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Study on Changes in Vegetation Carbon Footprint and Its Influencing Factors in Xinjiang, a Typical Arid Region of China

Land 2026, 15(1), 10; https://doi.org/10.3390/land15010010 (registering DOI)

by Shunfa Yang^1,2

, Mei Zan^1,2,*

, Cong Xue^1,2

, Lili Zhai^1,2

, Jia Zhou^1,2, Zhongqiong Zhao^1,2 and Jian Ke^1,2

Reviewer 1: Anonymous

Reviewer 2: Anonymous

Reviewer 3: Anonymous

Land 2026, 15(1), 10; https://doi.org/10.3390/land15010010 (registering DOI)

Submission received: 5 November 2025 / Revised: 10 December 2025 / Accepted: 17 December 2025 / Published: 20 December 2025

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Title: Study on the Changes of Vegetation Carbon Footprint and Influencing Factors in typical arid areas of Xinjiang, China

I have carefully read this interested manuscript on changing vegetation and factors influencing the carbon footprint in typical arid region of Xinjiang, China. The manuscript is well written and proved the sufficient evidence how the carbon emissions was significantly increased in some cites while the vegetation and human activity are the main causes for carbon footprint and vegetation factors are the negative influence the footprint. On the 21 year based data the area of cropland grass land and woodland need to expand for the carbon neutrality in studied region but before it’s accepted for the publication the some revision should be need to improve the manuscript.

The tile of the manuscript is seemed good and readable.

The abstract of the manuscript desire to be improve by adding the methodology.

The introduction id written well but can be improve by incorporate the knowledge gap, hypothesis and objective.

The major vegetation types of the study area can be included in the manuscript.

The methodology of the manuscript is requiring including the detail about the human activity use to estimate the carbon footprint.

The result of the manuscript is written well.

The conclusion of the manuscript is written vas similar to the results and needs to be shorten by only write the major findings and recommendations.

Author Response

Comment 1: The tile of the manuscript is seemed good and readable.

Response 1: Thank you for the encouragement. We will certainly continue to do our best.

Comment 2: The abstract of the manuscript desire to be improve by adding the methodology.

Response 2: Thank you for this valuable suggestion. We completely agree and have supplemented the Abstract with details on our research methodology. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 11-16: We have changed “Using structural equation modeling (SEM) integrating vegetation, meteorological, and human activity factors, this study analyzed carbon footprint changes in Xinjiang from 2000 to 2020.” to “This study analyzes the changes in carbon footprint and its influencing factors in Xinjiang by employing a range of models, including Net Ecosystem Productivity (NEP), carbon emission fitting, carbon footprint analysis, and Structural Equation Modeling (SEM). Furthermore, using the carbon deficit vegetation investment estimation method, we quantify the additional vegetation area and investment required for Xinjiang to achieve carbon neutrality.”

Comment 3: The introduction id written well but can be improve by incorporate the knowledge gap, hypothesis and objective.

Response 3: Thank you for this valuable suggestion. We completely agree and have revised and improved the Introduction section accordingly. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 56-115: We have changed “Carbon Footprint, a globally recognized method for quantifying carbon emissions, systematically exposes the core impact of human activities on the climate. By tracking greenhouse gas emissions throughout a product’s entire lifecycle, it reveals crucial indicators of emission dynamics. This lifecycle assessment-based model offers a scientific foundation for understanding the link between global warming and human actions, but also serves as an important data support for optimizing low-carbon decision-making and formulating differentiated emission reduction strategies by accurately identifying high-carbon emission links. However, there has been no uniform definition of carbon footprint in current academic circles, and the current understanding of carbon footprint can be summarized in two ways, one approach is to use carbon footprint to quantify the greenhouse gas emissions associated with a particular activity or entity [2,3]; A second interpretation of the carbon footprint considers it the extent of vegetative area needed for photosynthetic absorption of carbon emission resulting from the combustion of fossil fuels [4,5]. The former focuses on assessing the carbon emissions of a product or production activity at all stages of its life cycle, while the latter systematically measures the combined impacts of human activities on terrestrial ecosystems. This paper uses the second concept to do the carbon footprint research in Xinjiang. Currently, domestic and international research on carbon footprint, in terms of research content, mainly focuses on the measurement of carbon footprint, spatial and temporal patterns, as well as influencing factors. Relevant studies show that China's carbon footprint is increasing year by year [6]. Exhibiting a spatial pattern where values are higher in the north and lower in the south [7,8]. Carbon footprint spatial variations are significantly influenced by factors including the energy mix, economic development level, and technological research and development [9,10]. Reducing political and financial risks and increasing clean energy use can curb carbon footprint levels [11,12]. In addition, studies have examined the ecological impacts of carbon emissions by analyzing the breadth and depth of carbon footprints [13]. In terms of research objects, including the carbon footprint of different products and industries [14,15]. Such as revealing the trend of various carbon footprints in China [16,17]. For carbon footprint studies, input-output analysis stands out as the most common research approach [18], life cycle Analysis [19], IPCC calculation methods, and logarithmic mean Divisa index methods [20]. For instance, one could utilize IPCC guidelines to create a model quantifying carbon emissions from energy use, aiming to analyze how these emissions are spatially distributed among different industries within China [21]. Accounting for carbon footprint of private consumption using an input-output model [22]. Figuring out the Carbon Footprints of Different Food Crops in China with Life Cycle Analysis [23,24]. By integrating input-output and life-cycle analysis to measure regional carbon footprints and assess interregional transfers in China, we establish a theoretical basis for greening traditional farming methods [25,26]. Although some progress has been made in carbon footprint research, in our earlier work [27], we evaluated the potential of Xinjiang’s vegetation to offset regional anthropogenic CO₂ emissions; however, a quantitative assessment of the exact vegetation cover (area) required to reach net-zero emissions remains lacking. It still needs to be further deepened. Currently, most of the studies on the spatial and temporal distribution of regional carbon footprints have focused on exploring the spatial correlation of the footprints, while the driving factors behind the footprints have been understudied. In addition, many studies analyzing carbon footprints focus mainly on carbon dioxide emissions caused by energy consumption, while ignoring carbon emissions caused by other production activities, which may lead to biased results. In view of this, in order to more accurately reflect the ecological carrying capacity of a region and the impact of human economic activities on the natural environment, we need to improve and supplement these research methods. In this study, we chose to include the total carbon emissions released by human production activities, such as agriculture, industry and tourism, and the productive land area needed to study the carbon footprint of Xinjiang. The annual vegetation NEP data from 2000 to 2020 are used as the level of vegetation carbon sequestration in Xinjiang, and combined with the carbon emission data, the carbon footprint of Xinjiang is calculated to analyze the spatial and temporal changes of Xinjiang's carbon footprint and its driving factors. In this way, we provide scientific references for Xinjiang to realize the “double carbon” goal and formulate refined carbon emission reduction policies in the future. ” to “As an internationally recognized quantitative tool for carbon emissions, the carbon footprint serves as a critical metric for tracking greenhouse gas (GHG) emissions throughout a product’s entire life cycle. It systematically elucidates the core mechanisms by which human activities impact the climate system. Currently, there are two primary perspectives on the carbon footprint. The first defines it as the total amount of greenhouse gases emitted directly or indirectly by a specific activity or entity [2, 3]; The other perspective views the carbon footprint as the vegetation area required to absorb these carbon emissions [4, 5]. The former approach focuses on assessing the quantity of carbon emissions at each stage of a product’s or activity’s entire life cycle. In contrast, the latter systematically measures the area of terrestrial vegetation ecosystems needed to sequester these emissions. This study adopts the second concept to investigate the carbon footprint of Xinjiang. Current research on carbon Footprint, both domestically and internationally, primarily focuses on three aspects: its quantification, spatiotemporal patterns, and influencing factors. Relevant studies indicate that China’s carbon footprint has shown a year-on-year increasing trend [6]. Concurrently, it exhibits a spatial pattern of being higher in the north and lower in the south [7, 8]. Factors such as energy structure, level of economic development, and technological R&D have been found to significantly influence the spatial variation of the carbon footprint [9, 10]. Furthermore, it has been suggested that its level can be curbed by reducing political and financial risks [13] and increasing the use of clean energy [14]. Moreover, with respect to the objects of study, investigations have assessed the ecological repercussions of carbon emissions through an analysis of the breadth and profundity of the carbon footprint [15]. The scope of such research encompasses the carbon footprints of disparate products and industrial sectors [16], exemplified by the revelation of evolutionary trends in the carbon footprint of food consumption [17]. From a methodological standpoint, the principal analytical instruments comprise Input-Output Analysis (IOA) [18], Life Cycle Assessment (LCA) [19], and the Logarithmic Mean Divisia Index (LMDI) method [20]. Illustrative applications include the construction of energy consumption-based carbon emission models using the IPCC methodology to investigate industrial spatial carbon footprints [21], the utilization of input-output models (MIRO) for the accounting of private consumption-induced carbon footprints [22], and the estimation of various crop carbon footprints via LCA, which furnishes a theoretical foundation for the green transformation of conventional cultivation systems [23, 24]. Furthermore, some studies have combined Input-Output Analysis with LCA to measure the carbon footprint of various regions in China and to analyze inter-regional carbon transfers [25, 26]. In the research on the spatiotemporal distribution of regional carbon footprints, most studies have concentrated on exploring spatial correlations, while the underlying driving factors have been insufficiently investigated. Therefore, future research needs to further delve into the causes of carbon footprint changes and explore feasible carbon reduction implementation methods.

