The Evolution of the Spatial Association Effect of Carbon Emissions in Transportation: A Social Network Perspective

The association effect between provincial transportation carbon emissions has become an important issue in regional carbon emission management. This study explored the relationship and development trends associated with regional transportation carbon emissions. A social network method was used to analyze the structural characteristics of the spatial association of transportation carbon emissions. Indicators for each of the structural characteristics were selected from three dimensions: The integral network, node network, and spatial clustering. Then, this study established an association network for transportation carbon emissions (ANTCE) using a gravity model with China’s provincial data during the period of 2007 to 2016. Further, a block model (a method of partitioning provinces based on the information of transportation carbon emission) was used to group the ANTCE network of inter-provincial transportation carbon emissions to examine the overall association structure. There were three key findings. First, the tightness of China’s ANTCE network is growing, and its complexity and robustness are gradually increasing. Second, China’s ANTCE network shows a structural characteristic of “dense east and thin west.” That is, the transportation carbon emissions of eastern provinces in China are highly correlated, while those of central and western provinces are less correlated. Third, the eastern provinces belong to the two-way spillover or net benefit block, the central regions belong to the broker block, and the western provinces belong to the net spillover block. This indicates that the transportation carbon emissions in the western regions are flowing to the eastern and central regions. Finally, a regression analysis using a quadratic assignment procedure (QAP) was used to explore the spatial association between provinces. We found that per capita gross domestic product (GDP) and fixed transportation investments significantly influence the association and spillover effects of the ANTCE network. The research findings provide a theoretical foundation for the development of policies that may better coordinate carbon emission mitigation in regional transportation.

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The Spatial Network Structure of China’s Regional Carbon Emissions and Its Network Effect

Energies ◽

10.3390/en11102706 ◽

2018 ◽

Vol 11 (10) ◽

pp. 2706 ◽

Cited By ~ 5

Author(s):

Feng Wang ◽

Mengnan Gao ◽

Juan Liu ◽

Wenna Fan

Keyword(s):

Network Structure ◽

Carbon Emissions ◽

Carbon Emission ◽

Geographical Location ◽

Network Effect ◽

Quadratic Assignment ◽

Spatial Correlations ◽

Emission Data ◽

Correlation Relationship ◽

Four Blocks

Under the “new normal”, China is facing more severe carbon emissions reduction targets. This paper estimates the carbon emission data of various provinces in China from 2008 to 2014, constructs a revised gravity model, and analyzes the network structure and effects of carbon emissions in various provinces by using social network analysis (SNA) and quadratic assignment procedure (QAP) analysis methods. The conclusions show that there are obvious spatial correlations between China’s provinces and regions in terms of carbon emissions: Tianjin, Shanghai, Zhejiang, Jiangsu and Guangdong are in the center of the carbon emission network, and play the role of “bridges”. Carbon emissions can be divided into four blocks: “bidirectional spillover block”, “net beneficial block”, “net spillover block” and “broker block”. The differences in the energy consumption, economic level and geographical location of the provinces have a significant impact on the spatial correlation relationship of carbon emissions. Finally, the improvement of the robustness of the overall network structure and the promotion of individual network centrality can significantly reduce the intensity of carbon emissions.

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Inter-Regional Spillover of Carbon Emissions and Employment in China: Is It Positive or Negative?

Sustainability ◽

10.3390/su11133622 ◽

2019 ◽

Vol 11 (13) ◽

pp. 3622 ◽

Cited By ~ 3

Author(s):

Wenbin Shao ◽

Fangyi Li ◽

Zhaoyang Ye ◽

Zhipeng Tang ◽

Wu Xie ◽

...

Keyword(s):

Economic Development ◽

Carbon Emissions ◽

Decomposition Method ◽

Carbon Emission ◽

Spillover Effects ◽

Efficiency Improvement ◽

Input Output ◽

Coastal Regions ◽

Regional Trade ◽

Positive Spillover

International and inter-regional trade in China has been promoted, the economic and environmental impacts of which are significant in regional development. In this paper, we analyzed the evolution of inter-regional spillover of carbon emissions and employment in China from 2007 to 2012 with structural decomposition method and multi-regional input-output tables. The index of carbon emission per employee (ICE) is designed and compared to indicate positive or negative spillover effects. We find that carbon emissions grow much more rapidly in interior regions than in coastal regions, due to spillover effects and own influences. Spillover effects rarely reduce the ICE of destination regions, but the own influences can decrease it in most regions. Although spillover may contribute to economic development in most regions, it is hardly a driver of efficiency improvement in destination regions. Based on these empirical findings, we put forward specific suggestions to improve the positive spillover effects on different kinds of regions.

