Study on the Carbon Emission Factors in Guangdong Province Based on Divisia Decomposition Method

[Objective] By decomposing and studying the relative factors of carbon emissions in Guangdong Province,the policy and suggestion on further keeping the sustainable development were put forward,which provided the reference for the carbon emission reduction in other provinces.[Method] Based on the carbon emissions formula which was put forward by Johan,three factors(the energy structure,energy efficiency and economy development) which affected the carbon emissions during 1996-2009 in Guangdong Province were studied by using Divisia decomposition method of logarithmic mean weight(LMD).[Result] The economy development was the main reason that caused the continuous significant increase of carbon emissions in Guangdong Province.The improvement of energy efficiency was the important manner for decreasing the energy consumption and the carbon emissions.The adjustment and optimization of energy consumption structure had the huge potential for reducing the carbon emissions in Guangdong Province.[Conclusion] The carbon emissions in Guangdong Province would continue to increase in the future for a long time.When formulated the development strategy in the future,it needed pay special attention to keep the accord development of economy and environment.

China's low-carbon competitiveness and its effect decomposition from the perspective of wellbeing performance of ecological input

From the perspective of wellbeing performance of ecological input,this paper constructs a low-carbon competitiveness evaluation model with wellbeing performance of carbon emissions as the measurement standard,and uses the LMDI factor decomposition method to decompose the total effect of low-carbon competitiveness changes into technology effect and service effect.And then it conducts positive analysis and comparison of the low-carbon competitiveness and its effect contribution of G20 countries from1990 to 2018.The results are as follows:Firstly,in 2018,the UK,France,Argentina,Brazil,and Germany had higher low-carbon competitiveness.From 1990 to 2018,the low-carbon competitiveness of the UK,Turkey,Germany,Italy,and Brazil increase rapidly.Secondly,from 1990 to 2018,the total effect of low-carbon competitiveness of G20 member states was all positive,that is to say,the overall wellbeing performance of carbon emissions increased,technology effect and service effect are positive in 17 countries and negative in 2 countries respectively.Thirdly,China's low-carbon competitiveness is low,lacking static and dynamic advantages,although the technology effect is the highest,but the service effect is the lowest,resulting in a low total effect,which indicates that the wellbeing performance of economic growth is the main bottleneck of China's low-carbon development.Finally,the policy recommendations for China's future low-carbon transition and sustainable development are put forward.

Driving factors and spatio-temporal features underlying industrial SO_(2) emissions in“2+26”in North China and extended cities

As one of the largest global emitters of sulfur dioxide(SO_(2)),China faces increasing pressure to achieve sustainable economic and social development.Using panel data of 58 prefecture-level cities in North China between 2003 and 2017,this paper considers the dynamic spatio-temporal characteristics of industrial SO_(2) emissions in the"2+26"in North China and extended cities in North China and decomposes the determinants of industrial SO_(2) emissions into eight effects using the Generalized Divisia Index Model(GDIM).The contributions of each effect on changes in emissions are assessed on regional,provincial,and prefectural levels,as well as according to various stages.The results indicate the following.First,industrial SO2 emissions in the"2+26"cities in North China and extended cities in North China exhibit spatial autocorrelation and agglomeration effects.Cities with high-high(HH)and low-low(LL)agglomeration patterns were concentrated in Shanxi and Henan provinces,respectively.Second,industrialization,energy consumption,and economic development were the main factors that increased industrial SO2 emissions,while technology,energy sulfur intensity,and economic sulfur intensity were the key factors that reduced them.Third,13 cities,induding Tangshan,were the most important regions where further emissions regulations need to be implemented.These cities were divided into three types and different corresponding measures for reducing their emissions are suggested.Based on the conclusions of this study,this paper puts forward some targeted policy recommendations for reducing industrial SO_(2) emissions according to different categories of cities.

Spectral decomposition method for predicting magmatic intrusion into a coal bed

Accurate prediction of magmatic intrusion into a coal bed is illustrated using the method of seismic spectral decomposition.The characteristics of coal seismic reflections are first analyzed and the effect of variable time windows and domain frequencies on the spectral decomposition are examined.The higher domain frequency of coal bed reflections using the narrower STFT time window,or the smaller ST scale factor,are acceptable.When magmatic rock intrudes from the bottom of the coal bed the domain frequency of the reflections is decreased slightly,the frequency bandwidth is narrowed correspondingly,and the response from spectral decomposition is significantly reduced.Intrusion by a very thin magmatic rock gives a spectral decomposition response that is just slightly less than what is seen from a normal coal bed.Results from an actual mining area were used to validate the method.Predicting the boundary of magmatic intrusions with the method discussed herein was highly accurate and has been validated by observations from underground mining.