Although previous research on the carbon footprint has made considerable progress, studies concerning mainland China, and particularly Xinjiang—the country’s largest provincial-level administrative region and a typical arid zone worldwide—are notably scarce. While we have previously assessed the capacity of Xinjiang’s vegetation to offset regional emissions [27], a quantitative assessment of the precise vegetation area required to achieve carbon neutrality is still lacking. Many studies analyzing the carbon footprint primarily focus on carbon emissions from energy consumption, often neglecting those from other production activities. This limitation can lead to an assessment of only partial carbon neutrality outcomes. Therefore, this study utilizes annual Net Ecosystem Productivity (NEP) data from 2000–2020 to represent the carbon sequestration level of vegetation in Xinjiang. We integrate this with total carbon emission data from all human activities, including industry, agriculture, and tourism, to calculate the region’s carbon footprint. Subsequently, we analyze its spatiotemporal variations and driving factors, and investigate the monetary investment required in vegetation for Xinjiang to achieve carbon neutrality. The research aims to explore a viable pathway toward a carbon neutrality strategy for arid-zone ecosystems, thereby providing a practical case study and a scientific reference for formulating refined carbon reduction policies for the world’s arid regions to meet their “dual carbon” goals.”

Comment 4: The major vegetation types of the study area can be included in the manuscript.

Response 4: Thank you for this valuable suggestion. We completely agree and have revised the Discussion section 4.3 accordingly. Specifically, we have incorporated the main vegetation types of the study area into our recommendations for achieving future carbon neutrality. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 393-490: We have changed “ 4.1. Analysis of the causes of carbon footprint changes

From 2000 through 2020, there was a considerable rise in Xinjiang’s carbon footprint, which can be divided into two stages, 2000-2011 Xinjiang vegetation carbon footprint showed a slow increasing trend, and 2012-2020 showed a significant increasing trend. Total area of vegetation carbon footprint in Xinjiang in 2000, 2011 and 2020 was 30.41×10⁴ km², 46.42×10⁴ km² and 104.48×10⁴ km², respectively, and the vegetation carbon footprint in Xinjiang increased by 3.44 times from 2000 to 2020. Xinjiang's industry is dominated by heavy industries such as energy, chemicals and metallurgy, which consume large amounts of energy and emit high levels of carbon. Xinjiang's urbanization has accelerated in recent years, and infrastructure construction and transportation will lead to increased carbon emissions. Population growth drives higher energy consumption and carbon emissions, a trend potentially exemplified by the surge in car ownership within Xinjiang, carbon emissions from transportation trips have also increased. People’s living standards have improved and consumption patterns have changed, and these human activities have led to a rapid increase in Xinjiang’s carbon footprint in later years. Vegetation in Xinjiang plays a role in curbing the growth of carbon footprint, and this study found that the NEP of Xinjiang forests shows a trend of slow decline, which may be affected by the aging of forests, and relevant studies show that by 2020, the average age of most of the natural coniferous forests in the Altay and Tianshan Mountains will reach 74 years, which has already tended to be in the stage of old-growth forests [36], and the increase in the age of the forests has caused a decrease in the sequestration capacity of forests, thus leading to the decrease of their carbon sinks. decrease in carbon sinks [37,38]. Overcultivation and overgrazing in some areas of Xinjiang have led to a decline in the quality of vegetation and a weakening of carbon absorption capacity. Progress in the transformation of Xinjiang’s energy structure has been slow, proportion of clean energy replacing fossil energy is low.

The above reasons are contributing to the increase in Xinjiang’s carbon footprint, and in the future Xinjiang should upgrade its industrial technology and increase energy efficiency transformation to reduce energy consumption. The use of green and low-carbon agricultural chemicals, as well as energy-efficient tillage and irrigation techniques, will effectively reduce the carbon footprint.

