Influence of land urbanization on carbon sequestration of urban vegetation: A temporal cooperativity analysis in Guangzhou as an example

Asymmetric response of vegetation GPP to impervious surface expansion: Case studies in the Yellow and Yangtze River Basins

Terrestrial gross primary production (GPP) changes due to impervious surfaces significantly impact ecosystem services in watersheds. Understanding the asymmetric response of vegetation GPP to impervious surface expansion is essential for regional development planning and ecosystem management. However, the asymmetric response of vegetation GPP to the impacts of impervious surface expansion is unknown in different watersheds. This paper selected the Yellow River and Yangtze River basins as case studies. We characterized the overall change in GPP based on changes in impervious surface ratio (ISR), determined impervious surface expansion's direct and indirect impacts on GPP in the two watersheds, and further analyzed the asymmetric response of the compensatory effects of indirect influences on the impervious surface expansion in different watersheds. The results showed that: (1) The vegetation GPP decreased with increasing ISR in the Yangtze River Basin, while that in the Yellow River Basin first increased and then reduced. (2) The direct impacts of increased ISR reduced vegetation GPP, while the indirect impacts both had a growth-compensating effect. Growth compensation stabilized at approximately 0.40 and 0.30 in the Yellow and Yangtze River Basins. (3) When the ISR was 0.34-0.56, the growth compensation could offset the reduction of GPP due to direct impact and ensure that the background vegetation GPP was not damaged in the Yellow River Basin. In contrast, the background vegetation GPP was inevitably impaired with increased ISR in the Yangtze River Basin. Therefore, this study suggests that the ISR should be ensured to be between 0.34 and 0.56 to maximize the impervious surface of the Yellow River Basin without compromising the background vegetation GPP. While pursuing impervious surface expansion in the Yangtze River Basin, other programs should be sought to compensate for the loss to GPP.

The spatial response of carbon storage to territorial space composition and landscape pattern changes: A case study of the Fujian Delta urban agglomeration, China

Understanding the impact mechanisms of territorial space composition and landscape pattern changes on carbon storage is critical to balance the development and utilization of territorial space and the conservation of the ecosystem. Thus, taking the Fujian Delta urban agglomeration (FDUA) of China as an example, this paper analyzed the impact of the transference in territorial space composition and the change in the coupling coordination degree (CCD) of landscape patterns on carbon storage based on the urban-rural gradient and grid scales. Results illustrated that the areas of agricultural, green, and blue spaces continued to decline, while the intensity of economic space expansion increased from 20.86 to 42.45% during 2000-2020. The grids with CCD change of landscape patterns declined mainly (accounting for 64.31%) in the first decade and rose mainly (accounting for 76.79%) in the second decade. The carbon loss of each under rural gradient was gradually serious. The percentage of grids with moderate and significant decrease in carbon storage escalated from 27.83 to 70.21%. Additionally, grids experiencing high carbon loss moved from the northeast coast to the southwest inland. The response of carbon storage change showed that the expansion of agricultural space occupied by economic space played a crucial role in the carbon loss in each urban-rural gradient. The carbon loss caused by supplementing agricultural space with green space increased from the urban to the field. Enhancing the CCD of landscape patterns can boost carbon storage, and the scattering expansion of economic space needs to be avoided. This paper provides a novel perspective to explore the spatial response of carbon storage change to the territorial space composition and landscape pattern evolution, which is important to optimize the territorial space pattern and improve the regional carbon sink capacity.

Synergies and trade-offs of ecosystem services affected by land use structures of small watershed in the Loess Plateau

The Chinese government has implemented a series of ecological restoration projects in the Loess Plateau (LP), and the surface cover changed dramatically, impacting the ecosystem services (ESs) greatly. In this study, we used K-means clustering to classify the land use structures (LUSs) of the LP from 1990 to 2015 at the small watershed scale, and investigated the effects of LUS on water supply (WS), soil conservation (SC), and carbon sequestration (CS, expressed as NPP) with constraint lines. The values of WS and SC were obtained from the InVEST simulation, validated by the hydrographic station data. The results showed that the LUSs in LP were cropland structure (CLS, distinguished with CS), forest structure (FS), grassland structure (GS), crop-grassland structure (CGS), crop-forest-grassland structure (CFGS) and a very few areas of barren structure (BS). The proportion of dominant land use in those LUSs with a balance of WS, SC, and CS was 0.6-0.7 (cropland in CLS), 0.5 (forest in FS), 0.45/0.4 (cropland/grassland in CGS), 0.75 to 0.85 (grassland in GS), and 0.15/0.4/0.25 to 0.35 (cropland/forest/grassland in CFGS), respectively. The types of constraint curves of ESs for those LUSs involves hump-shaped curve, negative convex, half-concave-waved curve and concave-waved curve. This study proposed a method to objectively delineate LUS and improved the constraint line method to make it suitable for cases with less data, innovatively presenting the variation of ESs inside LUSs, which may provide a reference for optimal land planning and sustainable development of social-ecological systems.

