CICERO Research Archive (CICERO Senter for klimaforskning)
Not a member yet
    1083 research outputs found

    PT Sarana Multi Infrastruktur (PTSMI)

    No full text
    Category: Second Opinion, Sector: Development, Issuer type: Financial Institution, Shading: Medium GreenpublishedVersio

    Hva sier spesialrapporten om 1,5 °C om lavutslippsomstilling for Oslo?

    Get PDF
    Klimaetaten i Oslo kommune har gitt CICERO Senter for klimaforskning i oppdrag å sammenstille resultater og funn fra klimapanelets spesialrapport om 1,5 °C som kan være særlig relevant for Oslo kommunes klimaarbeid. Et av hovedfunnene fra spesialrapporten er at for å begrense oppvarmingen til 1,5 °C, må klimagassutslippene reduseres med 40-50% innen 2030 sammenlignet med 2010-nivå, og være «netto-null» innen 2050, altså at det fjernes like mye CO2 fra atmosfæren som det slippes ut. Oslo kommune kan spille en viktig rolle i arbeidet med å begrense global oppvarming. Rapporten diskuterer bl.a. omstilling til et lavutslippssamfunn, styring og organisering, transport, karbonfangst og –lagring, byggeaktivitet og infrastruktur, bioenergi og indirekte utslipppublishedVersio

    Agricultural Development Bank of China (ADBC)

    No full text
    Category: Second Opinion, Sector: Banking, Issuer type: Financial Institution, Shading: Dark GreenpublishedVersio

    GRACE model and applications

    Get PDF
    This report is a documentation of the GRACE model. GRACE is a computable general equilibrium model aimed at supporting studies of the global consequences of human activities that affect the drivers of climate change. The model is comprehensive, in the sense that is comprises all economic activities in the world, as expressed by national accounts data, and links greenhouse gas emissions and impacts of climate change to these economic activities. It explains human responses to changes in socioeconomic drivers, policies and impacts of climate change by means of economic theories of production and consumption, and derive the socioeconomic consequences from the impacts on prices in market equilibrium. The comprehensiveness combined with the modelling of individual behaviour makes GRACE a tool for integrating knowledge from research with different perspectives and help derive dependencies between countries, sectors and scales. The report gives examples on how important these dependencies are for evaluations of climate policies and challenges related to the future impacts of climate change

    SYK Univeristy Properties of Finland

    No full text
    Category: Second Opinion, Sector: Real Estate, Issuer type: Corporate, Shading: Medium GreenpublishedVersio

    Landshypotek bank

    Get PDF
    Category: Second Opinion, Sector: Banking, Issuer type: Financial Institution, Shading: Dark GreenpublishedVersio

    Inferring Surface Albedo Prediction Error Linked to Forest Structure at High Latitudes

    Get PDF
    Predicting the surface albedo of a forest of a given species composition or plant functional type is complicated by the wide range of structural attributes it may display. Accurate characterizations of forest structure are therefore essential to reducing the uncertainty of albedo predictions in forests, particularly in the presence of snow. At present, forest albedo parameterizations remain a nonnegligible source of uncertainty in climate models, and the magnitude attributable to insufficient characterization of forest structure remains unclear. Here we employ a forest classification scheme based on the assimilation of Fennoscandic (i.e., Norway, Sweden, and Finland) national forest inventory data to quantify the magnitude of the albedo prediction error attributable to poor characterizations of forest structure. For a spatial domain spanning ~611,000 km2 of boreal forest, we find a mean absolute wintertime (December–March) albedo prediction error of 0.02, corresponding to a mean absolute radiative forcing ~0.4 W/m2. Further, we evaluate the implication of excluding albedo trajectories linked to structural transitions in forests during transient simulations of anthropogenic land use/land cover change. We find that, for an intensively managed forestry region in southeastern Norway, neglecting structural transitions over the next quarter century results in a foregone (undetected) radiatively equivalent impact of ~178 Mt‐CO2‐eq. year−1 on average during this period—a magnitude that is roughly comparable to the annual greenhouse gas emissions of a country such as The Netherlands. Our results affirm the importance of improving the characterization of forest structure when simulating surface albedo and associated climate effects.publishedVersio

    Landsea Properties

    No full text
    Category: Second Opinion, Sector: Real Estate, Issuer type: Corporate, Shading: Medium GreenpublishedVersio

    Potensial og barrierer for kommunale klimatiltak

    Get PDF
    I denne rapporten har vi sett på potensial og barrierer for lokale klimatiltak der vi har lagt til grunn at Norge fram mot 2050 må redusere sine klimagassutslipp med 80-90% for å bli et såkalt lavutslippssamfunn. Skal Norge klare disse utslippsmålene vil det kreve at vi både får ned det relative utslippet per enhet (for eksempel per kjørte kilometer), og at vi reduserer omfanget av utslippsintensive aktiviteter der full erstatning med energinøytrale energikilder ikke er mulig. Dette innebærer omstilling. Rapporten viser at kommunene kan ha en vesentlig rolle å spille i et arbeid med omstilling til lavutslippssamfunnet. De kan utløse mange tiltak gjennom virkemidlene de har til rådighet.publishedVersio

    Fastpartner

    Get PDF
    Category: Second Opinion, Sector: Real Estate, Issuer type: Corporate, Shading: Medium GreenpublishedVersio

    918

    full texts

    1,083

    metadata records
    Updated in last 30 days.
    CICERO Research Archive (CICERO Senter for klimaforskning)
    Access Repository Dashboard
    Do you manage Open Research Online? Become a CORE Member to access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard! 👇