scholarly journals Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3102 ◽  
Author(s):  
Yihui Chen ◽  
Minjie Li ◽  
Kai Su ◽  
Xiaoyong Li
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Agricultural Development ◽  
Agricultural Sector ◽  
Industrial Structure ◽  
Arable Land ◽  
Added Value ◽  
Agricultural Labor ◽  
Intergovernmental Panel ◽  
Per Capita

With the development of agricultural modernization, the carbon emissions caused by the agricultural sector have attracted academic and practitioners’ circles’ attention. This research selected the typical agricultural development province in China, Fujian, as the research object. Based on the carbon emission sources of five main aspects in agricultural production, this paper applied the latest carbon emission coefficients released by Intergovernmental Panel on Climate Change of the UN (IPCC) and World Resources Institute (WRI), then used the ordered weighted aggregation (OWA) operator to remeasure agricultural carbon emissions in Fujian from 2008–2017. The results showed that the amount of agricultural carbon emissions in Fujian was 5541.95 × 103 tonnes by 2017, which means the average amount of agricultural carbon emissions in 2017 was 615.78 × 103 tonnes, with a decrease of 13.13% compared with that in 2008. In terms of spatial distribution, agricultural carbon emissions in the eastern coastal areas were less than those in the inland regions. Among them, the highest agricultural carbon emissions were in Zhangzhou, Nanping, and Sanming, while the lowest were in Xiamen, Putian, and Ningde. In addition, this paper selected six influencing variables, the research and development intensity, the proportion of agricultural labor force, the added value of agriculture, the agricultural industrial structure, the per capita disposable income of rural residents, and per capita arable land area, to clarify further the impacts on agricultural carbon emissions. Finally, geographically- and temporally-weighted regression (GTWR) was used to measure the direction and degree of the influences of factors on agricultural carbon emission. The conclusion showed that the regression coefficients of each selected factor in cities were positive or negative, which indicated that the impacts on agricultural carbon emission had the characteristics of geospatial nonstationarity.

scholarly journals Analysis of Influencing Factors of Carbon Emissions in China’s Logistics Industry: A GDIM-Based Indicator Decomposition

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5742
Author(s):  
Changyou Zhang ◽  
Wenyu Zhang ◽  
Weina Luo ◽  
Xue Gao ◽  
Bingchen Zhang
Keyword(s):  
Influencing Factors ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Added Value ◽  
Total Carbon ◽  
Carbon Intensity ◽  
Contribution Ratio ◽  
Logistics Industry ◽  
Per Capita ◽  
First Time

Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China’s logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry.

Carbon Emission of Mining Industry’s Energy Consumption in Heilongjiang Province

2015 ◽  
Vol 1092-1093 ◽  
pp. 1597-1600
Author(s):  
Zhong Hua Wang ◽  
Xin Ye Chen
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Mining Industry ◽  
Calculation Model ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Heilongjiang Province ◽  
Low Carbon

The need to reduce carbon emission in Heilongjiang Province of China is urgent challenge facing sustainable development. This paper aims to make explicit the problem-solving of carbon emission to find low carbon emission ways. According to domestic and foreign literatures on estimating and calculating carbon emissions and by integrating calculation methods of carbon emissions, it was not possible to consider all of the many contributions to carbon emissions. Calculation model of carbon emissions suitable to this paper is selected. The carbon emissions of energy consumption in mining industry are estimated and calculated from 2005 to 2012, and the characteristics of carbon emission are analyzed at the provincial level. It makes the point that carbon emissions of energy consumption in mining industry can be reduced when we attempt to alter energy consumption structure, adjust industrial structure and improve energy utilization efficiency.

Research on the Relationship between Economic Growth, Environmental Governance Investment and Carbon Emission--Based on the Time Series Data from 2000 to 2019

2020 ◽  
pp. 713-727
Author(s):  
Xiaohui Wang, Xin Zhang
Keyword(s):  
Economic Growth ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
Environmental Governance ◽  
Time Series Data ◽  
Series Data ◽  
Per Capita ◽  
The Relationship

The study on the relationship between investment in environmental governance, carbon emission and economic growth is helpful for the relevant government departments to coordinate the influence among them when formulating the policies of reducing emission and conserving energy, so as to take the comparative advantages of various factors and promote the benign interaction between economic development and environmental governance. In this paper, the data of Per capita GDP, per capita investment in environmental governance and per capita CARBON dioxide emissions in China from 2000 to 2019 are selected as the research basis, and variables are studied by means of Granger causality and impulse response function. As shown in the results, there is a single Granger relationship between investment in environmental governance and carbon emissions, that is, the increase of investment in environmental governance leads to the reduction of carbon emissions. The influence of economic growth on environmental governance investment is small, but in the long term, it can restrain the growth of carbon emissions. Investment in environmental governance can promote economic growth and stimulate a reduction in the emissions in the short term; Economic growth was hindered by the emissions in the long term and fail to stimulate increased investment in environmental governance. Based on these findings, this paper proposes policy Suggestions for optimizing the structure of environmental governance investment, improving the carbon emission monitoring and response mechanism, and strengthening the technological level of energy conservation and emission reduction.

