Next Article in Journal
Cost-Benefit Analysis and Model Preference of Public Transportation in Can Tho City, Vietnam
Next Article in Special Issue
Assessing the Spatio-Temporal Dynamics of Land Use Carbon Emissions and Multiple Driving Factors in the Guanzhong Area of Shaanxi Province
Previous Article in Journal
A Novel Green Ocean Strategy for Financial Sustainability (GOSFS) in Higher Education Institutions: King Abdulaziz University as a Case Study
Previous Article in Special Issue
Slope Scaling Effect and Slope-Conversion-Atlas for Typical Water Erosion Regions in China
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Progress and Hotspots of Research on Land-Use Carbon Emissions: A Global Perspective

College of Public Administration, Huazhong Agricultural University, Wuhan 430700, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(9), 7245; https://doi.org/10.3390/su15097245
Submission received: 27 March 2023 / Revised: 19 April 2023 / Accepted: 24 April 2023 / Published: 27 April 2023
(This article belongs to the Special Issue Land Use/Cover Change and Its Environmental Effects)

Abstract

:
Carbon emissions from land use change are the leading causes of the greenhouse effect. Exploration of the progress and hotspots of research on land-use carbon emissions (LUCE) is crucial for mitigating global climate warming. However, a comprehensive and systematic review of LUCE research from a global perspective is still lacking. We used the WoS Core Collection Database to analyze the current status of research on LUCE from a global perspective with the aid of a bibliometrix tool, aiming to reveal research hotspots and future development trends. We found that (1) the process of LUCE research has gone through a nascent exploration stage (1992–2001), a problem-focused stage (2002–2011), and a prosperous development stage (2012–2022) under different policy orientations. European and North American countries prioritize LUCE research more than others. (2) Overseas research hotspots mainly focus on the climate effects of land-use change, the impact of deforestation and fire on carbon stocks, the impact of soil organic carbon stocks on climate change and biodiversity, and agricultural carbon emissions. Research hotspots in China mainly focus on the study of the influencing factors of land-use carbon emissions, the path to achieving the dual carbon goal, and the transition to a low carbon economy. (3) Research frontiers show that China mainly researches low-carbon land use intensification in the context of a “dual carbon” strategy; carbon emission reduction based on energy transition; and the multi-dimensional, dynamic, and accurate tracking and monitoring of land-use carbon emission systems using remote sensing satellite data. Other countries have shifted from measuring historical land-use carbon emissions, deforestation, degradation and fire carbon emissions to biomass combustion and global warming mitigation research. This study enhances the depth and breadth of LUCE research, which can provide a theoretical foundation and scientific reference for subsequent research on LUCE.

1. Introduction

The international community recognizes global warming as a crucial environmental issue [1]. Historical data show that warming caused by human activities will continue for hundreds to thousands of years from the pre-industrial era to the present, with socio-economic development consuming large amounts of fossil fuels, leading to a significant increase in greenhouse gas concentrations while satisfying the required products and services. As a result of human activities, the global average surface temperature has increased by about 1 °C above pre-industrial levels. With the dramatic increase in global population and urbanization, global warming is becoming more pronounced and could lead to problems such as melting glaciers, more frequent natural disasters, and imbalances in ecosystems. Studies have shown that excessive increases in atmospheric carbon dioxide concentrations produce a greenhouse effect [2] and that land use change is one of the leading causes of the greenhouse effect [3]. Therefore, how to reduce and effectively control CO2 emissions has become a key guiding principle for environmental policy in countries around the world.
Following the Intergovernmental Panel on Climate Change (IPCC), land-use change was the second-leading source of CO2 emissions in 2010, accounting for roughly 11% [4]. Land use change directly affects the carbon balance of terrestrial ecosystems and indirectly affects regional carbon emission levels, thus significantly influencing the global carbon cycle process [5,6]. Both a source and a sink of carbon are engaged in land use change. Scholars mostly discuss carbon emission mechanisms from the perspective of the relationship between land cover characteristics, the natural environment, human activities, and the carbon cycle. One category is the physiological metabolic mechanism or natural disturbance process that affects the photosynthesis, respiration, growth, and decomposition rate of plants, mainly by the natural physiological metabolism of land; the other category is the disturbance and restoration mechanism mainly by the participation of human activities, including the change of land cover caused by changing land use and management practices [7]. In contrast, human socioeconomic activities such as fossil fuel use, industrial production activities, and the production and disposal of domestic waste are defined as anthropogenic disturbances of the carbon cycle in a broad sense and have become the main source of land-use carbon emissions [8]. Land-use carbon emissions refer to the processes, activities and mechanisms by which the land releases carbon dioxide to the atmosphere during its changes and the human production activities it hosts, and can be divided into direct and indirect carbon emissions.
Land use and carbon emissions research has yielded a wealth of results. Researchers have examined the spatial patterns of LUCE based on the carrying and ecological functions of land [9,10]. They have identified that different types of land function as carbon sources and sinks accordingly [11], such as forests, grasslands, and industries [12,13], and that changes in the management practices (e.g., irrigation, tillage, fertilization, etc.) of specific land use types (with a focus on agricultural land) can result in changes in global carbon fluxes and stocks [14], accounting for soil carbon stocks and carbon fluxes under different land use practices, which are measured using model estimation, sample plot inventory, and remote sensing techniques. With the development of urbanization, some researchers explored how the regional carbon cycle was affected by land use type, structure, scale, and intensity [15,16], predicted the peak carbon under different scenarios concerning the relationship between population, economy, technology, construction land, and carbon emissions [17,18,19], and proposed carbon reduction from energy transformation [20,21]. The choice and impact of market policies are discussed based on carbon trading, offset and sequestration cost–benefit analysis and spatial mechanism trade-offs, and the analysis of carbon emissions and the social costs of emission reduction, social welfare benefits from emission reduction behaviors, the emission reduction efficiency of different policies, and policy choices [22,23] is more focused. Research on carbon quota allocation, price trading mechanisms and the socio-economic benefits derived from carbon trading market behavior has become an important topic in urban carbon emission reduction research [24,25]. The above studies have enriched the LUCE research on different spatial scales and formed a research lineage of “emission mechanism–model measurement–driving effect–reduction strategies”. LUCE research needs to be more transparent and complex, though, because natural and human factors, such as economic, political, climatic, and soil, influence land use change. Researching land-use carbon emissions not only provides a scientific reference for global warming mitigation but also has important practical value for the assessment of the carbon emission effect of land use planning, land-use carbon emission reduction, and its optimal regulation.
In recent years, there are more and more papers on carbon emissions research, and many scholars have reviewed and summarized carbon emissions on a micro level; for example, a review of carbon footprints [26], the carbon emissions of commercial buildings [27], and China’s carbon emission trading policies [28]. Most of the reviews are based on Citespace software for visualization studies, but with the development of information visualization technology, Bibliometrix software based on the R language environment is gradually being applied in scientific research; its visualization is easy for the reader to understand at a glance. A systematic review of the existing related literature can help to grasp the development pulse and frontier trends of carbon emission research. However, there is a lack of systematic reviews and an in-depth integration of the research hotspots, research trends, and the development process of land-use carbon emissions from a global perspective.
Given the above, we used bibliometrix software to conduct a comprehensive review and analysis of LUCE-related articles from 1992 to 2022, aiming to systematically analyze the current status of LUCE research and research hotspots in the past 30 years from a global perspective by combining visualized knowledge mapping, and to provide subsequent research and relevant policymakers with an understanding of the development background and research on land-use carbon emissions trends. The rest of this paper is organized as follows: Section 2 introduces the data sources and research methods of this study; Section 3 presents the basic analysis of land-use carbon emissions research, including the number of publications and citations, academic journals, author collaboration networks, research institutions, and national productivity; Section 4 analyzes the research hotspots of land-use carbon emissions and their evolution. Finally, in the Section 5, we propose the future research directions and main research contents.

2. Materials and Methods

2.1. Data Sources

The Web of Science is the world’s largest and most comprehensive academic literature database, covering natural sciences, social sciences, humanities, and other subject areas, with a powerful citation search function and strict literature quality assurance. We exported the research data from the core collection of Web of Science on 31 March 2022, and each data record primarily contains the author, title, abstract, and relevant literature citations. Synthesizing the available official reporting literature [1], we selected “land use”, and “carbon emission” as research keywords. The search method was retrieval subject as TS = (“land use*” AND “carbon emission*”), which can ensure the specific keywords of this study are searched in the subject search and guarantee the quality of the study. The document type was only restricted to “Article”, and the language was restricted to “English”. Because the earliest LUCE-related literature was recorded in 1992, we selected “1992–2022” as the search time to ensure the completeness of LUCE-related literature and obtained a total of 1278 pieces of literature data. To eliminate the interference of irrelevant literature and ensure the accuracy and completeness of papers in the field of LUCE research, we manually screened out the literature that did not belong to the field of land use and carbon emissions, and the screening criteria were to read the title and abstract of the literature carefully. If the title and abstract could not distinguish whether the literature was related to LUCE, the full text was read separately, and the opinions of relevant experts were sought before deciding whether to include the literature in the study. We finally obtained 1092 effective records by de-duplication and the removal of irrelevant data for bibliometric analysis to develop preliminary knowledge of LUCE research.

2.2. Research Method

Bibliometrix is a scientific bibliometric tool built using the R language environment and developed by Aria and Cuccurullo [29]. It is more flexible than other tools and integrates several bibliometric tools’ network analysis and visualization functions. The bibliometrix toolkit based on the R language can be used for the whole process of scientific literature measurement and visual presentation. It can import and process literature information from SCOPUS, Web of Science, PubMed, and other databases, statistically analyze relevant scientific literature indices, construct data matrices, conduct research and visualization processing in co-citation, coupling, collaboration analysis, and co-word analysis, and complete a complete set of literature information analysis and visualization of the results. However, in terms of its visualization effect, it needs to be further improved and can be combined with other packages of R language (ggplot2 package) and VOSviewer software to beautify the scientific visualization. Bibliometrix software launches interactive web pages by entering biblioshiny commands into the R language program. The installation and operation steps were as follows: firstly, we needed to download and install the latest version of RStudio and the R language toolkit (URL: https://cran.r-project.org/ and http://www.rstudio.com accessed on 1 April 2022); secondly, we opened RStudio and typed the command (install. packages (“bibliometrix”)) into the control interface window to complete the installation of the bibliometrix program; thirdly, after successful installation, we could successfully invoke the bibliometrix functions with the library (bibliometrix) command.
In this paper, the bibliometrix and biblioshiny software packages were used to analyze and visualize the research status and research trends in the field of LUCE. We used the core collection of Web of Science as a bibliometric database. We detected and drew the visual knowledge networks about the number of published and cited studies, research journals, authors, teams, institutions and countries, research keywords, and themes of LUCE research using bibliometrix. Based on the tools of co-occurrence analysis, cluster analysis, and thematic evolution analysis of biliometrix software, we identified the topic hotspots and research frontiers. Then, we presented the future directions of LUCE research. The flowchart of bibliometric analysis is shown in Figure 1.

