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Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

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10.1016/j.heliyon.2024.e36292
e36292
Research Article
Effect of water Resource utilization in Poyang lake area on carbon emissions based on decoupling theory
Fu Shuai fushuai1019@126.com
abc⁎
Xu Bingxian a
Peng Yuxin a
Yu Jie a
Feng Yingxiang a
Li Xiuxiang c
Li Lanhai b
a Land Resource Management, School of Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang, 330013, PR China
b Xinjiang Key Laboratory of Water Cycle and Water Utilization in Arid Zone, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urmqi, 830011, PR China
c International commodity Price analysis and Forecast Research Innovation Team, Jiangxi University of Finance and Economics, Nanchang, 330013, PR China
⁎ Corresponding author. Land Resource Management, School of Finance and Public Administration, Jiangxi University of Finance and Economics, Nanchang, 330013, PR China. fushuai1019@126.com
16 8 2024
30 8 2024
16 8 2024
10 16 e3629221 5 2024
9 8 2024
13 8 2024
© 2024 The Authors. Published by Elsevier Ltd.
2024

https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
The utilization of regional water resources has the potential to impact carbon emissions. Maintaining a decoupled relationship between water resources and carbon emissions facilitates harmonious regional development. Understanding the mechanism of their coordination is conducive to achieving the "Double Carbon" goal and control of regional carbon emissions and water resource consumption. This study examines the decoupling relationship between water resource utilization and carbon emissions in Poyang Lake area, China, employing the Tapio decoupling model and the LMDI(logarithmic mean divisia index) decomposition model. The results indicate that carbon emissions in Poyang Lake area exhibited a gradual increase, accompanied by an annual growth rate of 5.99 %. The water supply exhibited a slow expansion. They have exhibited state of affairs strong negative decoupling and expansive negative decoupling over the past 15 years. Moreover, this situation is most acute and worsening in the secondary industry. The water use structure effect and water economic benefit effect are the primary factors affecting carbon emission increases, contributing 57.93 % and 65.66 %, respectively. Carbon emissions intensity is the largest inhibiting factor, which accounts for a maximum contribution of 42.96 %. The order of potency of the driving factors is as follows: water economic benefit > carbon emission intensity > water use structure > water use efficiency. In summary, this research recognised the enhancement of the water economic efficiency index not only facilitates the decoupling phenomenon but also improves the water-carbon relationship, especially in the secondary industry. It serves as a compelling illustration of the significance of elucidating the interrelationship between regional water and carbon dynamics, and charting the course for the formulation of regional policies that would facilitate the advancement of environmentally conscious and carbon-neutral development, as well as water conservation.

Keywords

Water resources
Carbon emission
Decoupling relationship
Poyang lake area
Driving factors
==== Body
pmc1 Introduction

In the current severe situation of global climate change, the influence of greenhouse gases, especially carbon dioxide (CO2), on climate change has been reiterated, such as the “United Nations Framework Convention on Climate Change” in 1992 [1], the “Kyoto Protocol to the United Nations Framework Convention on Climate Change” in 1997 [2], and the “Paris Agreement” in 2015 [3]. How to reduce CO2 emissions, countries around the world are striving to find an efficient and reasonable path. For developing countries, seeking carbon reduction on the basis of ensuring normal development within the country or region is undoubtedly a daunting challenge. As the world's largest developing country, a major carbon emitter and a responsible leader in global environmental governance, China attaches great importance to the dual carbon issue and has adopted green economic growth as one of the five new concepts of economic development [4,5]. In 2020, China proposed a significant strategic deployment of the "Double Carbon" goal, which involved adjusting its energy structure and economic development. To accomplish this challenging task, water resources, serving as a clean energy source, play a vital role [6,7]. The distribution and utilization of water resources impact ecological environment development as well as carbon sequestration [8]. Additionally, the advancement, application, and preservation of water resource brought about by regional economic growth alters the structure, efficiency and economic benefits derived from water utilization, which in turn affects carbon emissions [9]. Consequently, to resolve the apparent contradiction between economic growth and low-carbon emission and to facilitate the integrated advancement of regional water and carbon dynamics, it is imperative to elucidate the interconnections between the water utilization and carbon emissions.