scholarly journals Factors Affecting Energy-Related Carbon Emissions in Beijing-Tianjin-Hebei Region

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
Jing-min Wang ◽  
Yu-fang Shi ◽  
Xue Zhao ◽  
Xue-ting Zhang
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Structure ◽  
Factors Affecting ◽  
Economic Output ◽  
Level Model ◽  
The Impact ◽  
The Relationship

Beijing-Tianjin-Hebei is a typical developed region in China. The development of economy has brought lots of carbon emissions. To explore an effective way to reduce carbon emissions, we applied the Logarithmic Mean Divisia Index (LMDI) model to find drivers behind carbon emission from 2003 to 2013. Results showed that, in Beijing, Tianjin, and Hebei, economic output was main contributor to carbon emissions. Then we utilized the decoupling model to comprehensively analyze the relationship between economic output and carbon emission. Based on the two-level model, results indicated the following: (1) Industry sector accounted for almost 80% of energy consumption in whole region. The reduced proportion of industrial GDP will directly reduce the carbon emissions. (2) The carbon factor for CO2/energy in whole region was higher than that of Beijing and Tianjin but lower than that of Hebei. The impact of energy structure on carbon emission depends largely on the proportion of coal in industry. (3) The energy intensity in whole region decreased from 0.79 in 2003 to 0.40 in 2013 (unit: tons of standard coal/ten thousand yuan), which was lower than national average. (4) The cumulative effects of industrial structure, energy structure, and energy intensity were negative, positive, and negative, respectively.

Cost Analysis of Carbon Emission Based on Carbon Finance

2014 ◽  
Vol 1065-1069 ◽  
pp. 3030-3034
Author(s):  
Nai Ping Zhu ◽  
Qi Zhao ◽  
Yang Shen
Keyword(s):  
Carbon Emissions ◽  
Cost Estimation ◽  
Carbon Emission ◽  
Cost Control ◽  
Added Value ◽  
Estimation Model ◽  
Factors Affecting ◽  
Cost Estimation Model ◽  
Carbon Finance ◽  
The Cost

For the purpose of encouraging enterprises to save energy and reduce emissions from the internal demand and providing insight and inspiration to future study,this article not only describes the carbon finance coefficient model based on factors related to carbon finance but also establishes cost estimation model of carbon emissions according to the factors affecting the cost of carbon emissions and carbon finance coefficient.The resulted shows that carbon emissions currency cost namely the monetary costs of carbon emissions is the market value and the currency value of carbon emissions cost based on the financial market conditions.The result of the present work introduces that the cost of carbon emission has a correlation with prevention costs,cost control,carbon content,industrial added value,carbon finance index and so on so that governments and enterprises should take some measures such as perfecting carbon finance system and setting up the cost control of system consciousness to reduce the cost of carbon emissions and protect our environment.

Energy Consumption and Structural Reformation in Chinese Northeast Old Industrial Base

2013 ◽  
Vol 448-453 ◽  
pp. 4281-4284 ◽  
Author(s):  
Shao Bo Liu
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Energy Utilization ◽  
Energy Structure ◽  
Energy Technology ◽  
Industrial Base ◽  
Old Industrial Base ◽  
Emissions Intensity

Using IPCC methodology, the carbon emissions of Chinese Northeast Old Industrial Base is calculated, and the energy's synthesized impact on carbon emissions intensity is presented. The resulting shows that the carbon emissions in the three northeast provinces decreased 52.87% from 2000 to 2010, of which, Liaoning, Jilin and Heilongjiang are individually 60.09%, 45.47% and 54.14% lower. The implications are that the energy structure is one of the main factors in carbon emission in the Old Industrial Base of Northeast China, and its industrial structure is changing greatly due to energy consumption carbon emission. To adjust optimally the energy and industrial structure, and to develop the energy technology to promote energy utilization are recommended.

scholarly journals The carbon emissions of Chinese cities

2012 ◽  
Vol 12 (14) ◽  
pp. 6197-6206 ◽  
Author(s):  
H. Wang ◽  
R. Zhang ◽  
M. Liu ◽  
J. Bi
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
National Policy ◽  
Emission Inventories ◽  
Chinese Cities ◽  
Industrial Energy ◽  
Per Capita ◽  
Policy Priority

Abstract. As increasing urbanization has become a national policy priority for economic growth in China, cities have become important players in efforts to reduce carbon emissions. However, their efforts have been hampered by the lack of specific and comparable carbon emission inventories. Comprehensive carbon emission inventories for twelve Chinese cities, which present both a relatively current snapshot and also show how emissions have changed over the past several years, were developed using a bottom-up approach. Carbon emissions in most Chinese cities rose along with economic growth from 2004 to 2008. Yet per capita carbon emissions varied between the highest and lowest emitting cities by a factor of nearly 7. Average contributions of sectors to per capita emissions for all Chinese cities were 65.1% for industrial energy consumption, 10.1% for industrial processes, 10.4% for transportation, 7.7% for household energy consumption, 4.2% for commercial energy consumption and 2.5% for waste processing. However, these shares are characterized by considerable variability due to city-specific factors. The levels of per capita carbon emissions in China's cities were higher than we anticipated before comparing them with the average of ten cities in other parts of the world. This is mainly due to the major contribution of the industry sector in Chinese cities.

