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Background: Carbon footprint is a widely used tool to measure the impact of human activities on global warming. The lockdowns caused by the COVID-19 pandemic have significantly changed energy consumption forms and decreased CO2 emissions worldwide. This research is a trial to elaborate the effect of COVID-19 pandemic on the carbon footprint of the High Institute of Public Health (HIPH). Objective(s): The present study aimed at measuring the amount of water, electricity, fuel, and paper consumption by HIPH before and during the emergence of COVID-19 and assessing the carbon footprint of the HIPH population inside the building through the same period. Methods: A cross-sectional survey was done using a pre-designed questionnaire targeting 10 % of the HIPH population before and during the pandemic. Bills of water, electricity, paper, and fuel consumption were used to calculate the carbon footprint for one year before and one year during COVID-19. Results: Online responses increased during COVID-19 emergence (69.2% during COVID-19 pandemic versus 44.1% before COVID-19 pandemic). Females were more than 2/3 of the respondents (70.6%). There was a significant difference in traveling outside Egypt before and during COVID-19 (X2=12.794, p-value=0.002). A significant reduction in the average time spent in front of the computer at HIPH was found during the emergence of COVID-19 as most of the work became from home (X2= 18.443, p-value= 0.001). Significant reduction in the consumption of hot drinks, cold drinks, bottled water and food inside the HIPH was noticed (X2=50.219, p-value<0.0001; X2=12.030, p-value=0.017; X2=15.945, p-value=0.004; X2=72.929, p-value<0.0001 respectively). The carbon footprint of HIPH in the period from July 2018 to June 2019 was 79.43MT of CO2e. In the period from July 2020 to June 2021, it was 59.85MT of CO2e with a 25% reduction in the emission. Conclusion: The carbon footprint of HIPH was reduced during the lockdown period compared to that before the epidemic. So, efforts should be gathered to hasten the reduction of carbon footprint through encouraging online teaching and changing lifestyle. [ABSTRACT FROM AUTHOR]

The exploration of the dependency structure of the Chinese and EU carbon trading markets is crucial to the construction of a globally harmonized carbon market. In this paper, we studied the characteristics of structural interdependency between China's major carbon markets and the European Union (EU) carbon market before and after the launch of the national carbon emissions trading scheme (ETS) and the occurrence of the new coronavirus (COVID-19) by applying the C-vine copula method, with the carbon trading prices of the EU, Beijing, Shanghai, Guangdong, Shenzhen and Hubei as the research objects. The study shows that there exists a statistically significant dependence between the EU and the major carbon markets in China and their extremal dependences and dependence structures are different at different stages. After the launch of the national carbon ETS, China has become more independent in terms of interdependency with the EU carbon market, and is more relevant between domestic carbon markets. Most importantly, we found that the dependence between the EU and Chinese carbon markets has increased following the outbreak of COVID-19, and tail dependency structures existed before the launch of the national carbon ETS and during the outbreak of the COVID-19. The results of this study provide a basis for the understanding of the linkage characteristics of carbon trading prices between China and the EU at different stages, which in turn can help market regulators and investors to formulate investment decisions and policies. [ABSTRACT FROM AUTHOR]

This paper provides a picture of how societies in the G7 countries have responded to the COVID-19 pandemic. Our point of departure is to examine the effects of the pandemic in terms of four fundamental normative sources for well-being: Solidarity (S; willingness for social cooperation), Agency (A; empowerment to shape one's prospects through one's own efforts), GDP (G), and Environmental Performance (E)--SAGE for short. The normative foundations of SAGE are communitarianism, classical liberalism, materialistic utilitarianism, and ecoethics. We find that although G and E responded predictably and uniformly to the pandemic (such as G declining and carbon emissions improving), the societal responses were strikingly different. Societies that are cohesive and empowered (high S and A) may be expected to cope with the pandemic better than those that are fragmented and disempowered (low S and A). Furthermore, the pandemic has had diverse effects on S and A; while some societies became cohering and empowering (rising S and A), others became fragmenting and disempowering (falling S and A), and yet others became fragmenting and empowering. We also show that most G7 countries experienced greater tribalization (measured as the difference between inward S and outward S) during the pandemic. These trends are a matter of concern since they suggest that the willingness and perceived ability to address collective challenges collectively have waned. The analysis also suggests that governments' social policies may have an important role to play alongside economic and health policies in coping with the pandemic. [ABSTRACT FROM AUTHOR]