A substantial body of research has been conducted in recent years on the correlation between water use and carbon emissions, primarily in the context of energy. Including: the relationship between urban water systems and carbon emissions [10], the carbon reduction benefits of wastewater regeneration and value-added utilization [11], and the correlation between water energy consumption and carbon emissions under different irrigation modes [12]. Human social development is the main reason for water consumption as well as carbon emissions. To analyze the effects of socioeconomic development on water and carbon emissions, the decoupling theory is introduced. Decoupling theory aims to explore the correlation of environmental damage and economic growth [13]. In light of these considerations, Tapio [14] developed the Tapio elastic decoupling theoretical model, which has been extensively utilized in the context of water utilization [15], carbon emissions [16], economic development [17], etc. Zhu et al. [18] analyzed the relationship between GDP and water consumption in Yunnan and Guizhou province by decoupling elasticity model, found that the decoupling status is suboptimal. Ji et al. [8] analyzed the water-carbon relationship of the Qin River basin by the theory of decoupling and found that the water-carbon relationship of the region was poor overall but in a phase of gradual coordination. In addition, there is also research on the decoupling relationship between yield, water resource consumption, and carbon emissions in crop production [19], as well as the coupling and coordination relationship between water and economy in typical arid areas of northwest China [20]. To better understand the primary factors influencing the decoupling status and to explore effective adjustment strategies, driving effect decomposition is a widely applied method. The methodologies employed in such studies include the LMDI decomposition model [21], the IPAT equation [22], the STRIPAT model [23], the Environmental Kuznets Curve [24], the VAR model [25], and the partial least squares method [26]. Among them, the LMDI model is widely used to research the influences for its complete decomposition, no residuals, and allowing data to contain zero values [27,28]. Jiang et al. [29] analyses the spatial and temporal features of the decoupling state and its driving factors for the industry water supply in Beijing-Tianjin-Hebei region, China, indicating that the decoupling status is favorable and stable, and the technical effect is the key primary determinant of decoupling status. Li et al. [30] applied decoupling theory and the LMDI model to study the decoupling connection between economic growth and water resource consumption in the five northwestern provinces from 2004 to 2018, found that water intensity is the primary factor driving decoupling. Zhang et al. [31] examine the relation of agricultural water pollution and economic development in the Yangtze River Economic Belt, establishes an LMDI decomposition model to investigate the relation of agricultural ash water footprint and economic development, and the economic level effect exerts a significant positive driving effect. Upon reviewing the aforementioned literature on decoupling theory and the LMDI model, it becomes evident that current research focuses on the relation of carbon emissions and energy [32,33], the economy and water resources [21,34], and water resources and energy [10,35]. A paucity of studies has hitherto addressed regional water-carbon decoupling and the driving forces behind carbon emission decoupling from a water consumption perspective.

Poyang Lake, the largest fresh water lake, is located in the middle of Yangtze River, China. It exhibits a distinctive hydrological phenomenon, known as a "flood area, dry line", which is the result of seasonal influence [36]. Large variations in the water level restrict irrigation water use and the urban water supply, and the Three Gorges Reservoir impoundment exacerbates water stress in the lake [37]. In addition, as an important ecological and economic pioneer area in China, the Poyang Lake area has rapidly developed industries such as energy, chemical, and metallurgy, and has become a pillar industry in the region, which determines the fact that the carbon emission intensity in the region is relatively high. Moreover, studies have demonstrated a notable decline in the region's carbon storage capacity [38]. Concurrently, as the energy and its related sectors expand rapidly, the variations in the utilization of water resources within the region have emerged as a pivotal factor influencing regional economic growth and, subsequently, carbon emissions. Therefore, achieving coordinated development of water and carbon in the Poyang Lake area is of great significance for the construction of the ecological and economic zone in the region and even the achievement of the "dual carbon" goal. At present, most studies have focused on water storage [39,40] and water area change [41,42] in Poyang Lake. Few studies has considered the comprehensive interrelationship between water utilization and carbon emissions. And the driving factors influencing the water utilization and the change in carbon emissions in the Poyang Lake area under social development remain unclear. So we collect the data pertaining to energy consumption and water utilization from 2007 to 2021 in Poyang Lake area. The Tapio and LMDI models were employed to investigate the coordination status, mechanism of action, and identification of carbon emission driving factors between them in the region. The aim of this research is to provide basic support for subsequent research in the Poyang Lake region, as well as reference for achieving the "dual carbon" goals and coordinated development of water and carbon in the region.

2 Materials and methods

2.1 Study area

Poyang Lake lies in southeastern China, north of Jiangxi Province, which is an important large-scale lake within China (Fig. 1). It undertakes various ecological functions, including flood control and storage, climate regulation, the degradation of pollution and biodiversity protection [43]. As it is located in the subtropical humid monsoon zone, this area has a mild climate and abundant rainfall. The annual precipitation is 1542 mm, and the annual temperature is 16.5–17.8 °C [44]. The total area of the Poyang Lake area is 21744.33 km2, representing 13.03 % of the total area of Jiangxi Province(calculated by GIS). The total water resources in Poyang Lake area are 21.826 × 108 m3, and some studies show that the amount of carbon emissions in the area surrounding Poyang Lake has increased rapidly over the past few decades, with a growth rate of 337.39 % [45].Fig. 1 Geographical location and overview of the Poyang Lake area.

Fig. 1

2.2 Data sources

The 2007–2021 energy consumption data and GDP of the Poyang Lake area are from the ‘China Energy Statistics Yearbook’(https://www.stats.gov.cn/) and the ‘Jiangxi Statistics Yearbook’(https://www.jiangxi.gov.cn/col/col386/index.html); water utilization data are from the ‘Jiangxi Water Resources Bulletin’(http://slt.jiangxi.gov.cn/). Total carbon emissions and carbon emissions in various industries, total water supply, water supply volume, total GDP, and GDP of each industry of 19 counties (districts) in the study area from 2007 to 2021 are calculated by the collected data. For missing county-level data in some years, we obtained estimates by using city-level data and the average magnitude of change in the same county (district) in the previous and subsequent years to obtain. Additionally, the same approach was applied to ensure the completeness and accuracy of the dataset, taking into account the availability of information at both the city and neighboring year level.

