Coal is the dominant primary energy source in China and the major source of greenhouse gases and air pollutants. To facilitate the use of coal in an environmentally satisfactory and economically viable way, clean coal...Coal is the dominant primary energy source in China and the major source of greenhouse gases and air pollutants. To facilitate the use of coal in an environmentally satisfactory and economically viable way, clean coal technologies （CCTs） are necessary. This paper presents a review of recent research and development of four kinds of CCTs： coal power generation; coal conversion; pollution control; and carbon capture, utilization, and storage. It also outlines future perspectives on directions for technology re search and development （R＆D）. This review shows that China has made remarkable progress in the R＆D of CCTs, and that a number of CCTs have now entered into the commercialization stage.展开更多
Biogas upgrading for removing CO2 and other trace components from raw biogas is a necessary step before the biogas to be used as a vehicle fuel or supplied to the natural gas grid. In this work, three technologies for...Biogas upgrading for removing CO2 and other trace components from raw biogas is a necessary step before the biogas to be used as a vehicle fuel or supplied to the natural gas grid. In this work, three technologies for biogas upgrading, i.e., pressured water scrubbing(PWS), monoethanolamine aqueous scrubbing(MAS) and ionic liquid scrubbing(ILS), are studied and assessed in terms of their energy consumption and environmental impacts with the process simulation and green degree method. A non-random-two-liquid and Henry's law property method for a CO2 separation system with ionic liquid 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide([bmim][Tf2N]) is established and verified with experimental data. The assessment results indicate that the specific energy consumption of ILS and PWS is almost the same and much less than that of MAS. High purity CO2 product can be obtained by MAS and ILS methods, whereas no pure CO2 is recovered with the PWS. For the environmental aspect, ILS has the highest green degree production value, while MAS and PWS produce serious environmental impacts.展开更多
According to this problem that every regional technology innovation of SMEs and innovation environment are different, the method on secondary relative evaluation to measure the innovation capability of SMEs in 9 provi...According to this problem that every regional technology innovation of SMEs and innovation environment are different, the method on secondary relative evaluation to measure the innovation capability of SMEs in 9 provinces and 3 municipalities is developed in this paper. First the Fuzzy Integral Comprehensive Evaluation is adopted to measure the comprehensive index states of technological innovation of SMEs in different regions, and then the BCC model in Data Envelopment Analysis is used to calculate the secondary relative evaluation of regional technology innovation capability in SMEs, so that this method not only settles the relevance between indexes influencing regional technology innovation capability of SMEs, but also eliminates the influence of objective basic condition, and then provides bases for every region to make out policies and rules on technological innovation of SMEs and for enterprise to establish relevant strategy of technological innovation.展开更多
Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanc...Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.展开更多
Currently, carbon materials, such as graphene,carbon nanotubes, activated carbon, porous carbon, have been successfully applied in energy storage area by taking advantage of their structural and functional diversity. ...Currently, carbon materials, such as graphene,carbon nanotubes, activated carbon, porous carbon, have been successfully applied in energy storage area by taking advantage of their structural and functional diversity. However, the development of advanced science and technology has spurred demands for green and sustainable energy storage materials.Biomass-derived carbon, as a type of electrode materials, has attracted much attention because of its structural diversities,adjustable physical/chemical properties, environmental friendliness and considerable economic value. Because the nature contributes the biomass with bizarre micro structures,the biomass-derived carbon materials also show naturally structural diversities, such as OD spherical, 1D fibrous, 2D lamellar and 3D spatial structures. In this review, the structure design of biomass-derived carbon materials for energy storage is presented. The effects of structural diversity, porosity and surface heteroatom doping of biomass-derived carbon materials in supercapacitors, lithium-ion batteries and sodium-ion batteries are discussed in detail. In addition, the new trends and challenges in biomass-derived carbon materials have also been proposed for further rational design of biomass-derived carbon materials for energy storage.展开更多
