort behov av att revidera och komplettera dessa vÀrden. Den hÀr rapporten redovisar resultat frÄn projektet Underlag för reviderade ASEK-vÀrden för luftföroreningar (REVSEK), som med finansiering av Trafikverket genomfördes under 2018-19 i syfte att Ästadkomma ett underlag för reviderade ASEK-vÀrden för luftföroreningar (exklusive vÀxthusgaser) frÄn vÀgtrafiken utifrÄn de senaste vetenskapliga resultaten. För att med en relativt liten budget och pÄ relativt kort tid (elva mÄnader) ta fram ett sÄ bra underlag som möjligt fokuserade projektet pÄ följande forskningsfrÄgor: a. Vilka hÀlsoutfall finns det tillrÀcklig vetenskaplig evidens för, vilka exponering-responsfunktioner bör anvÀndas och för vilken eller vilka luftföroreningskomponenter? b. Vilka Àr skadekostnaderna för de relevanta hÀlsoutfallen enligt (a)? c. Vad Àr befolkningsexponeringen av luftföroreningar enligt (a) och vad Àr en lÀmplig generalisering av denna exponering (t.ex. i form av olika stora tÀtorter)? d. Vad Àr skadekostnaden per kg NOx respektive NH3 till följd av marina övergödningseffekter? e. GÄr det att modellera hur utslÀpp av NOx och VOC ger upphov till marknÀra ozon, sÄ att kostnaderna för ozonets inverkan pÄ vÀxtlighet kan kopplas ihop med utslÀppen? f. Vad Àr skadekostnaden per kg PM10 till följd av nedsmutsning av byggnader?Underlag för reviderade ASEK-vÀrden för luftföroreningar (REVSEK

    Wear particles from road pavements with rubber mixed bitumen : comparison with reference pavement

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    Studded tyre wear of road pavements causes emissions of inhalable particles (PM10). Allowed concentration of PM10 is regulated by an EU directive which is implemented in an environmental quality standard in Sweden. One way of reducing pavement wear particles is to adjust the properties of the road pavement. In the present project the effect on particle emission from mixing milled tyre rubber into the pavement bitumen has been investigated. Tests were made by the VTI road simulator using two pavement constructions containing rubber (GAP11 and GAÖ11) and one reference pavement (ABS11). GAP=GAR (Gap Graded Asphalt Rubber), ABS=SMA (Stone Mastic Asphalt) and GAÖ=OGAR (Open Graded Asphalt Rubber). The concentrations and size distributions of the emitted particles were measured. The results show that GAP11 causes lower PM10 concentrations (in this laboratory environment 20–25%) than the reference pavement ABS11, while the GAÖ11 does not differ from the reference. Size distributions show that PM10 has a bi-modal distribution with two mass maxima at 4–5 and 7–8 ÎŒm. GAP11 decreases the mass size distribution mainly in the finer mode, while GAÖ11 seems to affect mainly the coarser mode. Ultrafine particles are emitted during all tests and have number distribution maxima at around 20–30 nm. These particles are formed in the interaction between tyre studs and pavement and/or tyre rubber. Higher speed generates higher concentrations of ultrafine particles. All in all, the results indicate a lowering effect on PM10 emissions caused by GAP11, while the GAÖ11 does not seem to lower the emissions as compared to the reference pavement ABS11.English translation of VTI notat 8-2011 "Slitagepartiklar frĂ„n vĂ€gbelĂ€ggningar med gummiinblandad bitumen: jĂ€mförelser med referensbelĂ€ggning"</p

    Slitagepartiklar frÄn vÀgbelÀggningar med gummiinblandad bitumen : jÀmförelser med referensbelÀggning

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    DubbdĂ€cksslitage av vĂ€gbelĂ€ggningar orsakar emissioner av inandningsbara partiklar (PM10) vars tillĂ„tna halt i omgivningsluften Ă€r reglerad enligt en miljökvalitetsnorm. Ett sĂ€tt att minska partikelemissionen Ă€r att anpassa belĂ€ggningarnas egenskaper. Föreliggande projekt har undersökt betydelsen för partikelbildningen av inblandning av gummi frĂ„n bildĂ€ck i tvĂ„ belĂ€ggningars bitumenfas. Undersökningen genomfördes i VTI:s provvĂ€gsmaskin dĂ€r tvĂ„ gummiinblandade belĂ€ggningar av olika konstruktion (GAP11 och GAÖ11) och en referensbelĂ€ggning (ABS11) undersöktes. De bildade partiklarnas halter och storleksfördelningar studerades

    A regional model for surface ozone in Southeast Asia

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    As part of the model intercomparison study MICS Asia II, the Swedish MATCH model was set up for Southeast and East Asia. In that study, the comprehensive photochemistry scheme of MATCH was used for the first time in Asia. The current work focuses on results of surface ozone from the MATCH model simulations falling outside the model intercomparison study. Model results of surface ozone concentrations for the entire year of 2001 were investigated and compared with measurements in Southeast Asia. The model produced higher surface ozone concentrations than the observations at all of the non-remote stations investigated but underestimated during the dry season at remote locations. Modelled seasonal variation was similar to, but less pronounced than, the variation in the measurements. This study indicates that NO(x) is the limiting precursor for ozone production in the model, while the fractionation in different species and total amount of non-methane volatile organic compounds (NMVOC) emissions are less important. Naturally emitted NMVOC, isoprene, is an important precursor of surface ozone at certain conditions, and a better inventory of these emissions is needed. Deposition velocities of ozone also have impact on surface concentrations. To improve the model performance, it is important to add a land use inventory with corresponding deposition velocities
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