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Abstract The aim of this study is to evaluate the incremental innovation performance of nuclear energy projects. Within this context, a novel model is generated which consists of two different stages, and large nuclear reactors are taken into consideration. Firstly, the Pythagorean fuzzy DEMATEL is used to weight the phases of technology S-Curve for nuclear energy projects. Moreover, the second stage includes the ranking two-generation technology S-curve with integer patterns for nuclear energy projects. In this framework, the best combinations are selected for innovation life cycle pattern with the integer code series. The findings demonstrate that the nuclear energy companies need to consider the two-generation technology S-Curve because continuous technological developments are occurring for nuclear power generation. It is also determined that aging in the first generation is the most significant period of two-generation technology S-Curve for nuclear energy projects. In this process, critical decisions should be made regarding future technological investments. In addition, the growth phase in the second generation is also important for the effectiveness of the nuclear energy technology. Conducting effective evaluations in these processes will contribute to increasing the efficiency of companies.

Moisture availability is a strong determinant of decomposition rates in forests worldwide. Climate models suggest that many terrestrial ecosystems are at risk from future droughts, suggesting moisture limiting conditions will develop across a range of forests worldwide. The impacts of increasing drought conditions on forest carbon (C) fluxes due to shifts in organic matter decay rates may be poorly characterised due to limited experimental research. To appraise this question, we conducted a meta-analysis of forest drought experiment studies worldwide, examining spatial limits, knowledge gaps and potential biases. To identify limits to experimental knowledge, we projected the global distribution of forest drought experiments against spatially modelled estimates of (i) future precipitation change, (ii) ecosystem total above-ground C and (iii) soil C storage. Our assessment, involving 115 individual experimental study locations, found a mismatch between the distribution of forest drought experiments and regions with higher levels of future drought risk and C storage, such as Central America, Amazonia, the Atlantic Forest of Brazil, equatorial Africa and Indonesia. Decomposition rate responses in litter and soil were also relatively under-studied, with only 30 experiments specifically examining the potential experimental impacts of drought on C fluxes from soil or litter. We propose new approaches for engaging experimentally with forest drought research, utilising standardised protocols to appraise the impacts of drought on the C cycle, while targeting the most vulnerable and relevant forests.

Abstract This study aims to analyze the innovation strategies for the green supply chain management with QFD (quality function deployment) multidimensionally. The novelty of the study is to define the criteria of green supply chain for each stage of QFD and propose a hybrid model by IVIF (interval-valued intuitionistic fuzzy) DEMATEL (decision making trial and evaluation laboratory) and IVIF MOORA (Multi-Objective Optimization by Ratio Analysis) respectively. The results demonstrate that understanding the customer expectations with customer relation management is the most important innovation strategy for the green supply chain management in energy industry with the consecutive stages of QFD whereas benchmarking the competitive market environment has relatively the last seat in the ranking. Hence, it is recommended that energy companies should have an effective customer relationship management. In this context, these companies should make a detailed analysis to learn what their customers directly expect from them. With the help of this issue, these companies should generate their product and services based on these expectations. Additionally, it is also stated that new service and product development is also essential for energy companies to improve their innovativeness. For this purpose, a research and development department should be created, and the qualified people should be employed. Additionally, different opinions should be collected from various parties, such as customers, employees, and suppliers. Since customers who are satisfied will prefer these companies, the energy companies can catch the opportunity to increase their market share.

Anaerobic nitrogen removal technologies offer advantages in terms of energy and cost savings over conventional nitrification-denitrification systems. A mathematical model was constructed to evaluate the influence of process operation on the coexistence of nitrite dependent anaerobic methane oxidizing bacteria (n-damo) and anaerobic ammonium oxidizing bacteria (anammox) in a single granule. The nitrite and methane affinity constants of n-damo bacteria were measured experimentally. The biomass yield of n-damo bacteria was derived from experimental data and a thermodynamic state analysis. Through simulations, it was found that the possible survival of n-damo besides anammox bacteria was sensitive to the nitrite/ammonium influent ratio. If ammonium was supplied in excess, n-damo bacteria were outcompeted. At low biomass concentration, n-damo bacteria lost the competition against anammox bacteria. When the biomass loading closely matched the biomass concentration needed for full nutrient removal, strong substrate competition occurred resulting in oscillating removal rates. The simulation results further reveal that smaller granules enabled higher simultaneous ammonium and methane removal efficiencies. The implementation of simultaneous anaerobic methane and ammonium removal will decrease greenhouse gas emissions, but an economic analysis showed that adding anaerobic methane removal to a partial nitritation/anammox process may increase the aeration costs with over 20%. Finally, some considerations were given regarding the practical implementation of the process.

