scholarly journals Analysis on Measurement, Decoupling Effect and Influencing Factors of Agricultural Carbon Emissions in Major Grain Producing Areas—Taking Henan Province as An Example

2021 ◽  
Vol 261 ◽  
pp. 04030
Author(s):  
YiLin Shen ◽  
Shu Yu
Keyword(s):  
Economic Development ◽  
Agricultural Economic ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Henan Province ◽  
Total Output ◽  
Chemical Fertilizers ◽  
Decoupling Analysis ◽  
Decoupling Effect ◽  
First Time

Based on the scientific calculation of agricultural carbon emissions in Henan Province, the Tapio decoupling model is used to analyze its relationship with economic development, and its driving factors are analyzed in combination with the LMDI model. The results show that the total amount of agricultural carbon emissions in Henan Province from 2010 to 2019 is on the rise, of which chemical fertilizers are the largest source of carbon emissions. The decoupling analysis shows that before 2019, the weak decoupling between agricultural carbon emissions and the total output value of the planting industry was mainly weak, and a strong decoupling state appeared for the first time in 2019. This means that the level of agricultural economic development is the main force driving the growth of carbon emissions.

scholarly journals Influencing Factors of Carbon Emissions in the Construction Industry Based on Logarithmic Mean Divisia Index: A Case Study of China

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
Wang Lijuan
Keyword(s):  
Economic Development ◽  
Energy Saving ◽  
Construction Industry ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Henan Province ◽  
Logarithmic Mean

Carbon emission is further intensified as urbanization and industrialization continue to accelerate. China has maintained its rapid economic development and urbanization in the last 2 decades. The development of the construction industry has not only consumed a large number of energy sources but also resulted in significant carbon emissions, causing some environmental damage. Recognizing the major influencing factors of carbon emissions in the construction industry has become a research hotspot to alleviate environmental pollution caused by the construction industry and meet industrial demands for energy saving and emission reduction. In this study, the factors that influence annual carbon emissions of different building types in China from 2011 to 2018 were decomposed by Logarithmic Mean Divisia Index (LMDI) through a case study in Henan Province. The major influencing factors of carbon emissions have been identified. Results demonstrate that the per capita carbon emission in the construction industry in Henan Province remains high from 2011 to 2018, but it decreases year by year. Carbon emissions from the construction industry in Henan Province increase due to economic development and energy structure. Energy efficiency can inhibit carbon emissions from the construction industry in Henan Province. The obtained conclusions have a positive effect on analyzing annual variations in carbon emissions from the construction industry in a region, identifying influencing factors, and proposing specific countermeasures of energy saving and emission reduction.

scholarly journals Urban Ecological Efficiency and Its Influencing Factors—A Case Study in Henan Province, China

2019 ◽  
Vol 11 (18) ◽  
pp. 5048 ◽  
Author(s):  
Tao Liu ◽  
Jixia Li ◽  
Juan Chen ◽  
Shaolei Yang
Keyword(s):  
Economic Development ◽  
Influencing Factors ◽  
Efficiency Analysis ◽  
Henan Province ◽  
Measure Data ◽  
Ecological Efficiency ◽  
Ecological Civilization ◽  
Growth Trend ◽  
Static And Dynamic Analysis ◽  
Significant Difference

The urban ecological civilization construction relates to welfare of the people and the national future. It is an important field of the high-quality economic development to improve the urban ecological efficiency level. The purpose of this research is to provide a new perspective and method for the quantitative study of the urban sustainable development, and also to provide some decision-making references for the improvement of the urban ecological efficiency in Henan province. This paper uses the slacks-based measure-data envelopment analysis (SBM-DEA) model containing the undesirable output and the Malmquist index model to fully evaluate the urban ecological efficiency level in Henan province during the period of 2005–2016, via both the static and dynamic analysis. Based on this, the bootstrap regression model is applied in analyzing the influencing factors of the urban ecological efficiency. The research shows three findings. First, according to the static efficiency analysis, the urban ecological efficiency in Henan province is low as a whole and has a big promotion space. Moreover, there is a significant difference in the urban ecological efficiency level among the five regions because of the different geographical locations and social and economic development situations of the cities. Second, according to the dynamic efficiency analysis, in the last 12 years, the urban ecological efficiency in Henan province has shown an overall growth trend, and the technological progress has played a major role in promoting the urban ecological efficiency in Henan province. Third, according to the influencing factor analysis, the governmental financial support hinders the improvement of the urban ecological efficiency in Henan province, while the level of opening to the outside world, the urban population density, and the urban greening level promote it.

