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Rising temperatures, increasingly frequent extreme weather events and sea level rise are playing a growing role in shaping displacement, rural-urban migration, circular movements but also voluntary and forced immobilities. The debate on climate mobilities – the interplay between climate change and human mobility – is currently moving centre stage in migration studies. Migration theory, on the other hand, does not necessarily reflect sufficiently on the role of the environment in mobility patterns. Including an understanding of the complex nature of climate mobilities avoids assuming climate change related mobility as new or exceptional per se, and offers understanding of the plural, multi-causal, and political ways in which climate change and human im/mobilities intersect.

The potential of renewable energy should be fully exploited in the transportation sector to achieve a cleaner production. Therefore, this paper proposes an on-grid hybrid hydrogen refueling and battery swapping station powered by wind energy. This novel concept can promote the development of low-carbon emission vehicles including hydrogen-based vehicle and battery electric vehicle. During the daily operation of the station, the multiple uncertainties may lead to a higher operational cost. To address this problem, a hybrid stochastic/distributionally robust optimization method is proposed to handle different uncertainties for the energy management problem. The first type of uncertainties can be depicted by a certain distribution, i.e. electricity price and wind power, which is processed by a stochastic optimization method. The second type of uncertainties is associated with human behaviors and is difficult to find its probability distribution, i.e. the hydrogen demand of hydrogen-based vehicles, so the second type is processed by a distributionally robust optimization method. The overall objective is to minimize the total operational cost of the station, which also considers the battery swapping station overstock punishment. Because a reasonable battery swapping scheduling can reduce the waiting time of users and operational cost of the station. The results indicate that the proposed method can effectively address the conservatism of solutions as its total operational cost is 4.4% lower than that of the hybrid stochastic/robust optimization method under a high confidence level.

The determination of minimum free energy pathways (MFEP) is one of the most widely used strategies to study reactive processes. For chemical reactions in complex environments, the combination of quantum mechanics (QM) with a molecular mechanics (MM) representation is usually necessary in a hybrid QM/MM framework. However, even within the QM/MM approximation, the affordable sampling of the phase space is, in general, quite restricted. To reduce drastically the computational cost of the simulations, several methods such as umbrella sampling require performing a priori a selection of a reaction coordinate. The quality of the computed results, in an affordable computational time, is intimately related to the reaction coordinate election which is, in general, a nontrivial task. In this work, we provide an approach to model reactive processes in complex environments that does not require the a priori selection of a reaction coordinate. The proposed methodology combines QM/MM simulations with an extrapolation of the nudged elastic bands (NEB) method to the free energy surface (FENEB). We present and apply our own FENEB scheme to optimize MFEP in different reactive processes, using QM/MM frameworks at semiempirical and density functional theory levels. Our implementation is based on performing the FENEB optimization by uncoupling the optimization of the band in a perpendicular and tangential direction. In each step, a full optimization with the spring force is performed, which guarantees that the images remain evenly distributed. The robustness of the method and the influence of sampling on the quality of the optimized MFEP and its associated free energy barrier are studied. We show that the FENEB method provides a good estimation of the reaction barrier even with relatively short simulation times, supporting that its combination with QM/MM frameworks provides an adequate tool to study chemical processes in complex environments.

Nanosecond-level transient electromagnetic disturbance (TED), including very fast transient overvoltage caused by operation of disconnectors, high-altitude electromagnetic pulse, and many other fast transients may interfere or even damage the electrical equipment. As one of the main overvoltage protective equipment, the protective performance of metal-oxide surge arresters (MOAs) under nanosecond-level TED should be investigated and then compared with that under microsecond-level TED, especially the lightning impulse. Based on a testing platform containing a 400-kV pulse generator with adjustable rise time from 5 to 100 ns, the behaviors of nonlinearity, fast impulse response, and converting impedances of three types of 10-kV MOAs under TED with different rise time were explored experimentally in this article. The peak residual voltages of 10-kV MOAs under TED with the rise time of 5 ns at 5 kA are 50.2–60.7% higher than those under the lightning impulse. The rise time of TED has significant influence on the peak voltage and impedance converting behaviors of MOAs. A circuit model of 10-kV MOAs under nanosecond-level TED is built and validated by experimental results, which can be applied in insulation coordination and design of protective devices against TED.