3. Basic Analysis of LUCE Research

3.1. The Number of Publications and Citations

We analyzed the number of publications and citations in the field of LUCE research from 1992 to 2022 (Figure 2). The bar chart shows that the number of publications in the field of LUCE research has increased exponentially. The line chart indicates that the average citations per paper fluctuate. The LUCE research is roughly divided into three stages from 1992 to 2022 based on the above features: (1) Preliminary exploration stage (1992–2001), where the average number of publications per year is only 3.3, with an average number of citations per year of 326.0. This is the beginning stage of LUCE, with fewer articles and citations. During this period, international scholars mainly concentrated on research on forest carbon stock, forestry carbon emission reduction, and carbon emission dynamics due to land use change. These studies provide a solid foundation for subsequent research. (2) Problem-focused stage (2002–2011): the average number of publications per year is 20.2, with an average number of citations per year of 2327.9. Throughout the whole stage, the academic community paid greater attention to LUCE, transitioning from auxiliary research to an independent research topic. The number of publications grew, and the number of citations reached its highest. During this period, with the diversification of research methods and the maturity of research techniques, the research mainly covers the impact of global land use on the carbon cycle, carbon emissions from agroecosystems, carbon management in forests, biofuels, soil organic carbon, and other issues. (3) Prosperous development stage (2012–2022): the average number of annual publications is 77.91, while the average number of annual citations is 1951.42. As 2012 is a critical point in time for the end of the first commitment period of the Kyoto Protocol and the discussion of post-2020 measures to address climate change, the number of publications increased dramatically. In 2015, with the adoption of the Paris Agreement at the Paris Climate Change Conference, how to mitigate global warming by reducing land-use carbon emissions sparked widespread international interest. From the viewpoint of human activities, research on carbon emissions reduction and low-carbon optimization increased significantly and is still flourishing.
The appearance of highly cited articles suggests that the research has significantly impacted the subsequent investigation. As a result, it will promote the advancement of that research. Therefore, we summarized the contributions of highly cited literature on LUCE in Table 1.

3.2. Academic Journals

With the support of several prominent academic journals, the development of LUCE research can continue. We listed the top ten journals regarding the number of articles on LUCE research in Table 2. These journals have published 308 papers, representing 28.21% of all LUCE research publications. In terms of printed journals, the journal with the most published articles is Environmental Research Letters, with 50 articles, followed by the Journal of Cleaner Production and Global Change Biology, with 43 and 40 papers. The top ten journals are all high-quality journals with an average impact factor of 7.896. It indicates that the international mainstream academic community is paying more attention to the field of LUCE. In Figure 3, the cumulative number of articles in the field of LUCE in each journal over time is shown. Forest Ecology and Management was the first to publish a LUCE-related article in 1992, increasing from 1 in 1992 to 24 in 2022. Interestingly, the productivity of the journals was relatively weak until 2015, but then the production increased substantially between 2015 and 2022, especially the Journal of Cleaner Production and Sustainability.

3.3. Research Authors

We listed the top twenty most influential authors in the field of LUCE research. Figure 4 shows that Houghton RA and Defries RS started their research on LUCE earlier, in 1999, demonstrating that they established the research’s theoretical foundations. Houghton RA published an article titled “Emissions of carbon from forestry and land-use change in tropical Asia” in Global Change Biology in 1999, which measured the net carbon emissions from forestry and land use change in South and Southeast Asia through a bookkeeping model [40]. This study is crucial for evaluating how human activity affects the global carbon cycle. In terms of total citations, Houghton RA has the highest total number of citations (7414); the paper “Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land-Use Change” was published in Science in 2008, with 2967 citations. The study emphasizes the value of using waste as biofuels, arguing that an effective system must ensure the use of raw materials for biofuels (e.g., waste, carbon-poor land) [30]. In terms of the number of papers published, the top four authors are Ciais P, Liu Y, Houghton RA, and Zhang Y, with 22 papers, 21 papers, 20 papers, and 20 papers, respectively. The main research direction of Ciais P is historical CO2 emissions from land use/land cover change and its uncertainty, enriching the applied research of LUCE. Since 1998, authors mainly concentrated on Europe and the United States, and Chinese scholars began to pay attention to LUCE research in 2002. After 2008, the number of publications on LUCE research exploded, which indicates academics have widely valued LUCE research, which has inspired more influential studies.
To understand collaborative communication between authors, we drew a collaborative network diagram of authors, which can reflect the composition of research teams. The distance and connection density between teams can reflect the intensity of cooperation among research teams, and the number of nodes in the teams can reflect their size. It can be seen from Figure 5 that the authors engaged in land-use carbon emission research have formed seven teams: Team 1 includes Ciais P, Houghton RA, Sitch S, Pongratz J, Arneth A, and other members. They concentrate on measuring carbon emissions from land use and land-cover change [41,42], carbon emissions from deforestation and fire [43], and the terrestrial carbon cycle [33]; Team 2 includes van der Werf GR, Randerson JT, Defries RS, Morton DC, Hansen MC, and other members. They focus on the estimation of global fire emissions [36], carbon emissions from biomass burning [44,45], fire emissions from deforestation in the Amazon Basin [46], and the role of forest loss in the global carbon cycle in South America [47]; Team 3 includes Huang XJ, Chuai XW, Zhao RQ, Liu Y, Zhang Y, and other members. They select China or a province as the study area, measure carbon emissions from land-use change and management [13] and its influencing factors [48], spatial and temporal changes in carbon footprint [49,50], and low-carbon land management effects [51]; Team 4 mainly includes Li Y and Xia CY. They contributed to the quantitative study of the spatial pattern of urban carbon metabolism [52], the impact of city size on carbon metabolism [53,54], and the integrated impact of land-use change on carbon balance [55]; Team 5 mainly includes Aragão LEOC and Shimabukuro YE. They estimate carbon emissions from deforestation and fire in the Brazilian Amazon through modeling [15,56]; Team 6 mainly includes Fearnside PM and Graca PMLD. They work on the impact of land-use change on global warming [57], the impact of land-use change on biomass and carbon fluxes [58], and the climate effects of deforestation in the Amazon region [59]; Team 7 mainly includes Herold M and Verchot L. They focus on emission trends and their uncertainties in the land use sector in the tropics [60], as well as the integrated monitoring of reducing emissions from deforestation and forest degradation [61]. Generally speaking, team cooperation is relatively scattered, and the degree of connection between the teams is relatively low. Overall collaboration among authors is infrequent, cross-national exchanges among authors are generally lacking, and there are few representative large-scale collaborative networks.

3.4. Research Institutions

We counted the top ten international research institutions that published several articles in LUCE research (Table 3). These research institutions issued 292 pieces of literature, representing 26.74% of the literature. The Chinese Academy of Sciences published the most significant number of publications in the field of LUCE research, followed by the University of Maryland, Woods Hole Research Center, and the University of Exeter. The study suggests that China, the United States (the US), and other, European countries have more substantial research power, while other countries and regions have a relatively weaker research level. Notably, China is the only country in developing countries with representation in the top 10 most influential research institutions, the most representative of which is the Chinese Academy of Sciences, which has been organizing and conducting LUCE-related research for a long time.

3.5. Research Country and Scientific Production

We plotted the scientific production of LUCE research to examine the level of investment by different countries. The top 10 countries in terms of scientific productivity are shown in Figure 6, including four European countries (the UK, Germany, Netherlands, and France), three American countries (the US, Canada, and Brazil), two Asian countries (China and Indonesia), and one Oceanian country (Australia). The fact that most of the world’s scientific productivity is focused in Europe and North America indicates that developed countries attach great importance to LUCE. Many of them have generally experienced peak carbon. Developing countries have greater urgency and difficulty achieving carbon emission neutrality targets due to the limitations of relevant technology, capital, and human resource power.
From the type of country, the countries with higher scientific productivity are mainly concentrated in countries with both developed agriculture and livestock, such as the United States (906 articles), China (794 articles), the United Kingdom (332 articles), and Australia (191 articles), while Germany, Canada, and Japan, where agriculture is more developed, published 187, 83, and 71 articles, respectively. Finland and Denmark, where animal husbandry is more developed, published 113 and 38 articles, respectively. This indicates that different countries pay different levels of attention to research in the field of LUCE. With the development of agriculture and animal husbandry, they play an increasingly important role in carbon reduction activities. Studies have shown that agricultural production activities have become one of the important sources of GHG emissions, among which livestock is the main GHG emission source from agriculture. Therefore, carbon emission reduction in agriculture and livestock is essential to achieve carbon neutrality.
This paper creates a network of collaboration amongst the ten countries that have conducted the most research on LUCE to examine international collaboration and exchanges (Figure 7). We can draw two conclusions: (1) Australia, the US, the UK, and other nations engage in extensive international collaboration; and (2) European countries also have more opportunities for cooperation and communication on LUCE. The number of LUCE-related articles in European countries is equal to that in other countries, especially in the European Union (EU).
The socioeconomic background of EU countries causes the high level of LUCE there. It is predicted that the average land–atmosphere fluxes in the EU will be equivalent to 3.1% to 6.9% of the total fossil fuel emissions in the EU between 1990 and 2100 [62]. European nations implemented land management measures to boost agricultural productivity after World War II. Mechanization and the extensive use of synthetic fertilizers has made it possible to farm on poor and unstable soils. The agricultural landscape in Europe transformed after the 1950s due to agricultural intensification and growth [63]. Intensive farming alters natural ecosystems and disturbs the soil environment, leading to significant soil carbon loss, which in turn can also lead to poor soil quality and low crop productivity. Therefore, governments in the European Union and academics in the EU are increasingly interested in LUCE research. Two crucial policies play a massive role in driving Europe’s historical carbon reduction process. One is the European Union Emissions Trading System, which is regarded as the most powerful market tool for lowering greenhouse gas emissions (GHG); the other is the European Climate Law, which pledges the EU to eliminate GHG by a further 55% from 1990 levels by 2030 and to become carbon neutral in the land use, forestry, and agricultural sectors by 2035. It shows that the EU has made a significant effort to mitigate global climate change.