4.2. Recommendations for promoting carbon neutrality in Xinjiang

Most of the carbon neutrality values of Xinjiang cities and towns showed different degrees of decreasing trends between 2000 and 2020, especially around 2012, when the carbon deficit values of several cities and towns turned from positive to negative, indicating that carbon emissions gradually exceeded the carbon absorption by vegetation. Among them, major carbon sinks in Xinjiang that are basically carbon-neutral during the 21-year period include the cities of Altay, Bortala, Bayingolin, Kizilsu Kirgiz, Tacheng and Yili, and the cities that have transitioned from being carbon sinks to being carbon sources after 2012 are Aksu, Hami, Hotan and Kashgar. Four cities, Changji, Kelamayi, Turpan and Urumqi, have been major carbon source areas in Xinjiang from 2000 to 2020. This trend reflects that Xinjiang has faced serious carbon neutrality challenges over the past 21 years, mainly due to increased energy consumption and ecological and environmental pressures as a result of industrialization and urbanization under rapid economic development in Xinjiang. The industrial structure of Xinjiang is dominated by heavy industries such as energy, chemicals and metallurgy, which consume a large amount of fossil energy and produce large amounts of carbon emissions in the production process. Xinjiang's energy consumption structure is dominated by fossil energy sources such as coal and oil. In addition, the proliferation of automobile ownership in Xinjiang over the past 21 years has further contributed to the rise in carbon emissions. Achieving economic development while effectively controlling carbon emissions and facilitating a green, low-carbon transition is a critical challenge that must be addressed to meet Xinjiang’s dual-carbon goals [39]. The rapid economic development of Xinjiang over the period 2000-2020 has been accompanied by an increase in carbon emissions, which has posed a serious challenge to Xinjiang, and in order to achieve “dual-carbon” goal for Xinjiang, following measures are needed for future development: formulate a sustainable territorial spatial planning scheme and promote the intensive use of land. In addition, most of the unutilized land in Xinjiang is desert, but it still has a certain carbon sequestration capacity [40]. Xinjiang has a vast desert, and its total carbon sink is undoubtedly huge. Sustainable ecological and economic development in Xinjiang necessitates a rational land-use reconfiguration, specifically the conversion of underutilized land into grassland under the constraint of efficient water use, thereby augmenting vegetation area and ecosystem carbon sequestration potential. In addition, Xinjiang persists in upholding the regulations that designate protected arable land areas, Three North Protective Forest Project, the Degraded Grassland Rehabilitation Project and the Ecological Rehabilitation Project, in order to ensure that the area of arable land, forest land and grassland does not decrease in size or quality.

In the future, Xinjiang should strengthen the protection of the six major carbon sinks of Altay, Bortala, Bayingolin, Kizilsu Kirghiz, Tacheng, and Yili, and vigorously develop eco-tourism in conjunction with the favorable ecological environment of the carbon sinks; and accelerate the industrial upgrading and transformation of the four major carbon source areas of Changji, Karamay, Turpan, and Urumqi. Accelerate industrial upgrading and transformation in the four major carbon source areas, improve technical energy utilization efficiency, and vigorously develop use of clean energy. Promote the participation of the whole society in carbon neutral actions. Promoting sustainable economic and ecological development, these measures are the way to ensure that Xinjiang realizes the goal of carbon neutrality, sustainable development and a beautiful Xinjiang.

4.3. Accelerating the Construction of Carbon Trading Market in Xinjiang

This study obtained the major carbon source and sink areas in Xinjiang, and estimated the amount and area of vegetation investment in Xinjiang as a whole and in 14 prefectures and cities to achieve carbon neutrality by relying on vegetation, This can be used in the carbon trading market to promote carbon trading between source and sink areas, achieving sustainable development for the economy and the natural environment. The carbon trading market is a market mechanism for realizing emission reduction targets through the purchase and sale of carbon emission rights. Its core lies in incentivizing enterprises to reduce carbon emissions through market means, thus fostering green and low-carbon development. In 2024, Interim Regulations on Carbon Emission Trading Administration officially took effect, which provided a national legal framework for carbon trading in Xinjiang, clarifying core rules such as quota allocation, data verification and market supervision. As a major energy and resource province in China, Xinjiang has made staged progress in building a carbon trading market, driven by “dual-carbon” goal.

Altay pioneered grassland carbon sink trading in Xinjiang, hosting the region’s first project under the International Voluntary Emission Reduction Standard, realizing carbon sink trading through restoration of degraded grasslands. The proceeds will feed the grassland ecological restoration. This model provides a demonstration for the transformation of ecological value in arid, semi-arid areas, and promotes exploration of “grassland carbon sinks + eco-tourism” integrated development path in Altay region. For example, Yili, relying on the Gongliu branch of the State Forestry Administration in the western Tianshan Mountains, has been selected as a national forestry carbon sink pilot project to promote synergy between ecological restoration and the development of carbon sinks. Combining forestry carbon sinks with ecological restoration, through the model of “systematic management + land greening + carbon trading”, it has realized a win-win situation in terms of ecological and economic benefits. For example, Shunchuang Energy Technology Co., Ltd. in Kashgar invested 2 million yuan to carry out forest carbon sink data mapping, and released the potential of forest carbon sink development through the artificial intervention new forest project, exploring the carbon sink development mode suitable for the climatic conditions of southern Xinjiang. However, Xinjiang has not yet established a regional carbon trading venue, resulting in narrow financing channels for enterprises, high transaction costs, low market liquidity and awareness, and enterprises relying on the national carbon market or inter-provincial trading, with insufficient market connectivity.

In the future, Xinjiang needs a synergistic effort between policy and market to build a robust regional carbon trading platform. Enhancing market liquidity and participation is crucial. By leveraging Xinjiang’s ecological characteristics, a “carbon sink +” integrated development model should be realized, combining carbon sink trading with eco-tourism and green agriculture. This approach will transform carbon trading into a new engine for green economic growth, contributing to the reduction of Xinjiang’s carbon footprint. By striving to create a “carbon neutral” Xinjiang, it can achieve sustainable and high-quality development. ” to “4.1. Analysis of the causes of carbon footprint changes

From 2000 to 2020, Xinjiang’s carbon footprint experienced a considerable rise, characterized by two distinct stages: a slow increase from 2000–2011, followed by a significant acceleration from 2012–2020. The total vegetation carbon footprint area expanded from 30.41×10⁴ km² in 2000 and 46.42×10⁴ km² in 2011 to 104.48×10⁴ km² in 2020, marking a 3.44-fold increase over the two decades.This surge is attributable to several interconnected factors. Economically, Xinjiang’s industrial structure is dominated by heavy industries like energy, chemicals, and metallurgy, which are highly energy-intensive and carbon-emissive. Demographically, rapid urbanization and population growth have fueled higher energy demand, a trend exemplified by the surge in car ownership and associated transportation emissions. Societally, rising living standards and evolving consumption patterns have further contributed to the carbon footprint.

Concurrently, the region’s natural carbon sinks are weakening. This study observed a slow decline in the Net Ecosystem Productivity of Xinjiang’s forests, potentially due to forest aging. Research indicates that by 2020, the average age of natural coniferous forests in the Altay and Tianshan Mountains had reached 74 years, trending towards an old-growth stage [36]. This maturation reduces their carbon sequestration capacity, thereby diminishing their carbon sink function [37,38]. Furthermore, ecological pressures from overcultivation and overgrazing in some areas have degraded vegetation quality and weakened carbon absorption. The slow pace of energy structure transformation, with a low proportion of clean energy replacing fossil fuels, has exacerbated the issue. To address these challenges, future strategies must focus on upgrading industrial technology and improving energy efficiency. In the agricultural sector, the adoption of green, low-carbon agrochemicals and energy-efficient tillage and irrigation techniques will be essential to effectively reduce the overall carbon footprint.

