A national-scale assessment of land subsidence in China's major cities.

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.

Exploration of the impact of dysbiosis in the gut microbiota on microbial composition in children's neurodevelopment.

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.

Spatiotemporal characteristics of meteorological drought events in 34 major global river basins during 1901-2021.

Meteorological drought is a crucial driver of various types of droughts; thus, identifying the spatiotemporal characteristics of meteorological drought at the basin scale has implications for ecological and water resource security. However, differences in drought characteristics between river basins have not been clearly elucidated. In this study, we identify and compare meteorological drought events in 34 major river basins worldwide using a three-dimensional drought-clustering algorithm based on the standardised precipitation evapotranspiration index on a 12-month scale from 1901 to 2021. Despite synchronous increases in precipitation and potential evapotranspiration (PET), with precipitation increasing by more than three times the PET, 47 % (16/34) of the basins showed a tendency towards drought in over half their basin areas. Drought events occurred frequently, with more than half identified as short-term droughts (lasting less than or equal to three months). Small basins had a larger drought impact area, with major drought events often originating from the basin boundaries and migrating towards the basin centre. Meteorological droughts were driven by changes in sea surface temperature (SST), especially the El Niño Southern Oscillation (ENSO) or other climate indices. Anomalies in SST and atmospheric circulation caused by ENSO events may have led to altered climate patterns in different basins, resulting in drought events. These results provide important insights into the characteristics and mechanisms of meteorological droughts in different river basins worldwide.

The changing nature of groundwater in the global water cycle.

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.

Fertilizer management for global ammonia emission reduction.

Crop production is a large source of atmospheric ammonia (NH3), which poses risks to air quality, human health and ecosystems1-5. However, estimating global NH3 emissions from croplands is subject to uncertainties because of data limitations, thereby limiting the accurate identification of mitigation options and efficacy4,5. Here we develop a machine learning model for generating crop-specific and spatially explicit NH3 emission factors globally (5-arcmin resolution) based on a compiled dataset of field observations. We show that global NH3 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 practices6-9. Furthermore, spatially optimizing fertilizer management, as guided by the machine learning model, has the potential to reduce the NH3 emissions by about 38% (1.6 ± 0.4 Tg N yr-1) without altering total fertilizer nitrogen inputs. Specifically, we estimate potential NH3 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 NH3 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.

A meta-analysis highlights globally widespread potassium limitation in terrestrial ecosystems.

Potassium (K+ ) is the most abundant inorganic cation in plant cells, playing a critical role in various plant functions. However, the impacts of K on natural terrestrial ecosystems have been less studied compared with nitrogen (N) and phosphorus (P). Here, we present a global meta-analysis aimed at quantifying the response of aboveground production to K addition. This analysis is based on 144 field K fertilization experiments. We also investigate the influences of climate, soil properties, ecosystem types, and fertilizer regimes on the responses of aboveground production. We find that: K addition significantly increases aboveground production by 12.3% (95% CI: 7.4-17.5%), suggesting a widespread occurrence of K limitation across terrestrial ecosystems; K limitation is more prominent in regions with humid climates, acidic soils, or weathered soils; the effect size of K addition varies among climate zones/regions, and is influenced by multiple factors; and previous N : K and K : P thresholds utilized to detect K limitation in wetlands cannot be applied to other biomes. Our findings emphasize the role of K in limiting terrestrial productivity, which should be integrated into future terrestrial ecosystems models.

Long-term gridded land evapotranspiration reconstruction using Deep Forest with high generalizability.

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.

High-resolution (1 km) Köppen-Geiger maps for 1901-2099 based on constrained CMIP6 projections.

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 CO2-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 .

Global distribution and climatic controls of natural mountain treelines.

