Cited by Nonlinear relationship between urban form and transport CO2 emissions: Evidence from Chinese cities based on machine learning

Ecological transitions in Xinjiang, China: Unraveling the impact of climate change on vegetation dynamics (1990–2020) DOI

Haichao Hao,

Junqiang Yao,

Yaning Chen

et al.

Journal of Geographical Sciences, Journal Year: 2024, Volume and Issue: 34(6), P. 1039 - 1064

Published: June 1, 2024

Language: Английский

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Impact and zoning of production-living-ecological spaces changes on carbon balance: Evidence from Shandong province, China DOI

Chao Liu,

Yueqing Xu,

Zhengxin Ji

et al.

Journal of Geographical Sciences, Journal Year: 2025, Volume and Issue: 35(2), P. 293 - 314

Published: Feb. 1, 2025

Language: Английский

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Vegetation Carbon Source/Sink Dynamics and Extreme Climate Response in the Yangtze River Delta Coastal Zone DOI

Yujing Han,

Zhen Han

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1456 - 1456

Published: Feb. 11, 2025

Coastal zones, as transition areas for sea/land interaction, have substantial carbon sequestration potential while also being particularly vulnerable to extreme climate. Consequently, it has become essential evaluate the vegetation sinks in coastal zone under climate conditions. In this study, we evaluated net ecosystem productivity (NEP) typical regions within Yangtze River Delta from 2000 2020. We studied regional and chronological properties of NEP its response The results revealed following: (1) Vegetation demonstrated a fluctuating rising trend over past 21 years, with an interannual change rate 1.96 gC·m−2·a−1, 21-year average was 249.22 gC·m−2·a−1. Spatially, southern part region had higher than northern part, central part. (2) overall area showed characteristics sink, sink accounting 82.41%. Among ecosystems, forest ecosystems exhibited strongest capacity, followed by cropland wetland urban grassland relatively weaker capacities. (3) spatial upward trend, consistent temporal trend. There is high risk degradation future. (4) NEP’s temperature more pronounced. largest explanatory power observed SU25 TMAX during single-factor analysis. interaction analysis found following three factor groups: R99p∩TMAX, SU25∩TNx, TXx∩LST. highlight complex synergistic interplay among these influences on NEP. findings offer scientific basis ecological protection attainment dual-carbon goals Delta.

Language: Английский

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

Yin Zhang, Weibo Ma, Nan Wang

et al.

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

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Decoupling the Impacts of Climate Change and Human Activities on Terrestrial Vegetation Carbon Sink DOI

Shuheng Dong,

Wanxia Ren,

Xiaobin Dong

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(23), P. 4417 - 4417

Published: Nov. 26, 2024

Net ecosystem productivity (NEP) plays a vital role in quantifying the carbon exchange between atmosphere and terrestrial ecosystems. Understanding effects of dominant driving forces their respective contribution rates on NEP can aid effective management sinks, especially rapidly urbanizing coastal areas where climate change (CC) human activities (HA) occur frequently. Combining MODIS NPP products meteorological data from 2000 to 2020, this paper established Modis NPP-Soil heterotrophic respiration (Rh) model estimate magnitude China’s zone (CCZ). Hotspot analysis, variation trend, partial correlation, residual analysis were applied explore spatiotemporal patterns contributions CC HA dynamics NEP. We also explored changes different land use types. It was found that there is clear north–south difference spatial pattern CCZ, with Zhejiang Province serving as main watershed for difference. In addition, most regions showed an improvement Beijing–Tianjin–Hebei region Shandong Province, but pixel values here generally not high southern provinces. According types forces, these primarily results synergistic HA. provinces south are mainly dominated by single-factor-driven degradation. The area contributes increase much larger than CC. From perspective types, forests farmland contributors CCZ.

Language: Английский

Citations

Nonlinear relationship between urban form and transport CO2 emissions: Evidence from Chinese cities based on machine learning DOI

Linna Li, Zilin Deng, Xiaoyan Huang

et al.

Journal of Geographical Sciences, Journal Year: 2024, Volume and Issue: 34(8), P. 1558 - 1588

Published: Aug. 1, 2024

Language: Английский

Citations