Sustainable development is a significant scientific issue of global concern. Geography, as a comprehensive discipline focusing on the coupled relationship between human activities and the natural environment, provides systematic research and solutions for achieving the United Nations Sustainable Development Goals (SDGs). However, there is currently a lack of comprehensive reviews. This paper summarizes the theoretical framework and research progress of Geography supporting the SDGs and explores its future key research areas. This article indicates that: (1) Geography, in conducting integrated research on human-nature systems and serving regional and global sustainable development processes, has innovatively proposed and developed theoretical frameworks such as social-ecological systems, pattern-process-service-sustainability, metacoupling, and Classification-Coordination-Collaboration. These research frameworks include elements of human-environment system interconnections, process coupling, spatial coupling, and systematic regulation oriented towards SDGs, forming a comprehensive theoretical framework supporting sustainable development research in Geography, also referred to as "sustainable geography theoretical framework". (2) Geography has made positive progress in supporting the United Nations SDGs research in areas such as multi-source data acquisition, localization of indicator systems and multi-scale progress assessment, analysis of inter-target linkage mechanisms, and SDG achievement pathways. Geography provides important theoretical and methodological support for SDG research. (3) Geography and sustainable development-related research mainly focus on climate-ecological crisis response, sustainable utilization of food-energy-water resources, regional development and planning, human well-being and social governance, and the construction of SDG assessment indicators and databases. (4) In future research, there is a need to innovate and develop sub-disciplines of Sustainable Geography, optimize the construction of SDGs indicator systems, develop SDGs assessment and decision-making models, strengthen artificial intelligence geography, deepen research on human-nature system coupling, and promote regional and global sustainable development in the process of advancing innovation in the discipline of Geography.
Rural development in the new era has ushered in material development opportunities but it is still faced with significant problems of imbalance and inadequacy. Rural social innovation is not only an important endogenous driving force to promote socioeconomic development and reform, but also a key force to break the dual "exogenous-endogenous" structure in rural areas, realize their neo-endogenous development, and promote the full implementation of the rural revitalization strategy to build a livable, viable, and beautiful countryside. This study interprets the conceptual characteristics of social innovation and rural social innovation in the theoretical perspective, sorts out the practical evolution of rural social innovation at home and abroad, explains the internal logic of rural social innovation and rural revitalization in the new era, summarizes the pathway for the realization of rural social innovation to promote rural revitalization, and looks ahead to the future key research areas of rural social innovation. The results show that the essence of rural social innovation lies in enhancing the active capabilities of rural society to achieve sustainable social benefits and promote rural sustainable development. From the perspective of social innovation theory, China's rural development has gone through an initial trial stage, a tortuous exploratory stage, a formal practice stage, and an innovative development stage. Rural social innovation plays a positive role in promoting rural revitalization and neo-endogenous development through innovation initiatives, processes, representation, and goals. In addition, rural revitalization can also react to and strengthen rural social innovation. According to the strategic and practical needs of rural revitalization, one method for promoting rural revitalization through rural social innovation is to reconstruct the relationships among the government, markets, and society. Future research into rural social innovation in the new era should be focused on examining its logical evolution and theoretical exploration, identifying its key elements and invisible thresholds, summarizing its network evolution and driving mechanism, and realizing its dynamic tracking and effect evaluations to provide theoretical guidance and a practical reference for the neo-endogenous development of rural revitalization in China.
The optimal allocation and scientific management of rural logistics resources is the key to unblock the domestic transportation cycle, and it is also the focus of the construction of a powerful transportation country and the integration of urban and rural transportation. From two perspectives of driving and walking, this study constructs a research framework for the evaluation of rural logistics terminal distribution with accessibility and equity. This study analyzes the accessibility of 440000 administrative villages in China and their nearest rural logistics terminal facilities. By using the online map tool, this study reveals the spatial distribution pattern and regional differences of rural logistics terminal facilities, and evaluates the spatial equity of rural logistics terminal facilities at the county level with Lorenz curves and Gini coefficients. The results show that: (1) Accessibility of rural logistics terminal facilities presents significant regional difference, and it declines from the coast to the interior, which is consistent with the socio-economic development pattern in China. (2) Accessibility of logistics terminal facilities presents significant urban-rural differences. According to the comparative analysis of travel distance, travel time, and travel modes, the urban-rural differences have been widened on travel time and by walking. (3) Based on the analysis with rural population distribution, the distribution of rural logistics terminal facilities presents the transport-related exclusion. The above findings can provide scientific support for the scientific layout of rural logistics terminal facilities so that we could promote the people-oriented integrated development of urban and rural transportation, and assist rural revitalization, so as to achieve common prosperity.
