Spatiotemporal patterns and carbon balance zoning optimization of county-level carbon budget in Fujian Province

Summary

The terrestrial ecosystem carbon budget is critical for mitigating global climate change and advancing regional low-carbon development. This study analyzes county-level carbon budgets in Fujian Province, China’s first ecological civilization pilot zone, from 2000 to 2023. Spatiotemporal dynamics of carbon emissions and sequestration were investigated, and a carbon balance zoning framework was developed. County-level carbon emissions exhibited a coastal-high, inland-low pattern, in contrast to the spatial distribution of sequestration. The carbon compensation rate displayed temporal stability, whereas the economic contribution coefficient showed pronounced spatial heterogeneity and the ecological support coefficient conformed to a low-coastal, high-inland structure. By integrating the evolutionary characteristics of carbon balance zones from 2000 to 2023 with major function-oriented zoning, nine sub-regions were identified and targeted optimization strategies were proposed. These findings elucidate the mechanisms of county-level carbon balance, thereby contributing to regional low-carbon transitions and informing carbon reduction strategies.

Graphical abstract

Highlights

• •Carbon sources clustered coastally while sinks concentrated inland
• •ECC declined seaward-to-inland, ESC showed opposite gradient across Fujian Province
• •Based on MFOZ types, Fujian Province can be classified into 9 zones

Environmental science; Environmental monitoring; Applied sciences

Introduction

The Intergovernmental Panel on Climate Change (IPCC) warned in its Sixth Assessment Report (AR6) Synthesis Report (Climate Change 2023) that global average temperature has increased by 1.1°C. Globally, all nations are confronted with unprecedented climate risks accompanied by frequent extreme weather disasters, which have generated adverse impacts of varying magnitudes on human productive activities and livelihoods.¹ As one of the most important greenhouse gases in the atmosphere, The activity pathways of carbon dioxide are intrinsically linked to global climate change^2,3 and constitutes a critical threat to human survival and sustainable development.⁴ Balancing carbon emissions and carbon sequestration directly influences the progress of achieving dual carbon goals,^5,6 serving as a core issue in global climate change research.⁷ This balance can reconcile conflicts between economic growth and ecological resource conservation, promote regional collaborative low-carbon transformation through spatial governance thinking, and progressively realize ecological common prosperity.

Extensive research has been conducted globally in this domain, primarily focusing on carbon budget accounting,^8,9 spatiotemporal patterns,¹⁰ carbon compensation mechanisms,¹¹ and spatial correlation analyses of carbon budgets.¹² Carbon budget accounting, which forms the foundation for revealing regional carbon source-sink dynamics, has seen continuous methodological refinement using diverse data sources like energy consumption and remote sensing, with the emission factor method emerging as the most widely applied.¹³ While initial investigations often concentrated on specific ecosystem types such as croplands,^14,15 forests,¹⁶ or grasslands,¹⁷ there is a growing recognition of the need to integrate the carbon sink functions of entire terrestrial ecosystems for a more holistic evaluation.¹⁵ Regarding spatiotemporal dynamics, existing studies have largely analyzed regional differences at single scales,^18,19 with only a few exploring cross-scale variations,²⁰ from global²¹ to national²² and urban agglomeration scales.²³ Carbon compensation, a vital component of improving ecological compensation mechanisms, has seen models constructed at provincial, county, and watershed scales,²⁴ with applications spanning diverse fields from ecological engineering^25,26,27 to tourism,^28,29 and even extending to individual willingness to pay.³⁰ Finally, conducting carbon balance analyses and formulating spatial zoning strategies based on carbon budget accounting are recognized as effective pathways to promote regional carbon neutrality.^31,32 Within this context, major function-oriented zones (MFOZs), delineated by governments based on core regional functions, present a valuable analytical lens, as significant differences across MFOZ types transcend traditional administrative boundaries and enhance the understanding of regional heterogeneity’s impact on carbon budgets.³³ Overall, existing literature has largely concentrated on national, provincial, urban agglomeration and typical watershed scales, whereas county-level carbon budget research remains insufficient.³⁴ As China’s first national ecological civilization pilot zone, Fujian Province possesses unique ecological endowments and institutional innovation experience, rendering it a typical and representative research case. To fill the above research gaps, this study took 67 county-level administrative units of Fujian as research objects, and systematically explored the spatiotemporal differentiation of terrestrial ecosystem carbon budgets alongside county-scale carbon balance zoning optimization.

The marginal contributions and innovations of this research are reflected in two dimensions: (1) this study improved the theoretical foundation of county-level carbon balance accounting. Previous studies mostly only calculated single ecosystem type carbon sinks including cropland,^14,15 forest¹⁶ and grassland ecosystems,¹⁷ which failed to fully characterize county-level carbon flux structures. By establishing a holistic carbon accounting framework integrating multi-type vegetation carbon sequestration and anthropogenic carbon emission inventories, this study mitigated the systematic bias embedded in traditional carbon accounting methods. (2) This research constructed a carbon balance zoning framework considering territorial functional heterogeneity. Conventional carbon compensation zoning schemes regard administrative units as homogeneous research objects and ignores the differentiated carbon source-sink patterns formed by varied territorial development orientations (Guo et al., 2024). This study incorporated major function-oriented zones (MFOZs) planning into the carbon balance zoning framework to reveal the systematic differences in carbon compensation demand among different functional zones.

Results

Research area

Fujian Province lies on the southeastern coast of China, within the geographic range of 23°31′N–28°18′N and 115°50′E−120°43′E (Figure 1). It covers a land area of 124,000 km², with jurisdiction over nine prefecture-level cities and the Pingtan Comprehensive Experimental Zone. As China’s first National Ecological Civilization Pilot Demonstration Zone, Fujian boasts a forest coverage rate of 65.12%—the highest in the country for 45 consecutive years—and substantial carbon sink endowment. It exhibits a spatially stratified carbon sequestration regime characterized by “mountain forest carbon sinks + coastal blue carbon sinks,” providing a natural spatial foundation for county-level carbon compensation research.

