Found 9746 publications. Showing page 42 of 390:
Based upon the thermodynamic simulation of a biogas-SOFC integrated process and the costing of its elements, the present work examines the economic feasibility of biogas-SOFCs for combined heat and power (CHP) generation, by the comparison of their economic performance against the conventional biogas-CHP with internal combustion engines (ICEs), under the same assumptions. As well as the issues of process scale and an SOFC’s cost, examined in the literature, the study brings up the determinative effects of: (i) the employed SOFC size, with respect to its operational point, as well as (ii) the feasibility criterion, on the feasibility assessment. Two plant capacities were examined (250 m3·h−1 and 750 m3·h−1 biogas production), and their feasibilities were assessed by the Internal Rate of Return (IRR), the Net Present Value (NPV) and the Pay Back Time (PBT) criteria. For SOFC costs at 1100 and 2000 EUR·kWel−1, foreseen in 2035 and 2030, respectively, SOFCs were found to increase investment (by 2.5–4.5 times, depending upon a plant’s capacity and the SOFC’s size) and power generation (by 13–57%, depending upon the SOFC’s size), the latter increasing revenues. SOFC-CHP exhibits considerably lower IRRs (5.3–13.4% for the small and 16.8–25.3% for the larger plant), compared to ICE-CHP (34.4%). Nonetheless, according to NPV that does not evaluate profitability as a return on investment, small scale biogas-SOFCs (NPVmax: EUR 3.07 M) can compete with biogas-ICE (NPV: EUR 3.42 M), for SOFCs sized to operate at 70% of the maximum power density (MPD) and with a SOFC cost of 1100 EUR·kWel−1, whereas for larger plants, SOFC-CHP can lead to considerably higher NPVs (EUR 12.5–21.0 M) compared to biogas-ICE (EUR 9.3 M). Nonetheless, PBTs are higher for SOFC-CHP (7.7–11.1 yr and 4.2–5.7 yr for the small and the large plant, respectively, compared to 2.3 yr and 3.1 yr for biogas-ICE) because the criterion suppresses the effect of SOFC-CHP-increased revenues to a time period shorter than the plant’s lifetime. Finally, the economics of SOFC-CHP are optimized for SOFCs sized to operate at 70–82.5% of their MPD, depending upon the SOFC cost and the feasibility criterion. Overall, the choice of the feasibility criterion and the size of the employed SOFC can drastically affect the economic evaluation of SOFC-CHP, whereas the feasibility criterion also determines the economically optimum size of the employed SOFC.
MDPI
2022
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2022
Low trophic species are often mentioned as additional food sources to achieve broader and more sustainable utilisation of the ocean. The aim of this study was to map the food potential of Norwegian orange-footed sea cucumber (Cucumaria frondosa). C. frondosa contained 7% protein, 1% lipids with a high proportion of polyunsaturated fatty acids, and a variety of micronutrients. The nutrient density scores (NDS) of C. frondosa were above average compared towards daily recommended intakes (DRI) for men and women (age 31–60) but below when capped at 100% of DRI. The concentrations of persistent organic pollutants and trace elements were in general low, except for inorganic arsenic (iAs) (0.73 mg per kg) which exceeded the limits deemed safe by food authorities. However, the small number of samples analysed for iAs lowers the ability to draw a firm conclusion. The carbon footprint from a value chain with a dredge fishery, processing in Norway and retail in Asia was assessed to 8 kg carbon dioxide equivalent (CO2eq.) per kg C. frondosa, the fishery causing 90%. Although, C. frondosa has some nutritional benefits, the carbon footprint or possible content of iAs may restrict the consumption.
MDPI
2022
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2022
This scoping study proposes a methodology to develop indicator(s) on the risk of chemicals on various types of ecosystems, habitats and species. This indicator is designed to answer the very different needs coming from environmental policy and strategies. Its aim is to reflect the consequences of human activities (e.g., farming) on ecosystems taking into account different protection goals that can cover specific or protected habitats (or the relevant communities or species in these habitats) or intensively used areas such as agricultural landscapes, which are very relevant in terms of representativity.
In order to develop such an indicator, the methodological approach retained to calculate maps showing a specific risk, illustrated as different degrees of exceedance of tolerable effect thresholds, is to combine different layers of information on which areas/habitats/ecosystems, contain which species, that are exposed to which amounts of chemicals. Information on the sensitivity of the species towards different toxicological effects, and how sensitive the species are to the applied chemicals, is used as ‘connectors’ between the different layers of spatial information.
