Pine Wilt Disease (PWD), a devastating epidemic, poses a severe threat to the carbon sink function and stability of China's forest ecosystems. However, accurate long-term quantification of carbon loss remains challenging due to historical data gaps and scale mismatches between macro-statistics and micro-ecological processes. To accurately quantify the forest carbon loss caused by PWD, this study integrates multi-source remote sensing products with national monitoring data across China. Methodologically, we proposed an innovative ensemble learning-based "stand-to-tree" scale conversion strategy to reconstruct mean biomass per tree (MBT) from macroscopic remote sensing observations, and designed a bottom-up approach to aggregate carbon loss from local outbreak patches to the national level. Results indicate that: (1) From 1998 to 2022, PWD caused a cumulative carbon loss of 12.06 Tg C (95% scenario envelope: 9.88-15.79 Tg C). The spatiotemporal evolution exhibited a "latent accumulation-diffusion-explosive growth" pattern, with 2017 as a critical tipping point, where hotspots shifted from the southeast coast to the Yangtze River basin and northern suitable habitats. (2) Landscape analysis revealed that PWD outbreaks were predominantly distributed near forest edges and were spatiotemporally associated with subsequent forest-boundary retreat. This study provides a detailed national carbon loss inventory and a scientific basis for understanding the spatial association between disease outbreaks and landscape patterns, facilitating the formulation of ecosystem-based control strategies.

The rational allocation of healthcare resources is vital for establishing a healthcare system that aligns with the levels of economic and social development. As a comprehensive discipline integrating geography, cartography, remote sensing, and computer science, Geographic Information System (GIS) can visualize and analyze spatial information through mapping. By utilizing GIS's statistical analysis and data visualization functions, this study provides a more efficient and intuitive analysis of Shanghai's spatial healthcare resource allocation and a more comprehensive assessment of its current allocation status. To examine the spatial correlation and spatial proximity, we apply the Global Moran Index (Moran's I), the Local Indicators of Spatial Association (LISA) test, and Hot Spot Analysis (Getis-Ord Gi∗) for assessment. Furthermore, by utilizing the Lorenz curve and Gini coefficient, this study provides a new perspective by expanding the measurement dimensions for assessing healthcare resource allocation in Shanghai. The results show that: From the global spatial correlation perspective, the allocation of healthcare resources in Shanghai exhibits spatial clustering. From the local spatial correlation perspective, healthcare resources in Shanghai show significant regional disparities, with resources concentrated in central urban areas. And from a multidimensional perspective, the equity of allocation of healthcare resources in Shanghai in 2022 was higher when measured by population (0.298 ± 0.063) and economy (0.292 ± 0.027) than by geographic area (0.612 ± 0.100) and green spaces (0.590 ± 0.110) of the Gini coefficient. These findings offer valuable insights for promoting the structural optimization and spatial distribution of healthcare resources in Shanghai.

Oedaleus decorus asiaticus (O. decorus) is a significant pest in the grasslands of Inner Mongolia, posing considerable challenges to the development of animal husbandry. To understand the key factors influencing the population distribution of O. decorus, field surveys were conducted from 2018 to 2020, during which the population count, growth stage, and location information of O. decorus were recorded. Daily soil moisture (SM) data and daily land surface temperature (LST) data were obtained from the National Tibetan Plateau Data Center, and a Generalized Additive Model (GAM) was constructed. Our findings indicate that the SM (S8) in August of the previous year is the most critical factor, with an F-value of 27.422, followed by the LST (L10) in October of the previous year, the LST (L6) in June of the survey year, the SM (S9) in September of the previous year, the LST (L3) in March of the survey year, and the LST (L5) in May of the survey year, with F-values of 7.848, 7.223, 5.823, 4.919, and 3.547, respectively. S8 and S9 can be regarded as vital indicators for predicting and monitoring the occurrence of O. decorus. However, the contributions of S8 and S9 to O. decorus density differ considerably. S8 is negatively correlated with O. decorus density, while S9 values below 0.29 m3/m3 can promote the growth of O. decorus. A higher LST during early overwintering correlates with increased O. decorus density. During the survey year, LST emerged as the primary factor affecting grasshopper density. Additionally, it plays a more complex role during incubation periods. This study clearly identifies SM and LST as the major factors influencing the occurrence of O. decorus, which will aid in predicting and monitoring its density.

