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The global spread of the COVID-19 virus has led to difficulties in many branches of the economy, including significant effects on the urban transport industry. Thus, countries around the world have introduced different mobility policies during the pandemic. Due to government restrictions and the changed behaviors of transport users, companies providing modern urban mobility solutions were forced to introduce new business practices to their services. These practices are also apparent in the context of the electric shared mobility industry. Although many aspects and problems of electric shared mobility have been addressed in scientific research, pandemic scenarios have not been taken into account. Noticing this research gap, we aimed to update a previously developed model of factors that influence the operation of electric shared mobility by incorporating aspects related to the COVID-19 pandemic and its impact on this industry. This article aims to identify the main factors influencing the electric shared mobility industry during the COVID-19 and post-lockdown periods, together with their operation areas and the involved stakeholders. The research was carried out on the basis of expert interviews, social network analysis (SNA), and the use of the R environment. The article also presents sustainable transport management recommendations for cities and transport service operators, which can be implemented after a lockdown caused by an epidemic. The results in this paper can be used to support transport modeling and the creation of new policies, business models, and sustainable development recommendations. The contents will also be helpful to researchers worldwide in preparing literature reviews for articles related to sustainable management in the COVID-19 pandemic reality. [ABSTRACT FROM AUTHOR]

The transportation sector is a major contributor to carbon dioxide emissions, and the resulting climate change. The diffusion of alternative fuel vehicles, including hybrid electric vehicles (HEV), is an important solution for these issues. This study aimed to evaluate the factors affecting the ownership ratio of HEVs, particularly passenger vehicles, and the regional differences in the purchase of HEVs in Japan. This study performed a fixed-effects regression analysis with panel data for 47 prefectures during the period 2005–2015 to evaluate the factors affecting the HEV ownership ratio and conducted three cluster analyses to investigate the regional differences in diffusion in terms of price categories, body types, and drive systems of HEVs. Some demographic and social factors were found to affect the ownership ratio in Japan, whereas economic factors, including prefecture-level subsidies for purchasing HEVs, were not. Regarding regional differences, prefectures in urban areas with higher income levels tend to purchase more expensive and large-sized HEVs. These results suggest that a strategy to sell the right vehicle to the right person and region is essential for further promoting HEVs in Japan. [ABSTRACT FROM AUTHOR]

Extensive surfaces of land are currently under-utilized, marginal and/or contaminated (MUC) in many EU and neighbouring countries. In the past few years, scientific research has demonstrated that bioenergy crops can potentially render this land profitable, generating income for the local populations and, at the same time, reaching the goals of the new Renewable Energy Directive (REDII) without interfering with food production. The main purpose of this paper is to measure net economic returns by computing benefits and costs of low indirect Land Use Change (iLUC) biofuel production on MUC land from the perspective of both the private investors and social welfare. A standard cost-benefit technique was applied to analyse and compare net returns of different advanced bioenergy value-chains in monetary terms. Productivity, economic feasibility and green-house gas (GHG) emissions impact were assessed and considered for the economic analysis. The considered pathways were cellulosic or second generation (2G) ethanol from Giant reed (Arundo donax) in Italy, electricity from miscanthus, biochemicals from spontaneous grass and cultivated Lucerne (Alpha-alfae) with sorghum for biomethane in Germany, and 2G ethanol from Willow (Salix viminalis) in Ukraine. For the risk assessment, Monte Carlo simulation was applied. The results indicated that in Italy and Ukraine, although the production of 2G ethanol would allow positive net yearly margins, the investments will not be profitable compared to the baseline scenarios. In Germany, the work showed good profitability for combined heat and power (CHP) and biochemicals. On the other hand, investments in biomethane showed negative results compared with the baseline scenarios. Finally, the Monte Carlo simulation enabled us to identify the range of possible economic results that could be attained once volatility is factored in. While for Italy the likelihood of yielding positive results remains lower than 20 percent, case studies in Ukraine and Germany showed higher certainty levels, ranging from 49 to 91 percent. [ABSTRACT FROM AUTHOR]

