Multidimensional analysis and enhancement strategies for ecological environment quality at the county level under dual carbon goals: a case study of Shaanxi Province, China

Frontiers in Environmental Science, Journal Year: 2025, Volume and Issue: 13

Published: Jan. 20, 2025

With the intensification of global climate change and environmental degradation, goals carbon peaking neutrality have become crucial strategies for promoting sustainable development in various countries. However, most studies on ecological environment quality (EEQ) focus urban areas, with limited attention to county-level analyses, particularly regarding complex interactions between climate, topography, human activities. This study aims address this gap by investigating spatiotemporal evolution multidimensional driving factors EEQ 107 counties Shaanxi Province, China. Using Google Earth Engine (GEE) platform MODIS imagery, along methods such as Remote Sensing Ecological Index (RSEI), Hurst exponent, GeoDetector, analyzed evolutionary characteristics mechanisms EEQ, explored improvement management different types county within framework dual goals. The results indicate that: 1) From 2000 2020, overall Province showed a fluctuating upward trend, improving from moderate level good level, although some experienced slight degradation 2010 2020. 2) spatial distribution displayed “low-high-low-high” gradient north south, indicating superior conditions southern central-northern counties, while northern regions faced significant challenges. 3) future trend is expected be one continuous improvement, must paid ongoing risks highly urbanized areas. 4) differentiation primarily driven influenced synergistic effects multiple factors. For varying levels it essential comprehensively consider factors, implement tailored sequestration enhancement strategies. not only propose targeted approaches reinforce storage but also offer valuable policy guidance, thereby making contribution achieving at level.

Language: Английский

Detection of driving factors and critical thresholds for carbon sequestration capacity in urban agglomerations using a combined causal inference and machine learning approach

GIScience & Remote Sensing, Journal Year: 2025, Volume and Issue: 62(1)

Published: March 24, 2025

The carbon sequestration capacity in urban agglomeration ecosystems is crucial for enhancing scientific understanding of the cycle and promoting sustainable development to mitigate climate change. However, existing studies on driving factors, particularly regarding determining causal mechanisms critical thresholds remain unclear. To address this knowledge gap, we propose a CMSC framework which integrates inference machine learning methods reveal underlying determine drivers affecting Yangtze River Delta (YRDUA). were heterogeneous between municipal county non-municipal YRDUA. nighttime light, surface solar radiation downwards, air temperature, total precipitation population density that impacted (municipal) counties YRDUA 0.04 (0.4) nW·cm−2·sr−1·yr−1, −6.1 × 104 (−5.46 104) J·m−2·yr−1, 0.013 (0.017) K·yr−1, 3.64 10−5 (2.51 10−5) m·yr−1 −0.04 people·km−2·yr−1, respectively. Furthermore, long-term (from 2021 2100) dataset with county-level scale was generated using inference-based model. In context neutrality, found optimal emission scenario low-carbon SSP3, under average most will exceed 1 107 t. Our study provides constructive basis science-based ecological management China.

Language: Английский

Application potential and spatiotemporal uncertainty assessment of multi-layer soil moisture estimation in different climate zones using multi-source data

Journal of Hydrology, Journal Year: 2024, Volume and Issue: unknown, P. 132229 - 132229

Published: Oct. 1, 2024

Language: Английский