Lunar landforms, characterized by the elevation variations on lunar surface, is a result of diverse internal and external forces acting upon it since its formation. Lunar geomorphological classification serves as the cornerstone of lunar geomorphology research and is crucial for lunar geomorphology mapping. This study draws inspiration from terrestrial geomorphological classification systems to propose a comprehensive framework for categorizing lunar landforms. We consider multiple factors, including macroscopic morphology, genesis, morphological characteristics, combinational morphology, sub-morphology, slope morphology, material composition, and age. Based on these indicators, the paper constructs a multi-level classification scheme for lunar landform types, encompassing nine levels. To demonstrate the applicability of this multi-level classification, we conducted a case study in the Chang'e-5 sample return area. We generated a detailed geomorphological map and established a corresponding database of lunar landform types for the landing area. This research provides a foundational framework for lunar geomorphological mapping and offers valuable insights into the evolutionary processes that have shaped the lunar surface. The proposed classification scheme can serve as a reference for future lunar exploration missions and contribute to a deeper understanding of the evolutionary process of lunar landforms.
The physical geography and hydroclimatic conditions in the arid region of in northwestern China leading to diverse flood-generation mechanisms. Under the influence of global and regional climate change, the spatiotemporal variation of floods and flood-generation mechanism in this region is still unclear and restricts flood prevention and mitigation and the implementation of the Belt and Road Initiative in the major regions. Based on the series of the annual maximum flood peak discharge in 58 river basins in the study area from 1961 to 2017, we analyzed and revealed the mechanisms, spatial distribution and interannual variation characteristics of flood in the basin in the past 60 years based on statistical tests and machine learning approaches. The results show that the frequency of extreme floods and the annual maximum flood peak discharge magnitude are increasing, with the maximum increase in the frequency of extreme floods at about 0.84 times/10 years, and the maximum increase in the annual maximum flood peak discharge magnitude at about 29%/10 years compared with the multi-year average, and the largest increase is mainly observed in the eastern Tianshan Mountains and the Qilian Mountains. There are three main flood generation mechanisms, i.e., rain (R), snow (S) and mix (M), the frequency of R and M floods increased significantly, while the frequency of S floods decreased. The contribution of flood mechanisms transformation to the increase of annual maximum flood peak discharge magnitude can reach up to 38%, which is significantly higher than the contribution of a single hydrometeorological factor such as precipitation. The results of this study emphasize the importance of attributing and predicting the changes of flood characteristics in geographically complex region from the perspective of flood mechanisms. Engineering hydrological design in the changing environment also needs to consider the influence of the heterogeneity of flood samples caused by different flood mechanisms on the flood frequency analysis, so as to provide scientific support for flood risk management and response in the basin.
The morphological characteristics of floods are important indicators for flood prevention and control, and have important indicative significance. Traditional hydrological studies mainly focus on the change of characteristics in flood magnitude under the changing environment, and the characteristics and mechanism of changes in flood morphological parameters under the influence of urbanization and climate change remain to be further explored. Taking the highly urbanized river network area of the Taihu plain as a typical example, this paper proposed a process-based method to identify flood events, and revealed the change in flood morphological characteristics and its driving mechanisms between 1971 and 2020. The results show that not only the flood magnitude (peak water level and water level increment) but also the morphological characteristics of flood fluctuation (such as rate of rising limb and recession) have changed significantly in the Taihu plain under the background of changing environment. Impervious area has a non-linear effect on the flood morphological characteristics. In the study area, the stations with significant breakpoint for peak water level occupy 61.5%, and 76.9% stations showed a significant upward trend. 46.2% of the stations have a significant breakpoint for rate of rising limb, and all stations showed an increasing trend, among which, 38.5% of the stations reach the significance level. A total of 53.8% of the stations have significant mutation and significant trends of recession rate, and the recession rate reaches 0.628 mm·d-1·a-1 in the whole period in the study area (p<0.05). The antecedent water level conditions and rainfall characteristics are the main driving factors affecting the flood morphological pattern in the river network area of the Taihu plain. The results of this study could deepen the understanding of flood evolution in the Taihu plain region under a changing environment, and provide reference and support for flood disaster prevention and control in similar plain river network areas.
