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• The performance of twelve evapotranspiration products was assessed using dense eddy covariance measurements over different ecosystems. • The remote-sensing ET products and synthesis ET outperformed other categories. • All the products fail to capture the heterogeneity of ET over the forest, cropland, and wetland with small areas but high ET values, leading to the underestimation of basin-averaged ET by 18.9% to 60.7%. Accurate terrestrial evapotranspiration (ET) estimation over complex surfaces with spatial heterogeneity is crucial for local, regional, and global applications. Currently, a variety of global ET products with different spatiotemporal resolutions have been developed and evaluated. However, little is known about their performance in capturing the heterogeneity of ET over complex surfaces. Focusing on the Heihe River Basin (HRB), a typical arid and semi-arid region that is hydrologically vulnerable, this study compared ET from eleven global ET products (six remotely- sensed ET, two land surface model ET, one hydrological model-based ET, one reanalysis ET, and one synthesis ET) and one regional ET dataset against dense eddy covariance observations in terms of the magnitude, seasonal cycle, and spatial pattern. In general, the remotely-sensed ET and synthesis ET outperformed other categories, with the operational Simplified Surface Energy Balance (SSEBop), Penman-Monteith–Leuning (PML), Moderate Resolution Imaging Spectroradiometer (MOD16) and Global LAnd Surface Satellite (GLASS) performing relatively better (root mean square error ranging from 1.22 to 1.57 mm d-1). Across all the land cover types, ET products reproduced a relatively feasible ET over the desert steppe, meadow, and barren, but substantially underestimated ET over ecosystems with high ET values but a low land area fraction over HRB (cropland, wetland, and forest). This highlights the importance of accurately representing the heterogeneity and local climates in the complex land surfaces for ET quantification in regional water resource management. [ABSTRACT FROM AUTHOR]

• High-resolution satellite ET products were assessed using in-situ measurements. • The diurnal and seasonal cycle of ET from remote sensing products was analyzed. • DisALEXI-JPL daily ET has stronger correlations with in-situ ET than PT-JPL ET. • The accuracy of ECOSTRESS ET is more affected by geographic regions than biome types. Remote sensing has become a data source long ago for estimating evapotranspiration (ET), but often with a dilemma between temporal and spatial resolution. The recent ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) reaches a satisfactory compromise. It provides 70 m spatial resolution and an average 4-day revisit cycle at different times of a day, making granular analysis of ET in diurnal changes and field-scale a reality. In this study, we assessed one instantaneous ET and two daily ECOSTRESS ET products (ECO3ETPTJPL & ECO3ETALEXI) at site scale, using 31 AmeriFlux towers in six regions spanning the continental US, during the period from July 2018 to September 2021. Assuming that eddy covariance sites within a region share similar climate features, we evaluated the capacity of ECOTSRESS to quantify the ET over heterogeneous landscapes. Generally, DisALEXI-JPL daily ET (R2 = 0.45) have stronger correlations with in-situ ET than both PT-JPL instantaneous ET (R2 = 0.23) and daily ET (R2 = 0.11), while they all tend to overestimate ET in most regions. The diurnal cycles of PT-JPL instantaneous ET and seasonal cycles of two daily ET were visualized site by site; all can show temporal variations of ET. Comparing ECOSTRESS ET across and within the six regions, we found that ECOSTRESS ET accuracy varies by region, regardless of their biomes. Understanding the mechanisms controlling ET and how different data sets are able to capture ET is essential for assessing how land cover changes and human-induced disturbances influence plant water use and stress. In this regard, our study provides a deep evaluation of ECOSTRESS ET, paving the ground for future studies aiming to describe ET across heterogeneous landscapes at a finer scale. [ABSTRACT FROM AUTHOR]