4. Analysis of Research Hotspots and Thematic Evolution

4.1. Analysis of Keywords Co-Occurrence Network

Keywords are a concise summary and distillation of an article’s central topics. When two or more keywords occur on the same paper simultaneously, it is known as keyword co-occurrence. We only extracted the top forty keywords from the keyword co-occurrence network and used the co-occurrence feature in VOSviewer software to generate the keyword co-occurrence graph (Figure 8). Each node reflects a keyword from the chart, and the node’s size indicates how frequently the keyword appears. Two keywords are related if they are on the same line. It is commonly believed that the thicker the lines, the more closely the subject content is related.
As shown in Figure 8, the keywords involved in the field of LUCE that appear more frequently are Carbon emission, Land-use change, Land use, Climate-change, Deforestation, Carbon sequestration, REDD, China, Carbon, and Agriculture, indicating that LUCE have been widely studied with reference to climate change, deforestation, carbon sequestration, agriculture, etc., and its research has made significant progress in depth and breadth. The primary greenhouse gas and aerosol emissions (biogeochemical impacts) resulting from land use at the global level are CO2, N2O, and CH4 emissions [18,64]. Deforestation, degradation, and other natural vegetation conversions to agricultural land are the leading causes of CO2 emissions to the atmosphere. Human activities such as land use change and climate change remove CO2 from the atmosphere through reforestation following agricultural abandonment and the restoration of non-forest vegetation, afforestation, and forest regeneration just after timber harvest [65]. Using N fertilizer, handling manure, and burning biomass are the primary sources of N2O emissions [66]. Enteric animal fermentation, incomplete biomass combustion, and rice farming are the primary sources of CH4 emissions.
Additionally, the production of crops, changes in forestry and land use, and other elements contribute to agricultural carbon emissions. Some studies have shown that carbon emissions from agriculture now account for 30% of all anthropogenic carbon emissions worldwide. Therefore, it has also made carbon reduction in agriculture a critical issue. South Asia and sub-Saharan Africa, in particular, are experiencing rapid population growth, while many food-producing regions of the world are threatened by climate change. They eventually started to develop new kinds and increase the use of chemical fertilizers to ensure a sufficient food supply, resulting in increasing land degradation and soil salinization, which impacted the ecosystem’s carbon cycle globally.

4.2. High-Frequency Keyword Cluster Analysis

This paper conducted a cluster analysis of high-frequency keywords to examine LUCE research hotspots (Figure 9). It eventually obtained 40 keywords, forming five clusters. The larger the circle, the more frequently the keywords appear. We generated five clusters by using the keyword clustering function, and each cluster represents a LUCE hotspot. Among them, the most commonly appearing keywords are Land-use change, Carbon emission, Deforestation, Carbon sequestration, and Agriculture. It indicates that these five are the hotspots of LUCE research, and the core research contents of these five hotspots are specifically described below.
Cluster 1 focuses on carbon cycle mechanisms for global climate mitigation. The main keywords include Land-use change, Climate-change, Tropical forests, Greenhouse-gas emissions, Climate-change mitigation, Sustainable development, Carbon footprint, Global warming Mitigation, Life cycle assessment, and the Carbon cycle. Several studies have indicated that the climate effects of land-use change and climate change can provide approaches for curbing global warming or regulating local climates, thereby improving human living circumstances [67]. Methodologically, Dynamic Global Vegetation Models are commonly used to evaluate GHG removal and emissions from vegetation and soils due to land-use change and climate change, with reliable and steadily expanding estimates [68,69]; bookkeeping models are used to assess anthropogenic GHG emissions and removals from different land use changes and forestry events [67,70,71]; the dedicated Land Use Model Intercomparison Project includes simulations of alternative land use, land-use change, and climate change to determine the potential of land use and land-use change for climate change mitigation under different future climate evolutions [72]. In short, there has been significant progress in the field of LUCE research recently, which provides a practical approach to developing the United Nations Sustainable Development Goals. The range of methodologies for assessing the climate effects of land-use change and climate change has expanded; a greater understanding of land–atmosphere processes, particularly across scales, and synergies between land-use change and climate effects, has developed.
Cluster 2 concentrates on regional carbon sources and sink patterns due to land use change. The main keywords include Urbanization, Sustainability, Land use, China, Carbon emissions, Carbon balance, Carbon sink, Biomass, and Bioenergy. Land-use change affects the Earth’s carbon sources and carbon sinks by changing human-made surface ecosystems [73]. When deforestation transforms land into grassland and agricultural land, it acts as a carbon source; land use practices such as afforestation, reforestation, and improved forest management can contribute to carbon storage in forests. However, since land-use change is affected by human factors (economic, political, and cultural concepts) and natural factors (terrain, climate, and soil conditions), studying the driving mechanism of LUCE has been a popular topic of academic discussion. Research has revealed that LUCE are influenced by various factors, including population, economic output, energy structure, industrial type, land structure, urbanization, etc. [11,74,75,76]. Therefore, clarifying the driving mechanism of LUCE can provide a theoretical reference for regional sustainable development. China, the second-largest economy in the world and the country with the highest carbon emissions [77], has promised that it will reach its carbon peak around 2030 and achieve carbon neutrality by 2050. The lack of time and technical support are obstacles for China to achieving its “dual carbon” goal. Therefore, China should give priority to the “four-pronged” innovation strategy of “emission reduction, sink increase, carbon conservation, and carbon sequestration” through energy structure transformation, industrial structure adjustment, and land use management [78].
Cluster 3 is devoted to comprehending how deforestation affects carbon stores. The main keywords include Remote sensing, REDD, Kyoto Protocol, Forest degradation, Deforestation, Carbon stocks, Brazil, and Amazon. Studies have shown that tropical forests can store 160 to 250 Pg of carbon, about a quarter of the total carbon stocks in terrestrial ecosystems [79,80]. Land-use change significantly impacts carbon stocks in tropical forests [48]. Nevertheless, the evaluation of carbon stocks in tropical forests needs to be more explicit since it is difficult to estimate how it changes due to forest degradation [81,82]. Reducing emissions from deforestation and degradation (REDD) has become a crucial economic mechanism for curbing global warming. The future of REDD implementation relies on a series of negotiations that can significantly impact the maintenance or replacement of the Kyoto Protocol after 2012 and the end of tropical forests [56]. Therefore, it is urgent to assess the stabilization of deforestation and forest degradation to ensure the efficacy of REDD [83]. The world’s largest continuous tropical forest is found in Brazil, but due to deforestation, about 20% of the original forest has been replaced by pasture or agriculture [84]. It has been revealed that since 2005, deforestation in the Brazilian Amazon has dropped, but frontier forests continue to be degraded by logging, fires, and deforestation [85,86]. Technically, we can observe the dynamic process of the Amazon Forest degradation by employing field measurements, satellite remote sensing, and airborne LiDAR. Field measurements are usually constrained by the size of samples and time duration, resulting in uncertainty about the magnitude of degradation effects on forest structure and carbon stocks [83]; satellite-based estimates can support degradation mapping over large areas, even remote areas, but are limited by the spatial resolution of satellite images, making it harder to notice tiny changes in forest structure due to low-intensity degradation [81,87,88,89]. Compared to the above two methods, airborne LiDAR data have finer spatial scales and can better assess carbon stocks in intact and damaged forest types, and airborne LiDAR also has the potential to enhance the regional assessment of biomass by observing regional changes in carbon stocks [90].
Cluster 4 aims to study soil organic carbon stocks and biodiversity. The main keywords include Soil organic carbon, Greenhouse gases, Ecosystem services, Carbon storage, Carbon sequestration, Biofuels, and Biodiversity. It indicates that soil organic carbon is essential to the Earth’s carbon cycle. Land-use change can also affect the dynamic process of soil organic carbon, directly affecting the input of soil organic carbon stocks by influencing the net primary production of the surface layer and the retention of dead organic materials. It can also indirectly affect the output of soil organic carbon stocks by potentially altering the soil’s biological, chemical, and physical reactions [91]. Irrational land use patterns, poor land management, vegetation types, and anthropogenic disturbances can all accelerate soil erosion, affecting soil organic carbon stocks [92]. To reduce GHG and mitigate global climate change, international institutions have proposed carbon sequestration, which is considered one of the best strategies. It can capture carbon to replace the direct discharge of CO2 into the atmosphere, and includes physical and biological carbon sequestration. Governments should fully use carbon sequestration in terrestrial ecosystems, which is the most economical and environmentally friendly approach, while also providing low-carbon technologies such as biofuels with less regulatory advantage. Although climate change is not the main factor contributing to the decline in biodiversity and ecosystems [93], a rising body of research indicates that climate change has broad and significant consequences on biodiversity’s structural, compositional, and functional traits. More than 18% of terrestrial ecoregions may have experienced increased habitat loss and fragmentation due to climate deterioration, resulting in species extinction and other adverse effects on ecosystem functions and services [94].
Cluster 5 mainly studied agricultural carbon emissions and their reduction. The main keywords include Agriculture, Indonesia, Forests, Carbon, and Afforestation. Carbon emissions from agricultural activities are also an essential source of carbon emissions. The irrational use of agricultural inputs such as fertilizers and insecticides, the excessive use of agricultural land, and the devastation of vegetation brought on by overgrazing and over-cultivation have affected the carbon balance of agroecosystems and exacerbated the carbon emissions of farming systems, particularly in developing countries [95,96]. Johnson et al. argued that agricultural carbon emissions mainly originate from agricultural waste, enteric fermentation, manure management, rural energy use, rice fields, and biological burning [97]. Restructuring intra-agricultural land (such as afforestation and reforestation) and preventing agricultural intensification are two ways to reduce agricultural carbon emissions. Although the members of the Association of Southeast Asian Nations have low energy consumption due to their smaller economies, their agricultural carbon emissions are relatively high. As climate conditions worsen, governments worldwide have agreed to tackle climate change through various carbon reduction efforts. Indonesia has also committed to the United Nations Framework Convention on Climate Change and the Paris Agreement to reduce carbon emissions to 41% by 2030. The Indonesian government is preparing a gradual reduction plan to control carbon trading, including incentives for a carbon tax, an accepted policy tool to reduce carbon in agriculture. Furthermore, some scholars suggest a uniform tax and quantitative standard, with a uniform carbon tax on inputs with negative externalities in production and subsidies on positive externalities. Except for the carbon taxes, countries have adopted various agricultural engineering and technological measures to promote carbon reduction in agriculture [98].