A Monte Carlo simulation methodology is suggested in order to assess the impact of ambient wind on a vehicle's performance and emissions. A large number of random wind profiles is generated by implementing the Weibull and uniform statistical distributions for wind speed and direction, respectively. Wind speed data are drawn from eight cities across Europe. The vehicle considered is a diesel-powered, turbocharged, light-commercial vehicle and the baseline trip is the worldwide harmonized light-duty vehicles WLTC cycle. A detailed engine-mapping approach is used as the basis for the results, complemented with experimentally derived correction coefficients to account for engine transients. The properties of interest are (engine-out) NO and soot emissions, as well as fuel and energy consumption and CO2 emissions. Results from this study show that there is an aggregate increase in all properties, vis-à-vis the reference case (i.e., zero wind), if ambient wind is to be accounted for in road load calculation. Mean wind speeds for the different sites examined range from 14.6 km/h to 24.2 km/h. The average increase in the properties studied, across all sites, ranges from 0.22% up to 2.52% depending on the trip and the property (CO2, soot, NO, energy consumption) examined. Based on individual trip assessment, it was found that especially at high vehicle speeds where wind drag becomes the major road load force, CO2 emissions may increase by 28%, NO emissions by 22%, and soot emissions by 13% in the presence of strong headwinds. Moreover, it is demonstrated that the adverse effect of headwinds far exceeds the positive effect of tailwinds, thus explaining the overall increase in fuel/energy consumption as well as emissions, while also highlighting the shortcomings of the current certification procedure, which neglects ambient wind effects. [ABSTRACT FROM AUTHOR]

Air pollution caused by traffic and other sources remains a challenge in big cities and urbanized areas in Germany and abroad. Nitrogen dioxide emissions, particulate matter, noise emissions, and ozone are still problematic issues with negative impacts on both the environment and human health. In 2018, the German Federal Government launched the "Lead City Program," a €130-million fund to support five selected so-called Lead Cities in developing and implementing air quality policies. This article comparatively analyzes the policy-making process and policy content for better air quality in the three (out of five) Lead Cities—Essen, Herrenberg, and Reutlingen. Conceptually, we rely on two theoretical frameworks—the policy package approach (PPA) and the multiple streams framework (MSF). The objective, thus, is an ex-post analysis of policy development by means of two policy science-based concepts. Based on document-based desk research and qualitative interviews with policymakers and stakeholders in each of the three cities, we identified a number of key variables that created a window of opportunity and paved the way for the selection of the policy packages. The resulting five key variables are direct interaction between the different governance levels, long-standing non-compliance with the European Union (EU) NO2 limit values in many German cities, the resulting European and national infringement proceedings, the diesel scandal, and the Lead City Program as overall multiple stream-coupling facilitators. The results are then discussed regarding the explanatory power of MSF and PPA and the mutual potential linkages these concepts offer for future research. [ABSTRACT FROM AUTHOR]

Timely and accurate agricultural information is needed to inform resource allocation and sustainable practices to improve food security in the developing world. Obtaining this information through traditional surveys is time consuming and labor intensive, making it difficult to collect data at the frequency and resolution needed to accurately estimate the planted areas of key crops and their distribution during the growing season. Remote sensing technologies can be leveraged to provide consistent, cost-effective, and spatially disaggregated data at high temporal frequency. In this study, we used imagery acquired from unmanned aerial vehicles to create a high-fidelity ground-truth dataset that included examples of large mono-cropped fields, small intercropped fields, and natural vegetation. The imagery was acquired in three rounds of flights at six sites in different agro-ecological zones to capture growing conditions. This dataset was used to train and test a random forest model that was implemented in Google Earth Engine for classifying cropped land using freely available Sentinel-1 and -2 data. This model achieved an overall accuracy of 83%, and a 91% accuracy for maize specifically. The model results were compared with Rwanda's Seasonal Agricultural Survey, which highlighted biases in the dataset including a lack of examples of mixed land cover. [ABSTRACT FROM AUTHOR]

This study quantifies the potential responses of 11 staple crop yields to projected changes in temperature and precipitation in Rwanda, using a cross sectional model based on yield data collected across more than 14,000 villages. We incorporated a relatively high spatial resolution dataset on crop productivity, considered a broad range of crops relevant to national agricultural production priorities, used environmental data developed specifically for Rwanda, and reported uncertainty both from our estimation model and due to uncertainty in future climate projections. We estimate that future climate change will have the largest impacts on potential productivity of maize, bush bean, and Irish potato. All three crops are likely to experience a reduction in potential yields of at least 10% under Representative Concentration Pathway (RCP) 4.5 and at least 15% under RCP 8.5 by 2050. Notably, these are important crops nationally, and three of the crops targeted by Rwanda's Crop Intensification Program. We find that the most severe reductions in potential crop yields will occur in the drier eastern savannah and plateau regions, but that the impacts of climate change could be neutral or even positive in the highlands through mid-century. The refined spatial scale of our analysis allows us to identify potentially vulnerable regions where adaptation investments may need to be prioritized to support food security and climate resilience in Rwanda's agricultural sector. [ABSTRACT FROM AUTHOR]