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This study highlights how Chinese economic development detrimentally impacted water quality in recent decades and how this has been improved by enormous investment in environmental remediation funded by the Chinese government. To our knowledge, this study is the first to describe the variability of surface water quality in inland waters in China, the affecting drivers behind the changes, and how the government-financed conservation actions have impacted water quality. Water quality was found to be poorest in the North and the Northeast China Plain where there is greater coverage of developed land (cities + cropland), a higher gross domestic product (GDP), and higher population density. There are significant positive relationships between the concentration of the annual mean chemical oxygen demand (COD) and the percentage of developed land use (cities + cropland), GDP, and population density in the individual watersheds (p < 0.001). During the past decade, following Chinese government-financed investments in environmental restoration and reforestation, the water quality of Chinese inland waters has improved markedly, which is particularly evident from the significant and exponentially decreasing GDP-normalized COD and ammonium (NH4+-N) concentrations. It is evident that the increasing GDP in China over the past decade did not occur at the continued expense of its inland water ecosystems. This offers hope for the future, also for other industrializing countries, that with appropriate environmental investments a high GDP can be reached and maintained, while simultaneously preserving inland aquatic ecosystems, particularly through management of sewage discharge.

AbstractAlthough canopy height has long been a focus of interest in ecology, it has remained difficult to study at large spatial scales. Recently, satellite‐borne LiDAR equipment produced the first systematic high resolution maps of vegetation height worldwide. Here we show that this new resource reveals three marked modes in tropical canopy height ~40, ~12, and ~2 m corresponding to forest, savanna, and treeless landscapes. The distribution of these modes is consistent with the often hypothesized forest‐savanna bistability and suggests that both states can be stable in areas with a mean annual precipitation between ~1,500 and ~2,000 mm. Although the canopy height states correspond largely to the much discussed tree cover states, there are differences, too. For instance, there are places with savanna‐like sparse tree cover that have a forest‐like high canopy, suggesting that rather than true savanna, those are thinned relicts of forest. This illustrates how complementary sets of remotely sensed indicators may provide increasingly sophisticated ways to study ecological phenomena at a global scale.

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.

Although hydrothermal carbonization of biomass components is known to be mainly governed by reaction temperature, consistent reports on the effect and statistical significance of process conditions on hydrochar properties are still lacking. The objective of this research was to determine the importance and significance of reaction temperature, retention time and solid load on the properties of hydrochar produced from an industrial lignocellulosic sludge residue. According to the results, reaction temperature and retention time had a statistically significant effect on hydrochar ash content, solid yield, carbon content, O/C-ratio, energy densification and energy yield as reactor solid load was statistically insignificant for all acquired models within the design range. Although statistically significant, the effect of retention time was 3-7 times lower than that of reaction temperature. Predicted dry ash-free solid yields of attained hydrochar decreased to approximately 40% due to the dissolution of biomass components at higher reaction temperatures, as respective oxygen contents were comparable to subbituminous coal. Significant increases in the carbon contents of hydrochar led to predicted energy densification ratios of 1-1.5 with respective energy yields of 60-100%. Estimated theoretical energy requirements of carbonization were dependent on the literature method used and mainly controlled by reaction temperature and reactor solid load. The attained results enable future prediction of hydrochar properties from this feedstock and help to understand the effect of process conditions on hydrothermal treatment of lignocellulosic biomass.

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.

AbstractExtreme weather events can have strong negative impacts on species survival and community structure when surpassing lethal thresholds. Extreme, short‐lived, winter warming events in the Arctic rapidly melt snow and expose ecosystems to unseasonably warm air (for instance, 2–10 °C for 2–14 days) but upon return to normal winter climate exposes the ecosystem to much colder temperatures due to the loss of insulating snow. Single events have been shown to reduce plant reproduction and increase shoot mortality, but impacts of multiple events are little understood as are the broader impacts on community structure, growth, carbon balance, and nutrient cycling. To address these issues, we simulated week‐long extreme winter warming events – using infrared heating lamps and soil warming cables – for 3 consecutive years in a sub‐Arctic heathland dominated by the dwarf shrubsEmpetrum hermaphroditum, Vaccinium vitis‐idaea(both evergreen) andVaccinium myrtillus(deciduous). During the growing seasons after the second and third winter event, spring bud burst was delayed by up to a week forE. hermaphroditumandV. myrtillus, and berry production reduced by 11–75% and 52–95% forE. hermaphroditumandV. myrtillus, respectively. Greater shoot mortality occurred inE. hermaphroditum(up to 52%),V. vitis‐idaea(51%), andV. myrtillus(80%). Root growth was reduced by more than 25% but soil nutrient availability remained unaffected. Gross primary productivity was reduced by more than 50% in the summer following the third simulation. Overall, the extent of damage was considerable, and critically plant responses were opposite in direction to the increased growth seen in long‐term summer warming simulations and the ‘greening’ seen for some arctic regions. Given the Arctic is warming more in winter than summer, and extreme events are predicted to become more frequent, this generates large uncertainty in our current understanding of arctic ecosystem responses to climate change.