scholarly journals Valuation of Water Resource Green Efficiency Based on SBM–TOBIT Panel Model: Case Study from Henan Province, China

2020 ◽  
Vol 12 (17) ◽  
pp. 6944
Author(s):  
Yiru Guo ◽  
Yan Hu ◽  
Ke Shi ◽  
Yuriy Bilan
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Water Resources ◽  
Environmental Pollution ◽  
Influencing Factors ◽  
Water Resource ◽  
Henan Province ◽  
Arid Areas ◽  
Efficiency Assessment

With progress in China’s industrialization and urbanization, the contradiction of social and economic development with water resource supply–demand and water environmental pollution becomes increasingly prominent. To cope with the dual constraints of resource shortage and environmental regulations, the concept of water resource green efficiency that considers economic, environmental, and ecological factors is highly involved to promote sustainable economic development. The theoretical and practice circle devote to scientific green efficiency assessment of water resources and effective recognition of relevant influencing factors. However, to an extent they neglect social benefits brought by sustainable development and possible influences of industrial restructuring on green efficiency. They also lack concern on green efficiency of water resources in inland arid areas. To offset the disadvantages of existing studies, the philosophy of sustainable development was integrated into the input–output assessment system of green efficiency of water resources, and an assessment model was constructed using the SBM–Tobit (slack-based measure and Tobit) method. Moreover, a case study based on Henan Province, China was carried out. The green efficiencies of water resources in 18 cities of Henan Province during 2011–2018 were calculated. The operation mechanism of relevant influencing factors was discussed, and the methods to improve green efficiency of water resources were determined. Results reveal that the sustainable green efficiency of water resources in Henan Province increased in fluctuation during 2011–2018. The mean green efficiency increased from 0.425 in 2011 to 0.498 in 2018. At present, green efficiency of water resources in Henan Province remains at a low level, with a mean of 0.504. Reducing water consumption intensity and increasing investment to water environmental pollution technologies can promote green efficiency of water resources significantly. Conclusions provide a new method for scientific measurement and green efficiency assessment of water resources in inland arid areas.

scholarly journals Crop Production and Agricultural Carbon Emissions: Relationship Diagnosis and Decomposition Analysis

2021 ◽  
Vol 18 (15) ◽  
pp. 8219
Author(s):  
Jianli Sui ◽  
Wenqiang Lv
Keyword(s):  
Economic Growth ◽  
Agricultural Economic ◽  
Carbon Emissions ◽  
Emission Intensity ◽  
Crop Production ◽  
Carbon Emission ◽  
Decomposition Analysis ◽  
Lmdi Method ◽  
Carbon Emission Intensity ◽  
Decoupling Analysis

Modern agriculture contributes significantly to greenhouse gas emissions, and agriculture has become the second biggest source of carbon emissions in China. In this context, it is necessary for China to study the nexus of agricultural economic growth and carbon emissions. Taking Jilin province as an example, this paper applied the environmental Kuznets curve (EKC) hypothesis and a decoupling analysis to examine the relationship between crop production and agricultural carbon emissions during 2000–2018, and it further provided a decomposition analysis of the changes in agricultural carbon emissions using the log mean Divisia index (LMDI) method. The results were as follows: (1) Based on the results of CO2 EKC estimation, an N-shaped EKC was found; in particular, the upward trend in agricultural carbon emissions has not changed recently. (2) According to the results of the decoupling analysis, expansive coupling occurred for 9 years, which was followed by weak decoupling for 5 years, and strong decoupling and strong coupling occurred for 2 years each. There was no stable evolutionary path from coupling to decoupling, and this has remained true recently. (3) We used the LMDI method to decompose the driving factors of agricultural carbon emissions into four factors: the agricultural carbon emission intensity effect, structure effect, economic effect, and labor force effect. From a policymaking perspective, we integrated the results of both the EKC and the decoupling analysis and conducted a detailed decomposition analysis, focusing on several key time points. Agricultural economic growth was found to have played a significant role on many occasions in the increase in agricultural carbon emissions, while agricultural carbon emission intensity was important to the decline in agricultural carbon emissions. Specifically, the four factors’ driving direction in the context of agricultural carbon emissions was not stable. We also found that the change in agricultural carbon emissions was affected more by economic policy than by environmental policy. Finally, we put forward policy suggestions for low-carbon agricultural development in Jilin province.