4.3. Analysis of Thematic Evolution in the Field of LUCE

We used the co-occurrence network and keyword cluster analysis to understand the research hotspots of LUCE. However, the development trends of LUCE research and thematic evolution are uncertain. Therefore, we used Origin 2021 software to draw an annual heatmap of keywords in the field of LUCE (Figure 10), which can more intuitively reflect the trend of keywords over time; the darker the color, the more frequently occurring keywords were. We discovered that Carbon emission, Land-use change, Land use, Climate change, and Deforestation have existed for nearly seven years, and are appearing more and more frequently, by observing the annual frequency changes of keywords. Carbon sequestration, Remote sensing, REDD, and Urbanization have all become popular in recent years.
This paper employs bibliometrix’s theme evolution module to generate a Sankey diagram (Figure 11), aiming to visualize the thematic evolution of LUCE research. The thematic evolution module defines three time segments, and three evolution nodes were formed automatically in 2012, 2018, and 2020. There are single paths and differentiated paths for thematic evolution. A single approach reveals that the research topic has not changed, and differentiated practices are more significant than single paths for related research. Carbon dioxide emission (1992–2022), Climate change (1992–2022), and Deforestation (2020–2022) are all single research paths. As shown by the thematic evolution pathway diagram, there are three clear frontier research pathways: Climate change (1992–2012)—Carbon emissions (2013–2017)—Deforestation (2018–2020)—Land-use change (2021–2022); Land-use change (1992–2012)—Carbon sequestration (2013–2017)—Remote sensing (2018–2020)—Carbon emissions (2020–2022); and Land-use change (1992–2017)—Urbanization (2018–2020)—Renewable energy (2018–2022).
Climate change (1992–2012)—Carbon emissions (2013–2017)—Deforestation (2018–2020)—Land-use change (2021–2022): Global warming has been one of the largest and widest challenges facing mankind to date. Anthropogenic climate change is already seriously affecting extreme weather and climate events in all regions of the globe, and how to deal with a series of challenges caused by greenhouse gases has become a key concern and an urgent issue for countries around the world. Zaehle et al. found that higher land use and productivity can offset some of the carbon sequestration caused by global warming [66]. The balance of terrestrial carbon in Europe is highly uncertain. The current net carbon sequestration in European terrestrial ecosystems is believed to be predominantly the result of previous land use changes, such as forest regeneration and forest degradation. It is unclear if and how much this sequestration will last in the future [99]. However, emissions from land-use change and significant deforestation considerably impact the global carbon budget. Land use and land-cover changes between 1990 and 2010 were responsible for 12.5% of anthropogenic carbon emissions [38]. Forest loss is mostly to blame for these emissions. REDD, forest conservation, sustainable management, and a host of other tools may all contribute significantly to controlling global temperature rises [32]. The mechanism of land use change, especially forest degradation, on climate change, is not clear at present, so land use management practices such as reducing forest degradation and deforestation are also one of the pathways to curb global warming.
Land-use change (1992–2012)—Carbon sequestration (2013–2017)—Remote sensing (2018–2020)—Carbon emissions (2020–2022): Land-use change has been recognized as a global concern, and land use patterns controlled by human activities lead to changes in their land use types that affect global greenhouse gas emissions and soil carbon stocks. Land-use change plays a critical role in global carbon dynamics, and implementing effective land use management to increase soil carbon stocks is an effective means of mitigating atmospheric CO2 levels. The most common method for monitoring land-use change is remote sensing, which can provide continuous and spatial estimates of aboveground biomass, which is valuable for analyzing and quantifying carbon stocks and emission factors and has become a helpful tool for tracking carbon emissions. Currently, many academics use remote sensing techniques to evaluate carbon emissions from wildfires [15] to measure and track the dynamics of forest carbon stocks [89], biomass burning emissions [36], drivers of tropical deforestation [100], and other research areas. Remote sensing satellite data can also track historical variability, and its availability has dramatically expanded the ability of researchers to track past carbon emissions data. Advances in remote sensing technology have led to the broader application of satellite data in the field of carbon emissions. Therefore, further research should use remote sensing satellite data for large-scale analysis; for instance, to calculate the carbon storage capacity of the world’s vegetation, map the habitat of blue carbon, and determine the potential for carbon sequestration. These studies are essential for establishing global carbon monitoring and supporting nations in achieving the Paris Agreement and IPCC emission reduction targets.
Land-use change (1992–2017)—Urbanization (2018–2020)—Renewable energy (2018–2022): The change in land use types and the transformation of land function from single to multi-function is a remarkable feature of urbanization. Since urbanization is a gradual process, its evolution is accompanied by reconfiguring spatial elements such as resources, land, transportation, and population. Urban regions, which have a high concentration of people and socioeconomic activity, are crucial for developing ways to mitigate climate change [101,102]. Improving land use efficiency and intensification to meet the demand for land from urbanization has emerged as the primary issue for boosting regional economic development because excessive energy consumption and irresponsible use of land resources no longer fit the current route of social evolution [103,104]. Driven by the triple pressure of rapid economic growth, industrialization, and urbanization, a large number of industrial and production activities consume large amounts of energy. However, economic growth and increased energy consumption are the biggest drivers of carbon emissions, but as technology advances, energy efficiency improvements and energy mix transformation will be the most important factors in carbon reduction. With the advent of renewable energy sources, their efficiency and environmental impact are becoming significant topics of debate in the scientific community. Whether biofuels are a possible solution to mitigate climate change depends to a large extent on the type of biofuel and even on the combination of biofuels under consideration. The impact of energy crops on land use change also plays an important role in the selection of different crops for biofuel production. How will the effective distribution of global urbanized land resources affect the future carbon emission intensity with the optimization of industrial structures? These considerations have emerged as central issues for promoting green urban development and achieving carbon emission reduction under the dual pressure of economic restructuring and land remediation. Therefore, the study of land-use carbon emissions based on the perspective of the energy transition is also a frontier issue of academic interest.

5. Discussion and Conclusions

5.1. Discussion

Research advances in LUCE have produced a wide range of results in terms of theory, technology, and applications. Based on our findings, although the timing and content of research on LUCE vary across countries, all have contributed to research progress in this area. Therefore, we present their research progress and challenges based on different countries to provide new insights for researchers and government regulators around the world to inform the mitigation of global climate change and advance emission reduction efforts.
(1) North American countries are dominant in terms of the number of publications and research power. The United States, as the world’s largest economy, cumulatively produces a large number of carbon emissions, and after reaching its carbon peak in 2007, its carbon emissions began to gradually decline. Its carbon reduction policy is mainly based on the innovation of clean energy technology, and the reduction of carbon emissions by adjusting its energy structure and improving energy self-sufficiency. This model has achieved both certain carbon reduction results and technological advantages. However, the differences in the governing philosophies of the two parties has led to the poor continuity of some of the U.S. carbon reduction policies. Therefore, the U.S. should promote the combination of administrative control and market mechanisms through taxation, financial subsidies, and carbon trading means to jointly promote the implementation of carbon reduction policies. The Canadian federal government attaches great importance to climate goals, and to achieve carbon neutrality and promote green economic growth, it has tilted policy funds toward key areas of emission reduction to support green technology innovation, encourage clean energy development, and establish a new federal greenhouse gas offset system to regulate supply and demand and make full use of market mechanisms to control and reduce greenhouse gas emissions.
(2) Many Asian countries began large-scale economic construction after the end of World War II, and with the rapid economic development of countries such as China, Japan, South Korea, and India, the demand for energy and industrial products has increased dramatically, resulting in the rapid growth of carbon emissions. Although China is a late starter in the study of carbon emissions from land use, it has achieved considerable results. Currently, China is an international leader in clean energy technologies, such as the photovoltaic industry, which has laid a solid foundation for the new energy industry. However, in the process of promoting carbon peaking and carbon neutrality, some places inevitably have “one-size-fits-all” and “campaign-style” carbon reduction actions, resulting in unsatisfactory emission reduction results. In this context, China should further improve its carbon emission taxation policy and carbon emission trading market. Meanwhile, carbon emissions from land use are still a popular topic in academic circles, and have been for a long time, and scholars should learn from the mature experience of foreign countries to continuously improve the overall framework and methodological system of land-use carbon emissions research, to provide theoretical support for carbon reduction work. In recent years, India’s relatively rapid economic growth has come mainly from its reliance on fossil fuels, which is also the main source of greenhouse gases in the country. Agroforestry is one of the most critical elements for India to achieve its sustainability and climate agenda, and agroforestry green policy strategies can help increase soil organic carbon, an important strategy for offsetting GHG emissions. Developing countries such as India need international support to decarbonize their economies and meet the Paris Climate Agreement target of limiting temperature rise to 1.5 °C.
(3) European countries also have a relatively high research impact, and the EU was the first region in the world to develop carbon governance and has long been a leader in addressing climate change. EU countries signed the Kyoto Protocol in 1997, and the then 15 EU member states committed to reducing greenhouse gas emission levels by 8% compared to 1990 during the period 2008–2012; in 2007, to cope with the threat of global warming, the EU put forward the target of reducing greenhouse gas emissions by 30% in developed countries by 2020 compared to 1990; in 2011, the EU released the EU 2050 Low Carbon Economy Roadmap, proposing that by 2050, the EU will achieve a low-carbon economy transition and reduce greenhouse gas emissions by 80–90% compared to 1990; in 2019, the EU released the European Green Deal, proposing that Europe will achieve net zero greenhouse gas emissions by 2050 and become the first carbon neutral region in the world. Germany, France, and the UK have made important contributions to carbon emission reduction in the EU by gradually reducing carbon dioxide emissions since they successively achieved peak carbon emissions in the early 1990s. However, due to the influence of population growth and economic development, the CO2 emissions of EU member states such as Spain and Turkey have risen significantly, which has to a certain extent inhibited the effectiveness of the EU as a whole in reducing emissions. The EU’s carbon emissions trading market is an example of the results of a market-based emission reduction mechanism, but due to the lack of effective economic support and political guarantees, and the pursuit of unilateral attention to climate, the development of EU carbon governance also faces challenges. Therefore, developed countries should take more responsibility for emission reduction to compensate for the climate impact caused by their high energy-consuming economic growth in the early industrial revolution; developing countries should fulfill their emission reduction commitments and promote economic development. In conclusion, due to the differences in the level of economic development, resource endowment, and the degree of technological development among countries, the global emission reduction issue still faces a serious challenge.