Mountain treelines are thought to be sensitive to climate change. However, how climate impacts mountain treelines is not yet fully understood as treelines may also be affected by other human activities. Here, we focus on "closed-loop" mountain treelines (CLMT) that completely encircle a mountain and are less likely to have been influenced by human land-use change. We detect a total length of ~916,425 km of CLMT across 243 mountain ranges globally and reveal a bimodal latitudinal distribution of treeline elevations with higher treeline elevations occurring at greater distances from the coast. Spatially, we find that temperature is the main climatic driver of treeline elevation in boreal and tropical regions, whereas precipitation drives CLMT position in temperate zones. Temporally, we show that 70% of CLMT have moved upward, with a mean shift rate of 1.2 m/year over the first decade of the 21st century. CLMT are shifting fastest in the tropics (mean of 3.1 m/year), but with greater variability. Our work provides a new mountain treeline database that isolates climate impacts from other anthropogenic pressures, and has important implications for biodiversity, natural resources, and ecosystem adaptation in a changing climate.

Low-carbon energy policies benefit climate change mitigation and air pollutant reduction in megacities: An empirical examination of Shenzhen, China.

The low-carbon transformation of energy system has great significance for megacities to mitigate climate change, which brings co-benefits to improve urban air quality. Taking China's megacity, Shenzhen, as an example, this study examines the potential of wide-ranging energy policies in urban GHG emission reduction and the associated synergistic effect on decreasing major air pollutant emissions. Based on the low emissions analysis platform (LEAP) model, the major results show that an effective implementation of newly emerging energy policies could help cap GHG emissions of Shenzhen in 2025 and nearly halve them by 2035, which would contribute substantially to reducing urban air pollutant emissions. At the sectoral level, the synergistic effect of emission reduction would be the strongest in the transportation sector, followed by the electricity and manufacturing sectors, while it is not significant in the building sector. Moreover, all policies on energy efficiency improvement and demand management that reduce fossil energy consumption show synergistic effects on decreasing air pollutants, while policies on energy structural optimization show differentiated impacts across SO2, NOx, VOCs, and PM2.5. Urban managers should prioritize energy policies with strong synergistic effects and specifically promote the wide application of rooftop PV system and deep electrification of road transportation.

Satellites reveal Earth's seasonally shifting dust emission sources.

Establishing mineral dust impacts on Earth's systems requires numerical models of the dust cycle. Differences between dust optical depth (DOD) measurements and modelling the cycle of dust emission, atmospheric transport, and deposition of dust indicate large model uncertainty due partially to unrealistic model assumptions about dust emission frequency. Calibrating dust cycle models to DOD measurements typically in North Africa, are routinely used to reduce dust model magnitude. This calibration forces modelled dust emissions to match atmospheric DOD but may hide the correct magnitude and frequency of dust emission events at source, compensating biases in other modelled processes of the dust cycle. Therefore, it is essential to improve physically based dust emission modules. Here we use a global collation of satellite observations from previous studies of dust emission point source (DPS) dichotomous frequency data. We show that these DPS data have little-to-no relation with MODIS DOD frequency. We calibrate the albedo-based dust emission model using the frequency distribution of those DPS data. The global dust emission uncertainty constrained by DPS data (±3.8 kg m-2 y-1) provides a benchmark for dust emission model development. Our calibrated model results reveal much less global dust emission (29.1 ± 14.9 Tg y-1) than previous estimates, and show seasonally shifting dust emission predominance within and between hemispheres, as opposed to a persistent North African dust emission primacy widely interpreted from DOD measurements. Earth's largest dust emissions, proceed seasonally from East Asian deserts in boreal spring, to Middle Eastern and North African deserts in boreal summer and then Australian shrublands in boreal autumn-winter. This new analysis of dust emissions, from global sources of varying geochemical properties, have far-reaching implications for current and future dust-climate effects. For more reliable coupled representation of dust-climate projections, our findings suggest the need to re-evaluate dust cycle modelling and benefit from the albedo-based parameterisation.

Anthropogenic activities dominated tropical forest carbon balance in two contrary ways over the Greater Mekong Subregion in the 21st century.