4.2. Accelerating the Construction of Carbon Trading Market in Xinjiang

This This study identified major carbon source and sink areas in Xinjiang and quantified the vegetation investment required for carbon neutrality at both the regional and prefectural levels. These findings can directly inform a carbon trading market, facilitating transactions between source and sink areas to promote sustainable economic and environmental development. The carbon trading market, a mechanism for achieving emission reductions through the buying and selling of carbon credits, incentivizes enterprises to lower emissions, thereby fostering green, low-carbon growth. The 2024 implementation of the Interim Regulations on Carbon Emission Trading Administration has provided a crucial national legal framework for Xinjiang, clarifying core rules on quota allocation, data verification, and market supervision. As a major energy province, Xinjiang has made phased progress in establishing its carbon market, driven by the “dual-carbon” goals.

Pioneering local projects offer valuable models. Altay initiated Xinjiang’s first grassland carbon sink trading under an international voluntary standard, using proceeds from restored grasslands to fund further ecological restoration. This demonstrates a viable pathway for transforming ecological value in arid regions and exploring a “grassland carbon sink + eco-tourism” model. Similarly, Yili was selected as a national forestry carbon sink pilot, achieving a win-win for ecology and the economy through a “systematic management + land greening + carbon trading” approach. In Kashgar, corporate investment in forest carbon sink data mapping is unlocking development potential suitable for southern Xinjiang’s climate.

Despite this progress, Xinjiang lacks a regional carbon trading venue. This results in limited financing channels, high transaction costs, low market liquidity and awareness, and an over-reliance on the national market, leading to insufficient market connectivity. Looking ahead, a synergistic policy and market effort is needed to build a robust regional carbon trading platform. Enhancing liquidity and participation is paramount. By leveraging Xinjiang’s unique ecology, a “carbon sink+” integrated development model—combining carbon trading with eco-tourism and green agriculture—must be realized. This will transform carbon trading into a new engine for green growth, reducing Xinjiang’s carbon footprint and steering the region toward sustainable, high-quality development and the ultimate goal of a carbon-neutral Xinjiang.

4.3. Recommendations for promoting carbon neutrality in Xinjiang

From 2000 to 2020, most cities in Xinjiang exhibited a declining trend in carbon neutrality, with several key areas like Aksu, Hami, Hotan, and Kashgar transitioning from carbon sinks to sources post-2012. Major cities such as Urumqi and Kelamayi remained persistent carbon sources throughout the period. This alarming trend, highlighting severe challenges to Xinjiang’s dual-carbon goals [39], is primarily driven by an energy-intensive industrial structure dominated by heavy industry and a fossil fuel-dependent energy mix. Rapid urbanization and a proliferation of automobiles have further exacerbated emissions. To reverse this, future strategies must focus on sustainable land use and enhancing the region’s vast carbon sink potential. Although predominantly desert, Xinjiang’s unutilized land holds significant sequestration capacity [40]. Therefore, optimizing territorial spatial planning and fully leveraging the immense carbon sink of its deserts are critical measures for decoupling economic growth from emissions and achieving a green, low-carbon transition.

Achieving sustainable development in Xinjiang requires a strategic land-use reconfiguration, prioritizing the conversion of underutilized land into grasslands under strict water-use constraints to boost ecosystem carbon sequestration. This ecological restoration must prioritize native, drought-resistant species adapted to local conditions. The region’s flora includes desert xerophytes like *Haloxylon* and *Tamarix*, grassland species such as *Stipa*, and forests featuring *Picea*, *Larix*, and *Populus euphratica*. These species are ideal due to their extensive root systems and water-conserving traits. Successful implementation also depends on upholding key national policies. Xinjiang must continue to enforce regulations protecting arable land and advancing major ecological projects, including the Three North Protective Forest and the Degraded Grassland Rehabilitation initiatives. By integrating scientific, site-specific planting with these robust policy frameworks, Xinjiang can effectively expand its carbon sinks and ensure the stability of its arable land, forest, and grassland areas, paving the way for its carbon neutrality goals.

To achieve its carbon neutrality goals, Xinjiang must adopt a differentiated, region-specific strategy. For the six major carbon sinks—Altay, Bortala, Bayingolin, Kizilsu Kirgiz, Tacheng, and Yili—the focus should be on strengthening ecological protection and leveraging their favorable environments to develop eco-tourism. Concurrently, the four major carbon source areas—Changji, Karamay, Turpan, and Urumqi—must accelerate industrial upgrading, enhance energy efficiency, and transition towards clean energy sources. Beyond these industrial and ecological measures, fostering broad societal participation in carbon neutrality initiatives is crucial. The integrated implementation of these strategies is fundamental to steering Xinjiang towards a sustainable future, ensuring the realization of its carbon neutrality objectives and the vision of a beautiful Xinjiang.”

Comment 5: The methodology of the manuscript is requiring including the detail about the human activity use to estimate the carbon footprint.

Response 5: Thank you for this valuable suggestion. We completely agree and have supplemented the Methods section of the revised manuscript with details on the human activities used to estimate the carbon footprint. The specific additions have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 198-202: We have changed “Carbon footprint is the area of vegetation required to absorb carbon emissions through photosynthesis, and is used to measure the occupation of ecological space by carbon emissions. The carbon footprint is measured based on the natural ecosystem and socio-economic system perspectives. NEP data were used as an indicator of carbon sequestration in ecosystems” to “Carbon footprint from a dual-system perspective, encompassing both natural and socio-economic systems. The carbon sequestration of the natural ecosystem is quantified using the NEP. The total carbon emissions from the socio-economic system are calculated as the sum of emissions from human activities, primarily including industry, agriculture, and tourism”

Comment 6: The result of the manuscript is written well.

Response 6: Thank you for your positive feedback. We will continue to work hard to improve the quality of our research.

Comment 7: The conclusion of the manuscript is written vas similar to the results and needs to be shorten by only write the major findings and recommendations.

Response 7: Thank you for this valuable suggestion. We completely agree and have streamlined the Conclusion section to focus on the main findings and recommendations. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 492-515: We have changed “This study explores the carbon footprint of Xinjiang and its influencing factors, with the aim of providing data support for the amount of vegetation and investment budget needed to achieve carbon neutrality in Xinjiang, and providing scientific basis and policy recommendations for Xinjiang to realize the goal of “double carbon”. Results of the study show that:

(1) Between 2000 and 2020, NEP of vegetation in Xinjiang showed a slow upward trend, with the total annual NEP increasing from 6434.45×10⁴ t in 2000 to 8149.66×10⁴ t in 2020, with an annual growth rate of 1.19%, and average annual NEP values ranging from 124.21 to 168.45 g C m^-2 yr^-1 between. The total vegetation NEP of six regions, including Altay, Bortala, Bayingolin, Kizilsu Kirghiz, Tacheng, and Yili, accounted for 66.95% of the total in Xinjiang, constituting a major carbon sink. During the same period, the total carbon emissions in Xinjiang increased significantly from 2836.08×10⁴ t to 15457.91×10⁴ t, with an average annual growth rate of carbon emissions of 8.84%, of which the four regions of Urumqi, Changji, Kumul and Karamay accounted for 61.31% of the total amount of Xinjiang, constituting the main carbon source area.

