岩石风化碳汇遥感估算及其时空变化分析

张宇; 罗为群; 刘美玲; 李梦琦; 张莉; 陈芳芳; 张扬岑; 陈蕊

doi:10.11932/karst20240401

岩石风化碳汇遥感估算及其时空变化分析

doi: 10.11932/karst20240401

张宇^{1, 3, 4,},
罗为群^{1, 2, ,},
刘美玲⁴,
李梦琦⁴,
张莉³,
陈芳芳⁵,
张扬岑⁶,
陈蕊⁴

1.
中国地质科学院岩溶地质研究所/自然资源部岩溶生态系统与石漠化治理重点实验室，广西桂林 541004
2.
广西平果喀斯特生态系统国家野外科学观测研究站/百色平果喀斯特生态系统广西野外科学观测研究站，广西平果 531406
3.
航天宏图信息技术股份有限公司, 北京 100195
4.
中国地质大学(北京)信息工程学院, 北京 100083
5.
河南省第一地质勘查院有限公司，河南郑州 450001
6.
上海交通大学设计学院, 上海 200240

基金项目: 国家重点研发课题（2022YFF1300702）；中国地质调查局项目（DD20221820）；广西岩溶动力学重大科技创新基地开放课题（KBL202103）

详细信息

作者简介:
张宇（1995－），男，硕士，研究方向：生态遥感。E-mail：zhangyu_yf@piesat.cn

通讯作者:
罗为群（1980－），男，研究员，研究方向：岩溶生态与石漠化治理。E-mail：125639802@qq.com。

中图分类号: X141
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- 被引次数: 0
出版历程
- 收稿日期: 2023-01-19
- 录用日期: 2023-07-21
- 修回日期: 2023-07-20
- 刊出日期: 2024-08-25

Estimation of the carbon sink of rock weathering by remote sensing and analysis of its spatiotemporal variations

ZHANG Yu^{1, 3, 4
,},
LUO Weiqun^{1, 2
, ,},
LIU Meiling⁴,
LI Mengqi⁴,
ZHANG Li³,
CHEN Fangfang⁵,
ZHANG Yangcen⁶,
CHEN Rui⁴

1.
Institute of Karst Geology,CAGS/Key Laboratory of Karst Ecosystem and Treatment of Rocky Desertification, Ministry of Natural Resources, Guilin, Guangxi 541004, China
2.
Pingguo Guangxi, Karst Ecosytem, National Observation and Research Station/Pingguo Baise, Karst Ecosystem, Guangxi Observation and Research Station, Pingguo, Guangxi 531406, China
3.
Piesat Information Technology Co., Ltd., Beijing 100195, China
4.
School of Information Engineering, China University of Geosciences (Beijing), Beijing 10083, China
5.
Henan No.1 Geological Exploration Institute Co., Ltd. Henan 450001, China
6.
School of Design, Shanghai Jiao Tong University, Shanghai 200240, China