Palaeoflood events are instantaneous responses of hydrological processes to extreme climate. Through field investigation, a loess-paleosol sedimentary profile containing a set of overbank flood deposits (OFD1, OFD2 and OFD3) that recorded the extraordinary palaeoflood events was found on the platform scarp of the Shahe River, a tributary of the Huaihe River. The sediment samples were collected, and the physical and chemical properties and optically stimulated luminescence (OSL) dating were analyzed. The results showed that the end-members analysis of particle size indicated that OFD1, OFD2, and OFD3 were overbank flood deposits affected by hydrodynamic forces. However, the particle size composition of OFD3 and OFD1 primarily consisted of sand (>60%), while the particle size composition of OFD2, S0, Lt and L1 was mainly silt (>70%). The magnetic susceptibility values of OFD3 and OFD1 were significantly higher than those of S0, Lt and L1, and the contents of Na2O, K2O and SiO2 were higher, while the contents of Al2O3 and Fe2O3 were lower in OFD3 and OFD1. The particle size composition, magnetic susceptibility value and geochemical element composition of OFD2 were similar to those of S0, Lt and L1, but significantly different from those of OFD1 and OFD3. These differences could be attributed to the varying material sources of OFD2, OFD3, and OFD1. OSL dating and a stratigraphic chronological framework of sedimentary profile indicated that the three extraordinary palaeoflood events were recorded during the late Holocene from 1550 to 1400 a BP in the Huaihe River basin. The analysis of high-resolution climate proxy indicators, atmospheric circulation factors, and global mean temperature demonstrated that the extreme flood events that occurred during the late Holocene from 1550 to 1400 a BP were a direct response to the abrupt climate changes, corresponding to the severe climate deterioration period of the Northern and Southern Dynasties in China. These findings are significant in understanding the regional response of hydrological climate change to global change.
Streamflow from the Lena River is one of the major sources of freshwater in the Arctic Ocean and has a significant impact on the Arctic atmosphere, sea ice thermal processes and ocean thermohaline circulation. In recent years, streamflow in the Lena River basin is changing significantly with intensified global warming. In order to investigate the response of streamflow to climate change in the Lena River basin, the study firstly analyzed the trends of precipitation, air temperature and streamflow in the basin from 1975 to 2014 using the M-K trend test. Then, we constructed the abcd-cr hydrological model by considering a coupled snowmelt and permafrost module. Based on the abcd-cr model, we simulated climatic scenarios and quantitatively estimated the relative changes of annual and seasonal streamflow and the elasticities of annual and seasonal streamflow to changes in air temperature and precipitation respected to different climate scenarios. Results showed that: (1) Both the annual and seasonal air temperatures in the Lena River showed increasing trends from 1975 to 2014; The annual, summer, and autumn precipitation presented increasing trends while the spring and winter precipitation showed decreasing trends; The annual, spring, autumn, and winter streamflow had significant increasing trends while the summer streamflow showed a non-significant decreasing trend. (2) The climate scenario simulation results quantified the variations in annual and seasonal streamflow resulting from changes in precipitation and air temperature. (3) The results of sensitivity analysis showed that annual streamflow increases with the increase of precipitation and decreases with the increase of air temperature; The impact of precipitation change on seasonal streamflow is similar to that of annual streamflow change. However, the impacts of air temperature varied in different seasons. Specifically, the relative change of summer streamflow is the largest, while that of winter streamflow is the smallest. The impact of air temperature on seasonal streamflow is more complex than that of annual streamflow due to the interactions between seasonal evaporation and freeze-thaw processes. With increasing air temperature, spring streamflow increases, while streamflow in other seasons decreases.
