scholarly journals Truck Arrivals Scheduling with Vessel Dependent Time Windows to Reduce Carbon Emissions

2019 ◽  
Vol 11 (22) ◽  
pp. 6410 ◽  
Author(s):  
Mengzhi Ma ◽  
Houming Fan ◽  
Xiaodan Jiang ◽  
Zhenfeng Guo
Keyword(s):  
Carbon Dioxide ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Time Window ◽  
Container Terminal ◽  
Time Windows ◽  
Hybrid Genetic Algorithm ◽  
Total Carbon ◽  
Queuing Model ◽  
Marine Container Terminal

Irregular external truck arrivals at a marine container terminal often leads to long queues at gates and substantial greenhouse gas emissions. To relieve gate congestion and reduce carbon emissions, a new truck arrival pattern called “vessel dependent time windows (VDTWs)” is proposed. A two-phase queuing model is established to describe the queuing process of trucks at gate and yard. An optimization model is established to assign time window and appointment quota for each vessel in a marine container terminal running a terminal appointment system (TAS) with VDTWs. The objective is to minimize the total carbon dioxide emissions of trucks and rubber-tired gantry cranes (RTGCs) during idling. The storage capacity constraints of each block and maximum queue length are also taken into consideration. A hybrid genetic algorithm based on simulated annealing is developed to solve the problem. Results based on numerical experiments demonstrate that this model can substantially reduce the waiting time of trucks at gate and yard and carbon dioxide emissions of trucks and RTGCs during idling.

scholarly journals SUSTAINABLE GREEN CITY LOGISTIC SOLUTION FOR THE PRAGUE AGGLOMERATION AND RETAIL CHAIN

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Dana Sommerauerová ◽  
Jan Chocholač ◽  
Klara Urbanova
Keyword(s):  
Carbon Dioxide ◽  
Information And Communication Technologies ◽  
Carbon Dioxide Emissions ◽  
Time Windows ◽  
Communication Technologies ◽  
Business Environment ◽  
Total Carbon ◽  
Routing Problem ◽  
Information And Communication ◽  
Green City

During the 20th century, population growth and changes in the business environment also led  to a change in mobility requirements. Gradually, there was an increase in transport performance in the area of passenger and freight transport. These trends are also characteristic of the 21st century, when it is also possible to talk about the fundamental development of modern information and communication technologies. The sustainable and green city logistics deals with all transport (passenger and freight) and includes material and goods flows and movements of people inside and outside the city and agglomeration with respect to the sustainability pillars. This article deals with the possibilities of supplying Lidl Česká republika v.o.s. (hereinafter Lidl) stores in Prague agglomeration from the planned logistic centre in Buštěhrad. Two scenarios are tested in terms of total carbon dioxide emissions produced: standard way of distributing goods to stores (scenario A) and sustainable and green way of distributing goods to stores (scenario B). The scientific methods and approaches are used in this article, there are: scenario analysis, vehicle routing problem with pickup and delivery with time windows and carbon dioxide emissions calculation approaches.  

scholarly journals The Paradoxical Relationship between Renewable Energy and Economic Growth: A Cross-National Panel Study, 1990-2013

2017 ◽  
Vol 23 (2) ◽  
pp. 540-564 ◽  
Author(s):  
Ryan P Thombs
Keyword(s):  
Economic Growth ◽  
Carbon Dioxide ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Total Carbon ◽  
Renewable Energy Consumption ◽  
Negative Effect ◽  
Cross National

This cross-national study employs a time-series cross-sectional Prais-Winsten regression model with panel-corrected standard errors to examine the relationship between renewable energy consumption and economic growth, and its impact on total carbon dioxide emissions and carbon dioxide emissions per unit of GDP. Findings indicate that renewable energy consumption has its largest negative effect on total carbon emissions and carbon emissions per unit of GDP in low-income countries. Contrary to conventional wisdom, renewable energy has little influence on total carbon dioxide emissions or carbon dioxide emissions per unit of GDP at high levels of GDP per capita. The findings of this study indicate the presence of a “renewable energy paradox,” where economic growth becomes increasingly coupled with carbon emissions at high levels of renewable energy, and the negative effect of economic growth on carbon emissions per unit of GDP lessens as renewable energy increases. These findings suggest that public policy should be directed at deploying renewable energy in developing countries, while focusing on non-or-de-growth strategies accompanied with renewable energy in developed nations.

scholarly journals The Impact of Green Technology Innovation on Carbon Emissions in the Context of Carbon Neutrality in China: Evidence from Spatial Spillover and Nonlinear Effect Analysis

