A process-level hierarchical structural decomposition analysis (SDA) of energy consumption in an integrated steel plant

A hierarchical structural decomposition analysis(SDA) model has been developed based on process-level input-output(I-O) tables to analyze the drivers of energy consumption changes in an integrated steel plant during 2011-2013. By combining the principle of hierarchical decomposition into D&L method, a hierarchical decomposition model for multilevel SDA is obtained. The developed hierarchical IO-SDA model would provide consistent results and need less computation effort compared with the traditional SDA model. The decomposition results of the steel plant suggest that the technology improvement and reduced steel final demand are two major reasons for declined total energy consumption. The technical improvements of blast furnaces, basic oxygen furnaces, the power plant and the by-products utilization level have contributed mostly in reducing energy consumption. A major retrofit of ancillary process units and solving fuel substitution problem in the sinter plant and blast furnace are important for further energy saving. Besides the empirical results, this work also discussed that why and how hierarchical SDA can be applied in a process-level decomposition analysis of aggregated indicators.

Carbon Emission of Regional Land Use and Its Decomposition Analysis: Case Study of Nanjing City, China

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.

The Singular Value Decomposition Analysis between Summer Precipitation in the Dongting Lake Region and the Global Sea Surface Temperature

By dint of the summer precipitation data from 21 stations in the Dongting Lake region during 1960-2008 and the sea surface temperature(SST) data from NOAA,the spatial and temporal distributions of summer precipitation and their correlations with SST are analyzed.The coupling relationship between the anomalous distribution in summer precipitation and the variation of SST has between studied with the Singular Value Decomposition(SVD) analysis.The increase or decrease of summer precipitation in the Dongting Lake region is closely associated with the SST anomalies in three key regions.The variation of SST in the three key regions has been proved to be a significant previous signal to anomaly of summer rainfall in Dongting region.

An Intercomparison of Rules for Testing the Significance of Coupled Modes of Singular Value Decomposition Analysis

This paper clarifies the essence of the significance test of singular value decomposition analysis （SVD）, and investigates four rules for testing the significance of coupled modes of SVD, including parallel analysis, nonparametric bootstrap, random-phase test, and a new rule named modified parallel analysis. A numerical experiment is conducted to quantitatively compare the performance of the four rules in judging whether a coupled mode of SVD is significant as parameters such as the sample size, the number of grid points, and the signal-to-noise ratio vary. The results show that the four rules perform better with lower ratio of the number of grid points to sample size. Modified parallel analysis and nonparametric bootstrap perform best to abandon the spurious coupled modes, but the latter is better than the former to retain the significant coupled modes when the sample size is not much larger than the number of grid points. Parallel analysis and random-phase test are robust to abandon the spurious coupled modes only when either （1） the observations at the grid points are spatially uncorrelated, or （2） the coupled signal is very strong for parallel analysis and is not weak for random-phase test. The reasons affecting the accuracy of the test rules are discussed.

Structural Decomposition Analysis on Energy Intensity Changes at Regional Level

As China's energy intensity fluctuated in recent years, it is necessary to examine whether this fluctuation happened at a regional level. This paper establishes a decomposition model by using the structural decomposition analysis (SDA) method at a regional level. Then this model is employed to empirically analyze the changes of Beijing's energy intensity. The conclusions are as follows: during 2002-2010, except petroleum, the energy intensity decreased and the changes were mostly attributed to the technology changes, while the final use variation actually increased the energy intensity; comparing different periods of 2002-2010, the decline rates of energy intensity for coal and hydropower were decreasing, resulting from the production technology being more energy-intensive than before; the energy intensity changes of petroleum firstly increased substantially and then decreased moderately.

Competition between(18,18)and(18,16)Configurations in Ni2(CO)5:An Isomerization Energy Decomposition Analysis

The potential energy landscape of the neutral Ni_(2)(CO)_(5) complex was re-examined.A new C_(2v) structure with double bridging carbonyls is found to compete with the previously proposed triply carbonyl-bridged D_(3h) isomer for the global minimum of Ni_(2)(CO)_(5).Despite that the tri-bridged isomer possesses the more favored(18,18)configuration,where both metal centers satisfy the 18-electron rule,the neutral Ni_(2)(CO)_(5) complex prefers the di-bridged geometry with(18,16)configuration.The isomerization energy decomposition analysis reveals that the structural preference is a consequence of the maximization of electrostatic and orbital interactions.