Identifying the interactions of land use functions (LUFs) is of great significance for alleviating the contradiction between human and land, and promoting sustainable use of land resources. However, few studies concerned the interactions of LUFs in urban agglomerations of ecologically fragile areas in China at a fine scale. In this study, we constructed a quantitative and visualized evaluation system of LUFs that conforms to three primary functions, ten sub-functions, and nineteen indicators of Lanzhou-Xining urban agglomeration (LXUA) in the upper reaches of the Yellow River basin based on the production-living- ecological functions. Then, the comprehensive evaluation method, hot spot analysis, and geographic weighted regression (GWR) model were used to identify the interactions among LUFs and influencing factors of LXUA from 2000 to 2020 at the county and grid scales. The results show that the LXUA is dominated by ecological function (EF), and EF and living function (LF) showing a “U” shaped change feature, while production function (PF) show an inverted “U” shaped change feature. Meanwhile, the cold spots and hot spots of PF and EF present the spatial characteristic of “overall dispersion and local aggregation”, while the LF has no cold spots, and the hot spots present the spatial characteristic of “point-axis”. Moreover, the PF and LF are in a synergistic relationship at two scales, with complementarity in space, while the EF and PF and the PF and LF are both in a trade-offs relationship, with overlap in space. Finally, socioeconomic development factors have remarkable impact on LUFs at the county scale, while LUFs at the grid scale is the comprehensive result of natural conditions, socioeconomic factors, accessibility and political factors. The results can provide references for the LXUA to differentiated design the land use policy, and provide empirical case for other ecologically fragile areas to alleviate the trade-offs of LUFs.

China’s forests, which balance atmospheric carbon (C) levels through photosynthesis, play a crucial role in combating global climate change. The emergence of Pine wilt disease (PWD), caused by the pine wood nematode (PWN, Bursaphelenchus xylophilus), has challenged the stability of these forests, leading to significant tree mortality and disrupting the original ecological balance. However, the impact of PWD on carbon storage and recovery in Chinese forests remains unclear. In this study, we integrated multiple data sources, including forest surveys, remote sensing, and meteorological observations, and applied a method of finely partitioning the resistance of host pine trees across China. Using the MaxEnt model, a live carbon risk model, and a C recovery REGIME model that incorporates disturbance mechanisms, we predicted the forest C risk loss caused by the comprehensive invasion of PWD and assessed the C recovery time for affected forests. We estimate that the total risk of C loss due to PWD invasion under current climate conditions in Chinese forests is 483.23 Tg C, with an average C recovery time of 13.95 years. The main risk areas for PWD are concentrated in the southern coastal regions of China and adjacent provinces, presenting a risk spillover pattern that radiates from focal areas outward. The six provinces with the highest forest risk degree (risk C/total regional C) are, in order, Fujian (13.69%), Zhejiang (9.42%), Hunan (7.49%), Guangxi (7.40%), Jiangxi (7.35%), and Guangdong (7.05%). Our findings indicate that the severe consequences of PWD invasion have transformed affected forests from C sinks to sources. This underscores the urgency of implementing effective measures to block its introduction and spread, thereby promoting the recovery and sustainable development of forest ecosystems.

The future of the ecologically fragile areas on the Qinghai-Tibet Plateau (QTP) is a matter of concern. With the implementation of the Western Development Strategy, the Lanzhou-Xining Urban Agglomeration (LXUA) has encountered conflicts and compromises between urban expansion, ecological protection, and farmland protection policies in the rapid development of the past 2 decades. These deeply affect the land use layout, making the ecological sustainable development of the ecologically fragile areas of the QTP a complex and urgent issue. Exploring the impact of different policy-led land use patterns on regional ecosystem services is of great significance for the sustainable development of ecologically fragile areas and the formulation of relevant policies. Following the logical main line of “history-present-future”, the Patch-level Land Use Simulation (PLUS) model, which explores potential factors of historical land use, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model were used to construct three future scenarios for the modernization stage in 2031 dominated by different land use policies in this study. These scenarios include the Business-as-Usual Scenario (BS), the Cropland Protection Scenario (CP), and the Ecological Protection Scenario (EP). The study analyzed and predicted land use changes in the LXUA from 2001 to 2031 and assessed carbon storage, habitat quality at different time points, and water yield in 2021. The results indicated that land use changes from 2001 to 2021 reflect the impacts and conflicts among the Western Development Strategy, ecological protection policies, and cropland preservation policies. In 2031, construction land continues to increase under all three scenarios, expanding northwards around Lanzhou, consistent with the actual “northward expansion” trend of Lanzhou City. Changes in other land uses are in line with the directions guided by land use policy. By 2031, carbon storage and habitat quality decline under all scenarios, with the highest values observed in the EP scenario, the lowest carbon storage in the BS scenario, and the lowest habitat quality in the CP scenario. Regarding water yield, the LXUA primarily relies on alpine snowmelt, with construction land overlapping high evapotranspiration areas. Based on the assessment of ecosystem services, urban expansion, delineation of ecological red lines, and improvement of cropland quality in the LXUA were proposed. These findings and recommendations can provide a scientific basis for policy makers and planning managers in the future.