Evolution trends and structural decomposition of China's green value-added over 40 years of reform and opening-up

China's 40-year history of reform and opening-up includes rapid economic development as well as pollution and environmental governance.Using a four-stage division,this study explores the evolution trend and structural decomposition of China's green value-added by constructing a non-competitive input-output table for environmental pollution from 1978 to 2017.The results indicate that pollution production coefficients increased continuously,and the green value-added index decreased.Additionally,the structural decomposition showed that investment and export were critical for economic growth during the period,though they were accompanied by serious pollution problems.The pollution generated by the raw material(represented by coal mining)and processing industries(represented by the textiles)were not controlled effectively.Pollution treatment for these industries should be strengthened in the future.The study has implications for government officials,policy makers,and academics.First,China should make green development a core concept for economic development,increase environmental pollution governance,develop a“green GDP,”incorporate the external costs of environmental pollution into the national economic accounting system.Second,it must change the investment and export structure as well as the traditional economic development pattern that exacerbates pollution.Specifically,the country should develop industries with low pollution and promote the export of industries producing high value-added products and increase green GDP per capita.Third,it should closely monitor the development of highly polluting industries.Upgrading technology to reduce pollution and strengthening pollution treatment will reduce the number of polluting industries and improve environmental governance efficiency.

Crop production changes and the impact of Grain for Green program in the Loess Plateau of China

Since the Grain for Green(GFG)program was implemented in 1999,most steeply sloping farmlands in the Loess Plateau of China have been returned to forestland and grassland.To understand its impact on the food production,this study analyzed the spatiotemporal changes of food crop production(FCP)in the plateau and quantified the contribution of sown area and yield changes to the total FCP during 1998–2014 using factor decomposition models,and then discussed the impact of GFG program on the FCP based on literature data.With the implementation of GFG program,total sown area in the Loess Plateau quickly deceased by 17.3%from 1998 to 2003,and then gradually restored to 1.03×107 hm2 in 2010.Thereafter,it slightly decreased to 1.02×107 hm2(94.6%of the area in 1998)in 2014.By contrast,total FCP generally showed an apparent growth trend,averagely increased by 1.71%per year in the whole plateau during 1998–2014.This increase was jointly contributed by the improved yield of individual crops,and the adjustment of cropping structure,i.e.,the expansion of high yield maize crop.The factor decomposition analysis results indicate that the sown area shrinkage only reduced the growth rate of total FCP by 0.29%per year during 1998–2014,although a significant impact was found for the early stage of 1999–2003.The results suggest that the implementation of GFG program would not induce an obvious risk of the food security.Therefore,it is suggested that the GFG program should be set as a long-term strategic policy,by not only supporting the conversion of slope farmlands,but also helping local farmers to seek sustainable ways of land use to improve the income and livelihood.It can be combined with the poverty eradication program,to simultaneously achieve the national goals of ecological civilization building and the livelihood improvement of rural people in the Loess Plateau.Considering rainfall limitation,the conversion of slope farmlands should be prioritized to grasslands.

The Factor Decomposition Theorem of Bounded Generalized Inverse Modules and Their Topological Continuity

In this paper we obtain a Douglas type factor decomposition theorem about certain important bounded module maps. Thus, we come to the discussion of the topological continuity of bounded generalized inverse module maps. Let X be a topological space, x →Tx ： X→L（E） be a continuous map, and each R（Tx） be a closed submodule in E, for every fixed x C X. Then the map x→ Tx^＋： X→L（E） is continuous if and only if ｜｜Tx^＋｜｜ is locally bounded, where Tx^＋ is the bounded generalized inverse module map of Tx. Furthermore, this is equivalent to the following statement： For each x0 in X, there exists a neighborhood ∪0 at x0 and a positive number λ such that （0, λ^2）lohtatn in ∩x∈∪0C／σ（Tx^＋Tx）, where a（T） denotes the spectrum of operator T.

Leaf litter decomposition characteristics and controlling factors across two contrasting forest types

Plant leaf litter decomposition provides a source of energy and nutrients in forest ecosystems.In addition to traditional environmental factors,the degradation process of litter is also affected by plant functional traits and litter quality.However,at the community level,it is still unclear whether the relative importance of plant traits and litter quality on the litter decomposition rate is consistent.A year-long mixed leaf litter decomposition experiment in a similar environment was implemented by using the litterbag method in seven typical forest types in Dongling Mountain,Beijing,North China,including six monodominant communities dominated by Juglans mandshurica,Populus cathayana,Betula dahurica,Betula platyphylla,Pinus tabuliformis and Larix gmelinii var.principis-rupprechtii and one codominant community dominated by Fraxinus rhynchophylla,Quercus mongolica and Tilia mongolica.The results showed that there were considerable differences in the litter decomposition rate(k-rate)among the different forest types.The community weighted mean(CWM)traits of green leaves and litter quality explained 35.60%and 9.05%of the k-rate variations,respectively,and the interpretation rate of their interaction was 23.37%,indicating that the CWM traits and their interaction with litter quality are the main factors affecting the k-rate variations.In the recommended daily allowance,leaf nitrogen content,leaf dry matter content,leaf tannin content and specific leaf area were the main factors affecting the k-rate variations.Therefore,we suggest that future studies should focus on the effects of the CWM traits of green leaves on litter decomposition at the community level.