2.3 Carbon emission estimation

The methodology employed by the Intergovernmental Panel on Climate Change (IPCC) for the estimation of carbon emissions arising from energy consumption ‘Guidelines for National Greenhouse Gas Inventories’ [46,47] is used in the study, with the following formula:(1) C=(k1a∑j=12EC1,j+k2b∑j=37EC2,j+k3cEC3,8+k4dEC4,9)×4412

where k1, k2, k3, and k4 represent the respective carbon emission coefficients pertaining to coal, oil, natural gas, and electricity; a. b, c, and d are the converted standard coal coefficients for the four energy sources, 0.7143t/(kw·h), 1.4286t/(kw·h), 1.33t/(kw·h), 0.1229t/(kw·h) respectively; j represents all basic energy projects, including coal, gasoline, crude oil, kerosene, coke, gasoline, natural gas, fuel oil, and electricity; EC1, EC2, EC3, and EC4 are the energy consumption of coal, oil, natural gas, and electricity; the transformation coefficient of 44/12 indicates the ratio of CO2 and C molecular weights. The carbon emission coefficients for each kind of energy are derived from the recommendations of China Development and Reform Commission Energy Research Institute [47], the values of coal, oil, natural gas and electricity are 0.7476, 0.5825, 0.4435 and 0 respectively.

2.4 Decoupling model

Tapio decoupling model integrates two kinds of indices, the total quantity variation and the relative quantity variation [48], which can objectively and accurately measure and analyze decoupling relationships. In this study, Tapio's decoupling analysis theory on the water resource utilization status (W) and carbon emission status (C) was structured. The decoupling index e from the base year to a specific period t is defined as follows:(2) e=Ct−C0C0Wt−W0W0

where Ct and Wt are are carbon emissions and supply of water for the period t, respectively, and C0 and W0 are the carbon emissions and water supply for the baseline period, respectively. The decoupling index e can be distinguished into 8 decoupling states, as shown in Table 1.Table 1 Classification of decoupling relationships between carbon emissions and water resource utilization.

Table 1Decoupling type	Decoupling state	ΔC	ΔW	e	
Coupling	Expansive coupling (EC)	>0	>0	[0.8,1.2)	
Recessive coupling (RC)	<0	<0	[0.8,1.2)	
Decoupling	Strong decoupling (SD)	<0	>0	(-∞,0)	
Weak decoupling (WD)	>0	>0	[0,0.8)	
Recessive decoupling (RD)	<0	<0	[1.2,+∞)	
Negative decoupling	Strong negative decoupling (SND)	>0	<0	(-∞,0)	
Weak negative decoupling (WND)	<0	<0	[0,0.8)	
Expansive negative decoupling (END)	>0	>0	[1.2,+∞)	

2.5 LMDI model

The LMDI decomposition model and Kaya identity permit the decomposition of carbon emissions into the following components:(3) C=∑i=1Ci=∑i=1W•WiW•GDPiWi•CiGDPi

(4) wi=WiW,gi=GDPiWi,ci=CiGDPi

where C is carbon emissions, W is total water supply, and i = 1, 2, and 3 represent the primary, secondary, and tertiary industries, respectively. wi represents the structure of water utilization, gi represents the water economic benefit, and ci represents the carbon emissions intensity.

According to the LMDI addition model provided by Ang [49], the formula for calculating carbon emissions from a given base year to any subsequent year is as follows:(5) Ct−C0=ΔC=Δs+Δw+Δg+Δc

where Δs represents the change in carbon emissions caused by water supply, defined as the water resource use effect; Δw represents the change in carbon emissions caused by water supply structure, defined as the water use structure effect; Δg represents the change in carbon emissions caused by water use economic benefits, defined as the water economic benefit effect; and Δc represents the change in carbon emissions caused by changes in GDP, defined as the carbon emission intensity effect. Each indicator can be calculated using equations (6), (7), (8), (9):(6) Δs=∑i=1Ci,t−Ci,0lnCi,t−lnCi,0•lnsi,tsi,0

(7) Δw=∑i=1Ci,t−Ci,0lnCi,t−lnCi,0•lnwi,twi,0

(8) Δg=∑i=1Ci,t−Ci,0lnCi,t−lnCi,0•lngi,tgi,0

(9) Δc=∑i=1Ci,t−Ci,0lnCi,t−lnCi,0•lnci,tci,0

Coupling with Eq. (2) and Eq. (5), it can be obtained that:e=(Ct−C0)/C0ΔW/W0=(Δs+Δw+Δg+Δc)/C0ΔW/W0=ΔsC0+ΔwC0+ΔgC0+ΔcC0ΔW/W0=(st−s0)/C0ΔW/W0+(wt−w0)/C0ΔW/W0+(gt−g0)/C0ΔW/W0+(ct−c0)/C0ΔW/W0

(10) =e1+e2+e3+e4

where the carbon emissions and water resource utilization decoupling index is decomposed into four types of decoupling indices: the water resource use index (e1), water use structure index (e2), water economic benefit index (e3), and carbon emission intensity index (e4).