Understanding the stoichiometry of carbon (C), nitrogen (N) and phosphorus (P) in lake sediments is of great significance in enhancing the stoichiometric studies of terrestrial water ecosystems and revealing the response trajectory of biogenic elements between macrophyte- and algae-dominated lake ecosystems. Based on 20 sediment cores covering the whole lake, the total organic carbon (TOC), total nitrogen (TN) and total phosphorus (TP) in the sediments of shallow eutrophic Yilong lake were measured, and the influence of macrophyte- and algae-dominated lake on the carbon, nitrogen and phosphorus stoichiometry was discussed. The results showed that the stoichiometric characteristics of C, N and P in lake sediments presented spatial and temporal heterogeneity. The contents of TOC, TN and TP in the algae-dominated stage of Yilong lake were (4.83±1.47)%, (0.42±0.09)% and (0.04±0.01)%, respectively, which were significantly higher than those in the macrophyte-dominated stage ((3.87±0.98)%, (0.31±0.08)% and (0.03±0.02)%, respectively). The C∶N∶P value of 347∶26∶1 for the algae-dominated lake stage was significantly lower than that of the macrophyte-dominated lake stage (519∶35∶1). This reflected the effect of aquatic plant community succession during the macrophyte- to algae-dominated stage transformation, and the impact of altered water environments on the ecological stoichiometry of low homeostasis organisms. Among different elements, due to the composition of organic matter sources, the function and activity of chemical elements, the C and N elements in sediments of Yilong lake were mainly enriched in the estuary and littoral zone, while the P element was enriched in the deep-water area, resulting in a low coupling between the P element and the C and N elements. In the surface 0~15 cm layer, the burial amounts of TOC, TN and TP in the sediments of Yilong lake were 1829 t/km2, 160 t/km2 and 16 t/km2, respectively. The average burial rate in the top 0~5 cm (algae-dominated stage) was elevated by 30%-36% compared to the bottom 10~15 cm (macrophyte-dominated stage), but burial in the bottom 10-15 cm layer was 1.5 times higher than in the top 0-5 cm layer, as affected by water content. Comparison with other eutrophic lakes revealed that temperature greatly influenced the effective burial of organic matter in lakes and played a key role in regulating the source and sink functions of C, N and P in lake sediments. The high water temperature of Yilong lake made it easier for sediment nutrients to be released into the lake water, which aggravated the difficulty of lake ecological restoration. The ecological stoichiometry and burial characteristics of lake revealed in this study can provide an important scientific basis for deepening the understanding of C, N and P cycles in plateau lakes and evaluating nutrient burial.
Kashin-Beck disease (KBD) control in Xizang has now entered a new stage of consolidation and improvement. Clarifying the spatiotemporal mechanism of its regression is of great significance for promoting the long-term prevention and control of endemic diseases in the plateau. Based on the detection rate data of KBD in Xizang from 2000 to 2015 and by the methods of random forest and spatial statistics, this study analyzed the spatiotemporal variation characteristics of KBD and explored the main factors affecting the regression of KBD and their regional differences. The results showed that: (1) The condition of KBD decreased steadily in all parts of Xizang during 2000-2015. The spatial distribution of KBD gradually converged to the east from the overall pattern of high in the east and low in the west, high in the south and low in the north. The disease was the most serious and had the longest duration in Qamdo wards. (2) The top four major factors affecting the regression of KBD were per capita food consumption of farmers and herdsmen, per capita GDP, per capita disposable income of farmers and herdsmen, and NDVI. Except for NDVI, all the other factors showed negative correlations with the detection rate of KBD. (3) In Ali, the prevalence of KBD was mainly influenced by per capita GDP and the income level of farmers and herdsmen, while in the middle reaches of the Yarlung Zangbo River and Qamdo, wards were more affected by dietary factors. (4) The dominant factors for the prevalence of KBD varied greatly within different years, which specifically manifested as a shift from natural factors to humanistic and social factors. Social economy, dietary nutrition and land use patterns played important roles in the prevention and control of KBD in Xizang. In view of the unique environmental conditions in Xizang, strengthening diversified food supply and adhering to returning farmland to forests and grasslands are still the basic countermeasures for preventing and controlling KBD. Meanwhile, raising the economic development level of endemic areas and enhancing the dietary nutrition of local residents are the fundamental guarantees for the long-term prevention and control of KBD in the plateau.