(2) Carbon footprint of Xinjiang increased significantly from 2000 to 2020, with the total area increasing from 30.41×10⁴ km² in 2000 to 104.49×10⁴ km² in 2020, an increase of about 3.44 times. Human activities are the main positive factor for the increase of carbon footprint, while vegetation factor is its main negative factor. The ability of vegetation NEP to offset carbon emissions in Xinjiang has been gradually weakening: between 2000 and 2010, vegetation NEP was able to offset carbon emissions to achieve carbon neutrality, but after 2011, the growth rate of carbon emissions has far exceeded the ability of vegetation NEP to achieve carbon neutrality. In seven cities, including Karamay, Urumqi, Turpan, Changji, Kumul, Aksu and Hotan, carbon emissions have always exceeded the maximum carbon carrying capacity of local vegetation ecosystems, and Kashgar and Yili regions have approached the carbon absorption limit of regional vegetation in recent years.

(3) Xinjiang needs to invest 106.77×10⁸ dollars to achieve carbon neutrality by relying entirely on vegetation, of which the invested area of cropland, woodland and grassland is 8029, 1710 and 35016 km² respectively. in order to realize “double carbon” goal of Xinjiang, it is necessary to speed up the construction of the carbon trading market in Xinjiang, formulate a sustainable spatial plan for the national territory, and strictly implement ecological protection policies. Strictly implement ecological protection policies. On the premise of rationally utilizing water resources, it has continued to carry out locally appropriate afforestation, returning farmland to forests and grasslands, optimizing the types of crops on arable land, protecting rivers and wetlands, and rationally adjusting the distribution of tree species in forested areas to enhance the stability of ecosystems. At the same time, the ability to protect carbon sequestration by vegetation in major carbon sink areas such as Altay, Bortala, Bayingolin, Kizilsu Kirghiz, Tacheng and Yili cities should be strengthened, and ecotourism, green agriculture and other green economies should be vigorously developed. Accelerate the transformation of economic structure in major carbon source areas such as Urumqi, Changji , Kumul and Karamay City, and effectively control the growth of carbon emissions. Promoting a low-carbon lifestyle for all people, advocating energy conservation and emission reduction, and promoting the participation of the whole society in carbon neutral actions are all measures that are necessary for Xinjiang to realize the goal of carbon neutrality and sustainable development.” to “This study explored the carbon footprint of Xinjiang and its influencing factors to provide data support for the vegetation area and investment needed to achieve carbon neutrality. The results show that from 2000 to 2020, while the total annual Net Ecosystem Productivity of vegetation slowly increased from 6434.45×10⁴ t to 8149.66×10⁴ t, carbon emissions surged dramatically from 2836.08×10⁴ t to 15457.91×10⁴ t. A factor analysis revealed that human activities were the primary positive driver of this growing carbon footprint, whereas the vegetation factor acted as the main negative inhibitor. This dynamic imbalance is evident in the geography: six regions (Altay, Bortala, Bayingolin, Kizilsu Kirgiz, Tacheng, and Yili) formed the major carbon sinks (66.95% of total Net Ecosystem Productivity), while four regions (Urumqi, Changji, Kumul, and Karamay) were the dominant carbon sources (61.31% of total emissions). Consequently, Xinjiang’s carbon footprint expanded significantly, with its total area increasing from 30.41×10⁴ km²in 2000 to 104.49×104 km² in 2020, an increase of about 3.44 times. The vegetation’s capacity to offset emissions was overwhelmed after 2011. To reverse this trend, an investment of 106.77×10⁸ dollars is required to convert 8029 km² of cropland, 1710 km² of woodland, and 35016 km² of grassland. Achieving this demands a multi-pronged strategy: accelerating a regional carbon trading market, enforcing sustainable spatial planning, and implementing strict ecological protection. This includes targeted afforestation, optimizing crop types, and, crucially, strengthening carbon sinks in areas like Altay and Yili through eco-tourism, while accelerating the low-carbon economic transformation in source areas like Urumqi and Karamay. Promoting a low-carbon lifestyle and broad societal participation are also essential for Xinjiang to meet its dual carbon and sustainable development goals.”

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Using structural equation modeling (SEM) integrating vegetation, meteorological, and human activity factors, authors present an extensive and interesting this study in order to analyzed carbon footprint changes in Xinjiang from 2000 to 2020. The thinking behind the research in the manuscript is clear. The text is generally well-structured. Here are some suggestions to back up my idea and help the author improve the quality of the paper:

Keywords can be improved, avoiding, if possible, to repeat the same words that appear in the title, facilitating the searching engines work.

The text contains empty spaces or improperly used capital letters such as: Xinjiang’ s…. the “doublé carbon” goal…..hazards, It is crucial …

How did you estimate this value $106.77×10⁸ ?

The introduction presents very long and dense paragraphs that blur the core message. In fact it seems that they are copied paragraphs interspersed. The Introduction section should be divided into logical paragraphs, each centered on a specific aspect of the topic. Please improve.

In the Materials and Methods section, it says: "Land use data were obtained from the China 30-meter land use dataset provided by Mr. Yang Jie's team from Wuhan University." This seems like an unscientific expression. I suggest changing it, although thanks should be given to the professor.

Are the formulas for equations 1, 2, and 3 your own or from other authors?

How did you obtain the maps in Figure 4?

The partial discussion of the results appears in the Results section. I suggest including them in the Discussion section.

No mention was made in the discussion of the scope or limitations of the study findings

I am not in favor of including acronyms in the conclusions.

In the references section, the authors do not follow the journal's guidelines. Please review.

The current version is not ready for publication.

Author Response

Comment 1: Keywords can be improved, avoiding, if possible, to repeat the same words that appear in the title, facilitating the searching engines work.

Response 1: Thank you for this valuable suggestion. We completely agree and have streamlined the keywords accordingly. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 29: We have changed “ NEP, Carbon emission, Carbon footprint, Carbon neutrality, SEM, Xinjiang ” to “ NEP, Carbon emission, Carbon neutrality, SEM ”

Comment 2: The text contains empty spaces or improperly used capital letters such as: Xinjiang’ s…. the “double carbon” goal…..hazards, It is crucial …

Response 2: Thank you for your valuable comment. We completely agree and have carefully proofread the entire manuscript to correct errors in spacing and improper capitalization. The specific corrections have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

We have changed “Xinjiang’s” to “Xinjiang’s”;We have changed ““double carbon”” to “ “double carbon” ”;We have changed “goal…..hazards, It is crucial” to “goal…..hazards, it is crucial”.

Comment 3: How did you estimate this value $106.77×10⁸ ?

Response 3: We appreciate the opportunity to elaborate on our calculation process. The total investment figure was derived by first determining the average carbon deficit for each vegetation type. This was achieved by calculating the 21-year (2000-2020) mean carbon deficit for cropland, forestland, and grassland across all 14 cities in Xinjiang. Subsequently, these average values were input into our vegetation investment formula, leading to the estimated total investment of 106.77 × 10⁸ USD for achieving carbon neutrality in Xinjiang. For a detailed breakdown of these calculations, please refer to Table 1 below, which contains the source data for Figure 6.