AbstractAlthough our observing capabilities of solar‐induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in‐situ SIF observing capability especially in “data desert” regions, improving cross‐instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.

Abstract Urban transformation is vital to global sustainable development as humans increasingly come to dwell in cities. Within cities, the mobility sector promises the highest potential of carbon emission reduction. The disruptive business innovation brought about by the advent of app-based smart-sharing systems is emancipating collaborative consumption of mobility at larger and deeper scales, ranging from car-pooling, expanded electric vehicle (EV) use to bike-sharing. Synchronizing the existing yet under-realized low-carbon transport modes in cities, such as public transport, with emerging and diversifying app-based sharing mobility business models, offers huge potential to transform urban mobility toward sustainability. Yet, the rapid business expansion and innovation of the sharing mobility companies have profoundly challenged existing socio-economic relationships, knowledge systems and physical infrastructures in cities. This study explores the synergy between the social-ecological innovation in the sharing economy and the sustainable development of urban systems, using empirical data from three business cases in the emerging sharing mobility sector – in modes of ride-sharing, EV-sharing and bike-sharing - of Shanghai, China. It indicates that there is a strong co-evolution mechanism between the transformation towards more sustainable city at the macro-level and the business ecosystem innovation towards greener and smarter transport at the meso-level. We argue that the two level transformations, triggered by the disruptive innovation of the sharing economy and led by urban transformation towards sustainability, mutually influence each other and re-enforce sustainable values and practices in the fast changing urban context and business innovations in Shanghai.

Miscanthus (ANDERSSON) is considered a promising perennial industrial crop for providing biomass in a growing bioeconomy. One approach to increasing the biodiversity-enhancing ecosystem services of Miscanthus is the co-cultivation of flower-rich native wild plant species (WPS), for example, the perennial WPS common tansy (Tanacetum vulgare L.) and mugwort (Artemisia vulgaris L.), as well as the biennial WPS wild teasel (Dipsacus fullonum L.) and yellow melilot (Melilotus officinalis L.). This study tested whether these selected WPS would be as suitable for combustion as Miscanthus, in this case the sterile hybrid Miscanthus x giganteus Greef et Deuter, allowing for a mixing of the biomasses. By doing so, no additional value chain (e.g. biogas production) would be necessary to economically exploit the diversification of the agricultural system for bioenergy production. Feedstock samples of Miscanthus and the four above-mentioned WPS from a field trial in southwest Germany were used to investigate the combustion characteristics as well as the higher heating value (HHV). It was found that all WPS exhibited better combustion properties than Miscanthus with respect to ash melting behavior at similar HHVs of 16.3–17.5 MJ kg−1. From an admixture of >30% WPS to the Miscanthus biomass, a significant increase in the ash melting temperature by 20% from 1000 to 1200 °C was shown. Thus, the mixture of WPS and Miscanthus could potentially improve the combustion quality, leading to reduced costs in the incineration plant operation process. However, the reduced costs of incineration should be greater than the loss in productivity due to the lower biomass yields from the WPS. This is highly dependent on the particular site conditions and the establishment success of the WPS and needs to be investigated in long-term studies.

The activity of methanogens and related bacteria which inhabit the coal beds is essential for stimulating new biogenic coal bed methane (CBM) production from the coal matrix. In this study, the microbial community structure and methanogenesis were investigated in Southern Qinshui Basin in China, and the composition and stable isotopic ratios of CBM were also determined. Although geochemical analysis suggested a mainly thermogenic origin for CBM, the microbial community structure and activities strongly implied the presence of methanogens in situ. 454 pyrosequencing analysis combined with methyl coenzyme-M reductase (mcrA) gene clone library analysis revealed that the archaeal communities in the water samples from both coal seams were similar, with the dominance of hydrogenotrophic methanogen Methanobacterium. The activity and potential of these populations to produce methane were confirmed by the observation of methane production in enrichments supplemented with H2 + CO2 and formate, and the only archaea successfully propagated in the tested water samples was from the genus Methanobacterium. 454 pyrosequencing analysis also recovered the diverse bacterial communities in the water samples, which have the potential to play a role in the coal biodegradation fueling methanogens. These results suggest that the biogenic CBM was generated by coal degradation via the hydrogenotrophic methanogens and related bacteria, which also contribute to the huge CBM reserves in Southern Qinshui Basin, China.