A review of applied research on low-carbon urban design: based on scientific knowledge mapping

The construction of low-carbon cities is an essential component of sustainable urban development. However, there is a lack of a comprehensive low-carbon city design and evaluation system that incorporates "carbon sink accounting-remote sensing monitoring-numerical modelling-design and application" in an all-around linkage, multi-scale coupling, and localized effects. This paper utilizes the Citespace tool to evaluate low-carbon city design applications by analyzing literature in the Web of Science (WOS) core collection database. The results reveal that low-carbon cities undergo four stages: "measurement-implementation-regulation - management." The research themes are divided into three core clustering evolutionary pathways: "extension of carbon sink functions," "spatialisation of carbon sink systems," and "full-cycle, full-dimensional decarbonisation." Applications include "Utility studies of multi-scale carbon sink assessments," "Correlation analysis of carbon sink influencing factors," "Predictive characterisation of multiple planning scenarios," and "Spatial planning applications of urban sink enhancement." Future low-carbon city construction should incorporate intelligent algorithm technology in real-time to provide a strong design basis for multi-scale urban spatial design with the features of "high-precision accounting, full-cycle assessment and low-energy concept."

The Impact of Urbanization on the Relationship between Carbon Storage Supply and Demand in Mega-Urban Agglomerations and Response Measures: A Case of Yangtze River Delta Region, China

Rapid urbanization in mega-urban agglomerations disturbs the balance of carbon storage supply and demand (CSD) and constrains the achievement of sustainable development goals. Here, we developed a socio-ecological system (SES) framework coupled with ecosystem services (ES) cascade and DPSIR model to systematically analyze the impacts and responses of urbanization affecting CSD. We quantified urbanization and CSD using multi-source remote sensing data, such as land use and night lighting, together with related socio-economic data, such as total energy consumption, population and GDP. We found that from 2000 to 2020, the urbanization of Yangtze River Delta region (YRD) led to a decrease of 2.75% in carbon storage supply and an increase of 226.45% in carbon storage demand. However, carbon storage supply was still larger than carbon storage demand, and the spatial mismatch of CSD is the most important problem at present. Therefore, it is necessary to explore the response measures from the comprehensive perspective of SES. We identified key ecological conservation areas using a Marxan model to protect the carbon storage capacity in ecological subsystems, and promoted a carbon compensation scheme based on both the grandfather principle and the carbon efficiency principle, reconciling the contradiction between ecological conservation and socio-economic development in the social subsystem. Finally, this study quantified the threshold of urbanization based on the carbon neutrality target at which CSD reaches an equilibrium state. This study proposed a SES framework, and a set of methodologies to quantify the relationship between urbanization and CSD, which will help mega-urban agglomerations to promote harmonious development of urbanization and ecological conservation and to achieve the carbon peak and carbon neutrality targets proposed by the Chinese government.

Analysis of the Spatio-Temporal Characteristics of Nanjing’s Urban Expansion and Its Driving Mechanisms

The expansion and evolution of urban areas are the most perceptible manifestations of the transformation of the urban spatial form. This study uses remote sensing images of Nanjing from 2001, 2006, 2011, 2016, and 2021, along with socio-economic data to analyse the spatio-temporal characteristics of the city’s urban expansion. Furthermore, we utilize a binary logistic regression to quantitatively analyse the driving forces in each stage. We find that from 2001 to 2021, Nanjing’s urban area expanded approximately 3.97 times. Notably, the city started moving from a stage of medium-speed development to rapid development in 2006, and then slowed down and returned to medium-speed development in 2011. The urban land mainly expanded in the north, northeast, southeast, and southwest directions in a lopsided cross-shape roughly along the northwest-southeast direction; meanwhile, the city’s centre of gravity continuously moved towards the southeast. Among the driving factors, neighbourhood (distance from planned commercial centres, railways, and highways), topography, and geolocation (distance from the Yangtze River, and elevation) had a greater, albeit inhibitory effect on urban expansion. However, the effects of different socio-economic factors (GDP per capita, resident population, secondary and tertiary industry, etc.) varied across different time periods.

