Estimation of karst carbon sink fluxes from rock weathering and analysis of their spatiotemporal dynamics in Yunnan Province
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摘要: 岩溶地区特有的岩石风化碳汇，被认为是全球碳失汇的重要方面，进行岩石风化碳汇估算和时空演变特征分析，有助于岩溶地区碳评估与政策制定。文章基于云南省可溶性岩石类型划分，利用GEM-CO2模型估算2001—2020年云南省岩石风化碳汇通量，进而分析岩石风化碳汇时空演变格局及趋势，估测云南省岩石风化碳汇未来变化趋势。结果表明：（1）2001—2020年，云南省年均消耗CO2通量187.79×103 mol·km−2·a−1，消耗CO2总质量
63116.4 ×103 t，C总质量17377.4 ×103 t；不同岩石年均消耗CO-2通量由大到小依次为：碳酸盐岩（582.91×103 mol·km−2·a−1）>页岩（207.22×103 mol·km−2·a−1）>酸性火山岩（87.55×103 mol·km−2·a−1）>砂岩（56.29×103 mol·km−2·a−1）>变质岩和深成岩（51.2×103 mol·km−2·a−1）。（2）空间格局上，岩石风化碳汇通量呈现为“四周高，中部低”，其中，滇东地区自北向南逐渐增加，滇西靠近边境区域较高，滇中、滇北地区岩石风化碳汇通量较低；全省岩石风化碳汇通量变异系数在0~0.64之间，其中，强变异区域占全省比例为14.75%；变异性呈现为“四周低，中部高”，由滇中向四周逐渐降低。（3）Hurst指数为0.30~0.63，2001—2020年岩石风化碳汇的反向持续发展趋势略高于正向持续发展趋势，预测未来云南省滇东及滇西北地区岩石风化碳汇通量将呈现增加趋势，约占云南省总面积的39.86%，滇东北和滇东部分地区将持续减少，约占34.86%。Abstract:Research on the global transfer of "carbon sources" and "carbon sinks" has revealed the potential existence of previously unidentified carbon sinks within the continental biosphere. Among these, the dynamic chemical process of rock weathering constitute a major carbon sink capable of sequestering atmospheric CO2. The carbon sink from rock weathering constitutes an integral component of this "missing carbon sink". Notebly, the distinctive biogeochemical process of rock, particularly in karst landscapes, has been increasingly recognized as a critical and persistent carbon sink. Carbonate minerals dissolve through carbonic acid formed from atmospheric or soil-derived CO2 and water, generating bicarbonate ions that are transported via river systems to the oceans, thereby sequestering carbon over geological timescales. Therefore, accurately estimating the magnitude of the carbon sink from rock weathering and understanding its spatiotemporal dynamics are essential for regional carbon assessments, climate change mitigation strategies, and policy formulation in karst-dominated regions. Yunnan Province, situated in Southwest China, is one of the country's primary karst development areas, characterized by diverse soluble and silicate rock types, making it an ideal natural laboratory for such investigations. This study aims to quantify carbon sink fluxes from rock weathering in Yunnan Province from 2001 to 2020, analyze its spatiotemporal evolution characteristics, and project future trends under ongoing environmental changes. Based on a detailed classification of soluble and insoluble rocks within Yunnan Province, this study employed the well-established Global Erosion Model for CO2 consumption (GEM-CO2) model.This model estimates the CO2 consumption flux ($ {{F}}_{{{\text{CO}}_{2}}} $) resulting from the chemical weathering of different rock types by integrating surface runoff data with specific lithological coefficients ($ a $) that represent the weathering potential of each rock. The fundamental equation is ($ {{F}}_{{{\text{CO}}_{2}}}=Q\cdot a $), where ($ Q $) is the annual surface runoff. Runoff ($ Q $) was calculated using the Turc method, which estimates actual evaporation ($ E $) based on annual precipitation ($ P $) and temperature ($ T $) data, with ($ Q $) derived as ( $ P $-$ E $). High-resolution spatial data, including a 1∶500,000 geological map (resampled to a 1-km grid) and long-term meteorological datasets (precipitation and temperature) from 2001 to 2020, were utilized as primary inputs. Following flux estimation, a suite of robust statistical and geospatial methods was applied. The Theil-Sen Median trend analysis and Mann-Kendall significance test were used to detect monotonic trends in the carbon sink fluxes over the two-decade period. The coefficient of variation (CV) was calculated to assess the stability and variability of fluxes. Finally, to predict the future persistence or reversal of these trends, the Hurst exponent, derived from Rescaled Range (R/S) analysis, was calculated and combined with Sen's slope to generate a map of future trend predictions. The key findings of this study are multifaceted, (1) From 2001 to 2020, the estimated annual average CO2 consumption flux attributable to rock weathering in Yunnan Province was 187.79 × 103 mol·km−2·a−1. This corresponds to a total CO2 consumption mass of approximately 63.12×106 t and a total carbon mass of 17.38×106 t over the two decades. Significant disparities were observed among different types of lithology in their contribution to the carbon sink. Carbonate rocks exhibited the highest average annual CO2 