Carbon and pollutant emissions drive climate change and affect health and daily life. The Covid-19 pandemic created an unprecedented opportunity to understanding the impact of carbon and pollutant emission. In this paper were identified Telecommunications records-derived general mobility indices as contributors to the PM10 pollutant concentration development in industry-intensive Sisak-Moslavina County, Croatia, during the Covid19 outbreak in 2020. Time-series of daily mean PM10 concentrations and mobility changes indicators are analysed for their statistical properties identification, decomposed, and the decomposing components examined for association using Tailored software developed in the R environment for statistical computing. [ABSTRACT FROM AUTHOR]

Tourism is one of the fastest-growing sectors in the world with a shift from mass tourism to personalized travel. Nevertheless, it generates significant environmental impacts. The current events associated with quarantine measures generated by COVID-19 represent, however, a risk for this sector. It is hence necessary to create strategies that allow efficient decision-making for all echelons and actors for a rapid recovery. Tourists are key actors, which makes necessary to facilitate tourism trip planning according to tourists' preferences as a complex process. In this paper, we propose a novel model of tourist trip planning for heterogeneous preferences in a tourist group and selection of transport modes, in the first instance, while a second step seeks at minimizing the level of CO2 emissions. A comparison of the two models is made considering the objectives associated with individual tourist benefits and group profit equity, in contrast to the inclusion of the cost of CO2 emissions. A numerical comparison is carried out with a total of 546 data sets. Results illustrate the conflict between those objectives by generating an inverse relationship between the individual and group profit equity of tourists, in addition to individual benefit and emission minimization. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic lockdowns led to a sharp drop in socio-economic activities in China in 2020, including reductions in fossil fuel use, industry productions, and traffic volumes. China's economy suffered a serious negative effect from COVID-19. However, there is a "positive effect" on CO 2 emissions reduction. Here, for the first time, this paper constructs a new model named "Weighted Multi-regional Hypothetical Extraction Method (WMHEM)" based on a multiregional input-output model. It not only solves the problems of traditional HEM methods such as improper use of assumptions, excessive reliance on industry intermediate input, but also accurately reflects the impact of external shocks on the inter-industry linkages. By using the monthly economic data of each provinces in China during COVID-19 (except Hong Kong，Macao and Taiwan) an the latest Multi-regional input-output tables, the "economic negative effect" and "CO 2 emission positive effect" under COVID-19 in China are measured. Results show that COVID-19 lockdown was estimated to have reduced China's CO 2 emissions substantially between January and March in 2020, with the largest reductions in February. With the spread of coronavirus controlled, China's CO 2 emissions rebounded in April. In addition, key emission reduction sectors and key development encouraged sectors are selected by combining "economic negative effect" and "CO 2 emission positive effect" during COVID-19. Therefore, policies recommendations are put forward based on forward and backward linkages respectively which are from two ends of the supply chain to turn pandemic-related CO 2 emissions declines into firm climate action. • COVID-19 has negative effects on economy, but positive effects on CO 2 emissions. • A new model is used to measure economic and CO 2 emission effects during COVID-19. • Hubei had the biggest economic and CO 2 emission effects on China due to COVID-19. • Economic and CO 2 emission effects of COVID-19 are combined to select key sectors. [ABSTRACT FROM AUTHOR]

