ABSTRACT
In response to the coronavirus disease 2019 pandemic, the Chinese government implemented blockade measures in Hubei, which largely affected the emission of pollutants. This work is aimed to explore the effects of epidemics on pollutants at different temperatures in Hubei, China. We applied for a panel nonlinear model with autonomous search thresholds to explore this, using daily average temperature as a threshold variable, and PM2.5 set as the explained variable, and the cumulative number of confirmed coronavirus disease 2019 cases set as the explanatory variable. An empirical analysis was conducted by running the proposed model and using nine cities in China most impacted by the pandemic. The results show that there was a non-linear negative relationship between the cumulative number of confirmed coronavirus disease 2019 cases and PM2.5. A more detailed non-linear relationship between the two was uncovered by the proposed panel threshold regression model. When the temperature crosses the threshold value (12.5 degrees C and 20.5 degrees C) in sequence, the estimated value was -0.0688, -0.0934, and -0.1520 in that order. This means that this negative non-linear relationship increased with increasing temperature. This work helps to explore the effect of coronavirus disease 2019 on pollutions at different temperatures and provides a methodological reference to study their nonlinear relationship.
ABSTRACT
The COVID-19 pandemic has a significant impact on renewable energy. This work investigates the effect of pandemic on the renewable energy research from four aspects: the regional cooperation model of renewable energy research, the research hotspots of renewable energy during the pandemic, the development trend of renewable energy research hotspots in the post-pandemic, policy recommendations for development in the postepidemic era. Systematic literature review (SLR), latent semantic analysis (LSA), and machine learning-based analysis (principle component analysis) are used to analyze the relevant literature on the COVID-19 and renewable energy in the Scopus database. The results of geographic visualization analysis show the COVID-19 pandemic has not hindered but promoted bilateral cooperation in the field of renewable energy among the " the Belt and Road " partner countries, with China at the core. The results of visual analysis of research hotspots show the research in the field of renewable energy during pandemics is divided into two categories: "opportunities" and "crisis", and further obtained five categories: sustainable development, environmental management, carbon emission, solar photovoltaic power, and wind power. The results of the keyword evolution map indicate the two main directions of renewable energy research in the post-pandemic: (1) Clean energy investment has become an important measure to revitalize the economy after the epidemic. (2) Energy efficiency research will effectively promote the sustainable development of renewable energy. Finally, we put forward policy suggestions on how to build a smart energy system in the post-epidemic era.
ABSTRACT
Purpose The purpose of this research is to systematically analyze the existing literature of the supply chain to explore the impact of COVID-19 on the international cooperation in supply chain research between the US and China. Design/methodology/approach Supply chain publications obtained from the Scopus database were analyzed using statistical technique and visual analysis. First, created three datasets of supply chain publications for three time periods: 2010-2019, 2015-2019 and 2020-2021. Then, compared the changes in international cooperation in supply chain research between the US and China before and during the epidemic, as well as the international cooperation patterns for the two countries. Findings The study found that during the pandemic, the average monthly number of collaborative publications between China and the US on supply chain research was higher than the five and the ten years before the epidemic. In other words, the epidemic has not led to a decline in international cooperation between the US and China. On the contrary, the epidemic has stimulated international cooperation on supply chain research in the two countries. Secondly, research on the international cooperation patterns of supply chain research shows that China and the US have always been each other's largest partners, and the two countries have generally maintained or increased international cooperation with their top research producing countries during the epidemic. In addition, in supply chain research during the epidemic, the proportion of US-China cooperation in China's international cooperation has declined, while that of the US has increased. Research limitations/implications The time span of the datasets used to analyze the research status before and during COVID-19 is different. Due to the nature of data collection, available time of the dataset during COVID-19 is much shorter. Publications during the COVID-19 continue to grow, and the trends shown by the research results may change somewhat. Furthermore, the search query may not be comprehensive enough to capture all publications related to the supply chain. Practical implications The research results help determine the impact of the COVID-19 outbreak on international cooperation in US-China supply chain research, and it is of great significance to researchers and policymakers in the field of logistics and supply chain operations. Originality/value This study gives a feasible analysis strategy for international cooperative research, which adds great value to this field.
ABSTRACT
The COVID-19 epidemic has severely affected the world economy and energy markets. In order to alleviate the shock, stabilize the financial market, and promote economic recovery, the Fed announced an unlimited QE policy. In order to understand the impact of the policy on the energy market under the extreme events, the study selected WTI crude oil and coal prices from January 1, 2018 to May 7, 2021 as the research objects. Taking the two years before the epidemic, the epidemic stage was further divided into four small stages according to the three peaks of the epidemic in the US. The MF-DCCA model calculations show that coal and WTI crude oil have an interactive relationship. The risks between them are not just averaged and superimposed, but transmitted and interacted.The MF-DFA model calculation results show that due to the disorder of energy supply and demand under the epidemic, market efficiency in the first quarter of 2020 has dropped rapidly. However, market effi-ciency decoupled from the development of the epidemic in the second half of 2020. Especially after the announcement of the QE policy, market efficiency has improved significantly. However, under the excessive monetary policy, market efficiency declined in the first half of 2021. This shows that the policy has a certain effect on alleviating the impact of the epidemic on the energy market. But this improvement is not sustainable from the long term. As prices rise, inflation continues. In the future, the volatility and risk of the energy futures market will increase.