Allocating on coal consumption and CO2 emission from fair and efficient perspective: empirical analysis on provincial panel data of China.

This paper considers a problem of how to allocate resource effectively and equitably among provinces. To address the problem, a total factor resource input-oriented data envelopment analysis (DEA) model is used to evaluate the energy and environmental efficiency for 30 provinces in China during 2009-2013 in this paper. Based on the evaluation results, from efficient and fair perspective, a revised DEA-based resource allocation model is established. It is worth pointing out that the model takes the input orientation and output orientation into account at the same time and can be used to allocate coal consumption and carbon emission by 2020 for 30 provinces in China. Results indicate that if the Chinese government wants to fulfill the CO2 emission reduction targets of 40-45% by 2020, and coal consumption intensity reduction target during 13th Five-Year Plan, inefficient provinces will undertake more coal consumption and carbon emission intensity reduction obligation share. And provinces with historical high coal consumption and high CO2 emission intensity will have greater potential of coal consumption and carbon emission intensity reduction. In addition, this paper set several scenarios of gross domestic product (GDP) growth rate, under the scenarios analysis, finds the growth rate of GDP has negative effect on reduction of coal consumption and carbon dioxide emissions intensity. This research provides more realistic practical significance for achieving sustainable economic development.

Comprehensive evaluation on low-carbon development of coal enterprise groups.

Scientifically evaluating the level of low-carbon development in terms of theoretical and practical significance is extremely important to coal enterprise groups for implementing national energy-related systems. This assessment can assist in building institutional mechanisms that are conducive for the economic development of coal business cycle and energy conservation as well as promoting the healthy development of coal enterprises to realize coal scientific development and resource utilization. First, by adopting systematic analysis method, this study builds low-carbon development evaluation index system for coal enterprise groups. Second, to determine the weight serving as guideline and criteria of the index, analytic hierarchy process (AHP) is applied using integrated linear weighted sum method to evaluate the level of low-carbon development of coal enterprise groups. Evaluation is also performed by coal enterprise groups, and the process comprises field analysis and evaluation. Finally, industrial policies are proposed regarding the development of low-carbon coal conglomerate strategies and measures. This study aims mainly to guide the low-carbon development of coal enterprise groups, solve the problem of coal mining and the destruction of ecological environment, support the conservation of raw materials and various resources, and achieve the sustainable development of the coal industry.

Characterization of soybean genomic features by analysis of its expressed sequence tags.

We analyzed 314,254 soybean expressed sequence tags (ESTs), including 29,540 from our laboratory and 284,714 from GenBank. These ESTs were assembled into 56,147 unigenes. About 76.92% of the unigenes were homologous to genes from Arabidopsis thaliana ( Arabidopsis). The putative products of these unigenes were annotated according to their homology with the categorized proteins of Arabidopsis. Genes corresponding to cell growth and/or maintenance, enzymes and cell communication belonged to the slow-evolving class, whereas genes related to transcription regulation, cell, binding and death appeared to be fast-evolving. Soybean unigenes with no match to genes within the Arabidopsis genome were identified as soybean-specific genes. These genes were mainly involved in nodule development and the synthesis of seed storage proteins. In addition, we also identified 61 genes regulated by salicylic acid, 1,322 transcription factor genes and 326 disease resistance-like genes from soybean unigenes. SSR analysis showed that the soybean genome was more complex than the Arabidopsis and the Medicago truncatula genomes. GC content in soybean unigene sequences is similar to that in Arabidopsis and M. truncatula. Furthermore, the combined analysis of the EST database and the BAC-contig sequences revealed that the total gene number in the soybean genome is about 63,501.

[Amplification of 5' cDNA end of a disease resistance gene homolog using RACE system from soybean].

Based on part of a known partial cDNA sequence of a disease resistance gene homolog, KR3-1, obtained by screening a cDNA library from soybean, 5'-RACE-PCR was carried out with gene specific primers and universal primers. After the nested PCR reaction,an amplified fragment of 447 bp in length which overlapped the known KR3-1 sequence by 129 bp was obtained subsequently. Thus, a 5' cDNA end of KR3 was successfully cloned.