Policy mixes to achieve sustainable mobility after the COVID-19 crisis

Selective adsorption of fluorinated super greenhouse gases within a metal-organic framework with dynamic corrugated ultramicropores

Perfluorocompound (PFC) gases play vital roles in microelectronics processing. Requirements for ultra-high purities traditionally necessitate use of virgin sources and thereby hinder the capture, purification, and reuse of these costly gases. Most importantly, gaseous PFCs are incredibly potent greenhouse gases with atmospheric lifetimes on the order of 103-104 years, and thus any environmental emissions have an outsized and prolonged impact on our climate. The development of sorbents that can capture PFC gases from industrial waste streams has lagged substantially behind the progress made over the last decade in capturing CO2 from both point emission sources and directly from air. Herein, we show that the metal-organic framework Zn(fba) (fba2- = 4,4'-(hexafluoroisopropylidene)bis-benzoate) displays an equilibrium selectivity for CF4 adsorption over N2 that surpasses those of all water-stable sorbents that have been reported for this separation. Selective adsorption of both CHF3 and CH4 over N2 is also evident, demonstrating a general preference for tetrahedral C1 gases. This selectivity is enabled by adsorption within narrow corrugated channels lined with ligand-based aryl rings, a site within this material that has not previously been realized as being accessible to guests. Analyses of adsorption kinetics and X-ray diffraction data are used to characterize sorption and diffusion of small adsorbates within these channels and strongly implicate rotation of the linker aryl rings as a gate that modulates transport of the C1 gases through a crystallite. Multi-component breakthrough measurements demonstrate that Zn(fba) is able to resolve mixtures of CF4 and N2 under flow-through conditions. Taken together, this work illuminates the dynamic structure of Zn(fba), and also points toward general design principles that can enable large CF4 selectivities in sorbents with more favorable kinetic profiles.

Recent advances in green technology and Industrial Revolution 4.0 for a sustainable future

This review gives concise information on green technology (GT) and Industrial Revolution 4.0 (IR 4.0). Climate change has begun showing its impacts on the environment, and the change is real. The devastating COVID-19 pandemic has negatively affected lives and the world from the deadly consequences at a social, economic, and environmental level. In order to balance this crisis, there is a need to transition toward green, sustainable forms of living and practices. We need green innovative technologies (GTI) and Internet of Things (IoT) technologies to develop green, durable, biodegradable, and eco-friendly products for a sustainable future. GTI encompasses all innovations that contribute to developing significant products, services, or processes that lower environmental harm, impact, and worsening while augmenting natural resource utilization. Sensors are typically used in IoT environmental monitoring applications to aid ecological safety by nursing air or water quality, atmospheric or soil conditions, and even monitoring species' movements and habitats. The industries and the governments are working together, have come up with solutions-the Green New Deal, carbon pricing, use of bio-based products as biopesticides, in biopharmaceuticals, green building materials, bio-based membrane filters for removing pollutants, bioenergy, biofuels and are essential for the green recovery of world economies. Environmental biotechnology, Green Chemical Engineering, more bio-based materials to separate pollutants, and product engineering of advanced materials and environmental economies are discussed here to pave the way toward the Sustainable Development Goals (SDGs) set by the UN and achieve the much-needed IR 4.0 for a greener-balanced environment and a sustainable future.

Nassani A, H. Binsaeed R, Zaman K. Green investing in China's air cargo industry: Opportunities and challenges for sustainable transportation

Aviation cargo remains vital in the economic activities to transported goods from one place to another. The developed and developing countries mainly consider the transaction routes for air transportation for safe and quickest mode. Chinese economy is attracting the global World through its exports. The country's air cargo system is mainly reliant on gasoline and petroleum-based fuels, which harms the country's green transportation agenda. The high use of fuel combustions in the aviation sector needed greenfield investment that helps to use green energy as an alternative sustainable fuel. Further, sustainable aviation insurance and financial coverage are needed to mitigate the adverse negative externalities from air cargo operations. Based on the crucial facts, the study used air cargo operations, transportation fuel combustions, private investment in the transportation and insurance coverage in the pollution damage function for the China economy using data from 1975 to 2020. The research employed a non-linear ARDL Bounds testing strategy to break down the sequence of variables into dynamic positive and negative multipliers. Positive shocks in air freight, insurance services, and greenfield investment have been shown to reduce carbon emissions immediately and over the long term. In the short term, carbon damages are exacerbated by the negative shocks resulting from the use of transportation fuel and the availability of insurance. Moreover, both the positive and negative shocks associated with transportation fuel combustions and air transportation freights contribute to a rise in carbon damage. The variance decomposition analysis validated the asymmetric correlations between the aforementioned variables in the intertemporal environment. Based on the findings, negative shocks from total fuel combustions are expected to impose the greatest carbon damages over the next decade, followed by insurance services and air freight operations. The study concludes that air cargo operations need to be sustainable transacting routes fueled by biofuel energy sources, greenfield investment, and sustainable aviation insurance coverage to achieve the 'green is clean' transportation agenda.