Regional Disparities in China's Mainland at Provincial Level Between 2000 and 2005

Based on the methodology provided by Organization for Economic Co-operation and Development,we analyze regional disparities in China's mainland at provincial level between 2000 and 2005.It regards regional GDP growth as the joint result of contribution of a number of factors,i.e.capital productivity,capital per manpower,specialization,employment rate,active population,and population.The results show that for all provincial units,capital per manpower is a dominant contributing factor to the growth of GDP per capita during the period from 2000 to 2005 while capital productivity has quite significant negative impacts.Specialization contributes differently in different provinces.In most provincial units,employment rate and age activity have a positive impact on growth of GDP per capita,though not very significantly.

Java Computer Animation for Effective Learning of the Cholesky Algorithm with Transportation Engineering Applications

In this paper, the well-known Cholesky Algorithm (for solving simultaneous linear equations, or SLE) is re-visited, with the ultimate goal of developing a simple, user-friendly, attractive, and useful Java Visualization and Animation Graphical User Inter-face (GUI) software as an additional teaching tool for students to learn the Cholesky factorization in a step-by-step fashion with computer voice and animation. A demo video of the Cholesky Decomposition (or factorization) animation and result can be viewed online from the website: http://www.lions.odu.edu/~imako001/cholesky/demo/index.html. The software tool developed from this work can be used for both students and their instructors not only to master this technical subject, but also to provide a dynamic/valuable tool for obtaining the solutions for homework assignments, class examinations, self-assessment studies, and other coursework related activities. Various transportation engineering applications of SLE are cited. Engineering educators who have adopted “flipped classroom instruction” can also utilize this Java Visualization and Animation software for students to “self-learning” these algorithms at their own time (and at their preferable locations), and use valuable class-meeting time for more challenging (real-life) problems’ discussions. Statistical data for comparisons of students’ performance with and without using the developed Java computer animation are also included.

Carbon Emissions from Industrial Sectors in China:Driving Factors and the Potential for Emission Reduction

We use the refined Laspeyres index decomposition method to determine the main CO2 emissions from industry and analyze differences in these over the period 1994-2007. Then we examined the decoupling state between carbon emissions and economic growth and the effectiveness of the implementation of emission reduction policy. We found that output effect is the dominant positive factor for carbon emissions growth in China＇s industrial sectors, and the effect of energy intensity change is the mainfactor affecting carbon emission reductions; the impact of these two factors is respectively 357.20% and -248.67%. The food industry, textile industry and machinery industry show a decreasing trend in emissions, and emissions from the oil industry increased by 217.75%. From 1994 to 2007 and 2000 to 2007, the decoupling index of carbon emissions and the industrial sector was 0.63 and 0.56 respectively. This indicates carbon emissions and economic growth are in a weak decoupling state, and emission reduction policies lack efficacy. These findings can be used in the design of policy priorities for improving decoupling across industrial sectors.

A Factor Decomposing Model of Water Use Efficiency at Sector Level and Its Application in Beijing

The paper explores the contribution of different factors affecting water use efficiency(WUE) of each sector and explores ways to improve WUE.A new Multi-Sector and Multi-Factors Logarithmic Mean Divisia Index(MLMDI) decomposition method was developed that enabled the identification of WUE by sector into 11 factors in terms of their order of importance.An application to Beijing at the 19 sector level was made for the period between 2002–2007.The water conservation effects of six measures proposed during the 12th-Five-Year-Plan of Beijing were assessed.It was found that,to decrease the transferred out and export of agriculture products and increasing water prices would be the top two most effective measures to promote water conservation.While the adjustment of direct water use structure would contribute in less significant way,the adjustment of industrial structure would have a negative effect.

The Action of Structure and Efficiency on Energy Intensity Variation in China- An Empirical Analysis Based on AWD

This paper discusses the factors influencing Chinese energy intensity from 1980 to 2003 based on adaptive weighting Divisia index method and the analyzing results are different in different phase. In period of 1980～1990, both the structure factor and the technology factor effected positively Chinese energy intensity＇s fall but the former became inefficacy and even turned out to be negative in 1991～2001 meanwhile the later factor strengthened its function. After 2001, the two factors promoted Chinese energy intensity＇s rising together. The conclusion is given in the end.