Figure 1.

Geographical location of the study area in Fujian Province, China

Materials and methods

In terms of carbon emissions, Fujian exhibits an “industry-dominated, spatially concentrated” pattern. Through interprovincial carbon market collaboration and forestry carbon credit trading mechanisms, the province has effectively alleviated the tension between ecological protection and economic development. Furthermore, the net-zero emission factory model exemplified by CATL has become a global benchmark for low-carbon industrial transformation.

Fujian is selected as the study area due to its representativeness and exemplary in ecological progress, carbon sink endowments, and low-carbon transition practices. As a pioneer in national ecological civilization construction, Fujian’s practical exploration of carbon budget accounting, ecological carbon compensation mechanisms and differentiated carbon balance zoning can provide empirical references for advancing harmonious human-nature modernization nationwide.

Data source

The land use classification data (2000–2023) for the study area were obtained from the China Land Cover Dataset (CLCD) with a resolution of 30 m × 30 m. NPP (net primary productivity) data were sourced from NASA’s MOD17A3 dataset (https://search.earthdata.nasa.gov/search/) at 500 m × 500 m resolution. GDP statistics were collected from the Fujian Statistical Yearbook and Fujian Statistical Bulletin. Spatial data, including administrative vector boundaries and urban point locations, were acquired from the Resource and Environment Data Cloud Platform (http://www.resdc.cn). To guarantee spatiotemporal data consistency, administrative boundary data across years were unified to the 2020 county-level vector standard. Kinmen County was excluded from the scope of analysis due to a lack of accessible statistical data.

Technical roadmap

This study was designed to achieve the following objectives (Figure 2): (1) to analyze the spatiotemporal differentiation patterns of carbon budgets; (2) to evaluate county-level energy utilization efficiency and carbon sink capacity; (3) to clarify the refined carbon balance zoning layout informed by MFOZs.

Figure 2.

Data collection and processing methods used in this study

Research methods

Carbon emissions

County-level fossil energy consumption data from statistical yearbooks suffer from inherent limitations and uncertainties in bottom-up accounting. Therefore, this study adopted the EDGAR 2024 greenhouse gas (GHG) grid dataset as the core carbon emission data source. This dataset provides gridded emissions of the full suite of anthropogenic greenhouse gases, including CO₂, CH₄, N₂O, and fluorinated gases, aggregated to CO₂-equivalent mass using the Global Warming Potential (GWP) values from the IPCC Fifth Assessment Report. The emission boundary for our analysis is therefore defined as total anthropogenic GHG emissions in CO₂-equivalents. County-level emissions were extracted from the gridded EDGAR data by spatially overlaying the official administrative boundary vector layer for Fujian Province and aggregating all grid-cell emissions within each county’s jurisdiction. While the carbon sequestration estimates are based on the gross uptake of CO₂ by vegetation, using the EDGAR data, which provides total CO₂-equivalent emissions, ensures a comprehensive and internationally comparable emissions accounting framework. The potential slight inconsistency between the CO₂-equivalent emission boundary and the CO₂-only sequestration boundary is acknowledged and consistently applied across all county-level carbon balance indicators (CCR, ECC, and ESC), making the relative comparisons and zoning results robust.

Carbon sequestration

Vegetation sequesters carbon from the atmosphere through photosynthesis. NPP, namely the carbon fixed by vegetation, is an important component of the carbon cycle in terrestrial ecosystems,³⁵ and the reaction formula is as follows:

$$6{CO}_2+6H_{2}O\to C_6{H}_{12}{O}_6+O_2$$ (Equation 1)

For every 1 g of dry matter produced, 1.63 g of carbon dioxide is fixed. That is, for every 1g of NPP produced, 1.63 g of carbon dioxide can be absorbed.^36,37

Carbon compensation rate

The carbon compensation rate (CCR) is the ratio of carbon sequestration to carbon emissions in a certain county, which can characterize the carbon emission reduction pressure of the region.³⁸ The calculation formula is as follows:

$$CCR=C{S}_i/C_i$$ (Equation 2)

In the formula, CSi and Ci represent the carbon sequestration and carbon emissions of the region respectively; A CCR value >1 indicates that the region functions as a carbon sink. When CCR<1, it indicates that the region behaves as a net carbon source.

Economic contribution coefficient

The economic contribution coefficient (ECC) represents carbon productivity from an economic perspective and the calculation method is as follows³⁹:

$$ECC=\left(G_i/G\right)/\left(C_i/C\right)$$ (Equation 3)

In the formula, Gi and Ci represent the GDP and carbon emissions of a certain county respectively, and G and C represent the GDP and carbon emissions of Fujian Province, respectively. When ECC>1, it indicates that the region has relatively high energy utilization efficiency and carbon productivity. When ECC<1, it indicates that the area has relatively low energy utilization efficiency and carbon productivity.

Ecological support coefficient

The ecological support coefficient (ESC) characterizes the carbon sink capacity of the county, and the formula is as follows³⁹:

$$ESC=\left({CS}_i/CS\right)/\left(C_i/C\right)$$ (Equation 4)

In the formula, CSi and Ci represent the carbon sequestration and carbon emissions of a certain county, respectively, and CS and C represent the carbon sequestration and carbon emissions of Fujian Province, respectively. When ESC>1, it indicates that the region has a relatively high carbon sink capacity. When ESC<1, it indicates that the region has a relatively low carbon sink capacity.

Kernel density estimation

Utilize kernel density analysis to study the evolution trends of carbon emissions and carbon absorption, employing the Epanechnikov function.

$$K\left(x\right)=\{\begin{array}{c}\frac{3}{4}\left(1-x^2\right),x\in \left(-1,1\right)\\ 0,\text{Others}\end{array}$$ (Equation 5)

In the formula: x represents the year, and t represents the values of carbon emissions and carbon sequestration in each city.