Impact of COVID-19 Pandemic on Daily Mobility of the Elderly Living in Small Cities in Lodz Province

The article presents a study into the impact that the COVID-19 pandemic had on the daily mobility of those over 60 residing in small towns in the Lodz Province. The study determines the impact on the trip destination, trip frequency, preferred means of transport, distance and duration of trips, and length of the target activity. To achieve these objectives, a survey was conducted using the CATI technique (Computer Assisted Telephone Interviewing), which comprised 500 residents of small towns in the Lodz Province aged 60+, who were divided into three classes of small towns (by population size). In order to determine the impact of the COVID-19 pandemic on the daily mobility of those over 60, the tools the authors decided to use descriptive statistics and hypothesis testing. Overall, the pandemic was found to have had only a minor impact on the changes in transport behavior of those over 60 in small towns. Only 9% of respondents declared any effect on their daily mobility. The impact mainly involved a reduction in travel time and frequency, primarily among the oldest residents. Since a low level of daily mobility leads to low social activity, especially for the elderly-with a consequent sense of loneliness or even depression-towns should take measures to improve the already poor situation, one that has been further exacerbated by the pandemic.

Nanoparticle Exsolution from Nanoporous Perovskites for Highly Active and Stable Catalysts

Nanoporosity is clearly beneficial for the performance of heterogeneous catalysts. Although exsolution is a modern method to design innovative catalysts, thus far it is predominantly studied for sintered matrices. A quantitative description of the exsolution of Ni nanoparticles from nanoporous perovskite oxides and their effective application in the biogas dry reforming is here presented. The exsolution process is studied between 500 and 900 °C in nanoporous and sintered La0.52 Sr0.28 Ti0.94 Ni0.06 O3±δ . Using temperature-programmed reduction (TPR) and X-ray absorption spectroscopy (XAS), it is shown that the faster and larger oxygen release in the nanoporous material is responsible for twice as high Ni reduction than in the sintered system. For the nanoporous material, the nanoparticle formation mechanism, studied by in situ TEM and small-angle X-ray scattering (SAXS), follows the classical nucleation theory, while on sintered systems also small endogenous nanoparticles form despite the low Ni concentration. Biogas dry reforming tests demonstrate that nanoporous exsolved catalysts are up to 18 times more active than sintered ones with 90% of CO2 conversion at 800 °C. Time-on-stream tests exhibit superior long-term stability (only 3% activity loss in 8 h) and full regenerability (over three cycles) of the nanoporous exsolved materials in comparison to a commercial Ni/Al2 O3 catalyst.

Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia

COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstrated a metric of time series, namely log-moving-average-ratio (LMAR), to identify the waves and directions of the changes in the disease cases and check-ins (MySejahtera). Based on the detected waves and changes, we explore the relationship between the two. Using the stimulus-organism-response model with our results, we presented a four-stage model: (1) government-imposed movement restrictions, (2) revenge travel, (3) self-imposed movement reduction, and (4) the new normal. The inverse patterns between check-ins and pandemic waves suggested that the self-imposed movement reduction would naturally happen and would be sufficient for a smaller epidemic wave. People may spontaneously be aware of the severity of epidemic situations and take appropriate disease prevention measures to reduce the risks of exposure and infection. In summary, LMAR is more sensitive to the waves and could be adopted to characterize the association between travel willingness and confirmed disease cases.

