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This paper aims at reviewing the life cycle assessment (LCA) literature on second generation bioethanol based on lignocellulosic biomass and at identifying issues to be resolved for good LCA practice. Reviews are carried out on respective LCA studies published over the last six years. We use the classification of lignocellulosic biomass to define system boundaries, so that the comparison among LCA results can be thoroughly assessed based on identified system components. A basis for attributing environmental burden for different biomass feedstocks is also suggested. Despite the non-homogeneous systems, we conclude that second generation bioethanol performs better than fossil fuel at least for the two most studied impact categories, net energy output and global warming. For the latter category, carbon sequestration at the biomass generation stage can even consistently offset the GHG emissions from all parts of the life cycle chains at high ethanol percentage (≥85%). The aspect of biogenic carbon and agrochemical input for energy crops and biomass residues, and the effect of removal of the latter from soil have not been treated consistently. In contrast, the exclusion of upstream chain of biomass waste feedstocks is observed in practice. The bioethanol conversion process is mostly based on simultaneous saccharification and co-fermentation, characterized by high yield and low energy input. In this regard, the LCA results tend to under estimate the real impacts of the current technology. The choice of allocation methods strongly influences the final results, particularly when economic value is used as a reference. Substitution of avoided burden seems to be the most popular allocation method in practice, followed by partition based on mass, energy, and economic values.

Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity, actual litter decomposition, and potential litter decomposition) during secondary succession after shifting cultivation in wet tropical forest of Mexico.We test the importance of three alternative drivers of ecosystem processes: vegetation biomass (vegetation quantity hypothesis), community‐weighted trait mean (mass ratio hypothesis), and functional diversity (niche complementarity hypothesis) using structural equation modeling. This allows us to infer the relative importance of different mechanisms underlying ecosystem process recovery.Ecosystem process rates changed during succession, and the strongest driver was aboveground biomass for each of the processes. Productivity of aboveground stem biomass and leaf litter as well as actual litter decomposition increased with initial standing vegetation biomass, whereas potential litter decomposition decreased with standing biomass. Additionally, biomass productivity was positively affected by community‐weighted mean of specific leaf area, and potential decomposition was positively affected by functional divergence, and negatively by community‐weighted mean of leaf dry matter content.Our empirical results show that functional diversity and community‐weighted means are of secondary importance for explaining changes in ecosystem process rates during tropical forest succession. Instead, simply, the amount of vegetation in a site is the major driver of changes, perhaps because there is a steep biomass buildup during succession that overrides more subtle effects of community functional properties on ecosystem processes. We recommend future studies in the field of biodiversity and ecosystem functioning to separate the effects of vegetation quality (community‐weighted mean trait values and functional diversity) from those of vegetation quantity (biomass) on ecosystem processes and services.

In wetlands, a distinct zonation of plant species composition occurs along moisture gradients, due to differential flooding tolerance of the species involved. However, "flooding" comprises two important, distinct stressors (soil oxygen demand [SOD] and partial submergence) that affect plant survival and growth. To investigate how these two flooding stressors affect plant performance, we executed a factorial experiment (water depth x SOD) for six plant species of nutrient-rich and nutrient-poor conditions, occurring along a moisture gradient in Dutch dune slacks. Physiological, growth, and biomass responses to changed oxygen availability were quantified for all species. The responses were consistent with field zonation, but the two stressors affected species differently. Increased SOD increased root oxygen deprivation, as indicated by either raised porosity or increased alcohol dehydrogenase (ADH) activity in roots of flood-intolerant species (Calamagrostis epigejos and Carex arenaria). While SOD affected root functioning, partial submergence tended more to reduce photosynthesis (as shown both by gas exchange and 13C assimilation), leaf dark respiration, 13C partitioning from shoots to roots, and growth of these species. These processes were especially affected if the root oxygen supply was depleted by a combination of flooding and increased SOD. In contrast, the most flood-tolerant species (Juncus subnodulosus and Typha latifolia) were unaffected by any treatment and maintained high internal oxygen concentrations at the shoot : root junction and low root ADH activity in all treatments. For these species, the internal oxygen transport capacity was well in excess of what was needed to maintain aerobic metabolism across all treatments, although there was some evidence for effects of SOD on their nitrogen partitioning (as indicated by 865N values) and photosynthesis. Two species intermediate in flooding tolerance (Carex nigra and Schoenus nigricans) responded more idiosyncratically, with different parameters responding to different treatments. These results show that partial submergence and soil flooding are two very different stressors to which species respond in different ways, and that their effects on physiology, survival, and growth are interactive. Understanding species zonation with water regimes can be improved by a better appreciation of how these factors affect plant metabolism independently and interactively.

