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‘DRIVE4EU - Dandelion Rubber and Inulin Valorization and Exploitation for Europe’, a demonstration project, aims at the development of a value chain for natural rubber and inulin from Rubber dandelions. The objective of the project is to set up a new European chain for the production and processing of natural rubber. This will enable the EU to become less dependent on the import of natural rubber and at the same time to respond to the threat of a global rubber shortage. The viability of using Rubber dandelions for rubber and inulin production depends on the sustainability of this new value chain. The results of a general economic assessment shows that the total costs over the whole value chain are dominated by the costs for cultivation and harvesting and the cost for biorefining. The combination of natural rubber and inulin makes Rubber dandelion very interesting as a production platform. Proceedings of the 25th European Biomass Conference and Exhibition, 12-15 June 2017, Stockholm, Sweden, pp. 1292-1293

The Indian Ocean Experiment (INDOEX) was an international, multiplatform field campaign to measure long-range transport of air pollution from South and Southeast Asia toward the Indian Ocean during the dry monsoon season in January to March 1999. Surprisingly high pollution levels were observed over the entire northern Indian Ocean toward the Intertropical Convergence Zone at about 6°S. We show that agricultural burning and especially biofuel use enhance carbon monoxide concentrations. Fossil fuel combustion and biomass burning cause a high aerosol loading. The growing pollution in this region gives rise to extensive air quality degradation with local, regional, and global implications, including a reduction of the oxidizing power of the atmosphere.

Abstract In this study, we investigate the driving forces behind the changes in residential energy consumption (REC) in China’s urban and rural areas over the 2001–2012 period. Based on the logarithmic mean Divisia index method, the REC changes are decomposed into seven driving forces, which are climate change, energy price, energy expenditure mix, energy cost share (in total expenditure), expenditure share (in income), per capita income and population effects. According to the results, climate effect due to increasing days with abnormal temperature, energy cost share effect characterized by more expenditure to be paid for energy use, income effect describing constant income growth in the residential sector definitely increase REC in both urban and rural areas. In contrast, energy prices and energy expenditure mix effects negatively contribute to the REC increase, respectively because of the increase in energy prices and the transition from the low-priced energy to high-priced energy. Expenditure share and population effects play opposite roles in urban and rural areas, and the reasons and implications are analysed in depth.

China has achieved impressive rapid economic growth over the past 30 years but accompanied by significant extreme weather events and environmental changes caused by global change and overfast urbanization. Using the absolute hazards index (AHI), we assessed the spatial distribution patterns and related health effects of 4 major extreme natural disasters, including drought, floods (landslides, mudslides), hails, and typhoons from 2000 to 2011 at the provincial level in China. The results showed that (1) central and south China were the most affected by the 4 natural disasters, and north China suffered less; (2) the provinces with higher AHI suffered most from total death, missing people, collapse, and emergently relocated population; (3) the present health emergency response system to disasters in China mainly lacks a multidisciplinary approach. In the concluding section of this article, suggestions on preparedness and rapid response to extreme health events from environmental changes are proposed.

In this article, we introduce and study a two-stage stochastic optimization problem suitable to solve strategic optimization problems of car-sharing systems that utilize electric cars. By combining the individual advantages of car-sharing and electric vehicles, such electric car-sharing systems may help to overcome future challenges related to pollution, congestion, or shortage of fossil fuels. A time-dependent integer linear program and a heuristic algorithm for solving the considered optimization problem are developed and tested on real world instances from the city of Vienna, as well as on grid-graph-based instances. An analysis of the influence of different parameters on the overall performance and managerial insights are given. Results show that the developed exact approach is suitable for medium sized instances such as the ones obtained from the inner districts of Vienna. They also show that the heuristic can be used to tackle very-large-scale instances that cannot be approached successfully by the integer-programming-based method.

The acceptability, energy consumption, and environmental benefits of electric vehicles are highly dependent on travel patterns. With increasing ride-hailing popularity in mega-cities, urban mobility patterns are greatly changing; therefore, an investigation of the extent to which electric vehicles would satisfy the needs of ride-hailing drivers becomes important to support sustainable urban growth. A first step in this direction is reported here. GPS-trajectories of 144,867 drivers over 104 million km in Beijing were used to quantify the potential acceptability, energy consumption, and costs of ride-hailing electric vehicle fleets. Average daily travel distance and travel time for ride-hailing drivers was determined to be 129.4 km and 5.7 h; these values are substantially larger than those for household drivers (40.0 km and 1.5 h). Assuming slow level-1 (1.8 KW) or moderate level-2 (7.2 KW) charging is available at all home parking locations, battery electric vehicles with 200 km all electric range (BEV200) could be used by up to 47% or 78% of ride-hailing drivers and electrify up to 20% or 55% of total distance driven by the ride-hailing fleet. With level-2 charging available at home, work, and public parking, the acceptance ceiling increases to up to 91% of drivers and 80% of distance. Our study suggests that long range BEVs and widespread level-2 charging infrastructure are needed for large-scale electrification of ride-hailing mobility in Beijing. The marginal benefits of increased all electric range, effects on charging infrastructure distribution, and payback times are also presented and discussed. Given the observed heterogeneity of ride-hailing vehicle travel, our study outlines the importance of individual-level analysis to understand the electrification potential and future benefits of electric vehicles in the era of shared smart transportation.

Tourism is an important economic sector that has a significant impact on sustainability indicators, such as GHG emissions and cohesion. Local policy makers are increasingly challenged to manage the urban tourism system at large. As part of a EU funded project, the authors have conceptualized sustainable urban tourism as the ‘management of competing values’ represented in a conceptual model of ecology, visitability, livability, equity, economic growth and smart citizenship. A simulation game was designed and implemented to improve social learning about these competing values. The game was played in six European cities, with around 15 local policy-makers and stakeholders in each session. The players indicated a high level of satisfaction with the game and social learning. In order to understand to what extent the game is able to validate and communicate the competing values model, the start and end states of the tourism values of the cities, as logged in the game’s dashboard, were analyzed in a comparative manner. The analysis shows significant differences in how cities manage sustainable tourism, with marked differences in ecology and smart citizenship. The differences in tourism issues and policy making styles demonstrate the value of a simulation approach to support future planning processes.

Better prediction of turbulent airflow around urban trees is necessary because it impacts urban pollutant dispersion, outdoor thermal comfort, energy efficiency, pedestrian-level comfort and urban heat island mitigation. A major challenge is how to obtain an accurate numerical model of the turbulent flow field around trees and an improved parameterization of the turbulent momentum deficit using the drag coefficient (Cd). To address this challenge, we use wind tunnel tests and real trees to measure Cd for four common subtropical tree species: Ficus microcarpa, Mangifera indica, Michelia alba and Bauhinia blakeana. The results show that the Cd of the four trees ranges from 0.523 to 0.932, and that the negative relationship between Cd and wind speed (U) can be expressed by the exponential formula Cd=a*U−b. A three-dimensional model of wind modification by trees is proposed, and its accuracy is verified with wind tunnel measurements. With precise Cd and model, the predictability of the influence of trees on urban wind in subtropical areas is enhanced (root mean square error RMSE ranging from 2.89 m/s to 0.45 m/s). Future development and applications of the numerical model will help provide useful guidelines for urban landscape management and sustainable urban planning in terms of urban ventilation.