The tropical forest carbon (C) balance threatened by extensive socio-economic development in the Greater Mekong Subregion (GMS) in Asia is a notable data gap and remains contentious. Here we generated a long-term spatially quantified assessment of changes in forests and C stocks from 1999 to 2019 at a spatial resolution of 30 m, based on multiple streams of state-of-the-art high-resolution satellite imagery and in situ observations. Our results show that (i) about 0.54 million square kilometers (21.0% of the region) experienced forest cover transitions with a net increase in forest cover by 4.3% (0.11 million square kilometers, equivalent to 0.31 petagram of C [Pg C] stocks); (ii) forest losses mainly in Cambodia, Thailand, and in the south of Vietnam, were also counteracted by forest gains in China due mainly to afforestation; and (iii) at the national level during the study period an increase in both C stocks and C sequestration (net C gain of 0.087 Pg C) in China from new plantation, offset anthropogenetic emissions (net C loss of 0.074 Pg C) mainly in Cambodia and Thailand from deforestation. Political, social, and economic factors significantly influenced forest cover change and C sequestration in the GMS, positively in China while negatively in other countries, especially in Cambodia and Thailand. These findings have implications on national strategies for climate change mitigation and adaptation in other hotspots of tropical forests.

Large-scale reforestation can increase water yield and reduce drought risk for water-insecure regions in the Asia-Pacific.

Large-scale reforestation can potentially bring both benefits and risks to the water cycle, which needs to be better quantified under future climates to inform reforestation decisions. We identified 477 water-insecure basins worldwide accounting for 44.6% (380.2 Mha) of the global reforestation potential. As many of these basins are in the Asia-Pacific, we used regional coupled land-climate modeling for the period 2041-2070 to reveal that reforestation increases evapotranspiration and precipitation for most water-insecure regions over the Asia-Pacific. This resulted in a statistically significant increase in water yield (p < .05) for the Loess Plateau-North China Plain, Yangtze Plain, Southeast China, and Irrawaddy regions. Precipitation feedback was influenced by the degree of initial moisture limitation affecting soil moisture response and thus evapotranspiration, as well as precipitation advection from other reforested regions and moisture transport away from the local region. Reforestation also reduces the probability of extremely dry months in most of the water-insecure regions. However, some regions experience nonsignificant declines in net water yield due to heightened evapotranspiration outstripping increases in precipitation, or declines in soil moisture and advected precipitation.

Decarbonising the iron and steel sector for a 2 °C target using inherent waste streams.

The decarbonisation of the iron and steel industry, contributing approximately 8% of current global anthropogenic CO2 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% CO2 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 CO2 emission to the 2 °C sectoral target requirements is expected to be reduced before 2050, without any external investments.

Absorption Enhancement of Black Carbon Aerosols Constrained by Mixing-State Heterogeneity.

Atmospheric black carbon (BC) has a large yet highly uncertain contribution to global warming. When mixed with non-BC/coating material during atmospheric aging, the BC light absorption can be enhanced through the lensing effect. Laboratory and modeling studies have consistently found strong BC absorption enhancement, while the results in ambient measurements are conflicting, with some reporting weak absorption enhancement even for particles with large bulk coating amounts. Here, from our direct field observations, we report both large and minor absorption enhancement factors for different BC-containing particle populations with large bulk non-BC-to-BC mass ratios. By gaining insights into the measured coating material distribution across each particle population, we find that the level of absorption enhancement is strongly dependent on the particle-resolved mixing state. Our study shows that the greater mixing-state heterogeneity results in the larger difference between observed and predicted absorption enhancement. We demonstrate that by considering the variability in coating material thickness in the optical model, the previously observed model measurement discrepancy of absorption enhancement can be reconciled. The observations and improved optical models reported here highlight the importance of mixing-state heterogeneity on BC's radiative forcing, which should be better resolved in large-scale models to increase confidence when estimating the aerosol radiation effect.

Effects of design parameters, microbial community and nitrogen removal on the field-scale multi-pond constructed wetlands.

