A Preliminary Study of the Carbon Emissions Reduction Effects of Land Use Control

How has carbon storage changed in the Yili-Tianshan region over the past three decades and into the future? What has driven it to change?

Predicting future land use changes and assessing carbon storage remain challenging. Nowadays, how nature and socioeconomics drive changes in carbon storage is a hot topic in research. In this study, through the projection of land use type and the integration of the PLUS, Integrated Valuation of Ecosystem Services and Trade-offs (InVEST), and Geodetector models, we constructed a framework for assessing carbon storage in different land use scenarios. Utilizing this framework, it is possible to project land use change and estimate carbon storage based on different development scenarios. We applied the framework to the Yili Tianshan region and identified the main driving forces for carbon storage change. Further, we estimated the carbon storage in the Yili Tianshan region in 2035 under four scenarios (RE, NE, EP, and CLP). The results showed the following: 1) Between 1990 and 2020, there was an increase in the forest area and water bodies in the Yili-Tianshan region, mainly from bare land. 2) As shown on the time scale, carbon storage increases in the Yili-Tianshan region with a W-shaped fluctuation by converting grasslands and bare land into forests. On a spatial scale, the carbon storage was lower in the center and higher on both sides in the Yili-Tianshan region. 3) In 2035- RE, 2035-ND, and 2035-EP scenarios, the carbon storage was increased by 4.30 Tg, 6.67 Tg, and 12.08 Tg; in the 2035-CLP scenario, it was decreased by 14.63 Tg. The Yili-Tianshan region experienced a notable rise in carbon storage under the 2035-EP scenario compared to the other three scenarios. 4) Soil type played a significant role in the spatial differentiation of carbon storage in Yili-Tianshan (q value 0.5958), followed by population density (0.5394). The changes in carbon storage in the Yili-Tianshan region are the result of synergistic effects of multiple factors, in which the soil type∩soil erosion intensity are the most important. This research could provide a reference method for improving regional carbon storage.

Urban land use carbon emission intensity in China under the "double carbon" targets: spatiotemporal patterns and evolution trend

In-depth research on the spatiotemporal patterns and evolution trend of urban land use carbon emission intensity (ULUCEI) can reveal the internal relationship between urban land use and carbon emissions, which is crucial for achieving carbon emission reduction and "double carbon" targets. This paper proposed a conceptual framework of ULUCEI; the methods of kernel density estimation (KDE), exploratory spatial data analysis (ESDA), and spatial Markov chains were adopted for exploring the spatiotemporal patterns and evolution trend of China's ULUCEI from 2000 to 2017. The following conclusions are drawn through research. (1) There was an increasing trend in ULUCEI in China from 0.102 in 2000 to 0.283 in 2017. From the regional perspective, the ULUCEI in the eastern region is markedly higher than that in the central and western regions. Moreover, the results of nuclear density estimation indicate that China's ULUCEI shows an obvious upward and polarized trend. (2) China's ULUCEI shows a positive spatial autocorrelation. The types of spatial agglomeration include "high-high" agglomeration, "high-low" polarization, "low-high" collapse, and "low-low" homogeneity, and there are obvious disparities in the distribution rules of cities with different spatial agglomeration forms. (3) China's ULUCEI presents strong stability and "club convergence" trend. Moreover, spatial factors significantly affect the dynamic transition of China's ULUCEI, and its effect on the shifting upwards gradually enhances with increasing lag type. This paper therefore suggests that policymakers should formulate differentiated urban land low-carbon use models and carbon emission reduction policies to reduce ULUCEI.

The Impact of Urban Construction Land Change on Carbon Emissions-A Case Study of Wuhan City

Urban construction land (UCL) change is a significant cause of changes in urban carbon emissions. However, as the extent of this effect is currently unclear, cities cannot easily formulate reasonable carbon reduction policies in terms of land use. Taking the city of Wuhan, China, as an example, this paper combines data on land use and carbon emissions from 1995 to 2019 and uses spatial analysis, curve estimation, and correlation evaluation to explore the direct and indirect effects of the UCL changes on carbon emissions. The results show that: (1) Between 1995 and 2019, the UCL area in Wuhan increased by 193.44%, and carbon emissions increased by 78.63%; moreover, both changes showed a gradually increasing spatial correlation, and the quantitative relationship could be better fitted with a composite function model; (2) The UCL change had mainly an indirect impact on carbon emissions via factors such as population and energy use intensity per unit of carbon emissions; (3) The maximum value of carbon emissions inside a unit area decreased during the study period, with an average annual decrease of about 2.02%. Therefore, the city of Wuhan can promote the achievement of its carbon emissions reduction targets by improving the existing land use policies, for example, by dividing the city into multiple functional zones.

