The impact of immigration on human capital and carbon dioxide emissions in the USA: an empirical investigation

Author(s):  
Melike Dedeoğlu ◽  
Emrah Koçak ◽  
Zübeyde Şentürk Uucak
2021 ◽  
Vol 13 (13) ◽  
pp. 7148
Author(s):  
Wenjie Zhang ◽  
Mingyong Hong ◽  
Juan Li ◽  
Fuhong Li

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.


2021 ◽  
Vol 5 (2) ◽  
pp. 22
Author(s):  
Chiara Binelli

Several important questions cannot be answered with the standard toolkit of causal inference since all subjects are treated for a given period and thus there is no control group. One example of this type of questions is the impact of carbon dioxide emissions on global warming. In this paper, we address this question using a machine learning method, which allows estimating causal impacts in settings when a randomized experiment is not feasible. We discuss the conditions under which this method can identify a causal impact, and we find that carbon dioxide emissions are responsible for an increase in average global temperature of about 0.3 degrees Celsius between 1961 and 2011. We offer two main contributions. First, we provide one additional application of Machine Learning to answer causal questions of policy relevance. Second, by applying a methodology that relies on few directly testable assumptions and is easy to replicate, we provide robust evidence of the man-made nature of global warming, which could reduce incentives to turn to biased sources of information that fuels climate change skepticism.


2019 ◽  
Vol 26 (3) ◽  
pp. 31-38
Author(s):  
Wojciech Gis ◽  
Maciej Gis ◽  
Piotr Wiśniowski ◽  
Mateusz Bednarski

Abstract Limiting emissions of harmful substances is a key task for vehicle manufacturers. Excessive emissions have a negative impact not only on the environment, but also on human life. A significant problem is the emission of nitrogen oxides as well as solid particles, in particular those up to a diameter of 2.5 microns. Carbon dioxide emissions are also a problem. Therefore, work is underway on the use of alternative fuels to power the vehicle engines. The importance of alternative fuels applies to spark ignition engines. The authors of the article have done simulation tests of the Renault K4M 1.6 16v traction engine for emissions for fuels with a volumetric concentration of bioethanol from 10 to 85 percent. The analysis was carried out for mixtures as substitute fuels – without doing any structural changes in the engine's crankshafts. Emission of carbon monoxide, carbon dioxide, hydrocarbons, oxygen at full throttle for selected rotational speeds as well as selected engine performance parameters such as maximum power, torque, hourly and unit fuel consumption were determined. On the basis of the simulation tests performed, the reasonableness of using the tested alternative fuels was determined on the example of the drive unit without affecting its constructions, in terms of e.g. issue. Maximum power, torque, and fuel consumption have also been examined and compared. Thus, the impact of alternative fuels will be determined not only in terms of emissions, but also in terms of impact on the parameters of the power unit.


Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2942 ◽  
Author(s):  
Karol Tucki ◽  
Olga Orynycz ◽  
Antoni Świć ◽  
Mateusz Mitoraj-Wojtanek

The article analyzes the dynamics of the development of the electromobility sector in Poland in the context of the European Union and due to the economic situation and development of the electromobility sector in the contexts of Switzerland and Norway. On the basis of obtained data, a forecast was made which foresees the most likely outlook of the electric car market in the coming years. The forecast was made using the creeping trend method, and extended up to 2030. As part of the analysis of the effect of the impact of electromobility, an original method was proposed for calculating the primary energy factor (PEF) primary energy ratio in the European Union and in its individual countries, which illustrates the conversion efficiency of primary energy into electricity and the overall efficiency of the power system. The original method was also verified, referring to the methods proposed by the Fraunhofer-Institut. On the basis of all previous actions and analyses, an assessment was made of the impact of the development of the electromobility sector on air quality in the countries studied. Carbon dioxide tank-to-wheels emission reductions which result from the conversion of the car fleet from conventional vehicles to electric motors were then calculated. In addition to reducing carbon dioxide emissions, other pollutant emissions were also calculated, such as carbon monoxide (CO), nitrogen oxides (NOx) and particulate matter (PM). The increase in the demand for electricity resulting from the needs of electric vehicles was also estimated. On this basis, and also on the basis of previously calculated primary energy coefficients, the emission reduction values have been adjusted for additional emissions resulting from the generation of electricity in power plants.


2009 ◽  
Vol 31 (3) ◽  
pp. 425-445 ◽  
Author(s):  
Richard S.J. Tol ◽  
Stephen W. Pacala ◽  
Robert H. Socolow

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