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Spatial Association Effect of Haze Pollution in Cheng-Yu Urban Agglomeration

Scientific Reports ◽

10.1038/s41598-020-66665-8 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Degang Zhang ◽

Yuanquan Lu ◽

Yuan Tian

Keyword(s):

Structural Characteristics ◽

Spatial Association ◽

Spillover Effects ◽

Urban Agglomeration ◽

Association Network ◽

Causality Test ◽

Spatial Spillover ◽

Haze Pollution ◽

Spatial Spillover Effects ◽

Four Blocks

Abstract This study takes a network perspective to examine the spatial spillover effects of haze pollution in Cheng-Yu urban agglomeration which is the fourth largest urban agglomeration and a comprehensive demonstration zone of new urbanization in China. Firstly, we use Granger causality test to construct haze pollution spatial association network, and then we apply social network analysis to reveal the structural characteristics of this network. The results show that: haze pollution in Cheng-Yu urban agglomeration is a complex multithreaded network. Chongqing, Chengdu, Guang’an, Luzhou, Deyang and Nanchong are the centers of the network, sending and transmitting the most relationships. The haze pollution spatial association network can be divided into net beneficiary block, net overflow block, bilateral overflow block and broker block. These four blocks present obvious geographical distribution characteristics and are partly related to the difference of urbanization. The above results contribute by illustrating the current spatial spillover situation of haze pollution and provide a theoretical foundation for the government that it should simultaneously consider cities’ statues and their spatial spillover effects in the network rather than simple geographic proximity when formulating future haze pollution control policies in urban agglomeration.

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Analysis and Measurement of Carbon Emission Aggregation and Spillover Effects in China: Based on a Sectoral Perspective

Sustainability ◽

10.3390/su12218966 ◽

2020 ◽

Vol 12 (21) ◽

pp. 8966

Author(s):

Jinpeng Liu ◽

Delin Wei

Keyword(s):

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

Decomposition Analysis ◽

Life Cycle Management ◽

Spillover Effects ◽

Current Status ◽

Economic Sectors ◽

National Economic ◽

The Impact

Faced with the environmental pressure of global warming, China has achieved certain results in emission reduction, but this needs to be completed more efficiently. Therefore, this article conducts a more comprehensive and in-depth study of China’s carbon emissions from the perspective of the development of national economic sectors and taps the potential for emission reduction in various sectors. Taking into account the adjustment of the national economic sector and the current status of carbon emissions, the study period was from 2003 to 2017. The logarithmic mean Divisia index (LMDI) method was used to measure and analyze the impact of seven factors, including urban construction conditions, on the carbon emissions of various sectors. According to the commonalities and differences of the impacts, 42 sectors were aggregated into four categories. At the same time, the input–output structure decomposition analysis (IO–SDA) model was used to analyze the spillover effects of intersectoral carbon emissions. According to the research results, based on the characteristics of the four types of sectors, and fully considering the spillover effects, the improvement of life cycle management to control energy consumption in the entire supply chain was taken as the leading idea. Moreover, combined with the actual development situation, four types of sectoral carbon emission reduction paths and optimization strategies are proposed to establish a more sustainable demand structure in order to achieve emission reduction.