Table 1 Measurement of profit and loss of vegetation to achieve carbon neutrality in Xinjiang as a whole and in each city on average from 2000 to 2020

Name	Cultivated land	forest land	grassland	Total profit and loss
Altay	29.1450	23.6300	58.2900	111.0650
Bayingolin	29.8460	2.8564	57.9184	90.6208
Bortala	15.3320	2.7199	14.4456	32.4975
Kashgar	5.0556	0.4378	2.3090	7.8024
Kizilsu Kirghiz	5.4621	0.2604	33.7806	39.5031
Tacheng	51.2975	5.6956	41.1344	98.1275
Yili	37.9541	19.4353	31.9592	89.3486
Aksu	-12.6221	-0.2940	-4.4250	-17.3411
Changji	-96.2672	-15.6762	-61.6508	-173.5942
Kumul	-11.3442	-1.2129	-34.3560	-46.9131
Hotan	-0.9576	-0.0672	-1.8214	-2.8462
Karamay	-133.5528	-1.8648	-43.4882	-178.9058
Turpan	-19.8450	-1.3230	-23.3702	-44.5382
Urumqi	-25.7544	-17.1696	-68.6742	-111.5982
Xinjiang	-126.2510	17.4277	2.0514	-106.7719

Comment 4: The introduction presents very long and dense paragraphs that blur the core message. In fact it seems that they are copied paragraphs interspersed. The Introduction section should be divided into logical paragraphs, each centered on a specific aspect of the topic. Please improve.

Response 4: Thank you for this valuable suggestion. We completely agree and have revised the Introduction section accordingly. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Comment 5: In the Materials and Methods section, it says: "Land use data were obtained from the China 30-meter land use dataset provided by Mr. Yang Jie's team from Wuhan University." This seems like an unscientific expression. I suggest changing it, although thanks should be given to the professor.

Response 5: Thank you for this valuable and constructive suggestion. We completely agree that the original phrasing was not sufficiently scientific. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 158:We have changed “ Land use data were obtained from the China 30-meter land use dataset provided by Mr. Yang Jie's team from Wuhan University” to “Land use data were obtained from the China 30-meter land use dataset”

Comment 6: Are the formulas for equations 1, 2, and 3 your own or from other authors?

Response 6: Thank you for your valuable comment. We would like to clarify that Methods 1, 2, and 3 are not our original proposals but were adopted from other authors. The original sources for these methods have been duly cited in the text.

Comment 7: How did you obtain the maps in Figure 4?

Response 7: Thank you for your question. For Figure 4, we used administrative boundary data from the Tianditu Service Center (https://cloudcenter.tianditu.gov.cn/dataSource) in ArcMap 10.8. We linked the city-level carbon footprint data to the boundary attributes and used a graduated display to visualize the data.

Comment 8: The partial discussion of the results appears in the Results section. I suggest including them in the Discussion section.

Response 8: Thank you for this valuable suggestion. We completely agree and have relocated parts of the discussion of the results from the Results section to the Discussion section. The specific changes have been highlighted in red in the newly uploaded manuscript.

Comment 9: No mention was made in the discussion of the scope or limitations of the study findings.

Response 9: We sincerely thank you for this valuable suggestion, which we have fully accepted. In response, we have added a discussion of the study’s limitations to the second paragraph of Section 4.3, “Recommendations for promoting carbon neutrality in Xinjiang.” We acknowledge that our classification of vegetation types was limited to primary categories (cropland, forestland, and grassland). In our future research, we plan to conduct more detailed investigations into the carbon sink capacity of specific vegetation types based on field conditions. This will enable the selection of more suitable vegetation for planting, thereby assisting Xinjiang in achieving its carbon neutrality goals. The specific revisions have been highlighted in red in the latest uploaded version of the manuscript. The detailed modification is as follows:

Ln 393-490: We have changed “ 4.1. Analysis of the causes of carbon footprint changes

4.2. Recommendations for promoting carbon neutrality in Xinjiang

4.3. Accelerating the Construction of Carbon Trading Market in Xinjiang

4.2. Accelerating the Construction of Carbon Trading Market in Xinjiang

4.3. Recommendations for promoting carbon neutrality in Xinjiang

Comment 10: I am not in favor of including acronyms in the conclusions.

Response 10: Thank you for this valuable comment. We completely agree and have revised the conclusion section by spelling out all abbreviations. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Comment 11: In the references section, the authors do not follow the journal's guidelines. Please review.

Response 11: Thank you for your valuable comment. We agree completely and have revised all references according to the journal’s format. The specific changes have been highlighted in red in the newly uploaded manuscript.

Comment 12: The current version is not ready for publication.

Response 12: We are grateful for the insightful comments provided. We have thoroughly addressed the feedback from all three reviewers, including yourself, in a point-by-point response. The latest version of the manuscript, incorporating these revisions, has been submitted for your consideration. We eagerly await your review.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear colleagues,

The paper "Study on the Changes of Vegetation Carbon Footprint and Influencing Factors in typical arid areas of Xinjiang, China" employs structural equation modeling (SEM) to analyze changes in carbon footprint in Xinjiang from 2000 to 2020. It takes into account the net ecosystem productivity (NEP), carbon emissions, and the carbon footprint (with human activities and vegetation factors). The authors propose a series of recommendations for achieving carbon neutrality in Xinjiang (in terms of investment to expand cropland, woodland, and grassland, as well as implementing vegetation expansion, improving carbon markets, and transforming carbon-source economies). It is a case study of best practices for a carbon neutrality strategy in arid ecosystems (this idea should be underlined as a main motivation for choosing the topic).

The research is logically structured and well argued, and the methodology is appropriate. However, the section on Literature Review is missing. There is an error in section numbering, as Section Three has been forgotten.

Figures should be better explained, and a section/subsection should not end abruptly with a figure or table.

The quality of English should be improved. Some sentences do not contain the classic subject and predicate:

“For carbon footprint studies, input-output analysis stands out as the most common research approach [18], life cycle Analysis [19], IPCC calculation methods, and logarithmic mean Divisia index methods [20]. For instance, one could utilize IPCC guidelines to create a model quantifying carbon emissions from energy use, aiming to analyze how these emissions are spatially distributed among different industries within China [21]. Accounting for carbon footprint of private consumption using an input-output model [22]. Figuring out the Carbon Footprints of Different Food Crops in China with Life Cycle Analysis [23,24].”

There are various typos, for instance: “and strictly implement ecological protection policies. Strictly implement ecological protection policies”.

In my opinion, it might become a valuable research paper after a suitable revision.

All the best.

Author Response

Comment 1: It is a case study of best practices for a carbon neutrality strategy in arid ecosystems (this idea should be underlined as a main motivation for choosing the topic).

Response 1: Thank you for your affirmation. Following your suggestion, we have now emphasized this point in the Introduction as a primary motivation for our study.

Comment 2: The research is logically structured and well argued, and the methodology is appropriate. However, the section on Literature Review is missing. There is an error in section numbering, as Section Three has been forgotten.