Spatiotemporal evolution characteristics of carbon emissions

At the county-level, most counties exhibited an upward trend in carbon emissions, with coastal counties showing significantly higher growth rates than mountainous regions. At the prefecture-level scale, Quanzhou City consistently recorded the highest emissions in Fujian Province, followed by Fuzhou City and Zhangzhou City, while Sanming City and Nanping City maintained the lowest levels. At the provincial scale, carbon emission trends were divided into two phases: rapid growth (2000–2011) and slowed growth (2012–2023) (Figure 3). Overall, Fujian’s carbon emissions transitioned from sharp increases to gradual deceleration. The notable emission surge across scales during 2010–2011 is attributed to Fujian’s establishment of the West Coast Economic Zone around 2011, which spurred industrial investments and accelerated emissions. Post-2012, China’s prioritization of ecological civilization and green development policies contributed to the slowed growth trend.

Figure 3.

Carbon emissions of Fujian Province from 2000 to 2023

(A) Spatial distribution of carbon emissions in Fujian Province in 2003.

(B) Spatial distribution of carbon emissions in Fujian Province in 2013.

(C) Spatial distribution of carbon emissions in Fujian Province in 2023.

(D) Temporal-scale analysis of carbon emissions in Fujian Province from 2000 to 2023.

(E) Kernel density estimation of carbon emissions in Fujian Province from 2000 to 2023.

From 2000 to 2023, carbon emissions at the county level in Fujian Province exhibited an overall upward trend, albeit with notable spatial heterogeneity. Coastal counties experienced substantially higher growth rates than their inland mountainous counterparts, forming a distinct “coastal-inland” gradient that persisted throughout the study period.

At the city level, Fuzhou City consistently ranked first in total emissions, followed by Zhangzhou City and Longyan City, while Ningde City and Nanping City maintained the lowest levels—further underscoring structural regional disparities. The provincial emission trajectory can be characterized by two distinct phases: a period of rapid growth (2000–2011) and a subsequent phase of decelerated growth (2012–2023). The pronounced emission surge observed across all scales during 2010–2011 is largely attributable to industrial expansion spurred by the establishment of the West Coast Economic Zone in March 2011. The post-2012 slowdown aligns with China’s national strategy prioritizing ecological civilization and green development (Figure 3D).

Using the natural breaks classification method, county-level emissions were grouped into five tiers for the years 2003, 2013, and 2023 (Figures 3A–3C). The results reveal a stable spatial pattern characterized by “high emissions along the coast and low emissions inland.” Counties such as Xiamen City and the vicinity of Shishi City consistently occupied higher-tier categories, with Xiamen remaining in the highest tier throughout the period. Counties like Pingnan maintained consistently low emission levels. Overall, the spatial distribution of emissions remained largely unchanged from 2000 to 2023, suggesting strong path dependence in regional emission disparities.

Kernel density estimation (Figure 3E) provides further insights into the evolving distribution of emissions. The density curves for 2003, 2013, and 2023 exhibit a consistent rightward shift, confirming a province-wide increase in emission levels. The right tail of the distribution has progressively lengthened, indicating the emergence of counties with emissions far exceeding the provincial average—both in number and magnitude. Moreover, the transition from a “sharp-peaked” to a “broad-peaked” curve reflects increasing dispersion and growing divergence in county-level emission trajectories. Nevertheless, the persistent unimodal shape suggests that most counties remain concentrated around the evolving peak, indicating that the overall distribution structure has not fundamentally changed.

Spatiotemporal evolution characteristics of carbon sequestration

Drawing on an analysis of county-level carbon sequestration data in Fujian Province from 2000 to 2023, the findings reveal the following patterns. At the county scale, carbon sequestration exhibited a fluctuating yet generally upward trend, with carbon levels in mountainous counties consistently and significantly exceeding those in coastal counties. At the prefecture-level city scale, Nanping, Longyan, and Sanming ranked among the highest in the province throughout the study period. At the provincial scale, total carbon sequestration followed a trajectory of “fluctuating growth” (Figure 4D). Notably, relatively high values were observed during 2000–2004 and 2019–2023. The latter peak is correlated with Fujian’s designation as a national ecological civilization pilot zone in 2016, as three years of policy implementation may have contributed to elevating the province’s carbon sequestration levels.

Figure 4.

Carbon sequestration in Fujian Province from 2000 to 2023

(A) Spatial distribution of carbon sequestration in Fujian Province in 2003.

(B) Spatial distribution of carbon sequestration in Fujian Province in 2013.

(C) Spatial distribution of carbon sequestration in Fujian Province in 2023.

(D) Temporal-scale analysis of carbon sequestration in Fujian Province from 2000 to 2023.

(E) Kernel density estimation of carbon sequestration in Fujian Province from 2000 to 2023.

Figures 4A–4C reveals a distinct spatial pattern in county-level carbon sequestration, characterized by low values in coastal areas and high values in inland regions. Over the study period, the total area of carbon sinks exhibited a gradual expansion. Industrialized coastal counties such as Shishi City showed markedly lower carbon sequestration levels compared to ecologically advantaged counties like Shanghang. High-value zones were mainly concentrated in Nanping and Longyan, whereas low-value areas were clustered in more urbanized regions, including Fuzhou, Xiamen, and Ningde. This spatial configuration remained comparatively stable throughout the 2000–2023 period.

Figure 4E presents the kernel density estimation for carbon sequestration. By 2023, the left side of the density curve shifted rightward, indicating an expansion of low-value areas and a relative reduction in high-value areas. The peak height decreased slightly, and the peak width narrowed marginally, suggesting a weakening of regional divergence. The curve’s shape evolved from a “dominant peak with multiple secondary peaks” (multimodal) in 2003 to a “dominant peak with one secondary peak” (bimodal) by 2023, transitioning from a “sharp-peaked” to a “broad-peaked” form. This morphological change reflects growing disparities in carbon sequestration levels among counties.

