Carbon sinks associated with biological carbon pump in karst surface waters: progress, challenges, and prospects.

The biological carbon pump (BCP) associated with aquatic photosynthesis in karst surface waters converts dissolved inorganic carbon (DIC) into organic carbon. In the context of global climate change, BCP could be an important carbon sink mechanism, ultimately regulating atmospheric carbon dioxide (CO) and mitigating climate change. Because of the high DIC and pH, and low dissolved CO [CO (aq)], the hydrochemical characteristics of karst surface water bodies cause C limitation in BCP efficiency.

The effect of digital infrastructure development on household energy consumption expenditure--taking broadband China strategy as an example.

The provision of digital infrastructure and affordable energy for households is an important direction for improving the living conditions of the population. The link between digital infrastructure development and affordable energy should be examined if multiple sustainable development goals are to be achieved simultaneously for the residential sector. This study employs a staggered difference-in-differences model to investigate the effect of digital infrastructure development on household energy consumption expenditure (HECE) by using the Broadband China Strategy as an example.

Machine learning combined with geodetector to predict the spatial distribution of soil heavy metals in mining areas.

An accurate understanding of the spatial distribution of soil heavy metals (HMs) is crucial for the effective prevention of soil pollution and remediation strategies. Traditional machine learning models often overlook the spatially stratified heterogeneity inherent to environmental data, which can impair predictive accuracy. Therefore, we combined the Geodetector model (GDM) with machine learning models.

Experimental study on ultrasonic reduction of irreducible water saturation in low permeability reservoir.

Irreducible water saturation is an important factor affecting the development effect of low permeability reservoir. Using the self-developed ultrasonic generator, kerosene was used as simulated oil, the natural low-permeability siltstone cores with different physical properties in Zhongyuan Oilfield were selected for indoor oil displacement experiment, and the effect of ultrasonic action on the saturation of irreducible water in low-permeability reservoirs was evaluated. It was found that ultrasound can further reduce the saturation of irreducible water on the basis of oil flooding.

Effects of naturally aged microplastics on arsenic and cadmium accumulation in lettuce: Insights into rhizosphere microecology.

Naturally aged microplastics (NAMPs) are commonly found in farmland soils contaminated with heavy metals (HMs), such as arsenic (As) and cadmium (Cd); yet their combined effects on soil-plant ecosystems remain poorly understood. In this study, we investigated the toxic effects of NAMPs and As-Cd on lettuce, considering the influence of earthworm activity, and examined changes in As-Cd bioavailability in the rhizosphere. Four experimental systems were established: soil-only, soil-lettuce, soil-earthworms, and soil-lettuce-earthworms systems, with four NAMPs concentrations (0, 0.

Carbon, hydrogen, nitrogen and chlorine isotope fractionation during 3-chloroaniline transformation in aqueous environments by direct photolysis, TiO photocatalysis and hydrolysis.

This study investigates carbon, hydrogen, nitrogen and chlorine isotope fractionation during the transformation of 3-chloroaniline (3-CA) via direct photolysis, TiO photocatalytic degradation at neutral condition and hydrolysis at pH 3, pH 7 and pH 11. Direct photolysis and ∙OH reaction (UV/HO) showed similar inverse isotope fractionation (ε) for carbon (1.9 ± 0.

Optical and Dielectrical Properties of Opal Water Content Determination Using Terahertz Time-Domain Spectroscopy.

The optical and dielectric properties of opals with different water contents were investigated using terahertz time-domain spectroscopy. The refractive indices and absorption coefficients showed different trends due to the different water contents. The effective medium theory was used to extract the intrinsic dielectric permittivity of opal from opal-polytetrafluoroethylene mixtures.

Deciphering the mineral code of urinary stones: A first look at zinc isotopes.

Zinc (Zn) is an essential element for all living organisms, and Zn isotopes play a key role in studying the formation of disease. Despite extensive studies on Zn isotopes in healthy and diseased human tissues, the role of Zn isotopes in urinary stones remains unexplored. This study investigates Zn isotopes in 37 urinary stones using multi-collector inductively coupled plasma mass spectrometry.