Alpine swamp meadows on the Tibetan Plateau,with the highest soil organic carbon content across the globe,are extremely vulnerable to climate change.To accurately and continually quantify the gross primary production...Alpine swamp meadows on the Tibetan Plateau,with the highest soil organic carbon content across the globe,are extremely vulnerable to climate change.To accurately and continually quantify the gross primary production（GPP） is critical for understanding the dynamics of carbon cycles from site-scale to global scale.Eddy covariance technique（EC） provides the best approach to measure the site-specific carbon flux,while satellite-based models can estimate GPP from local,small scale sites to regional and global scales.However,the suitability of most satellite-based models for alpine swamp meadow is unknown.Here we tested the performance of four widely-used models,the MOD17 algorithm（MOD）,the vegetation photosynthesis model（VPM）,the photosynthetic capacity model（PCM）,and the alpine vegetation model（AVM）,in providing GPP estimations for a typical alpine swamp meadow as compared to the GPP estimations provided by EC-derived GPP.Our results indicated that all these models provided good descriptions of the intra-annual GPP patterns（R〉20.89,P〈0.0001）,but hardly agreed with the inter-annual GPP trends.VPM strongly underestimated the GPP of alpine swamp meadow,only accounting for 54.0% of GPP_EC.However,the other three satellite-based GPP models could serve as alternative tools for tower-based GPP observation.GPP estimated from AVM captured 94.5% of daily GPP_EC with the lowest average RMSE of 1.47 g C m^（-2）.PCM slightly overestimated GPP by 12.0% while MODR slightly underestimated by 8.1% GPP compared to the daily GPP_EC.Our results suggested that GPP estimations for this alpine swamp meadow using AVM were superior to GPP estimations using the other relatively complex models.展开更多
基金Acknowledgements The authors gratefully acknowledge the funding support from the National Key Basic Research Program of China （2013CB228500）, the National Natural Science Foundation of Chi- na （71203119）, and the Advanced Coal Technology Consortium of CERC （2016YFE0102500）.
文摘Coal is the dominant primary energy source in China and the major source of greenhouse gases and air pollutants. To facilitate the use of coal in an environmentally satisfactory and economically viable way, clean coal technologies （CCTs） are necessary. This paper presents a review of recent research and development of four kinds of CCTs： coal power generation; coal conversion; pollution control; and carbon capture, utilization, and storage. It also outlines future perspectives on directions for technology re search and development （R＆D）. This review shows that China has made remarkable progress in the R＆D of CCTs, and that a number of CCTs have now entered into the commercialization stage.
基金Supported by the National Basic Research Program of China(2013CB733506,2014CB744306)the National Natural Science Foundation of China(21036007,51274183)
文摘Biogas upgrading for removing CO2 and other trace components from raw biogas is a necessary step before the biogas to be used as a vehicle fuel or supplied to the natural gas grid. In this work, three technologies for biogas upgrading, i.e., pressured water scrubbing(PWS), monoethanolamine aqueous scrubbing(MAS) and ionic liquid scrubbing(ILS), are studied and assessed in terms of their energy consumption and environmental impacts with the process simulation and green degree method. A non-random-two-liquid and Henry's law property method for a CO2 separation system with ionic liquid 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide([bmim][Tf2N]) is established and verified with experimental data. The assessment results indicate that the specific energy consumption of ILS and PWS is almost the same and much less than that of MAS. High purity CO2 product can be obtained by MAS and ILS methods, whereas no pure CO2 is recovered with the PWS. For the environmental aspect, ILS has the highest green degree production value, while MAS and PWS produce serious environmental impacts.
文摘According to this problem that every regional technology innovation of SMEs and innovation environment are different, the method on secondary relative evaluation to measure the innovation capability of SMEs in 9 provinces and 3 municipalities is developed in this paper. First the Fuzzy Integral Comprehensive Evaluation is adopted to measure the comprehensive index states of technological innovation of SMEs in different regions, and then the BCC model in Data Envelopment Analysis is used to calculate the secondary relative evaluation of regional technology innovation capability in SMEs, so that this method not only settles the relevance between indexes influencing regional technology innovation capability of SMEs, but also eliminates the influence of objective basic condition, and then provides bases for every region to make out policies and rules on technological innovation of SMEs and for enterprise to establish relevant strategy of technological innovation.
