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- Hailong, Li, et al.
(författare)
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Impacts of impurities in CO2-fluids on CO2 transport process
- 2006
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Ingår i: Proceedings of the ASME Turbo Expo. - 0791842398 - 9780791842393 ; , s. 367-375
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Konferensbidrag (refereegranskat)abstract
- There are four possible transportation means that could be used to deliver CO2: motor carriers, railway carriers, water carriers, and pipeline. The impurities in CO2-fluids have significant impacts on the thermodynamic properties that will further affect the design, operation and cost of CO2 transport. This paper focuses on how impurities in CO 2-fluids affect thermodynamic properties, and how the changes of properties affect CO2 transport process. Vapor-liquid equilibrium (VLB), critical point and densities are essential thermodynamic properties for designing a CO2 transport process. Studies on these properties will be carried out for CO2-mixtures based on the combinations of the common impurities such as SO2, H2S, CH4, Ar, O2 and N2. Moreover with a real case of pipeline for CO2 transport, the impact of impurities on transport process will be demonstrated in more details.
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| 2. |
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| 3. |
- Lu, Liu, et al.
(författare)
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High-performance formaldehyde prediction for indoor air quality assessment using time series deep learning
- 2024
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Ingår i: Building Simulation. - : TSINGHUA UNIV PRESS. - 1996-3599 .- 1996-8744.
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Tidskriftsartikel (refereegranskat)abstract
- Indoor air pollution resulting from volatile organic compounds (VOCs), especially formaldehyde, is a significant health concern needed to predict indoor formaldehyde concentration (Cf) in green intelligent building design. This study develops a thermal and wet coupling calculation model of porous fabric to account for the migration of formaldehyde molecules in indoor air and cotton, silk, and polyester fabric with heat flux in Harbin, Beijing, Xi'an, Shanghai, Guangzhou, and Kunming, China. The time-by-time indoor dry-bulb temperature (T), relative humidity (RH), and Cf, obtained from verified simulations, were collated and used as input data for the long short-term memory (LSTM) of the deep learning model that predicts indoor multivariate time series Cf from the secondary source effects of indoor fabrics (adsorption and release of formaldehyde). The trained LSTM model can be used to predict multivariate time series Cf at other emission times and locations. The LSTM-based model also predicted Cf with mean absolute percentage error (MAPE), symmetric mean absolute percentage error (SMAPE), mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) that fell within 10%, 10%, 0.5, 0.5, and 0.8, respectively. In addition, the characteristics of the input dataset, model parameters, the prediction accuracy of different indoor fabrics, and the uncertainty of the data set are analyzed. The results show that the prediction accuracy of single data set input is higher than that of temperature and humidity input, and the prediction accuracy of LSTM is better than recurrent neural network (RNN). The method's feasibility was established, and the study provides theoretical support for guiding indoor air pollution control measures and ensuring human health and safety.
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| 4. |
- Olsson, Alexander, et al.
(författare)
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Potential for carbon sequestration and mitigation of climate change by irrigation of grasslands
- 2014
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Ingår i: Applied Energy. - : Elsevier BV. - 0306-2619 .- 1872-9118. ; 136, s. 1145-1154
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Tidskriftsartikel (refereegranskat)abstract
- The climate change mitigation potential of irrigation powered by a photovoltaic water pumping system (PVWPS) to restore degraded grasslands has been investigated using the Intergovernmental Panel on Climate Change (IPCC) 2006 Guidelines for National Greenhouse Gas Inventories for Agriculture, Forestry and Other Land Use. The purpose of this study is to develop a generic and simple method to estimate the climate change mitigation benefit of a PVWPS. The possibility to develop carbon credits for the carbon offset markets has also been studied comparing carbon sequestration in grasslands to other carbon sequestration projects. The soil carbon sequestration following irrigation of the grassland is calculated as an annual increase in the soil organic carbon pool.The PVWPS can also generate an excess of electricity when irrigation is not needed and the emissions reductions due to substitution of grid electricity give additional climate change mitigation potential.The results from this study show that the carbon sequestration and emissions reductions benefits per land area using a PVWPS for irrigating grasslands are comparable to other carbon sequestration options such as switching to no-till practice. Soil carbon in irrigated grasslands is increased with over 60% relative to severely degraded grasslands and if nitrogen fixing species are introduced the increase in soil organic carbon can be almost 80%. Renewable electricity generation by the PVWPS will further increase the mitigation benefit of the system with 70-90%. When applying the methodology developed in this paper to a case in Qinghai, China, we conclude that using a PVWPS to restore degraded grasslands for increased grass production and desertification control has a climate change mitigation benefit of 148Mg (1Mg=1metricton) CO2-equivalents (CO2-eq) per hectare in a cold temperate, dry climate during a 20year process of soil organic carbon sequestration and emissions reductions. Leakage due to an increase in N2O emissions from the additional biomass production and introduction of nitrogen fixing species is included in this result. The most important conclusion from our case is that if soil carbon sequestration is lower than 24Mg CO2-eq per hectare including leakage, then the climate change mitigation benefit is larger if PV is used to produce electricity for the grid.
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