Analyses of the scale and structural characteristics of construction land serve as the basis for optimizing the spatial pattern of territorial planning. Existing studies have focused mainly on the horizontal expansion of urban construction land. Therefore, based on the Google Earth Engine (GEE) platform, in this paper, we use high-precision land-use cover data, DEM data and socioeconomic data to construct the standard dominant comparative advantage index (NRCA) using the geological mapping analysis method and we systematically analyze the horizontal scale, slope spectrum characteristics, gradient effects and driving factors of construction land in the Lanzhou–Xining urban agglomeration (LXUA) from 1990 to 2020 at four scales: the urban agglomeration, provincial area, typical city and county (district) scales. The results of the study show that urban construction land, rural settlement land and other construction land in the LXUA show “linear”, inverted-“U” and “J” growth patterns, respectively. Three types of construction land show different spatial transfer characteristics. The scale and extent of climbing of urban construction land in the LXUA is gradually decreasing over time, and the number of climbing rural settlement lands in 2000–2010 was as high as 34 counties (districts), while the number of counties (districts) with strong climbing degrees of other construction land rose to 12 from 2010 to 2020. The relative hotspots of the slope-climbing phenomenon of the three types of construction land have gradually expanded spatially, with Lanzhou city and Xining city as the center, and the overall spatial characteristics are “more in the east and less in the west”. The population and GDP are the main factors influencing the slope-climbing phenomenon of urban construction land, while rural settlements are influenced mainly by natural conditions, and accessibility is the key factor affecting other construction land.

Grasshoppers can greatly interfere with agriculture and husbandry, and they will breed and grow rapidly in suitable habitats. Therefore, it is necessary to extract the distribution of the grasshopper potential habitat (GPH), analyze the spatial-temporal characteristics of the GPH, and detect the different effects of key environmental factors in the meadow and typical steppe. To achieve the goal, this study took the two steppe types of Xilingol (the Inner Mongolia Autonomous Region of China) as the research object and coupled them with the MaxEnt and multisource remote sensing data to establish a model. First, the environmental factors, including meteorological, vegetation, topographic, and soil factors, that affect the developmental stages of grasshoppers were obtained. Secondly, the GPH associated with meadow and typical steppes from 2018 to 2022 were extracted based on the MaxEnt model. Then, the spatial-temporal characteristics of the GPHs were analyzed. Finally, the effects of the habitat factors in two steppe types were explored. The results demonstrated that the most suitable and moderately suitable areas were distributed mainly in the southern part of the meadow steppe and the eastern and southern parts of the typical steppe. Additionally, most areas in the town of Gaorihan, Honggeergaole, Jirengaole, as well as the border of Wulanhalage and Haoretugaole became more suitable for grasshoppers from 2018 to 2022. This paper also found that the soil temperature in the egg stage, the vegetation type, the soil type, and the precipitation amount in the nymph stage were significant factors both in the meadow and typical steppes. The slope and precipitation in the egg stage played more important roles in the typical steppe, whereas the aspect had a greater contribution to the meadow steppe. These findings can provide a methodical guide for grasshopper control and management and for further ensuring the security of agriculture and husbandry.

