Strategic Environmental Assessment of Land Transportation: An Application of DEA with Undesirable Output Approach

The efficiency of land transportation contributes significantly to determining a country’s economic and environmental sustainability. The examination of land transportation efficiency encompasses performance and environmental efficiency to improve system performance and citizen satisfaction. Evaluating the efficiency of land transportation is a vital process to improve operation efficiency, decrease investment costs, save energy, reduce greenhouse gas emissions, and enhance environmental protection. There are many methods for measuring transportation efficiency, but few papers have used the input and output data to evaluate the ecological efficiency of land transportation. This research focuses on evaluating the environmental efficiency for land transportation by using the data envelopment analysis (DEA) method with undesirable output to handle unwanted data. By using this, the paper aims to measure the performance of land transportation in 25 Organization for Economic Co-operation and Development (OECD) countries in the period of 2015–2019, considered as 25 decision-making units (DMUs) in the model. For identifying the ranking of DMUs, four inputs (infrastructure investment and maintenance, length of transport routes, labor force, and energy consumption) are considered. At the same time, the outputs consist of freight transport and passenger transport as desirable outputs and carbon dioxide emission (CO2) as an undesirable output. The proposed model effectively determines the environment-efficient DMUs in a very time-efficient manner. Managerial implications of the study provide further insight into the investigated measures and offer recommendations for improving the environmental efficiency of land transportation in OECD countries.

Urbanization and carbon dioxide (CO2) emission nexus in the CEMAC countries

PurposeThis study investigates the relationship between urbanization and carbon dioxide emission in the Central African Economic and Monetary Community from 1990 to 2019. The literature reveals that the relationship between urbanization and carbon dioxide emissions is still debatable and the existing findings are inconclusive.Design/methodology/approachCarbon dioxide is the regressand; while, urbanization, gross domestic product (GDP) and financial development (FD), rule of law (ROL) and government effectiveness (GEF) are the regressors. Johansen Fisher and Kao residual co-integration tests alongside the fully modified and dynamic ordinary least squares.FindingsThe results show a significant positive relationship between urbanization and carbon dioxide emissions. The causality tests results show that carbon dioxide granger causes urbanization, GDP and FD unit directionally.Research limitations/implicationsThe countries' governments should effectively improve their legal systems to regulate carbon dioxide emissions. Urbanization laws should be implemented to limit urbanization environmental deteriorating effects on carbon dioxide emissions. This occurs as the countries practiced unregulated urbanization which increases population's environmental impacts. The study recommends sustainable green urbanization policies for environmental conservation through tree planting and horticulture. Balance development in urban and rural areas is vital to decongest the urban cities' pressure in the states. The governments should motivate the private sector with rural investments captivating policies to limit rural urban migration.Originality/valueThe findings contribute value by supporting a positive link between urbanization and carbon dioxide emissions in the CEMAC zone. The causality tests findings confirm the view that carbon dioxide granger causes urbanization, GDP and FD unit directionally. This value addition is essential to the governments and policy makers to mitigate urbanization and carbon dioxide emissions in the CEMAC region.

Correlation and Dynamic Volatility Spillover between Green Investing Market, Coal Market, and CO2 Emissions: Evidence from Shenzhen Carbon Market in China

With the continuous expansion scale of carbon market and the development of carbon trading mechanism, carbon emission right, as a new financial asset, is being brought into the category of asset allocation by more and more investors. As the burning of coal is the major source of carbon dioxide, China is facing serious ecological and environmental problems, which restrict the development of low-carbon economy. In order to reach the carbon dioxide emission reduction targets and promote the development of green investment market, the carbon market should be a good emission reduction measure. The correlation and dynamic volatility spillover among coal, carbon, and green investing markets are becoming a hot topic for current research. The paper applies both VAR-GARCH-DCC and VAR-GARCH-BEKK models to draw some significant conclusions. (1) The green investment market, coal market, and Shenzhen carbon market show obvious time-varying correlation, and the volatility of the green investment market is higher. (2) There is a bidirectional Granger causality between green investing and coal markets. (3) The investment portfolio and hedging mechanism of the market are established to reduce the risk and help investors obtain higher returns.