Response 2: Thank you for your valuable suggestions. We have fully addressed them by first, supplementing and improving the Introduction, and second, correcting the section numbering throughout the manuscript. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 56-115: We have changed “Carbon Footprint, a globally recognized method for quantifying carbon emissions, systematically exposes the core impact of human activities on the climate. By tracking greenhouse gas emissions throughout a product’s entire lifecycle, it reveals crucial indicators of emission dynamics. This lifecycle assessment-based model offers a scientific foundation for understanding the link between global warming and human actions, but also serves as an important data support for optimizing low-carbon decision-making and formulating differentiated emission reduction strategies by accurately identifying high-carbon emission links. However, there has been no uniform definition of carbon footprint in current academic circles, and the current understanding of carbon footprint can be summarized in two ways, one approach is to use carbon footprint to quantify the greenhouse gas emissions associated with a particular activity or entity [2,3]; A second interpretation of the carbon footprint considers it the extent of vegetative area needed for photosynthetic absorption of carbon emission resulting from the combustion of fossil fuels [4,5]. The former focuses on assessing the carbon emissions of a product or production activity at all stages of its life cycle, while the latter systematically measures the combined impacts of human activities on terrestrial ecosystems. This paper uses the second concept to do the carbon footprint research in Xinjiang. Currently, domestic and international research on carbon footprint, in terms of research content, mainly focuses on the measurement of carbon footprint, spatial and temporal patterns, as well as influencing factors. Relevant studies show that China's carbon footprint is increasing year by year [6]. Exhibiting a spatial pattern where values are higher in the north and lower in the south [7,8]. Carbon footprint spatial variations are significantly influenced by factors including the energy mix, economic development level, and technological research and development [9,10]. Reducing political and financial risks and increasing clean energy use can curb carbon footprint levels [11,12]. In addition, studies have examined the ecological impacts of carbon emissions by analyzing the breadth and depth of carbon footprints [13]. In terms of research objects, including the carbon footprint of different products and industries [14,15]. Such as revealing the trend of various carbon footprints in China [16,17]. For carbon footprint studies, input-output analysis stands out as the most common research approach [18], life cycle Analysis [19], IPCC calculation methods, and logarithmic mean Divisa index methods [20]. For instance, one could utilize IPCC guidelines to create a model quantifying carbon emissions from energy use, aiming to analyze how these emissions are spatially distributed among different industries within China [21]. Accounting for carbon footprint of private consumption using an input-output model [22]. Figuring out the Carbon Footprints of Different Food Crops in China with Life Cycle Analysis [23,24]. By integrating input-output and life-cycle analysis to measure regional carbon footprints and assess interregional transfers in China, we establish a theoretical basis for greening traditional farming methods [25,26]. Although some progress has been made in carbon footprint research, in our earlier work [27], we evaluated the potential of Xinjiang’s vegetation to offset regional anthropogenic CO₂ emissions; however, a quantitative assessment of the exact vegetation cover (area) required to reach net-zero emissions remains lacking. It still needs to be further deepened. Currently, most of the studies on the spatial and temporal distribution of regional carbon footprints have focused on exploring the spatial correlation of the footprints, while the driving factors behind the footprints have been understudied. In addition, many studies analyzing carbon footprints focus mainly on carbon dioxide emissions caused by energy consumption, while ignoring carbon emissions caused by other production activities, which may lead to biased results. In view of this, in order to more accurately reflect the ecological carrying capacity of a region and the impact of human economic activities on the natural environment, we need to improve and supplement these research methods. In this study, we chose to include the total carbon emissions released by human production activities, such as agriculture, industry and tourism, and the productive land area needed to study the carbon footprint of Xinjiang. The annual vegetation NEP data from 2000 to 2020 are used as the level of vegetation carbon sequestration in Xinjiang, and combined with the carbon emission data, the carbon footprint of Xinjiang is calculated to analyze the spatial and temporal changes of Xinjiang's carbon footprint and its driving factors. In this way, we provide scientific references for Xinjiang to realize the “double carbon” goal and formulate refined carbon emission reduction policies in the future. ” to “As an internationally recognized quantitative tool for carbon emissions, the carbon footprint serves as a critical metric for tracking greenhouse gas (GHG) emissions throughout a product’s entire life cycle. It systematically elucidates the core mechanisms by which human activities impact the climate system. Currently, there are two primary perspectives on the carbon footprint. The first defines it as the total amount of greenhouse gases emitted directly or indirectly by a specific activity or entity [2, 3]; The other perspective views the carbon footprint as the vegetation area required to absorb these carbon emissions [4, 5]. The former approach focuses on assessing the quantity of carbon emissions at each stage of a product’s or activity’s entire life cycle. In contrast, the latter systematically measures the area of terrestrial vegetation ecosystems needed to sequester these emissions. This study adopts the second concept to investigate the carbon footprint of Xinjiang. Current research on carbon Footprint, both domestically and internationally, primarily focuses on three aspects: its quantification, spatiotemporal patterns, and influencing factors. Relevant studies indicate that China’s carbon footprint has shown a year-on-year increasing trend [6]. Concurrently, it exhibits a spatial pattern of being higher in the north and lower in the south [7,8]. Factors such as energy structure, level of economic development, and technological have been found to significantly influence the spatial variation of the carbon footprint [9,10]. Furthermore, it has been suggested that its level can be curbed by reducing political and financial risks [13] and increasing the use of clean energy [14]. Moreover, with respect to the objects of study, investigations have assessed the ecological repercussions of carbon emissions through an analysis of the breadth and profundity of the carbon footprint [15]. The scope of such research encompasses the carbon footprints of disparate products and industrial sectors [16], exemplified by the revelation of evolutionary trends in the carbon footprint of food consumption [17]. From a methodological standpoint, the principal analytical instruments comprise Input-Output Analysis (IOA) [18], Life Cycle Assessment (LCA) [19], and the Logarithmic Mean Divisia Index (LMDI) method [20]. Illustrative applications include the construction of energy consumption-based carbon emission models using the IPCC methodology to investigate industrial spatial carbon footprints [21], the utilization of input-output models (MIRO) for the accounting of private consumption-induced carbon footprints [22], and the estimation of various crop carbon footprints via LCA, which furnishes a theoretical foundation for the green transformation of conventional cultivation systems [23,24]. Furthermore, some studies have combined Input-Output Analysis with LCA to measure the carbon footprint of various regions in China and to analyze inter-regional carbon transfers [25,26]. In the research on the spatiotemporal distribution of regional carbon footprints, most studies have concentrated on exploring spatial correlations, while the underlying driving factors have been insufficiently investigated. Therefore, future research needs to further delve into the causes of carbon footprint changes and explore feasible carbon reduction implementation methods.

Comment 3: Figures should be better explained, and a section/subsection should not end abruptly with a figure or table.

