• Energy Research
• Open Access close
• 7. Clean energy close
• 13. Climate action close
• 8. Economic growth close
• Hyper Article en Ligne close

Upwelling processes bring nutrient-rich waters from the deep ocean to the surface. Areas of upwelling are often associated with high productivity, offering great economic value in terms of fisheries. The sensitivity of spring/summer-time coastal upwelling systems to climate change has recently received a lot of attention. Several studies have suggested that their intensity may increase in the future while other authors have shown decreasing intensity in their equatorward portions. Yet, recent observations do not show robust evidence of this intensification. The Senegalo-Mauritanian upwelling system (SMUS) located at the southern edge of the north Atlantic system (12°N–20°N) and most active in winter/spring has been largely excluded from these studies. Here, the seasonal cycle of the SMUS and its response to climate change is investigated in the database of the Coupled Models Inter comparison Project Phase 5 (CMIP5). Upwelling magnitude and surface signature are characterized by several sea surface temperature and wind stress indices. We highlight the ability of the climate models to reproduce the system, as well as their biases. The simulations suggest that the intensity of the SMUS winter/spring upwelling will moderately decrease in the future, primarily because of a reduction of the wind forcing linked to a northward shift of Azores anticyclone and a more regional modulation of the low pressures found over Northwest Africa. The implications of such an upwelling reduction on the ecosystems and local communities exploiting them remains very uncertain.

Abstract This work aims to predict the general performances of a pilot parabolic trough collector during transient periods. To do so, a one-dimensional thermal model has been developed. It has been validated with experimental results from two different experimental setups, in steady-state conditions, with a transmitted power maximum error of 3.4%. Since the model only predicts the collector's thermal behavior, the parabolic trough collector has been first optically qualified. Then, optical efficiencies were used as input for the model. Experimental results were obtained in steady-state conditions and compared to the model. Then, experimental and numerical results were compared during two period of time with varying inlet conditions (i.e. dynamic condition tests): the first one with stable conditions, and the other one with harsh conditions. The developed model showed a good capability of predicting the thermal behavior of the parabolic trough collector with unstable environment (DNI, mass flow, inlet temperature), with a 9.6% relative standard error in the worst case. As a conclusion, while previous studies only focused on steady-state conditions, it has been showed that this kind of model can be used to precisely predict the dynamic behavior of large power plants.

Abstract This paper investigates the optimal choice of building energy efficiency (BEE) standard in the context of centralised urban district heating system in northern China. By employing a techno-economic analysis approach, we demonstrate that the current BEE standard implemented in the Chinese cities should be tightened further in order to achieve a socially optimal level. Without considering the externality costs associated with carbon dioxide (CO2) emissions, current BEE standards need to be upgraded to the equivalent level of French RT2005 standard coupled with a properly designed district coal-fired Combined Heat and Power (CHP). In contrast, the equivalent efficiency standard of Swedish building code is preferably to be implemented in the case of explicit carbon emission restriction as long as the marginal cost of carbon emission (carbon price) is sufficiently high. The fuel-switching policy (from coal to natural gas) in the urban district heating system would result in significant increase in overall costs if the BEE upgrade is not taken into account simultaneously. It is also found that BEE improvements in northern Chinese cities are more cost-effective than investing in low-carbon technologies such as wind power or Carbon Capture and storage in the EU and US with regard to CO2 emissions mitigation.

Abstract. An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation–climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Biodiesel can be produced from vegetable oils, animal fats, and waste cooking oils by transesterification with ethanol (also called ethanolysis) in order to substitute fossil fuels. In this work, the batch ethanolysis of high oleic sunflower oil was transferred into a continuous microstructured device, which induces a better control of heat and mass transfers. Various parameters were studied, notably the initial ethanol to oil molar ratio. An innovative method using NIR spectroscopy was also developed to on-line monitor the transesterification reaction of high oleic sunflower oil with ethanol in microreactors (circular PFA tube 1/1600 OD, 0.0200 ID). The reactions were monitored directly in the microreactors through sequential scans of the reaction medium by the means of an adequate probe. The asset of the method is that no sample collection or preparation is necessary. Partial Least Squares regression was used to develop calibration and prediction models between NIR spectral data and analytical data obtained by a reference method (gas chromatography with flame ionization detection, GC–FID). This method is fast, safe, reliable, nondestructive and inexpensive contrary to conventional procedures, such as gas chromatography and high performance liquid chromatography generally used to determine the composition of crude transesterification medium.

Predicting likely species responses to an alteration of their local environment is key to decision‐making in resource management, ecosystem restoration and biodiversity conservation practice in the face of global human‐induced habitat disturbance. This is especially true for forest trees which are a dominant life form on Earth and play a central role in supporting diverse communities and structuring a wide range of ecosystems. In Europe, it is expected that most forest tree species will not be able to migrate North fast enough to follow the estimated temperature isocline shift given current predictions for rapid climate warming. In this context, a topical question for forest genetics research is to quantify the ability for tree species to adapt locally to strongly altered environmental conditions (Kremer et al. ). Identifying environmental factors driving local adaptation is, however, a major challenge for evolutionary biology and ecology in general but is particularly difficult in trees given their large individual and population size and long generation time. Empirical evaluation of local adaptation in trees has traditionally relied on fastidious long‐term common garden experiments (provenance trials) now supplemented by reference genome sequence analysis for a handful of economically valuable species. However, such resources have been lacking for most tree species despite their ecological importance in supporting whole ecosystems. In this issue of Molecular Ecology, De Kort et al. () provide original and convincing empirical evidence of local adaptation to temperature in black alder, Alnus glutinosa L. Gaertn, a surprisingly understudied keystone species supporting riparian ecosystems. Here, De Kort et al. () use an innovative empirical approach complementing state‐of‐the‐art landscape genomics analysis of A. glutinosa populations sampled in natura across a regional climate gradient with phenotypic trait assessment in a common garden experiment (Fig. ). By combining the two methods, De Kort et al. () were able to detect unequivocal association between temperature and phenotypic traits such as leaf size as well as with genetic loci putatively under divergent selection for temperature. The research by De Kort et al. () provides valuable insight into adaptive response to temperature variation for an ecologically important species and demonstrates the usefulness of an integrated approach for empirical evaluation of local adaptation in nonmodel species (Sork et al. ).