Periodic energy decomposition analysis for electronic transport studies as a tool for atomic scale device manufacturing

Atomic scale manufacturing is a necessity of the future to develop atomic scale devices with high precision.A different perspective of the quantum realm,which includes the tunnelling effect,leakage current at the atomic-scale,Coulomb blockade and Kondo effect,is inevitable for the fabrication and hence,the mass production of these devices.For these atomic-scale device development,molecular level devices must be fabricated.Proper theoretical studies could be an aid towards the experimental realities.Electronic transport studies are the basis to realise and interpret the problems happening at this minute scale.Keeping these in mind,we present a periodic energy decomposition analysis(pEDA)of two potential candidates for moletronics:phthalocyanines and porphyrins,by placing them over gold substrate cleaved at the(111)plane to study the adsorption and interaction at the interface and then,to study their application as a channel between two electrodes,thereby,providing a link between pEDA and electronic transport studies.pEDA provides information regarding the bond strength and the contribution of electrostatic energy,Pauli’s energy,orbital energy and the orbital interactions.Combining this analysis with electronic transport studies can provide novel directions for atomic/close-toatomic-scale manufacturing(ACSM).Literature survey shows that this is the first work which establishes a link between pEDA and electronic transport studies and a detailed pEDA study on the above stated molecules.The results show that among the molecules studied,porphyrins are more adsorbable over gold substrate and conducting across a molecular junction than phthalocyanines,even though both molecules show a similarity in adsorption and conduction when a terminal thiol linker is attached.A further observation establishes the importance of attractive terms,which includes interaction,orbital and electrostatic energies,in correlating the pEDA study with the transport properties.By progressing this research,further developments could be possible in atomic-scale manufacturing in the future.

CO2 Emission from Electricity Generation in Malaysia： A Decomposition Analysis

In tenth Malaysian Plan, Malaysian government had voluntarily targeted to reduce its emission intensity to 40% compared to the 2005 level by the year 2020 and recently re-pledge to reduce more and declared for 45% emission reduction by 2030. Looking at the country＇s high dependency to the fossil fuel generation it is a high concern on the increasing CO2 emission in Malaysia. This paper intends to analyze the current status of CO2 emissions from electricity generation in Malaysia during the period 1992-2014 by applying the LMDI （logarithmic mean Divisia index） technique to find the nature of the factors influencing the changes in CO2 emissions. The decomposition analysis observed three biggest factors contributed to the reduction of CO2 emission throughout the period which is thermal generation effect, electricity generation efficiency effect and electricity structure effect.

Decomposition analysis applied to energy and emissions:A literature review

Decomposition analysis has been widely used to assess the determinants of energy and CO_(2)emissions in academic research and policy studies.Both the methodology and application of decomposition analysis have been largely improved in the past decades.After more than 50 years’developments,decomposition studies have become increasingly sophisticated and diversified,and tend to converge internally and integrate with other analytical approaches externally.A good understanding of the literature and state of the art is critical to identify knowledge gaps and formulate future research agenda.To this end,this study presents a literature survey for decomposition analysis applied to energy and emission issues,with a focus on the period of 2016–2021.A review for three individual decomposition techniques is first conducted,followed by a synthesis of emerging trends and features for the decomposition analysis literature as a whole.The findings are expected to direct future research in decomposition analysis.

Structural Decomposition Analysis of the Decline in China's CO_2 Emission Intensity 2005–2010

Here we utilize input-output tables for 2005 and 2010 to calculate the change in carbon dioxide emission intensity. Results show that total carbon dioxide emissions were 6.79 and 9.30 billion tons, and carbon dioxide emission intensity was 0.37 and 0.33 ton per thousand CNY in 2005 and 2010, respectively. Carbon dioxide emission intensity declined 11% over these five years. We used structural decomposition analysis modeling to measure the effect of four factors on this reduction in intensity. We found that the contribution values of energy structure, energy efficiency, economic growth mode and economic structure were -0.001, -0.102, 0.050, and 0.013 ton per thousand CNY, respectively. Changes in energy efficiency and energy structure are major factors promoting decreases in carbon dioxide emission intensity; the effect of the former is more distinct than the latter. Economic growth mode and economic structure are major factors that increase carbon dioxide emission intensity, whereby the effect of the former is more distinct than the latter.