AbstractNitrous oxide (N2O) is a potent greenhouse gas and causes stratospheric ozone depletion. While the emissions of N2O from soil are widely recognized, recent research has shown that terrestrial plants may also emit N2O from their leaves under controlled laboratory conditions. However, it is unclear whether foliar N2O emissions are universal across varying plant taxa, what the global significance of foliar N2O emissions is, and how the foliage produces N2O in situ. Here we investigated the abilities of 25 common plant taxa, including trees, shrubs and herbs, to emit N2O under in situ conditions. Using 15N isotopic labeling, we demonstrated that the foliage‐emitted N2O was predominantly derived from nitrate. Moreover, by selectively injecting biocide in conjunction with the isolating and back‐inoculating of endophytes, we demonstrated that the foliar N2O emissions were driven by endophytic bacteria. The seasonal N2O emission rates ranged from 3.2 to 9.2 ng N2O–N g−1 dried foliage h−1. Extrapolating these emission rates to global foliar biomass and plant N uptake, we estimated global foliar N2O emission to be 1.21 and 1.01 Tg N2O–N year−1, respectively. These estimates account for 6%–7% of the current global annual N2O emission of 17 Tg N2O–N year−1, indicating that in situ foliar N2O emission is a universal process for terrestrial plants and contributes significantly to the global N2O inventory. This finding highlights the importance of measuring foliar N2O emissions in future studies to enable the accurate assigning of mechanisms and the development of effective mitigation.

This chapter presents current knowledge, methods, and applications of nutritional energetics in an aquaculture setting. All organisms ingest and metabolize macronutrients that supply dietary energy and the nutrients have different fates. The different aspects of energy flow from feed to fish or shrimp are similar to those known in land animals or birds, but the aquatic mode of life imposes challenges and confers advantages both at the cellular level and at the whole organism level. Energy gain and losses are governed by the efficiency with which the macronutrients are utilized. The application of net energy system as prevailing in monogastric land animal nutrition is also valid for aquatic organisms. The large number of species reared by aquaculture is a real challenge, but many of the basic principles are valid across species. There is a need for precisely quantifying the partition of dietary digestible energy for somatic growth, reproduction, and other physiological changes due to environmental factors.

To mitigate the climate change-induced water shortage and realize the sustainable development of agriculture, drip irrigation, a more efficient water-saving irrigation method, has been intensively implemented in most arid agricultural regions in the world. However, compared to traditional border irrigation, how drip irrigation affects the biophysical conditions in the cropland and how crops physiologically respond to changes in biophysical conditions in terms of water, heat and carbon exchange remain largely unknown. In view of the above situation, to reveal the mechanism of drip irrigation in improving spring wheat water productivity, paired field experiments based on drip irrigation and border irrigation were conducted to extensively monitor water and heat fluxes at a typical spring wheat field (Triticum aestivum L.) in Northwest China during 2017–2020. The results showed that drip irrigation improved yield by 10.3 % and crop water productivity (i.e., yield-to-evapotranspiration-ratio) by 15.6 %, but reduced LAI by 16.9 % in contrast with border irrigation. Under drip irrigation, the lateral development of spring wheat roots was promoted by higher soil temperature combined with frequent dry-wet alternation in the shallow soil layer (0–20 cm), which was the basis for efficient absorption of water and fertilizer, as well as efficient formation of photosynthate. Meanwhile, drip irrigation increased net radiation and decreased latent heat flux by inhibiting leaf growth, thereby increased sensible heat, causing a higher soil temperature (+1.10 ℃) and canopy temperature (+1.11 ℃). Further analysis proved that soil temperature was the key factor affecting yield formation. Based on the above conditions, the decrease in leaf distribution coefficient (−0.030) led to the decrease in evapotranspiration (−5.7 %) and the increase in ear distribution coefficient (+0.029). Therefore, drip irrigation emphasized the role of soil moisture in the soil-plant-atmosphere continuum, enhanced crop activity by increasing field temperature, especially soil temperature, and finally improved yield and water productivity via carbon reallocation. The study revealed the mechanism of drip irrigation for improving spring wheat yield, and would contribute to improving Earth system models in representing agricultural cropland ecosystems with drip irrigation and predicting the subsequent biophysical and biogeochemical feedbacks to climate change.

AbstractClimate change alters surface water availability (WA; precipitation minus evapotranspiration, P − ET) and consequently impacts agricultural production and societal water needs, leading to increasing concerns on the sustainability of water use. Although the direct effects of climate change on WA have long been recognized and assessed, indirect climate effects occurring through adjustments in terrestrial vegetation are more subtle and not yet fully quantified. To address this knowledge gap, here we investigate the interplay between climate‐induced changes in leaf area index (LAI) and ET and quantify its ultimate effect on WA during the period 1982–2016 at the global scale, using an ensemble of data‐driven products and land surface models. We show that ~44% of the global vegetated land has experienced a significant increase in growing season‐averaged LAI and climate change explains 33.5% of this greening signal. Such climate‐induced greening has enhanced ET of 0.051 ± 0.067 mm year−2 (mean ± SD), further amplifying the ongoing increase in ET directly driven by variations in climatic factors over 36.8% of the globe, and thus exacerbating the decline in WA prominently in drylands. These findings highlight the indirect impact of positive feedbacks in the land–climate system on the decline of WA, and call for an in‐depth evaluation of these phenomena in the design of local mitigation and adaptation plans.