3 Results

3.1 Characteristics of carbon emissions and water resource utilization in Poyang lake area

The carbon emissions from 2007 to 2021 in Poyang Lake area are calculated by equation (1), and the results are presented in Fig. 2. The overall carbon emissions in the Poyang Lake area show an upward trend and are relatively stable, increasing from 32.88 × 106 t in 2007 to 72.86 × 106 t in 2021, with an average annual growth rate of 5.99 %. The total water supply fluctuates significantly and increases slowly overall, from 48.02 × 109 m3 in 2007 to 51.93 × 109 m3 in 2021. From the point of view of carbon emissions in different industries, the secondary industry accounts for over 75 % of the total emissions, which is much higher than the sum of the primary and tertiary industries, and its trend of change is similar with that of the total carbon emissions. There has been no discernible change in carbon emissions from the primary industry, while the overall carbon emissions from the tertiary industry have increased, albeit at a relatively slow rate. With regards to water supply, the primary industry makes up the largest share, approximately 65 %, with fluctuations similar of the total water supply and no significant upward or downward trend. The water supply of the secondary industry shows an inverted U-shaped change, showing a tendency of first rising and then declining, which is closely associated with the development of industry in this region. The changes in water supply of the secondary and tertiary sectors were relatively minor. The secondary sector consistently supplied more water than the tertiary sector, with the exception of 2009 and 2020. And the water supply of tertiary industry is gradually exceed that of secondary industry after 2020. In general, the increase in carbon emissions of this area is relatively stable, while the total water supply fluctuates greatly. These phenomena indicate that the region lacks a comprehensive plan for the sustainable management of water resource. So the region's water-carbon relationship may not be as optimistic as it could be. With the development of tourism and other service industries in the Yangtze River Economic Belt, and the promotion of the status of the canal, the water use of tertiary industry is also gradually promoted [50]. The coordination of water resources among industries must be accelerated, and the optimization of water-use structures to achieve a rational allocation of water resources is of paramount importance for the region's sustainable promotion of harmonious ecological and economic growth [51,52].Fig. 2 Carbon emission and water resource utilization by industry in Poyang Lake area, 2007–2021.

Fig. 2

3.2 Decoupling of water resources utilization and carbon emission in Poyang lake area

According to the Tapio model, Fig. 3 illustrates the decoupling index of the Poyang Lake area(the y-axis on the left represents the numerical range of water resource utilization index and water use structure index, while the y-axis on the right represents the numerical range of water economic benefit index, carbon intensity index, and total decoupling index). Prior to 2013, this area was predominantly characterized by significant negative decoupling, signifying an unsustainable pattern of water-carbon interaction. Specifically, during the period of 2010–2011, negative decoupling intensified, resulting in a worse form of water-carbon relationship development. It is noteworthy that transient episodes of weak decoupling were observed during 2008–2009 and 2012–2013, indicating a relatively improved state of water-carbon relationship and a more harmonious coexistence between the two elements. From 2013 to 2020, strong negative decoupling and expansive negative decoupling predominantly characterized this period, while recessive coupling was also observed from 2014 to 2015. At the same time, the decoupling index values for the periods of 2013–2014, 2015–2016, and 2018–2019 are exceptionally high, primarily attributed to the consistent growth of carbon emissions, whereas the water supply has remained largely unchanged during these time. It can also be seen from Fig. 2 that the change in water supply in these periods is almost a horizontal line. It is surmised that the consistent annual rainfall across these three periods could be the underlying factor behind this observed phenomenon. This stability in rainfall leads to a relatively constant water demand in the primary industry, thereby maintaining a consistent water supply [53]. This results in the decoupling index exhibiting abnormal increasing or decreasing. These observations suggest a profound lack of coordination between water and carbon dynamics during this particular period. After 2020, the decoupling index gradually returned to stability, and a weak decoupling state appeared again, indicating that the relationship between water and carbon gradually recovered well. In summary, the decoupling scenario in the Poyang Lake area experienced initial stability, followed by a gradual decline, and ultimately demonstrated signs of improvement. Notably, the years 2013 and 2020 marked crucial turning points in this trend. In further analysis of the factors driving the decoupling index, four indices can be derived through the application of equation (10), as illustrated in Fig. 3. The key driving factor for decoupling water resource utilization from carbon emissions is the water economic benefit index, with its most significant effect from 2013 to 2020, and in 2016–2017, its contribution rate reached 65.66 %. The water resource utilization index is the main inhibitory factor of the decoupling relationship, which has remained at a relatively stable value, with a contribution rate of 41.16 % in 2012–2013. The carbon emission intensity index and water use structure index fluctuated, gradually transitioning from inhibition to promotion over time, and then gradually changed back to inhibition in recent years. Their overall contribution rate gradually weakened. In general, the decoupling index of water resource utilization and carbon emissions underwent a significant transformation approximately in 2013. This development underscores the need for continued monitoring and strategic adjustments to promote sustainable water use and mitigate carbon emissions effectively. As depicted in Fig. 3, the decoupling index exhibited a consistent trend of change prior to 2013, with numerous occurrences of a weak decoupling state within that timeframe, then changed sharply and was basically in the strong negative decoupling state. After 2020, the carbon and water relationship began to ease, and the weak decoupling state reappeared. Therefore, the coordination of the overall water-carbon relationship in the Poyang Lake area is poor, but there is still a trend towards decoupling.Fig. 3 The decoupling of carbon emission and water resources utilization in Poyang Lake from 2007 to 2021 and index decomposition results.