Decomposition Analysis of Carbon Emissions Growth of Tertiary Industry in Beijing

The output as well as carbon dioxide emissions of tertiary industry have increased continuously in Beijing. Therefore, the tertiary industry has become a new ifeld that needs to be explored for energy saving and emission reduction. This paper calculates the direct and indirect carbon dioxide emissions of tertiary industry in Beijing from 2005 to 2012 using the input-output analysis method. The results indicate that both the direct and indirect carbon dioxide emissions increased continuously and the latter grew more quickly than the former. The growth of the direct and indirect carbon dioxide emissions of tertiary industry was decomposed, which showed that four factors inlfuence the growth of carbon emission of the tertiary industry, including the changes of industrial scale, industrial structure, energy consumption intensity and carbon coefifcient. The results show that the industrial scale advancement and the direct energy carbon coefifcient change promote the increase of direct carbon dioxide emissions, while the shift of industrial structure and the change of direct energy consumption intensity have the restrain on it. The industrial scale enlargement, industrial structure shift and the indirect energy carbon emission coefifcient change promote the growth of indirect carbon dioxide emissions, while the indirect energy consumption intensity change has a restrain.

A DECOMPOSITION METHOD OF STRUCTURAL DECOMPOSITION ANALYSIS

Over the past two decades, structural decomposition analysis (SDA) has developed into a major analytical tool in the field of input-output (IO) techniques, but the method was found to suffer from one or more of the following problems. The decomposition forms, which are used to measure the contribution of a specific determinant, are not unique due to the existence of a multitude of equivalent forms, irrational due to the weights of different determinants not matching, inexact due to the existence of large interaction terms.In this paper, a decomposition method is derived to overcome these deficiencies, and we prove that the result of this approach is equal to the Shapley value in cooperative games,and so some properties of the method are obtained. Beyond that, the two approaches that have been used predominantly in the literature have been proved to be the approximate solutions of the method.

Influencing mechanism of energy-related carbon emissions in Xinjiang based on the input-output and structural decomposition analysis

Analysis of carbon emission mechanism based on regional perspectives is an im- portant research method capable of achieving energy savings and emission reductions. Xin- jiang, an important Chinese energy production base, is currently going through a period of strategic opportunities for rapid development. Ensuring stable socio-economic development while achieving energy savings and meeting emission reductions targets, is the key issue currently facing the region. This paper is based on the input-output theory, and conducts a structural decomposition analysis on the factors affecting energy-related carbon emissions in Xinjiang from 1997 to 2007; this analysis employs a hybrid input-output analysis framework of ＂energy - economy - carbon emissions＂. （1） Xinjiang＇s carbon emissions from energy con- sumption increased from 20.70 million tons in 1997 to 40.34 million tons in 2007; carbon emissions growth was mainly concentrated in the production and processing of energy re- sources, the mining of mineral resources, and the processing industry. （2） The analysis of the direct effects of the influencing factors on carbon emissions showed that the change in per capita GDP, the final demand structure, the population scale, and the production structure were the important factors causing an increase in carbon emissions, while the decrease in carbon emission intensity during this period was the important influencing factor in stopping the growth of carbon emissions. This showed that while the sizes of Xinjiang＇s economy and population were growing, the economic structure had not been effectively optimized and the production technology had not been efficiently improved, resulting in a rapid growth of carbon emissions from energy consumption. （3） The analysis of the indirect effects of the influencing factors of carbon emission showed that the inter-provincial export, fixed capital formation, and the consumption by urban residents had significant influence on the changes in carbon emissions from energy consumption in Xinjiang. （4） The growth of investments in fixed assets of carbon intensive industry sectors, in addition to the growth of inter-provincial exports ofenergy resource products, makes the transfer effect of inter-provincial ＂embodied carbon＂ very significant.