consumption flux at 582.91×103 mol·km−2·a−1, accounting for 53.95% of the total CO2 consumed, thus establishing them as the predominant rock type driving the weathering carbon sink in the province. This was followed by shale (207.22×103 mol·km−2·a−1), acid volcanic rocks (87.55×103 mol·km−2·a−1), sandstone (56.29×103 mol·km−2·a−1), and metamorphic and plutonic rocks (51.2×103 mol·km−2·a−1). (2) The spatial distribution of the rock weathering carbon sink flux demonstrated a distinct pattern characterized as "high in the surrounding areas and low in the central region". High-flux zones were primarily concentrated in eastern Yunnan, with values gradually increasing from north to south, and in the border regions of western Yunnan. In contrast, low-flux zones were predominantly located in central and northern Yunnan. The coefficient of variation (CV) for the flux across the province ranged from 0 to 0.64, indicating varying degrees of temporal stability. Areas of high variability (CV ≥ 0.35) constituted 14.75% of the province's area and were mainly situated in central Yunnan (around Kunming, Chuxiong, and Dali), forming a pattern of "high variability in the center and low variability in the surrounding areas". This pattern suggests that the carbon sink in central Yunnan is more sensitive to interannual environmental fluctuations, potentially influenced by intensive human activities and specific lithological compositions (sandstone and shale). (3) Temporal trend analysis revealed a slight overall declining trend in total CO2 consumption mass from 2001 to 2020, with a linear slope of - 0.0055 , although significant interannual fluctuations were observed. Theil-Sen analysis indicated that areas exhibiting a decreasing trend (approximately 76.93% of the province's area with significant change) were more extensive than those showing an increasing trend (22.98%), with the most pronounced decreases occurring in northwestern and central Yunnan and increases concentrated in northeastern Yunnan (e.g., Zhaotong). The Hurst exponent for the carbon sink flux across the province ranged from 0.30 to 0.63, indicating a complex mix of future behaviors. Approximately 57.18% of the area exhibited a Hurst index less than 0.5, suggesting an anti-persistent trend (future reversal of the past trend), while 42.82% displayed an index greater than 0.5, indicating a persistent trend. By integrating Sen's slope and the Hurst index, future predictions were derived. It is projected that areas with an increasing trend in the carbon sink flux from rock weathering will cover approximately 39.86% of the province, mainly concentrated in eastern and northwestern Yunnan. Conversely, areas predicted to experience a continuous decrease will account for approximately 34.86% of the province, predominantly distributed in central, northeastern, and parts of eastern Yunnan.This study provides a comprehensive quantitative assessment of the carbon sink from rock weathering in Yunnan Province over the past two decades. The results highlight the dominant role of carbonate rocks and reveal significant spatial heterogeneity and temporal variability in this carbon sink, primarily driven by the interplay of lithology, climate (precipitation and temperature), and potentially human activities. The predictive analysis offers valuable insight, suggesting a slight net increase in future sink areas despite recent declining trends. These findings provide crucial scientific evidences for understanding the regional carbon budget, validate the efficacy of the GEM-CO2 model for large-scale assessments, and support the formulation of targeted ecological restoration and carbon management policies in Yunnan Province and similar karst regions worldwide. -
图 1 云南省地表基岩分布图
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 1. Distribution map of surface bedrock in Yunnan Province
图 2 云南省2001—2020年不同岩性岩石风化碳汇消耗CO2质量占比图
Figure 2. Proportion of CO2 mass consumed by carbon sinks from rock weathering of different types of lithology in Yunnan Province from 2001 to 2020
图 3 云南省2001—2020年不同岩性岩石风化碳汇消耗CO2通量及总年均分布图
注：a为碳酸盐岩；b为页岩；c为变质岩和深成岩；d为砂岩；e为酸性火山岩；f为年均总消耗CO2通量。本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 3. Annual average distribution of CO2 fluxes consumed by karst carbon sinks from rock weathering of different types of lithology in Yunnan Province from 2001 to 2020
Note: a. carbonate rock; b. shale; c. metamorphic rock and plutonic rock; d. sandstone; e. acid volcanic rock; f. the annual average total CO2 consumption flux.