基金Project(2012CB725403)supported by the National Basic Research Program of ChinaProjects(71210001,51338008)supported by the National Natural Science Foundation of ChinaProject supported by World Capital Cities Smooth Traffic Collaborative Innovation Center and Singapore National Research Foundation Under Its Campus for Research Excellence and Technology Enterprise(CREATE)Programme
文摘Short-term traffic flow prediction is one of the essential issues in intelligent transportation systems(ITS). A new two-stage traffic flow prediction method named AKNN-AVL method is presented, which combines an advanced k-nearest neighbor(AKNN)method and balanced binary tree(AVL) data structure to improve the prediction accuracy. The AKNN method uses pattern recognition two times in the searching process, which considers the previous sequences of traffic flow to forecast the future traffic state. Clustering method and balanced binary tree technique are introduced to build case database to reduce the searching time. To illustrate the effects of these developments, the accuracies performance of AKNN-AVL method, k-nearest neighbor(KNN) method and the auto-regressive and moving average(ARMA) method are compared. These methods are calibrated and evaluated by the real-time data from a freeway traffic detector near North 3rd Ring Road in Beijing under both normal and incident traffic conditions.The comparisons show that the AKNN-AVL method with the optimal neighbor and pattern size outperforms both KNN method and ARMA method under both normal and incident traffic conditions. In addition, the combinations of clustering method and balanced binary tree technique to the prediction method can increase the searching speed and respond rapidly to case database fluctuations.
基金supported by the National Natural Science Foundation of China (51702117,51672055)Major Research Projects Fund of Jilin Institute of Chemical Technology (2016006)Natural Science Foundation of Heilongjiang Province of China (E201416)
文摘Currently, carbon materials, such as graphene,carbon nanotubes, activated carbon, porous carbon, have been successfully applied in energy storage area by taking advantage of their structural and functional diversity. However, the development of advanced science and technology has spurred demands for green and sustainable energy storage materials.Biomass-derived carbon, as a type of electrode materials, has attracted much attention because of its structural diversities,adjustable physical/chemical properties, environmental friendliness and considerable economic value. Because the nature contributes the biomass with bizarre micro structures,the biomass-derived carbon materials also show naturally structural diversities, such as OD spherical, 1D fibrous, 2D lamellar and 3D spatial structures. In this review, the structure design of biomass-derived carbon materials for energy storage is presented. The effects of structural diversity, porosity and surface heteroatom doping of biomass-derived carbon materials in supercapacitors, lithium-ion batteries and sodium-ion batteries are discussed in detail. In addition, the new trends and challenges in biomass-derived carbon materials have also been proposed for further rational design of biomass-derived carbon materials for energy storage.
基金National Natural Science Foundation of China(41571042,40603024)
文摘Alpine swamp meadows on the Tibetan Plateau,with the highest soil organic carbon content across the globe,are extremely vulnerable to climate change.To accurately and continually quantify the gross primary production（GPP） is critical for understanding the dynamics of carbon cycles from site-scale to global scale.Eddy covariance technique（EC） provides the best approach to measure the site-specific carbon flux,while satellite-based models can estimate GPP from local,small scale sites to regional and global scales.However,the suitability of most satellite-based models for alpine swamp meadow is unknown.Here we tested the performance of four widely-used models,the MOD17 algorithm（MOD）,the vegetation photosynthesis model（VPM）,the photosynthetic capacity model（PCM）,and the alpine vegetation model（AVM）,in providing GPP estimations for a typical alpine swamp meadow as compared to the GPP estimations provided by EC-derived GPP.Our results indicated that all these models provided good descriptions of the intra-annual GPP patterns（R〉20.89,P〈0.0001）,but hardly agreed with the inter-annual GPP trends.VPM strongly underestimated the GPP of alpine swamp meadow,only accounting for 54.0% of GPP_EC.However,the other three satellite-based GPP models could serve as alternative tools for tower-based GPP observation.GPP estimated from AVM captured 94.5% of daily GPP_EC with the lowest average RMSE of 1.47 g C m^（-2）.PCM slightly overestimated GPP by 12.0% while MODR slightly underestimated by 8.1% GPP compared to the daily GPP_EC.Our results suggested that GPP estimations for this alpine swamp meadow using AVM were superior to GPP estimations using the other relatively complex models.
