Research on the Spatial-Temporal Coupling Characteristics between China's Net Carbon Sink of Cultivated Land Use and Grain Yield

doi:10.21203/rs.3.rs-3217379/v1

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Research on the Spatial-Temporal Coupling Characteristics between China's Net Carbon Sink of Cultivated Land Use and Grain Yield

https://doi.org/10.21203/rs.3.rs-3217379/v1

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In order to alleviate the increasingly severe climate warming problem, countries are actively promoting low-carbon economic transformation. Cultivated land use activities have dual effects of carbon emission and carbon absorption. An in-depth analysis of China’s net carbon source/sink of cultivated land use and its relationship with grain yield can provide decision-making references for ensuring food security and achieving China's "30.60 dual carbon" goal. Taking China's 31 provinces as the research unit, the net carbon sink of cultivated land use between 1991 and 2021 was calculated, the driving factors of carbon emission from cultivated land use were analyzed, the spatial-temporal characteristics of carbon emission and net carbon sink were pictured, and the improved Tapio coupling index was used to explore the relationship between the net carbon sink of cultivated land use and grain yield. The results showed that: (1) The carbon emission of cultivated land use showed an upward first and then downward trend, reaching a peak of 81.0579 million tons in 2015. Among the factors influencing carbon emissions of cultivated land use, the efficiency and economic factors have the most significant positive and negative effects on the carbon emission reduction of cultivated land use, respectively. (2) In the past 31 years, the net carbon sink of cultivated land use has increased from 404.595 million tons to 666.848 million tons, and China's cultivated land use system has always been in a state of carbon sinks. (3) At the national level, the net carbon sink of cultivated land use and grain yield are growth coupling or yield-dominant coupling in most years. The types of coupling at the regional level are varied but still dominated by growth coupling. Typically, provinces have a balanced relationship between the increased net carbon sink of cultivated land use and the increase in grain yield. Accordingly, the transformation of cultivated land use should be accelerated, the industrial structure of the plantation industry should be optimized, reasonable cultivated land protection policies should be formulated, and the reduction of carbon sources and increase of carbon sinks in large emitting provinces should be promoted by classification and batch.

food security

carbon emission

net carbon sink of cultivated land use

spatial-temporal characteristics

Tapio decoupling index

China's cultivated land use system has always been in a state of carbon sinks.
Eight coupling types are repositioned according to the net carbon sink and grain yield variation characteristics.
In most years, the net carbon sink of cultivated land use and grain yield is growth or yield-dominant coupling.

The relationship between reducing carbon sources and grain increase is coordinated

China has one-fifth of the world's population but only 7% of the world's cultivated land; as food security matters in national destiny and people's well-being, China's food security faces multiple challenges. The report of the 20th National Congress of the Communist Party of China puts food security in a prominent position. It proposes to guarantee national food security with the new development concept of an "all-encompassing approach to food." According to the "China Agricultural Outlook Report (2022–2031)", China's grain demand will rise to 864 million tons in 2030 even under a controlled grain consumption scenario. This enormous grain demand makes it necessary for China to maintain a pattern of cultivated land use characterized by high-intensity inputs of agricultural materials. The IPCC report shows that the carbon emissions from agricultural activities account for 13.5% of the total global carbon emissions and are rising, making carbon emissions from cultivated land use an essential source of global greenhouse gas increase(Xu et al., 2015). Since the process of cultivated land use will emit a large volume of greenhouse gases, its following environmental consequences cannot be ignored. If climate warming continues in the medium and long term, food production will be seriously affected(S. Chen et al., 2016). The essence of the "all-encompassing approach to food" is the sustainable development of agriculture, ecological protection, and balanced development of agricultural modernization, the basis of which is food safety. The country must play the role of cultivated land use to realize an adequate food supply.

Cultivated land use has a dual role of carbon source and carbon sink, and its utilization status directly affects national food security, ecologically sustainable development, and social harmony and stability. In the existing research on carbon emissions of cultivated land use, researchers have used various methods such as field experiments(Yan et al., 2015), model simulations(Li et al., 2003), and emission factors (Fu et al., 2022; Li et al., 2011; Wu et al., 2022a) to conduct studies. Related research can be divided into two streams: one stream is to pay attention to a specific type of carbon source, such as agricultural waste treatment (Shi et al., 2017), and examine the carbon emissions and emission reduction paths of specific links or whole processes in depth(Xia and Yan, 2020; Zhu et al., 2017); the other stream is to measure the total amount of carbon emissions generated by multiple types of carbon sources, focusing on the carbon emissions generated by the production process of cultivated land use, for example, Li et al. (2011) constructed an accounting inventory of agricultural carbon emissions containing six emission factors of fertilizer, pesticide, agricultural film, tillage, irrigation, and diesel; and decomposed the influencing factors of carbon emissions through the Kaya identity deformation. In addition, the carbon sequestration function of cultivated land soils and covers makes cultivated land use activities have dual effects of carbon emission and carbon absorption (Aertsens et al., 2013; Okolo et al., 2020; SMITH et al., 1997; West et al., 2010). Studies regarded the carbon content of the annual net biomass of crops as the carbon sequestration of cultivated land use (L. Chen et al., 2016), and have used the unit area method (Yin et al., 2016), the mass balance equation (Wang et al., 2017), and the net primary productivity of crops (Cao et al., 2022; Yang and Chen, 2016) to measure it. Among them, the net crop productivity method has been popularly applied to the study of regional crop carbon sink accounting, taking into account convenience and accuracy.

Based on estimating of carbon emissions and absorption of cultivated land use, scholars have extensively explored the net carbon effect of cultivated land use. Chen et al. (2015) measured the net carbon sink of cultivated land use in China from 1991 to 2011; Li et al. (2022) analyzed the temporal variation and spatial differentiation characteristics of the net carbon sink of cultivated land use; Wu et al. (2022b) conducted a study on the driving factors of net carbon effect of cultivated land use and the decoupling effect of net carbon sink and agricultural production. In an overview of the existing studies, the carbon source and carbon sink accounting lists of cultivated land use have been continuously expanded and improved; the relationship between net carbon sink and agricultural production has also been extensively explored. However, there is still room for improvement: (1) studies focus on construction land and urban land use, and little research has been conducted on the net carbon sink of cultivated land use; (2) the geographical scope of research is mainly limited to provincial or prefecture-level cities, and there are few comprehensive and systematic studies on the spatial-temporal characteristics analysis of net carbon sinks of cultivated land use nationwide. (3) The existing studies on decoupling cultivated land use have focused on the linkage between carbon emissions and agricultural output (Cheng et al., 2022) and less on the relationship between net carbon sink and grain yield.

Based on the research mentioned earlier, this paper conducts an accounting for carbon emissions and carbon absorption of cultivated land use in 31 provinces of the mainland of China (excluding Hong Kong, Macao, and Taiwan) from 1991 to 2021, measures the net carbon effect based on the difference between carbon source and sink, analyzes the driving factors of carbon emissions of cultivated land use, and pictures the spatial-temporal characteristics of carbon emission and net carbon sink. Furthermore, the expanded TAPIO coupling index was used to explore the relationship between the net carbon sink of cultivated land use and grain yield. In order to enrich the existing research on the intersection of net carbon sink of cultivated land use and grain production, as well as provide references for scientifically guiding the low-carbon transition of cultivated land use, ensuring food security, achieving China's "30.60 dual carbon" goal and promoting green and high-quality development of agriculture.