摘要

摘要: 岩石风化过程吸收的 CO₂ 是全球碳循环“遗漏汇”中的一部分, 岩石风化碳汇估算对掌握区域与全球碳汇效应及与全球气候变化的关系具有重要意义。文章选取贵州省作为实验区域，以20年作为时间跨度，收集了气象、岩性等数据，首先借助动态时间规整方法选取了岩石风化碳汇的影响因子，然后利用GEM-CO₂模型进行岩溶碳汇量的估算，最后运用Mann-Kendall趋势法和统计法揭示实验区域的2001－2020年岩溶碳汇时空演变规律。结果表明：(1) 影响岩石风化速度、消耗CO₂量的主要因素为岩石类别，其次为年均降水量，温度对于CO₂消耗的响应具有滞后性；(2) 贵州省岩石风化消耗CO₂量较多的地区主要在黔东北、黔西南、黔南以及黔东南部分地区，消耗CO₂较少的地区主要分布在黔西北地区；(3) 20年间，贵州省年均岩溶碳汇量大约在0~1.04×10³t C·km⁻²·a⁻¹之间，呈波动上升的趋势。基于遥感数据的全球或区域尺度碳汇估算为碳源/汇时空变化分析提供了基础数据，为当地碳汇交易、环境政策的制定提供参考。
- 岩溶碳汇 /
- DTW /
- GEM-CO₂模型 /
- Mann-Kendall趋势检验
Abstract: As a type of natural carbon sink, rock weathering plays a critical role in the global carbon cycle by storing atmospheric carbon dioxide (CO₂). This process is particularly significant in mitigating climate change, although its contributions are often underestimated or overlooked in broader carbon calculation practices. The present study focuses on Guizhou Province, China, a region that is characterized by extensive karst landforms. These landforms are of particular interest because they are highly effective in capturing atmospheric CO₂ through rock weathering. This study aims to explore the spatiotemporal dynamics of the carbon sink of rock weathering from 2001 to 2020. This study integrates various data sources, including remote sensing data, meteorological records, and lithological information, to estimate the carbon sink capacity with the GEM-CO₂ model. This study also employs advanced analytical techniques such as Dynamic Time Warping (DTW) and statistical methods to analyze the spatiotemporal evolution of carbon sink. The findings of this study reveal that the rock type is a primary factor influencing the rate of rock weathering and CO₂ consumption, followed closely by annual precipitation. The temperature also plays a significant role, although the responses of its effects are observed to be lagged. This indicates that changes in temperature may affect CO₂ absorption rates several years after the initial temperature fluctuation occurred. This study identifies that the regions with the highest CO₂ consumption through rock weathering are predominantly concentrated in the northeastern, southwestern, southern, and southeastern parts of Guizhou Province. These areas are characterized by widespread formations of carbonate rocks and higher precipitation levels, which can jointly enhance the weathering process and increase carbon sequestration. In contrast, the northwestern regions, which are dominated by silicate rocks and receive lower levels of precipitation, exhibit the lowest levels of CO₂ consumption. This discrepancy underscores the importance of both lithological composition and climatic conditions in determining the effectiveness of natural carbon sink. From 2001 to 2020, the annual average karst carbon sink in Guizhou Province ranged from 0 to 1.04×10³ t C·km⁻²·a⁻¹. Although there was a general trend of fluctuation, the overall pattern showed an increase in carbon sequestration capacity. However, the analysis did not reveal any significant single trend over the two decades. This lack of a clear trend suggests a complex interplay between geological and climatic factors that influence carbon sequestration in karst landforms. The variability in carbon sink capacity observed in this study highlights the sensitivity of natural carbon sink to the changes in environmental conditions, particularly in precipitation and temperature.The spatial distribution of carbon sink closely mirrors the distribution of carbonate rocks in Guizhou Province. This correlation emphasizes the critical role that carbonate rocks play in the global carbon cycle due to their high solubility, which can accelerate the process of CO₂ absorption. Areas with more annual precipitation were found to have a greater capacity for carbon sequestration, and this result reinforces the importance of hydrological factors in the weathering process. This finding is particularly relevant for the regions that are expected to experience changes in precipitation patterns due to climate change, as it suggests that shifts in hydrological conditions could have a significant impact on the efficacy of natural carbon sink.In addition to these findings, this study also highlights the importance of both geological formations and climatic conditions when the carbon sequestration potential of different regions are estimated. The application of the GEM-CO₂ model in this study provides a robust framework for estimating the carbon sink at a regional scale. The effectiveness of this model in this context offers critical data that can be used to guide the development of carbon trading mechanisms and environmental policies aimed at enhancing the natural carbon sink. By integrating geological and climatic data, this model allows a more nuanced understanding of the factors that contribute to the carbon sequestration in karst landforms.The insights gained from this study are invaluable for informing carbon management strategies, particularly in regions with similar geological and climatic conditions. The findings of this study suggest that the carbon sequestration through rock weathering could be a viable component of mitigation efforts for climate change in a wider range. However, the fluctuating nature of carbon sink over the study period indicates that the natural carbon sink is highly sensitive to changes in environmental conditions. This sensitivity underscores the need for adaptive management strategies that can respond to changes in climate and ensure the continued effectiveness of natural carbon sink.Furthermore, this study lays the groundwork for future research to explore the further implications of rock weathering in global carbon cycles. It advocates a more integrated approach that considers both natural and human factors of mitigating climate change. As the climate change continues altering global weather patterns, understanding the role of natural processes like rock weathering in the carbon cycle will be increasingly important for us to develop effective strategies to manage and mitigate the impacts of climate change.
- karst carbon sink /
- GEM-CO₂ model /
- Mann-Kendall trend test /
- DTW

HTML

图 1 贵州省行政区划及岩性分布

Figure 1. Administrative division and lithology distribution of Guizhou Province

下载: 全尺寸图片幻灯片

图 2 基于DTW的年均降水量、气温与总碳汇量的相关性分析

Figure 2. Correlation analysis of annual average precipitation, temperature and total carbon sink based on DTW