The report highlights the data required for the development of such an indicator and their availability through a review of existing databases. A case study illustrates the applicability of the indicator and the need for further development.
ETC/HE
2022
Health Risk Assessment of Air Pollution and the Impact of the New WHO Guidelines
Air pollution is a major cause of premature death and disease and is the single largest environmental health risk in Europe. Heart disease and stroke are the most common reasons for premature deaths attributable to air pollution, followed by lung diseases and lung cancer.
The health risk assessment methodology assumptions have been recently adapted to follow the recommendations by the World Health Organisation (WHO), released in 2021. The new global air quality guidelines by WHO provide up-to-date health-based guideline levels for major health-damaging air pollutants and new recommendations for assessing the risk of exposure to air pollution.
This report estimates the health risk related to air pollution in 2020 based on the latest methodology. The estimates consider the number of premature deaths and years of life lost related to exposure to fine particulate matter, ozone and nitrogen dioxide, both for the 27 Member States of the European Union and for additional 14 European countries (Albania, Andorra, Bosnia and Herzegovina, Iceland, Kosovo, Liechtenstein, Monaco, Montenegro, North Macedonia, Norway, San Marino, Serbia, Switzerland, and Türkiye).
A sensitivity analysis to the changes in concentration-response functions and counterfactual concentrations is performed to understand the impact of such changes on the mortality outcome estimates. The sensitivity analysis included both old and new health risk methodology assumptions but also the recommendation from the ELAPSE study on the concentration response functions. The ELAPSE project includes some of the most recent studies on the health effects at low air pollution levels by examining associations between exposures to relatively low levels of air pollution across Europe, including levels below the current EU standards.
The results for 2020 show that the largest health risks are estimated for the countries with the largest populations. However, in relative terms, when considering e.g., years of life lost per 100 000 inhabitants, the largest relative risks are observed in central and eastern European countries for PM2.5, in central and southern European countries for NO2, and south and eastern European for O3. The lowest impact is found for the northern and north-western parts of Europe, where the concentrations are lowest. The number of premature deaths attributed to air pollution in 2020 compared to 2019, increased for PM2.5 and decreased for NO2 and O3. Apart from the changes in concentrations and demographics, the COVID-19 pandemics seems to also have an influence on these changes. For PM2.5, the reduction in concentrations were counteracted by the excess of deaths due to the pandemics. In the case of NO2, the reduction in concentrations was more pronounced as a result of the lockdown measures and the drastic reduction in traffic and its impact in reducing mortality was bigger than the increasing impact of excess of deaths due to COVID-19.
Changing assumptions on concentration-response functions and counterfactual concentrations have implications for estimating mortality health outcomes. The sensitivity analysis shows that it is not straightforward to assess which assumptions estimates the highest health impacts when both factors change. In this case, the final outcome will depend on the concentration at the grid-cell level. The latest assumptions are expected to reduce the health outcomes for PM2.5 and increase for NO2 and O3, when compared to the previous one. When aggregated to all countries, the health outcomes are reduced by over 40 % for PM2.5 and increased by 50 % and 30 % for NO2 and O3, respectively, in 2020. However, this change varies across countries depending on the concentration level the population in the individual countries is exposed to.
ETC/HE
2022
Epidemiological studies have increasingly shown that ambient air pollution is not only associated with mortality but also with the occurrence of a number of long and short-term diseases. Further, the Global Burden of Disease study clearly indicated, that e. g. particulate matter pollution is also associated with a considerable burden of disease related to morbidity effects.
In addition to the most recent EEA’s health risk assessments, this report estimates the morbidity related health burden associated with exposure to the same three key air pollutants: fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Years lived with disability (YLDs) or attributable hospitalisation cases are assessed for the year 2019 for numerous European countries, depending on the respective data availability. Besides, the methodological approach as well as reviews on evidence-based health outcomes, health data and concentration-response functions are provided.
For the ten considered risk-outcome pairs, the results showed the highest morbidity related burden of disease in Europe for PM2.5 associated with chronic obstructive pulmonary disease (COPD) with 51.6 YLDs per 100 000 inhabitants ≥25 years. For NO2 the highest morbidity burden resulted from diabetes mellitus (DM) with 54.6 YLDs per 100 000 inhabitants ≥35 years. For short-term O3 exposure hospital admissions due to respiratory diseases were estimated at 18 attributable cases per 100 000 inhabitants ≥65 years.