Effects of urban land intensive use on carbon emissions in China: spatial interaction and multi-mediating effect perspective

Land intensive use is important for sustainable land use while carbon emission is a constraint to achieve carbon neutrality; they are closely related and committed to sustainable socioeconomic development. The spatial interactions and complex mechanisms between them make it difficult to clarify their relationship precisely. This paper combines the spatial Durbin model and mediating effect model to describe the effects of urban land intensive use (ULIU) on carbon emissions (CEs) for 30 provinces in China during 1995-2018. An inverse U-shaped relationship between ULIU and CEs is proved while considering the spatial interaction. All the provincial observed values of ULIU are less than the inflection point of the curve, which means that the improvement of the ULIU will cause more CEs. Meanwhile, ULIU has multi-indirect effects on CEs, with urbanization and industrial structure upgrading playing mediating roles in the mechanism. The spatial spillover effects of CEs per unit area on the neighboring provinces are negative, indicating that the interregional influence cannot be ignored. These findings have theoretical and practical significance as they reveal the multi-effects of ULIU on CEs. To realize carbon emission reduction effectively, more attention should be paid to improving the intensity of the urban land and strengthening the regional cooperation.

Carbon emissions from land use in Jiangsu, China, and analysis of the regional interactions

Land carbon emissions are primarily determined by land use type, and these emissions could be transferred during interprovincial trade activities. This study took Jiangsu in China as a case, assigned all the energy-related carbon emissions to land, and analyzed the transferred land use carbon emissions through the application of a tele-coupling framework. Finally, the physical spatial distribution of transferred land use carbon emissions within Jiangsu at high resolution was simulated. China and Jiangsu emitted 2.27 × 10⁹ t and 1.43 × 10⁸ t of carbon in 2012, respectively, with industrial and mining land being the biggest emission source, generating more than 70% of their total emissions. Overall, Jiangsu's net carbon emissions transferred to other provinces was 2.41 × 10⁶ t in urban land and 9.03 × 10⁵ t in industrial and mining land, and these carbon emissions were mainly transferred to Hebei, Shandong, and Inner Mongolia. Land utilization intensity and economic development influenced the carbon emission transfer to some extent. Other provinces also transferred a large amount of carbon emissions to Jiangsu, of which 2.57 × 10⁶ t was in urban land and 3.18 × 10⁷ t was in industrial and mining land. Our simulation showed that the emissions in both land use types exhibited a south-north difference within Jiangsu; more specifically, urban land carbon emissions were mainly concentrated in core urban areas, especially in Suzhou, Wuxi, and Nanjing, whereas industrial and mining land carbon emissions were mostly distributed in the periphery of core urban areas and along the Yangtze River. To balance economic development and environment protection, the government must limit the expansion of construction land (especially industrial and mining land), and developed regions should implement various types of ecological compensation measures to help less developed regions reduce carbon embodied in trade activities.

Human Activity Intensity in China under Multi-Factor Interactions: Spatiotemporal Characteristics and Influencing Factors

Human activities involving nature have various environmental impacts. The assessment of the spatial and temporal evolution of human activity intensity (HAI) and its driving forces is significant for determining the effects of human activities on regional ecological environments and regulating such activities. This research quantified the HAI of China, assessed its spatiotemporal characteristics, and analyzed its influencing factors based on the land use data and panel data of 31 provinces in mainland China. The results indicate that the HAI in China is increasing, with the average value increasing from 15.83% in 1980 to 20.04% in 2018, and the HAI was relatively serious in the Beijing–Tianjin–Hebei region, Yangtze River Delta and Pearl River Delta in this period. The spatial differences in the HAI in China show a pattern of being strong in the east and weak in the west, and the spatial center of gravity of China’s HAI has gradually moved west, changing from a central enhancement mode to a point-like “core” enhancement mode. The dominant factors affecting spatial differences in HAI are economic and industrial levels. Labor, population, and capital factors also strongly impact HAI, and energy consumption and pollution emissions have little impact. These results deepen the understanding of the underlying mechanism of the environmental impact of human activities and provide a scientific basis for land-use-related decision making and eco-environment construction.