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Complex Network Analysis of Carbon Emission Transfers under Global Value Chains

10.21203/rs.3.rs-1084334/v1 ◽

2021 ◽

Author(s):

Yanfang Wang ◽

Jingmin Yao

Keyword(s):

Network Analysis ◽

Complex Network ◽

Carbon Emissions ◽

Carbon Emission ◽

High Income ◽

Reverse Direction ◽

Quadratic Assignment ◽

Bipolar Structure ◽

Complex Network Analysis ◽

Emission Transfers

Abstract Accompanied with the increasing complicated global value chain (GVC) networks is the carbon emission transfers among countries. Utilizing the complex network analysis alongside quadratic assignment procedure (QAP), this paper detects the community structure and influencing forces of the emission transfers under GVCs. The results imply that the bipolar structure of the network transformed gradually to tripolar owing largely to the surging of carbon emissions from China. Evidence on the existence of environmental Kuznets curve (EKC) in the emission transfers from high-income countries to low-income countries, and a U-shape relationship in the transfers in the reverse direction, suggesting that growing carbon emissions from both low- and high-income countries transferred to other high-income countries gradually. Gaps in technology, especially in patent applications, between source and destination countries played an important role therein. JEL: F14, F18, Q56, R15

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Carbon Emission Estimation of Assembled Composite Concrete Beams during Construction

Energies ◽

10.3390/en14071810 ◽

2021 ◽

Vol 14 (7) ◽

pp. 1810

Author(s):

Kaitong Xu ◽

Haibo Kang ◽

Wei Wang ◽

Ping Jiang ◽

Na Li

Keyword(s):

Life Cycle ◽

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

Composite Beams ◽

Total Carbon ◽

Construction Process ◽

Low Carbon ◽

Carbon Emission Reduction ◽

The Government

At present, the issue of carbon emissions from buildings has become a hot topic, and carbon emission reduction is also becoming a political and economic contest for countries. As a result, the government and researchers have gradually begun to attach great importance to the industrialization of low-carbon and energy-saving buildings. The rise of prefabricated buildings has promoted a major transformation of the construction methods in the construction industry, which is conducive to reducing the consumption of resources and energy, and of great significance in promoting the low-carbon emission reduction of industrial buildings. This article mainly studies the calculation model for carbon emissions of the three-stage life cycle of component production, logistics transportation, and on-site installation in the whole construction process of composite beams for prefabricated buildings. The construction of CG-2 composite beams in Fujian province, China, was taken as the example. Based on the life cycle assessment method, carbon emissions from the actual construction process of composite beams were evaluated, and that generated by the composite beam components during the transportation stage by using diesel, gasoline, and electric energy consumption methods were compared in detail. The results show that (1) the carbon emissions generated by composite beams during the production stage were relatively high, accounting for 80.8% of the total carbon emissions, while during the transport stage and installation stage, they only accounted for 7.6% and 11.6%, respectively; and (2) during the transportation stage with three different energy-consuming trucks, the carbon emissions from diesel fuel trucks were higher, reaching 186.05 kg, followed by gasoline trucks, which generated about 115.68 kg; electric trucks produced the lowest, only 12.24 kg.

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Examining the Driving Factors of the Direct Carbon Emissions of Households in the Ebinur Lake Basin Using the Extended STIRPAT Model

Sustainability ◽

10.3390/su13031339 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1339

Author(s):

Ziyuan Chai ◽

Zibibula Simayi ◽

Zhihan Yang ◽

Shengtian Yang

Keyword(s):

Energy Consumption ◽

Carbon Emissions ◽

Carbon Emission ◽

Driving Factors ◽

Series Data ◽

Lake Basin ◽

Stirpat Model ◽

Consumption Structure ◽

Ebinur Lake ◽

Ebinur Lake Basin

In order to achieve the carbon emission reduction targets in Xinjiang, it has become a necessary condition to study the carbon emission of households in small and medium-sized cities in Xinjiang. This paper studies the direct carbon emissions of households (DCEH) in the Ebinur Lake Basin, and based on the extended STIRPAT model, using the 1987–2017 annual time series data of the Ebinur Lake Basin in Xinjiang to analyze the driving factors. The results indicate that DCEH in the Ebinur Lake Basin during the 31 years from 1987 to 2017 has generally increased and the energy structure of DCEH has undergone tremendous changes. The proportion of coal continues to decline, while the proportion of natural gas, gasoline and diesel is growing rapidly. The main positive driving factors affecting its carbon emissions are urbanization, vehicle ownership and GDP per capita, while the secondary driving factor is residents’ year-end savings. Population, carbon intensity and energy consumption structure have negative effects on carbon emissions, of which energy consumption structure is the main factor. In addition, there is an environmental Kuznets curve between DCEH and economic development, but it has not yet reached the inflection point.

