CICERO Research Archive (CICERO Senter for klimaforskning)
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Kan utlån i butikker få folk til å kjøpe mindre? Erfaringer fra forsøk med utlån av verktøy i Jernias butikker i Tromsø og Drammen
Get PDFRapporten dokumenterer resultater fra en utprøving av en ordning der jernvarebutikker i Tromsø og Drammen har lånt ut verktøy til forbrukere. I dette forsøket har kundene kunnet benytte bibliotekenes lånekort for å identifisere seg og registrere lånet i butikken. Denne rapporten presenterer noen sentrale erfaringer fra piloten, basert på en surveyundersøkelse av de som har lånt utstyr i Jernias butikker, supplert med dybdeintervjuer med noen av disse. Hovedfokus for rapporten er brukernes egne
erfaringer med ordningen. Undersøkelsene viser at brukerne har hatt gode erfaringer med sine lån, og at ordningen inspirerte flere til å låne og dele mer i fremtiden.
Gjennom ordningen har lånerne også lært å bruke ulike verktøy og utstyr, og fått erfaringer med å låne direkte i butikkene som kan forlenge levetiden til gjenstander de allerede eier. Studien gir ikke indikasjoner på at ordningen medfører økt forbruk, ved at informanter prøver ut utstyr som senere kjøpes inn. Integrasjonen av bibliotekenes lånekort i kjøpene ble imidlertid forhindret av tekniske og praktiske problemer, og en alternativ registreringsmetode ble derfor først og fremst benyttet
The Emissions Model Intercomparison Project (Emissions-MIP): Quantifying model sensitivity to emission characteristics
Get PDFAnthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth–atmosphere system, alter the formation of clouds and precipitation, and have a substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO2 injection, seasonality of SO2 and black carbon (BC) particulate emissions, and the assumed fraction of SO2 emissions that is injected into the atmosphere as particulate phase sulfate (SO4) in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find large variation in atmospheric lifetime across models for SO2, SO4, and BC, with a particularly large relative variation for SO2, which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of −0.35 W m−2), SO2 lifetime over Northern Hemisphere land (maximum difference of 0.8 d), surface SO2 concentration (up to 59 % decrease), and surface sulfate concentration (up to 23 % increase). Emitting SO2 at height consistently increased SO2 and SO4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to ensure that anthropogenic emission injection height and SO4 emission fraction are accurately and consistently represented in global models.The Emissions Model Intercomparison Project (Emissions-MIP): Quantifying model sensitivity to emission characteristicspublishedVersio
Air pollution impacts on in-hospital case-fatality rate of ischemic stroke patients
Get PDFBackground: A growing body of evidence suggests that air pollution exposure is associated with an increased risk for cardiovascular diseases. Data regarding the impact of long-term air pollution exposure on ischemic stroke mortality are sparse. Methods: The German nationwide inpatient sample was used to analyse all cases of hospitalized patients with ischemic stroke in Germany 2015–2019, which were stratified according to their residency. Data of the German Federal Environmental Agency regarding average values of air pollutants were assessed from 2015 to 2019 at district-level. Data were combined and the impact of different air pollution parameters on in-hospital case-fatality was analyzed. Results: Overall, 1,505,496 hospitalizations of patients with ischemic stroke (47.7% females; 67.4 % ≥70 years old) were counted in Germany 2015–2019, of whom 8.2 % died during hospitalization. When comparing patients with residency in federal districts with high vs. low long-term air pollution, enhanced levels of benzene (OR 1.082 [95%CI 1.034–1.132],P = 0.001), ozone (O3, OR 1.123 [95%CI 1.070–1.178],P 8 % independent of residence area-type and area use (OR 1.518 [95%CI 1.012–2.278],P = 0.044). Conclusion: Elevated long-term air pollution levels in residential areas in Germany, notably of benzene, O3, NO, SO2, and PM2.5, were associated with increased stroke mortality of patients. Research in context: Evidence before this study: Besides typical, established risk factors, increasing evidence suggests that air pollution is an important and growing risk factor for stroke events, estimated to be responsible for approximately 14 % of all stroke-associated deaths. However, real-world data regarding the impact of long-term exposure to air pollution on stroke mortality are sparse. Added value of this study:The present study demonstrates that the long-term exposure to the air pollutants benzene, O3, NO, SO2 and PM2.5 are independently associated with increased case-fatality of hospitalized patients with ischemic stroke in Germany.publishedVersio
A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)