Spatiotemporal evolution characteristics of carbon compensation rate

As illustrated in Figure 5D, the CCR across Fujian Province from 2000 to 2023 exhibited a generally stable trend at the provincial level, with values fluctuating within a relatively narrow range. For instance, from approximately 2.23 in 2000 to around 0.62 in 2023. Indicating that the province’s carbon sequestration capacity has gradually fallen short of its carbon emissions over the past 24 years. Among all regions, Nanping City consistently recorded the highest CCR, peaking at 4.33 in 2001, a pattern largely attributable to its extensive forest coverage, strong carbon sink capacity, and relatively low emissions stemming from a less industrialized economic structure. In contrast, Xiamen City, as a special economic zone and one of Fujian’s most developed and energy-intensive areas, maintained the lowest CCR throughout the study period.

Figure 5.

Carbon compensation rate in Fujian Province from 2000 to 2023

(A) Spatial distribution of carbon compensation rate in Fujian Province in 2003.

(B) Spatial distribution of carbon compensation rate in Fujian Province in 2013.

(C) Spatial distribution of carbon compensation rate in Fujian Province in 2023.

(D) Temporal-scale analysis of carbon compensation rate in Fujian Province from 2000 to 2023.

Figures 5A–5C illustrates pronounced spatial disparities in the (CCR) across Fujian Province, characterized by a distinct northwest-southeast gradient. In 2003, inland mountainous counties dominated the highest CCR tier, including Yongtai (32.27), Pingnan (30.72), and Mingxi (27.93), whereas most coastal counties fell into the lowest category, such as Changle (0.09), the urban area of Zhangzhou (0.12), and the urban area of Fuzhou (0.16). By 2013, the threshold for the highest CCR tier had decreased to a range of 12–20, with counties like Pingnan (19.69) and Yongtai (16.72) persisting as major carbon sinks, while coastal industrial areas such as Shishi (0.02) remained in the lowest tier. In 2023, this spatial configuration persisted, with Pingnan (18.86) leading the highest tier and Shishi (0.006) along with the urban area of Zhangzhou (0.04) occupying the lowest. Over the 24-year study period, the pronounced northwest-southeast gradient remained evident, underscoring the enduring dichotomy between forested inland carbon sinks and industrialized coastal carbon sources.

Spatiotemporal evolution characteristics of economic contribution coefficient

According to Figure 6, in 2003, the ECC ranged from 0.06 to 9.83, indicating imbalances between carbon emissions contributions and economic contributions across counties. High ECC values were concentrated in coastal areas, such as Shishi City and Dongshan City, reflecting higher carbon productivity and energy efficiency compared to other regions.

Figure 6.

Spatial distribution of the economic contribution coefficient in Fujian Province (2003, 2013, and 2023)

Conversely, counties like Zhangping City, Datian County, and Hua’an County exhibited relatively low ECC values. In 2003, 50 counties had ECC>1, suggesting alignment between economic development and technological levels. However, by 2013, the number of counties with ECC >1 slightly decreased to 49, attributed to rapid economic growth and urbanization outpacing technological advancements, leading to increased carbon emissions. From 2003 to 2023, Fujian Province’s government prioritized sustainable development, gradually increasing the number of counties with ECC >1 from 50 to 45, stabilizing thereafter. This trend reflects improved carbon productivity and energy efficiency in most regions, likely driven by the 2006 provincial policy Implementation Opinions on the General Plan for Ecological Province Construction. By integrating carbon emission intensity targets into local planning and enforcing stricter environmental regulations, Fujian Province promoted industrial transformation and upgrades, enhancing energy efficiency. Currently, the ECC exhibits a spatial pattern of “high values around the periphery and low values in the central areas,” maintaining steady progress.

Spatiotemporal evolution characteristics of ecological support coefficient

Figure 7 highlights a spatial pattern of “high inland values and low coastal values,” particularly demarcated by a line from Lianjiang County to Yunxiao County. In 2003, southern regions south of this line were low-value ESC areas, while northern regions benefited from forest resources in southern China’s key forest zones, exhibiting high carbon sequestration capacity. By 2013, low ESC values persisted in coastal areas (e.g., economically developed regions with low carbon sequestration capacity). From 2010 to 2023, high ESC values expanded to include Shouning county and Zhouning county, linked to Ningde City’s “Four Forests” ecological initiatives, which boosted vegetation coverage. Throughout 2013–2023, county governments balanced economic growth with ecological protection, optimizing industrial structures and maintaining stable ESC levels. Overall, Fujian Province’s ecological carrying capacity has gradually strengthened, driven by sustained policy efforts to harmonize development with environmental sustainability.

Figure 7.

Spatial distribution of the county-level ecological support coefficient in Fujian Province (2003, 2013, and 2023)

Optimization of carbon balance zoning based on major function-oriented zones

Based on carbon emissions accounting and guided by China’s carbon peaking and carbon neutrality Standard System Development Guidelines. With reference to zoning frameworks proposed by Kong (2023), Fujian Province was classified into four zones using indicators including carbon emissions volume, carbon sequestration capacity, ESC, and ecological carrying coefficient (ECC): (1) carbon neutrality demonstration zone (ECC>1, ESC>1), where economic activities exhibit high carbon efficiency coupled with sufficient ecosystem carbon offset capacity, demonstrating pioneer potential for carbon neutrality; (2) carbon sink conservation zone (ECC<1, ESC>1), characterized by low economic-contributed carbon emissions yet significant ecosystem carbon sequestration capacity, requiring prioritized protection to expand carbon sink reserves; (3) industrial decarbonization transition zone (ECC>1, ESC<1), marked by economic reliance on high-carbon industries but insufficient ecological restoration capacity, urgently needing technological upgrading and energy substitution; and (4) low-carbon revitalization collaboration zone (ECC<1, ESC<1), where both economic and ecological carbon efficiencies remain suboptimal, necessitating cross-regional collaboration and policy support for low-carbon revitalization. Corresponding low-carbon optimization strategies were formulated accordingly. A comparative analysis of carbon balance zoning patterns in Fujian Province was conducted for 2003, 2013, and 2023.

