Spatio-temporal evolutionary characteristics of carbon emissions and carbon sinks of marine industry in China and their time-dependent models

Marine Policy ◽  
2022 ◽  
Vol 135 ◽  
pp. 104879
Author(s):  
Jinghui Wu ◽  
Bo Li
Keyword(s):  
Carbon Emissions ◽  
Time Dependent ◽  
Carbon Sinks ◽  
Marine Industry ◽  
Spatio Temporal

scholarly journals The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China

2021 ◽  
Vol 18 (2) ◽  
pp. 705
Author(s):  
Hongpeng Guo ◽  
Sidong Xie ◽  
Chulin Pan
Keyword(s):  
Carbon Emissions ◽  
Structural Changes ◽  
Multiple Linear Regression Model ◽  
Industry Structure ◽  
Estimation Methods ◽  
Low Carbon ◽  
Carbon Sinks ◽  
Resource Endowment ◽  
The Government ◽  
The Impact

This paper focuses on the impact of changes in planting industry structure on carbon emissions. Based on the statistical data of the planting industry in three provinces in Northeast China from 1999 to 2018, the study calculated the carbon emissions, carbon absorptions and net carbon sinks of the planting industry by using crop parameter estimation and carbon emissions inventory estimation methods. In addition, the multiple linear regression model and panel data model were used to analyze and test the carbon emissions and net carbon sinks of the planting industry. The results show that: (1). The increase of the planting area of rice, corn, and peanuts in the three northeastern provinces of China will promote carbon emissions, while the increase of the planting area of wheat, sorghum, soybeans, and vegetables will reduce carbon emissions; (2). Fertilizer application, technological progress, and planting structure factors have a significant positive effect on net carbon sinks, among which the changes in the planting industry structure have the greatest impact on net carbon sinks. Based on the comprehensive analysis, it is suggested that, under the guidance of the government, resource endowment and location advantages should be given full play to, and the internal planting structure of crops should be reasonably adjusted so as to promote the development of low-carbon agriculture and accelerate the development process of agricultural modernization.

scholarly journals Land Economic Efficiency and Improvement of Environmental Pollution in the Process of Sustainable Urbanization: Case of Eastern China

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 845
Author(s):  
Binbin Chang ◽  
Lei Chen
Keyword(s):  
Land Use ◽  
Environmental Pollution ◽  
Carbon Emissions ◽  
Temporal Evolution ◽  
Eastern China ◽  
Land Resources ◽  
Land Use Efficiency ◽  
Use Efficiency ◽  
Spatio Temporal ◽  
Land Economic

Economic development, environmental protection and land resources are important components in sustainable cities. According to the environmental Kuznets curve, developing countries are prone to environmental pollution problems while developing their economies. At the same time, as urbanization progresses, the problem of inadequate land resources and land use efficiency in China is coming to the fore. Although China is a developing country, it began to actively implement environmental protection measures years ago in an effort to transform itself into an innovative country. Therefore, as an economic and policy pioneer region, can eastern China benefit from all three aspects of land–economy–environment at the same time? Or will the increase in land economic efficiency (Land_EcoE) and the improvement of environmental pollution occur simultaneously? With the characteristics of land use efficiency and other concepts, this study combines economic factors and land factors to establish a Land_EcoE evaluation system. On the basis of mapping the spatio-temporal evolution of carbon emissions and Land_EcoE, and discussing the spatio-temporal evolution characteristics and correlation between them initially and visually by means of geographic data visualization, this study uses the data of 84 prefecture-level cities and municipalities directly under the central government in eastern China from 2011 to 2017 to test the research hypotheses from a quantitative perspective. Specifically, this study analyzes the correlation between Land_EcoE and environmental pollution by constructing a panel regression model. The conclusions show that, in general, the increase in Land_EcoE in eastern China is associated with the increase in carbon emissions. For a group of prefecture-level cities with the most developed economies in eastern China, the increase in Land_EcoE is correlated with the decrease in carbon emissions. Based on this research, this study proposes a series of policy implications on how to promote simultaneous economic–land–environmental benefits.