Oedaleus decorus asiaticus is one of the dominant harmful pests in central Inner Mongolia, China. Large-scale outbreaks of this pest create many serious problems in animal husbandry and agriculture. Therefore, understanding the underlying mechanisms between plant losses and Odecorus at different density levels and growth stages can guide the development of monitoring and prediction measures to reduce damage. In this study, an unmanned aerial vehicle (UAV) carrying a camera was employed to collect multi-spectral data. Further, nine vegetation indices (VIs) were analyzed to explore the most suitable indices for estimating plant loss caused by O. decorus in different growth stages. The following results were obtained: (1) The second instar nymphs of O. decorus could promote vegetation growth. As the density level in each cage increased, the biomass of each cage increased (nymph density < 30 nymphs/m2) and then decreased (nymph density ≥ 30 nymphs/m2). When nymph density was greater than 60 nymphs/m2, the biomass in those cages decreased significantly. (2) With respect to the control group, large damage began to emerge during the third instar nymphal stage. In particular, the largest vegetation loss was caused by fourth nymphal larvae. (3) The ratio vegetation index (RVI) appeared as the most excellent index for reflecting Leymus chinensis loss caused by O. decorus at different growth stages. Nevertheless, the difference vegetation index (DVI) was better than the RVI in the fifth instar nymphal stage.

City health examination and evaluation of territorial spatial planning is a new policy tool in China. However, research on city health examination and evaluation of territorial spatial planning is still in the exploratory stage in China. Guided by sustainable cities and communities (SDG11), a reasonable city health examination and evaluation index system for Xining City in Qinghai Province is constructed in this paper. The improved technique for order preference by similarity to ideal solution (TOPSIS) was used to quantify the evaluation results, and the city health index was visualized using the city health examination signals and warning panel. The results show that the city health index of Xining City continuously rose from 35.76 in 2018 to 69.76 in 2020. However, it is still necessary to address the shortcomings in innovation, coordination, openness and sharing and to improve the level of city space governance in a holistic way. This study is an exploration of the methodology used in city health examination and the evaluation of territorial spatial planning in China, which can provide a foundation for the sustainable development of Xining City and also provide a case reference for other cities seeking to carry out city health examinations and evaluations of territorial spatial planning in China.

A Pressure-State-Response (PSR) model framework was used to construct an ecological security assessment index system and to evaluate the degree of ecological security for Qinghai Province in China from 1996 to 2015. Our results indicate that the degree of ecological security has increased between the years 1996 and 2015. During this time period the eco-environmental pressures in this region have been mitigated to some extent. From 1996 to 2011, the degree of ecological security was in a state of extreme warning and the regional ecological system was very insecure. From 2012 to 2015, the degree of security was in a state of serious warning and the regional ecological system was insecure. Pressure indexes increased from 0.068 in 1996 to 0.197 in 2015, accompanied by continuously increasing eco-environmental pressures. The state index during this period has also generally increased. On the whole, the response index from 1996 to 2015 showed an upward trend. During the economic development of the Qinghai Province, long-term consumption of the environment and the resources has made it difficult to significantly improve the eco-environmental condition of this region over a short-term period. The findings from our investigation provide references for future regional ecological environment administration and decision-making.

Natural capital is a basic condition for human survival, and its utilization evaluation is the core issue of regional sustainable development. Based upon the improved three-dimensional ecological footprint model, this study discusses the dynamic changes in natural capital time series and spatial patterns in Qinghai Province from 2011 to 2020. The driving factors of ecological footprint change were revealed using partial least squares (PLS). The results demonstrate that (1) from 2011 to 2020, the per capita ecological footprint of Qinghai Province will increase from 2.505 hm2/person to 3.125 hm2/person. The per capita ecological capacity is affected by resource endowment and is maintained at 3.982–4.160hm2/person, thus indicating a weak downward trend year by year. (2) During the study period, the per capita EFdepth, of Qinghai exhibited an overall growth trend and increased from 1.299 hm2/person to 1.419 hm2/person. The per capita EFsize was primarily affected by the ecological capacity and reached the highest value of 1.352hm2/person in 2019. The three-dimensional model demonstrates that the per capita EFsize (bottom area) changes slightly during the four periods. (3) Over the past 10 years, the capital flow occupancy rate of Qinghai Province has increased from 26.23 % to 30.90 % with an average annual growth rate of 1.65 %, this indicating a large potential for natural capital utilization. (4) The PLS model revealed that energy consumption, ecological construction, social consumption, population, and economic development are the primary factors affecting the increase in natural capital utilization in Qinghai Province. This study aims to provide a reference for promoting regional sustainable development goals, for achieving coordinated development of resources, the environment, and the social economy, and for accelerating the construction of ecological civilization.

