Regulation of deep carbon degassing by gas-rock-water interactions in a seismic region of Southern Italy.

A comprehensive hydrogeochemical survey of the geothermal waters from the Nappe Zone (Maghrebides fold-and-thrust belt) was undertaken to determine the origins of geothermal waters and to assess the health risks associated with their potentially toxic elements. A total of 11 geothermal water and 3 stream water samples were collected and analysed for major and trace elements (As, B, Ba, Fe, Mn, Pb, Sr, Zn). Two main geothermal water groups were highlighted by hydrogeochemical diagrams and multivariate analyses (PCA, HCA): the first group is the Na−Cl type, TDS &gt; 10 g/L, controlled by deep circulation, while the second group is the Na-Cl−HCO3 type, TDS &lt; 2 g/L, and controlled by shallow circulation. A curved hydrogeochemical evolution path, observed from mixed bicarbonate shallow groundwater to chloride geothermal water, indicates that the interaction with evaporites drives the chemistry of the geothermal samples. On these, the As enrichments come from sulphide oxidation polymetallic mineralisation during the upwelling to the surface from E–W major lineaments. Therefore, E–W lineaments are potential areas for mineral prospecting. The health risk assessment reveals that the concentration of potentially toxic elements in geothermal waters are lower than the guideline values for the protection of freshwater aquatic life and dermal exposure (bathing or balneology). 

Major- and Trace-Element Geochemistry of Geothermal Water from the Nappe Zone, Northern Tunisia: Implications for Mineral Prospecting and Health Risk Assessment

The Qinghai-Tibetan Plateau (TP) is the source of many large Asian rivers and has significant social, ecological and economic importance. However, few hydrogeochemistry and stable isotope studies have been performed in the Maqu catchment of the eastern TP. In this study, the hydrogeochemical composition and stable isotopes (δD and δ18O) of surface water and groundwater samples collected in the Maqu catchment were analysed to characterise the surface water and groundwater, investigate the contributions of different sources, and determine CO2 consumptions. Different techniques were used, including inverse modelling, end member mixing analysis (EMMA), and a forward mass balance model. The results indicated that all water samples are of the HCO3-Ca type. Both the surface water and groundwater are of meteoric origin and there is close contact between them (except wetlands). Water in the wetlands is substantially evaporated (0-45%). Calcite and illite generally precipitate, whereas chlorite and CO2 generally dissolve along groundwater flow paths in the east. The mean contributions of fresh surface waters, mountain-front groundwaters, and anthropogenic inputs to the surface water samples are 56%, 16%, and 28%, respectively. Carbonate and silicate weathering are the dominant sources of major cations. Moreover, high CO2 consumption rates in both the surface runoff and groundwater make the Maqu catchment an important carbon sink in the Yellow River Basin. With many newly-found conclusions on the Maqu catchment, the present study not only provides insight into the catchment but also contributes to a comprehensive understanding of the water cycle and CO2 consumptions on the TP. 

Hydrogeochemical characterization and CO2 consumption in the Maqu catchment of the Qinghai-Tibetan Plateau by multiple hydrogeochemical methods

As the world's largest energy consumer and carbon emitter, the task of carbon emission reduction is imminent. In order to realize the dual-carbon goal at an early date, it is necessary to study the key factors affecting China's carbon emissions and their non-linear relationships. This paper compares the performance of six machine learning algorithms to that of traditional econometric models in predicting carbon emissions in China from 2011 to 2020 using panel data from 254 cities in China. Specifically, it analyzes the comparative importance of domestic economic, external economic, and policy uncertainty factors as well as the nonparametric relationship between these factors and carbon emissions based on the Extra-trees model. Results show that energy consumption (ENC) remains the root cause of increased carbon emissions among domestic economic factors, although government intervention (GOV) and digital finance (DIG) can significantly reduce it. Next, among the external economic and policy uncertainty factors, foreign direct investment (FDI) and economic policy uncertainty (EPU) are important factors influencing carbon emissions, and the partial dependence plots (PDPs) confirm the pollution haven hypothesis and also reveal the role of EPU in reducing carbon emissions. The heterogeneity of factors affecting carbon emissions is also analyzed under different city sizes, and it is found that ENC is a common driving factor in cities of different sizes, but there are some differences. Finally, appropriate policy recommendations are proposed by us to help China move rapidly towards a green and sustainable development path. 