Using 40-year experiment data from a mono-modal rainfall area of northern Togo, we analyzed soil fertility dynamics when 2 and 3-year fallows were alternated with 3-year rotation of groundnut, cotton and sorghum. The control treatment consisted to continuous cultivate the soil in a rotation of groundnut/cotton/sorghum without fallow periods. For each rotation, two fertilisation rates were applied: no fertilisation and mineral fertiliser application during the cropping and/or the fallow periods. Yields of unfertilised crops, which averaged 1 t ha-1 during the first years of cultivation, were often nil in the long-term. In the long-term, yields of fertilised cotton and sorghum decreased by 32 and 50 %, respectively compared to the average of 2.4 and 1.6 t ha-1 obtained during the first decade of cultivation. The long-term decline in crop productivity was mitigated when fallow periods were alternated with cropping periods, and consequently there was partial compensation in terms of production for the unproductive fallowed plots. Long-term yields of fertilised cotton and sorghum in the periodically fallowed plots were 40 and 50 % higher than those in continuously cropped plots, respectively; they were 90 and 60 % higher than those in continuously cropped plots without fertilisation. Like for crop productivity, soil C, N and exchangeable Ca and Mg decreased less in periodically fallowed plots than in continuously cropped plots. The limited soil C decline when fallows were alternated with crops appears to be the consequence of no-tillage period rather than the effect of the highest C inputs to the soil.

Due to the increasing awareness of climate change, depletion of natural resources, and increasing world population, companies in the agri-food sector need to redesign their existing supply chains and take into account both the economic and environmental impact of their operations. In practice not all the required information is available in advance due to various sources of uncertainty in agri-food supply chains. In this research a multi-objective two-stage stochastic programming model is proposed to analyse and evaluate the economic and environmental impacts to account for uncertainty in agri-food supply chains. A mushroom supply chain in the Netherlands is presented as an illustrative case study. Optimal production planning decisions calculated with a two-stage stochastic programming model are compared with the results of an equivalent deterministic model. The results of the optimizations show that accounting for stochasticity in important model parameters can reduce the difference between expected and realized economic performance by approximately 4% on average. Moreover, this paper demonstrates that including stochastic model parameters can reduce the environmental impact without compromising the current economic performance. Given the assumptions in the setup of the case study and the available information, it is concluded that applying a 2-stage stochastic programming approach for production planning decisions can lead to improved economic and environmental performance in an agri-food supply chain. New findings in real-life case studies are needed to get profound insights and understanding on the impact of uncertainty on production planning decisions in sustainable agri-food supply chains.

Sustainability is commonly assessed along environmental, societal, economic and technological dimensions. A crucial aspect of sustainability is that inter-generational equality must be ensured. This requires that sustainability is attained in the here and now as well as into the future. Therefore, what is perceived as 'sustainable' changes as a function of societal opinion and technological and scientific progress. A concept that describes the ability of systems to change is adaptive capacity. Literature suggests that the ability of systems to adapt is an integral part of sustainable development. This paper demonstrates that indicators measuring adaptive capacity are underrepresented in current urban water sustainability studies. Furthermore, it is discussed under which sustainability dimensions adaptive capacity indicators are lacking and why. Of the >90 indicators analysed, only nine are adaptive capacity indicators, of which six are socio-cultural, two technological, one economical and none environmental. This infrequent use of adaptive capacity indicators in sustainability assessments led to the conclusion that the challenge of dynamic and uncertain urban water systems is, with the exception of the socio-cultural dimension, not yet sufficiently reflected in the application of urban water sustainability indicators. This raises concerns about the progress towards urban water systems that can transform as a response variation and change. Therefore, research should focus on developing methods and indicators that can define, evaluate and quantify adaptive capacity under the economic, environmental and technical dimension of sustainability. Furthermore, it should be evaluated whether sustainability frameworks that focus on the control processes of urban water systems are more suitable for measuring adaptive capacity, than the assessments along environmental, economic, socio-cultural and technological dimensions.

European consumers are willing to pay more for “green” electricity, as they highly value renewable energy sources for the contribution to combating climate change. There is a push for getting higher levels of sustainability, leading to a differentiation of Europe‘s electricity market. In this differentiation, the large potential of wind energy is recognized. More specifically, North Sea countries prefer to plan wind arrays (far) out at sea. This article offers a review of the main arguments for offshore wind energy, described in comparison with its onshore counterpart. It is stated that offshore wind farms (OWFs) generate “dark green” electricity as they mitigate greenhouse gas emissions and contribute to the protection of (some) marine life. Applying an informational governance framework, this article further assesses whether this dark green message has been exploited through further differentiation of the electricity market, and provides an analysis of why this is not (yet) the case. It is concluded that the dominant discourse in onshore wind power development hinders a favorable ecological differentiation toward offshore wind power.

Abstract This work assesses the impacts of aggressive driving behavior on pollutants emissions and energy consumption at a city level. Furthermore, it performs an economic analysis considering the potential avoided emissions and fuel savings and discusses potential policy measures to address this topic. The results showed that aggressive driving significantly impacts energy consumption and emissions, with energy consumption increasing by more than ∼200% and emissions by 330% for aggressive driving compared to non-aggressive driving (in MJ/km and in g/km, respectively). This increment was found to be even higher for diesel vehicles than for gasoline vehicles. On the contrary, gasoline vehicles showed higher percentages of increase for most emissions (CO, NOx and NO). Results also revealed that aggressive driving impacts are higher for local streets when examining the city level. Moreover, the economic analysis showed that significant cost reductions may be achieved by avoiding aggressive driving, reaching up to 52.5 k€ on a daily basis. In conclusion, this study is of particular relevance to policy makers and urban planners, enabling to obtain a comprehensive overview of the impacts of aggressive driving behaviors at a city level and providing new insights to perform further developments and to assess the feasibility of the implementation of policy measures.