The hydrochemical and isotopic compositions of water are controlled by natural and anthropogenic factors, therefore, it is of great significance to study the hydrochemical and isotopic compositions, changes and contributing factors for the rational utilization and scientific management of water resources within a watershed. Hydrochemistry, water (δD/δ18O-H2O) and carbon (δ13C-DIC) isotope samples from surface-groundwater in the Yulong Snow Mountains-Lijiang area, China, were analyzed to reveal the spatial evolution of the above indicators along the water flow direction, to compare the changes of water chemical compositions between 2005 and 2021, and to explore the spatio-temporal differences of regional water environment affected by human activities. Results showed that: (1) In the basin, surface water and groundwater were mainly recharged by local atmospheric precipitation and glacier-snow meltwater, and the water chemistry types were mainly Ca·Mg-HCO3 and Ca-HCO3, while the concentrations of Na+, K+, Cl- and increased in some wells due to human activities; (2) Under the influence of natural processes and human activities, δD/δ18O-H2O values increased along the direction of the surface-groundwater flow, while the value of δ13C-DIC decreased. Concentrations of Na+, K+, Cl- and increased significantly after water flows through the main urban area; (3) Water quality of the Yuhe River was reduced from class III to class IV (NH4+ exceeded the standard) after the river flows through the Dayan ancient town, and significant negative correlation between Na++K+ and δ13C-DIC, Cl-+ and δ13C-DIC occurred in wells from the ancient town, which revealed the negative impact of tourism activities on the water environment; and (4) Compared with 2005, the growth rates of Na+, K+, Cl- and concentrations in the Yanggong River, which were fed by urban sewage and wastewater, were greater than those of Lashi Lake, Yufengsi Spring and Tuanshan Reservoir waters. Our study revealed that human activities had a certain negative impact on the water environment in the Yulong Snow Mountain-Lijiang area, which provided basic data for water resources protection in the river basin and also confirmed that the combination of isotopes and water chemistry is an important means to study the water environment change and the contributing factors.
As the world's largest carbon dioxide (CO2) emitter and a major trading country, both anthropogenic and natural factors play an important role in China's carbon budget. However, previous studies mostly focused on evaluating anthropogenic emissions or the natural carbon cycle separately, and few included trade-related (import and export) CO2 emissions and its contribution to global warming. Using the CarbonTracker CT2019 assimilation dataset and China trade emissions from the Global Carbon Project, we found that the change trend of global CO2 flux had obvious spatial heterogeneity, which was mainly affected by anthropogenic CO2 flux. From 2000 to 2018, carbon emissions from fossil fuels in the world and in China showed an obvious increasing trend, but the magnitude of the increase tended to slow down. In 2018, the radiative forcing (RF) caused by China's import and export trade was 0.0038 W m-2, and the RF caused by natural carbon budget was -0.0027 W m-2, offsetting 1.54% and 1.13% of the RF caused by fossil fuels that year, respectively. From 2000 to 2018, the contribution of China's carbon emission from fossil fuels to global RF was 11.32%. Considering China's import and export trade, the contribution of anthropogenic CO2 emission to global RF decreased to 9.50%. Furthermore, taking into account the offset of carbon sink from China's terrestrial ecosystems, the net contribution of China to global RF decreased to 7.63%. This study demonstrates that China's terrestrial ecosystem and import and export trade are all mitigating China's impact on global anthropogenic warming, and also confirms that during the research process on climate change, comprehensively considering the carbon budget from anthropogenic and natural carbon budgets is necessary to a systematic understanding of the impacts of regional or national carbon budgets on global warming.
