Abstract Valley‐basin terrains represent one of Earth's most prominent landforms and host numerous urban settlements. However, these topographically constrained regions frequently experience severe winter aerosol pollution. One critical challenge in elucidating the formation and evolution mechanisms of valley aerosol pollution lies in the precise quantification of its complex vertical difference in aerosol chemistry. To address this, we conducted simultaneous high‐resolution real‐time field measurements at two distinct elevations (urban surface and mountaintop sites with approximately 640 m vertical separation) in Lanzhou, a typical urban valley in northwest China, in January 2021. Significant vertical differences were observed in submicron aerosol (PM1) chemical composition, sources, and temporal variations within this confined terrain. Primary emissions from residential cooking, traffic, and heating activities were major contributors to ground‐level PM1 (averaging 42%), whereas secondary aerosols dominated (76%) at the mountaintop. Most notably, vertical differences in primary aerosol contributions reached ∼40% during persistent cold‐air pool (CAP) episodes characterized by strong temperature inversions and suppressed development of boundary layers. Our study quantitatively reveals the vertical variations in aerosol chemistry, demonstrating that synoptic systems and boundary layer dynamics critically govern air quality in valley cities by regulating vertical mixing. Furthermore, these findings highlight that combining precise CAP weather forecasts with targeted primary emission controls could be a highly effective strategy for mitigating winter aerosol pollution in similar topographically confined regions globally.

ABSTRACT Remotely sensed air temperature data from NASA POWER are widely used in regions with scarce climatic observations, particularly for agricultural applications such as calculating crop water requirements. This study employed a suite of machine learning (ML) algorithms to correct biases in NASA POWER air temperature outputs, including multiple support vector regression (SVR) variants—Linear SVR, Quadratic SVR, Cubic SVR, Fine Gaussian SVR, Medium Gaussian SVR, Coarse Gaussian SVR—and ensemble decision tree models: bagged trees (BGT) and boosted trees (BT). The objective of this study was to assess the ability of different ML algorithms to reduce biases in NASA POWER air temperature data, with the broader goal of identifying the most suitable ML method for air temperature bias correction in Nigeria. For this analysis, we used daily air temperature records from seven meteorological stations across diverse regions of Nigeria. The performance of NASA POWER minimum and maximum air temperature datasets was evaluated using standard error metrics. Subsequent application of ML algorithms significantly improved data accuracy: the normalized root mean square error (NRMSE) of the corrected outputs was mostly below 10%, indicating excellent predictive performance when ML was integrated. Among the SVR variants tested, Fine Gaussian SVR consistently yielded the best prediction results. This finding suggests that Fine Gaussian SVR is a robust tool for enhancing the reliability of air temperature data—critical for improving the accuracy of crop water requirement calculations in regions where in-situ air temperature observations are limited.

Eruca sativa Mill. is an underutilized crop for the production of oil. Evaluating the exact potential of E. sativa oil quantity and quality, and salinity-associated physiological adaptations with low-quality saline water would be helpful for making decisions about its large-scale cultivation on marginal lands. A lysimeter (drum-pot) experiment was conducted under a series of saline water irrigation (ECiw 0.72, 4.02, 7.32, 10.42, and 13.43 dS.m−1) and the physiological data was taken at the seed-filling stage. The results showed that all the growth and yield parameters declined under higher salinity. The linear regression model showed a 50% reduction in weights of shoots, siliquae, and seeds at irrigation salinity (ECiw) of 13 dS.m−1. Seed oil content was only significantly declined at higher salinity of ECiw 13.43 dS.m−1 compared to control. Palmitic and linoleic acids were increased from 4.66 to 6.06% and 9.76 to 13.7%, respectively; and erucic acid declined from 43.7 to 40.35% at higher salinity. Photosynthetic pigments, osmotic potential, K+/Na+ ratio, and CAT activity significantly declined; and RWC, soluble sugars, proline, Na+, K+, malondialdehyde, proteins and APX activity were significantly augmented with increasing salinity. The results demonstrate that E. sativa makes osmotic adjustments for survival under salinity and could be grown on marginal lands for industrial oil production.

Abstract Soil freezing characteristics are predominantly governed by the mechanism of bound water, which essentially constitutes a multicomponent cations distribution within the electrical double‐layer (EDL) on clay particles. The freezing behavior of bound water is determined by two critical factors: (a) the distribution characteristics of cation solutions; (b) the quantitative relationship between cation concentration and freezing point. Although EDL‐based unfrozen water model has been proposed, the freezing characteristics of multicomponent cation solutions remain poorly understood. Our findings indicate that: (a) The synergistic effect of multicomponent cations increases the freezing point depression coefficient of bound water (i.e., the degree of freezing point lowering per unit concentration) by several‐fold compared to NaCl solution; (b) For typical mineral soils with low Na+ content (<15%), a linear freezing point depression equation can accurately characterize the freezing process of multicomponent cation solutions; (c) typical mineral soils exhibit highly similar cation distribution characteristics. By integrating the freezing point depression equation with EDL theory, this study not only improves the EDL‐based unfrozen water model but also develops a parameterized model applicable to typical mineral soils, and elucidating the intrinsic mechanisms of the model's robustness. Validation using measured data from 12 typical soil types demonstrates that this parameterized model can accurately predict unfrozen water content in sands, silts, and clays with low to moderate clay content within the temperature range of −0.263°C to −20°C. The study establishes a theoretical framework distinct from conventional water potential theory, thereby deepening the understanding of freezing characteristics in frozen soils.