Promoting economic and environmental resilience in the post-COVID-19 era through the city and regional on-road fuel sustainability development

How to control the global temperature rise within 1.5 °C in the post-COVID-19 era has attracted attention. Road transport accounts for nearly a quarter of global CO2 emissions, and the related sulfur dioxide (SO2) emissions also trigger air pollution issues in population-intensive cities and areas. Many cities and states have announced a timetable for phasing out urban-based fossil fuel vehicles. By combining a Markov-chain model with a dynamic stochastic general equilibrium (DSGE) model, the impacts of on-road energy structural change led by phasing out fossil fuel vehicles in the road transportation sector are evaluated. The impact of automobile emissions (both CO2 and SO2) on the environment is evaluated, taking into consideration of variation between cities, regions, and countries. Two other major driving forces in addition to CO2 emissions reduction in promoting fossil fuel vehicles' transition toward net-zero carbon are identified and analyzed with multiple different indicators. Under the framework of the DSGE model, climate policy instruments' effects on economic development, energy consumption, and their link to economic and environmental resilience are evaluated under exogenous shocks as well.

A systematic review of the impacts of the coronavirus crisis on urban transport: Key lessons learned and prospects for future cities

The COVID-19 pandemic continues to have a significant impact on the transport sector worldwide. Lockdown and physical distancing requirements continue to be enforced in many cities leading to severe travel restrictions and travel demand reduction to limit the spread of the disease. This article provides bibliometric evidence-based insights into how the pandemic has exposed the vulnerability of established public transport systems and shared mobility solutions. It shows how some transport interventions can accelerate the shift to sustainable urban mobility practices such as micro-mobility and active transport. To accomplish this, the article examines recent studies (244 publications) from the Scopus database using a rigorous systematic literature review approach covering the period from January 2020 to February 2021. Importantly, the mapping of bibliographic coupling and co-citation analysis showed four heterogeneous clusters representing research efforts into "environment", "travel behavior and mode choice", "public transport", and "interventions". Inductive reasoning is used to analyze the disruptions that cities have encountered worldwide, the rapid interventions that were put in place, the aftershocks and the short and long-term impacts. Finally, the paper summarizes the lessons learned and opportunities ahead, and the challenges that must be overcome. The article also outlines pathways to build on the momentum of sustainable practices as part of a holistic approach for enabling resilient transport solutions for the new urban world.

Will the Effects of COVID-19 on Commuting and Daily Activities of the University Students Be Maintained? Evidence from a Small Town in Sicily

As many studies have already shown, the COVID-19 pandemic has had a great impact on the daily routines of people all over the world. University students form one of the most affected groups of people, since they have had to interrupt many of the activities that they usually perform, and have also had to get used to a new way of learning (e-learning). An important question that now arises is whether the changes that were identified within the pandemic period are to be maintained when the risk of being infected is eliminated. To this end, 537 university students of the Kore University of Enna, Italy, were surveyed. Their responses are analyzed descriptively, and an ordinal regression model is being developed to shed more light on the likelihood of retaining changes related with to transport mode choice. The results show that the likelihood of retaining all the changes when commuting and during daily activities is very high, demonstrating such willingness from the participants. Moreover, it has been shown that public transport has increased the probability of people being negatively affected by the pandemic in the long-term, and opportunities appear for increasing the modal share of active modes.

In Search of Non-Obvious Relationships between Greenhouse Gas or Particulate Matter Emissions, Renewable Energy and Corruption

The article concerns the issue of the existence of non-obvious relationships and of potential correlations between the emission of greenhouse gases and particulate matter (PM), renewable energy and corruption perceptions. Additionally, it analyses the possible impact of these above-mentioned connections on the economic, environmental and social situation in the context of further economic development, including during the COVID-19 pandemic and in relation to European countries. The issue of reducing dirty energy sources and corrupt activities is not only a problem considered at the state level, but it is very closely related to the operation of many private enterprises. The conducted research applied methods of desk research as well as comparative quantitative analyses and used extensive statistical data of most European Union member states as well as the United Kingdom and Norway. The ambiguity of the results obtained in the research does not allow for an explicit verification of the existence of relationships between corruption and the pro-ecological initiatives influencing the lower intensity of greenhouse gases and particulate matter (PM) to the atmosphere or increasing share of renewable energy in the whole energy consumption. However, in many analysed cases it is possible to observe the occurrence of the indicated relationships, which, although not considered to be a rule, may give direction to further detailed research in this area, in particular in order to show the resulting beneficial or unfavourable implications for the performance and development of companies and the economy as a whole with rules of sustainability.