A Comparative Decomposition Analysis of the Factors Driving Energy-related Carbon Emissions from Three Typical Provinces in China:Jiangsu, Henan and Inner Mongolia

An accurate understanding of the real situation of energy-related carbon emissions and the main factors driving the carbon emissions increments are crucial for China to realize its emission mitigation targets.Adopting the comparative decomposition of an extended LMDI(Log-Mean Divisia Index)approach, this study decomposed the changes in carbon emissions of Jiangsu, Henan, and Inner Mongolia, which are located in the eastern, central and western parts of China.This analysis led to three main findings.1)During the period of 1996–2017, the energy-related carbon emissions in the examined provinces exhibited upward trends, but with some differences among the provinces.2)The influences of driving factors on carbon emissions varied distinctly in different provinces and economic stages.Economic growth had the largest positive effect on provincial carbon emissions increases.From 1996 to 2017, the contribution rates of economic development to emissions growth in Henan, Jiangsu and Inner Mongolia were 307.19%, 205.08% and 161.26%, respectively.This influence was followed by urbanization and population size.3)Energy intensity played a leading role in facilitating emissions-reduction in the examined provinces, except for during the tenth Five-Year Plan, followed by the energy structure.The effect of rural population proportion was the weakest among all the curbing factors.Furthermore, urban and rural resident’s energy consumption per capita demonstrated relatively minor impacts and disparate directions of influence in the different provinces and economic periods, but began to play increasing roles in driving up provincial emissions changes.For example, residential energy consumption in Jiangsu contributed over 7.9% to the total carbon emission growth in 1996-2017, among which urban residents’ per-capita energy consumption contributed more than 3.8%.In view of these findings, policy makers should formulate targeted emission reduction measures that are based on the distinct situations and key factors which affect carbon emissions in each province.

Strategic Measures to Reduce China's Carbon Emissions: Based on an Index Decomposition Analysis of Carbon Emissions in Eight Industries

This article uses the refined Laspeyres index decomposition method to examine the overall trends and characteristics of carbon emissions in eight Chinese industries for the period 1994-2008. The results show that every one percentage point increase in economic scale will result in an average increase of 15 Mt （million tonnes） in carbon emissions. However, different industries vary greatly in terms of marginal carbon emissions caused by economic growth. The economic structure＇s bias toward heavy industry fuels the increase of carbon emissions： every one percentage point rise in the share of manufacturing industry produces an average of 56 Mt carbon emissions. Technological progress helps reduce energy intensity and serves as a core driver in reducing carbon emissions, in that every one percentage point decrease in energy intensity will cause an average reduction of 33 Mt in carbon emissions. Our coal-dominated energy structure has resulted in a persistently high level of carbon emissions, suggesting that the reduction effect brought about by changes in energy structureis not significant. Nevertheless, lowering the density of overall carbon emissions is a positive signal, indicating that China is optimizing its energy structure. Only by promoting industrial restructuring, optimizing energy structure, encouraging energy-saving technologies and technological innovation, and reorienting industry can China achieve low-carbon development and control pollution.

Energy decomposition analysis for intramolecular non-covalent interaction in solvated environment

In this work, the intra-EDA method, which is a recently developed energy decomposition analysis scheme for intramolecular non-covalent interaction is extended from gas phase to solvated environment. It is the first analysis scheme that performs analysis for intramolecular interaction in solution. By fragmentation scheme, a molecule is divided into intramolecular interacting fragments and environmental fragments via single bond homolysis breaking. The solvent effect is taken into account by implicit solvation model. Intramolecular interaction free energy is estimated as the separated treatment of inter-fragment interactions in dielectric environment. The analysis results highlight the importance of solvent effects to intramolecular non-covalent interaction.

Level-direction decomposition analysis with a focus on image watermarking framework

This research addresses the new level-direction decomposition in the area of image watermarking as the further development of investigations. The main process of realizing a watermarking framework is to generate a watermarked image with a focus on contourlet embedding representation. The approach performance is evaluated through several indices including the peak signal-to-noise ratio and structural similarity, whereby a set of attacks are carried out using a module of simulated attacks. The obtained information is analyzed through a set of images, using different color models, to enable the calculation of normal correlation. The module of the inverse of contourlet embedding representation is correspondingly employed to obtain the present watermarked image, as long as a number of original images are applied to a scrambling module, to represent the information in disorder. This allows us to evaluate the performance of the proposed approach by analyzing a complicated system, where a decision making system is designed to find the best level and the corresponding direction regarding contourlet embedding representation. The results are illustrated in appropriate level-direction decomposition. The key contribution lies in using a new integration of a set of subsystems, employed based upon the novel mechanism in contourlet embedding representation, in association with the decision making system. The presented approach is efficient compared with state-of-the-art approaches, under a number of serious attacks. A number of benchmarks are obtained and considered along with the proposed framework outcomes. The results support our ideas.