Alpine meadow plants, adapted to humid and cold environments, are highly sensitive to environmental factors such as drought and heat. However, the physiological responses of individual alpine meadow species to drought and heat stress remain unclear. In this study, four representative species of typical functional groups in an alpine meadow of the Qinghai-Tibet Plateau were selected as experimental materials. Heat (H1, H2), drought (D1, D2), and combined stress (D1H1, D2H2) treatments were implemented to reveal the biomass and physiological characteristics’ response to a constant drought and heat environment. Our results showed that the leaf water content (LWC) of Kobresia humilis and Poa annua increased significantly under heat stress and the compound stress (P<0.05). The effect of a single factor on LWC was greater than that of multiple factors. The aboveground biomass (AGB) of Oxytropis ochrocephala and Saussurea pulchra decreased significantly under compound stress (P<0.05). The response patterns of the net photosynthetic rate (Pn) and transpiration rate (Tr) of K. humilis and P. annua under various stress treatments were similar; as were those of O. ochrocephala and S. pulchra. The stomatal conductance (Gs) variation in K. humilis, P. annua, O. ochrocephala, and S. pulchra were the same under three kinds of stress treatments. The photosynthetic characteristics were more sensitive to the effects of composite than those of single factors. The drought × heat × species treatment had a significant influence on various indexes except on height (Ht) and the belowground biomass (BGB) (P<0.01). Within a certain range, daytime temperature (DT) promoted the Ht and increased the LWC of the plants, while it inhibited their AGB and intercellular CO2 concentration (Ci). The Pn, Tr, and Gs were more sensitive to soil moisture than to DT. The results help improve understanding of the physiological response regularity of representative alpine meadow plant species to continuous drought and high temperature conditions at the species level, and provided experimental data and theoretical basis to identify the decisive factors of stress response.

(1)change class code: 1:"gain"2:"loss"3:"gain then loss": afforested areas are eventually destroyed back to non-forest land4:"loss then gain":forest areas recovered or replanted after disturbances (2)Citation Please cite the dataset including version number and the following paper when using this forest change result: Jing Guo, Peng Gong, Iryna Dronova & Zhiliang Zhu (2022) Forest cover change in China from 2000 to 2016, International Journal of Remote Sensing, 43:2, 593-606, DOI: 10.1080/01431161.2021.2022804 (3)Notes 1. We encourage people to send us feedback if you found some mistakes while using this data via email. 2. Welcome discussions around potential collaborations. 【You can email Jing (guoj15@tsinghua.org.cn).】

Establishing a national park system is an important component of the ecological identity of China and an essential measure to achieving natural and ecological protection though governance systems. The goal was to create a model province that integrated environmental protection, ecological integrity, management and support systems, coordinated development, comprehensive evaluation, and livelihood protection, with national parks serving as the main body. A further goal was to obtain a reference and basis for the official establishment of a number of national parks and the initial establishment of a national park system in 2021. Based on the progress of the pilot national park system in Qinghai, in this study, we have summarized some common and individual problems encountered in the construction of a model national park province. Further, five key foci were revealed during the 14th Five-Year Plan period: resource management and functional areas, ecosystem protection, support system construction, coordinated community development, and nature education and ecological experience.

China is undergoing rapid urbanization, which has caused undesirable urban sprawl and ecological deterioration. Urban growth boundaries (UGBs) are an effective measure to restrict the irrational urban sprawl and protect the green space. However, the delimiting method and control measures of the UGBs is at the exploratory stage in China. In this paper, a cellular automata model based on multi-criteria evaluation (MCE-CA) was proposed to delimit the UGBs. The MCE-CA model considers influencing factors related to urban growth and generates UGBs based on spatiotemporally dynamic simulations. The MCE-CA model was applied to generate the UGBs of Jiayuguan City in 2020 and 2030, the results show that the simulation accuracy is higher than 0.8 and the compactness increases to 0.23, which demonstrates that the MCE-CA model is an effective model for delimiting UGBs. Moreover, the MCE-CA model can corporate the contradiction between environmental protection and urban development, promoting urban smart growth and sustainable development. UGBs is an effective tool for China to realize ecological civilization construction and improve the spatial governance ability, and the MCE-CA model can be used to assist planners in delimiting future UGBs, this study provides a methodological reference for future research of UGBs in Chinese cities.