Achieving the peak of carbon dioxide (CO 2) emissions requires a large amount of green and low-carbon investment. Whether the green finance system can efficiently support the capital need for achieving the CO 2 emissions target in the context of the COVID-19 epidemic is a matter of concern. This paper constructs a system dynamics model (SD model) to illustrate the quantitative relationship between the green finance system and CO 2 emissions and introduce the COVID-19 epidemic as a variable to analyze ten simulation scenarios regarding the carbon emissions commitment realization under different green finance and economic growth status. It is shown that: (1) Regardless of the impact of COVID-19, China can meet its commitment by reaching its CO 2 emissions peak in 2030 and realizing a 20% non-fossil energy proportion in 2025; (2) Under the impact of the epidemic, the goal can not be obtained in all energy consumption scenarios when the government expenditure on the environment is low. The target year of reaching CO 2 emissions peak becomes 2033, 2037, and 2040. The results indicate that reducing government expenditure on environment protection makes the CO 2 emissions peak target less likely to be achieved within a given time frame. We also concluded with important policy implications according to the result of the simulations. Overall, this study makes a reference for other economies and researchers to quantitatively predict the interaction relationship between the green finance system and CO 2 emissions in the context of COVID-19, which provides policymakers with insights into a joint power of energy consumption upgrading and green capital guidance. • Providing empirical studies regarding the mechanism of the inhibitory effect of green finance on CO 2 emissions. • Using systems dynamics model to address the missing data problem. • Making solid suggestions under COVID-19 Epidemic. • Building the relationship between the green finance system and CO 2 emissions and making forecasts for "3060" mission result. [ABSTRACT FROM AUTHOR]

This paper explores people's willingness to reduce travel consumption in support of the transition to a low-carbon pathway beyond COVID-19, using new survey data from UK car drivers and air travellers. Evidence from our study indicates that reductions of 24% - 30% to car use and 20% - 26% to air travel could be sustained in the long term. This potentially could lead to annual reductions of 343–529 kgCO 2 per car driver (20% - 29% of pre-COVID-19 car emissions) and 215–359 kgCO 2 per air traveller (10% - 20% of pre-COVID-19 emissions from flying), suggesting that behavioural change may be a major route to emissions reductions. We find that stated voluntary reductions are greater among those who report having 'more time to do creative things' since the start of the COVID-19 lockdowns. Hence, recovery policies promoting low-carbon leisure time may be a key to consumption reductions. We also find that higher-income travellers consume and pollute substantially more than the rest, and yet there is little difference in relative voluntary reductions across the income distribution. We conclude that behaviour associated with affluence represents a major barrier to a low-carbon transition, and that policies must address over-consumption associated with affluence as a priority. [ABSTRACT FROM AUTHOR]

While the deployment of technological innovation was able to avert a devastating global supply chain fallout arising from the impact of ravaging COronaVIrus Disease 19 (COVID-19) pandemic, little is known about potential environmental cost of such achievement. The aim of this paper is to identify the determinants of logistics performance and investigate its empirical linkages with economic and environmental indicators. We built a macro-level dataset for the top 25 ranked logistics countries from 2007 to 2018, conducting a set of panel data tests on cross-sectional dependence, stationarity and cointegration, to provide preliminary insights. Empirical estimates from Fully Modified Ordinary Least Squares (FMOLS), Generalized Method of Moments (GMM), and Quantile Regression (QR) model suggest that technological innovation, Human Development Index (HDI), urbanization, and trade openness significantly boost logistic performance, whereas employment and Gross Fixed Capital Formation (GFCF) fail to respond in such a desirable path. In turn, an increase in the Logistic Performance Index (LPI) is found to worsen economic growth. Finally, LPI exhibits a large positive effect on carbon emissions, which is congruent with a strand of the literature highlighting that the modern supply chain is far from being decarbonized. Thus, this evidence further suggest that more global efforts should be geared to attain a sustainable logistics. • Examining 25 topmost Logistics Countries on many fronts. • Technological innovation, HDI, urbanization, and trade openness spur logistic performance. • Logistic performance does not improve with employment rate and Gross Fixed Capital Formation. • Logistic performance increases carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