5.2. Conclusions

Through a comprehensive summary of LUCE research and the use of bibliometrix software to conduct a knowledge mapping analysis of the LUCE-related articles from 1992 to 2022, we objectively present the distribution of research teams, institutions, journals, and research hotspots and frontiers in this paper, reveal a more comprehensive analysis of the history of the development of LUCE research, and provide support for a more scientific prediction of LUCE research’s future developments. The conclusions are as follows.
(1) The number of papers published in land-use carbon emissions research generally increased year by year from 1992 to 2022. In terms of research teams, research teams related to land-use carbon emissions are relatively scattered, and the degree of connection between teams is low. In terms of research institutions, the Chinese Academy of Sciences is the research institution with the most papers published in land-use carbon emission research. In terms of research strength, the United States, China, the United Kingdom, France, Australia, and other countries are considered to be the leading research forces, and the cooperation and exchange between developed countries in regions such as Europe and North America are also relatively extensive, but China is relatively autonomous.
(2) In terms of research hotspots, overseas research mainly focuses on the climate effects of land-use change, the impact of deforestation and fire on carbon stocks, the impact of soil organic carbon stocks on climate change and biodiversity, and agricultural carbon emissions. China mainly focuses on the study of the influencing factors of land-use carbon emissions, the path to achieving the dual carbon goal, and the transition to a low carbon economy.
(3) With the development of science and technology, the research perspective and technical means of land-use carbon emissions have been enriched. In terms of research frontiers, China mainly researches low-carbon land use intensification in the context of a “dual carbon” strategy; carbon emission reduction based on energy transition; and the multi-dimensional, dynamic, and accurate tracking and monitoring of land-use carbon emission systems using remote sensing satellite data. Other countries have shifted from measuring historical land-use carbon emissions, deforestation, degradation, and fire carbon emissions to biomass combustion and global warming mitigation research.
Generally, research on LUCE is becoming increasingly abundant. A multi-disciplinary cross-fertilization of integrated environmental science, earth ecology, and sustainable development has replaced single disciplines such as geography or ecology in LUCE research. Research topics include carbon emissions from land use, agriculture, and forests. Research emphasis has steadily switched from quantitative measurement to investigating the impact mechanism in LUCE, combined with remote sensing satellite technologies to track and predict the future trend of LUCE worldwide.