Time Series Analysis of Global Energy Indices: Logarithmic and Normalized Techniques for Developmental Studies

Diverse opinions exist in the time series analysis of energy and related indices, difference in methodology, sample size, and time variation. This paper will make a conscious effort to converge the divergent outlooks. To accomplish this essential task, five energy indices consisting of energy consumption (EC), gross domestic product (GDP), carbon dioxide emission (CDE), the human development index (HDI), and oil price (OP) were selected. Two analytical methods were adopted, namely logarithmic and normalized techniques, which are designed to complement each other in drawing unfalsified statistical inference concerning the causality between the energy indices. The methods were subjected to four statistical tests and analyses: the augmented Dickey-Fuller, cointegration, pairwise Granger causality, and vector error correction model (VECM). Irrespective of prevailing challenges, both logarithmic and normalized techniques unanimously filtered out causalities. This consisted of neural flow between oil price and energy consumption, gross domestic product and carbon dioxide emission, and energy consumption and the human development index, unidirectional flow between energy consumption and the human development index, oil price and energy consumption, gross domestic product and carbon dioxide emission, and the human development index and oil price, whereas a normalized technique established bidirectional flow between gross domestic product and the human development index, and the human development index and oil price. Pertinently, the research suggests appropriate policies that will generate sustainable development in all the causal directions. Assiduously, the overwhelming agreement between both techniques at the 0.05 level is recommended for further validation with more modern econometric tests.

The relationship of economic growth and carbon-dioxide emissions: an application on member countries of Organization of Islamic Cooperation

Motivation: Humanity has benefited from natural resources in production activities throughout history and this pressure on natural resources has increased even more with the efforts of industrialization. In this process, people benefited heavily from fossil fuels in their production and distribution activities, thereby damaging the environment and the atmosphere to a large extent. With the destruction of the environment, it has become important for the countries and the academic circles to measure environmental damage with the increase of economic activities in order to take various measures. Aim: At this point, in this study, the relationship between economic growth and carbon-dioxide emissions was examined within the scope of 50 countries that are members of the Organization of Islamic Cooperation (OIC). In this process, annual data of the countries concerned between 1995 and 2017 were used; Pedroni Cointegration Analysis, Granger Causality Analysis, Pooled Mean Group Estimator (PMGE) and Mean Group Estimator (MGE) methods were used to measure and estimate the relationship between these two variables. The causality analysis shows that the economic growth is the Granger cause of carbon-dioxide emissions in the country group studied. In addition, the coefficients obtained in PMGE and MGE analyzes were found as 0.43 and 0.33 and were statistically significant and positive. Then, with the help of Hausman Homogeneity Test, it was decided between the two estimators, and it concluded that PMGE Estimator is the more reliable estimator. Results: The results obtained with the PMGE estimator indicate that the 1% increase in economic growth increased carbon dioxide emission by 0.43%.

Investigation of the influence of varying tumbling strategies on a tumbling self-piercing riveting process

The increasing demands for the reduction of carbon dioxide emission require intensified efforts to increase resource efficiency. Especially in the mobility sector with large moving masses, resource savings can contribute enormously to the reduction of emissions. One possibility is to reduce the weight of the vehicles by using lightweight technologies. A frequently used method is the implementation of multi-material systems. These consist of dissimilar materials such as steel, aluminium or plastics. In the production of these systems, the joining of the different materials and geometries is a central challenge. Due to the increasing demands on the joints, the challenges for the joining processes itself are also increasing. Since conventional joining processes are rather rigid and can only react to a limited extent to disturbance variables or changing process variables, new methods and technologies are required. A widely used conventional joining method with these properties is self-piercing riveting. Because of the rigid tool combination and the fact that the rivet geometry that can be used is related to the tools, the joining of multi-material systems requires tool and rivet changes during the process. In order to extend the process window of joining with self-piercing rivet elements, the process is enhanced with a tumbling kinematic of the punch. The integration of tumbling results in a significant increase in the adjustable process parameters. This enables a higher material flow control in the joining process through a specific tumbling strategy. The materials investigated are a steel and an aluminium alloy, which differ significantly in their mechanical properties and have many applications in automotive engineering, especially for structural car body components. The steel material is a galvanized HCT590X+Z dual-phase steel, which is characterised by a low yield strength, combined with high tensile strength and a good hardening behaviour. The aluminium alloy is an EN AW-6014. The precipitation-hardening alloy consists of aluminium, magnesium and silicon with a high strength and energy absorption capability. The objective of this work is to obtain a fundamental knowledge of the new tumbling self-piercing riveting process. With different mechanical properties and different sheet thicknesses of the joining partners, the influences of these parameters on the tumbling strategy of the riveting process are analysed. Such a tumbling strategy is based on the tumbling angle, the tumbling onset and the tumbling kinematics. These parameters are investigated in the context of the work for selected combinations of multi-material systems consisting of HCT590X+Z and EN AW-6014. With the variation of the parameters, the versatility of the process can be investigated and influences of the tumbling on the self-piercing riveting process can be identified. To illustrate the results, force–displacement curves from the joining process of the individual joints are compared and the geometry of the rivet undercut and rivet heads are geometrically measured. Furthermore, micrographs allow the analysis of the characteristic joint parameters interlock, residual sheet thickness and end position of the rivet head.