Urban agglomerations serve as crucial platforms for constructing substantial domestic circulation and fostering harmonious regional development in China. Given the evolution of the integrated development of urban agglomerations, the characteristics of their internal spatial networks inevitably lead to the carbon peak paths of individual cities being influenced by their proximate counterparts. Consequently, this study focused on the Yangtze River Delta urban agglomeration, which boasts a high degree of integration within China, constructed a spatial weight matrix based on composite geographic and economic dimensions, applied a spatial econometric model to analyze the spatial correlation of carbon emissions in this urban agglomeration, and further applied the spatially embedded Genetic Algorithm-Long Short-Term Memory (GA-LSTM) model to simulate dynamically the peak paths of carbon emissions in this urban agglomeration. The empirical results revealed several important findings: (1) Considering the spatial correlation effects of the urban agglomeration, the carbon peaks of several cities occur sooner than expected, and most cities experience a reduction in their peak level, indicating that the spatial correlation effect can effectively optimize the spatial pattern of carbon emissions. However, the post-peak emission dynamics of these cities are not significantly affected. (2) In the baseline scenarios, with the exception of Suzhou (Jiangsu) and Bozhou, all cities attain their carbon peak by 2030, with most cities in Anhui province maintaining a steady decrease in carbon emissions after 2019, some cities in Jiangsu and Zhejiang provinces experiencing a relatively slow decrease in carbon emissions after reaching the peak, and Shanghai and Nantong showing a rebound trend of slow increase in carbon emissions after reaching their peak at an early stage. (3) Under the green scenarios, the total carbon emissions from the Yangtze River Delta urban agglomeration follow a steady downward trend since 2019, effectively reversing the inertial growth under the baseline scenarios, and the cities within the urban agglomeration show significant improvement in the time to peak, peak level, and post-peak situation, which contributes to a synergistic emission reduction pattern.
The digital economy is a pivotal driver for fostering high-quality economic development in China, which is crucial in attaining carbon peak and neutrality objectives. Given its significance as a core vehicle for national urbanization initiatives, elucidating the influence and spatial implications of the digital economy on carbon emission efficiency at the county and district levels is imperative for China's new urbanization strategy, bolstering ecological civilization and advancing green transformation and development in the contemporary era. Utilizing the entropy weight method and the SBM-DEA model, this study assessed the digital economy's development level and carbon emission efficiency in 19 counties within the Changsha-Zhuzhou-Xiangtan metropolitan area spanning 2011 to 2021. Spatial analysis techniques were employed to delineate the spatiotemporal patterns and clustering characteristics of the digital economy and carbon emission efficiency at the county scale within this metropolitan region. Furthermore, we leveraged the OLS model and the spatial Durbin model to empirically scrutinize the impact and spatial effect of the digital economy on carbon emission efficiency in the study area. The key findings are as follows: (1) There exists a significant disparity in the development of the digital economy and carbon emission efficiency across the Changsha-Zhuzhou-Xiangtan metropolitan area, exhibiting a spatial distribution pattern characterized by "high in the north and low in the south". (2) The digital economy in this metropolitan area consistently exerts a noteworthy stimulatory effect on carbon emission efficiency, and this influence is markedly strengthened upon the inclusion of various control variables. (2) The digital economy in the Changsha-Zhuzhou-Xiangtan metropolitan area exhibits a substantial positive spatial effect on carbon emission efficiency, with a more significant impact on local carbon emission efficiency compared with neighboring counties.
In the context of rapid urbanization, promoting low-carbon school trips is a crucial strategy for fostering sustainable urban development. However, the factors influencing carbon emissions from school trips during compulsory education remain unclear. This study focuses on Kaifeng, a city experiencing rapid spatial expansion and reconstruction. Utilizing multi-source spatiotemporal big data, large-scale micro-surveys, and the SHAP model (an interpretable machine learning method), we explore the nonlinear mechanisms and threshold effects of low-carbon school trips. The results reveal the following: (1) Carbon emissions from school trips show significant spatial disparities, making rapid expansion of outer areas critical for emission reduction efforts. (2) Temporal and spatial accessibility are the most critical factors impacting carbon emissions. Secondary schools should be planned within a 15-minute walking circle, while primary schools need optimization to be within a 13-minute one. (3) Effective management of schools surrounding the built environment can support low-carbon school trips. Optimal conditions for low-carbon school trips include a road network density of 10-14 km/km2, a land use mix of 2.4-2.7, and primary schools accommodating up to 1000 people. (4) The lack of students' ability to travel independently also restricts low-carbon school trips. Developing safe routes and promoting walking school buses are effective strategies for creating child-friendly cities. The research results provide valuable insights for the refined planning and governance of urban education resource distribution and low-carbon development.