Development of Electromobility in European Union Countries under COVID-19 Conditions

The introduction of electromobility contributes to an increase in energy efficiency and lower air pollution. European countries have not been among the world’s leading countries in this statistic. In addition, there have been different paces in the implementation of electromobility in individual countries. The main purpose of this paper is to determine the directions of change and the degrees of concentration in electromobility in European Union (EU) countries, especially after the economic closure as a result of the COVID-19 pandemic. The specific objectives are to indicate the degree of concentration of electromobility in the EU and changes in this area, especially during the COVID-19 pandemic; to determine the dynamics of changes in the number of electric cars in individual EU countries, showing the variability in this aspect, while also taking into account the crisis caused by COVID-19; to establish the association between the number of electric cars and the parameters of the economy. All EU countries were selected for study by the use of the purposeful selection procedure, as of December 31, 2020. The analyzed period covered the years 2011–2020. It was found that in the longer term, the development of electromobility in the EU, measured by the number of electric cars, is closely related to the economic situation in this area. The crisis caused by the COVID-19 pandemic has influenced the economic situation in all EU countries, but has not slowed down the pace of introducing electromobility, and may have even accelerated it. In all EU countries, in the first year of the COVID-19 pandemic, the dynamics of introducing electric cars into use increased. The growth rate in the entire EU in 2020 was 86%, while in 2019 it was 48%. The reason was a change in social behavior related to mobility under conditions of risk of infection. COVID-19 has become a positive catalyst for change. The prospects for the development of this type of transport are very good because activities related to the development of the electromobility sector perfectly match the needs related to the reduction of pollution to the environment.

Impact of the COVID-19 Pandemic to the Sustainability of the Energy Sector

In order to control the COVID-19 pandemic, the governments of the world started to implement measures regarding social distance and social contacts, including closures of cities, work and study relocations, and work suspension. The epidemical situation and the lockdown of the economy by governments in various countries caused changes in production, changes in the habits of energy consumers and other energy-related changes. This article analyses the impact of the global pandemic on the energy sector and the relationship with the progress to the sustainability of the energy sector. The systematic literature review was performed in the Web of Science (WoS) database. The research follows recommendations of the SALSA (Search, Appraisal, Synthesis and Analysis) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approaches. A total of 113 relevant articles were selected for the analysis. All selected articles were categorized according to their application and impact areas. The five main impact areas of the COVID-19 pandemic to the sustainability of the energy sector were identified: consumption and energy demand; air pollution; investments in renewable energy; energy poverty; and energy system flexibility. Based on the current research findings and perception of the problem, the main insights for future research in the field are provided.

Seesaw scenarios of lockdown for COVID-19 pandemic: Simulation and failure analysis

The ongoing COVOD-19(SARS-CoV-2) outbreak has had a devastating impact on the economy, education and businesses. In this paper, the behavior of an epidemic is simulated on different contact networks. Herein, it is assumed that the infection may be transmitted at each contact from an infected person to a susceptible individual with a given probability. The probability of transmitting the disease may change due to the individuals' social behavior or interventions prescribed by the authorities. We utilized simulation on the contact networks to demonstrate how seesaw scenarios of lockdown can curb infection and level the pandemic without maximum pressure on the poor societies. Soft scenarios consist of closing businesses 2, 3, and 4 days in between with four levels of lockdown respected by 25%, 50%, 75%, and 100% of the population. The findings reveal that the outbreak can be flattened under softer alternatives instead of a doomsday scenario of complete lockdown. More specifically, it is turned out that proposed soft lockdown strategies can flatten up to 120% of the pandemic course. It is also revealed that transmission probability has a crucial role in the course of the infection, growth rate of the infection, and the number of infected individuals.

Containment, Health, and Social Policies in the Time of COVID-19 - Patterns and Determinants of Initial Reponses from Spring 2020 Across 120 Countries

The COVID-19 pandemic has triggered an unprecedented number of policy responses around the world across multiple policy domains. While governments have combined containment and health policies with social policies (CHSP) during the initial phase of the pandemic in various ways, current literature offers little knowledge of the patterns of these combinations and their determinants and outcomes. This paper fills this gap by investigating CHSP combinations across more than 120 countries. We further examined whether the CHSP policy response was determined by political regimes or compensation hypotheses-serving the purposes of responding to pre-existing economic downturns, inequality, or social unrest. We also investigated the associations between CHSP responses and mobility, virus infection, and unemployment. Using policy data from the Oxford COVID-19 Government Response Tracker, results from sequence analysis indicated that governments' CHSP responses could be clustered into five categories: high social policies (SP), middle SP, containment and health (CH) leading SP, low SP, and gradual high SP. We used multinomial regression models to investigate determinants of CHSP responses. We found that CHSP policy responses did not differ by political regime, and CHSP combinations were not driven by compensation hypotheses. Instead, GDP per capita and government effectiveness were the key drivers for high levels of policy responses. We also found that low SP responses were associated with fewer mobility changes. Taken together, our findings suggest that lower income countries required more support and resources in order for them to adopt necessary CH and SP responses.