[Construction of Key Technology System for Mine Ecological Restoration Under System Perspective].

Mine ecological restoration has experienced a long-term development process in China, in which various technologies have been constantly developing and integrating. Based on the related theoretical research and field program, the technical system of mine ecological restoration was constructed, and the characteristics of key technologies were specifically grasped. In this research, the environment, including natural elements and the spatial environment, is the object of mine ecological restoration, which requires further long-term investigation and monitoring.

[Quantitative Analysis of the Drivers of the Spatio-temporal Evolution of Vegetation NPP in the Beijing-Tianjin-Hebei Ecological Barrier Area].

The Taihangshan-Yanshan Region is an important ecological barrier area in Beijing-Tianjin-Hebei, and it is of great importance to investigate the spatial distribution pattern and driving mechanism of net primary productivity （NPP） of vegetation for ecological restoration. The MOD17A3HGF.061 NPP dataset was obtained using the Google earth engine（GEE）, and Sen trend, coefficient of variation, partial correlation, complex correlation, and residual analysis were applied to investigate the spatial and temporal patterns of vegetation NPP in the study area and to quantitatively isolate the relative contributions of climate change and human activities.

Leaching behavior and stabilization/solidification characterization of heavy metals from silicomanganese slag.

The utilization of silicomanganese slag (SMS) for the partial substitution of cement holds significant importance in handling environmental risks and achieving the harmless and resourceful utilization of industrial solid wastes. Nevertheless, an in-depth analysis of the leaching behaviors of heavy metals and the solidification/stabilization mechanisms in SMS and cementitious materials is still lacking. In this study, we adopted the toxicity characteristic leaching procedure and horizontal vibration method to simulate the natural leaching environment, thereby exploring the leaching risks related to heavy metals in the aforementioned materials.

Development of a Zynq-Based Seismic Acquisition Station for the Exploration of Antarctic Subglacial Lakes.

The Antarctic region holds significant scientific research value and potential resources. Currently, limited research exists on the use of seismic exploration methods for Antarctic subglacial lakes compared to their use on other continents. Moreover, few reports are available on systems capable of multi-channel seismic data acquisition, remote data quality monitoring, and high-speed real-time data recycling in the extremely low temperatures of Antarctica.

Optimization and analysis of rib working resistance in push-the-bit rotary steerable drilling system.

The rib working resistance of push-the-bit rotary steerable drilling system seriously affects its dynamic performance. For example, the backing pressure problem caused by steps in the well wall during the working process of CNOOC Welleader static push-the-bit rotary steerable drilling tool is discussed in this paper. Based on the structure and working principle of CNOOC Welleader system, a corresponding theoretical model of force analysis is established, and an optimal design method to reduce the backing pressure problem is proposed in combination with numerical simulation and experimental research.

Dynamic analysis of green technology innovation in products and processes under supply chain competition scenarios-A study based on stochastic differential game model.

This paper investigates the dynamics of market competition among manufacturers pursuing two types of green technology innovation: product innovation and process innovation, which provides a novel perspective on how green technological innovations contribute to enhancing product greenness. Using a two-tier supply chain framework, the study examines the differences in cost-sharing across various types of innovation and the impact of game players on product greenness. A stochastic differential game model involving a shared supplier and two competing manufacturers is constructed.

Ensemble learning-assisted quantitative identifying influencing factors of cadmium and arsenic concentration in rice grain based multiplexed data.

Rapid and accurate prediction of rice Cd (rCd) and rice As (rAs) bioaccumulation are important for assessing the safe utilization of rice. Currently, there is lack of comprehensive and systematic exploration of the factors of rCd and rAs. Herein, ensemble learning (EL) was first used to analysis the 23 factors in 8 categories (heavy metal pollution characteristics, soil properties, geographical characteristics, meteorological factors, socio-economic factors, environmental factors, rice type, and nutrient element) in typical regions of China based on the results of 193 research papers from 2000 to 2024 in Web of Science database.