Get PDFTropical forest dynamics play a crucial role in the global carbon, water, and energy cycles. However, realistically simulating the dynamics of competition and coexistence between different plant functional types (PFTs) in tropical forests remains a significant challenge. This study aims to improve the modeling of PFT coexistence in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vegetation demography model implemented in the Energy Exascale Earth System Model (E3SM) land model (ELM), ELM-FATES. Specifically, we explore (1) whether plant trait relationships established from field measurements can constrain ELM-FATES simulations and (2) whether machine learning (ML)-based surrogate models can emulate the complex ELM-FATES model and optimize parameter selections to improve PFT coexistence modeling. We conducted three ensembles of ELM-FATES experiments at a tropical forest site near Manaus, Brazil. By comparing the ensemble experiments without (Exp-CTR) and with (Exp-OBS) consideration of observed trait relationships, we found that accounting for these relationships slightly improves the simulations of water, energy, and carbon variables when compared to observations but degrades the simulation of PFT coexistence. Using ML-based surrogate models trained on Exp-CTR, we optimized the trait parameters in ELM-FATES and conducted another ensemble of experiments (Exp-ML) with these optimized parameters. The proportion of PFT coexistence experiments significantly increased from 21 % in Exp-CTR to 73 % in Exp-ML. After filtering the experiments that allow for PFT coexistence to agree with observations (within 15 % tolerance), 33 % of the Exp-ML experiments were retained, which is a significant improvement compared to the 1.4 % in Exp-CTR. Exp-ML also accurately reproduces the annual means and seasonal variations in water, energy, and carbon fluxes and the field inventory of aboveground biomass. This study represents a reproducible method that utilizes machine learning to identify parameter values that improve model fidelity against observations and PFT coexistence in vegetation demography models for diverse ecosystems. Our study also suggests the need for new mechanisms to enhance the robust simulation of coexisting plants in ELM-FATES and has significant implications for modeling the response and feedbacks of ecosystem dynamics to climate change.publishedVersio
The Regional Aerosol Model Intercomparison Project (RAMIP)
Get PDFChanges in anthropogenic aerosol emissions have strongly contributed to global and regional trends in temperature, precipitation, and other climate characteristics and have been one of the dominant drivers of decadal trends in Asian and African precipitation. These and other influences on regional climate from changes in aerosol emissions are expected to continue and potentially strengthen in the coming decades. However, a combination of large uncertainties in emission pathways, radiative forcing, and the dynamical response to forcing makes anthropogenic aerosol a key factor in the spread of near-term climate projections, particularly on regional scales, and therefore an important one to constrain. For example, in terms of future emission pathways, the uncertainty in future global aerosol and precursor gas emissions by 2050 is as large as the total increase in emissions since 1850. In terms of aerosol effective radiative forcing, which remains the largest source of uncertainty in future climate change projections, CMIP6 models span a factor of 5, from −0.3 to −1.5 W m−2. Both of these sources of uncertainty are exacerbated on regional scales. The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change. RAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality.publishedVersio
Climate insurance in developing countries
Get PDFCICERO Center for International Climate Research and Vista Analyse have been commissioned by Norad to undertake a mapping of relevant literature to gather knowledge about insurance arrangements aimed at climate change. The focus has primarily been on sovereign level insurance arrangements, but also arrangements aimed at small-scale food producers, and mainly in Sub-Saharan Africa. The project has been carried out by Andreas Hoel-Holt and Haakon Vennemo at Vista Analyse, and Sofie Skjeflo at CICERO Center for International Climate Research. Quality Assurance has been carried out by Asbjørn Torvanger at CICERO. We would like to thank Norad for an interesting assignment. Lauren Naville Gisnås has been our con-tact person at Norad. We are grateful for useful input from Norad to an earlier draft of this report.publishedVersio
Assessing heat effects on respiratory mortality and location characteristics as modifiers of heat effects at a small area scale in Central-Northern Europe
Get PDFHeat effects on respiratory mortality are known, mostly from time-series studies of city-wide data. A limited number of studies have been conducted at the national level or covering non-urban areas. Effect modification by area-level factors has not been extensively investigated. Our study assessed the heat effects on respiratory mortality at a small administrative area level in Norway, Germany, and England and Wales, in the warm period (May–September) within 1996–2018. Also, we examined possible effect modification by several area-level characteristics in the framework of the EU-Horizon2020 EXHAUSTION project.publishedVersio