Structural Decomposition Analysis to Investigate the Changes in Energy Consumption in Pakistan

The world energy demand is increasing due to rapid growth in the global economy,industrialization,and urbanization.Pakistan is also confronted with increasing energy demand on one hand and is confronted with the challenge of energy demand-supply gap on the other hand.Since energy is the major driver for growth,it becomes important to investigate the trends of energy consumption in a country and the factors that are most affecting the changes in the use of energy.This particular study aims to investigate the use of energy by all the economic sectors of Pakistan during 2000–2012.The major contribution is the first time application of structural decomposition analysi for energy usage along with using Input-Output data for the period of 2002–2012.The results show the fluctuation of the energy intensity of the sectors throughout the study period.Also,the overall effect of energy intensity is negative on energy consumption and it shows a negative contribution value of-80.90%for the study period.Furthermore,the focus on more energy-intensive products like cement,automobiles,iron,steel products and the increasing final demand of the economy contributes to the growth of energy consumption in Pakistan during 2000–2012.

Changes in the epidemiological profile of suicide in Hong Kong:a 40-year retrospective decomposition analysis

The suicide rate in Hong Kong has increased significantly over the past four decades.Population subgroups such as the elderly or economically-distressed are reported to be more vulnerable than others to suicidal behaviors,while changing suicide meth-ods(such as charcoal burning which emerged in 1998),has also contributed signifi-cantly to increasing suicide rates.However,the extent of the contribution of different factors to changes in suicide rate remains unclear.This paper reported on a decom-position analysis of the epidemiological profile of suicide in Hong Kong between 1976 and 2015,specifically considering factors underlying the increasing suicide rate over this period.Completed death registry information was available from the Census and Statistics Department of the Hong Kong SAR for this investigation.We compared absolute and relative contributions of gender,age and suicide method to rate changes over time.Changes in suicide rate were generally underpinned by more than one factor.Population aging in a rapidly-aging city contributed significantly to suicide rate increases,whilst jumping from a height had the greatest influence on rate changes throughout the study period.Suicides by male aged 25-34 years and 45-54 years were more likely to be triggered by economic factors,compared with the other gender-age subgroups.The decomposition approach provided a compre-hensive understanding about how socioeconomic factors and suicide methods inter-acted to influence over-time suicide patterns.This research supports development of more focused suicide prevention measures to reduce suicide rate.

A decomposition analysis to examine the change in the number of recipients in the comprehensive social security assistance(CSSA)system

Social security is an important social and public policy measure to help address poverty in any contemporary society.The Comprehensive Social Security Assistance(CSSA)system in Hong Kong provides a safety net for those aged children and adults below 65 years old who cannot support themselves financially.It is designed to bring their income up to a prescribed level to meet their basic needs.The rapid increase in social welfare expenditure in the last decade has become a concern to the Hong Kong SAR Government.The overall social welfare expenditure has accounted for nearly 15.6%of government expenditure in 2018,with the total amount increasing from$58 billion to$90 billion(an increase of 72.4%)for the period 2014-2018.However,the amount spent on CSSA only increased from$20.7 billion to$22.3 billion with an increase of 7.7%only for the same period.The much slower magnitude of increase is related to the reduction in the number of CSSA recipients,which decreased from 237,501 to 185,528 over the period.A decomposition method was used to assess the changes in the number of people in the CSSA system.It showed that the rate of arriving into the system has been decreasing due to a robust economy with a very low unemployment rate;whereas moving out of the system has also been decreasing in the past 5 years.This phenomenon can be partly attributed to the widening of the income gap in the community in the period.Despite the increase in population size,as long as employment conditions remain strong and the momentum of leaving the system can be maintained,the number of CSSA recipients will continue to decrease.However,the results also suggested that a certain proportion of CSSA recipients will not be able to move out of the system and have been trapped.Some innovative methods to help them out of CSSA are discussed.In view of the poor economic outlook arising from the COVID-19 pandemic,it is important for the Government to have effective measures to keep people in their jobs.If the unemployment rate will does not substantially increase and then increase of in CSSA recipients can be contained.