Carbon balance zoning is closely linked to regional economic development.⁴⁰ Given the significant disparities in strategic status, development stages, and economic conditions among counties within Fujian Province, decarbonization efforts should prioritize understanding regional development realities. By integrating the Fujian Province MFOZs planning with carbon emissions economic contribution rates and carbon sequestration ECCs,⁴¹ this study proposes 9 refined carbon balance zones (Figure 8) to reflect the interplay between regional functions and carbon sinks.

Figure 8.

Optimization of carbon balance zoning in Fujian Province based on major function-oriented zones (2003, 2013, and 2023)

Low-carbon development zones

This category comprises three subcategories: low-carbon development zones within major agricultural production zones, within key development zones, and within key ecological function zones. The first subcategory is predominantly agricultural, with limited industrial activity, and is mainly distributed across selected counties in Nanping City, Sanming City, and Longyan City. These areas host relatively well-developed agricultural industries, such as Ninghua’s Helong rice, Jianning’s white lotus, and Guangze’s white-feathered broilers. This subcategory has exhibited an overall expanding trend over time and constitutes the primary type of low-carbon development zone. The second subcategory, situated within key development zones, possesses substantial development potential alongside high energy utilization efficiency and robust carbon sink capacity. Primarily located in certain counties of Ningde City, Fuzhou City, and Zhangzhou City, this subcategory has shown a decreasing trend year by year. The third subcategory, found within Key Ecological Function Zones, is characterized by critical ecological roles, low land development intensity, and high energy efficiency and carbon sequestration capacity. It includes counties such as Taining county, Pingnan county, Shouning county, and Zherong county, where the local economy is mainly supported by the cultural tourism industry, with ongoing efforts to promote the integration of agriculture, culture, and tourism. Although the spatial extent of this category has remained relatively stable, it still exhibits a declining trend.

Carbon sink functional zones

This zone is divided into two subcategories: Carbon Sink Functional Zones within Major Agricultural Production Zones and within Key Ecological Function Zones. The former refers to areas with sound ecological quality yet relatively low carbon productivity, primarily oriented toward the provision of ecological products. These are mainly distributed in Pinghe county and Changting county, with their overall scope showing a decreasing trend. The latter constitutes the dominant type of Carbon Sink Functional Zone. These areas hold ecological significance for protection and restoration, supporting green and sustainable socioeconomic development, and safeguarding public well-being. However, they are also characterized by relatively low energy efficiency. This subcategory is mainly distributed in Wuyishan City and Anxi County.

Carbon source control zones

This zone consists of two subcategories: carbon source control zones within key development zones and within optimized development zones, predominantly concentrated in the coastal regions of Fujian Province. The first subcategory benefits from favorable locational conditions for development and exhibits high land suitability for development; however, its carbon sink capacity requires enhancement. During 2000–2023, the composition of this subcategory experienced dynamic fluctuations, with Huian county and Jinjiang City remaining relatively stable. Take Jinjiang City as an example, the region is dominated by labor-intensive manufacturing sectors including footwear and garment production, which consequently leads to substantial carbon emission outputs. The second subcategory features high land development intensity, well-established industrial sectors, and high energy utilization efficiency, but possesses weak carbon sink capacity. Since 2000, this subcategory has consistently included the urban areas of Fuzhou City, Xiamen City, and Quanzhou City. These areas exhibit high levels of urbanization, represent the most economically developed and densely populated regions within the province, and consequently generate high carbon emissions.

High-carbon optimization zones

This zone is further divided into three subcategories: high-carbon optimization zones within key development zones, within major agricultural production zones, and within key ecological function zones. The first subcategory possesses favorable locational conditions for development but exhibits both low carbon productivity and low carbon sink capacity. These areas are spatially dispersed across the province, primarily located in Changle District, the urban areas of Sanming City, Zhangzhou City, and Longyan City, as well as Longhai City, displaying a decreasing trend. The second subcategory primarily serves agricultural functions. Mainly distributed in Changtai County, Shunchang County, and Zhangping City, these areas have progressively promoted the construction of agricultural demonstration parks and bases integrating facility agriculture, high-value agriculture, and high-tech agriculture. This facilitates the transition from traditional farming practices to appropriately scaled operations. For instance, Changtai County was designated a provincial-level modern agricultural industrial park in 2019, which, while advancing agricultural product development, has also contributed to an increase in agricultural carbon emissions. The third subcategory primarily involves Datian County and Hua’an County. The rationale for their inclusion lies in their status as typical mountainous counties in Fujian Province, endowed with superior ecological conditions yet facing pressures related to transitioning their development models.

Discussion

As China’s pioneering national ecological civilization pilot zone, Fujian Province delivered valuable empirical references for the formulation of regional ecological carbon compensation mechanisms. This study systematically analyzed the county-level carbon budget of Fujian Province during 2000–2023, and comprehensively revealed its spatiotemporal evolutionary rules and spatial differentiation features of carbon balance. With the introduction of the ECC and ESC, this research constructed a dual-dimensional carbon balance zoning system integrating economic efficiency and ecological carrying capacity for Fujian Province.