Experimental Study on the Carbon Sequestration Benefit in Urban Residential Green Space Based on Urban Ecological Carrying Capacity

The CO2 concentration of urban residential green space in Changsha was experimentally investigated. Based on the experimental results, the variation characteristics and influencing factors of CO2 concentration in residential areas were analyzed considering both the measuring time and ecological plant structure. Then, through the concept of urban ecological bearing capacity, the carbon sequestration index of the urban residential areas was proposed in this paper. Finally, the regulating effects of varieties of vegetation on CO2 concentration among four urban residential areas were deeply analyzed and discussed. Results showed that green space with an ecological plant structure of trees-shrubs-grass exhibited greater improvement in the environmental carbon balance than those of shrubs or grass, and the atmospheric carbon sequestration capacity was significantly affected by the total quantity of the green space.

The Spatiotemporal Evolution and Prediction of Carbon Storage: A Case Study of Urban Agglomeration in China’s Beijing-Tianjin-Hebei Region

Due to rapid urban expansion, urban agglomerations face enormous challenges on their way to carbon neutrality. Regarding China’s urban agglomerations, 25% of the land contains 75% of the population, and all types of land are used efficiently and intensively. However, few studies have explored the spatiotemporal link between changes in land use and land cover (LULC) and carbon storage. In this work, the carbon storage changes from 1990 to 2020 were estimated using the InVEST model in China’s Beijing–Tianjin–Hebei (BTH) region. By coupling the Future Land Use Simulation (FLUS) model and InVEST model, the LULC and carbon storage changes in the BTH region in 2035 and 2050 under the natural evolution scenario (NES), economic priority scenario (EPS), ecological conservation scenario (ECS), and coordinated development scenario (CDS). Finally, the spatial autocorrelation analysis of regional carbon storage was developed for future zoning management. The results revealed the following: (1) the carbon storage in the BTH region exhibited a cumulative loss of 3.5 × 107 Mg from 1990 to 2020, and the carbon loss was serious between 2000 and 2010 due to rapid urbanization. (2) Excluding the ECS, the other three scenarios showed continued expansion of construction land. Under the EPS, the carbon storage was found to have the lowest value, which decreased to 16.05 × 108 Mg in 2035 and only 15.38 × 108 Mg in 2050; under the ECS, the carbon storage was predicted to reach the highest value, 18.22 × 108 Mg and 19.00 × 108 Mg, respectively; the CDS exhibited a similar trend as the NES, but the carbon storage was found to increase. (3) The carbon storage under the four scenarios was found to have a certain degree of similarity in terms of its spatial distribution; the high-value areas were found to be clustered in the northwestern part of Beijing and the northern and western parts of Hebei. As for the number of areas with high carbon storage, the ECS was found to be the most abundant, followed by the CDS, and the EPS was found to be the least. The findings of this study can help the BTH region implement the “dual carbon” target and provide a leading example for other urban agglomerations.

Expressing carbon storage in economic terms: The case of the upper Omo Gibe Basin in Ethiopia

Terrestrial carbon storage is important for planning decisions regarding climate change. Therefore, modelling the spatial distribution of carbon storage and valuation can help restore the sustainability of the ecosystems. This study aimed at showing the spatial and temporal variations in carbon storage and valuation in the upper Omo Gibe Basin. Land use/cover and carbon pool data based on field data collection and laboratory analyses supported by GIS and remote sensing were used. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) software was used for modelling carbon storage. The Global voluntary carbon market price and Tropical Economics of Ecosystems and Biodiversity (TEEB) data were used for describing carbon storage in economic terms. ANOVA was carried out to detect significant differences in carbon stock correlation with parameters. The results show that the annual carbon stock declined by 0.37 t/ha and the carbon market declined from USD 25.04 billion in 1988 to USD 24.01 billion in 2018. The highest loss of carbon storage and valuation was found in forest land followed by grazing land. Moreover, carbon stock was positively correlated with NDVI and habitat quality (p < 0.05). Slopes did not affect carbon stock (p > 0.05). This study helps promote and enhance carbon trading.

