Analysis of spatial and temporal evolution and driving factors of carbon emission in Shandong Province: based on the perspective of land use

The Yellow River Basin assumes an important ecological and economic function in China. The study of carbon emissions from land use in the nine provinces (regions) of the pathway is important to achieve carbon reduction. Based on the dynamic data of land use, energy, and economic changes in nine provinces (regions) for the past 30 years from 1990 to 2018, this study analyzed the spatial and temporal evolution characteristics of land-use carbon emissions by using the carbon emission coefficient method in the IPCC inventory method and evaluating the low-carbon development model of the nine provinces (regions) by land-use carbon emission intensity. Finally, the LMDI model was used to analyze the factors influencing land-use carbon emissions. The results showed that: (1) in the past 30 years, the net carbon emissions have shown a continuously increasing trend, and the difference in the spatial distribution of carbon emissions in different periods was obvious. The carbon sink effect was not significant enough to offset the carbon emissions generated. (2) The continuously decreasing carbon emission intensity values per unit of GDP indicate that the coordination between land-use and economic development was getting better. (3) The factors of population size, economic size, and land-use structure accelerated land-use carbon emissions, whereas land-use efficiency limited land-use carbon emissions. Accordingly, this paper puts forward some corresponding policy suggestions.

Land-use carbon emissions denote the release or sequestration of greenhouse gases (e.g., CO2, N2O) resulting from human land-use activities, with land-use changes exerting a major influence on land-use carbon emissions. Revealing the coupling mechanism between land-use changes and carbon emissions is of crucial theoretical significance for achieving “dual carbon” goals and mitigating global climate change. Based on the land-use change data of Jiangxi Province, this study explored the Spatial–temporal relationship between land-use carbon emissions and land-use changes in Jiangxi Province from 2000 to 2020 using a model of land-use dynamic degrees, a model of land-use transfer matrices, and the IPCC carbon emission accounting model. In this study, the factors influencing changes in land-use carbon emissions were comprehensively analyzed using an LMDI model and the Tapio decoupling model. The results indicated that: (1) Jiangxi Province’s land-use changes show a “two-increase, four-decrease” trend, with construction land and unused land experiencing the most significant shifts, while water, grassland, cropland, and forestland changes stayed near 1%. (2) Net land-use carbon emissions exhibit a rapid then gradual increase, with higher emissions in the north/south and lower levels in central regions. While overall land-use carbon emission intensity is declining, per capita emissions continue to rise. (3) Land-use carbon emission changes are primarily driven by emission intensity, land-use structure, efficiency, and economic level. In Jiangxi, economic growth mainly increases land-use carbon emissions, while land-use efficiency enhancement counters this trend. Jiangxi Province shows weak land-use carbon emission–economic growth decoupling, with land-use carbon emissions rising more slowly than economic growth. This study not only provides a typical case analysis and methodological framework for understanding the carbon emission effects of human–land relationships in rapidly urbanizing regions but also offers a specific scientific basis and policy insights for Jiangxi Province and other similar regions to formulate differentiated territorial spatial planning, promote ecological protection and restoration, and achieve green and low-carbon development pathways under the “dual carbon” goals.

Human activities and land transformation are important factors in the growth of carbon emissions. In recent years, construction land for urban use in China has expanded rapidly. At the same time, carbon emissions in China are among the highest in the world. However, little is known about the relationship between the two factors. This study seeks to estimate the carbon emissions and carbon sequestrations of various types of land based on the land cover data of 137 county-level administrative regions in Shandong Province, China, from 2000 to 2020.The study estimated the carbon emissions for energy consumption using energy consumption data and night-time light images, hence, net carbon emissions. The Tapio decoupling coefficient was used to analyze the decoupling between the net carbon emissions and construction land, and where the model for the decoupling effort was constructed to explore the driving factors of decoupling. The results showed that net carbon emissions in Shandong Province continued to increase, and the areas with high carbon emissions were concentrated primarily in specific districts of the province. The relationship between net carbon emissions and construction land evolved from an expansive negative decoupling type to a strong negative decoupling type. Spatially, most areas in the province featured an expansive negative decoupling, but the areas with a strong negative decoupling have gradually increased. The intensive rate of land use and efficiencies in technological innovation have restrained carbon emissions, and they have contributed to an ideal decoupling situation. Although the intensity of carbon emission and the size of the population have restrained carbon emissions, efforts towards decoupling have faded. The degree of land use has facilitated carbon emissions, and in recent years, efforts have been made to achieve an ideal decoupling. The method of estimation of net carbon emissions devised in this research can lend itself to studies on other regions, and the conclusions provide a reference for China, going forward, to balance urbanization and carbon emissions.

