The 80 topsoil samples (0-10 cm) are collected from different land use types in built-up areas, northern new town (including chemical concentration area and concentrated residential areas) and suburban agricultural land at Shihezi oasis city in arid zone of Xinxiang, China. The aim of this study is to analysis the magnetic parameters of concentration, composition and particle size of magnetic properties for the urban topsoils, and to describe the spatial distribution under different circumstances of land use. The magnetic grain parameters show that the soils are dominated with coarser multi domain (MD) ferrimagnetic grain. The magnetic mineralogy parameters suggest that samples are dominated by ferrimagnetic minerals corresponding to magnetite-like minerals, but contain a small amount of anti-ferromagnetic material. From the spatial distribution, the concentration of magnetic minerals are ranked in the order of northern new town > built-up areas > suburban agricultural land. Particle size of magnetic minerals are ranked in the order of northern new town > suburban agricultural land > built-up areas. The high concentration of magnetic parameters areas is coincident with factories' area. However, the magnetic concentration in heavy chemical industry region (N1-N7) are low, and particle size of the magnetic particles is larger. XLF, SIRM and SOFT are effective magnetic parameter indexes indicating the light industrial zone of the study area. While, the discrimination in the heavy chemical industry area needs to combine with a magnetic particle parameters (XFD%) .
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Sci Rep
January 2025
School of Business Administration / Research Center for Energy Economics, Henan Polytechnic University, Jiaozuo, Henan, 454003, China.
Understanding the evolution of low-carbon efficiency in urban built-up areas is essential for developing countries striving to meet sustainable development goals. However, the mechanisms driving low-carbon efficiency and the associated development pathways remain underexplored. This study applies the Global Data Envelopment Analysis (DEA) model, the Global Malmquist-Luenberger Index, and econometric models to evaluate low-carbon efficiency and its determinants across China's urban built-up areas from 2010 to 2022.
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View Article and Find Full Text PDFSci Rep
January 2025
Hubei Key Laboratory of Biologic Resources Protection and Utilization, Hubei Minzu University, Enshi, 445000, Hubei Province, China.
As a key food production base, land use changes in the Jianghan Plain (JHP) significantly affect the surface landscape structure and ecological risks, posing challenges to food security. Assessing the ecological risk of the JHP, identifying its drivers, and predicting the risk trends under different scenarios can provide strategic support for ecological risk management and safeguarding food security in the JHP. In this study, the landscape ecological risk (LER) index was constructed by integrating landscape indices from 2000 to 2020, firstly analyzing its spatiotemporal characteristics, subsequently identifying the key influencing factors by using the GeoDetector model, and finally, simulating the risk changes under the four scenarios by using the Markov-PLUS model.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
College of Earth and Environmental Sciences, University of the Punjab, Lahore, 54000, Pakistan.
Rapid urbanization in Lahore has dramatically transformed land use and land cover (LULC), significantly impacting the city's thermal environment and intensifying climate change and sustainable development challenges. This study aims to examine the changes in the urban landscape of Lahore and their impact on the Urban thermal environment between 1990 and 2020. The previous studies conducted on Lahore lack the application of Geospatial artificial intelligence (GeoAI) to quantify land use and land cover, which is successfully covered in this study.
View Article and Find Full Text PDFJ Environ Manage
January 2025
School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China. Electronic address:
Flow cessation leads to severe degradation of river corridor landscape structure, habitat quality, and ecological functions. This study focuses on the representative river with ceased flow in northern China, the Yongding River plain section. Utilizing long-term, high-resolution satellite remote sensing imagery and the InVEST model, we analyzed the spatiotemporal evolution of landscape structure and habitat quality (HQ) before and after river corridor flow cessation over the past 50 years.
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