Sustainable Consumption in Consumer Behavior in the Time of COVID-19: Topic Modeling on Twitter Data Using LDA

By using text mining techniques, this study identifies the topics of sustainable consumption that are important during the COVID-19 pandemic. An Application Programming Interface (API) streaming method was used to extract the data from Twitter. A total of 14,591 tweets were collected using Twitter streaming API. However, after data cleaning, 13,635 tweets were considered for analysis. The objectives of the study are to identify (1) the topics users tweet about sustainable consumption and (2) to detect the emotion-based sentiments in the tweets. The study used Latent Dirichlet Allocation (LDA) algorithm for topic modeling and the Louvain algorithm for semantic network clustering. NRC emotion lexicon was used for sentiment analysis. The LDA model discovers six topics: organic food consumption, food waste, vegan food, sustainable tourism, sustainable transport, and sustainable energy consumption. While the Louvain algorithm detects four clusters—lifestyle and climate change, responsible consumption, energy consumption, and renewable energy, sentiment analysis results show more positive emotions among the users than the negative ones. The study contributes to existing literature by providing a fresh perspective on various interconnected topics of sustainable consumption that bring global consumption to a sustainable level.

Impact of COVID-19 pandemic on socio-economic, energy-environment and transport sector globally and sustainable development goal (SDG)

The United Nation's Sustainable Development Goals (SDGs) want to have a peaceful world where human life will be in a safe, healthy, sustainable environment without any inequalities. However, the year 2020 experienced a global pandemic due to COVID-19. This COVID-19 created an adverse impact on human life, economic, environment, and energy and transport sector compared to the pre-COVID-19 scenario. These above-mentioned sectors are interrelated and thus lockdown strategy and stay at home rules to reduce the COVID-19 transmission had a drastic effect on them. With lockdown, all industry and transport sectors were closed, energy demand reduced greatly but the time shift of energy demand had a critical impact on grid and energy generation. Decreased energy demand caused a silver lining with an improved environment. However, drowned economy creating a negative impact on the human mind and financial condition, which at times led to life-ending decisions. Transport sector which faced a financial dip last year trying to coming out from the losses which are not feasible without government aid and a new customer-friendly policy. Sustainable transport and the electric vehicle should take high gear. While people are staying at home or using work from home scheme, building indoor environment must specially be taken care of as a compromised indoor environment affects and increases the risk of many diseases. Also, the energy-efficient building will play a key role to abate the enhanced building energy demand and more generation from renewable sources should be in priority. It is still too early to predict any forecast about the regain period of all those sectors but with vaccination now being introduced and implemented but still, it can be considered as an ongoing process as its final results are yet to be seen. As of now, COVID-19 still continue to grow in certain areas causing anxiety and destruction. With all these causes, effects, and restoration plans, still SDGs will be suffered in great order to attain their target by 2030 and collaborative support from all countries can only help in this time.

Policy Impact on Regional Biogas Using a Modular Modeling Tool

Biogas development is expected to contribute to the National Recovery and Resilience plan to overcome the COVID-19 shock. Estimation of the agricultural biogas potential in economic terms can contribute to refining policies inciting effective sector development. In this paper, we attempt to do so by modeling a biogas chain from dedicated crops and livestock waste. This was achieved by coupling farming models to the biogas industry in a partial equilibrium framework. This allows for a comprehensive investigation of alternative measures in technology, size, spatial distribution and land use change. The integrated model was implemented in Lubelskie for the previous policy (green certificates) and the current policy (auction market). In both cases, the bottom-up profit driven optimization resulted in approximately 40 MWel, which shows a robust economic potential more than four times the biogas sector’s actual capacity in the region, also providing the detailed structure of the sector. When focusing on the industry structure, both scenarios give similar results regarding 1–2 MWel plant size close to the observed situation. The model also suggests a large number of new facilities <250 kWel, twice as important under scenario 2, indicating that other conditions beyond economy profitability should be fulfilled for further sector development.