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Linked in Life and Death: A Note on the Effect of Parental Death on Sibling Relations in Young and Middle Adulthood

Journal of Family Issues ◽

10.1177/0192513x20985566 ◽

2021 ◽

pp. 0192513X2098556

Author(s):

Karsten Hank

Keyword(s):

Family Relationships ◽

Fixed Effects ◽

Family System ◽

Parental Death ◽

Spillover Effects ◽

Three Dimensions ◽

Life And Death ◽

Sibling Relations ◽

Fixed Effects Regression ◽

Parent Child

Despite the important role of adult parent–child and sibling relations in the family system, only few studies have investigated yet, how the common adult experience of parental death impacts sibling relations. Estimating fixed-effects regression models using four waves of data from the German Family Panel (pairfam; n = 4,123 respondents), the present note focused on changes in three dimensions of adult siblings’ relationship qualities following the first parent’s death. Our analysis revealed a short-term positive effect of parental death on sibling contacts as well as longer-lasting increases in emotional closeness and conflicts. Next to an intensification of sibling relations following the first parent’s death, we also detected significant spillover effects from respondents’ relationship with the surviving parent to their sibling relations. Our analysis thus provided evidence for adult parent–child and sibling relations to be “linked in life and death,” underlining the benefits of jointly analyzing intra- and intergenerational family relationships.

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Mitigating the Energy Consumption and the Carbon Emission in the Building Structures by Optimization of the Construction Processes

Energies ◽

10.3390/en14113287 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3287

Author(s):

Alireza Tabrizikahou ◽

Piotr Nowotarski

Keyword(s):

Life Cycle ◽

Energy Consumption ◽

Structural Optimization ◽

Carbon Emissions ◽

Carbon Emission ◽

Construction Materials ◽

High Energy ◽

Building Structures ◽

Life Cycle Stages ◽

Reduction Of Energy Consumption

For decades, among other industries, the construction sector has accounted for high energy consumption and emissions. As the energy crisis and climate change have become a growing concern, mitigating energy usage is a significant issue. The operational and end of life phases are all included in the building life cycle stages. Although the operation stage accounts for more energy consumption with higher carbon emissions, the embodied stage occurs in a time-intensive manner. In this paper, an attempt has been made to review the existing methods, aiming to lower the consumption of energy and carbon emission in the construction buildings through optimizing the construction processes, especially with the lean construction approach. First, the energy consumption and emissions for primary construction materials and processes are introduced. It is followed by a review of the structural optimization and lean techniques that seek to improve the construction processes. Then, the influence of these methods on the reduction of energy consumption is discussed. Based on these methods, a general algorithm is proposed with the purpose of improving the construction processes’ performance. It includes structural optimization and lean and life cycle assessments, which are expected to influence the possible reduction of energy consumption and carbon emissions during the execution of construction works.

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Consumer willingness-to-pay for restaurant surcharges to reduce carbon emissions: default and information effects

Agricultural and Resource Economics Review ◽

10.1017/age.2021.7 ◽

2021 ◽

pp. 1-29

Author(s):

Dede Long ◽

Grant H. West ◽

Rodolfo M. Nayga

Keyword(s):

Climate Change ◽

Willingness To Pay ◽

Contingent Valuation ◽

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

Dichotomous Choice ◽

Carbon Reduction ◽

The Mean ◽

Agriculture And Food

Abstract The agriculture and food sectors contribute significantly to greenhouse gas emissions. About 15 percent of food-related carbon emissions are channeled through restaurants. Using a contingent valuation (CV) method with double-bounded dichotomous choice (DBDC) questions, this article investigates U.S. consumers’ willingness to pay (WTP) for an optional restaurant surcharge in support of carbon emission reduction programs. The mean estimated WTP for a surcharge is 6.05 percent of an average restaurant check, while the median WTP is 3.64 percent. Our results show that individuals have a higher WTP when the surcharge is automatically added to restaurant checks. We also find that an information nudge—a short climate change script—significantly increases WTP. Additionally, our results demonstrate that there is heterogeneity in treatment effects across consumers’ age, environmental awareness, and economic views. Our findings suggest that a surcharge program could transfer a meaningful amount of the agricultural carbon reduction burden to consumers that farmers currently shoulder.

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