Turing and Benjamin–Feir instability mechanisms in non-autonomous systems

2020 ◽  
Vol 476 (2238) ◽  
pp. 20200003 ◽  
Author(s):  
Robert A. Van Gorder
Keyword(s):  
Autonomous Systems ◽  
Reaction Diffusion ◽  
Reaction Rates ◽  
Time Dependent ◽  
Model Parameters ◽  
Time Varying ◽  
Reaction Diffusion Systems ◽  
Diffusion Systems ◽  
Dependent Model ◽  
Spatio Temporal

The Turing and Benjamin–Feir instabilities are two of the primary instability mechanisms useful for studying the transition from homogeneous states to heterogeneous spatial or spatio-temporal states in reaction–diffusion systems. We consider the case when the underlying reaction–diffusion system is non-autonomous or has a base state which varies in time, as in this case standard approaches, which rely on temporal eigenvalues, break down. We are able to establish respective criteria for the onset of each instability using comparison principles, obtaining inequalities which involve the in general time-dependent model parameters and their time derivatives. In the autonomous limit where the base state is constant in time, our results exactly recover the respective Turing and Benjamin–Feir conditions known in the literature. Our results make the Turing and Benjamin–Feir analysis amenable for a wide collection of applications, and allow one to better understand instabilities emergent due to a variety of non-autonomous mechanisms, including time-varying diffusion coefficients, time-varying reaction rates, time-dependent transitions between reaction kinetics and base states which change in time (such as heteroclinic connections between unique steady states, or limit cycles), to name a few examples.

scholarly journals Spatio-Temporal Clustering of Time-Dependent Origin-Destination Electronic Trace Data

2018 ◽  
Vol 130 ◽  
pp. 359-367
Author(s):  
Daphne van Leeuwen ◽  
Joost Bosman ◽  
Elenna Dugundji
Keyword(s):  
Time Dependent ◽  
Trace Data ◽  
Temporal Clustering ◽  
Spatio Temporal

The RC Analogy Provides a Versatile Computational Tool for Unsteady, Unidirectional Heat Conduction in Regular Solid Bodies Cooled by Adjoining Fluids

2003 ◽  
Vol 31 (3) ◽  
pp. 233-244
Author(s):  
Antonio Campo ◽  
Francisco Alhama
Keyword(s):  
Heat Transfer ◽  
Initial Conditions ◽  
Simulation Method ◽  
Heat Fluxes ◽  
Total Heat ◽  
Time Dependent ◽  
Total Heat Transfer ◽  
Transfer Rates ◽  
Electric Circuits ◽  
Spatio Temporal

Evaluation of spatio-temporal temperatures and total heat transfer rates in simple bodies (large plate, long cylinder and sphere) has been traditionally explained in undergraduate courses of heat transfer by the Heisler/Gröber or by the Boelter/Gröber charts. These three charts pose some restrictions with respect to the applicable times. Additionally, the charts do not provide information about the time-dependent heat fluxes at the surface. Conversely, evaluation of spatio-temporal temperatures, time-dependent heat fluxes at the surface and total heat transfer rates can be easily done for the entire time domain with the network simulation method (NSM) in conjunction with the commercial code PSPICE. NSM relies on the existing physical analogy between the unsteady transport of electric current and the unsteady transport of unidirectional heat by conduction. This analogy has been named the RC analogy in the specialized literature. The code PSPICE simulates the electric circuits for a specific body together with the imposed boundary and initial conditions, and produces numerical results for the quantities of interest, such as: the spatio-temporal temperature distributions; the time-dependent heat flux distributions at the surface; and the total heat transfer.

scholarly journals The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8169
Author(s):  
Zaijun Li ◽  
Xiang Zheng ◽  
Dongqi Sun
Keyword(s):  
Spatial Correlation ◽  
Carbon Emissions ◽  
Yangtze River ◽  
Temporal Correlation ◽  
Yangtze River Delta ◽  
River Delta ◽  
Direct And Indirect Effects ◽  
The Yangtze River ◽  
Spatio Temporal ◽  
The Yangtze River Delta