A machine learning algorithm to explore the drivers of carbon emissions in Chinese cities

Screening, classification, capacity estimation and reservoir modelling of potential CO2 geological storage sites in the NW Adriatic Sea, Italy

PurposeThis paper explores international trade of the Chinese manufacturing industries through the lenses of network analysis (NA) to visualise the world trade network of the Chinese economy, describe its topology and better explain the international organisation of Chinese manufacturing industries.Design/methodology/approachThe authors built a dataset of 40,550 Chinese companies and their 107,026 subsidiaries in 118 countries from Orbis-BVD and used a NA to investigate the connection between China and other countries. In particular, the authors studied the connections between Chinese companies and their subsidiaries in order to build a network of Chinese industries.FindingsThe authors found that the network of Chinese companies is ramified but not wide and it can be divided into two clusters. Moreover, the relations between China and other peripheral countries are strongly mediated by a few leading locations (e.g. Hong Kong and the USA).Originality/valueThis paper contributes to the literature in several ways. First, the authors provide empirical evidence on the magnitude and ramifications of Chinese enterprises in the world. The existing studies generally focus on applying NA to sectoral insights (Mao and Yang, 2012; Shaikh et al., 2016; Zheng et al., 2016; Wanzenbö ck, 2018; Krichene et al., 2019), whereas in this work the authors take a comprehensive view of the entire Chinese manufacturing system. Second, this paper complements the existing literature identifying the difference between cluster levels in Chinese manufacturing (Wu and Jiang, 2011) by proposing a cluster centralisation method to analyse the international network of Chinese firms rather than just the national network. Finally, the results also shed light on the international trade relationship between China, Hong Kong and the USA.

/pdf/economic-network-dynamics-a-structural-analysis-of-the-1rkjy2qn.pdf

Economic network dynamics: a structural analysis of the international connectivity of Chinese manufacturing firms

With the aim of deepening our understanding of deep-seated fluids upwelling and mixing in large regional aquifers, we performed a hydrogeochemical study of twenty-two springs in the Contursi area (upper Sele river valley, southern Apennines) by means of the measurements of chemical-physical parameters, major ions, trace elements, and stable and radioactive isotopes. Besides, we realized two updated geo-structural cross-sections in order to reconstruct the groundwater flowpath in the study area. The hydrogeochemical composition, as well as the water temperature allow to identify-three main groups of groundwater: Cold and Low salinity Groundwater (CLGW), Intermediate Salinity Groundwater (ISGW), and Thermal Salinity Groundwater (TSGW). The CLGW group, mostly emerging at the boundary of carbonate aquifers, is characterized by alkaline earth-bicarbonate hydrofacies. Instead, ISGW and TSGW, situated in the inner zone of the valley, show gradually a hydrogeochemical evolution towards sodium-chloride type hydrofacies domain with the highest salinity value. Stable isotope (δ18O-δD) of CLGW reveal the local meteoric origin of groundwater, while isotopic signatures of ISGW and TSGW is associated with the deep fluids inflow. CLGW hydrogeochemistry is clearly related to dissolution of carbonate rocks. On the other hand, for ISGW and TSGW an additional contribution from evaporitic rocks is supported by saturation indices values (gypsum and anhydrite) and validated by isotopic signature of dissolved sulphate (δ34S-δ18O). The application of two models based on tritium data (i.e., the piston-flow and well-mixed reservoir) attributes longer and deeper groundwater flowpaths to TSGW. Through geothermometric calculations (e,g., K-Mg and SiO2-quartz), the equilibrium temperature of deep fluids reservoir is also extrapolated (i.e., 75–96 °C). The results of the adopted hydrogeochemical multi-component approach allowed us to propose an interpretative model of groundwater flowpath for the Contursi area, where deep-seated tectonic discontinuities play a significant role for the upwelling of saline deep thermal fluids in shallow aquifers. 

Hydrogeochemical multi-component approach to assess fluids upwelling and mixing in shallow carbonate-evaporitic aquifers (Contursi area, southern Apennines, Italy)

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Fabrizio Parente

Author Tools

Chat about Author

Papers

Economic network dynamics: a structural analysis of the international connectivity of Chinese manufacturing firms

Hydrogeochemical multi-component approach to assess fluids upwelling and mixing in shallow carbonate-evaporitic aquifers (Contursi area, southern Apennines, Italy)