Author Contributions

Conceptualization, M.L. and Y.C. (Yinrong Chen); methodology, M.L.; software, M.L.; validation, K.C. and Y.C. (Yi Chen); formal analysis, M.L.; resources, M.L.; data curation, K.C. and Y.C. (Yi Chen); writing—original draft preparation, M.L.; writing—review and editing, M.L.; visualization, M.L.; supervision, Y.C. (Yinrong Chen) and K.C.; project administration, M.L.; funding acquisition, Y.C. (Yinrong Chen). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China, grant number 42271270.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. IPCC. Climate Change 2021: The Physical Science Basis. In Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2021. [Google Scholar]
  2. Mahowald, N.M.; Ward, D.S.; Doney, S.C.; Hess, P.G.; Randerson, J.T. Are the impacts of land use on warming underestimated in climate policy? Environ. Res. Lett. 2017, 12, 094016. [Google Scholar] [CrossRef]
  3. Longo, M.; Saatchi, S.; Keller, M.; Bowman, K.; Ferraz, A.; Moorcroft, P.R.; Morton, D.C.; Bonal, D.; Brando, P.; Burban, B.; et al. Impacts of degradation on water, energy, and carbon cycling of the Amazon tropical forests. JGR Biogeosci. 2020, 125, e2020JG005677. [Google Scholar] [CrossRef] [PubMed]
  4. Guo, C.; Wang, X.; Li, Y.; He, X.; Zhang, W.; Wang, J.; Shi, X.; Chen, X.; Zhang, Y. Carbon footprint analyses and potential carbon emission reduction in China’s major peach orchards. Sustainability 2018, 10, 2908. [Google Scholar] [CrossRef]
  5. Neupane, P.R.; Gauli, A.; Maraseni, T.; Kübler, D.; Mundhenk, P.; Dang, M.V.; Köhl, M. A segregated assessment of total carbon stocks by the mode of origin and ecological functions of forests: Implication on restoration potential. Int. For. Rev. 2017, 19, 120–147. [Google Scholar]
  6. Santos, C.O.D.; Pinto, A.D.S.; Silva, J.R.D.; Parente, L.L.; Mesquita, V.V.; Santos, M.P.D.; Ferreira, L.G. Monitoring of carbon stocks in Pastures in the Savannas of Brazil through ecosystem modeling on a regional scale. Land 2023, 12, 60. [Google Scholar] [CrossRef]
  7. Houghton, R.A. Magnitude, distribution and causes of terrestrial carbon sinks and some implications for policy. Clim. Policy 2002, 2, 71–88. [Google Scholar] [CrossRef]
  8. Kuo, J.H.; Lin, C.L.; Chen, J.C.; Tseng, H.H.; Wey, M.Y. Emission of carbon dioxide in municipal solid waste incineration in Taiwan: A comparison with thermal power plants. Int. J. Greenh. Gas Control 2011, 5, 889–898. [Google Scholar] [CrossRef]
  9. Sohngen, B.; Mendelsohn, R. The net carbon emissions from historic land use and land use change. J. For. Econ. 2019, 34, 263–283. [Google Scholar]
  10. Rosan, T.M.; Goldewijk, K.K.; Ganzenmüller, R.; O’Sullivan, M.; Pongratz, J.; Mercado, L.M.; Aragon, L.E.R.C.; Heinrich, V.; Randow, C.V.; Wiltshire, A. A multi-data assessment of land use and land cover emissions from Brazil during 2000–2019. Environ. Res. Lett. 2021, 16, 074004. [Google Scholar] [CrossRef]
  11. Xu, Q.; Yang, R.; Dong, Y.X.; Liu, Y.X.; Qiu, L.R. The influence of rapid urbanization and land use changes on terrestrial carbon sources/sinks in Guangzhou, China. Ecol. Indic. 2016, 70, 304–316. [Google Scholar] [CrossRef]
  12. Zhang, M.; Huang, X.; Chuai, X.; Yang, H.; Lai, L.; Tan, J. Impact of land use type conversion on carbon storage in terrestrial ecosystems of China: A spatial-temporal perspective. Sci. Rep. 2015, 5, 10233. [Google Scholar] [CrossRef]
  13. Lai, L.; Huang, X.; Yang, H.; Chuai, X.; Zhang, M.; Zhong, T.; Chen, Z.; Chen, Y.; Wang, X.; Thompson, J.R. Carbon emissions from land use change and management in China between 1990 and 2010. Sci. Adv. 2016, 2, e1601063. [Google Scholar] [CrossRef]
  14. Guo, Y.; Yin, W.; Chai, Q.; Yu, A.; Zhao, C.; Fan, Z.; Fan, H.; Coulter, J.A. No tillage and previous residual plastic mulching with reduced water and nitrogen supply reduces soil carbon emission and enhances productivity of following wheat in arid irrigation areas. Field Crop. Res. 2021, 262, 108028. [Google Scholar] [CrossRef]
  15. Lima, A.; Silva, T.S.F.; de Aragão, L.E.O.e.C.; de Feitas, R.M.; Adami, M.; Formaggio, A.R.; Shimabukuro, Y.E. Land use and land cover changes determine the spatial relationship between fire and deforestation in the Brazilian Amazon. Appl. Geogr. 2012, 34, 239–246. [Google Scholar] [CrossRef]
  16. Wang, G.; Han, Q.; de Vries, B. Assessment of the relation between land use and carbon emission in Eindhoven, the Netherlands. J. Environ. Manag. 2019, 247, 413–424. [Google Scholar] [CrossRef]
  17. Chuai, X.; Huang, X.; Wang, W.; Zhao, R.; Zhang, M.; Wu, C. Land use, total carbon emissions change and low carbon land management in Coastal Jiangsu, China. J. Clean. Prod. 2015, 103, 77–86. [Google Scholar] [CrossRef]
  18. Hong, C.; Burney, J.A.; Pongratz, J.; Nabel, J.E.M.S.; Mueller, N.D.; Jackson, R.B.; Davis, S.J. Global and regional drivers of land use emissions in 1961–2017. Nature 2021, 589, 554–561. [Google Scholar] [CrossRef]
  19. Zhang, W.; Xu, H. Effects of land urbanization and land finance on carbon emissions: A panel data analysis for Chinese provinces. Land Use Policy 2017, 63, 493–500. [Google Scholar] [CrossRef]
  20. Meng, F.; Zhou, Z.; Zhang, P. Multi-Objective Optimization of Land Use in the Beijing–Tianjin–Hebei Region of China Based on the GMOP-PLUS Coupling Model. Sustainability 2023, 15, 3977. [Google Scholar] [CrossRef]
  21. Huang, J.; Li, W.; Huang, X.; Guo, L. Analysis of the Relative Sustainability of Land Devoted to Bioenergy: Comparing Land-Use Alternatives in China. Sustainability 2017, 9, 801. [Google Scholar] [CrossRef]
  22. Goulder, L.H.; Parry, L.W. Instrument choice in environmental policy. Rev. Env. Econ. Policy 2008, 2, 152–174. [Google Scholar] [CrossRef]
  23. Böhringer, C.; Carbone, J.C.; Rutherford, T.F. Unilateral climate policy design: Efficiency and equity implications of alternative instruments to reduce carbon leakage. Energy Econ. 2012, 34, S208–S217. [Google Scholar] [CrossRef]
  24. Raupach, M.R.; Davis, S.J.; Peters, G.P.; Andrew, R.M. Sharing a quota on cumulative carbon emissions. Nat. Clim. Change 2014, 4, 873–879. [Google Scholar] [CrossRef]
  25. Qiu, Y.; Qiao, J.; Pardalos, P.M. A branch-and-price algorithm for production routing problems with carbon cap-and-trade. Omega 2016, 68, 49–61. [Google Scholar] [CrossRef]
  26. Yang, Y.; Meng, G. The evolution and research framework of carbon footprint: Based on the perspective of knowledge mapping. Ecol. Indic. 2020, 112, 106125. [Google Scholar] [CrossRef]
  27. Lu, X.; Lai, J. Review on carbon emissions of commercial buildings. Renew. Sustain. Energy Rev. 2020, 119, 109545. [Google Scholar] [CrossRef]
  28. Huang, W.; Wang, Q.; Li, H.; Fan, H.; Qian, Y.; Klemeš, J.J. Review of recent progress of emission trading policy in China. J. Clean. Prod. 2022, 349, 131480. [Google Scholar] [CrossRef]
  29. Aria, M.; Cuccurullo, C. Bibliometrix: An R tool for comprehensive science mapping analysis. J. Informetr. 2017, 11, 959–975. [Google Scholar] [CrossRef]
  30. Searchinger, T.; Heimlich, R.; Houghton, R.A.; Dong, F.; Elobeid, A.; Fabiosa, J.; Tokgoz, S.; Hayes, D.; Yu, T.H. Use of US croplands for biofuels increases greenhouse gases through emissions from land use change. Science 2008, 319, 1238–1240. [Google Scholar] [CrossRef]
  31. Canadell, J.G.; Le Quere, C.; Raupach, M.R.; Field, C.B.; Buitenhuis, E.T.; Ciais, P.; Conway, T.J.; Gillett, N.P.; Houghton, R.A.; Marland, G. Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc. Natl. Acad. Sci. USA 2007, 104, 18866–18870. [Google Scholar] [CrossRef]
  32. Nepstad, D.C.; Verssimo, A.; Alencar, A.; Nobre, C.; Lima, E.; Lefebvre, P.; Schlesinger, P.; Potter, C.; Moutinho, P.; Mendoza, E.; et al. Large-scale impoverishment of Amazonian forests by logging and fire. Nature 1999, 398, 505–508. [Google Scholar] [CrossRef]
  33. Piao, S.; Fang, J.; Ciais, P.; Peylin, P.; Huang, Y.; Sitch, S.; Wang, T. The carbon balance of terrestrial ecosystems in China. Nature 2009, 458, 1009–1013. [Google Scholar] [CrossRef]
  34. Pendleton, L.; Donato, D.C.; Murray, B.C.; Crooks, S.; Jenkins, W.A.; Sifleet, S.; Craft, C.B.; Fourqurean, J.; Kauffman, J.B.; Marbà, N.; et al. Estimating global “blue carbon” emissions from conversion and degradation of vegetated coastal ecosystems. PLoS ONE 2012, 7, e43542. [Google Scholar] [CrossRef]
  35. Houghton, R.A. Aboveground Forest Biomass and the Global Carbon Balance. Glob. Change Biol. 2005, 11, 945–958. [Google Scholar] [CrossRef]
  36. van der Werf, G.R.; Randerson, J.T.; Giglio, L.; van Leeuwen, T.T.; Chen, Y.; Rogers, B.M.; Mu, M.; van Marle, M.J.E.; Morton, D.C.; Collatz, G.J.; et al. Global fire emissions estimates during 1997–2016. Earth Syst. Sci. Data 2017, 9, 697–720. [Google Scholar] [CrossRef]
  37. Zomer, R.J.; Trabucco, A.; Bossio, D.A.; Verchot, L.V. Climate change mitigation: A spatial analysis of global land suitability for clean development mechanism afforestation and reforestation. Agr. Ecosyst. Environ. 2008, 126, 67–80. [Google Scholar] [CrossRef]
  38. Houghton, R.A.; House, J.I.; Pongratz, J.; Van Der Werf, G.R.; DeFries, R.S.; Hansen, M.C.; Le Quéré, C.; Ramankutty, N. Carbon emissions from land use and land-cover change. Biogeosciences 2012, 9, 5125–5142. [Google Scholar] [CrossRef]
  39. Wise, M.; Calvin, K.; Thomson, A.; Clarke, L.; Bond-Lamberty, B.; Sands, R.; Smith, S.J.; Janetos, A.; Edmonds, J. Implications of limiting CO2 concentrations for land use and energy. Science 2009, 324, 1183–1186. [Google Scholar] [CrossRef]
  40. Houghton, R.A.; Hackler, J.L. Emissions of carbon from forestry and land-use change in tropical Asia. Glob. Change Biol. 1999, 5, 481–492. [Google Scholar] [CrossRef]
  41. Kondo, M.; Sitch, S.; Ciais, P.; Achard, F.; Kato, E.; Pongratz, J.; Houghton, R.A.; Canadell, J.G.; Patra, P.K.; Friedlingstein, P.; et al. Are land-use change emissions in Southeast Asia decreasing or increasing? Glob. Biogeochem. Cycles 2022, 36, e2020GB006909. [Google Scholar] [CrossRef]
  42. Peng, S.; Ciais, P.; Maignan, F.; Li, W.; Chang, J.; Wang, T.; Yue, C. Ensitivity of land use change emission estimates to historical land use and land cover mapping. Glob. Biogeochem. Cycles 2017, 31, 626–643. [Google Scholar] [CrossRef]
  43. Gasser, T.; Ciais, P. A theoretical framework for the net land-to-atmosphere CO2 flux and its implications in the definition of “emissions from land-use change”. Earth Syst. Dynam. 2013, 4, 171–186. [Google Scholar] [CrossRef]