The marginal contributions of this paper are as follows: firstly, taking into account the dual attributes of carbon source and carbon sink of cultivated land use, scientifically measuring China's net carbon sink of cultivated land use and comprehending its temporal evolution characteristics and spatial-temporal evolution patterns, and judging the evolution process and development trend of net carbon effect of cultivated land use, aiming to improve the accounting research of net carbon sink of cultivated land use; secondly, this study investigates the coupling status between net carbon sink of cultivated land use and grain yield from both quantitative and velocity perspectives at the national and provincial levels, which complements the study of the relationship between net carbon sink and food production from the perspective of an "all-encompassing approach to food"; thirdly, when measuring the coupling index, eight coupling types are repositioned according to the variation characteristics of net carbon sink and grain yield, making the findings more compatible with the intrinsic relationship between homogeneous indicators, which can be extended to explore the long-term relationship between ecological indicators and economic indicators.

2.1. Calculation of carbon emissions of cultivated land use

According to the works of literature, this paper summarized that the carbon emissions of cultivated land use are mainly greenhouse gas emissions directly or indirectly caused by farmers' produce behaviors, which are mainly consequences of the following types of activities: (1) Direct or indirect carbon emissions caused by agricultural materials, such as fertilizers, pesticides, and agricultural films in production and usage. (2) Energy consumption, such as diesel, electricity, and other energy consumed in the use of agricultural machinery and agricultural irrigation, which can lead to direct or indirect carbon emissions. (3) Cultivated land planting activities, such as tilling, destroy the soil's organic carbon pool, which is released into the air and produces carbon emissions.

The existing literature on carbon emission measurement of cultivated land use has not yet formed a well-recognized method. This paper follows the IPCC carbon emission coefficient method adopted by Tian et al. (2012) to calculate the carbon emission of cultivated land use, mainly investigating six carbon sources of fertilizer, pesticide, agricultural film, agricultural machinery, irrigation, and tillage; the calculation formula is as follows:

$$\text{C = }{\text{C}}_{\text{f }}\text{+ }{\text{C}}_{\text{p }}\text{+}{\text{ C}}_{\text{m }}\text{+ }{\text{C}}_{\text{e }}\text{+ }{\text{C}}_{\text{i }}\text{+ }{\text{C}}_{\text{t}}$$

In Eq. (1), C represents the total carbon emission from cultivated land use (unit: ton). ${\text{C}}_{\text{f}}$, ${\text{C}}_{\text{p}}$, ${\text{C}}_{\text{m}}$, ${\text{C}}_{\text{e}}$, ${\text{C}}_{\text{i}}$, and ${\text{C}}_{\text{t}}$ represent the carbon emissions (unit: ton) caused by fertilizer, pesticide, agricultural film, agricultural machinery, irrigation, and tillage in the process of cultivated land use, respectively. Based on related studies (Li et al., 2011; Wang and Zhang, 2016; West and Marland, 2002; Wu et al., 2007; Zhao et al., 2010; Zhi and Gao, 2009), the formula and coefficients for calculating carbon emissions of cultivated land use were derived (Table 1).

Table 1

Calculation formula and carbon emission coefficient of each carbon emission source of cultivated land use.
Carbon Source	Formula	Carbon Source Input/Unit	Carbon Emission Coefficient	Reference
Fertilizer	${\text{C}}_{\text{f}}\text{ =}{\text{ G}}_{\text{f}}\text{ × A}$	${\text{G}}_{\text{f}}$: Fertilizer refining volume/kg	A = 0.896	West et al. (2002)
Pesticide	${\text{C}}_{\text{p}}\text{ = }{\text{G}}_{\text{p}}\text{ × B}$	${\text{G}}_{\text{p}}$: Pesticide usage/kg	B = 4.934	Zhi et al. (2009)
Agricultural film	${\text{C}}_{\text{m}}\text{ =}{\text{ G}}_{\text{m}}\text{ × D}$	${\text{G}}_{\text{m}}$: Agricultural film usage/kg	D = 5.18	Wang et al. (2016)
Agricultural machinery	${\text{C}}_{\text{e}}\text{ =}{\text{ A}}_{\text{a}}\text{ × E + }{\text{W}}_{\text{e}}\text{ × F}$	${\text{A}}_{\text{a}}$: Crop sown area/hm² ${\text{W}}_{\text{e}}$: Total power of agricultural machinery/kw	E = 16.47 F = 0.18	Zhao et al. (2010)
Irrigation	${\text{C}}_{\text{i}}\text{ =}{\text{ A}}_{\text{i}}\text{ × G}$	${\text{A}}_{\text{i}}$: Effective irrigated area / hm²	G = 20.5	Li et al. (2011)
Tillage	${\text{C}}_{\text{t}}\text{ =}{\text{ A}}_{\text{a}}\text{ × H}$	${\text{A}}_{\text{a}}$: Crop sown area/hm²	H = 3.126	Wu et al. (2007)

2.2. Decomposition of carbon emissions driving factors of cultivated land use

Compared with other factor decomposition methods, the LMDI decomposition method can eliminate the residual item, making the sum of the effects consistent with the total effect and thus making the model more convincing (Ang, 2015; Wang and Feng, 2017; Xu et al., 2016). According to the current literature results of Li et al. (2011), and combined with the actual situation of agricultural production, the formula is as follows:

$$\text{C = }\frac{\text{C}}{\text{AGRI}}\text{ × }\frac{\text{AGRI}}{\text{AGR}}\text{ × }\frac{\text{AGR}}{\text{AP}}\text{ × AP = AE × AS × EL × P}$$

In Eq. (2), C, AGRI, AGR, and AP represent the carbon emission of cultivated land use, the total output value of the plantation industry, the total output value of agriculture, forestry, animal husbandry and fishery industry, and total agricultural labor force in each province, respectively. While AE, AS, EL, and P represent agricultural efficiency factors, agricultural structure factors, agricultural economic level factors, and labor force factors. The change amount in carbon emissions from cultivated land use in period t (C_t) compared to carbon emissions from cultivated land use in the base period (C₀) can be expressed as follows:

$$\text{△}{\text{C}}_{\text{tot}}\text{ =}{\text{ C}}_{\text{t }}\text{-}{\text{ C}}_{\text{0}}\text{ = }\text{△}{\text{C}}_{\text{AE}}\text{ + }\text{△}{\text{C}}_{\text{AS}}\text{ + }\text{△}{\text{C}}_{\text{EL}}\text{ + }\text{△}{\text{C}}_{\text{P}}$$