Study on the Comprehensive Improvement of Ecosystem Services in a China’s Bay City for Spatial Optimization

Ecosystem services are characterized by region and scale, and contribute to human welfare. Taking Yantai city, a typical bay city in China, as the example, its three representative ecosystem services: food supply (FS), carbon sequestration (CS) and water yield (WY) were chosen as study targets. Based on analyzation of six different aspects of the supply and variation characteristic of demand, this study tried to propose advices for comprehensive improvement of ecosystem services for spatial optimization. The results showed that: (1) ecosystem services supply was strong in central and southern areas of Yantai, while the northern coastal areas were relatively weak; (2) synergistic relationships were found of FS-CS, FS-WY and CS-WY both in 2009 and 2015, with the strongest one for FS-WY. Additionally, in the synergistic relationships, each pair of ecosystem services was dominated by one ecosystem service; (3) most of the three pairs of synergistic relationships had the tendency to strengthen with larger scales; (4) four ecosystem demands changing areas were observed and comprehensive improvement suggestions for them were proposed. This work provides a new attempt to improve ecosystem services based on its supply-demand relationship, which will give a baseline reference for related studies in Yantai city, as well as other similar bay cities.

A Preliminary Study on the Impact of Landscape Pattern Changes Due to Urbanization: Case Study of Jakarta, Indonesia

Urbanization is changing land use–land cover (LULC) transforming green spaces (GS) and bodies of water into built-up areas. LULC change is affecting ecosystem services (ES) in urban areas, such as by decreasing of the water retention capacity, the urban temperature regulation capacity and the carbon sequestration. The relation between LULC change and ES is still poorly examined and quantified using actual field data. In most ES studies, GS is perceived as lumped areas instead of distributed areas, implicitly ignoring landscape patterns (LP), such as connectivity and aggregation. This preliminary study is one of the first to provide quantitative evidence of the influence of landscape pattern changes on a selection of urban ecosystem services in a megacity as Jakarta, Indonesia. The impact of urbanization on the spatiotemporal changes of ES has been identified by considering connectivity and aggregation of GS. It reveals that LP changes have significantly decreased carbon sequestration, temperature regulation, and runoff regulation by 10.4, 12.4, and 11.5%, respectively. This indicates that the impact of GS on ES is not only determined by its area, but also by its LP. Further detailed studies will be needed to validate these results.

Decomposing the global carbon balance pressure index: evidence from 77 countries

Understanding the relationship between carbon emissions and vegetation carbon sequestration is essential for reducing the greenhouse effect. In this study, we constructed a carbon balance pressure index to measure the eco-environment pressure caused by carbon emissions in 77 countries from 2000 to 2015, and the logarithmic mean Divisia index decomposition method was used to identify the key factors related to carbon balance pressure. As the change in vegetation carbon sequestration is relatively stable, carbon emissions have become the direct cause of the rise in the global carbon balance pressure. The carbon balance pressure in advanced economies decreased slowly, while that in emerging economies increased but the growth rate decreased. The decomposition results showed that carbon intensity is the main factor restraining the rise of carbon balance pressure, while GDP per capita and land population pressure are the main driving forces, and vegetation carbon sequestration intensity plays only a small role. Further analysis showed that the restraining effect of carbon intensity can offset the incremental effect of GDP per capita in advanced economies, and the vegetation carbon sequestration intensity also has a positive impact, but not in emerging economies. Besides, different factors play different roles depending on the country. The conclusions were also supported by various robustness tests.

Spatiotemporal Evolution of Urban Expansion Using Landsat Time Series Data and Assessment of Its Influences on Forests

Analysis of urban land use dynamics is essential for assessing ecosystem functionalities and climate change impacts. The focus of this study is on monitoring the characteristics of urban expansion in Hang-Jia-Hu and evaluating its influences on forests by applying 30-m multispectral Landsat data and a machine learning algorithm. Firstly, remote sensed images were preprocessed with radiation calibration, atmospheric correction and topographic correction. Then, the C5.0 decision tree was used to establish classification trees and then applied to make land use maps. Finally, spatiotemporal changes were analyzed through dynamic degree and land use transfer matrix. In addition, average land use transfer probability matrix (ATPM) was utilized for the prediction of land use area in the next 20 years. The results show that: (1) C5.0 decision tree performed with precise accuracy in land use classification, with an average total accuracy and kappa coefficient of more than 90.04% and 0.87. (2) During the last 20 years, land use in Hang-Jia-Hu has changed extensively. Urban area expanded from 5.84% in 1995 to 21.32% in 2015, which has brought about enormous impacts on cultivated land, with 198,854 hectares becoming urban, followed by forests with 19,823 hectares. (3) Land use area prediction based on the ATPM revealed that urbanization will continue to expand at the expense of cultivated land, but the impact on the forests will be greater than the past two decades. Rationality of urban land structure distribution is important for economic and social development. Therefore, remotely sensed technology combined with machine learning algorithms is of great significance to the dynamic detection of resources in the process of urbanization.

