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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.

In order to achieve the Paris Agreement goals of keeping the temperature rise well below 2 °C or even 1.5 °C, all countries would need to make fair and ambitious contributions to reducing emissions. A vast majority of countries have adopted reduction targets by 2030 in their Nationally Determined Contributions (NDCs). There are many alternative ways to analyze the fairness of national mitigation contributions. This article uses a model framework based on six equity principles of effort-sharing, to allocate countries’ reduction targets under global emissions scenarios consistent with meeting the Paris climate goals. It further compares these allocations with the NDCs. The analysis shows that most countries need to adopt more ambitious reduction targets by 2030 to meet 2 °C, and even more for 1.5 °C. In the context of 2 °C, the NDCs of the United States of America and the European Union lack ambition with respect to the approaches that emphasize responsibility; China's NDC projection falls short of satisfying any approach in 2030. In the context of 1.5 °C, only India, by implementing its most ambitious efforts by 2030, could be in line with most equity principles. For most countries, the NDCs would use most of their allowed emissions space for the entire 21 st century by 2030, posing a major challenge to transform to a pathway consistent with their fair contributions in the long-term.

Residential energy consumption in China increased dramatically over the period of 2002-2010. In this paper, we undertake a decomposition analysis of changes in energy use by Chinese households for five energy-using activities: space heating/cooling, cooking, lighting and electric appliances. We investigate to what extent changes in energy use are due to changes from appliances and to change in floor space, population and energy mix. Our decomposition analysis is based on the logarithmic mean Divisia index technique using data from the China statistical yearbook and China energy statistical yearbook in the period of 2002-2010. According to our results, the increase in energy-using appliances is the biggest contributor to the increase of residential energy consumption during 2002-2010 but the effect declines over time, due to energy efficiency improvements in those appliances. The second most important contributor is floor space per capita, which increased with 28%. Of the four factors, population is the most stable factor and energy mix is the least important factor. We predicted electricity use, with the help of regression-based predictions for ownership of appliances and the energy efficiency of appliances. We found that electricity use will continue to rise despite a gradual saturation of demand

In cold regions, the occurrence of frozen ground has a fundamental control over the character of the water cycle. To investigate the impact of changing ground temperature conditions on hydrological processes in the context of climate change, a distributed hydrological model with an explicit frozen ground module was applied to an alpine watershed in the upstream area of the Hei'he River in the Qilian Mountains, northwest China. After evaluating the base model, we considered scenarios of frost-free ground and climate change. Results showed that the base model with a frozen ground module successfully captured the water balance and thermal regimes in the basin. When the frozen ground module was turned off, the simulated groundwater recharge and base flow increased by a factor of two to three because surface runoff caused by exceeding infiltration capacities at high elevations, which occurred in the base model, was eliminated. Consequently, the river hydrograph became smoother and flatter, with summer flood peaks delayed and reduced in volume. The annual mean depth where subsurface runoff was generated, was about 2.4m compared to 1.1m in the base model. For a warming climate, a combination of increasing evapotranspiration and reducing permafrost area results in smoother and flatter hydrographs, and a reduction in total river discharge. Although our analysis using numerical models has its limitations, it still provides new quantitative understanding of the influences of frozen ground and climate change on hydrological processes in an alpine watershed.

One-stage autotrophic nitrogen (N) removal, requiring the simultaneous activity of aerobic and anaerobic ammonium oxidizing bacteria (AOB and AnAOB), can be obtained in spatially redox-stratified biofilms. However, previous experience with Membrane-Aerated Biofilm Reactors (MABRs) has revealed a difficulty in reducing the abundance and activity of nitrite oxidizing bacteria (NOB), which drastically lowers process efficiency. Here we show how sequential aeration is an effective strategy to attain autotrophic N removal in MABRs: Two separate MABRs, which displayed limited or no N removal under continuous aeration, could remove more than 5.5 g N/m(2)/day (at loads up to 8 g N/m(2)/day) by controlled variation of sequential aeration regimes. Daily averaged ratios of the surficial loads of O(2) (oxygen) to NH(4)(+) (ammonium) (L(O(2))/L(NH(4))) were close to 1.73 at this optimum. Real-time quantitative PCR based on 16S rRNA gene confirmed that sequential aeration, even at elevated average O(2) loads, stimulated the abundance of AnAOB and AOB and prevented the increase in NOB. Nitrous oxide (N(2)O) emissions were 100-fold lower compared to other anaerobic ammonium oxidation (Anammox)-nitritation systems. Hence, by applying periodic aeration to MABRs, one-stage autotrophic N removal biofilm reactors can be easily obtained, displaying very competitive removal rates, and negligible N(2)O emissions.

Eutrophication of lakes leading to loss of submersed macrophytes and higher turbidity is a worldwide phenomenon, attributed to excessive loading of phosphorus (P). However, recently, the role of nitrogen (N) for macrophyte recession has received increasing attention. Due to the close relationship between N and P loading, disentanglement of the specific effects of these two nutrients is often difficult, and some controversy still exists as to the effects of N. We studied the effects of N on submersed macrophytes represented by Vallisneria natans (Lour.) Hara in pots positioned at three depths (0.4 m, 0.8 m, and 1.2 m to form a gradient of underwater light conditions) in 10 large ponds having moderate concentrations of P (TP 0.03 ± 0.04 mg L(-1)) and five targeted concentrations of total nitrogen (TN) (0.5, 2, 10, 20, and 100 mg L(-1)), there were two ponds for each treatment. To study the potential shading effects of other primary producers, we also measured the biomass of phytoplankton (ChlaPhyt) and periphyton (ChlaPeri) expressed as chlorophyll a. We found that leaf length, leaf mass, and root length of macrophytes declined with increasing concentrations of TN and ammonium, while shoot number and root mass did not. All the measured growth indices of macrophytes declined significantly with ChlaPhyt, while none were significantly related to ChlaPeri. Neither ChlaPhyt nor ChlaPeri were, however, significantly negatively related to the various N concentrations. Our results indicate that shading by phytoplankton unrelated to the variation in N loading and perhaps toxic stress exerted by high nitrogen were responsible for the decline in macrophyte growth.

Multi-layer microgrids cluster (MLMC) has been formed in some certain areas with microgrids (MGs) merging into smart distributed system. It relies on an energy management system (EMS) to manage and schedule the optimal power flow among MGs and public power system in a stable and balanced way. Compared with EMS for single MG, energy management optimization for MLMC is much more complex that the interactions with other MGs require to be considered. In this paper a multi-time-scales EMS is proposed to minimize the total operating cost of MLMC. It consists of two parts: day-ahead static scheduling and real-time dynamic compensation. The day-ahead scheduling is an economic optimization based on the forecasting data within 24 hours. The real-time dynamic compensation is presented to compensate scheduling signal based on the real-time operating information, which is caused by the predictive error. Furthermore, charge-discharge protections of energy storage system (ESS) for each single MG are taken into account. A general-structure MLMG is studied as an example, and this problem is solved by mixed integer linear programming (MILP). The effectiveness of proposed EMS is verified in the MG Research Laboratory in Aalborg University, Denmark. The hardware-in-loop simulation results show the proposed EMS has a good convergence and performance in grid-connected mode.