In response to the inherent requirements of low-carbon land spatial planning in Jiangxi Province and the lack of existing research,this paper explored the mechanism of spatial form elements of Poyang Lake urban agglom...In response to the inherent requirements of low-carbon land spatial planning in Jiangxi Province and the lack of existing research,this paper explored the mechanism of spatial form elements of Poyang Lake urban agglomeration on urban carbon emissions.Based on generalized linear regression and geographically weighted regression models,this paper analyzed the spatiotemporal distribution characteristics of carbon emissions,the spatiotemporal relationship between urban form index and carbon emissions,and the spatial differentiation of the intensity of dominant factors from 63 county-level administrative units in the Poyang Lake city group from 2005 to 2020.The results showed that:①The carbon emissions of urban agglomerations around Poyang Lake are generally increasing,and the spatial distribution of carbon emissions is characterized by high-value concentration in the middle and low-value agglomeration in pieces;②The main driving factor for the spatial heterogeneity of carbon emissions was the expansion of built-up area;③Improving urban compactness and optimizing urban form could effectively reduce urban carbon emissions.The results showcased the correlation between urban spatial landscape pattern and the spatiotemporal distribution of carbon emissions,which could make the low-carbon land spatial planning in the Poyang Lake city group more reasonable and practical.展开更多
The enthalpies of formation of solid organic compounds containing carbon,nitrogen,oxygen,and hydrogen were estimated using two suggested descriptor sets,separately,by machine learning methods.The two descriptor sets a...The enthalpies of formation of solid organic compounds containing carbon,nitrogen,oxygen,and hydrogen were estimated using two suggested descriptor sets,separately,by machine learning methods.The two descriptor sets are both composed of descriptors of Benson’s groups and corrected groups.The main differences between them are that one is generated based on atoms and the other is based on bonds.An in-house program was specially written in Java to extract all the descriptors with a function to ensure that each atom(or bond)of a molecule is represented by Benson’s groups once for an atom-based(or bond-based)descriptor set.Multiple linear regression and partial least squares were used,separately,to build models to predict the enthalpy of formation for two descriptor sets.The combination of the models constructed by two descriptor sets based on the atoms and the bonds achieved the best-predicted results in this paper,and the corresponding results of the test set are better than that in the literature,from which the original data were retrieved.Further,a small data set of fluorinated molecules was collected,and satisfactory results were also obtained for these molecules containing fluorine with the assistance of the former data set.展开更多
基金by the 2022 National Natural Foundation of China(42261046)The 2021 Project for Humanities and Social Sciences of Jiangxi Higher Education Institutions(JC21237).
文摘In response to the inherent requirements of low-carbon land spatial planning in Jiangxi Province and the lack of existing research,this paper explored the mechanism of spatial form elements of Poyang Lake urban agglomeration on urban carbon emissions.Based on generalized linear regression and geographically weighted regression models,this paper analyzed the spatiotemporal distribution characteristics of carbon emissions,the spatiotemporal relationship between urban form index and carbon emissions,and the spatial differentiation of the intensity of dominant factors from 63 county-level administrative units in the Poyang Lake city group from 2005 to 2020.The results showed that:①The carbon emissions of urban agglomerations around Poyang Lake are generally increasing,and the spatial distribution of carbon emissions is characterized by high-value concentration in the middle and low-value agglomeration in pieces;②The main driving factor for the spatial heterogeneity of carbon emissions was the expansion of built-up area;③Improving urban compactness and optimizing urban form could effectively reduce urban carbon emissions.The results showcased the correlation between urban spatial landscape pattern and the spatiotemporal distribution of carbon emissions,which could make the low-carbon land spatial planning in the Poyang Lake city group more reasonable and practical.
基金Open Research Fund Program of Science and Technology on Aerospace Chemical Power Laboratory,China(No.120201B01)National Natural Science Foundation of China(Nos.21875061,21975066).
文摘The enthalpies of formation of solid organic compounds containing carbon,nitrogen,oxygen,and hydrogen were estimated using two suggested descriptor sets,separately,by machine learning methods.The two descriptor sets are both composed of descriptors of Benson’s groups and corrected groups.The main differences between them are that one is generated based on atoms and the other is based on bonds.An in-house program was specially written in Java to extract all the descriptors with a function to ensure that each atom(or bond)of a molecule is represented by Benson’s groups once for an atom-based(or bond-based)descriptor set.Multiple linear regression and partial least squares were used,separately,to build models to predict the enthalpy of formation for two descriptor sets.The combination of the models constructed by two descriptor sets based on the atoms and the bonds achieved the best-predicted results in this paper,and the corresponding results of the test set are better than that in the literature,from which the original data were retrieved.Further,a small data set of fluorinated molecules was collected,and satisfactory results were also obtained for these molecules containing fluorine with the assistance of the former data set.