  44. Randerson, J.T.; Chen, Y.; van der Werf, G.R.; Rogers, B.M.; Morton, D.C. Global burned area and biomass burning emissions from small fires. J. Geophys. Res. 2012, 117, G04012. [Google Scholar] [CrossRef]
  45. van Marle, M.J.E.; Kloster, S.; Magi, B.I.; Marlon, J.R.; Daniau, A.-L.; Field, R.D.; Arneth, A.; Forrest, M.; Hantson, S.; Kehrwald, N.M.; et al. Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015). Geosci. Model Dev. 2017, 10, 3329–3357. [Google Scholar] [CrossRef]
  46. van der Werf, G.R.; Morton, D.C.; DeFries, R.S.; Giglio, L.; Randerson, J.T.; Collatz, G.J.; Kasibhatla, P.S. Estimates of fire emissions from an active deforestation region in the southern Amazon based on satellite data and biogeochemical modelling. Biogeosciences 2009, 6, 235–249. [Google Scholar] [CrossRef]
  47. van Marle, M.J.E.; van der Werf, G.R.; de Jeu, R.A.M.; Liu, Y.Y. Annual South American forest loss estimates based on passive microwave remote sensing (1990–2010). Biogeosciences 2016, 13, 609–624. [Google Scholar] [CrossRef]
  48. Zhao, R.; Huang, X.; Liu, Y.; Zhong, T.; Ding, M.; Chuai, X. Carbon emission of regional land use and its decomposition analysis: Case study of Nanjing City, China. Chin. Geogr. Sci. 2015, 25, 198–212. [Google Scholar] [CrossRef]
  49. Chuai, X.; Lai, L.; Huang, X.; Zhao, R.; Wang, W.; Chen, Z. Temporospatial changes of carbon footprint based on energy consumption in China. J. Geogr. Sci. 2012, 22, 110–124. [Google Scholar] [CrossRef]
  50. Zhao, R.; Huang, X.; Liu, Y.; Zhong, T.; Ding, M.; Chuai, X. Urban carbon footprint and carbon cycle pressure: The case study of Nanjing. J. Geogr. Sci. 2014, 24, 159–176. [Google Scholar] [CrossRef]
  51. Chuai, X.; Huang, X.; Qi, X.; Li, J.; Zuo, T.; Lu, Q.; Li, J.; Wu, C.; Zhao, R. A Preliminary Study of the Carbon Emissions Reduction Effects of Land Use Control. Sci. Rep. 2016, 6, 36901. [Google Scholar] [CrossRef]
  52. Xia, C.; Li, Y.; Xu, T.; Ye, Y.; Shi, Z.; Peng, Y.; Liu, J. Quantifying the spatial patterns of urban carbon metabolism: A case study of Hangzhou, China. Ecol. Indic. 2018, 95, 474–484. [Google Scholar] [CrossRef]
  53. Xia, C.; Li, Y.; Xu, T.; Chen, Q.; Ye, Y.; Shi, Z.; Liu, J.; Ding, Q.; Li, X. Analyzing spatial patterns of urban carbon metabolism and its response to change of urbansize: A case of the Yangtze River Delta, China. Ecol. Indic. 2019, 104, 615–625. [Google Scholar] [CrossRef]
  54. Li, Y.; Shen, J.; Xia, C.; Xiang, M.; Cao, Y.; Yang, J. The impact of urban scale on carbon metabolism—A case study of Hangzhou, China. J. Clean. Prod. 2021, 292, 126055. [Google Scholar] [CrossRef]
  55. Xia, C.; Chen, B. Urban land-carbon nexus based on ecological network analysis. Appl. Energy 2020, 276, 115465. [Google Scholar] [CrossRef]
  56. Aragão, L.E.; Shimabukuro, Y.E. The Incidence of Fire in Amazonian Forests with Implications for REDD. Science 2010, 328, 1275–1278. [Google Scholar] [CrossRef]
  57. Fearnside, P.M. Global warming and tropical land use change: Greenhouse gas emissions from biomass burning, decomposition and soils in forest conversion, shifting cultivation and secondary vegetation. Clim. Change 2000, 46, 115–158. [Google Scholar] [CrossRef]
  58. Nogueira, E.M.; Fearnside, P.M.; Nelson, B.W.; França, M.B. Wood density in forests of Brazil’s ‘arc of deforestation’: Implications for biomass and flux of carbon from land-use change in Amazonia. For. Ecol. Manag. 2007, 248, 119–135. [Google Scholar] [CrossRef]
  59. Fearnside, P.M.; Righi, C.A.; de Alencastro Graca, P.M.L.; Keizer, E.W.H.; Cerri, C.C.; Nogueira, E.M.; Barbosa, R.I. Biomass and greenhouse-gas emissions from land-use change in Brazil’s Amazonian “arc of deforestation”: The states of Mato Grosso and Rondônia. For. Ecol. Manag. 2009, 258, 1968–1978. [Google Scholar] [CrossRef]
  60. Roman-Cuesta, R.M.; Rufino, M.C.; Herold, M.; Butterbach-Bahl, K.; Rosenstock, T.S.; Herrero, M.; Ohle, S.; Li, C.; Poulter, B.; Verchot, L.; et al. Hotspots of gross emissions from the land use sector: Patterns, uncertainties, and leading emission sources for the period 2000-2005 in the tropics. Biogeosciences 2016, 13, 4253–4269. [Google Scholar] [CrossRef]
  61. de Sassi, C.; Joseph, S.; Bos, A.B.; Duchelle, A.E.; Ravikumar, A.; Herold, M. Towards integrated monitoring of REDD+. Curr. Opin. Environ. Sustain. 2015, 14, 93–100. [Google Scholar] [CrossRef]
  62. Zaehle, S.; Bondeau, A.; Carter, T.R.; Cramer, W.; Erhard, M.; Prentice, I.C.; Reginster, I.; Rounsevell, M.D.A.; Sitch, S.; Smith, B.; et al. Projected changes in terrestrial carbon storage in Europe under climate and land use change, 1990–2100. Ecosystems 2007, 10, 380–401. [Google Scholar] [CrossRef]
  63. Van Zanten, B.T.; Verburg, P.; Espinosa, M.; Gomez-Y-Paloma, S.; Galimberti, G.; Kantelhardt, J.; Kapfer, M.; Lefebvre, M.; Manrique, R.; Piorr, A.; et al. European agricultural landscapes, common agricultural policy and ecosystem services: A review. Agron. Sustain. Dev. 2013, 34, 309–325. [Google Scholar] [CrossRef]
  64. Carlson, K.M.; Gerber, J.S.; Mueller, N.D.; Herrero, M.; MacDonald, G.K.; Brauman, K.A.; Havlik, P.; O’Connell, C.S.; Johnson, J.A.; Saatchi, S.; et al. Greenhouse gas emissions intensity of global croplands. Nat. Clim. Change 2016, 7, 63–68. [Google Scholar] [CrossRef]
  65. Ciais, P.; Tan, J.; Wang, X.; Roedenbeck, C.; Chevallier, F.; Piao, S.-L.; Moriarty, R.; Broquet, G.; Le Quéré, C.; Canadell, J.G.; et al. Five decades of northern land carbon uptake revealed by the interhemispheric CO2 gradient. Nature 2019, 568, 221–225. [Google Scholar] [CrossRef] [PubMed]
  66. Tian, H.Q.; Xu, R.T.; Canadell, J.G.; Thompson, R.L.; Winiwarter, W.; Suntharalingam, P.; Davidson, E.A.; Ciais, P.; Jackson, R.B.; Janssens-Maenhout, G.; et al. A comprehensive quantification of global nitrous oxide sources and sinks. Nature 2020, 586, 248–256. [Google Scholar] [CrossRef]
  67. Pongratz, J.; Schwingshackl, C.; Bultan, S.; Obermeier, W.; Havermann, F.; Guo, S. Land use effects on climate: Current state, recent progress, and emerging topics. Curr. Clim. Change Rep. 2021, 7, 99–120. [Google Scholar] [CrossRef]
  68. Krause, A.; Haverd, V.; Poulter, B.; Anthoni, P.; Quesada, B.; Rammig, A.; Arneth, A. Multimodel analysis of future land use and climate change impacts on ecosystem functioning. Earth’s Future 2019, 7, 833–851. [Google Scholar] [CrossRef]
  69. Obermeier, W.A.; Nabel, J.E.M.S.; Loughran, T.; Hartung, K.; Bastos, A.; Havermann, F.; Anthoni, P.; Arneth, A.; Goll, D.S.; Lienert, S.; et al. Modelled land use and land cover change emissions—A spatiotemporal comparison of different approaches. Earth Syst. Dynam. 2021, 12, 635–670. [Google Scholar] [CrossRef]
  70. Gasser, T.; Crepin, L.; Quilcaille, Y.; Houghton, R.A.; Ciais, P.; Obersteiner, M. Historical CO2 emissions from land use and land cover change and their uncertainty. Biogeosciences 2020, 17, 4075–4101. [Google Scholar] [CrossRef]
  71. Houghton, R.A.; Nassikas, A.A. Global and regional fluxes of carbon from land use and land cover change 1850–2015. Glob. Biogeochem. Cycles 2017, 31, 456–472. [Google Scholar] [CrossRef]
  72. Lawrence, D.M.; Hurtt, G.C.; Arneth, A.; Brovkin, V.; Calvin, K.V.; Jones, A.D.; Jones, C.D.; Lawrence, P.J.; de Noblet-Ducoudré, N.; Pongratz, J.; et al. The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: Rationale and experimental design. Geosci. Model Dev. 2016, 9, 2973–2998. [Google Scholar] [CrossRef]
  73. Quesada, B.; Arneth, A.; Robertson, E.; de Noblet-Ducoudré, N. Potential strong contribution of future anthropogenic land use and land-cover change to the terrestrial carbon cycle. Environ. Res. Lett. 2018, 13, 064023. [Google Scholar] [CrossRef]
  74. Li, Y.-N.; Cai, M.; Wu, K.; Wei, J. Decoupling analysis of carbon emission from construction land in Shanghai. J. Clean. Prod. 2019, 210, 25–34. [Google Scholar] [CrossRef]
  75. Wang, Z.; Hoffmann, T.; Six, J.; Kaplan, J.O.; Govers, G.; Doetterl, S.; Van Oost, K. Human-induced erosion has offset one-third of carbon emissions from land cover change. Nat. Clim. Change 2017, 7, 345–349. [Google Scholar] [CrossRef]
  76. Zhu, R.; Zhao, R.; Sun, J.; Xiao, L.; Jiao, S.; Chuai, X.; Zhang, L.; Yang, Q. Temporospatial pattern of carbon emission efficiency of China’s energy-intensive industries and its policy implications. J. Clean. Prod. 2021, 286, 125507. [Google Scholar] [CrossRef]
  77. Yang, J.; Li, Y.; Hay, I.; Huang, X. Decoding national new area development in China: Toward new land development and politics. Cities 2019, 87, 114–120. [Google Scholar] [CrossRef]
  78. Yu, G.; Hao, T.; Zhu, J. Discussion on action strategies of China’s carbon peak and carbon neutrality. Bull. Chin. Acad. Sci. 2022, 37, 423–434. [Google Scholar]
  79. Baccini, A.; Goetz, S.; Walker, W.S.; Laporte, N.T.; Sun, M.; Sulla-Menashe, D.; Hackler, J.L.; Beck, P.S.A.; Dubayah, R.O.; Friedl, M.A.; et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Clim. Change 2012, 2, 182–185. [Google Scholar] [CrossRef]
  80. Cao, M.; Woodward, F.I. Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their responses to climate change. Glob. Change Biol. 1998, 4, 185–198. [Google Scholar] [CrossRef]
  81. Bustamante, M.M.C.; Roitman, I.; Aide, T.M.; Alencar, A.; Anderson, L.O.; Aragão, L.; Asner, G.P.; Barlow, J.; Berenguer, E.; Chambers, J.; et al. Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity. Glob. Change Biol. 2016, 22, 92–109. [Google Scholar] [CrossRef]
  82. Aguiar, A.P.D.; Ometto, J.; Nobre, C.; Lapola, D.M.; Almeida, C.; Vieira, I.; Soares, J.V.; Alvala, R.C.D.S.; Saatchi, S.; Valeriano, D.D.M.; et al. Modeling the spatial and temporal heterogeneity of deforestation-driven carbon emissions: The INPE-EM framework applied to the Brazilian Amazon. Glob. Change Biol. 2012, 18, 3346–3366. [Google Scholar] [CrossRef]
  83. Longo, M.; Keller, M.; Dos-Santos, M.N.; Leitold, V.; Pinagé, E.R.; Baccini, A.; Saatchi, S.; Nogueira, E.M.; Batistella, M.; Morton, D.C. Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon. Glob. Biogeochem. Cycles 2016, 30, 1639–1660. [Google Scholar] [CrossRef]
  84. Gatti, L.V.; Basso, L.S.; Miller, J.B.; Gloor, M.; Domingues, L.G.; Cassol, H.L.G.; Tejada, G.; Aragão, L.E.O.C.; Nobre, C.; Peters, W.; et al. Amazonia as a carbon source linked to deforestation and climate change. Nature 2021, 595, 388–393. [Google Scholar] [CrossRef] [PubMed]