In addition to the estimates, the report contains suggestions for further sensitivity analyses. These would allow a better assessment of the effects resulting from different input data on the results.
The estimations presented in this report are the first of its kind that are carried out for a wide range of morbidity health outcomes associated with different outdoor air pollutants in Europe, using a consistent methodology and data from European health databases.
ETC/HE
2022
Inferring surface energy fluxes using drone data assimilation in large eddy simulations
Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.
2022
Wetland emission and atmospheric sink changes explain methane growth in 2020
Atmospheric methane growth reached an exceptionally high rate of 15.1 ± 0.4 parts per billion per year in 2020 despite a probable decrease in anthropogenic methane emissions during COVID-19 lockdowns. Here we quantify changes in methane sources and in its atmospheric sink in 2020 compared with 2019. We find that, globally, total anthropogenic emissions decreased by 1.2 ± 0.1 teragrams of methane per year (Tg CH4 yr−1), fire emissions decreased by 6.5 ± 0.1 Tg CH4 yr−1 and wetland emissions increased by 6.0 ± 2.3 Tg CH4 yr−1. Tropospheric OH concentration decreased by 1.6 ± 0.2 per cent relative to 2019, mainly as a result of lower anthropogenic nitrogen oxide (NOx) emissions and associated lower free tropospheric ozone during pandemic lockdowns. From atmospheric inversions, we also infer that global net emissions increased by 6.9 ± 2.1 Tg CH4 yr−1 in 2020 relative to 2019, and global methane removal from reaction with OH decreased by 7.5 ± 0.8 Tg CH4 yr−1. Therefore, we attribute the methane growth rate anomaly in 2020 relative to 2019 to lower OH sink (53 ± 10 per cent) and higher natural emissions (47 ± 16 per cent), mostly from wetlands. In line with previous findings, our results imply that wetland methane emissions are sensitive to a warmer and wetter climate and could act as a positive feedback mechanism in the future. Our study also suggests that nitrogen oxide emission trends need to be taken into account when implementing the global anthropogenic methane emissions reduction pledge.
2022
2022
Impacts of snow assimilation on seasonal snow and meteorological forecasts for the Tibetan Plateau
The Tibetan Plateau (TP) contains the largest amount of snow outside the polar regions and is the source of many major rivers in Asia. An accurate long-range (i.e. seasonal) meteorological forecast is of great importance for this region. The fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5) provides global long-range meteorological forecasts including over the TP. However, SEAS5 uses land initial conditions produced by assimilating Interactive Multisensor Snow and Ice Mapping System (IMS) snow data only below 1500 m altitude, which may affect the forecast skill of SEAS5 over mountainous regions like the TP. To investigate the impacts of snow assimilation on the forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer 2018. Significant changes occur in the springtime. Without snow assimilation, the reforecasts overestimate snow cover and snow depth while underestimating daily temperature over the TP. Compared to satellite-based estimates, precipitation reforecasts perform better in the west TP (WTP) than in the east TP (ETP). With snow assimilation, the reforecasts of snow cover, snow depth and temperature are consistently improved in the TP in the spring. However, the positive bias between the precipitation reforecasts and satellite observations worsens in the ETP. Compared to the experiment with no snow assimilation, the snow assimilation experiment significantly increases temperature and precipitation for the ETP and around the longitude 95∘ E. The higher temperature after snow assimilation, in particular the cold bias reduction after initialization, can be attributed to the effects of a more realistic, decreased snowpack, providing favourable conditions for generating more precipitation. Overall, snow assimilation can improve seasonal forecasts through the interaction between land and atmosphere.
2022
On behalf of Aluminiumindustriens Miljøsekretariat (AMS), NILU – Norwegian Institute for Air Research reviewed existing data on ambient air quality around aluminium smelters from the period 1992 – 2020. Changes in production technologies and treatment technologies have been implemented in this time period. Emissions to air and ambient concentrations of most compounds typically measured (PAHs, fluorides, sulphur dioxide, particulate matter, heavy metals) have decreased since the beginning of the 1990s as a result of improvement of the production technology.
NILU
2022