Among them, $\text{△}{\text{C}}_{\text{AE}}$, $\text{△}{\text{C}}_{\text{AS}}$, $\text{△}{\text{C}}_{\text{EL}}$ and $\text{△}{\text{C}}_{\text{P}}$ represent the contribution values of efficiency, structural, economic, and labor factors, respectively. After decomposition, the formulae are as follows:

$\text{△}{\text{C}}_{\text{AE }}\text{= ∑}\text{γ}\left(\text{ln}{\text{AE}}_{\text{t}}\text{-}\text{ln}{\text{AE}}_{\text{0}}\right)$	(4)
$\text{△}{\text{C}}_{\text{AS}}\text{ = ∑}\text{γ}\left(\text{ln}{\text{AS}}_{\text{t}}\text{-}\text{ln}{\text{AS}}_{\text{0}}\right)$	(5)
$\text{△}{\text{C}}_{\text{EL}}\text{= ∑}\text{γ}\left(\text{ln}{\text{EL}}_{\text{t}}\text{-}\text{ln}{\text{EL}}_{\text{0}}\right)$	(6)
$\text{△}{\text{C}}_{\text{P}}\text{ = ∑}\text{γ}\left(\text{ln}{\text{P}}_{\text{t}}\text{-}\text{ln}{\text{P}}_{\text{0}}\right)$	(7)
where, $\text{γ}\text{ = }\frac{{\text{C}}_{\text{t}} \text{- }{\text{ C}}_{\text{0}}}{\text{ln}{\text{C}}_{\text{t }}\text{-}\text{ ln}{\text{C}}_{\text{0}}}$.

2.3. Carbon absorption calculation of cultivated land use

According to the “IPCC Guidelines for National Greenhouse Gas Inventories” (Eggleston et al., 2006), combined with related research findings (L. Chen et al., 2016; Luo, 2014; Yin et al., 2016), crops on cultivated land capture carbon in the air through photosynthesis and synthesize it into carbohydrates. This paper mainly considers the amount of organic carbon formed after cultivated land cover (crop) absorbs and fixes carbon dioxide from the atmosphere through photosynthesis during its life cycle, which is the net primary production. Fixed carbon crops are used as raw materials for production and processing or as final products sold to new entities and consumed. Since the cultivated land use system does not generate subsequent carbon emissions and has left the cultivated land use system, they are treated as carbon removal and excluded in the analysis. This paper adopts the biomass estimation method to measure the carbon absorption of cultivated land use, and its carbon absorption estimation equation is as follows:

$$\text{Z = }{\sum }_{\text{i-1}}^{\text{n}}{\text{δ}}_{\text{i}}\text{ × }{\text{D}}_{\text{i}}\text{ × }\frac{\text{1 -}{\text{ γ}}_{\text{i}}}{{\text{H}}_{\text{i}}}$$

In Eq. (8), Z represents the carbon absorption of crop photosynthesis during the growth period; H_i represents the economic coefficient of the ith crop, that is, the ratio of economic yield to biological yield; D_i represents the economic yield of the ith crop; δ represents the carbon absorption rate per unit of organic matter synthesized by photosynthesis by the ith crop; γ represents the water content of the ith crop (Table 2).

Table 2

Carbon absorption rate, average water content, and economic coefficient of main crops.
Crop type	Main crop	Carbon absorption rate	Water content	Economic coefficient
Food crops	Rice	0.414	0.12	0.45
	Wheat	0.485	0.12	0.4
	Corn	0.471	0.13	0.4
	Beans	0.45	0.13	0.4
	Tubers	0.423	0.7	0.7
Economic crops	Cotton	0.45	0.08	0.1
	Peanuts	0.45	0.1	0.43
	Rapeseeds	0.45	0.1	0.25
	Sugarcane	0.45	0.5	0.5
	Beetroots	0.407	0.75	0.7
	Tobacco	0.45	0.85	0.55
	Fruits	0.45	0.9	0.7

2.4. Calculation of net carbon sink of cultivated land use

The net carbon sink of cultivated land use is the difference between carbon absorption and carbon emissions; the calculation formula is as follows:

S = Z - C

(9)

In Eq. (9): S is the net carbon sink of cultivated land use (unit: ton); Z and C are carbon absorption and carbon emissions volume, respectively. If S > 0, the cultivated land use is a carbon sink effect; if S < 0, it is a carbon source effect; when S = 0, the carbon absorption of crops offsets the carbon emission caused by the process of cultivated land use, achieving carbon neutrality.

2.5. Improved coupling index based on Tapio decoupling model

The concept of decoupling was first proposed by the World Organization for Economic Cooperation and Development (OECD, 2002) in 1993 to reflect the relationship between economic performance and environmental hazards. In 2005, Tapio improved the decoupling model of OECD and further proposed the decoupling elasticity model (Tapio, 2005). The Tapio decoupling index focuses on the relationship between two reverse indicators, while net carbon sink and grain yield are positive indicators. Therefore, exactly copying the concept and classification criteria of the Tapio decoupling index is inappropriate. According to Wu (2022), this study redefines the coupling index of net carbon sink of cultivated land use and grain yield based on the original Tapio decoupling index, and the calculation formula is as follows:

$$\text{ε = }\frac{\text{δS}/\text{S}}{\text{δA}/\text{A}}\text{ = }\frac{\text{(}{\text{S}}_{\text{i}}\text{-}{\text{S}}_{\text{0}}\text{)}/{\text{S}}_{\text{0}}}{{\text{(A}}_{\text{i}}\text{-}{\text{A}}_{\text{0}}\text{)}/{\text{A}}_{\text{0}}}$$

In Eq. (10): ε is the elasticity of grain yield growth of net carbon sink from cultivated land use, named coupling index; $\text{δS}$ represents the net carbon sink change of cultivated land use; S_i and S₀ are the net carbon sink of current and base periods, respectively. $\text{δA}$ is the change of grain yield, A_i and A₀ are the current and base periods’ output values, respectively. The coupling index is the ratio of the change rate of the net carbon sink to the change rate of the current and base periods’ grain yield, reflecting the coupling degree of the development process of the two indicators. The definition of the coupling state is shown in Fig. 1.

Table 3

Indicators and economic implications of various coupling states.
Quadrant	Coupling type	Net carbon sink change rate	Change rate of grain yield	Index of coupling	Economic Implications
Ⅰ	Yield-dominant coupling	(0, +∞)	(0, +∞)	[0, 0.8]	The growth rate of net carbon sink is significantly slower than that of grain yield.
	Growth coupling			(0.8, 1.2)	The growth rate of net carbon sink is consistent with the growth rate of grain yield.
	Eco-dominant coupling			[1.2, +∞)	The growth rate of net carbon sink is significantly faster than that of grain yield.
Ⅱ	Weak output decoupling	(0, +∞)	(-∞, 0)	(-∞, 0)	Net carbon sink growth, grain yield decline.
Ⅲ	Yield-dominant negative coupling	(-∞, 0)	(-∞, 0)	[0, 0.8]	The decline rate of net carbon sink is significantly slower than that of grain yield.
	Decay coupling			(0.8, 1.2)	Net carbon sink is consistent with the decline rate of grain yield.
	Eco-dominant negative coupling			[1.2, +∞)	The net carbon sink decreased significantly faster than the grain yield.
Ⅳ	Ecologically weak decoupling	(-∞, 0)	(0, +∞)	(-∞, 0)	Grain yield growth, net carbon sink decline.