• (1)Total carbon emissions and total terrestrial carbon sequestration both rose throughout the research period, yet the relative capacity of carbon sinks failed to keep pace with the growth of carbon sources. Carbon emissions presented a typical pattern of coastal carbon source agglomeration and inland carbon sink concentration, while carbon sequestration exhibited the reverse spatial distribution characteristic. This contrasting spatial pattern highlighted an urgent demand for county-level governance solutions that coordinate socioeconomic growth and carbon mitigation.
• (2)The county-scale ECC and ESC values showed prominent spatial heterogeneity across the province. ECC declined gradually from coastal developed regions to inland mountainous counties, whereas ESC decreased from inland ecological zones to coastal urbanized areas. Such remarkable spatial differentiation was tightly linked to the continuous rollout of provincial ecological restoration and protection projects.
• (3)Relying on carbon budget accounting results, all county-level units were categorized into four primary carbon balance functional zones. Combined with the composite characteristics of ECC and ESC, the study further subdivided the research area into nine differentiated subzones, which facilitated targeted identification of regional gaps in carbon abatement and carbon sink enhancement. The zoning system laid a solid scientific foundation for differentiated low-carbon spatial governance within Fujian Province. The county-scale MFOZ-coupled carbon balance zoning framework proposed in this study can provide a replicable analytical paradigm for other provincial ecological civilization pilot zones in China.

Spatiotemporal differentiation patterns of county-level carbon budget

The results indicate that carbon emissions in Fujian Province exhibit a spatial pattern characterized by lower levels in the northwest, progressively increasing toward the southeast coastal areas. This finding can be primarily attributed to regional disparities in economic structure and geographical conditions.⁴² As the province’s economic core, the southeastern coastal area concentrates a substantial number of industrial bases and port cities, resulting in significantly higher energy consumption intensity compared to the northwestern mountainous regions, which are predominantly oriented toward ecological protection. In 2023, carbon emissions in the urban areas of Fuzhou City, Putian City, and Xiamen City ranged from 12.62 to 16.94 million tons. Over time, this high-emission area has gradually expanded, forming an agglomeration effect—a phenomenon largely driven by rapid industrialization, which has established energy-intensive industries as the dominant sector within this contiguous region.

In contrast, carbon sequestration in Fujian Province displays a “southwest high, northeast low” distribution pattern,⁴³ with an overall increasing trend and gradual expansion of carbon sink areas. High-value carbon sequestration zones are concentrated in the southwestern part of the study area, primarily in Shanghang county, Wuping county, and Zhangping City within Longyan City. These areas are characterized by favorable ecological environmental quality, relatively slow economic development, and generally low development intensity—a pattern corroborated in their study of Longyan City.⁴⁴ Between 2000 and 2023, both the total area and aggregate volume of carbon sinks in Fujian Province increased. The highest carbon sequestration value in 2023 was recorded in Jianou City, Nanping City, reaching 5.32 million tons—an increase of 8.8% compared to 2000. This enhancement is correlated with the implementation of national environmental protection policies and the effectiveness of ecological civilization pilot zone construction, though the specific mechanisms require further investigation.⁴⁵ Conversely, certain counties in Quanzhou City, Putian City, and elsewhere have experienced a gradual decline in carbon absorption. This spatial pattern may be attributed to this decline is linked to environmental degradation resulting from rapid economic development, which has diminished the carbon sink capacity of local ecosystems.

Analysis of county-level energy utilization efficiency and carbon sink capacity

As a prominent demonstration zone for ecological civilization in China, Fujian Province has attracted considerable attention regarding its economic-ecological synergistic development. While most existing studies have focused on the spatiotemporal dynamics of carbon emissions,⁴⁶ driving factors,⁴⁷ and low-carbon high-quality development,⁴⁸ this study employs the ECC and ESC to investigate the natural and socioeconomic conditions underlying carbon sink capacity and energy utilization efficiency. Significant spatial heterogeneity exists across counties in terms of both economic contribution to carbon emissions and ecological carrying capacity. In southern Fujian (e.g., Shishi City, Hui’an county), which serves as a key industrial base guided by regional industrial planning,⁴⁹ the economic contribution substantially exceeds the carbon emission contribution, resulting in high ECC values. These areas face greater challenges and difficulties in carbon emission reduction, making it imperative to pursue both ecological and technological carbon sequestration.⁵⁰ In contrast, Zherong county, Shouning county, Zhouning county, Gutian county, and Pingnan county. All recognized as national ecological civilization construction demonstration areas, which have experienced improved vegetation coverage and enhanced carbon sink capacity under positive human intervention, thereby exhibiting relatively strong ESC values.

While the influence of human activities on ESC appears substantial in our results, consistent with findings from other studies,⁵¹ this does not preclude the potential role of climate variability. Our analytical framework was not designed to separate these effects, and thus this interpretation should be considered a plausible explanation warranting further targeted research. As a major manufacturing province, Fujian’s vegetation cover is directly affected by human activities such as urban expansion. With ecological civilization construction becoming a strategic priority in Fujian, green, low-carbon, and high-quality development has emerged as a central focus. In tandem with this developmental trajectory, carbon productivity and energy utilization efficiency have steadily improved across most regions. Human activities are progressively transitioning from high-carbon and extensive patterns toward low-carbon and intensive models, thereby fostering coordinated regional green development.

Optimization of carbon balance zoning

Carbon balance zoning serves as a spatial governance tool for achieving regional “dual carbon” goals, with its core objective being the reconciliation of conflicts between economic development and ecological protection. Drawing on the case of Fujian Province, this study integrates the MFOZs planning with a carbon balance indicator system. By selecting the years 2003, 2013, and 2023 for analysis, we further calculated the ECC and ESC. Based on the above analytical results, the study implements a zoning classification framework that divides the study region into four core functional categories. A finer partition yields nine distinctive subzones, exemplified by low-carbon development zones in major grain-producing functional areas and carbon source governance zones within optimized development functional regions. This classification allows for a systematic interpretation of how natural background conditions and industrial structure may interact to shape regional carbon balance characteristics, based on the observed spatial patterns of ECC and ESC. The proposed zoning approach not only overcomes the limitations of traditional single-indicator methods but also provides a spatial identification basis for designing differentiated low-carbon policies.