Distribution and controlling factors of dissolved inorganic carbon in urban rivers of a North China megacity: Insights from δC.

Transportation and transformation of the dissolved inorganic carbon (DIC) play a critical role in the regional carbon cycle. To clarify the natural and anthropogenic impacts on DIC, the concentration and isotopic composition of DIC (δC) in two typical urban rivers in northern China (Yongding River, YDR, and Chaobai River, CBR) were measured. Mass-balanced calculations were employed to quantify the impacts of different weathering processes.

Deciphering pollution sources and mechanisms controlling groundwater chemistry in a typical dense agricultural plain on Yungui Plateau.

Groundwater is a critical resource for economic growth and livelihoods in the dense agricultural plains of plateaus. However, contaminations from various sources pose significant threats to groundwater quality. Understanding the sources of groundwater contamination and the mechanisms of hydrochemical control is essential for the sustainable development of agriculturally intensive plains.

Identification of copper and lead pollution elements based on spectra of corn leaves in different leaf layers.

With the development of industrialization, environmental heavy metal pollution has become increasingly serious, and the growth of crops has been seriously affected by heavy metal pollution in the soil environment. Therefore, it is necessary to establish methods for distinguishing and monitoring heavy metal pollution. The application of hyperspectral remote sensing in heavy metal pollution monitoring demonstrates the great potential of using crop leaf spectra to accurately distinguish heavy metal pollution elements.

Synergistic effects of carbon and heat under disturbance of human activities: Evidence from a resource-based city of China.

For resource-based cities, the rapid development of industrialization and urbanization has led to significant carbon emissions (CEs), accelerated the rise of urban land surface temperatures (LSTs) and hindered sustainable urban development. This study constructed a model to measure the carbon-heat relationship to clarify the complex relationship between LSTs and CEs in resource-based cities. The results show that:1) High-temperature areas are primarily concentrated around the urban center and large industrial zones, with average LSTs reaching a peak of 35.

Rainstorms drive the carbon dioxide emissions during the algae-growing season in a large eutrophic lake.

Lakes are sources of atmospheric carbon dioxide (CO), contributing to global climate change. Temporal variations in lake CO emissions are pronounced, with algal growth and precipitation identified as important drivers. Eutrophic lakes often act as atmospheric CO sinks during the growing season.

Characteristics of boron isotopes and their indicative significance in groundwater arsenic mobilization from an alluvial basin.

Groundwater with high arsenic (As) concentration is widely distributed all over the world and seriously threatens human health. Due to the similar chemical properties, boron (B) would be used to understand the formation mechanism of high As groundwater. Thirty groundwater samples were collected from alluvial fan, transition area, and flat plain generally along the flow path in the northwestern Hetao Basin, China.

Hydrochemical characteristics and salinity formation mechanism of different water bodies in the southern Tibet, China.

Understanding the hydrochemical evolution of surface water and groundwater is crucial for protecting regional ecological environments. Currently, there are few quantitative studies on the relative contributions of different processes to salinity enrichment of water bodies. In this study, sixty-seven water samples were collected for chemical, and isotopic analysis, along with simulation calculations.

Correction Strategies for Isotopic Ratios in Overspiked Samples Using the Double Spike Technique.

The double spike (DS) technique is a highly effective approach for measuring the isotope ratios of many elements. However, it is common for some fraction of the prepared samples to be "overspiked." The usual solution for this problem involves repurifying and reanalyzing the samples to ensure data accuracy.

Deep learning for predicting porosity in ultra-deep fractured vuggy reservoirs from the Shunbei oilfield in Tarim Basin, China.

Deep and ultra-deep carbonate reservoirs in China, which account for 34% of the country's oil and gas reserves, pose significant challenges for porosity prediction due to their complex geological features, including extensive burial depth, weak seismic signals, and high heterogeneity. To address these challenges, this study develops an advanced deep learning approach specifically designed for ultra-deep, fault-controlled, fractured-vuggy reservoirs in the Tarim Basin. The study utilizes a three-dimensional seismic dataset and applies Principal Component Analysis (PCA) to select five key features from eight seismic attributes.