Response 3: Thank you for this valuable suggestion. We have fully addressed your comments by making appropriate modifications to both the content and the figures in section 3.2 of the Results and Analysis, and by providing a deeper explanation for them. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 265-282: We have changed “3.2. Carbon Footprint Spatial Changes

From 2000 to 2020, the vegetation carbon footprint in Xinjiang showed an overall increasing trend (Fig. 3). In 2000, the total area of the vegetation carbon footprint in Xinjiang was 30.41×10⁴ km², while in 2020, this area increased to 104.48×10⁴ km², which is an increase of about 3.44 times. There are significant spatial differences (Fig. 4), generally showing more in the north and less in the south. Among the various cities in Xinjiang, three regions of Changji , Urumqi and Kelamayi City have the most significant growth in their carbon footprints, making them the three regions with the largest carbon footprints in Xinjiang. Among them, Urumqi, as the capital of Xinjiang, the carbon footprint of Urumqi grows from 6.18 × 10⁴ km² in 2000 to 7.91 × 10⁴ km² in 2020, an increase of about 27.9%. The growth of Urumqi's carbon footprint is related to its position as a regional political, economic, and cultural center, with urban expansion and industrial development being the main sources of increased carbon emissions. Karamay city, as an important oil industry base in Xinjiang, has reduced its carbon footprint from 9.89 × 10⁴ km² in 2000 to 4.39 × 10⁴ km² in 2020, a reduction of about 55.6%, led by the support of the local government. Karamay has become the only region in Xinjiang with a reduced carbon footprint over a 21-year period, and this significant reduction is related to the transformation and upgrading of its oil extraction and processing activities. The carbon footprint of Changji a region ranked 2nd in terms of GDP across all states in Xinjiang, was 1.71×10⁴ km² in 2000, and by 2020, this figure had grown to 25.86×10⁴ km², an increase of about 15 times. Changji is the region with the fastest growing carbon footprint in Xinjiang, and this significant growth is related to the accelerated industrialization, increased energy consumption, and population growth in the Changji region.” to “As shown in Fig. 3, the carbon footprint of 14 cities in Xinjiang exhibited an overall increasing trend to varying degrees from 2000 to 2020. The changes can be classified into three distinct patterns. First, Altay, Urumqi, and Turpan were classified as the slow-increase type, with their carbon footprints rising from 0.14, 6.18, and 2.27×10⁴ km² in 2000 to 0.59, 7.91, and 4.43×10⁴ km² in 2020, respectively. Second, ten cities—Aksu, Bayingholin, Bortala, Changji, Hotan, Hami, Kashgar, Kizilsu Kirgiz, Tacheng, and Yili—belonged to the significant-increase type, with their carbon footprints escalating from 2.64, 2.19, 0.13, 1.71, 0.35, 1.08, 1.87, 0.20, 1.32, and 0.41×10⁴ km² in 2000 to 9.11, 6.17, 1.79, 25.86, 11.05, 16.24, 6.14, 2.43, 4.11, and 4.26×10⁴ km² in 2020, respectively. Third, Karamay was the only city that exhibited a slow-decrease type, with its carbon footprint declining from 9.89×10⁴ km² in 2000 to 4.39×10⁴ km² in 2020.

Overall, the total carbon footprint in Xinjiang showed a significant growth trend, increasing from a total area of 30.41×10⁴ km² in 2000 to 104.48×10⁴ km² in 2020, representing an approximate 3.44-fold increase. Spatially, the carbon footprint distribution in Xinjiang was notably heterogeneous. Although the total footprint was generally larger in the northern part than in the southern part, the growth rate in the southern region was significantly faster than that in the northern region.”

Comment 4: The quality of English should be improved. Some sentences do not contain the classic subject and predicate.

Response 4: Thank you for your valuable feedback. We have fully accepted it. Based on our point-by-point responses to the comments from you and the other two experts, we have thoroughly reviewed and polished the manuscript. The specific revisions have been highlighted in red in the newly uploaded version.

Comment 5: “For carbon footprint studies, input-output analysis stands out as the most common research approach [18], life cycle Analysis [19], IPCC calculation methods, and logarithmic mean Divisia index methods [20]. For instance, one could utilize IPCC guidelines to create a model quantifying carbon emissions from energy use, aiming to analyze how these emissions are spatially distributed among different industries within China [21]. Accounting for carbon footprint of private consumption using an input-output model [22]. Figuring out the Carbon Footprints of Different Food Crops in China with Life Cycle Analysis [23,24].” There are various typos, for instance: “and strictly implement ecological protection policies. Strictly implement ecological protection policies”.

Response 5: Thank you for this valuable suggestion. We completely agree and have revised and improved the aforementioned issues in the Introduction section. The specific changes have been highlighted in red in the newly uploaded manuscript. The detailed revisions are as follows:

Ln 56-115: We have changed “For carbon footprint studies, input-output analysis stands out as the most common research approach [18], life cycle Analysis [19], IPCC calculation methods, and logarithmic mean Divisia index methods [20]. For instance, one could utilize IPCC guidelines to create a model quantifying carbon emissions from energy use, aiming to analyze how these emissions are spatially distributed among different industries within China [21]. Accounting for carbon footprint of private consumption using an input-output model [22]. Figuring out the Carbon Footprints of Different Food Crops in China with Life Cycle Analysis [23,24].” There are various typos, for instance: “and strictly implement ecological protection policies. Strictly implement ecological protection policies” to “Moreover, with respect to the objects of study, investigations have assessed the ecological repercussions of carbon emissions through an analysis of the breadth and profundity of the carbon footprint [15]. The scope of such research encompasses the carbon footprints of disparate products and industrial sectors [16], exemplified by the revelation of evolutionary trends in the carbon footprint of food consumption [17]. From a methodological standpoint, the principal analytical instruments comprise Input-Output Analysis (IOA) [18], Life Cycle Assessment (LCA) [19], and the Logarithmic Mean Divisia Index (LMDI) method [20]. Illustrative applications include the construction of energy consumption-based carbon emission models using the IPCC methodology to investigate industrial spatial carbon footprints [21], the utilization of input-output models (MIRO) for the accounting of private consumption-induced carbon footprints [22], and the estimation of various crop carbon footprints via LCA, which furnishes a theoretical foundation for the green transformation of conventional cultivation systems [23,24]. Furthermore, some studies have combined Input-Output Analysis with LCA to measure the carbon footprint of various regions in China and to analyze inter-regional carbon transfers [25,26]. In the research on the spatiotemporal distribution of regional carbon footprints, most studies have concentrated on exploring spatial correlations, while the underlying driving factors have been insufficiently investigated. Therefore, future research needs to further delve into the causes of carbon footprint changes and explore feasible carbon reduction implementation methods.”

Comment 6: In my opinion, it might become a valuable research paper after a suitable revision.

Response 6: Thank you for your positive feedback and detailed comments. We have responded to each of the suggestions from you and the other two reviewers, and have uploaded a revised manuscript. We look forward to your further response.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Dear authors,

You have done good work in the revision of the manuscript and have included all the possible modifications in the present manuscript. now the manuscript is suitable for publication.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have followed most of the recommendations given. Therefore, as a consequence of the changes and corrections incorporated in this new version, the scientific quality of the manuscript has considerably improved. Then, it can be accepted.

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Study on Changes in Vegetation Carbon Footprint and Its Influencing Factors in Xinjiang, a Typical Arid Region of China

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