Assessing the Potential Impact of Land Use on Carbon Storage Driven by Economic Growth: A Case Study in Yangtze River Delta Urban Agglomeration

Economic development and land-use change can strongly affect terrestrial ecosystems’ carbon balance. This paper quantifies the changes in land use of Yangtze River Delta urban agglomeration (YRD) in 2020 and 2035 under three economic growth scenarios, exploring the concurrent impact on carbon storage. The results showed that the land carbon storage of YRD had decreased by 1453.80 Tg in 2000–2020, and will continue to decrease by 982.38 Tg, 1417.62 Tg, and 1636.21 Tg under the scenarios of a slow, medium, and rapid economic growth from 2020 to 2035, respectively. The large-scale occupation of cultivated land and woodland for construction land caused by economic development and population growth was an important reason. The occupation of cultivated land by construction land in Nanjing, Shanghai, and its surrounding areas had further intensified, while the reduction in carbon storage caused by the reduction in woodland had become more prominent in Hangzhou, Shaoxing, Jinhua, and the surrounding areas.

Effects of urbanization on productivity of terrestrial ecological systems based on linear fitting: a case study in Jiangsu, eastern China

The terrestrial ecosystem productivity and foundation of regional ecosystem services have been significantly influenced by recent urbanization processes. This study assesses the changes in terrestrial ecosystem productivity in Jiangsu from the years of 2000 to 2015 in response to the urbanization. A linear model that incorporates the traditional equalization method is proposed to improve the estimation accuracy of net primary productivity (NPP) loss. Results revealed that the land area of urban construction expanded rapidly during the research period to encompass an area of 8672.8 km². The rate of expansion was highest during 2005-2010. Additionally, the expansion rate of urban construction land was considerably higher in southern Jiangsu compared to the northern areas. The NPP exhibited a rising tendency from the year of 2000 to 2015, and varied from 33.30 to 40.23 Tg C/y. It was higher in the central parts, which include the cities of Yancheng and Nantong. The increase in urban construction land has resulted in a significant reduction in the terrestrial ecosystem productivity, i.e. a cumulative NPP loss of 2.55-2.88 Tg C during the research period. The NPP losses due to the conversion from cropland to constrction land were the highest, followed by the wetland. The work in this paper indicates that the rate of future productivity losses in terrestrial ecosystem in northern Jiangsu would be faster than the southern areas.

High resolution carbon emissions simulation and spatial heterogeneity analysis based on big data in Nanjing City, China

The accurate examination of the spatial distribution of carbon emissions is critical for carbon reduction strategies. Large uncertainties still exist for previous studies which tried to simulate carbon emissions in spatial, and the resolution needs to be improved to a large extent. At a city level, this study collected various sources of big data and designed a new methodology to examine carbon emissions in Nanjing city at a high resolution of 300 m. In addition, regional differences were compared, and influence factors were analyzed. This study found, the core urban area in Nanjing presented an obvious intensity variation, but the emission intensities were much lower than in those from the peripheral region where industrial land was mainly distributed. Broad areas away from urban areas, where cropland and rural residential land were distributed, presented low carbon emission intensities. Regionally, the districts in the core urban area always presented high emission intensities. The characteristics of land usage and social-economic development were key factors in determining carbon emissions. An increase in ecological land and a decrease in developed land will help carbon reduction strategies greatly. For social and economic development, adjustments in the structure of industry and energy use efficiency improvements will play key roles in the reduction of carbon emissions.

Spatial-temporal dynamics of carbon emissions and carbon sinks in economically developed areas of China: a case study of Guangdong Province

This study analysed spatial-temporal dynamics of carbon emissions and carbon sinks in Guangdong Province, South China. The methodology was based on land use/land cover data interpreted from continuous high-resolution satellite images and energy consumption statistics, using carbon emission/sink factor method. The results indicated that: (1) From 2005 to 2013, different land use/land cover types in Guangdong experienced varying degrees of change in area, primarily the expansion of built-up land and shrinkage of forest land and grassland; (2) Total carbon emissions increased sharply, from 76.11 to 140.19 TgC yr⁻¹ at the provincial level, with an average annual growth rate of 10.52%, while vegetation carbon sinks declined slightly, from 54.52 to 53.20 TgC yr⁻¹. Both factors showed significant regional differences, with Pearl River Delta and North Guangdong contributing over 50% to provincial carbon emissions and carbon sinks, respectively; (3) Correlation analysis showed social-economic factors (GDP per capita and permanent resident population) have significant positive impacts on carbon emissions at the provincial and city levels; (4) The relationship between economic growth and carbon emission intensity suggests that carbon emission efficiency in Guangdong improves with economic growth. This study provides new insight for Guangdong to achieve carbon reduction goals and realize low-carbon development.