The results indicate that the coastal economic core areas (Fuzhou City, Xiamen City, Quanzhou City), identified as carbon source control zones, maintain persistently high carbon emissions due to high urbanization rates and industrial agglomeration. Their low ESC values reflect the lag in industrial structure transformation. Inland mountainous areas are predominantly characterized by low-carbon development zones and carbon sink functional zones; however, the advancement of agricultural modernization has led to their transition toward high-carbon optimization zones, illustrating the dual impact of agricultural intensification on carbon emissions. Although key ecological function zones exhibit notable advantages in carbon sequestration, energy inefficiencies induced by tourism development have undermined their ecological contributions.

Spatial configurations of carbon balance zoning demonstrate prominent hierarchical correlation with regional economic gradients, as evidenced by the concentrated distribution of carbon source governance zones within affluent coastal metropolises and carbon sink conservation zones across economically lagging inland counties. This observed association is consistent with findings from other regions⁵² and suggests that economic structural factors may be important determinants of carbon balance characteristics. Nevertheless, the cross-sectional nature of this spatial association does not imply a deterministic relationship; other unobserved factors, including local institutional arrangements, industrial composition, and land-use history, likely moderate this association. The zoning framework proposed here should be interpreted as a descriptive spatial typology that captures observed patterns rather than a causal model of regional carbon balance determination. It is essential to clarify the development status of different zones and, based on actual conditions, formulate targeted ecological restriction policies. From an economic development perspective, guiding regions to advance industrial transformation, innovate energy utilization patterns, and improve energy efficiency holds significant positive implications for achieving regional carbon balance.⁵³

Theoretical contribution

The theoretical contributions of this paper are mainly reflected in the following four aspects:

Based on the multidisciplinary methods and perspectives of geography, ecology, and economics, this study constructs a carbon budget assessment system, expanding the theoretical framework of carbon budget, aiming to reveal the internal relationship of carbon budget balance at the county-level in Fujian Province. (1) Constructing the carbon budget accounting and carbon compensation zoning at the county scale is a key step in promoting ecological common prosperity. Given that the unified laws of carbon budget and carbon balance in existing studies based on county-level unit data are still unclear,³⁸ this study, from the perspective of the county scale in Fujian, the first pilot demonstration area of ecological civilization in China, provides new paths and academic perspectives for global county-scale carbon budget research. (2) This study calculates the carbon absorption of terrestrial ecosystems in Fujian Province, accurately assesses the current situation, trends, and countermeasures of county—level carbon budget and carbon balance, and compensates for the limitations of previous studies that mostly calculated single—type carbon sinks.⁵⁴ (3) This study makes up for the deficiency in the application of MFOZs in carbon budget balance research. By incorporating the MFOZs zone planning into the research framework of carbon budget balance, it reveals the differences under the county-level MFOZs planning in terms of the methods, contents, and intensities of territorial space development,³³ breaking the spatial boundaries of traditional administrative divisions.

Research implications

• (1)Deepening regional synergistic emission reduction mechanisms and establishing a differentiated responsibility system for coordinated development between mountainous and coastal areas. It is imperative to clarify emission reduction responsibilities between coastal and inland regions. Given the carbon emission spatial differentiation featuring low values in the northwest and concentrated high values in the southeast, coupled with the sustained expansion of high-emission regions across coastal urban clusters, the southeastern coastal economic core zone shall bear enhanced primary obligations for carbon abatement. Stricter targets for both total carbon emissions and emission intensity should be formulated, and the feasibility of establishing cross-county carbon emission trading and compensation mechanisms (e.g., within the Fuzhou-Putian-Quanzhou cities) should be explored. Concurrently, the carbon sink potential of the northwestern ecological barrier should be activated. The ecological advantages of high-value carbon sink areas in the northwest and southwest (e.g., Shanghang country, Wuping country, Zhangping City, and Jian’ou City), which exhibit an upward trend in carbon sequestration, should be fully leveraged by incorporating their carbon sink capacity into the regional carbon neutrality target accounting system. Ecological compensation for key ecological function counties (e.g., national ecological civilization construction demonstration counties such as Zherong country and Shouning country) should be enhanced to support the consolidation and improvement of carbon sink capacity in forest and wetland ecosystems, thereby achieving synergy between “carbon sequestration enhancement” and “ecological prosperity for local communities.”
• (2)Accelerating the green and low-carbon transition of the industrial system. In southern Fujian (e.g., Shishi City and Hui’an country), where high ECC values indicate substantial emission reduction pressures, stringent restrictions on new high-energy-consumption and high-emission projects should be enforced. Mandatory clean production, circular economy, and low-carbon transformation of existing industrial bases should be implemented. The development of high-tech and high-value-added industries should be vigorously promoted, alongside the transition toward clean energy structures, to simultaneously enhance both ecological and technological carbon sequestration capacity, thereby resolving the inherent conflict between industrial growth and emission reduction. Furthermore, inland mountainous areas should be guided to avoid replicating the traditional high-carbon development pathways of coastal regions. Under the premise of strict ecological protection, green industries such as ecotourism, under-forest economy, and specialized agricultural and forestry product processing should be developed. Low-carbon technologies in agricultural modernization should be promoted to prevent the decline in carbon absorption associated with agricultural intensification. The green threshold for accepting industrial transfers should be raised.
• (3)Optimizing carbon balance zoning governance strategies based on major function-oriented zones. The outcomes of carbon balance zoning should be fully utilized and deeply integrated into territorial spatial planning and the MFOZs strategy. For carbon source control zones (coastal core areas such as Fuzhou City, Xiamen City, and Quanzhou City), the strictest controls on construction land increment and carbon emission constraints should be implemented. Mandatory green transformation of industries and upgrading of the service sector toward high-end development should be enforced, with priority given to improving the ESC to address structural transformation lags. For carbon sink conservation zones and carbon neutrality demonstration zones (ecologically advantageous counties in the northwest and southwest), ecological protection redlines should be strictly observed and large-scale industrialization and urbanization should be restricted. The core tasks are to consolidate and enhance natural carbon sinks, moderately develop eco-friendly industries, and rigorously control ecological disturbances and energy consumption associated with tourism development. For low-carbon development zones and major agricultural production zones, a balance between development and protection should be maintained. On the basis of ensuring food security and ecological safety, green agricultural production models should be promoted to prevent excessive increases in carbon emissions resulting from agricultural modernization. The concentration of industries toward low-carbon directions should be guided to enhance county-level economic vitality. Concurrently, a dynamic monitoring, evaluation, and adjustment mechanism for zoning should be continuously improved. Regular updates of county-level carbon emission, carbon sequestration, ECC and ESC data should be conducted to monitor the development status and policy effectiveness of each zone. Zoning boundaries and policies should be dynamically adjusted based on evaluation results to ensure the timeliness and adaptability of spatial governance strategies.