An environmental justice analysis of air pollution in India
Get PDFDue to the lack of timely data on socioeconomic factors (SES), little research has evaluated if socially disadvantaged populations are disproportionately exposed to higher PM2.5 concentrations in India. We fill this gap by creating a rich dataset of SES parameters for 28,081 clusters (villages in rural India and census-blocks in urban India) from the National Family and Health Survey (NFHS-4) using a precision-weighted methodology that accounts for survey-design. We then evaluated associations between total, anthropogenic and source-specific PM2.5 exposures and SES variables using fully-adjusted multilevel models. We observed that SES factors such as caste, religion, poverty, education, and access to various household amenities are important risk factors for PM2.5 exposures. For example, we noted that a unit standard deviation increase in the cluster-prevalence of Scheduled Caste and Other Backward Class households was significantly associated with an increase in total-PM2.5 levels corresponding to 0.127 μg/m3 (95% CI 0.062 μg/m3, 0.192 μg/m3) and 0.199 μg/m3 (95% CI 0.116 μg/m3, 0.283 μg/m3, respectively. We noted substantial differences when evaluating such associations in urban/rural locations, and when considering source-specific PM2.5 exposures, pointing to the need for the conceptualization of a nuanced EJ framework for India that can account for these empirical differences. We also evaluated emerging axes of inequality in India, by reporting associations between recent changes in PM2.5 levels and different SES parameters.publishedVersio
A decentralized approach to model national and global food and land use systems
Get PDFThe achievement of several sustainable development goals and the Paris Climate Agreement depends on rapid progress towards sustainable food and land systems in all countries. We have built a flexible, collaborative modeling framework to foster the development of national pathways by local research teams and their integration up to global scale. Local researchers independently customize national models to explore mid-century pathways of the food and land use system transformation in collaboration with stakeholders. An online platform connects the national models, iteratively balances global exports and imports, and aggregates results to the global level. Our results show that actions toward greater sustainability in countries could sum up to 1 Mha net forest gain per year, 950 Mha net gain in the land where natural processes predominate, and an increased CO2 sink of 3.7 GtCO2e yr−1 over the period 2020–2050 compared to current trends, while average food consumption per capita remains above the adequate food requirements in all countries. We show examples of how the global linkage impacts national results and how different assumptions in national pathways impact global results. This modeling setup acknowledges the broad heterogeneity of socio-ecological contexts and the fact that people who live in these different contexts should be empowered to design the future they want. But it also demonstrates to local decision-makers the interconnectedness of our food and land use system and the urgent need for more collaboration to converge local and global priorities.publishedVersio
Changes in Land Cover and Management Affect Heat Stress and Labor Capacity
Get PDFGlobal warming is expected to exacerbate heat stress. Additionally, biogeophysical effects of land cover and land management changes (LCLMC) could substantially alter temperature and relative humidity locally and non-locally. Thereby, LCLMC could affect the occupational capacity to safely perform physical work under hot environments (labor capacity). However, these effects have never been quantified globally using a multi-model setup. Building on results from stylized sensitivity experiments of (a) cropland expansion, (b) irrigation expansion, and (c) afforestation conducted by three fully coupled Earth System Models (ESMs), we assess the local as well as non-local effects on heat stress and labor capacity. We found that LCLMC leads to substantial changes in temperature; however, the concomitant changes in humidity could largely diminish the combined impact on moist heat. Moreover, cropland expansion and afforestation cause inconsistent responses of day- and night-time temperature, which has strong implications for labor capacity. Across the ESMs, the results are mixed in terms of sign and magnitude. Overall, LCLMC result in non-negligible impacts on heat stress and labor capacity in low-latitude regions during the warmest seasons. In some locations, the changes of monthly average labor capacity, which are induced by the local effects of individual LCLMC options, could reach −14 and +15 percentage points. Thus, LCLMC-induced impacts on heat stress and their consequences for adaptation should be accounted for when designing LCLMC-related policies to ensure sustainable development.publishedVersio