图 4 岩石风化碳汇通量变化趋势
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 4. Trends in karst carbon sink fluxes from rock weathering
图 5 岩石风化碳汇通量变化趋势显著性
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 5. Significance of trends in karst carbon sink fluxes from rock weathering
图 6 云南省2001—2020年岩石风化碳汇作用消耗CO2质量趋势
Figure 6. Trends in CO2 mass consumed by karst carbon sinks from rock weathering in Yunnan Province from 2001 to 2020
图 7 2001—2020年云南省岩石风化碳汇通量变异系数
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 7. Coefficient of variation in karst carbon sink fluxes from rock weathering in Yunnan Province from 2001 to 2020
图 8 岩石风化碳汇通量Hurst指数
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 8. Hurst indices of karst carbon sink fluxes from rock weathering
图 9 云南省岩石风化碳汇通量未来趋势
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 9. Future trends of karst carbon sink fluxes from rock weathering in Yunnan Province
图 10 云南省2001—2020年年均温度
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 10. Annual average temperature in Yunnan Province from 2001 to 2020
图 11 云南省2001—2020年年均降水量
注：本图基于自然资源部标准地图服务网站GS(2019)3333号标准地图制作，底图无修改。
Figure 11. Annual average precipitation in Yunnan Province from 2001 to 2020
表 1 岩石类型及岩石系数
Table 1. Rock types and rock coefficients
岩石类型 岩石系数（$ a $） 变质岩和深成岩 0.095 酸性火山岩 0.222 砂岩 0.152 碳酸盐岩 1.586 页岩 0.627 冰川 0 
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表 2 Mann-Kendall检验趋势标准
Table 2. Mann-Kendall trend test
β Z 趋势类别 趋势特征 β>0 Z>2.58 4 极显著增加 β>0 1.96<Z≤2.58 3 显著增加 β>0 1.65<Z≤1.96 2 微显著增加 β>0 Z≤1.65 1 不显著增加 β=0 Z 0 无变化 β<0 Z≤1.65 −1 不显著减少 β<0 1.65<Z≤1.96 −2 微显著减少 β<0 1.96<Z≤2.58 −3 显著减少 β<0 Z>2.58 −4 极显著减少
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表 3 变异系数稳定等级
Table 3. Stability grading based on coefficient of variation
CV 稳定性类别 Vj≤0.05 微弱波动 0.05<Vj≤0.10 弱波动 0.10<Vj≤0.15 相对中波动 0.15<Vj≤0.20 中波动 0.20<Vj≤0.25 相对高波动 0.25<Vj≤0.30 高波动 0.30<Vj≤0.35 相对强波动 Vj≥0.35 强波动
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表 4 岩石风化碳汇通量Sen-Hurst未来变化趋势类别
Table 4. Sen-Hurst based future trends of flux categories for carbon sink fluxes from rock weathering
Hurst Slope 未来趋势 H>0.5 Sen>0 持续增加 Sen<0 持续减少 H=0.5 − 无法预测 H<0.5 Sen>0 由增加变为减少 Sen<0 由减少变为增加
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表 5 云南省2001—2020年6类岩石年均消耗CO2估算结果
Table 5. Estimated annual average CO2 consumption for six rock types in Yunnan Province from 2001 to 2020
岩石类型 面积/km2 消耗CO2通量/(103 mol·km−2·a−1) 消耗CO2质量/(103 t·a−1) 消耗C质量/(103 t·a−1) 硅酸盐岩 变质岩和深成岩 51034 51.20 114.97 39.54 酸性火山岩 10657 87.55 41.05 11.20 砂岩 153155 56.29 379.00 103.36 页岩 100705 207.22 918.20 250.42 碳酸盐岩 66383 582.91 1702.60 464.35 冰川 3 __ __ __ 总年均 __ 49.26 157.79 43.44 总计 381937 985.17 3155.82 868.87
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