Limitations of the study

All interpretations regarding the driving mechanisms of carbon budget spatiotemporal differentiation in this study were derived from descriptive spatiotemporal correlation analysis rather than rigorous causal identification. The indicator system (CCR, ECC, and ESC) and spatial analysis methods adopted in this research cannot eliminate confounding interference factors, so the previous explanatory conclusions only provide hypothetical inference rather than verified causal relationships. Future research can integrate quasi-experimental methods including difference-in-differences (DID), event study and instrumental variable models to quantitatively separate the net impacts of ecological policies, industrial transformation, and land use change on county-level carbon balance dynamics.

Resource availability

Lead contact

Requests for further information and resources should be directed to and will be fulfilled by the lead contact, Baoyin Li (liby@fjnu.edu.cn).

Materials availability

This study did not generate new unique reagents.

Data and code availability

• •This paper analyzes existing, publicly available data. These accession numbers for the datasets are listed in the key resources table.
• •This paper does not report original code.
• •Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Acknowledgments

This work was supported by the Major Program of the National Social Science Fund of China (2021MZD024), Fujian Provincial Department of Finance General Project (CR-2304), Fujian Provincial Department of Finance Special Fund (SC-299), Fujian Provincial Science and Technology Department University-Industry Collaboration Project (2020N5008), Fujian Provincial Water Resources Department Project (SC-290), and Fujian Forestry Bureau Project (SC-259). We also sincerely appreciate the editorial team of iScience and the assigned academic editor for their constructive comments and suggestions on this manuscript.

Author contributions

Conceptualization, S.Z., L.W., and Q.Z.; methodology, S.Z. and C.X.; investigation, S.Z., C.X., L.W., B.L., and B.C.; data curation, S.Z. and Q.Z.; formal analysis, S.Z., L.W., and Q.Z.; software, S.Z.; validation, C.X., B.L., and B.C.; writing – original draft, S.Z. and Q.H.; writing – review and editing, S.Z., C.X., B.L., and B.C.; supervision, L.W.; project administration, B.L. and B.C.; funding acquisition, B.L.

Declaration of interests

The authors declare no competing interests.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Deposited data
Land use	China Land Cover Dataset	https://zenodo.org/records/18180184
NPP	NASA’s MOD17A3 dataset	https://search.earthdata.nasa.gov/search/
GDP	Fujian Statistical Yearbook and Fujian Statistical Bulletin	https://tjj.fujian.gov.cn/xxgk/njgb/tjnj/
Administrative vector boundaries and urban point locations	Resource and Environment Data Cloud	http://www.resdc.cn
Carbon emissions	IEA, FAOSTAT, USGS, Global Energy Monitor, GHSL, ERA5, IASI	https://edgar.jrc.ec.europa.eu/
Software and algorithms
ArcGIS	ESRI	https://www.arcgis.com/index.html
SPSSAU	Beijing Qingxi Technology Co., Ltd	https://spssau.com/index.html
Excel	WPS Office	https://www.wps.cn/

Experimental model and study participant details

This article does not contain any studies with all the experimental models (animals, human subjects, plants, microbe strains, cell lines, primary cell cultures) performed by any of the authors.

Method details

Please provide precise details of all the procedures in the paper (behavioral task, generation of reagents, biological assays, modeling, etc.) such that it is clear how, when, where, and why procedures were performed. We encourage authors to provide information related to the experimental design as suggested by NIH and ARRIVE guidelines (e.g., information about replicates, randomization, blinding, sample size estimation, and the criteria for inclusion and exclusion of any data or subjects).

Quantification and statistical analysis

Carbon accounting and spatial pattern analyses were performed at the county level across 67 administrative units in Fujian Province. Anthropogenic carbon emissions were derived from the EDGAR 2024 gridded greenhouse gas (GHG) emission inventory, aggregated to each county’s jurisdiction by spatial overlay, and expressed as CO₂-equivalents using the GWP values from the IPCC Fifth Assessment Report. Terrestrial carbon sequestration was estimated from MOD17A3 net primary productivity (NPP) data, applying a conversion factor of 1.63 g CO₂ absorbed per gram of NPP produced. For each county, the carbon compensation rate (CCR), economic contribution coefficient (ECC), and ecological support coefficient (ESC) were calculated for the entire study period (2000–2023), with representative years 2003, 2013 and 2023 selected for detailed spatial visualization. Spatiotemporal evolutionary trends were examined via kernel density estimation employing the Epanechnikov function, and county-level carbon emissions and sequestration were each categorized into five tiers using the natural breaks classification method. Carbon balance zoning was established by integrating the composite thresholds of CCR, ECC and ESC with the major function-oriented zone (MFOZ) planning framework, resulting in four primary functional categories, which were further subdivided into nine refined subregions. All spatial overlays and statistical computations were conducted using standard geographic information and statistical software. Further details are provided in the Methods and Results sections, tables, and figures.

Additional resources

This study did not generate additional resource.