Abstract Increasing Arctic rainfall significantly impacts snow and ice processes, land runoff, and the ecological environment. However, the extent to which the rainfall increase is regionally dependent and how it responds to the large retreat of sea ice remains inadequately understood. This study quantifies the Arctic land rainfall increases attributable to sea ice loss under 2°C global warming using multi‐ensemble experiments combining all forcing with sea ice loss forcing. The findings indicate that sea ice retreat is responsible for 16% of the increase in summer Arctic land rainfall, with significant increases covering 46% of the region responses to 2°C warming. The most pronounced responses were observed along the Arctic coasts of Siberia and North America. Local warming caused by sea ice retreat contributes 68% of the rainfall increase, while the remainder results from the increase in total precipitation.

ABSTRACTAngelica sinensis plants suspected of virus infection were collected from Gansu Province, China, and small RNA sequencing was used to identify the causal agent of the symptoms. Alfalfa mosaic virus (AMV) was found to be present, and reverse transcription‐quantitative PCR (RT‐qPCR) was used to confirm that 10% of the symptomatic plants were infected. Fourteen days after AMV inoculation, transcriptomic analyses showed that the anthocyanin, flavone and flavonol biosynthesis pathways were up‐regulated in the leaves of A. sinensis. Proteomic analyses showed that the up‐regulated proteins in leaves inoculated with AMV were mainly concentrated in the phenylpropanoid biosynthesis pathway and the peroxidase structural domain. Fifteen proteins (genes) were jointly up‐regulated, enriched for the molecular function GO term oxidoreductase activity, acting on NAD(P)H and oxidoreductase activity, and the subcellular localisation of the differential genes was mainly concentrated in the cytoplasm and chloroplast. Differentially expressed genes were enriched in pathways such as phytopathogen interaction and phenylpropane biosynthesis in roots 35 days after AMV inoculation compared to healthy controls. F5H, CHIL, CCoAOMT, COMT and CCR genes related to ferulic acid metabolism were significantly down‐regulated in expression, and four MYB transcription factor genes related to the biosynthetic pathway of phenylpropanes were significantly up‐regulated. These results provide insight into the mechanisms of AMV infection and may be helpful for the cultivation of new A. sinensis varieties with high ferulic acid content.

ABSTRACTThe offshore Bengal Basin experienced sedimentation due to the interaction between the Indo‐Asian collision and the amalgamation of Indo‐Burma. To infer the provenance, paleoweathering and tectonic evolution of the Neogene sedimentary rocks from the Sangu Gas Field in the Bay of Bengal, Bangladesh, this study presents a new set of whole‐rock geochemical and detrital zircon U–Pb data. Major and trace element geochemistry indicates that these Neogene sediments originated from an active continental margin (ACM) tectonic environment associated with the recycled orogen, aligning well with the sandstones' quartz‐feldspar‐lithic composition. The geochemical characteristics and elemental ratios of the Neogene sedimentary rocks [e.g., Eu/Eu* (0.55–0.58), (La/Lu)N (9.2–10.0), La/Sc (2.30–3.98) and (La/Yb)N (8.46–10.03)], indicate a primary origin from felsic source rocks. The source rocks are dominantly granites that had undergone mild to moderate chemical weathering. The U–Pb ages of the Pliocene Tipam Group and the Miocene Surma Group range from 22.49 to 2794.45 and 28.04 to 3168.21 Ma, respectively. The sandstones of the Tipam and Surma groups exhibit a notable zircon age peak at around 440–620 Ma, which bears similarities to the Tethyan Himalaya (TH), Upper Lesser Himalaya (ULH) and Indo‐Burman Ranges (IBR). The secondary peaks at ~1500–2000 Ma correspond to the Lesser Himalaya (LH) ages. The additional subordinate peaks at ~700–1200 Ma reflect the age of the Higher Himalaya (HH). The notable increase in the younger detrital zircon (< 200 Ma) populations was observed in the Tipam Group samples (~22%). These additional young zircons were possibly derived from the recycled Paleogene arc of the Indo‐Burma Ranges that might have originated from the Burma magmatic arc.

Soil microbial communities play vital roles in driving ecosystem restoration. However, understanding of the successional dynamics of abundant and rare bacterial subcommunities and their relationships with ecosystem multifunctionality during restoration, particularly in desertified ecosystems, remains limited. Here, we examined the succession of abundant, intermediate, and rare bacterial subcommunities over a 53-year restoration chronosequence following the implementation of straw checkerboard barriers in the Tengger Desert, China. Our findings revealed that the establishment of straw checkerboard barriers significantly increased the richness of abundant, intermediate, and rare taxa over time. However, our results indicated a divergence in ecological processes underpinning the successional dynamics of soil bacterial communities. Stochastic processes and homogeneous selection primarily governed the assembly of abundant and rare subcommunities, respectively, as evidenced by fundamental differences in their niche breadth. More importantly, we further uncovered a dual mechanism underlying the relationships between soil bacterial communities and ecosystem multifunctionality. Abundant taxa were integrally associated with multiple nutrient cycling-related functions simultaneously, likely mediated through coordinated environmental responses or potential interspecies connections, whereas rare taxa were more linked to individual functions independently. These findings deepen our understanding of the successional dynamics of soil microbial communities and the microbe-ecosystem multifunctionality relationships in desert restoration.