To further study the spatial distribution and dynamic evolution of carbon emissions from animal husbandry in Shandong Province, the panel data of 16 prefecture-level cities in Shandong Province from 2001 to 2022 were used to measure the carbon emissions of animal husbandry and the carbon emission intensity of animal husbandry. Based on the combination of space, kernel density estimation, and LMDI decomposition model, the spatial and temporal evolution of carbon emissions from animal husbandry in Shandong Province and its driving factors were investigated. The results show that: (1) The total amount of animal husbandry carbon emissions in Shandong Province showed a fluctuating downward trend, with a decrease of 10.10% during the investigation period, showing a peripheral-agglomeration distribution pattern. The carbon emission intensity showed a gradual downward trend, with an average annual decline of 7.47%, showing stepped distribution characteristics of high in the west and low in the east. (2) The difference in carbon emissions of animal husbandry among cities in Shandong Province increased first and then decreased, and the growth distribution was basically in the form of “bimodal”, showing a polarization pattern. (3) The intensity effect has the most obvious inhibitory effect on the carbon emission of animal husbandry; the effect of agricultural structure changes from a promoting effect to an inhibiting effect. The inhibitory effect of the industrial structure effect is second only to the intensity effect; the economic effect has the greatest promoting effect; and the promotion effect of the population size effect is small.

In the context of global climate governance, the study of land-use carbon emissions in the Yellow River Basin is crucial to China's "dual-carbon" goal in addition to ecological conservation and the high-quality developments. This paper computed the land-use carbon emissions of 95 cities in the Yellow River Basin from 2000 to 2020 and examined its characteristics with respect to spatio-temporal evolution and driving mechanisms. The findings are as follows: (1) The overall net land-use carbon emissions in the Yellow River Basin rose sharply from 2000 to 2020. (2) From a spatial perspective, the Yellow River Basin's land-use carbon emissions are high in the middle-east and low in the northwest, which is directly tied to the urban development model and function orientation. (3) A strong spatial link exists in the land-use carbon emissions in the Yellow River Basin. The degree of spatial agglomeration among the comparable cities first rose and then fell. "Low-Low" was largely constant and concentrated in the upper reaches, whereas "High-High" was concentrated in the middle and lower reaches with an east-ward migratory trend. (4) The rates of economic development and technological advancement have a major positive driving effect. Moreover, the other components' driving effects fluctuate with time, and significant geographical variance exists. Thus, this study not only provides a rationale for reducing carbon emissions in the Yellow River Basin but also serves as a guide for other Chinese cities with comparable climates in improving their climate governance.

Rapid urbanization and agricultural expansion in arid regions have profoundly altered carbon cycles and landscape stability. Focusing on the Hexi Corridor, China, this study integrates multi-source geospatial data (1990–2020) to analyze the spatiotemporal evolution and driving factors of land-use carbon emissions (LUCE) and landscape ecological risks (LER). By integrating carbon accounting, LER assessment, bivariate spatial autocorrelation, and the Optimal Parameter Geographic Detector (OPGD), we quantify the intricate relationship between carbon dynamics and landscape integrity. Results indicate a transformative pattern of anthropogenic expansion and natural contraction, with a 2315.49 km2 net loss of unused land. Net carbon emissions surged 4.6-fold, while forest and grassland sinks exhibited a significant “lock-in effect” due to fragile ecological foundations. Simultaneously, LER followed an “inverted U-shaped” trajectory; the refined 5 × 5 km grid scale revealed a significant drop in high-risk areas from 44.65% to 10.96% following ecological restoration. Spatial analysis reveals a significant “spatial mismatch” between LUCE and LER, with oases manifesting “high carbon–low risk” clustering. Driver detection confirms a driving asymmetry. LUCE is dominated by anthropogenic factors (nighttime light, q > 0.90), whereas LER is profoundly constrained by natural backgrounds. Future governance must shift toward a collaborative system centered on source-based emission control and precise regional management to synergize low-carbon transition with landscape security.

The marine fishing industry has a huge carbon sink potential and is also an important source of carbon emissions. The low-carbon development of the marine fishing industry is particularly important. Based on the perspective of carbon neutrality, this study analyzed the trend of net carbon emissions, carbon emissions and carbon sinks in the offshore fishing industry in China and 11 coastal provinces from 2010 to 2019 and decomposed the driving factors of the net carbon emissions of the offshore fishing industry with the LMDI decomposition method. The results show the following: (1) China’s offshore fishing industry is in a partially carbon-neutral state. Overall, the net carbon emissions have decreased, and the carbon neutrality capacity has improved. However, the net carbon emissions have increased since 2016. From 2010 to 2019, both the carbon emissions and carbon sinks of China’s offshore fishing industry declined. Carbon emissions fluctuated at first and then declined rapidly, while carbon sinks rose slowly and then showed a significant downward trend. (2) The offshore fishing industry in coastal provinces is also in a state of partial carbon neutrality, and the trends of carbon emissions, carbon sinks and net carbon emissions in most provinces are consistent with the national trends, but there are large differences between regions. (3) For the whole country, among the driving factors of net carbon emissions in the offshore fishing industry, industrial development is the main positive driving factor, and population size is the main negative driving factor. The net carbon coefficient and energy intensity also play a certain role in driving net carbon emissions. (4) Population size is an important inhibitory factor for the net carbon emissions of the offshore fishing industry in most coastal provinces, and the driving direction of the net carbon coefficient, energy intensity and industrial development is inconsistent. Based on the above research, relevant suggestions are put forward for the green development of the marine fishing industry.

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.

Land use and cover change (LUCC) has a non-negligible impact on both carbon emissions and carbon sinks. Based on the analysis of land use dynamics in Shandong Province, this study simulates land use changes in Shandong Province in 2030 under the Natural Development Scenario (NDS) and Sustainable Development Scenario (SDS), classifies the risk level of carbon emissions in Shandong Province using the Land Use Carbon Emission (LUCE) risk indexes, and compares the differences between the risk level regions under NDS and SDS. This study shows that under the influence of LUCC, the carbon emissions in Shandong province increased significantly, from 90.5591 million tons in 2000 to 493.538 million tons in 2020, with urban land being the main source of carbon emissions, which increased from 90.0757 million tons in 2000 to 490.139 million tons in 2020. The main source of the increase in urban land was cropland. The LUCE was positively correlated with urban land area. The LUCE of SDS was 7.2423 million tons less than that of NDS. From 2000 to 2020, the risk areas of LUCE in Shandong province were mainly no-risk and mild-risk areas. The number of moderate-risk areas and high-risk areas of SDS was less than that of NDS. The rational organization of land use is important for Shandong Province to achieve low-carbon development.

Construction of a methodology framework to characterize dynamic full-sector land-use carbon emissions embodied in trade

Marine fisheries play a dual role in global warming as both a “carbon source” and “carbon sink.” This study analyzed carbon emissions from marine fisheries in Shandong Province from 2010 to 2022 by integrating carbon accounting, extended Kaya-LMDI decomposition, and System Dynamics (SD) modeling. The results reveal a distinct temporal trend characterized by an initial increase followed by a gradual decline in net carbon emissions, while marine carbon sinks increased steadily over the study period. Marine capture fisheries consistently remained the dominant source of total carbon emissions. Decomposition analysis reveals that economic scale and population were the primary drivers of carbon emission growth, while carbon intensity exerted a smaller but positive effect, whereas improvements in energy intensity and industrial structure contribute to emission reduction, highlighting the importance of energy efficiency improvement and industrial structural adjustment. Using a validated SD model to project trends from 2023 to 2035, we simulated three scenarios: Baseline (BS), High-Growth (HG), and Low-Carbon Development (LD) scenarios. The results show that the low-carbon development scenario achieves the most pronounced reduction in net carbon emissions, driven by simultaneous declines in capture emissions and a strong enhancement of carbon sink capacity from shellfish and algae aquaculture. In contrast, the baseline and high-growth scenarios exhibit relatively weaker mitigation effects. Overall, this study provides quantitative evidence and a strategic roadmap for advancing the green, sustainable transition of marine fisheries in Shandong Province, China.

Land use change is one of the key elements leading to carbon emission changes, and is of great significance to the process of achieving the goals of carbon peaking and carbon neutrality. In this study, we calculated the land-use carbon emissions (LCE) in the Guanzhong area (GZA) of Shaanxi province from 2000 to 2019 by using an improved LCE measurement model. Meanwhile, the spatial and temporal changes of LCE were analyzed and the driving forces were investigated based on the correlation analysis and multi-scale geographical weighting regression (MGWR). The results showed that the total amount of LCE showed a significant increasing trend from 2000 to 2019. Regions where the LCE significantly increased occupied 71.20% of the total area; these regions were distributed in the central and eastern parts of the study area. The LCE showed a significant positive spatial correlation and had a remarkable aggregation state. The H-H agglomeration area of LCE was distributed in the central urban agglomeration. The L-L agglomeration areas were always distributed in the southwest part of the GZA with low carbon emissions. The average correlation coefficients between LCE and nighttime light (NTL), population density (PD), and gross primary productivity (GPP) were 0.13, 0.21, and −0.05, respectively. The NLT and PD had obvious positive effects on LCE, while GPP has obvious negative effects on carbon emissions, which can be ascribed to the carbon sink effect of forests and grasslands. The results of this study have important reference value regarding the formulation of carbon emission reduction policies and the development of a low-carbon social economy.