In recent years, as China's peaking carbon dioxide emissions and air pollution control projects have converged, scholars have begun to focus on the synergistic mechanisms of greenhouse gas and pollution gas reduction. In 2020, the unprecedented coronavirus pandemic, which led to severe nationwide blockade measures, unexpectedly provided a valuable opportunity to study the synergistic reduction in greenhouse gases and polluting gases. This paper uses a combination of NO2, O3, and CO2 column concentration products from different satellites and surface concentrations from ground-based stations to investigate potential correlations between these monitoring indicators in four Chinese representative cities. We found that XCO2 decreased in March to varying degrees in different cities. It was witnessed that the largest decrease in CO2, −1.12 ppm, occurred in Wuhan, i.e., the first epicenter of COVID-19. We also analyzed the effects of NO2 and O3 concentrations on changes in XCO2. First, in 2020, we used a top-down approach to obtain the conclusion that the change amplitude of NO2 concentration in Beijing, Shanghai, Guangzhou, and Wuhan were −24%, −18%, −4%, and −39%, respectively. Furthermore, the O3 concentration increments were 5%, 14%, 12%, and 14%. Second, we used a bottom-up approach to obtain the conclusion that the monthly averaged NO2 concentrations in Beijing, Shanghai, and Wuhan in March had the largest changes, changing to −39%, −40%, and −61%, respectively. The corresponding amounts of changes in monthly averaged O3 concentrations were −14%, −2%, and 9%. However, the largest amount of change in monthly averaged NO2 concentration in Guangzhou was found in December 2020, with a value of −40%. The change in O3 concentration was −12% in December. Finally, we analyzed the relationship of NO2 and O3 concentrations with XCO2. Moreover, the results show that the effect of NO2 concentration on XCO2 is positively correlated from the point of the satellite (R = 0.4912) and the point of the ground monitoring stations (R = 0.3928). Surprisingly, we found a positive (in satellite observations and R = 0.2391) and negative correlation (in ground monitoring stations and R = 0.3333) between XCO2 and the O3 concentrations. During the epidemic period, some scholars based on model analysis found that Wuhan's carbon emissions decreased by 16.2% on average. Combined with satellite data, we estimate that Wuhan's XCO2 fell by about 1.12 ppm in February. At last, the government should consider reducing XCO2 and NO2 concentration at the same time to make a synergistic reduction. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic resulted in stay-at-home policies and other social distancing behaviors in the United States in spring of 2020. This paper examines the impact that these actions had on emissions and expected health effects through reduced personal vehicle travel and electricity consumption. Using daily cell phone mobility data for each U.S. county, we find that vehicle travel dropped about 40% by mid-April across the nation. States that imposed stay-at-home policies before March 28 decreased travel slightly more than other states, but travel in all states decreased significantly. Using data on hourly electricity consumption by electricity region (e.g., balancing authority), we find that electricity consumption fell about 6% on average by mid-April with substantial heterogeneity. Given these decreases in travel and electricity use, we estimate the county-level expected improvements in air quality, and, therefore, expected declines in mortality. Overall, we estimate that, for a month of social distancing, the expected premature deaths due to air pollution from personal vehicle travel and electricity consumption declined by approximately 360 deaths, or about 25% of the baseline 1500 deaths. In addition, we estimate that CO2 emissions from these sources fell by 46 million metric tons (a reduction of approximately 19%) over the same time frame. [ABSTRACT FROM AUTHOR]

Increased clean energy production from household solar panels is a potentially vital component of a sustainable energy transition and decarbonisation that can reduce carbon dioxide emissions from many countries. This paper investigates multiple channels of wealth effects on household solar-panel uptake. There is evidence of impacts of both financial and non-financial assets on solar-panel uptake, but the evidence for financial assets is much more robust. Compared to the highest-asset quartile, proportional solar-panel uptake is three percentage points lower for the second-highest quartile of households based on financial assets, all else equal. This gap grows to six percentage points for households in the lowest quartile for financial assets. The results are robust across many models using probit, logit and linear probability formats. Knowledge of the relative magnitudes of impacts of wealth channels is important for policymakers who are considering supporting solar-panel uptake, particularly following the COVID-19 pandemic, when efficiency of public spending will be crucial. Our results reveal that means testing for solar policy support should be based on financial-asset thresholds, rather than non-financial assets or income. These are globally important policy lessons in creating a viable climate change adaptation strategy through solar electrification. [Display omitted] • Financial assets are more important than non-financial assets for residential solar uptake. • Two components of financial assets, private pensions and other assets, have similar impacts. • Liabilities also have a positive association with household solar-panel uptake. • In contrast, income is not a significant contributor to residential solar uptake. • Means testing for policy support should be based on financial-asset thresholds. [ABSTRACT FROM AUTHOR]