2022 ◽  
Vol 19 (2) ◽  
pp. 730
Author(s):  
Shihong Zeng ◽  
Gen Li ◽  
Shaomin Wu ◽  
Zhanfeng Dong
Keyword(s):  
Carbon Dioxide ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Technology Innovation ◽  
Green Technology ◽  
Total Carbon ◽  
Marginal Rate ◽  
Spatial Spillover ◽  
Carbon Neutrality ◽  
The Impact

The Paris agreement is a unified arrangement for the global response to climate change and entered into force on 4 November 2016. Its long-term goal is to hold the global average temperature rise well below 2 °C. China is committed to achieving carbon neutrality by 2060 through various measures, one of which is green technology innovation (GTI). This paper aims to analyze the levels of GTI in 30 provinces in mainland China between 2001 and 2019. It uses the spatial econometric models and panel threshold models along with the slack based measure (SBM) and Global Malmquist-Luenberger (GML) index to analyze the spatial spillover and nonlinear effects of GTI on regional carbon emissions. The results show that GTI achieves growth every year, but the innovation efficiency was low. China’s total carbon dioxide emissions were increasing at a marginal rate, but the carbon emission intensity was declining year by year. Carbon emissions were spatially correlated and show significant positive agglomeration characteristics. The spatial spillover of GTI plays an important role in reducing carbon dioxide emissions. In the underdeveloped regions in China, this emission reduction effect was even more significant.

An approach to carbon emissions prediction using generalized regression neural network improved by genetic algorithm

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Zhida Guo ◽  
Jingyuan Fu
Keyword(s):  
Neural Network ◽  
Carbon Dioxide ◽  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Total Carbon ◽  
Generalized Regression Neural Network ◽  
Improved Method ◽  
Target Values ◽  
Generalized Regression

The study on scientific analysis and prediction of China’s future carbon emissions is conducive to balancing the relationship between economic development and carbon emissions in the new era, and actively responding to climate change policy. Through the analysis of the application of the generalized regression neural network (GRNN) in prediction, this paper improved the prediction method of GRNN. Genetic algorithm (GA) was adopted to search the optimal smooth factor as the only factor of GRNN, which was then used for prediction in GRNN. During the prediction of carbon dioxide emissions using the improved method, the increments of data were taken into account. The target values were obtained after the calculation of the predicted results. Finally, compared with the results of GRNN, the improved method realized higher prediction accuracy. It thus offers a new way of predicting total carbon dioxide emissions, and the prediction results can provide macroscopic guidance and decision-making reference for China’s environmental protection and trading of carbon emissions.

scholarly journals An Examination of Green Credit Promoting Carbon Dioxide Emissions Reduction: A Provincial Panel Analysis of China

2021 ◽  
Vol 13 (13) ◽  
pp. 7148
Author(s):  
Wenjie Zhang ◽  
Mingyong Hong ◽  
Juan Li ◽  
Fuhong Li
Keyword(s):  
Carbon Dioxide ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Emissions Reduction ◽  
Green Finance ◽  
Carbon Emissions Reduction ◽  
Negative Effect ◽  
Emissions Intensity ◽  
The Impact

The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.

Comparative Study on BRIC Carbon Dioxide Emissions - Econometric Empirical Test Based on Cross-Century Time Series Data

2012 ◽  
Vol 616-618 ◽  
pp. 1512-1515
Author(s):  
Wei Hua Du
Keyword(s):  
Carbon Dioxide ◽  
Time Series ◽  
Carbon Dioxide Emissions ◽  
Time Series Data ◽  
Comparative Statics ◽  
Total Carbon ◽  
Series Data ◽  
Per Capita Gdp ◽  
Bric Countries ◽  
Per Capita

Take for example the BRIC economies: Brazil, Russia, India and China. We investigated the time series data on the relationship between carbon dioxide emission and economic growth in these fast-growing developing countries by both comparative statics and comparative dynamics. The results show that there is the monotonic relationship between total carbon dioxide emissions, carbon dioxide emissions per capita and per capita GDP in any one of the BRIC countries. And there is decreasing relationship between the carbon dioxide emissions per unit GDP and per capita GDP.