Ecological multi-pond constructed wetlands (CWs) are an alternative wastewater treatment technology for nitrogen removal from non-point source pollution. As an important component of nitrogen cycles in the field-scale CWs, microorganisms are affected by design parameters. Nevertheless, the mechanism of design parameters affecting the distribution of microbial community and removal performance remains largely unexplored. In this study, satisfactory nitrogen removal performance was obtained in three multi-pond CWs. The highest mass removal rate per square meter (1104.0 mg/m2/day) and mass removal rate per cubic meter (590.2 mg/m3/day) for total nitrogen removal were obtained in the XY CW system during the wet season. The changes in seasonal parameters accounted for different removal performances and distributions of the microbial community. The combination of wastewater treatment technologies in the XY CW system consisting of ponds, CWs, and eco-floating treatment wetlands enriched the abundances of nitrogen-related functional genera. Correlation network analysis further demonstrated that longer hydraulic residence time and higher nitrogen concentration could intensify the enrichment of nitrogen-related functional genera. Regulating the combination of wastewater treatment technologies, the nitrogen concentration of influent, hydraulic loading rate, and water depth might promote the accumulation of microbial communities and enhance nitrogen removal. Macroscopical spatial/temporal regulation were proposed to enhance the treatment of non-point source pollution. The clarification of driving mechanism on design parameters, microbial community, and removal performance provided a novel perspective on the long-term maintenance of purification performance, practically sustainable applications, and scientific management of field-scale multi-pond CWs.

Two-Tier Synergic Governance of Greenhouse Gas Emissions and Air Pollution in China's Megacity, Shenzhen: Impact Evaluation and Policy Implication.

Making a cost-effective governance of greenhouse gas (GHG) emissions and air pollution is of great importance for megacities to pursue a sustainable future. To achieve this, the present study advocates megacities to implement a two-tier synergic governance system consisting of both synergic governance between GHG and air pollutant emission reductions and between megacities and their surrounding regions. Based on the LEAP model and WRF-SMOKE-CMAQ simulation platform, this study found that climate governance of China's megacity, Shenzhen, could synergistically contribute to decreasing urban annual PM2.5 concentration by 5.6% in 2030. Using synergic governance with surrounding regions could further help cap and then quickly decrease the megacity's GHG emissions and lower its PM2.5 concentrations by an additional 11.8%. The results demonstrated the substantial effects of transdepartment and transregional synergic governance on Shenzhen's GHG emission reduction and air quality improvement. Furthermore, this study suggested road transportation and power generation and supply as the two priority fields for wide-ranging megacities to promote two-tier synergic governance, highlighting an integration of improved urban electrification with high-efficiency electricity use and a renewable-based power supply.

Impacts of Chemical Degradation on the Global Budget of Atmospheric Levoglucosan and Its Use As a Biomass Burning Tracer.

Levoglucosan has been widely used to quantitatively assess biomass burning's contribution to ambient aerosols, but previous such assessments have not accounted for levoglucosan's degradation in the atmosphere. We develop the first global simulation of atmospheric levoglucosan, explicitly accounting for its chemical degradation, to evaluate the impacts on levoglucosan's use in quantitative aerosol source apportionment. Levoglucosan is emitted into the atmosphere from the burning of plant matter in open fires (1.7 Tg yr-1) and as biofuels (2.1 Tg yr-1). Sinks of atmospheric levoglucosan include aqueous-phase oxidation (2.9 Tg yr-1), heterogeneous oxidation (0.16 Tg yr-1), gas-phase oxidation (1.4 × 10-4 Tg yr-1), and dry and wet deposition (0.27 and 0.43 Tg yr -1). The global atmospheric burden of levoglucosan is 19 Gg with a lifetime of 1.8 days. Observations show a sharp decline in levoglucosan's concentrations and its relative abundance to organic carbon aerosol (OC) and particulate K+ from near-source to remote sites. We show that such features can only be reproduced when levoglucosan's chemical degradation is included in the model. Using model results, we develop statistical parametrizations to account for the atmospheric degradation in levoglucosan measurements, improving their use for quantitative aerosol source apportionment.