Fig. 3

To analyze regional characteristics, we calculated the decoupling status of each region from 2015 to 2016 and 2020 to 2021 on a county basis (Fig. 4), they belong to the prefecture-level cities of Nanchang, Jiujiang and Shangrao. During these periods, the decoupling status within the entire region persisted in being unsatisfactory. Among these counties, Yugan and Poyang both exhibit a strong negative decoupling trend, and their decoupling index was more abnormal than that of other regions, indicating a poor relationship between water and carbon. Hukou, Xinjian, and Nanchang city are experiencing a state of expansive negative decoupling, and the relationship between water and carbon is also far from optimistic. However, in the period of 2020–2021, Nanchang city has transitioned into a state of weak decoupling, resulting in an enhancement of the water-carbon relationship. Similarly, during the preceding time frame, the cities of Jiujiang city and De'an transitioned from a state of strong negative decoupling to a state characterized by both expansive negative decoupling and expansive coupling. Although the situation has marginally improved, the water-carbon relationship remains inadequate, as it has yet to achieve complete decoupling. In 2015–2016, Duchang and Yongxiu exhibited a state of weak decoupling, whereas Yongxiu specifically displayed a marked state of strong decoupling. The relationship between water and carbon in the three regions was good but then deteriorated. Duchang and Jinxian showed negative decoupling, while Yongxiu was in a state of expansion connection in 2020–2021. With regard to the regional distribution of the phenomenon under consideration, the areas of greatest concentration of water-carbon decoupling are to be found in the southwest of this region, which is part of Jiujiang and Nanchang. In general, the counties situated within the Shangrao region exhibited a strong negative decoupling trend across both time periods, whereas the remaining two regions demonstrated decoupling patterns in both instances. This corresponds to the level of development in the three regions. Compared with Shangrao, Nanchang and Jiujiang are more developed, which means they have more advanced means of water resource utilization and carbon emission control and more scientific and reasonable allocation of water resources among the three industries [34]. Therefore, the relationship of water and carbon between the two regions is better.Fig. 4 Spatial distribution of decoupling status at county (district) level in the Poyang Lake area between 2015-2016 and 2020–2021.

Fig. 4

Table 2 demonstrates the decoupling relationship between water resource utilization and carbon emissions across the three principal industries within the Poyang Lake area. According to the table, it is evident that there exist significant disparities in the decoupling situation among diverse industries. The primary industry's decoupling state has been favorable, demonstrating a cyclical trend that alternates between decoupling, negative decoupling, and decoupling again. The frequencies of decoupling and negative decoupling are identical, and the majority of these have been in decoupling in recent years. The transition within the secondary industry is evident. From 2007 to 2012, the linkage between water and carbon exhibited a generally favorable trend, with a predominantly weak decoupling state. However, after 2012, the relationship deteriorated significantly. This observation indicates the emergence of a widening discordance between the rapid increase in carbon emissions stemming from the secondary industry and the effective utilization of water resources. The situation of tertiary industry is similar to that of primary industry. It is also in the process of alternating decoupling and negative decoupling. In recent years, decoupling has become a prominent trend, and the interaction between water and carbon remains positive. However, it is crucial to emphasize that the negative decoupling state exhibited by the tertiary sector primarily manifests as expansion, with four consecutive periods from 2015 to 2019 characterized by this negative decoupling state of expansion. Generally, the interaction between water utilization and carbon emissions in the primary and tertiary industries exhibits a favorable correlation. Strong decoupling has occurred many times during the research period, and decoupling has become more frequent in recent years. Simultaneously, the deteriorating relationship between water and carbon in the secondary industry, coupled with the significant strong negative decoupling observed in recent years, remains an issue for attention. Hence, the pivotal aspect of enhancing the water-carbon nexus across the entire region lies in regulating the carbon emissions emanating from the secondary industry, thereby harmonizing its water-carbon relationship [54,55].Table 2 The decoupling status of carbon emissions and water resource utilization in the Poyang Lake area across various industries and time periods from 2007 to 2021.