Unlike the reverse indicator, the ideal relationship between the two co-directional indicators is a simultaneous increase, the positive coupling relationship. Therefore, the state of quadrant Ⅰ is optimal. However, subtle differences exist between the coupling types in this quadrant: Eco-dominant coupling and Yield-dominated coupling indicate an imbalance in the growth rate between ecological protection and grain yield. The best state is when and only when $\text{ε}\text{∈}\left(\text{0.8, 1.2}\right)$, the growth rate of net carbon sink is consistent with the growth rate of grain yield, named Growth coupling.

2.6. Data source

The data on carbon emission and carbon absorption of cultivated land use in 31 provinces of China mainland (excluding Hong Kong, Macao, and Taiwan) from 1991 to 2021, such as fertilizer, pesticide, agricultural film, agricultural machinery, tillage, irrigation, grain crop and economical crop yields and related data, were obtained from the “China Rural Statistical Yearbook (1990–2022)” and the statistical yearbook of 31 provinces in China. Among them, fertilizer measure is based on the pure amount of agricultural fertilizer; pesticide and agricultural film are based on the actual amount used in the year; agricultural machinery is based on the total power of agricultural machinery in the year; tillage is replaced by the sown area of crops in the year; irrigation is based on the effective irrigation area in the year. The economic coefficients required for the accounting of crop carbon sequestration, the carbon absorption rate per unit of organic matter synthesized by the crop through photosynthesis, and the water content of the crop were obtained from the relevant literature listed above, as shown in Tables 1 and 2. A descriptive statistical analysis of the data used is shown in Table 4.

Table 4

Descriptive statistical analysis of the data accounting for net carbon sinks from 1991–2021 for cultivated land use in China.
Index	Unit	Obs	Mean	Std. Dev.	Min	Max
Fertilizer refining volume	ton	961	1534127	1298583	15000	7160900
Pesticide usage	ton	961	45715.59	40318.73	266	198764
Agricultural film usage	ton	961	58112.93	58569.61	20	343524
Crop sown area	hm²	961	5131087	3602985	88550	15065000
Total power of agricultural machinery	kw	961	23488850	24703420	481200	133530200
Effective irrigated area	hm²	961	1879982	1484498	81500	6177590
Rice yield	ton	961	6504065	7242247	710	29137000
Wheat yield	ton	961	3795085	6613473	210	38028000
Corn yield	ton	961	5452287	7146274	7000	41492000
Beans production	ton	961	611114.2	1033153	1000	9319730
Tubers yield	ton	961	1054177	1089785	980	6813000
Cotton yield	ton	961	257101.6	621311.9	10	5160760
Peanuts yield	ton	961	495038.6	910838	33	5949340
Rapeseeds yield	ton	961	444833.4	607686.9	10	3387000
Sugarcane yield	ton	961	5656250	14293010	150	82155820
Beetroots yield	ton	961	778635.8	1392279	5	6296490
Tobacco yield	ton	961	110027.8	179352.9	10	1150020
Fruits yield	ton	961	5417739	6990424	1560	59440000

3.1. Spatial-temporal Characteristics of Carbon Emissions of Cultivated Land Use in China

Based on Eq. (1), the carbon emissions of cultivated land use in China from 1991 to 2021 are calculated, and the temporal variation characteristics of carbon emissions and growth rate of cultivated land use in China can be obtained (Fig. 2). The results show that the carbon emissions of cultivated land use in China have a rising and then declining trend, increasing from 36.9707 million tons in 1991 to 69.7625 million tons in 2021, with an average annual increase of 1.1273 million tons and an average annual growth rate of 2.23%; which may be due to the increase in the input of agricultural materials such as fertilizers, pesticides, agricultural films, and agricultural machinery or the degree of soil destruction caused by agricultural chemical and mechanization, together increasing carbon emissions of cultivated land use. Among them, the average annual growth rates of fertilizer, pesticide, agricultural film, agricultural machinery, tillage, and agricultural irrigation are 2.12%, 1.78%, 3.86%, 0.56%, 0.41%, and 1.24%, respectively. However, the growth rate declined after 2010 and stepped into a negative growth stage in 2016. The total carbon emission of cultivated land use decreased by 3.71% and 4.06% in 2018 and 2019, respectively, indicating that the carbon emission of cultivated land use in China is effectively controlled; this could be due to the continuous practice of the concept of low-carbon green development in agricultural production since the 18th CPC National Congress, since when China's cultivated land use pattern is changing from high-carbon to low-carbon.

The spatial patterns of carbon emissions from cultivated land use in 31 provinces of mainland China in 1991, 2000, 2010, and 2020 can be obtained with the calculation above. In order to compare the variability of carbon emissions of cultivated land use inter-provinces and regions more intuitively, the natural discontinuity method was used to divide carbon emissions into five levels; that is, level 1 has the lowest carbon emissions, and level 5 has the highest carbon emissions; as shown in Fig. 3.

At the provincial level, the provinces with level 1 and level 2 carbon emissions tend to decrease. Nine provinces, including Tibet, Ningxia, and Qinghai, belonged to the level 1 carbon emission region in 1991, and by 2021, two provinces were reduced. The level 2 carbon emission region was reduced from twelve provinces, including Shanxi, Guizhou, Zhejiang, and Fujian, to seven provinces in 2010 (Heilongjiang, Jilin, Liaoning, and Shaanxi provinces changed from level 2 carbon emission region to level 3 carbon emission region), and to six provinces in 2021 (Gansu Province turns to level 3 carbon emission region). From 1991 to 2021, two new provinces, Henan and Shandong, were added as Level 5 carbon emission provinces, and five new provinces, Hebei, Hubei, Anhui, Jiangsu, and Xinjiang, were added as Level 4 carbon emission provinces.

The above conclusions show that the traditional major grain-producing provinces are dominated by planting and highly dependent on cultivated land. At the same time, more inputs of high-carbon materials such as fertilizers, agricultural films, and pesticides lead to high carbon emissions from cultivated land use. These provinces have be-come the primary source of carbon emissions from cultivated land use, and the inter-provincial differences in carbon emissions tend to expand. At the regional level, the provinces with higher carbon emissions are mainly concentrated in the central and eastern regions, possibly due to the higher degree of intensification of cultivated land use in these regions. Compared with the difference in carbon emissions in different regions in 1991, the difference in carbon emissions in different regions tends to shrink. However, the total carbon emissions show a shift from the characteristics of "western region > northeastern region > eastern region > central region" in 1991, "eastern region > central region > western region > northeastern region" in 2000 and 2010, to "western region > central region > eastern region > northeastern region" in 2021.