Electricity production and its effects on carbon dioxide emissions in the Kingdom of Saudi Arabia: إنتاج الكهرباء وآثاره في انبعاثات ثاني أكسيد الكربون في المملكة العربية السعودية

2021 ◽  
Vol 5 (3) ◽  
pp. 134-108
Author(s):  
Zakiah Radhi Alhajji, Mohamed Elsayed Hafez Ali Zakiah Radhi Alhajji, Mohamed Elsayed Hafez Ali
Keyword(s):  
Carbon Dioxide ◽  
Saudi Arabia ◽  
Carbon Dioxide Emissions ◽  
Fossil Fuels ◽  
Electric Energy ◽  
Total Carbon ◽  
Electricity Production ◽  
Energy Productivity ◽  
Gulf Region ◽  
Kingdom Of Saudi Arabia

Because of increased demand for electrical energy in the Kingdom of Saudi Arabia, which has resulted in an increase in carbon dioxide emissions, the electricity system in the Kingdom of Saudi Arabia is the largest in the Gulf region and the Arab world, with approximately 61.7 gigatons (GW) of peak demand and 89.2 gigatons (GW) of available capacity in 2018 of electricity power. It has grown rapidly over more than 20 years and has almost doubled in size since 2000. Where we observe that the total carbon dioxide emissions in the Kingdom of Saudi Arabia from 1990 to 2020; where shows rapid growth in emissions of carbon dioxide and greenhouse gases, as it was found that CO2 emissions in 1990 amounted to 151 million metric tons compared to 2011 when it reached about 435 million metric tons, and the increase continued until 2020 when it reached about 530 million metric tons. The comprehensive study relied on time series analysis to carefully analyze the electric energy productivity rate from fossil fuels and the significant amount of carbon dioxide emissions typically resulting from promptly burning fossil fuels to naturally produce electric energy. Therefore, the Kingdom of Saudi Arabia, through Vision 2030 and the Paris Agreement on Climate Change, looks to reduce the rate of carbon dioxide emissions in the field of electric power generation by diversifying the fuels used or replacing them with clean and renewable energy such as solar and wind energy.

Social Impacts Due to Carbon Dioxide (CO2) Emissions. Evidence From Sub-Sahara African Countries (SSA) Compared to Southeast Asian Countries (ASEAN).

2021 ◽  
Author(s):  
Jean Baptiste Aboyitungiye ◽  
Suryanto Suryanto ◽  
Evi Gravitiani
Keyword(s):  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Explanatory Power ◽  
Value Added ◽  
Southeast Asian ◽  
Asian Countries ◽  
Asean Countries ◽  
Southeast Asian Countries

Abstract The recent climatic phenomena observed in developing countries since the 2000s have raised concerns, fears, and debates within the international community and economists. Human activities are largely responsible for atmospheric warming through their emissions of CO2 and polluting substances with dramatic consequences and numerous losses of human life in some countries. Using panel data covering the 2000-2016 period, this study investigated the social vulnerability due to the CO2 emissions through an empirical study of CO2’s determinants in selected countries of sub-Sahara African and Southeast Asian countries. The STIRPAT model gave out the result that; explanatories causes of carbon dioxide emissions are different in the two regions: the agriculture-forestry and fishing value-added, and human development index have a strong explanatory power on CO2 emissions in the ASEAN countries, the per-capita domestic product has a positive and significant influence on carbon emissions in the SSA countries, ceteris paribus, but was statistically insignificant in the ASEAN countries. The growing population decreases carbon emissions in the SSA selected countries while is not statically significant in the ASEAN countries. There is therefore a kind of double penalty: those who suffer, and will suffer the most from the impacts of climate change due to CO2 emissions, are those who contribute the least to the problem. These results provide insight into future strategies for the mitigation of climatic hazards already present in some places and potential for others which will be felt on different scales across the regions. Some of the inevitable redistributive effects of those risks can be corrected by providing financial support to the poorest populations hardest hit by natural disasters.

Research on the Methods of Reducing Carbon Emissions in Airspace Optimization

2013 ◽  
Vol 718-720 ◽  
pp. 858-862
Author(s):  
Dai Wu Zhu ◽  
Zhi Heng Liu ◽  
Shu Yang ◽  
Jian Guo Xu
Keyword(s):  
Carbon Dioxide ◽  
Regression Analysis ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Carbon Emission ◽  
International Community ◽  
Saving Energy ◽  
Function Model ◽  
Specific Data

The international community is increasingly concerned about saving energy and less carbon dioxide emissions. But with growing air passenger and cargo traffic, the airspace tension highlights would inevitably lead to the increase in carbon emissions. However, there is little research on the methods of reducing carbon emission in airspace optimization. So this paper does some research in this field. Firstly this paper provides and exemplifies the method for decreasing the carbon emissions in airspace optimization. Secondly it puts forward the BPR function model to estimating the amount of carbon emissions of the method of increasing the number of air routes and uses the Regression analysis to confirm the parameters αβ. At last utilizing the specific data testifies the huge contribution of reducing the amount of carbon emissions from airspace optimization.

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