  85. Zhang, K.; Castanho, A.D.D.A.; Galbraith, D.R.; Moghim, S.; Levine, N.M.; Bras, R.L.; Coe, M.T.; Costa, M.H.; Malhi, Y.; Longo, M.; et al. The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2, and land use. Glob. Change Biol. 2015, 21, 2569–2587. [Google Scholar] [CrossRef] [PubMed]
  86. Berenguer, E.; Ferreira, J.; Gardner, T.A.; Aragão, L.E.O.C.; De Camargo, P.B.; Cerri, C.E.; Durigan, M.; De Oliveira, R.C.; Vieira, I.C.G.; Barlow, J. A large-scale field assessment of carbon stocks in human-modified tropical forests. Glob. Change Biol. 2014, 20, 3713–3726. [Google Scholar] [CrossRef]
  87. Asner, G.P.; Knapp, D.E.; Broadbent, E.N.; Oliveira, P.J.; Keller, M.; Silva, J.N. Selective logging in the Brazilian Amazon. Science 2005, 310, 480–482. [Google Scholar] [CrossRef]
  88. Joshi, N.; Mitchard, E.T.A.; Woo, N.; Torres, J.; Moll-Rocek, J.; Ehammer, A.; Collins, M.; Jepsen, M.R.; Fensholt, R. Mapping dynamics of deforestation and forest degradation in tropical forests using radar satellite data. Environ. Res. Lett. 2015, 10, 034014. [Google Scholar] [CrossRef]
  89. Asner, G.P.; Powell, G.V.N.; Mascaro, J.; Knapp, D.E.; Clark, J.K.; Jacobson, J.; Kennedy-Bowdoin, T.; Balaji, A.; Paez-Acosta, G.; Victoria, E.; et al. High-resolution forest carbon stocks and emissions in the Amazon. Proc. Natl. Acad. Sci. USA 2010, 107, 16738–16742. [Google Scholar] [CrossRef]
  90. Zhu, E.; Deng, J.; Zhou, M.; Gan, M.; Jiang, R.; Wang, K.; Shahtahmassebi, A. Carbon emissions induced by land-use and land-cover change from 1970 to 2010 in Zhejiang, China. Sci. Total Environ. 2019, 646, 930–939. [Google Scholar] [CrossRef]
  91. Jafarian, Z.; Kavian, A. Effects of Land use Change on Soil Organic Carbon and Nitrogen. Commun. Soil Sci. Plan. 2013, 44, 339–346. [Google Scholar] [CrossRef]
  92. Arneth, A.; Shin, Y.-J.; Leadley, P.; Rondinini, C.; Bukvareva, E.; Kolb, M.; Midgley, G.F.; Oberdorff, T.; Palomo, I.; Saito, O. Post-2020 biodiversity targets need to embrace climate change. Proc. Natl. Acad. Sci. USA 2020, 117, 30882–30891. [Google Scholar] [CrossRef]
  93. Bellard, C.; Bertelsmeier, C.; Leadley, P.; Thuiller, W.; Courchamp, F. Impacts of climate change on the future of biodiversity. Ecol. Lett. 2012, 15, 365–377. [Google Scholar] [CrossRef]
  94. Segan, D.B.; Murray, K.A.; Watson, J.E.M. A global assessment of current and future biodiversity vulnerability to habitat loss-climate change interactions. Glob. Ecol. Conserv. 2016, 5, 12–21. [Google Scholar] [CrossRef]
  95. Hu, C.; Fan, J.; Chen, J. Spatial and Temporal Characteristics and Drivers of Agricultural Carbon Emissions in Jiangsu Province, China. Int. J. Environ. Res. Public Health 2022, 19, 12463. [Google Scholar] [CrossRef]
  96. Wang, G.; Liu, P.; Hu, J.; Zhang, F. Agriculture-Induced N2O Emissions and Reduction Strategies in China. Int. J. Environ. Res. Public Health 2022, 19, 12193. [Google Scholar] [CrossRef]
  97. Johnson, J.M.; Franzluebbers, A.J.; Weyers, S.L.; Reicosky, D.C. Agricultural opportunities to mitigate greenhouse gas emissions. Environ. Pollut. 2007, 150, 107–124. [Google Scholar] [CrossRef]
  98. Pugh, T.A.M.; Arneth, A.; Olin, S.; Ahlström, A.; Bayer, A.D.; Klein Goldewijk, K.; Lindeskog, M.; Schurgers, G. Simulated carbon emissions from land use change are substantially enhanced by accounting for agricultural management. Environ. Res. Lett. 2015, 10, 124008. [Google Scholar] [CrossRef]
  99. Nabuurs, G.J.; Schelhaas, M.J.; Mohren, G.F.M.J.; Field, C.B. Temporal evolution of the European forest sector carbon sink from 1950 to 1999. Glob. Change Biol. 2003, 9, 152–160. [Google Scholar] [CrossRef]
  100. De Sy, V.; Herold, M.; Achard, F.; Avitabile, V.; Baccini, A.; Carter, S.; Clevers, J.G.P.W.; Lindquist, E.; Pereira, M.; Verchot, L. Tropical deforestation drivers and associated carbon emission factors derived from remote sensing data. Environ. Res. Lett. 2019, 14, 094022. [Google Scholar] [CrossRef]
  101. Ribeiro, H.V.; Rybski, D.; Kropp, J.P. Effects of changing population or density on urban carbon dioxide emissions. Nat. Commun. 2019, 10, 3204. [Google Scholar] [CrossRef]
  102. Chen, B.; Xu, C.; Wu, Y.; Li, Z.; Song, M.; Shen, Z. Spatiotemporal carbon emissions across the spectrum of Chinese cities: Insights from socioeconomic characteristics and ecological capacity. J. Environ. Manag. 2022, 306, 114510. [Google Scholar] [CrossRef] [PubMed]
  103. Wang, Q.; Xiao, Y. Has Urban Construction Land Achieved Low-Carbon Sustainable Development? A Case Study of North China Plain, China. Sustainability 2022, 14, 9434. [Google Scholar]
  104. Dong, Y.; Jin, G.; Deng, X. Dynamic interactive effects of urban land-use efficiency, industrial transformation, and carbon emissions. J. Clean. Prod. 2020, 270, 122547. [Google Scholar] [CrossRef]
Figure 1. Flowchart of bibliometric analysis.
Figure 1. Flowchart of bibliometric analysis.
Sustainability 15 07245 g001
Figure 2. The trend in the number of publications and citations on LUCE research between 1992 and 2022.
Figure 2. The trend in the number of publications and citations on LUCE research between 1992 and 2022.
Sustainability 15 07245 g002
Figure 3. The growth trends of publications in the top 10 journals.
Figure 3. The growth trends of publications in the top 10 journals.
Sustainability 15 07245 g003
Figure 4. Authors’ production over time on LUCE research. (N. Articles represent the number of articles; TCpY represents total citations per year.).
Figure 4. Authors’ production over time on LUCE research. (N. Articles represent the number of articles; TCpY represents total citations per year.).
Sustainability 15 07245 g004
Figure 5. Author collaboration network.
Figure 5. Author collaboration network.
Sustainability 15 07245 g005
Figure 6. Country’s scientific production in the field of LUCE research.
Figure 6. Country’s scientific production in the field of LUCE research.
Sustainability 15 07245 g006
Figure 7. Countries Cooperative Network.
Figure 7. Countries Cooperative Network.
Sustainability 15 07245 g007
Figure 8. A keyword co-occurrence map of LUCE research.
Figure 8. A keyword co-occurrence map of LUCE research.
Sustainability 15 07245 g008
Figure 9. A keyword cluster map of LUCE research.
Figure 9. A keyword cluster map of LUCE research.
Sustainability 15 07245 g009
Figure 10. Heat maps of the annual keyword distribution in LUCE research between 1992 and 2022.
Figure 10. Heat maps of the annual keyword distribution in LUCE research between 1992 and 2022.
Sustainability 15 07245 g010
Figure 11. Thematic evolution path of LUCE research from 1992 to 2022.
Figure 11. Thematic evolution path of LUCE research from 1992 to 2022.
Sustainability 15 07245 g011
Table 1. The highlights of highly cited literature in the study of LUCE.
Table 1. The highlights of highly cited literature in the study of LUCE.
AuthorsHighlightTC 1YearJournal
Searchinger et al.This article argued that using good cropland to expand biofuels will probably increase greenhouse gases through emissions from land use change [30].29672008Science
Canadell et al.This article concluded that economic activity, carbon intensity, and natural efficiency contribute to releasing atmospheric CO2 [31].13012007PANS
Nepstad et al.This article proposed a model to indicate that logging and fire increase forest impoverishment and release forest carbon stocks into the atmosphere [32].8601999Nature
Piao et al.This article used three methods to analyze China’s terrestrial carbon balance and its driving mechanisms [33].8412009Nature
Pendleton et al.The article estimated the global “Blue Carbon” emissions from the conversion and degradation of vegetated coastal ecosystems [34].7112012PLoS One
Houghton et al.The article revealed that changes in forest biomass significantly impact existing estimates of carbon emissions in the tropics and the global carbon balance [35].7032005Global Change Biology
Van der Werf et al.The article revised the Worldwide Fire Emissions Database to estimate global fire emissions from 1997 to 2016 [36].6472017Earth System Science Data
Zomer et al.This study assessed the global land suitability for a clean development mechanism of afforestation and reforestation projects to mitigate climate change [37].6132008Agriculture Ecosystems & Environment
Houghton et al.The article estimated carbon emissions from land use and land-cover change [38].5902012Biogeosciences
Wise et al.The article suggested that managing anthropogenic carbon emissions from terrestrial and energy systems can limit atmospheric CO2 concentrations to low levels [39].5852009Science
1 total article citations.
Table 2. The top 10 academic journals for LUCE research.
Table 2. The top 10 academic journals for LUCE research.
JournalArticlesPercentage Occupied (%)Impact Factor (2021)
Environmental Research Letters504.586.947
Journal of Cleaner Production433.9411.072
Global Change Biology403.6613.211
Sustainability373.393.889
Science of The Total Environment262.3810.753
Forest Ecology and Management242.204.384
Land Use Policy242.206.189
Biogeosciences232.115.092
Global Environmental Change-Human and Policy Dimensions222.0111.160
Ecological Indicators191.746.263
Table 3. Top 10 research institutions for LUCE research.
Table 3. Top 10 research institutions for LUCE research.
InstitutionNumber of ArticlesCountry
Chinese Academy of Sciences58China
University of Maryland46the US
Woods Hole Research Center36the US
University of Exeter29the UK
Beijing Normal University28China
Wageningen University & Research25Netherlands
Humboldt–Universitat zu Berlin24Germany
Nanjing University24China
Peking University22China
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Liu, M.; Chen, Y.; Chen, K.; Chen, Y. Progress and Hotspots of Research on Land-Use Carbon Emissions: A Global Perspective. Sustainability 2023, 15, 7245. https://doi.org/10.3390/su15097245

AMA Style

Liu M, Chen Y, Chen K, Chen Y. Progress and Hotspots of Research on Land-Use Carbon Emissions: A Global Perspective. Sustainability. 2023; 15(9):7245. https://doi.org/10.3390/su15097245

Chicago/Turabian Style

Liu, Min, Yinrong Chen, Kun Chen, and Yi Chen. 2023. "Progress and Hotspots of Research on Land-Use Carbon Emissions: A Global Perspective" Sustainability 15, no. 9: 7245. https://doi.org/10.3390/su15097245

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop