A new estimation of carbon emissions from land use and land cover change in China over the past 300 years

Global impacts of land use on terrestrial carbon emissions since 1850

Since the Industrial Revolution, significant changes in global land-use patterns have occurred, which have disrupted terrestrial carbon emissions. However, the disturbance processes, change trends, and distribution patterns are not clear. Therefore, the changes in terrestrial carbon emissions (Eluc) caused by land-use change (LUC) since 1850 were analyzed in this study. The results showed that, owing to the sharp decrease in forestland (-13.39 %; 84.26 × 105 km2) and significant increases in built-up land (+1360.4 %; 7.21 × 105 km2), cropland (+175.8 %; 130.88 × 105 km2), and grassland (+162.6 %; 239.73 × 105 km2), the global Eluc increased from 0.42 Pg C in 1850 to 11.05 Pg C in 2018, with an average annual increase of approximately 3.42 Pg C yr-1, while the average annual carbon emissions after the 21st century reached 9.65 Pg C yr-1. Among them, direct Eluc increased by approximately 0.80 Pg C yr-1 and indirect Eluc increased by 2.62 Pg C yr-1. In addition, from 1850 to 2018, global Eluc was approximately 578.26 Pg C, with North America, Europe, and Asia being the largest regional sources. Our results highlight the changing trend and distribution pattern of global terrestrial carbon emissions under the influence of LUC since the Industrial Revolution and provide a scientific basis for regional and sectoral formulation of low-carbon emission-reduction policies and planning of low-carbon land-use patterns.

Carbon Storage Response to Land Use/Land Cover Changes and SSP-RCP Scenarios Simulation: A Case Study in Yunnan Province, China

Changes in terrestrial ecosystem carbon storage (CS) affect the global carbon cycle, thereby influencing global climate change. Land use/land cover (LULC) shifts are key drivers of CS changes, making it crucial to predict their impact on CS for low-carbon development. Most studies model future LULC by adjusting change proportions, leading to overly subjective simulations. We integrated the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, the Patch-generating Land Use Simulation (PLUS) model, and the Land Use Harmonization 2 (LUH2) dataset to simulate future LULC in Yunnan under different SSP-RCP scenarios of climate and economic development. Within the new PLUS-InVEST-LUH2 framework, we systematically analyzed LULC alterations and their effects on CS from 1980 to 2040. Results demonstrated that: (1) Forestland had the highest CS, whereas built-up land and water showed minimal levels. Western areas boast higher CS, while the east has lower. From 1980 to 2020, CS continuously decreased by 29.55 Tg. In the wake of population increase and economic advancement, the area of built-up land expanded by 2.75 times. Built-up land encroaches on other land categories and is a key cause of the reduction in CS. (2) From 2020 to 2040, mainly due to an increase in forestland, CS rose to 3934.65 Tg under the SSP1-2.6 scenario, whereas under the SSP2-4.5 scenario, primarily due to a reduction in forestland and grassland areas, CS declined to 3800.86 Tg. (3) Forestland is the primary contributor to CS, whereas the ongoing enlargement of built-up land is causing a sustained decline in CS. Scenario simulations indicate that future LULC changes under different scenarios will have a significant impact on CS in Yunnan. Under a green sustainable development pathway, Yunnan can exhibit significant carbon sink potential. Overall, this research offers a scientific reference for optimizing land management and sustainable development in Yunnan, aiding China's "double carbon" goals.

Investigation of the interactions and influencing factors of the Water-Land-Energy-Carbon system in the Yellow River Basin

The survival and advancement of human society are fundamentally dependent on the availability and sustainable management of water, land, and energy resources. The development and utilisation of various energy sources and a considerable number of natural resources lead to carbon emissions. A complex interplay exists between water, land, energy, and carbon, and their correlation lies at the core of the regional "natural-social-economic" system, which is crucial for human existence and advancement. Despite its importance, research on the water-land-energy‑carbon (WLEC) nexus is limited. In this study, we employed an innovative combination of the comprehensive assessment index, coupled coordination degree, panel vector autoregressive, and random forest models to investigate the spatiotemporal evolution, internal dynamic interactions, and external influencing factors of the WLEC system in the Yellow River Basin (YRB) from 2007 to 2021. The findings revealed that the degree of coupled coordination in the WLEC system of the YRB exhibited an overall steady upward trend. The spatial agglomeration effect was continuously enhanced, and regional disparities increased. Complex interaction mechanisms exist within the water, land, energy, and carbon subsystems in the YRB. Population size, land relief, and sunshine are the prevailing factors influencing the degree of coupling coordination in the WLEC. Addressing the trade-off relationship among the subsystems of the WLEC system is a key aspect of optimising its correlation relationship. This study provides a scientific basis and relevant suggestions for achieving the Double-Carbon Goal, promoting ecological protection and high-quality development in the YRB.

The impact of national land supervision system on urban low-carbon transformation: evidence from China

The land system is a crucial factor influencing urban low-carbon sustainable development. However, previous research has paid little attention to the effects and mechanisms of the national land supervision system (NLSS) on urban low-carbon transformation (ULCT). This study uses China's routine land inspection as a quasi-natural experiment and examines the impact of NLSS on ULCT using panel data from 283 Chinese cities between 2005 and 2016. The study finds that NLSS significantly promotes ULCT, with a series of robustness checks supporting this conclusion, showing a 1.95% improvement in carbon emission performance in cities under supervision. NLSS mainly facilitates ULCT by improving land use efficiency, upgrading the structural of the service sector, and promoting technological progress. Compared to eastern cities, southern cities, large cities, and non-resource-based cities, NLSS more effectively promotes low-carbon transformation in central and western, northern, small- and medium-sized, and resource-based cities. Additionally, in contrast to cities with high environmental awareness, high marketization levels, high financial development levels, and high fiscal pressure, NLSS more strongly promotes ULCT in cities with lower levels of these factors. Furthermore, NLSS exhibits a significant positive spatial spillover effect in promoting ULCT. In advancing ULCT, NLSS can be synergized with smart city pilot policies and innovative city pilot policies but has not shown synergies with low-carbon city pilot policies.

Investigating spatio-temporal variations and contributing factors of land use-related carbon emissions in the Beijing-Tianjin-Hebei Region, China

The land use change is the primary factor in influencing the regional carbon emissions. Studying the effects of land use change on carbon emissions can provide supports for the development policies of carbon emission. Using land use and energy consumption data, this study measures carbon emissions from land use dynamics in the Beijing-Tianjin-Hebei region from 2000 to 2020. The standard deviation ellipse model is employed to investigate the distribution characteristics of the spatial patterns of carbon emissions, while the Geographically and Temporally Weighted Regression (GTWR) model is used to examine the contributing factors of carbon emissions and their spatial and temporal heterogeneity. Results indicate a consistently increasing trend in carbon emissions from land use in the Beijing-Tianjin-Hebei region from 2000 to 2020. Construction land is characterized with both the primary source and an increasing intensity of carbon emissions. Besides, the spatial distribution of carbon emissions from land use in the Beijing-Tianjin-Hebei region demonstrates an aggregation pattern from in the northeast-southwest direction towards the center, with a greater aggregation trend in the east-west direction compared to that in the south-north direction. During the study period, a positive correlation was documented between carbon emissions and factors including total population, economic development level, land use degree, and landscape patterns. This correlation showed a decreasing trend and reached a stable level at the end of the study period. Moreover, the analysis showed a negative correlation between industrial structure and carbon emissions, which showed an increasing trend and reached a relatively high level at the end of the study period.

Can forests realize the carbon neutrality dream? Evidence from a global sample

The enlarge in economic activities and the urban population at the global level has brought about an increase in the demand for energy, food, and natural resources, as well as an exacerbation in global climate change concerns. In this respect, it is important to ensure the balance between global climate change and global economic activities. Therefore, a wide literature has emerged that searches for alternative solutions to improve climate change and carbon dioxide (CO2) emissions. The majority of existing studies emphasize the importance of renewable energy sources in environmental improvement efforts. Few studies highlight the importance of forestation in environmental improvement efforts, highlighting the non-linear effects of forestation. To fill this gap, this study uses panel data from 181 countries between 1990 and 2022 and evaluates the non-linear impact of economic growth, forest extent, energy efficiency, and urban growth on per capita CO2 emissions using a dynamic panel threshold and dynamic panel quantile threshold methods. Furthermore, we extend the model and conduct robustness tests examining the non-linear threshold effects of renewable and non-renewable energy consumption on per capita CO2 emissions. Our findings provide pieces of evidence that forest extents are an alternative solution to renewable energy use and energy efficiency in environmental improvement efforts.

Impacts of climate and land use change on terrestrial carbon storage: A multi-scenario case study in the Yellow River Basin (1992-2050)

Currently, socioeconomic development and climate change pose new challenges to the assessment and management of terrestrial carbon storage (CS). Accurate prediction of future changes in land use and CS under different climate scenarios is of great significance for regional land use decision-making and carbon management. Taking the Yellow River Basin (YRB) in China as the study area, this study proposed a framework integrating the land use harmonization2 (LUH2) dataset, the patch-generating land use simulation (PLUS) model, and the integrated valuation of ecosystem services and trade-offs (InVEST) model. Under this framework, we systematically analyzed the spatiotemporal evolution characteristics of land use and their impact on CS in the YRB from 1992 to 2050. The results showed that (1) CS was highest in forestland and lowest in construction land, with a spatial distribution of high in the south and low in the north. From 1992 to 2020, construction land, forestland, and grassland increased while cropland decreased, reducing the total CS by 74.04 Tg. (2) From 2020 to 2050, under SSP1-2.6 scenario, forestland increased by 158.87 %; under SSP2-4.5 scenario, unused land decreased by 65.55 %; and under SSP5-8.5 scenario, construction land increased by 13.88 %. By 2050, SSP1-2.6 scenario exhibited the highest CS (8105.25 Tg), followed by SSP2-4.5 scenario (7363.61 Tg), and SSP5-8.5 scenario was the lowest (7315.86 Tg). (3) Forestland and construction land were the most critical factors affecting the CS. Shaanxi and Shanxi had the largest CS in all scenarios, and Qinghai had a huge carbon sink potential under SSP1-2.6 scenario. Scenario modeling demonstrated that future climate and land-use changes would have significant impacts on terrestrial CS in the YRB, and green development pathways could strongly contribute to meeting the dual‑carbon target. Overall, this study provides a scientific basis for promoting low-carbon development, land-use optimization, and ecological civilization construction in YRB, China.

Spatiotemporal evolution and multi-scale coupling effects of land-use carbon emissions and ecological environmental quality

The coupling relationship between land-use carbon emissions (LCE) and ecological environmental quality (EEQ) is critical for regional sustainable development. Rapid urbanization promotes a notable increase in LCE, which imparts significant stress on EEQ. This study used land use and cover change (LUCC) and Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) data from the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) to evaluate LCE, applied a remote sensing ecological index (RSEI) model to calculate EEQ, and combined gravity and centroid movement trajectory models to analyze the spatiotemporal evolution characteristics of LCE and EEQ. Four-quadrant and coupling degree (CD) models were used to analyze the synergistic relationship and interaction intensity between LCE and EEQ based on three different scales of pixels, counties, and cities. The results show that: (1) LCE and EEQ exhibit clear spatial inequality distribution, and the total amount of LCE increased from 40.16 Mt. in 2000 to 131.99 Mt. in 2020; however, LCE has not yet reached peak carbon emissions. (2) From 2000 to 2020, cities with a strong correlation between LCE and EEQ showed an increasing trend, and the centroid of LCE moved sharply to Jiangxi during 2000-2005 and 2005-2010. (3) High-CD areas were primarily located in quadrant II, and low-CD areas in quadrant IV. The relationship between LCE and EEQ has improved over the past 21 years, and CD has been increasing. (4) The stability of the coupling results between LCE and EEQ was affected by different research scales; the larger the research scale is, the greater the change in the results. This study provides a scientific basis and practical scheme for LCE reduction, ecological environmental management, and regional sustainable development in the UAMRYR.

Spatial-temporal dynamics of land use carbon emissions and drivers in 20 urban agglomerations in China from 1990 to 2019

Urban agglomerations (UAs) are the largest carbon emitters; thus, the emissions must be controlled to achieve carbon peak and carbon neutrality. We use long time series land-use and energy consumption data to estimate the carbon emissions in UAs. The standard deviational ellipse (SDE) and spatial autocorrelation analysis are used to reveal the spatiotemporal evolution of carbon emissions, and the geodetector, geographically and temporally weighted regression (GTWR), and boosted regression trees (BRTs) are used to analyze the driving factors. The results show the following: (1) Construction land and forest land are the main carbon sources and sinks, accounting for 93% and 94% of the total carbon sources and sinks, respectively. (2) The total carbon emissions of different UAs differ substantially, showing a spatial pattern of high emissions in the east and north and low emissions in the west and south. The carbon emissions of all UAs increase over time, with faster growth in UAs with lower carbon emissions. (3) The center of gravity of carbon emissions shifts to the south (except for North China, where it shifts to the west), and carbon emissions in UAs show a positive spatial correlation, with a predominantly high-high and low-low spatial aggregation pattern. (4) Population, GDP, and the annual number of cabs are the main factors influencing carbon emissions in most UAs, whereas other factors show significant differences. Most exhibit an increasing trend over time in their impact on carbon emissions. In general, China still faces substantial challenges in achieving the dual carbon goal. The carbon control measures of different UAs should be targeted in terms of energy utilization, green and low-carbon production, and consumption modes to achieve the low-carbon and green development goals of the United Nations' sustainable cities and beautiful China's urban construction as soon as possible.