In terms of sub-regions, from 1991 to 2021, the average annual carbon emissions from cultivated land use in 13 major grain-producing provinces in China, including Heilongjiang, Henan, Shandong, Anhui, Jilin, and Hebei, were 42.6548 million tons, much higher than the remaining non-major grain-producing provinces of 20.5335 million tons. China should focus on transforming agricultural production methods in major grain-producing areas, widely adopting energy-saving and emission-reduction technologies, and comprehensively improving the utilization efficiency of agricultural materials to realize the carbon emission-reduction of cultivated land use eventually.

3.2. Analysis of carbon emissions driving factors of cultivated land use

Based on the above model and combined with the carbon emissions of cultivated land use in 31 provinces of mainland China measured in the above section, the decomposition results of the carbon emissions driving factors of cultivated land use in China from 1991 to 2021 are shown in Table 5.

Table 5

Carbon emissions' results drove factors of cultivated land use in China from 1991 to 2021(Unit: ton)
Year	Efficiency factor	Structural factor	Economic factor	Labor Factor	Total effect
1991	8832730	-747667	1011563	734956	9831582
1992	-1814472	-869266	4174080	-270827	1219516
1993	-4589302	-611089	7921847	-888922	1832535
1994	-9682124	-1499943	15279066	-1001073	3095925
1995	-11070305	360502	13918777	-8250	3200724
1996	-3179772	-601793	7477055	-527184	3168307
1997	1056229	-1312960	1396668	227769	1367706
1998	-35884	1579160	-700894	571680	1414062
1999	1627134	-319370	-503713	293203	1097253
2000	1293008	-1720434	402167	434562	409302
2001	-851775	-369669	3146705	-395541	1529720
2002	-494420	-723322	3417679	-843566	1356371
2003	1318900	-5075577	5981659	-1242980	982002
2004	-9518805	72453	13591369	-1334254	2810762
2005	-2665699	-533973	6703349	-1493805	2009873
2006	-3749637	1368768	5804205	-1112761	2310575
2007	-6631067	-474849	11032086	-1459335	2466835
2008	-7026360	-3028144	12495568	-556932	1884132
2009	-4189474	3021196	4581000	-1300876	2111845
2010	-11586359	3373529	11460010	-1039741	2207439
2011	-7446817	-2256730	12543434	-723190	2116698
2012	-6803883	1096919	8826276	-1302256	1817056
2013	-6040591	676754	8177003	-1573803	1239364
2014	-3661692	674997	5315846	-1054695	1274456
2015	-3492435	391661	4730439	-1335856	293809
2016	-2385624	-1570806	4134847	-733388	-554971
2017	465551	-194719	-168703	-2014225	-1912096
2018	-7485056	1526846	5427731	-2388278	-2918756
2019	-8242236	-1338249	9576532	-3068993	-3072946
2020	-8065311	-1616310	30479755	-22608359	-1810224
2021	-7278920	1408633	7547625	-2703748	-1026410
Total	-123394468	-9313450	225181033	-50720667	41752448

It can be seen from Table 5 that the efficiency factor, structural factor, and agricultural labor factor have promoted the carbon emission reduction of cultivated land use to varying degrees. In descending order, the effects of carbon reduction from cultivated land use are structural factor < labor factor < efficiency factor. Specifically, the structural factor cumulatively achieved 17.11% (9.3135 million tons) of carbon reduction, while the labor factor achieved 93.21% (50.7207 million tons) of carbon reduction. The efficiency factor is the most critical in inhibiting carbon emissions from cultivated land use, which achieves 226.75% (123.394 million tons) of carbon emission reduction. The rapid development of the agricultural economy is the most critical factor leading to increased carbon emissions from cultivated land use in China. Taking 1991 as the base year, the economic factor between 1991 and 2021 triggered a cumulative carbon increment of 413.80% (225.181 million tons).

Cultivated land use ensures national food security and supports ecological construction. The steady development of agriculture can provide strong support for China's economic and social development, and it is of great significance to cope with various risk challenges and maintain the overall situation of reform, development, and stability. Under the guidance of China's "30.60 dual carbon" target, developing low-carbon agriculture is imperative. However, balancing carbon reduction, food security, and agricultural economic development is necessary. The strategy of abandoning agricultural economic development, which matters to food security, to promote carbon reduction is infeasible. Therefore, to a certain extent, agricultural economic development will remain dominant in China's cultivated land use carbon emissions.

The rapid improvement of the agricultural economic level has led to the continuous increase of carbon emissions from cultivated land use in China. However, it is obvious that based on the fundamental role of agriculture in the national economy, steadily promoting agricultural development and increasing farmers' income will still be the fundamental strategy that China will adhere to for a considerable period. Therefore, the emission reduction model that abandons agricultural growth to promote agricultural carbon emission reduction will not be practical, and agricultural economic factors will still be the dominant factor of carbon emissions from cultivated land use in China. Under the guidance of China's "30.60 dual carbon” target, it is imperative to develop low-carbon agriculture. In order to grasp the balance between carbon reduction and economic development, it is crucial to change agricultural production methods to achieve carbon reduction in agriculture.

3.3. Analysis of spatial-temporal characteristics of net carbon sink of cultivated land use

3.3.1. Temporal evolution of net carbon sink of cultivated land use

Based on the accounting of carbon emissions and carbon absorption from cultivated land use in China's 31 provinces from 1991 to 2021, showing that carbon absorption is significantly higher than carbon emissions. Hence, the difference between the two measures is the net carbon sink. See Appendix 1 for an intuitive view of the timing changes.

During the 31 years, the annual average net carbon sink of cultivated land use was 507.2714 million tons. The base of carbon absorption was significantly higher than that of carbon emissions, while the annual average growth rate of carbon emission was slightly higher than that of carbon absorption. Therefore, the net carbon sink steadily increased, and the carbon sink effect continued to increase. In 1991, the net carbon sink of cultivated land use was 404.595 million tons, reaching 666.8488 million tons in 2021, equivalent to 2.445 billion tons of carbon dioxide equivalent. It can offset nearly a quarter of the country's total carbon emissions in that year, showing China's cultivated land use has a carbon reduction potential, and cultivated land use nationwide has a positive externality in the greenhouse gas emission reduction.

At the same time, the net carbon sink of cultivated land use in China exhibits a phased evolution law. According to the temporal characteristics of the total net carbon sink, the development process of net carbon sink can be divided into three stages: fluctuating growth (1991–2003), rapid growth (2004–2015), and steady growth (2016–2021). In the first stage, the net carbon sink of cultivated land use fluctuated, and there was a significant decline from 1999 to 2003. The academic community has recognized the reasons for the fluctuation in this stage, that is, low-efficiency and low-level production have made agricultural development a bottleneck, the scale of crop planting fluctuates significantly from year to year, the enthusiasm for agricultural materials input is low, and the carbon emission and carbon absorption of cultivated land use also fluctuate. The rapid growth of net carbon sinks characterizes the second stage. Since 2004, China has continuously promulgated Central Guidance No.1, stimulating enthusiasm for agricultural production. The density of agricultural inputs has been increasing, the scale of crop cultivation has been accelerating, carbon absorption has reached a new high, and carbon emissions peaked in 2015. The coexistence of high carbon emissions and sinks has become increasingly prominent. At this stage, the characteristics of China's extensive agricultural development driven by agricultural capital investment are becoming increasingly evident. Since 2016, carbon emissions have gradually decreased, while carbon absorption has remained high. The difference between the two has continued to expand, resulting in the continued growth of net carbon sinks, although the growth rate has slowed down from the previous stage. China's cultivated land use system has always been in a carbon surplus, and the carbon sink function is still increasing, making a valuable contribution to realizing the "dual carbon" commitment.