• Irrigation substantially alters the water, carbon, and nitrogen budgets in the cropland area. • Evapotranspiration as well as surface runoff and baseflow is sharply increased after irrigation. • Water use efficiency of each crop species is significantly enhanced because of irrigation. • The cropland area of the Heihe River Basin switches from being a carbon source to a carbon sink as a result of irrigation. Irrigation can substantially alter the hydrologic and biogeochemical cycles in river basins. However, little attention has been given to the quantitative evaluation of the effects of irrigation on both of these cycles. In this study, we utilized the latest version of the Community Land Model (CLM5) to assess the effects of irrigation on the water, carbon, and nitrogen budgets in a cropland area of a large endorheic river basin (Heihe River Basin, HRB) in northwestern China and further identified the contributions of each type of crop to the abovementioned budgets. The model has been validated against local flux towers, remote sensing products, and reanalysis datasets, demonstrating the capability of CLM5 in capturing the temporal and spatial characteristics of water, carbon, and nitrogen at the basin scale. Two numerical experiments, one with irrigation and one without it, were conducted to explore the relationships between water and carbon/nitrogen budgets for the period from 2000 to 2018. The simulation results showed that the greatest amount of irrigation was applied in the summer (>50 mm month−1) and then declined to a low level during the other seasons. Evapotranspiration (ET) in the cropland area sharply increased from 106 mm year−1 to 508 mm year−1, with an increase in surface runoff and baseflow after irrigation. Both irrigated gross primary production (GPP), net ecosystem exchange (NEE) and water use efficiency (WUE) peaked in the summer, which corresponded to the crop growing season. A shift in NEE from 6 gC m−2 year−1 to –229 gC m−2 year−1 indicated that the cropland area in the HRB switched from being a carbon source to a carbon sink because of irrigation. The corn area presented the largest increase/decrease in GPP/NEE after irrigation, whereas the lowest increase/decrease in GPP/NEE was observed in the cotton area. Total ecosystem carbon (TEC) and total ecosystem nitrogen (TEN) markedly increased as a result of irrigation, with increases of 3.29 × 1013 gC and 2.96 × 1012 gN, respectively, throughout the year in the cropland area. Overall, our study demonstrates that irrigation has substantial impacts on water, carbon, and nitrogen budgets in the cropland area of the HRB and provides important insights into the application of CLM5 in an arid basin with multiple crop types. [ABSTRACT FROM AUTHOR]

• Distinct seasonal and geographical variations of E pan trends are observed in China. • Declining wind speed plays a dominant role in the decreasing of E pan before 1989. • Decreasing relative humidity predominates the reversal of E pan trend after 1989. • Flash drought would likely occur over the subtropical monsoon zone. Pan evaporation (E pan) reflects the evaporation potential of surface water and is a key indicator of atmospheric evaporative demand. Previous studies have found a substantial decrease in E pan across China, dominated by declining wind speed and solar radiation before the late 2000 s. However, how E pan responds to the recovery of wind speed and solar radiation since the late 2000 s remains unclear. Here, we investigate the spatial and temporal patterns of E pan and analyze its controlling factors, based on the daily meteorological observations during 1965–2018 at 2,018 stations over China. We find that the annual E pan in the northwest and south of China is higher than that in the northeast and central parts of China. The national mean E pan decreases significantly during 1965–1989 at a rate of −6.57 mm yr−2, then reverses at a rate of 4.58 mm yr−2. Distinct seasonal discrepancies and geographical heterogeneities in E pan trends are observed. Declining wind speed mainly contributes to the decrease in E pan before 1989, while relative humidity is shown as the dominant factor that drives the growth of E pan after the turning point. The recovery of wind speed still has significant impact on E pan variation in parts of China, while E pan is only mainly affected by solar radiation in parts of central China in autumn. Our findings highlight the importance of understanding E pan variations and driving factors, and call for precautions and adaptation actions to combat and prevent flash droughts over China, especially in the south of China. [ABSTRACT FROM AUTHOR]

Competing Interests: The authors declare no competing interests.

Objective: To investigate the impact of gut microbiota dysbiosis on neurodevelopment in children., Methods: This study included 338 children aged 0-3 years admitted to our hospital from January to December 2022, The children were divided into a normal neurodevelopment group (169 cases) and a poor neurodevelopment group (169 cases). Basic personal information and clinical data were collected through a detailed questionnaire, and the microbial composition in fecal samples was analyzed using 16S rRNA gene sequencing., Results: Children in the poor neurodevelopment group showed a significant decrease in gut microbiota diversity compared to those in the normal neurodevelopment group (Shannon index, p  < 0.05). The abundance of Bifidobacterium and Veillonella genera significantly decreased ( p  < 0.05), while the abundance of Streptococcus genus increased significantly ( p  < 0.05)., Conclusion: There is an association between gut microbiota dysbiosis and poor neurodevelopment in children. The increased abundance of Streptococcus genus and decreased abundance of Bifidobacterium and Veillonella genera in the gut microbiota may be potential risk factors for poor neurodevelopment in preterm infants. Future research should further explore the potential beneficial effects of gut microbiota modulation on neurodevelopment in children.

China's massive wave of urbanization may be threatened by land subsidence. Using a spaceborne synthetic aperture radar interferometry technique, we provided a systematic assessment of land subsidence in all of China's major cities from 2015 to 2022. Of the examined urban lands, 45% are subsiding faster than 3 millimeters per year, and 16% are subsiding faster than 10 millimeters per year, affecting 29 and 7% of the urban population, respectively. The subsidence appears to be associated with a range of factors such as groundwater withdrawal and the weight of buildings. By 2120, 22 to 26% of China's coastal lands will have a relative elevation lower than sea level, hosting 9 to 11% of the coastal population, because of the combined effect of city subsidence and sea-level rise. Our results underscore the necessity of enhancing protective measures to mitigate potential damages from subsidence.