A low-carbon economy is the most important requirement to realize high-quality integrated development of the Yangtze River Delta. Utilizing the following models: a super-efficiency slacks-based measure model, a spatio-temporal correlation model, a bivariate LISA model, a spatial econometric model, and a geographically weighted random forest model, this study measured urban industrial eco-efficiency (IEE) and then analyzed its influencing effects on carbon emission in the Yangtze River Delta from 2000 to 2017. The influencing factors included spatio-temporal correlation intensity, spatio-temporal association type, direct and indirect impacts, and local importance impacts. Findings showed that: (1) The temporal correlation intensity between IEE and scale efficiency (SE) and carbon emissions exhibited an inverted V-shaped variation trend, while the temporal correlation intensity between pure technical efficiency (PTE) and carbon emissions exhibited a W-shaped fluctuation trend. The negative spatial correlation between IEE and carbon emissions was mainly distributed in the developed cities of the delta, while the positive correlation was mainly distributed in central Anhui Province and Yancheng and Taizhou cities. The spatial correlation between PTE and carbon emissions exhibited a spatial pattern of being higher in the central part of the delta and lower in the northern and southern parts. The negative spatial correlation between SE and carbon emissions was mainly clustered in Zhejiang Province and scattered in Jiangsu and Anhui provinces, with the cities with positive correlations being concentrated around two locations: the junction of Anhui and Jiangsu provinces, and within central Jiangsu Province. (2) The direct and indirect effects of IEE on carbon emissions were significantly negative, indicating that IEE contributed to reducing carbon emissions. The direct impact of PTE on carbon emissions was also significantly negative, while its indirect effect was insignificant. Both the direct and indirect effects of SE on carbon emissions were significantly negative. (3) It was found that the positive effect of IEE was more likely to alleviate the increase in carbon emissions in northern Anhui City. Further, PTE was more conducive to reducing the increase in carbon emissions in northwestern Anhui City, southern Zhejiang City, and in other cities including Changzhou and Wuxi. Finally, it was found that SE played a relatively important role in reducing the increase in carbon emissions only in four cities: Changzhou, Suqian, Lu’an, and Wenzhou.

scholarly journals Study of the Spatio-Temporal Differentiation of Factors Influencing Carbon Emission of the Planting Industry in Arid and Vulnerable Areas in Northwest China

2019 ◽  
Vol 17 (1) ◽  
pp. 187
Author(s):  
Yujie Huang ◽  
Yang Su ◽  
Ruiliang Li ◽  
Haiqing He ◽  
Haiyan Liu ◽  
...  
Keyword(s):  
Carbon Emissions ◽  
Carbon Emission ◽  
Agricultural Development ◽  
Inflection Point ◽  
Turning Point ◽  
Northwest China ◽  
Kuznets Curve ◽  
Similar Time ◽  
Average Value ◽  
Spatio Temporal

Due to the importance of understanding the relationship between agricultural growth and environmental quality, we analyzed how high-quality agricultural development can affect carbon emissions in Northwest China. Based on the concept of the environmental Kuznets curve, this study uses provincial panel data from 1993 to 2017 to make empirical analyses inflection point changes and spatio-temporal differences in agricultural carbon emissions. The highlights of our findings are as follows: (1) In Northwest China, there is an inverse N-shape curve, and the critical values are 3578 yuan/hm2 and 45,738 yuan/hm2, respectively. (2) For 2017, the agricultural economic intensity was 50,670 yuan/hm2, exceeding the critical value (high inflection point) of 45,738 yuan/hm2. (3) Ningxia, Gansu, and Qinghai have not reached the turning point. Having comparable climate, natural conditions, and overall environmental factors, these three provinces would reach the turning point at similar time periods. (4) The average value in agricultural carbon emission intensity in the region is 767.79 kg/hm2, and the order based on intensity is Xinjiang > Shaanxi > Ningxia > Gansu > Qinghai.

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