3.3.2. Spatial distribution pattern of net carbon sink of cultivated land use in China

In order to intuitively describe the spatial pattern of net carbon sink distribution of cultivated land use, the spatial distribution map (Fig. 4) was drawn based on the net carbon sink values in 1991, 2000, 2010, and 2021 to reflect the overall situation of cultivated land use in China from 1991 to 2021.

Over time, the carbon absorption of cultivated land use has increased in a few provinces, the carbon emission has increased first and then decreased, and the net carbon sink has maintained an overall upward trend. In 1991, only Shandong province's net carbon sink was higher than 40 million tons, the net carbon sink of Henan and Sichuan provinces was in the range of 30–40 million tons, and the net carbon sink of Jiangsu, Hunan, Guangdong, and Hebei provinces was in the range of 20–30 million tons. By 2000, the net carbon sink of Henan province was more than 40 million tons. The increase and decrease of net carbon sink volume vary among provinces, but the whole country's total net carbon sink volume still maintains a net growth. By 2010, the net carbon sink volume has increased in most regions, except for provinces such as Shanghai, Beijing, Zhejiang, and Fujian, where the net carbon sink volume has decreased. The net carbon sink of Henan Province is higher than 50 million tons. In addition, the net carbon sink of Heilongjiang, Shandong, and Guangxi provinces has reached 40–50 million tons. Sichuan, Hunan, Anhui, and eight other provinces lie 20–30 million tons, and the net carbon sink of the remaining 19 provinces is less than 20 million tons. By 2021, the net carbon sink of each province has jumped significantly. The net carbon sink of Heilongjiang, Henan, and Shandong provinces is more than 50 million tons. Heilongjiang ranks first in the country with 70.5465 million tons. Guangxi is 40–50 million tons, seven provinces, including Xinjiang, Inner Mongolia, Jilin, and Sichuan, rose to 30–40 million tons, and the net carbon sinks of the remaining 20 provinces are less than 30 million tons. The number of provinces in the high-value range of net carbon sinks has been increasing. The absolute level has also increased, indicating that the national cultivated land use pattern is slowly transforming from high carbon to low carbon.

The net carbon sink of cultivated land use in the major grain-producing areas was significantly higher than in the non-major grain-producing areas. Although the carbon emissions of cultivated land use in main grain-producing areas are higher than those in other provinces, they can still show significant positive externalities of greenhouse gas emission reduction by their strong crop carbon sink system in the short term. From 1991 to 2021, the average annual net carbon sink of cultivated land use in each province was the major grain-producing area (27.525 million tons) > the balanced grain production and marketing area (10.521 million tons) > the major grain-marketing area (4.816 million tons). The net carbon sink of cultivated land use in each region decreased exponentially. Therefore, the carbon sink effect of the cultivated land use system should be emphasized and brought into good use to guarantee crop cultivation in major grain-producing regions.

Along with the low-carbon transformation of cultivated land use in China, the net carbon sink of cultivated land use is characterized by a scattered distribution with high value in agricultural provinces and a clustered distribution with low value at the national level. By observing the average annual net carbon sink, Henan dominates among all provinces with 48.85371 million tons, followed by Shandong. Heilongjiang and Guangxi provinces are 30–40 million tons, while Hebei, Jilin, Jiangsu, Anhui, Hubei, Hunan, and Sichuan are 20–30 million tons. The net carbon sinks of the remaining provinces are less than 20 million tons. The comparison of carbon emission and carbon absorption calculation results shows that Heilongjiang, Guangxi, and Sichuan have always maintained high net carbon sinks. Because of the large scale of local agricultural production, the carbon sequestration of crops is high, and its production mode has gradually transformed from agricultural capital-driven to technology-driven. The dual characteristics of high carbon sinks and low carbon emissions result in the above regions maintaining high net carbon sinks. Henan, Shandong, and Hunan have the characteristics of both high carbon emission and high carbon sink. The carbon absorption of their crop production system is high. However, they are highly dependent on high-carbon emission agricultural materials such as fertilizers and pesticides, resulting in carbon emissions far exceeding other major grain-producing provinces. The cultivated land volume in Qinghai and Tibet is small, making it challenging to have outstanding performance in net carbon sink. In addition, the development of Shanghai and Beijing is not focused on agricultural production, which shows a "three-low" pattern of carbon emission, carbon absorption, and net carbon sink.

3.4. Net carbon sink of cultivated land use and grain yield

3.4.1. Characteristics of the relationship between net carbon sink of cultivated land use and grain yield at the provincial level of China

In order to comprehend the coordination degree of the relationship between ecology and yield of cultivated land use systems at the provincial level, the two indicators of net carbon sink of cultivated land use and grain yield are placed in the same coordinate axis. Based on the mean value of the two indicators from 1991 to 2021, the 31 provinces are divided into four categories: high-carbon sink high-yield (quadrant Ⅰ), high-carbon sink low-yield (quadrant Ⅱ), low-carbon sink low-yield (quadrant Ⅲ), low-carbon sink high-yield (quadrant Ⅳ), as shown in Fig. 5.

Figure 5 shows that the high-carbon sink high-yield type indicates that the use of cultivated land balances low carbon and increased production; and is the ideal relationship between net carbon sinks and agricultural production, with eleven provinces such as Henan, Shandong, and Heilongjiang located in this quadrant, all of which are major grain-producing provinces. These provinces have a large scale of agricultural production and a wide area of cultivated land, which not only brings high carbon sinks but also guarantees grain yield. The high-carbon sink low-yield type includes Guangxi, Xinjiang, and Yunnan provinces, where grain yield is not prominent. However, these provinces focus on resource and environmental protection in agricultural production, eventually showing more significant ecological advantages. The low-carbon sink high-yield type includes Liaoning and Jiangxi provinces, whose carbon emissions have exceeded the appropriate state under the corresponding production scale due to the high intensity of agricultural materials use and inappropriate waste disposal methods in cultivated land use; therefore, as one of the major grain-producing provinces, Liaoning and Jiangxi are critical for reducing carbon sources and increasing carbon sinks. The low-carbon sink low-yield type includes fifteen provinces, such as Zhejiang and Shanghai, which do not belong to the main agricultural-producing provinces. Their exploration of low-carbon agricultural technology, green planting methods, and supporting policies is insufficient, resulting in net carbon sinks and grain yields below average.