The study area of this paper is the Qinghai alpine agricultural mountain area. An ecological security early-warning model is used to identify the early warning signs of ecosystem destruction, environmental pollution and resource depletion in districts and counties from 2011 to 2018. A combination of qualitative and quantitative early-warning models is used to predict the existence of hidden or sudden advance warnings. The grey (1, 1) model (GM) is used to predict the evolution trend of ecological security warning situations from 2019 to 2021. On this basis, GIS technology is used to analyze the spatial pattern changes in three periods. The results show that from 2011 to 2018, the ecological environment in Qinghai's alpine agricultural mountainous area gradually improved. In 2018, the ecological security early-warning values of all districts and counties were greater than the 2011 values. However, in 2018, the ecological security early-warning levels of PA, LD and HZh (PA, LD and HZh refer to Ledu District, Ping'an District and Huzhu Tu Autonomous County respectively.) were in the "good" ecological early-warning state, while the ecological security levels of other cities were still in the "moderate" or "mild" ecological warning state. According to the prediction results, the early-warning level of ecological security in Qinghai's alpine agricultural mountainous areas will improve further in 2021, with the "good" states dominating. From a spatial perspective, the ecological environment in the northeast region is better than that in the southern region, and the internal differences in the ecological security early-warning levels tend to narrow. Thus, we propose that areas with different ecological security levels should focus on the management and protection of the ecological environment or carry out ecological restoration or reconstruction. The aim of this paper is to provide a reference for the improvement of the ecological environment in general and the sustainable development of the economy and society as well as the ecological environment of alpine agricultural mountainous areas in particular.

Enclosure is playing an important role in the storage of soil organic carbon (SOC) and root biomass accumulation in desert steppe. However, plant community types are complex and diverse in desert steppe of Inner Mongolia, northern China. This study analyzed relationships between plant communities and surface soil organic carbon stock (SOCS) in a desert steppe environment of Inner Mongolia. Total root biomass for S. breviflora, K. cristata, L. chinensis, S. krylovii, C. ammannii and A. mongolicum were 268.00, 731.71, 356.16, 305.73, 229.21 and 299.74 g/m2, respectively. Average SOC for S. breviflora, K. cristata, L. chinensis, S. krylovii, C. ammannii and A. mongolicum were 7.54, 11.75, 8.40, 7.14 6.07 and 7.17 g/kg, respectively. The upper 0-10 cm soil contained the highest amounts of root biomass and SOC, both of which gradually decreased with soil depth. Total SOCS for the six different types of plant communities ranged from 2.77 to 4.49 kg/m2 at 0-30 cm soil depth. SOC correlated positively with root biomass, clay and silt content and negatively with sand content over the 0-30 cm interval. Stratification ratios (SRs) of SOC increased with soil depth for different plant communities (except C. ammannii and A. mongolicum). This indicates better soil quality associated with S. breviflora, K. cristata, L. chinensis and S. krylovii, communities. Due to their influence on SOC distribution and soil properties, root systems are a key factor in grassland restoration. Root systems of plant communities in desert steppe environments also appear to represent major carbon sinks.

Based on the ecological footprint (EF) model, the dynamic changes in the per capita EF and per capita ecological carrying capacity (EC) in Qinghai Province from 2007 to 2017 were quantitatively analysed. The grey GM(1,1) prediction model was used to predict the per capita EF, per capita EC, and EF of ten thousand yuan of GDP. Additionally, the spatial change characteristics of the sustainable development status of the study area in four time periods were analysed using GIS technology. The results showed the following. (1) In the 11-year study period, Qinghai Province’s EF per capita grew gradually, increasing from 2.3027 hm2 in 2007 to 2.9837 hm2 in 2017. (2) The EC per capita in Qinghai Province remained a slight linear upward trend. (3) The environmental sustainability in Qinghai Province deteriorated over time. (4) According to the spatial characteristics, the overall sustainable development state changed markedly in the eastern region but was stable in the central and western regions. This paper proposes some countermeasures and suggestions to help Qinghai Province work towards sustainable development, such as controlling the population, adjusting the industrial structure, developing a low-carbon circular economy, and implementing ecological engineering.