Up on the roof and down in the dirt: Differences in substrate properties (SOM, potassium, phosphorus and pH) and their relationships to each other between sedum and wildflower green roofs

In urban areas green roofs provide important environmental advantages in regard to biodiversity, storm water runoff, pollution mitigation and the reduction of the urban heat island effect. There is a paucity of literature comparing different types of green roof substrates and their contributions to ecosystem services or their negative effects. This study investigated if there was a difference between sedum and wildflower green roof substrate properties (soil organic matter (SOM), potassium (K) and phosphorus (P) concentrations and pH values) of 12 green roofs in the city of Brighton & Hove. One hundred substrate samples were collected (50 from sedum roof substrates and 50 from wildflower roof substrates) and substrate properties were investigated using standard protocols. Comparisons were made between substrate characteristics on both types of roof substrate with a series of multiple linear regressions. Sedum roofs displayed significantly higher values of SOM, P and pH. There were significant positive relationships between SOM and K concentrations, SOM and P concentrations, pH and K concentrations and pH and P concentrations on sedum roofs. This study concluded that sedum roof substrates are more favourable for plant water use efficiency and also contained a significantly higher percentage of SOM than wildflower roofs. However, higher concentrations of P in sedum roof substrates may have implications in regard to leachates.

Spatiotemporal Dynamics of Carbon Storage in Response to Urbanization: A Case Study in the Su-Xi-Chang Region, China

Terrestrial ecosystem carbon storage plays an important role in mitigating global warming. Understanding the characteristics and drivers of changes in carbon storage can provide a scientific basis for urban planning and management. The objective of this study was to reveal the ways in which urbanization influences the spatial and temporal variations in carbon storage. In this study, we investigated the changes in carbon storage from 1990–2000, 2000–2010, and 2010–2018 in the Su-Xi-Chang region, which is a typical fast-growing urban agglomeration in China, based on the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. Moreover, we analyzed the impacts of urbanization-induced land-use changes on carbon storage. The results showed that in terms of space and time, the greatest loss of carbon storage occurred in developing urban areas and during the rapidly urbanizing stage. Our study revealed that the reduction in cultivated land was the greatest contributor to carbon stock losses. In addition, we found that some types of land use conversion can enhance carbon storage. Based on the results, some suggestions are proposed aimed at promoting urban sustainable development. This study also provides insights into enhancing urban sustainability for other urban agglomerations throughout the world.

Optimization of Land-Use Structure Based on the Trade-Off Between Carbon Emission Targets and Economic Development in Shenzhen, China

The approach of choosing an effective low-carbon land-use structure by multi-objective methods is commonly used in land-use planning. A common methodology is to calculate carbon emissions and conduct scenario simulations for the future. However, most Chinese cities have not implemented the methods for monitoring carbon emissions proposed by the Intergovernmental Panel on Climate Change (IPCC), especially Shenzhen, which is one of the fastest-growing cities in China. This study first calculated the carbon emissions for a typical year in Shenzhen under the guidance of the IPCC. Second, nighttime light data were used to spatialize the gross domestic product to obtain the economic benefit coefficients of the various land types. Finally, a multi-objective linear programming model was used to optimize the land-use structure under different scenarios for 2020 and 2025. The results show that (i) energy consumption contributed the most to local carbon emissions in 2016, at 94.75%; (ii) carbon emissions from paddy fields, animals, and humans were the second most dominant source; (iii) the intensity of carbon emissions from different land types in 2016 was variable; and (iv) compared with the natural scenario, an optimized land-use structure could reduce carbon emissions by 5.97% by 2020 and 12.61% by 2025. Under ideal simulation conditions, the simulated land-use pattern could not only meet the requirements of economic and social development, but also could effectively reduce carbon emissions, which is of great value to land managers and decision-makers.