3.4.2. Tapio coupling index of net carbon sink of cultivated land use and grain yield at China’s provincial level

The Tapio coupling status was measured based on the evolution of the net carbon sink change rate of cultivated land and grain yield in China from 1991 to 2021 (Fig. 6 Panel A). During the study period, the scattering points of the coupling index are primarily located in quadrant Ⅰ, reflecting the Growth coupling. In addition, the negative growth of net carbon sinks and the positive growth of grain yield in 1994 and 2003 showed an ecologically weak decoupling. From 1992 to 2002 (except 1994), the growth rate of the two indicators was relatively consistent, showing a yield-dominant coupling. In 2007 and 2008, the relationship between the two was eco-dominant coupling.

The Tapio coupling index was measured from 1991 to 2021 to determine the degree of coupling between the rate of change of net carbon sink of cultivated land use and grain yield in each province. The corresponding quadrant diagram is shown in Fig. 6 Panel B. Observing the coupling pattern, and the relationship types are more diversified among provinces. Most provinces are located in the quadrant Ⅰ, where the net carbon sink of cultivated land use and grain yield are initially coordinated and in an initial equilibrium state. The five provinces of Shandong, Shaanxi, Ningxia, Guizhou, and Tibet are yield-dominant coupling. Anhui, Henan, Heilongjiang, and the other twelve provinces belong to the growth coupling type. Among them, the net carbon sink and grain yield increase in Inner Mongolia is 320.45% and 300.66%, respectively, which has a significant exemplary role among provinces. Liaoning, Guangxi, Hubei, Hunan, and Xinjiang provinces show an eco-dominant coupling, but the increase of net carbon sink in each province was not prominent. While Fujian, Hainan, and Chongqing provinces show an eco-dominant negative coupling. In addition, Beijing, Shanghai, Zhejiang, and Guangdong belong to the decay coupling, and their net carbon sink of cultivated land use and grain yield has declined, which is to some extent related to the continuous reduction of the overall scale of agricultural production in these provinces.

The findings show that:

(1) From 1991 to 2021, the carbon emissions of cultivated land use in China showed an upward first and then downward trend, increasing from 36.9707 million tons in 1991 to 69.7625 million tons in 2021. However, the growth rate declined since 2010 and turned negative after 2016. Carbon emissions are higher in traditional agricultural provinces and lower in provinces with sparse cultivated land. While the inter-provincial differences in carbon emissions tend to expand, the inter-regional differences tend to shrink. Among the four factors influencing carbon emissions of cultivated land use, the efficiency factor has the most significant positive effect on the carbon emission reduction of cultivated land use, and the economic factor has the most significant negative effect. The agricultural economic development factor will continue to dominate carbon increment from cultivated land in China in the foreseeable future.

(2) China's cultivated land use system has a substantial carbon sink effect, showing a state of carbon surplus, and the net carbon sink of cultivated land use is generally on the rise. It has gone through three stages: fluctuating growth (1991–2003), rapid growth (2004–2015), and steady growth (2016–2021). From the perspective of spatial distribution, the net carbon sink shows a scattered distribution of high-value in agricultural provinces and a clustered distribution of low-value at the national level.

(3) Based on the characteristics of net carbon sink of cultivated land use and grain yield in each province, 31 provinces were divided into four types: high-carbon sink high-yield (eleven provinces including Henan, Shandong, and Heilongjiang), high-carbon sink low-yield (Guangxi, Yunnan, and Xinjiang), low-carbon sink low-yield (fifteen provinces including Zhejiang and Shanghai), and low-carbon sink high-yield (Liaoning and Jiangxi). At the national scale, the net carbon sink of cultivated land use and grain yield are growth or yield-dominant coupling in most years. The types of coupling at the provincial level are varied but still dominated by growth coupling. Furthermore, most provinces have a balanced relationship between the increased net carbon sink of cultivated land use and grain yield increase.

Based on the calculation of the net carbon sink of cultivated land use in 31 provinces of mainland China from 1991 to 2021, this paper analyzes the driving factors of carbon emission of cultivated land use, describes the spatial-temporal characteristics of carbon emission and net carbon sink, and explores the relationship between net carbon sink of cultivated land use and grain yield using the expanded Tapio coupling index. This study has improved the existing research on the accounting of net carbon sinks in cultivated land use and enriched the research on the relationship between net carbon sinks of cultivated land use and grain yield from an "all-encompassing approach to food." It can provide data reference in the cultivated land use field to realize the "30.60 dual carbon" goal and the green and high-quality development of agriculture in China.

The study found that from 1991 to 2021, the carbon emissions of cultivated land use in China showed an upward first and then downward trend and peaked in 2015, consistent with the relevant literature [1,2]. Among the four influencing factors of cultivated land use carbon emissions, efficiency factor, structural factor, and agricultural labor factor have significantly promoted the carbon emission reduction of cultivated land use. The efficiency factor has the greatest positive effect on the carbon emission reduction of cultivated land use, with a cumulative carbon emission reduction of 226.75% (123.394 million tons). The rapid development of the agricultural economy is the most important factor leading to increased carbon emissions from cultivated land in China. In the past 31 years, the economic factor has cumulatively triggered 413.80% (225.181 million tons) of carbon increment. To promote the green and sustainable development of agriculture, China should fully play the role of efficiency factors and change the mode of agricultural production. All regions should actively optimize the structure of the agricultural industry, further optimize the structure of the planting industry, and reduce the scale of planting crops with high resource consumption and large chemical investments. To ensure food security, China should promote the emission reduction of cultivated land use in each province by focus and batch, implement differentiated emission reduction policies, choose a low-carbon agricultural development path considering local endowments, and take the road of low-carbon agricultural development.

In addition, the results show that China's cultivated land system has a strong carbon sink effect, showing a state of carbon surplus, and the net carbon sink of cultivated land use is generally on the rise, consistent with Tian et al. (2015). The difference in the annual average scale of carbon emission, carbon sequestration, and net carbon sink measured in the two studies is due to the difference in accounting scope and study period. Although the process of cultivated land use in China involves many greenhouse gas emission sources, it can still show significant positive externalities in short-term greenhouse gas emission reduction under its strong crop carbon sink system. Accordingly, the government should formulate reasonable cultivated land protection policies and play a key role in ensuring national food security and supporting ecological construction. China should guard the red line of cultivated land protection of 120 million hm² and take adequate measures to intervene in the trends of "non-agriculturalization" and "non-grain" of cultivated land use so that the cultivated land system can continue to contribute to the realization of China's “30.60 dual carbon” goal and the green and high-quality development of agriculture. However, it is worth noting that although crops have significant short-term carbon sink benefits through photosynthetic uptake of CO₂ during their growth cycle, their long-term impact on the carbon cycle is still weak, as the organic carbon formed will be returned to the atmosphere soon through consumption as food or industrial raw materials. Due to the uncertainty of accounting coefficients, consumption cycles, and consumption ratios, this part of carbon emissions cannot be accounted for temporarily.