In recent decades, climate change and other anthropogenic activities have substantially affected groundwater systems worldwide. These impacts include changes in groundwater recharge, discharge, flow, storage, and distribution. Climate-induced shifts are evident in altered recharge rates, greater groundwater contribution to streamflow in glacierized catchments, and enhanced groundwater flow in permafrost areas. Direct anthropogenic changes include groundwater withdrawal and injection, regional flow regime modification, water table and storage alterations, and redistribution of embedded groundwater in foods globally. Notably, groundwater extraction contributes to sea level rise, increasing the risk of groundwater inundation in coastal areas. The role of groundwater in the global water cycle is becoming more dynamic and complex. Quantifying these changes is essential to ensure sustainable supply of fresh groundwater resources for people and ecosystems.

Crop production is a large source of atmospheric ammonia (NH 3 ), which poses risks to air quality, human health and ecosystems 1-5 . However, estimating global NH 3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy 4,5 . Here we develop a machine learning model for generating crop-specific and spatially explicit NH 3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH 3 emissions from rice, wheat and maize fields in 2018 were 4.3 ± 1.0 Tg N yr -1 , lower than previous estimates that did not fully consider fertilizer management practices 6-9 . Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH 3 emissions by about 38% (1.6 ± 0.4 Tg N yr -1 ) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH 3 emissions reductions of 47% (44-56%) for rice, 27% (24-28%) for maize and 26% (20-28%) for wheat cultivation, respectively. Under future climate change scenarios, we estimate that NH 3 emissions could increase by 4.0 ± 2.7% under SSP1-2.6 and 5.5 ± 5.7% under SSP5-8.5 by 2030-2060. However, targeted fertilizer management has the potential to mitigate these increases., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Previous datasets have limitations in generalizing evapotranspiration (ET) across various land cover types due to the scarcity and spatial heterogeneity of observations, along with the incomplete understanding of underlying physical mechanisms as a deeper contributing factor. To fill in these gaps, here we developed a global Highly Generalized Land (HG-Land) ET dataset at 0.5° spatial resolution with monthly values covering the satellite era (1982-2018). Our approach leverages the power of a Deep Forest machine-learning algorithm, which ensures good generalizability and mitigates overfitting by minimizing hyper-parameterization. Model explanations are further provided to enhance model transparency and gain new insights into the ET process. Validation conducted at both the site and basin scales attests to the dataset's satisfactory accuracy, with a pronounced emphasis on the Northern Hemisphere. Furthermore, we find that the primary driver of ET predictions varies across different climatic regions. Overall, the HG-Land ET, underpinned by the interpretability of the machine-learning model, emerges as a validated and generalized resource catering to scientific research and various applications., (© 2023. The Author(s).)

We introduce Version 2 of our widely used 1-km Köppen-Geiger climate classification maps for historical and future climate conditions. The historical maps (encompassing 1901-1930, 1931-1960, 1961-1990, and 1991-2020) are based on high-resolution, observation-based climatologies, while the future maps (encompassing 2041-2070 and 2071-2099) are based on downscaled and bias-corrected climate projections for seven shared socio-economic pathways (SSPs). We evaluated 67 climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and kept a subset of 42 with the most plausible CO 2 -induced warming rates. We estimate that from 1901-1930 to 1991-2020, approximately 5% of the global land surface (excluding Antarctica) transitioned to a different major Köppen-Geiger class. Furthermore, we project that from 1991-2020 to 2071-2099, 5% of the land surface will transition to a different major class under the low-emissions SSP1-2.6 scenario, 8% under the middle-of-the-road SSP2-4.5 scenario, and 13% under the high-emissions SSP5-8.5 scenario. The Köppen-Geiger maps, along with associated confidence estimates, underlying monthly air temperature and precipitation data, and sensitivity metrics for the CMIP6 models, can be accessed at www.gloh2o.org/koppen ., (© 2023. Springer Nature Limited.)

The decarbonisation of the iron and steel industry, contributing approximately 8% of current global anthropogenic CO 2 emissions, is challenged by the persistently growing global steel demand and limitations of techno-economically feasible options for low-carbon steelmaking. Here we explore the inherent potential of recovering energy and re-using materials from waste streams, high-temperature slag, and re-investing the revenues for carbon capture and storage. In a pathway based on energy recovery and resource recycling of glassy blast furnace slag and crystalline steel slag, we show that a reduction of 28.5 ± 5.7% CO 2 emissions to the sectoral 2 °C target requirements in the iron and steel industry could be realized in 2050 under strong decarbonization policy consistent with low warming targets. The technological schemes applied to engineer this high-potential pathway could generate a revenue of US$35 ± 16 and US$40 ± 18 billion globally in 2035 and 2050, respectively. If this revenue is used for carbon capture and storage implementation, equivalent CO 2 emission to the 2 °C sectoral target requirements is expected to be reduced before 2050, without any external investments., (© 2022. The Author(s).)