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图 3 不同岩石风化作用消耗CO₂百分比

Figure 3. Percentage of CO₂ consumed by weathering of different rocks

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图 4 2001、2010、2020年岩溶碳汇量分布

Figure 4. Distribution of karst carbon sink in 2001, 2010 and 2020

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图 5 2001－2020年贵州省相邻年份岩石风化碳汇量变化

Figure 5. Variations of carbon sink of rock weathering in Guizhou Province from 2001 to 2020

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图 6 2001－2020年贵州省相邻年份气候因子变化

Figure 6. Variations of climate factors in Guizhou Province from 2001 to 2020

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图 7 Mann-Kendall趋势检验 (a)总碳汇量变化趋势 (b) 典型岩溶地貌碳汇量变化趋势(c)非岩溶区碳汇量变化趋势

Figure 7. Trend testing of Mann-Kendall (a) change of total carbon sink; (b) change of carbon sink in typical karst landforms; (c) change of carbon sink in non-karst areas

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图 8 2001－2020年贵州省岩石风化碳汇量的变化趋势 (a) 20年中碳汇增加型发生频率 (b) 20年中碳汇不同变化形式空间分布

Figure 8. ariations of carbon sink of rock weathering in Guizhou Province from 2001 to 2020 (a) frequency of increasing carbon sink in 20 years; (b) spatial distribution of different patterns of carbon sink in 20 years

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图 9 Z-归一化年均降水、温度时序数据

Figure 9. Z-normalized time-sequencing data on annual average precipitation and temperature

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图 10 不同岩石碳汇Z-归一化时序数据

Figure 10. Z-normalized time-sequencing data on carbon sink in different rocks

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图 11 2001－2020各地物类型面积变化

Figure 11. Variations in area of different object types from 2001 to 2020

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图 12 Z-归一化森林面积与碳汇时序数据

Figure 12. Z-normalized forest area and time-sequencing data on carbon sink

下载: 全尺寸图片幻灯片

表 1 GEM-CO₂模型经验系数^[31]

Table 1. Empirical coefficient of the GEM-CO₂ model^[31]

岩石类型	经验系数a
变质岩及深成岩类	0.095
酸性火山岩	0.222
玄武岩	0.479
砂层与砂岩类	0.152
页岩类	0.627
碳酸盐岩类	1.586
蒸发岩类	0.293

下载: 导出CSV

表 2 2001－2010年贵州省岩溶碳汇类型

Table 2. Types of karst carbon sink in Guizhou Province from 2001 to 2010

类型	面积占比/%	描述
波动减少	5.43	20年中相邻年份碳汇量表现为减少形式的次数与面积显著大于增加形式，方差波动较大，碳汇总量减少。
稳定减少	3.90	20年中相邻年份碳汇量表现为减少形式的次数与面积显著大于增加形式，方差波动较小，碳汇总量减少。
波动稳定	33.86	20年中相邻年份碳汇量表现为减少的次数与面积同增加形式持平或相近，方差波动较大，碳汇总量几乎不变。
稳定	19.47	20年中相邻年份碳汇量表现为减少的次数与面积同增加形式持平或相近，方差波动较小，碳汇总量几乎不变。
波动增加	29.01	20年中相邻年份碳汇量表现为减少形式的次数与面积显著小于增加形式，方差波动较大，碳汇总量增加。
稳定增加	8.33	20年中相邻年份碳汇量表现为减少形式的次数与面积显著小于增加形式，方差波动较小，碳汇总量增加。

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表 3 2001－2020年贵州省不同类型岩石碳汇量贡献度

Table 3. Contribution rates of carbon sink of different types of rocks in Guizhou Province from 2001 to 2020

岩石类型	统计面积/km²	碳汇量占比/%
酸性火山岩	1413	0.26
砂岩、页岩、碳酸盐岩	59329	30.46
砂岩、碳酸盐岩	25648	14.59
碳酸盐岩	35566	34.10
砂岩、页岩	2215	0.64
页岩、碳酸盐岩	23654	14.62
深成岩及变质岩	2 010	0.22
砂岩	12095	1.66
砂岩、页岩、碳酸盐岩、玄武岩	5107	2.27
页岩	655	0.27
砂岩、碳酸盐岩、玄武岩	680	0.28
砂岩、页岩、玄武岩	1188	0.42
砂岩、玄武岩	297	0.07
蒸发岩类	/	/

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表 4 2001－2020年不同地物类型面积与碳汇的Pearson相关系数

Table 4. Pearson correlation coefficient between the area of different object types and the carbon sink from 2001 to 2020

土地利用类型	相关系数
森林	0.29
草地	−0.22
耕地	−0.12
建筑	0.19
其它	0.18

下载: 导出CSV

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