scholarly journals Forecasting the Agriculture Output Values in China Based on Grey Seasonal Model

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yan Chen ◽  
Li Nu ◽  
Lifeng Wu
Keyword(s):  
Economic Development ◽  
Agricultural Economic ◽  
Seasonal Variations ◽  
Prediction Accuracy ◽  
Animal Husbandry ◽  
Total Output ◽  
Developmental Trend ◽  
Seasonal Model ◽  
Different Seasons ◽  
Seasonal Data

The output values for agriculture, forestry, animal husbandry, and fishery are important indicators of agricultural economic development. Therefore, accurately predicting the output values for agriculture, forestry, animal husbandry, and fishery can capture the developmental trend and the optimize the structure. Agriculture, forestry, animal husbandry, and fishery are typical seasonal industries, and thus their output values vary greatly among different seasons. To accurately estimate the seasonal variations in the observed sequence and obtain better prediction results, the output values for agriculture, forestry, animal husbandry, and fishery in different quarters from 2018 to 2021 are predicted and analyzed by using the grey seasonal model (GSM). The results indicated that the prediction accuracy of GSM is relatively high. The output values for the agriculture, forestry, animal husbandry, and fishery as well as their total output value will increase gradually. It is an important achievement of structural reform under the new normal economic situation. In addition, the GSM provides a new method for predicting seasonal data.

scholarly journals Coupling Coordination and Influencing Factors among Tourism Carbon Emission, Tourism Economic and Tourism Innovation

2021 ◽  
Vol 18 (4) ◽  
pp. 1601
Author(s):  
Yue Pan ◽  
Gangmin Weng ◽  
Conghui Li ◽  
Jianpu Li
Keyword(s):  
Economic Development ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Tourism Industry ◽  
Compound System ◽  
Regional Innovation ◽  
Emission Efficiency ◽  
The Core ◽  
Coordination Degree

To discuss the coupling coordination relationship among tourism carbon emissions, economic development and regional innovation it is not only necessary to realize the green development of tourism economy, but also great significance for the tourism industry to take a low-carbon path. Taking the 30 provinces of China for example, this paper calculated the tourism carbon emission efficiency based on the super-efficiency Slacks based measure and Data envelope analyse (SBM-DEA) model from 2007 to 2017, and on this basis, defined a compound system that consists of tourism carbon emissions, tourism economic development and tourism regional innovation. Further, the coupling coordination degree model and dynamic degree model were used to explore its spatiotemporal evolution characteristics of balanced development, and this paper distinguished the core influencing factors by Geodetector model. The results showed that (1) during the study period, the tourism carbon emission efficiency showed a reciprocating trend of first rising and then falling, mainly due to the change of pure technical efficiency. (2) The coupling coordination degree developed towards a good trend, while there were significant differences among provinces, showing a gradient distribution pattern of decreasing from east to west. Additionally, (3) the core driving factors varied over time, however, in general, the influence from high to low were as follows: technological innovation, economic development, urbanization, environmental pollution control, and industrial structure. Finally, some policy recommendations were put forward to further promote the coupling coordination degree.

Analysis on the Status and Influencing Factors of Industrial Carbon Emissions in Northeast China

2013 ◽  
Vol 869-870 ◽  
pp. 866-869
Author(s):  
Shao Ping Li ◽  
Qian Wang ◽  
Yan Meng
Keyword(s):  
Energy Efficiency ◽  
Economic Development ◽  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Northeast China ◽  
Pull Factors ◽  
Industrial Carbon ◽  
Small Impact ◽  
The Status

This paper calculates the carbon emissions in the three northeastern provinces from 1997 to 2011 by using carbon formula, and compares the differences of the carbon emissions among the three provinces. Based on the LMDI model, the paper reveals the influences of every factor on the industrial carbon emissions. The population, economic development and industrialization rate are the pull factors in the increasing industrial carbon emissions, and the economic development is the main reason, followed by industrialization rate, the population has the least impact. The energy efficiency and structure of energy consumption are the inhibitory factors in the increasing industrial carbon emissions, energy efficiency is the most important factor to reduce industrial carbon emissions, and structure of energy consumption has a small impact on the industrial carbon emissions.

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