scholarly journals Symmetric and Asymmetric Impact of Poverty, Income Inequality, and Population on Carbon Emission in Pakistan: New Evidence From ARDL and NARDL Co-Integration

2021 ◽  
Vol 9 ◽  
Author(s):  
Salim Khan ◽  
Wang Yahong
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Environmental Degradation ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Policy Implications ◽  
Gdp Per Capita ◽  
Long Run ◽  
Asymmetric Impact ◽  
Per Capita

Several researchers have studied the relationship between poverty and environmental degradation, as these concerns are remained at top priority in achieving Sustainable Development Goals (SDGs). However, the symmetric and asymmetric impact of poverty and income inequality along with population and economic growth on carbon emissions (CO2e) has not been studied in the case of Pakistan. For this purpose, the short and long-run impact of poverty, income inequality, population, and GDP per capita on CO2e investigated by applying the Autoregressive Distributive Lag (ARDL) along with Non-linear Autoregressive Distributive Lag (NARDL) co-integration approach in the context of Pakistan for period 1971–2015. The symmetric results of the current study show poverty and population density along with GDP per capita increase carbon emissions in both the short and long-run, while income inequality has no impact on carbon emissions in the short-run. While in the long-run the symmetric results show that income inequality weakens environmental degradation in terms of carbon emissions. The analysis of NARDL also supports the results obtained from ARDL and suggests a positive effect of poverty, population, and economic growth on carbon emission in Pakistan. The empirical findings of the current study provide policy implications in light of the United Nation's SDGs for the development of Pakistan.

scholarly journals Understanding the Driving Patterns of the Carbon Emissions in Transport Sector in China: A Panel Data Analysis and Zoning Effect

2018 ◽  
Author(s):  
Danting Lin ◽  
Rongzu Qiu ◽  
Xisheng Hu ◽  
Jiankai Wang ◽  
Lanyi Zhang ◽  
...  
Keyword(s):  
Panel Data ◽  
Carbon Emissions ◽  
Inner Mongolia ◽  
Carbon Emission ◽  
Driving Forces ◽  
Panel Data Analysis ◽  
Transport Sector ◽  
Significant Variable ◽  
Provincial Level ◽  
Per Capita

China’s transportation industry has made rapid progress, which has led to a mass of carbon emissions. However, it is still unclear how the carbon emission from transport sector is punctuated by shifts in underlying drivers. This paper aims to examine the process of China’s carbon emissions from transport sector as well as its major driving forces during the period of 2000 to 2015 at the provincial level. We firstly estimate the carbon emissions from transport sector at the provincial level based on the fuel and electricity consumption using a top-down method. We find that the carbon emission per capita is steadily increasing across the nation, especially in the provinces of Chongqing and Inner Mongolia. However, the carbon emission intensity is decreasing in most provinces of China, except in Yunnan, Qinghai, Chongqing, Zhejiang, Heilongjiang, Jilin, Inner Mongolia, Henan and Anhui. We then quantify the effect of socio-economic factors and their regional variations on the carbon emissions using panel data model. The results show that the development of secondary industry is the most significant variable in both the entire nation level and the regional level, while the effects of the other variables vary across regions. Among these factors, population density is the main motivator of the increasing carbon emissions per capita from transport sector for both the whole nation and the western region, whereas the consumption level per capita of residents and the development of tertiary industry are the primary drivers of per capita carbon emissions for the eastern and central region.

scholarly journals Characterizing the Drivers of Global Food Trade Growth in 21th Century

2019 ◽  
Vol 11 (10) ◽  
pp. 14
Author(s):  
Silvia Andrés González-Moralejo ◽  
Juan Francisco López Miquel
Keyword(s):  
Global Economy ◽  
Agricultural Sector ◽  
Driving Forces ◽  
Descriptive Analysis ◽  
Relevant Information ◽  
Added Value ◽  
Developed Economies ◽  
Global Demand ◽  
Per Capita ◽  
Food Imports

21st century is characterised by a steady growth in the global demand for basic foodstuffs. This paper reviews the drivers of this growth, through a descriptive analysis of the main literature on the subject, in order to synthesize the most relevant information generated by researchers and position the current state of the issue. The results of the analysis suggest that emerging economies have taken over in the increase of food imports; this is due to the potential of countries such as China, India, Brazil and Russia, which have become propellers of the global economy. From the developing countries, the increase in population and income are the driving forces behind the dynamism of world food demand, whose direct consequences are the increase in per capita consumption, the acceleration of the urbanization process in these regions and the increase in the consumption of products with greater added value. In developed economies, increases in per capita income do not translate into increases in the demand for food; rather, its role with respect to global demand is to promote it as they deepen the production of biofuels, the liberalization of the agricultural sector and the signing of trade agreements. Finally, the work concludes by warning about the uncertainties that surround the demand for food imports, including the crucial role played by climate change.

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