scholarly journals The Impact of COVID-19 Lockdown on Global Warming: A Call for Policy Review

2020 ◽  
Vol 9 (2) ◽  
pp. 70-72
Author(s):  
Oluwatosin Samson Jegede ◽  
Sunday Olarewaju

Coronavirus disease 2019 (COVID-19) is probably the worst epidemic the world has experienced in recent times; it has led to drastic, lifesaving, and extraordinary decisions by governments of nations. Among such extraordinary measures is the closure of international borders leading to the cancellation of air travel by commercial airlines. The carbon emissions from air travel affect global warming. To this end, some authors ranked aircraft as if it were a country and compared the volume of carbon emissions generated by air travel to that generated by countries from other sources. Commercial air travel ranked seventh after Germany in terms of carbon emissions. This policy review, therefore, explored the impact of COVID-19 lockdown and travel restrictions on global warming. As a result of lockdown, there is a likelihood of a significant decrease in carbon emissions and global warming. Assuming the estimated global emissions remain constant annually, an estimated 9 gigatonnes of carbon dioxide emissions would be avoided by the end of 2020 provided that the lockdown continues. To accurately measure the value of reduced carbon dioxide emissions during the global lockdown, it is recommended that scientific studies be conducted to estimate the carbon emissions generated by the few aircraft granted waivers to transport essential commodities during the global lockdown and deduct it from the 9 gigatonnes. After the global lockdown, through a travel policy review, governments and organizations are encouraged to restrict physical meetings or activities that involve air travel only to situations where a physical presence is unavoidable.

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.


Author(s):  
Yu Kun Wang ◽  
Xiaoyong Zhang

Carbon emissions exacerbate global climate change. Transitioning away from coal is a cost-effective path to a low-carbon economy. Although many articles have considered the issue of manufacturers' production and emission of pollution. Few papers have discussed the impact of environmental tax and fuel tax on the cost of environmental degradation. This paper seeks to fill this gap by developing a theoretical model to discuss the relationship between environmental pollution and economic growth. Furthermore, in order to support the theoretical results and testify the relationship between carbon emissions and taxation, we take South Africa as a case for discussing the effect of environmental taxation and fuel levy on firms' carbon emissions. We show that the impact of environmental taxes on carbon dioxide emissions is greater than that of fuel taxes on carbon dioxide emissions. In addition, we find that the GDP level of South Africa is on the left of the inflection points of Kuznets Curve. In other words, the current growth of South Africa's economy is at the cost of worsening the environmental degradation.


2021 ◽  
pp. 17-23
Author(s):  
Szira Zoltán ◽  
Bárdos Kinga Ilona ◽  
Alghamdi Hani ◽  
Enkhjav Tumentsetseg ◽  
Erika Varga

2019 was Earth's second warmest year since 1850. In 2019 the global mean temperature was cooler than in 2016, but warmer than any other year explicitly measured. Consequently, 2016 is still the warmest year in historical observation history. Year-to-year rankings are likely to reflect natural fluctuations in the short term, but the overall pattern remains consistent with a long-term global warming trend. This would be predicted from global warming caused by greenhouse gases, temperature increase across the globe is broadly spread, impacting almost all areas of land and oceans. Climate change" and "global warming" are often used interchangeably but are of distinct significance. Global warming is the long-term heating of the Earth's climate system observed since the pre-industrial period as a result of human activities, mainly the combustion of fossil fuel, which raises the heat-trapping greenhouse gas levels in the Earth's air. The term is often used interchangeably with the term climate change, as the latter applies to warming caused both humanly and naturally, and the impact it has on our planet. This is most generally calculated as the average increase in global surface temperature on Earth. Carbon dioxide emission is one of the main reasons for global warming. Since the Industrial Revolution, human sources of carbon dioxide emissions have been growing. Human activities such as the burning of oil, coal and gas, as well as deforestation are the primary cause of the increased carbon dioxide concentrations in the atmosphere. In our research, let’s examine the relationship between the amount of carbon dioxide emissions and the GDP/capita in developed and developing countries.


Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7430
Author(s):  
Yang Ding ◽  
Qing Yang ◽  
Lanjuan Cao

This study examines the relationship between urbanization, economic growth, industrial transformation, technological change, public services, demographical change, urban and natural environmental changes, and carbon emissions using a dataset of 182 prefecture-level cities in China between 2001 and 2010. Specifically, this paper differs from previous studies in two aspects. First, the extant literature has focused on how economic processes accompanying rapid urbanization affect carbon emissions in urban areas but gives little attention to the other dimensions of urbanization, including social and environmental changes, which may have important effects on carbon emissions. We assessed the effects of 17 key processes accompanying urbanization in a full range of economic, social, and environmental dimensions on carbon dioxide emissions in urban areas. The results showed that social processes accompanied with rapid urbanization had distinct effects on carbon emissions, compared to economic and environmental processes. Specifically, improvement in public services, indicated by education and cultural developments, reduces the increase in carbon emissions during urbanization, while economic growth and urban construction reinforces the growth in carbon emissions. Second, we examined the impact of various urbanization processes on carbon dioxide emissions using a unique dataset of 182 prefecture-level cities that covers a wide span of regions in China. The results of our analyses on the city level have important implications for the formulation of comprehensive policies aimed at reducing carbon dioxide emission in urban areas, focusing on different urbanization processes in economic, social, and environmental phases.


Author(s):  
Shihong Zeng ◽  
Gen Li ◽  
Shaomin Wu ◽  
Zhanfeng Dong

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.


PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251816
Author(s):  
Deng Jie Long ◽  
Li Tang

With the change of social economic system and the rapid growth of agricultural economy in China, the amount of agricultural energy consumption and carbon dioxide emissions has increased dramatically. Based on the estimation of agricultural carbon dioxide emissions from 1991 to 2018 in China, this paper uses EKC model to analyze economic growth and agricultural carbon dioxide emissions. The Kaya method is used to decompose the factors affecting agricultural carbon dioxide emissions. The experimental results show that there is a co-integration relationship between economic growth and the total intensity of agricultural carbon emissions, and between economic growth and the intensity of carbon emissions caused by five types of carbon sources: fertilizer, pesticide, agricultural film, agricultural diesel oil and tillage. Economic growth is the main driving factor of agricultural carbon dioxide emissions. In addition, technological progress has a strong role in promoting carbon emission reduction, but it has a certain randomness. However, the impact of energy consumption structure and population size on carbon emissions is not obvious.


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.


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