Excessive carbon emissions will cause irreversible damage to the human living environment. Therefore, carbon neutrality has become an inevitable choice for sustainable development. Marine fishery is an essential pathway for biological carbon sequestration. However, it is also a source of carbon emissions. From this perspective, an in-depth assessment of the performance of carbon emissions and sinks from marine fisheries is required to achieve the goal of carbon neutrality. This paper measured the carbon emissions, carbon sinks, and net carbon emissions of marine fisheries in nine coastal provinces of China from 2005 to 2020 for the first time. Based on the calculation results, the log-mean decomposition index method was used to analyze the driving factors of net carbon emissions. The results suggested that, from 2005 to 2020, both the carbon emissions and carbon sinks of China’s marine fisheries increased, and the net carbon emissions showed a downward trend. There were variations in the performance of carbon emissions, carbon sinks, and net carbon emissions in different provinces, and only Shandong could consistently achieve carbon neutrality. Fujian and Liaoning achieved carbon neutrality in 2020. In terms of the contribution of each factor, the industrial structure was the main positive driver, and carbon intensity was the main negative driver. Based on the empirical results, this paper suggested increasing the implementation of the carbon tax policy, establishing a farming compensation mechanism and promoting carbon emissions trading and international blue carbon trading. The results could give a reference for the energy conservation and emission reduction of marine fisheries while enhancing the ecological benefits of their carbon sinks and helping to achieve the carbon neutrality target.

Carbon emissions are critical to climate change, and land-use change is an essential source of growth in carbon emissions. Research on land-use carbon emissions has become one of the hotspots in academic research. To explore the research hotspots and development trends of land-use carbon emissions in the last 20 years, CiteSpace software was used to conduct a quantitative analysis of relevant literature. This paper was based on the China National Knowledge Infrastructure (CNKI) and Web of Science (WoS) database literature on land-use carbon emissions from 2001 to 2020. The scientific research cooperation network CiteSpace software, with keyword co-occurrence, clustering, and burst word detection, was used to systematically analyze the main research strengths, hotspots and frontiers and clarify the research progress. The research results are as follows: (1) the amount of literature and the depth of research on land-use carbon emissions have increased yearly. However, there is little cooperation between research institutions and scholars, and there is still a lack of large-scale and stable research teams. (2) At the research hotspot level, the English literature focuses on building models and theoretical frameworks to study the internal mechanisms and driving factors of carbon emissions and climate change. The Chinese literature focuses on achieving regional carbon emissions reductions and carbon cycle goals and optimizing a low-carbon economy, transportation and land-use structure. (3) Research frontiers and trends show that the English literature first explored carbon sequestration, organic carbon, and carbon accounting. In China, the research frontiers are gradually becoming focused on influencing factors, decoupling analysis, and the built environment. The study will strengthen the intensity and depth of global carbon emission research and provide a reference for improving global climate change, protecting ecology and balancing economic development.

Land-use change is a crucial element influencing the patterns of carbon sinks/sources in the Yellow River Basin (YRB). Therefore, studying land-use carbon emissions (LUCE) in the YRB and the decoupling from economic development can help formulate emission reduction strategies. In order to explore the spatiotemporal characteristics of LUCE in the YRB, we estimated the LUCE in 69 cities in the YRB using the downscale energy balance table estimation method and land-use remote sensing data for seven phases from 1990 to 2020. The spatial and temporal features of LUCE were researched from three different spatial scales: the whole spatial scale of the YRB, the sub-basin level, and the city level. Furthermore, the Tapio decoupling model was utilized to research the decoupling state between LUCE and economic development using a multi-scale approach. The Logarithmic Mean Divisia Index (LMDI) model was employed to explore the influencing factors of LUCE in the YRB. These results showed the following: (1) The LUCE in the YRB went through two stages: “stable growth” (1990–2000) and “rapid growth” (2000–2020). The LUCE increased from 165 million tons in 1990 to 1.414 billion tons in 2020, and the average annual growth rate was 25.12%. The spatial pattern of LUCE in the YRB exhibited significant variations, with the LUCE showing a geographic differentiation of midstream > downstream > upstream. (2) Except for the expansive coupling state during 2000–2005 (e: 0.952) and the expansive negative decoupling state during 2015–2020 (e: 2.151), the YRB was in the weak decoupling state for the majority of the time periods. (3) Economic development was the major positive driving factor for the rise of LUCE in this basin, while energy consumption intensity was the primary inhibiting factor. Through a discussion of the features and influencing factors of LUCE, these results can be utilized to provide carbon emission reduction recommendations tailored to the characteristics of cities’ resources and economic development, which will be helpful for achieving low-carbon and sustainable development in the YRB.