Table 2Time	Primary industry	Secondary industry	Tertiary industry	
Decoupling index	Decoupling state	Decoupling index	Decoupling state	Decoupling index	Decoupling state	
2007–2008	1.18	RC	4.39	END	5.89	END	
2008–2009	−0.32	SD	−1.18	SND	0.10	WD	
2009–2010	−2.67	SND	0.63	WD	−3.27	SND	
2010–2011	1.19	EC	0.70	WD	−0.83	SND	
2011–2012	0.43	WND	0.65	WD	0.41	WD	
2012–2013	−0.24	SD	3.55	END	1.75	END	
2013–2014	/	/	−1.10	SND	4.62	END	
2014–2015	0.92	RC	15.71	RC	−2.28	SD	
2015–2016	−10.19	SND	13.74	END	2.39	END	
2016–2017	−2.93	SND	−4.09	SND	16.22	END	
2017–2018	1.44	END	−1.18	SND	42.18	END	
2018–2019	−19.58	SD	4.12	RD	178.51	END	
2019–2020	1.38	RD	−0.67	SND	−5.08	SD	
2020–2021	0.03	WD	−0.70	SND	0.33	WD	
Note: "/" indicates no data.

3.3 Driving factors of water resource utilization and carbon emission in Poyang lake area

The utilization of the LMDI decomposition model allowed for the elucidation of the various factors that influence carbon emissions and the decoupling relationship. According to equations (3), (4), the results of the calculations are clearly illustrated in Fig. 4 below. The carbon emissions within the Poyang Lake area increased by 39.98 million tons in the last 15 years. Except for the period of 2014–2015, the overall trend in carbon emissions within the region remains positive. From the vantage point of the overall trend in changes, the evolution of carbon emissions from 2007 to 2011 followed a sustained upward trajectory, and that from 2011 to 2015 had a downward trend. From 2015 to 2017, the upward trend was restored and gradually stabilized after 2017.

The primary driving factors in each period and their decomposition results are illustrated in Fig. 5 and enumerated in Table 3 (The positive value of each effect represents a positive driving force, while the negative value represents a negative driving force. The greater the absolute value of the effect, the more significant the driving effect.). Before 2012, the water structure effect served as the primary contributor to the rise in carbon emissions, and the contribution rate reached 57.93 % from 2009 to 2010. After 2012, the economic benefit effect of water use became the main factor, and the contribution rate reached 65.66 % from 2016 to 2017. The water structure effect has gradually emerged as the primary driving factor in mitigating carbon emissions. It is postulated that the unsustainable production practices and lifestyle choices observed during the initial stages of the region's development have had a substantial bearing on the overall carbon emissions [56], which is also supported by the above decoupling index analysis. In recent years, the region has witnessed significant development, accompanied by the government's heightened emphasis on environmental protection. The structure of regional water use has become more scientific and reasonable, which has gradually turned into a factor to restrain the increase in carbon emissions [57]. The carbon intensity effect has been the primary driver of carbon emission reductions in the region and it reached its maximum contribution of 42.96 % in 2014–2015. The overall impact of the water resource utilization effect is weak, the inhibition effect accounts for the majority, and its contribution rate is approximately 20 %. From a cumulative effect standpoint, the water economic benefit effect emerges as the most significant positive cumulative impact factor, whereas the carbon emission intensity effect stands out as the most substantial negative cumulative impact factor. The former is 2.43 times that of the latter. According to the actual situation in which the contribution rate of the water economic benefit effect in Fig. 5 has increased year by year, it can be considered that weakening the water economic benefit effect factor and enhancing the carbon emission intensity effect factor are the keys to controlling the expansion of carbon emissions within the region. The water use structure effect serves as a negative driving factor, whereas the water resource use effect functions as a positive driving factor. The cumulative impact of both factors, however, remains relatively minor. The cumulative effects of the four driving factors were ranked as follows: water economic benefit effect > carbon emission intensity effect > water use structure effect > water resource use effect.Fig. 5 The decomposition results of influencing factors in Poyang Lake area from 2007 to 2021.

Fig. 5

Table 3 Decomposition of Driving Forces for Various Time Periods in the Poyang Lake area from 2007 to 2021 (104 t).

Table 3Time	Carbon emission intensity effect	Water economic benefit effect	Water use structure effect	Water resource use effect	
2007–2008	−349.61	501.05	274.49	−235.49	
2008–2009	−159.49	626.96	−679.42	543.48	
2009–2010	−176.25	129.27	550.62	−94.42	
2010–2011	133.92	−217.40	569.07	245.49	
2011–2012	−518.34	454.35	599.57	−431.56	
2012–2013	−90.92	412.44	−610.25	778.88	
2013–2014	−427.42	681.30	−81.80	−12.85	
2014–2015	−941.79	527.59	351.72	−371.30	
2015–2016	−244.82	418.55	28.67	−3.03	
2016–2017	134.79	592.86	24.49	−150.76	
2017–2018	438.06	727.85	−346.31	152.60	
2018–2019	−114.24	638.03	−92.93	12.29	
2019–2020	183.56	2009.26	−1171.69	−555.47	
2020–2021	−169.64	841.91	−607.07	424.18	

According to the administrative region, we divided the study area into Nanchang, Jiujiang and Shangrao and calculated the driving effects from 2020 to 2021 (Fig. 6). The economic benefit effect of water use is the largest positive driving factor in this period, with a 40 % contribution rate followed by the effect of water resource utilization. The water use structure effect is the largest negative driving factor, and its contribution rate is above 20 %, succeeding this is the influence exerted by the carbon emission intensity effect. The general scenario of Nanchang mirrors that of the research region, with comparable levels of influence exhibited by the contributing factors. The driving impact of water resource use effect in Jiujiang has been considerably strengthened, with a contribution rate of 32.52 %, representing the largest share among the three regions. It gradually approaches 41.11 % of the economic benefit effect of water use with the maximum contribution rate. Correspondingly, the effect of water use structure is significantly weakened. The carbon emission intensity effect of Shangrao increased significantly, reaching 15.05 %,. In contrast, the effect of water resource utilization weakened slightly.Fig. 6 Cumulative contribution rate of regional influencing factors in Poyang Lake area from 2007 to 2021.

Fig. 6

4 Discussion

4.1 Impact of economic conditions on the water-carbon relationship

Over the past few years, much relevant research has focused on clarifying the complex relationship between carbon emissions and energy [51], energy and water [6], and water and the economy [54]. Various models have been employed to investigate the correlation and direction of their roles. In addition, there are also some studies that take "water-energy-carbon" as the perspective, and construct the overall research framework from the point of view of the correlation characteristics among the three [10,58]. This study distinguishes itself from prior research by specifically targeting the Poyang Lake area as the subject of its investigation. It delves into the intricate connection between water and carbon, analyzing it from the viewpoint of water resources utilization spanning from 2007 to 2021. Furthermore, it incorporates regional GDP as a metric to delve into the stimulatory impact of water resource utilization and economic growth on carbon emissions. According to the findings, the water-carbon nexus within the Poyang Lake area is unsatisfactory, with a preponderance of occurrences exhibiting a condition of pronounced negative decoupling, as well as instances of expansion negative decoupling. On the one hand, the water resources and carbon emissions in some economically developed cities tend to be more decoupled; on the other hand, the water-carbon relationship in the secondary industry is the worst, with negative decoupling and a trend of gradual aggravation. As the region's principal industry, the water-carbon relationship is adversely affected by the sharp increase in carbon emissions generated by the secondary industry, which is a consequence of the continued existence of high-energy-consuming and low-energy-efficient industries, as well as the unbridled economic development model [59]. This situation is exacerbated by the unchecked growth of these industries and the lack of sustainable economic development strategies.Furthermore, this phenomenon underscores the need for urgent action to transition towards more energy-efficient and environmentally sustainable industries, as well as the implementation of responsible economic policies that prioritize sustainability and long-term prosperity. These results are similar in the Qin River Basin [8]. Additionally, in the Poyang Lake area, the water economic benefits effect constitute the primary impetus for the increase in carbon emissions, whereas the impact of carbon emission intensity plays a pivotal role in restraining the regional growth of carbon emissions. Given that both of these factors are economic-based drivers, the region's water-carbon relationship is more intimately connected with economic growth. The existing structure of water utilization exhibits irrationalities, technological constraints, and the existence of a crude development model have the effect of exacerbating the escalation of carbon emissions within the designated region, as the economic benefits of water use in the region are not being realised. The adverse effect of carbon emission intensity also confirms the inefficiency of resource utilization in the region [32]. In summary, the most effective means of achieving a harmonious relationship between water and carbon is to optimize the water use structure of the region, with particular attention to the secondary industry, which is responsible for a significant proportion of carbon production. Furthermore, regions with a higher level of economic development tend to have a more advanced technological level and more comprehensive policy support, which makes the water-carbon relationship in these regions more scientific and reasonable [17,55]. As an area with a comparatively low economic development status, the Poyang Lake area has undergone a series of changes in land use [60], especially the substantial growth in the utilization of construction land in recent times has given rise to a considerable increase in carbon emissions. These findings offer the region an opportunity to align economic growth, water resources and carbon emissions, thus fostering regional environmental friendly and sustainable development. Additionally, the results may serve as a reference for other underdeveloped regions. They may also be used as a basis for optimizing regional industrial structures and resource management, as well as for scientific allocation.

4.2 Limitations and further research

This study presents a thorough examination of the intricate water-carbon nexus within the Poyang Lake area, delving into the role of water resource utilization and economic factors in shaping carbon emissions patterns. These findings offer some references for the basin and similar regions, but there are still some limitations. Firstly, due to the incomplete statistical data in the early period, this study estimates the data from 2007 to 2021, which will lead to the unconvincing results of the estimation. Secondly, This paper assumes a direct correlation between the utilization of water resources and the emission of carbon. The conclusions drawn from this assumption are useful for similar less developed regions to improve the water-carbon relationship. However, the reality is that the situation is frequently more complex than this, and the economic conditions are just one factor among many that affect the regional water-carbon relationship. Furthermore, the advantages and disadvantages of the water-carbon relationship do not always accurately reflect the region's economic development. This observation can be derived from the analysis of the water-carbon nexus across diverse geographical regions [6,15,54]. Finally, this study did not make a big breakthrough innovation in research methodology, the combination of Tapio model and LMDI decomposition model can better analyze the degree of linkage and role between certain elements, but there are still some limitations, for example, there are some limitations in the selection of drivers in the LMDI model, and the same is true in the selection of drivers in this study. Therefore, in the future, a better theoretical model is needed to analyze more comprehensively, including a smaller limitation on the selection of drivers and a more refined estimation result, etc., so as to improve the accuracy of similar studies.

5 Conclusion

This study rigorously analyzes the influence of water resources utilization on carbon emissions within the Poyang Lake area from 2007 to 2021 by the Tapio decoupling index model and LMDI decomposition model, focusing on the water-carbon decoupling status in the region as well as the primary driving forces that influence the variation in carbon emissions. Results reveal that the overall carbon emissions within the Poyang Lake area increases steadily with an average annual growth rate of 5.99 %, while the total water supply fluctuates and rises slowly, with the secondary industry and the primary industry as the main drivers, respectively. The decoupling relationship between carbon emissions and water resource utilization in the Poyang Lake area predominantly manifests as a state of strong negative decoupling and expansive negative decoupling. There are significant regional disparities, with the decoupling situation in some areas of Shangrao being particularly concerning. The water economic benefit index and the water resource use index are the main enablers and inhibitors of water-carbon decoupling, respectively. Among the three industries, the secondary industry has gradually deteriorated over time, and strong negative decoupling has become more frequent in recent years. Hence, the pivotal aspect of harmonizing regional water-carbon relationships lies in effectively managing carbon emissions emanating from the secondary industry. Significant disparities exist in the contribution rates of driving factors across diverse regions. The cumulative effects of the four driving factors are ranked as follows: water economic benefit effect > carbon emission intensity effect > water use structure effect > water resource use effect.

According to the findings of the study, a significant amount of carbon emissions emanating from the secondary industry has led to a consistent and sustained rise in the overall carbon emissions within the Poyang Lake area. The lack of coordination between the secondary industry and water resource utilization has contributed to the intensification of the negative decoupling between the two. So the overall carbon emission reduction plan for the Poyang Lake area should be deployed based on taking the secondary industry as the key element and integrating the actual situation of various regions. We must accord priority to the harmonious development of water-carbon relationship in the secondary industry of the economy. Local governments must undertake the strategic deployment of water conservation and carbon reduction measures that are commensurate with the actual development level of their respective regions, while avoiding the implementation of impractical planning endeavors. Furthermore, the inadequate structure and undue focus on water-related economic gains have accelerated the escalation of carbon emissions in the region. At this point, measures such as adjusting water prices in various industries and reallocating water resources can be taken to suppress the significant impact of these two factors. Finally, the water-carbon relationship within the Poyang Lake area will undergo significant enhancement, thereby fostering steady growth in the regional economy.

Data availability statement

Data associated with the study has not been deposited into a publicly available repository and data will be made available on request.

Funding

The research results were supported by the National Science Foundation (Grant No. 42361003 ); the Opening Foundation of Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone, 10.13039/501100009958 Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences (Grant No. XJYS0907-2023-22 ); 2022 Pure Zixi Carbon Neutral Practice Innovation Center project "Carbon neutral Fuzhou (Zixi) evaluation model construction and application(2022JDA07 ); 10.13039/501100004868 Jiangxi University of Finance and Economics , International commodity Price analysis and forecast research innovation team; Science Foundation of Jiangxi Education Department (Grant No.GJJ190269 ).

Compliance with ethical standards

This article does not involve potential conflicts of interest, nor does it involve human or animal research, and is strictly ethical.

Consent to publish

The participant has consented to the submission of the case report to the journal.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

CRediT authorship contribution statement

Shuai Fu: Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Methodology, Investigation, Funding acquisition, Data curation. Bingxian Xu: Project administration, Methodology, Formal analysis, Data curation. Yuxin Peng: Software, Resources, Investigation, Formal analysis. Jie Yu: Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Yingxiang Feng: Writing – original draft, Software, Resources, Project administration, Data curation. Xiuxiang Li: Methodology, Investigation. Lanhai Li: Writing – review & editing, Writing – original draft, Formal analysis, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The research results were supported by the National Science Foundation (Grant No. 42361003 ); the Opening Foundation of Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone, 10.13039/501100009958 Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences (Grant No. XJYS0907-2023-22 ); 2022 Pure Zixi Carbon Neutral Practice Innovation Center project "Carbon neutral Fuzhou (Zixi) evaluation model construction and application(2022JDA07 ); 10.13039/501100004868 Jiangxi University of Finance and Economics , International commodity Price analysis and forecast research innovation team; Science Foundation of Jiangxi Education Department (Grant No.GJJ190269 ).
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