Wu et al. (2022) explored the coupling coordination degree between net carbon sink and agricultural output value in terms of the relationship between the carbon effect and grain yield. They found that the relationship between the economy and ecology of cultivated land use has changed from overall imbalance to preliminary balance, with a certain gap between the realization of overall coordination and growth coupling. It is consistent with the conclusion of this paper. Different from related research, this paper uses the extended Tapio coupling index to measure the net carbon sink and grain yield of cultivated land use each year and finds that the net carbon sink of cultivated land use and grain yield are growth or yield-dominant coupling in most years at the national scale. The types of coupling at the provincial level are varied. However, most provinces have a balanced relationship between the increased net carbon sink of cultivated land use and grain yield increase. Therefore, it is necessary to encourage the major carbon emission provinces to suppress carbon sources and prioritize carbon sinks under the “all-encompassing approach to food” strategy. For example, for provinces such as Shaanxi and Guizhou, which are on the verge of the junction edge between yield-dominant coupling and ecologically weak decoupling, China needs to be alert to the situation in food production and the ecological benefits of farmland conflict. Provinces such as Henan, Anhui, and Heilongjiang, which have achieved growth coupling, should be encouraged to optimize their cultivated land use patterns and apply advanced production technologies. Although major agricultural provinces such as Hunan, Shandong, and Guangxi have large emission bases, the relationship between grain production and the ecological environment has been initially coordinated. The coupling state of these provinces can be further optimized by optimizing the structure of cultivated land use and strengthening the application of low-carbon technologies.

There are still some limitations in this study. The research limits the accounting scope to the cultivated land use system without considering the long-term impact after the removal of crop carbon. In addition, indicators such as crop economic coefficient in the crop carbon sequestration accounting are generally relatively stable, but these indicators may also change when the crop varieties are updated. This uncertainty will have a certain impact on the accuracy of the time-series accounting of crop carbon sequestration. With the future update and improvement of relevant accounting coefficients, a more accurate estimation of the carbon source/sink of cultivated land use can be carried out in the next step. Besides, the scale of the study is defined on the whole and provincial areas of China. Although it can provide a reference for the overall judgment of the net carbon effect of cultivated land use, it is still relatively macro. The follow-up research can be accurate at the city and state levels, leading to more detailed conclusions and targeted recommendations.

Supplementary Materials: Not applicable.

Author Contributions: Conceptualization, Q. Wang and L. Yao; methodology, Q. Wang; software, Q. Wang; validation, L. Yao, Y. Zhang. and Q. Wang.; formal analysis, Q. Wang; investigation, Y. Zhang; resources, Y. Zhang; data curation, Q. Wang; writing—original draft preparation, Q. Wang and L. Yao; writing—review and editing, L. Yao.; visualization, Q. Wang; supervision, L. Yao; project administration, L. Yao; funding acquisition, L. Yao All authors have read and agreed to the published version of the manuscript.

Funding: This research was funded by Shaanxi Natural Science funding, grant number: 2023-JC-QN-0801.

Institutional Review Board Statement: Not applicable.

Data Availability Statement: The data presented in this study are available in this manuscript.

Acknowledgments: Thanks to Shaanxi Natural Science funding and Northwest A&F University for supporting this research.

Conflicts of Interest: The authors declare no conflict of interest.

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\(\text{△}{\text{C}}_{\text{AE }}\text{= ∑}\text{γ}\left(\text{ln}{\text{AE}}_{\text{t}}\text{-}\text{ln}{\text{AE}}_{\text{0}}\right)\)	(4)
\(\text{△}{\text{C}}_{\text{AS}}\text{ = ∑}\text{γ}\left(\text{ln}{\text{AS}}_{\text{t}}\text{-}\text{ln}{\text{AS}}_{\text{0}}\right)\)	(5)
\(\text{△}{\text{C}}_{\text{EL}}\text{= ∑}\text{γ}\left(\text{ln}{\text{EL}}_{\text{t}}\text{-}\text{ln}{\text{EL}}_{\text{0}}\right)\)	(6)
\(\text{△}{\text{C}}_{\text{P}}\text{ = ∑}\text{γ}\left(\text{ln}{\text{P}}_{\text{t}}\text{-}\text{ln}{\text{P}}_{\text{0}}\right)\)	(7)
where, \(\text{γ}\text{ = }\frac{{\text{C}}_{\text{t}} \text{- }{\text{ C}}_{\text{0}}}{\text{ln}{\text{C}}_{\text{t }}\text{-}\text{ ln}{\text{C}}_{\text{0}}}\).

Research on the Spatial-Temporal Coupling Characteristics between China's Net Carbon Sink of Cultivated Land Use and Grain Yield

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Abstract

Figures

Highlights

1. Introduction

2. Data and Methods

2.1. Calculation of carbon emissions of cultivated land use

2.2. Decomposition of carbon emissions driving factors of cultivated land use

2.3. Carbon absorption calculation of cultivated land use

2.4. Calculation of net carbon sink of cultivated land use

2.5. Improved coupling index based on Tapio decoupling model

2.6. Data source

3. Results

3.1. Spatial-temporal Characteristics of Carbon Emissions of Cultivated Land Use in China

3.2. Analysis of carbon emissions driving factors of cultivated land use

3.3. Analysis of spatial-temporal characteristics of net carbon sink of cultivated land use

3.3.1. Temporal evolution of net carbon sink of cultivated land use

3.3.2. Spatial distribution pattern of net carbon sink of cultivated land use in China

3.4. Net carbon sink of cultivated land use and grain yield

4. Conclusion

5. Discussion

Declarations

References

Additional Declarations

Supplementary Files

Status:

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Carbon Source	Formula	Carbon Source Input/Unit	Carbon Emission Coefficient	Reference
Fertilizer	\({\text{C}}_{\text{f}}\text{ =}{\text{ G}}_{\text{f}}\text{ × A}\)	\({\text{G}}_{\text{f}}\): Fertilizer refining volume/kg	A = 0.896	West et al. (2002)
Pesticide	\({\text{C}}_{\text{p}}\text{ = }{\text{G}}_{\text{p}}\text{ × B}\)	\({\text{G}}_{\text{p}}\): Pesticide usage/kg	B = 4.934	Zhi et al. (2009)
Agricultural film	\({\text{C}}_{\text{m}}\text{ =}{\text{ G}}_{\text{m}}\text{ × D}\)	\({\text{G}}_{\text{m}}\): Agricultural film usage/kg	D = 5.18	Wang et al. (2016)
Agricultural machinery	\({\text{C}}_{\text{e}}\text{ =}{\text{ A}}_{\text{a}}\text{ × E + }{\text{W}}_{\text{e}}\text{ × F}\)	\({\text{A}}_{\text{a}}\): Crop sown area/hm² \({\text{W}}_{\text{e}}\): Total power of agricultural machinery/kw	E = 16.47 F = 0.18	Zhao et al. (2010)
Irrigation	\({\text{C}}_{\text{i}}\text{ =}{\text{ A}}_{\text{i}}\text{ × G}\)	\({\text{A}}_{\text{i}}\): Effective irrigated area / hm²	G = 20.5	Li et al. (2011)
Tillage	\({\text{C}}_{\text{t}}\text{ =}{\text{ A}}_{\text{a}}\text{ × H}\)	\({\text{A}}_{\text{a}}\): Crop sown area/hm²	H = 3.126	Wu et al. (2007)