Spatial Distribution Pattern and Influencing Factors of Physical Bookstores of Large Cities:A Case Study of Three National Central Cities in Western China

As cultural facilities,physical bookstore is an important part of urban infrastructure.Influenced by the development of social economy and the internet,physical bookstores also have become a combination of cultural space and tourism experience.In this case,it is necessary to explore the spatial characteristics and influencing factors of physical bookstores.This study uses Density-Based Spatial Clustering of Applications with Noise(DBSCAN),spatial analysis and geographical detectors to calculate the spatial distribution pattern and factors influencing physical bookstores in national central cities/municipality(hereafter using cities)in western China.Based on spatial data,population density,road density and other data,this study constructed a data set of the influencing factors of physical bookstores,consisting of 11 factors along 6 dimensions for 3 national central cities in western China.The results are as follows:first,the spatial distribution pattern of physical bookstores in Xi’an,Chengdu,and Chongqing is unbalanced.The spatial distribution of physical bookstores in Xi’an and Chongqing is from southwest to northeast and are relatively clustered,while those in Chengdu are relatively discrete.Second,the spatial distribution pattern of physical bookstores has been formed under the influence of different factors.The intensity and significance of influencing factors differ in the case cities.However,in general,the social factor,business factor,the density of research facilities,tourism factor and road density are the main driving factors in the three cities.There is a synergistic relationship between public libraries and physical bookstores.Third,the explanatory power becomes stronger after the interaction between various factors.In Xi’an and Chengdu,the density of communities and the density of research facilities have stronger explanatory power for the dependent variable after interacting with other factors.However,in Chongqing,the traffic factors have stronger explanatory power for the dependent variable after interacting with other factors.The results could provide a practical reference for the sustainable development of physical bookstores and encourage a love of reading among the public.

Spatial Distribution Pattern of the Steppe Toad-headed Lizard(Phrynocephalus frontalis) and Its Influencing Factors

Spatial distribution patterns are associated with life history and behavioral adaptations of animals. For studying the spatial distribution pattern of the steppe toad-headed lizard(Phrynocephalus frontalis) and its influencing factors,we conducted experiments in Hunshandake Sandy Land in Inner Mongolia,China in July 2009. By calculating the clustered indices,we found that the lizard was aggregately distributed when the sampling quadrat was smaller than 10 m × 10 m,and uniformly distributed when it was greater than 10 m × 10 m. The Nearest Neighbor Rule showed a clustering distribution pattern for P. frontalis and the distribution pattern was quadrat-sampling dependent. Furthermore,the cluster was determined by environmental factors when the sampling quadrat was smaller than 20 m × 20 m,but it was determined by both environmental factors and characteristics of the lizard when it was larger than 20 m × 20 m. Our results suggested that the steppe toad-headed lizards tended to aggregate into suitable habitat patches in desert areas. Additionally,we discussed that the lizard aggregation could be potentially used as an indictor of movement of sand dunes.

Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in Guizhou Province

Traditional villages have high historical,cultural,scientific,artistic,social and economic value.They reflect the harmony and balance among long-term production,human life and natural environment.They are a community of tangible and intangible cultural heritages,and have received extensive attention from political circles,academic circles and the public.Through the Arc GIS10.3 geographic information system,724 traditional villages in Guizhou Province,China are visualized,and the nearest neighbor index,geographic concentration index,imbalance index,kernel density estimation and other methods are employed to analyze the spatial distribution type,distribution balance,spatial agglomeration characteristics and influencing factors.Studies have shown that the traditional villages in Guizhou Province tend to be concentrated and distributed,spatially forming high-density areas in southeastern Guizhou,second high-density areas in Anshun,moderate-density areas in Tongren,and low-density areas in Zunyi.From the city (prefecture) scale,traditional villages in Guizhou Province are relatively concentrated in Qiandongnan Prefecture,Tongren City,Anshun City and Qiannan Prefecture.From a regional perspective,the distribution of traditional villages in Guizhou Province is uneven,mainly distributed in Qiannan,Qiandong and Qianzhong.Their spatial distribution is affected by factors such as natural environment,traffic accessibility,ethnic culture,and economic development.It reveals the spatial distribution characteristics and influencing factors of traditional villages in Guizhou Province,and provides relevant realistic and theoretical foundations for the protection,inheritance and innovative development of traditional villages.In addition,the formation mechanism of traditional villages needs to be further analyzed based on information reflecting the attributes of traditional villages such as village history,village types,site selection patterns,characteristic buildings,production and life.It is also necessary to improve the traditional village database and grading evaluation system,and formulate protection and development plans,to realize the activation and utilization of traditional village resources,and promote their renewal and modernization.

Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in Qiandongnan Prefecture

Taking the 409 traditional villages in Qiandongnan Miao and Dong Autonomous Prefecture announced by the Department of Housing and Urban-Rural Development of Guizhou Province from 2012 to 2019 as the research object,the distribution characteristics and influencing factors of the traditional villages was analyzed using ArcGIS 10.2 software and geographic proximity and other measurement methods.The results show that the spatial distribution of traditional villages in Qiandongnan prefecture presents an agglomeration pattern.The high-density distribution areas of traditional villages are Liping County,Congjiang County,Leishan County and Taijiang County.The distribution of traditional villages is mainly concentrated in the southern and central regions of Qiandongnan prefecture.The natural environment,social economy,national history and culture are the main factors affecting the spatial distribution of traditional villages in Qiandongnan prefecture.

Spatial Distribution Characteristics and Influencing Factors of National Wetland Parks in Shandong Province

Taking 68 national wetland parks(including pilot sites)in Shandong Province as the research objects,three time sections of 2011,2014 and 2017 were selected,to analyze the spatial distribution characteristics of national wetland parks in Shandong Province by using geographic concentration index,imbalance index and standard deviation ellipse method,and explore the infl uencing factors by using SPSS stepwise regression analysis.The results show that the spatial distribution of national wetland parks is extensive but unbalanced,with more in central Shandong and less in eastern Shandong,and the distribution of other regions is relatively uniform.National wetland parks in Shandong Province are distributed along the northeast-southwest direction and are increasingly moving east-west direction.The impacts of natural factors such as topography,hydrology and climate on the spatial distribution of national wetland parks are consistent.At the same time,human factors such as economic environment,traffi c accessibility and population status also play an important driving role.

Spatial Distribution of Hospitals in Handan City and Its Influencing Factors

Hospital is an important factor of people’s livelihood security,and the spatial layout of hospitals effectively ensures the medical convenience for residents.Location entropy and mathematical statistical analysis are used to study spatial distribution of hospitals.The results display that the distribution of medical facilities in Handan City is at a disadvantage level in Hebei Province,and medical facilities arr concentrated in the plain area.The layout of grade 3A hospitals in Hebei Province is characterized by urban centralization,and it is stronger in the east and weaker in the west.There is no medical facilities in Feixiang District of Handan City,and layout of medical facilities in Hanshan District and Congtai District is at advantage level of Handan City.The built-up area is the influencing factor for the distribution of medical resources.

Spatial distribution characteristics and influence factor analysis of landslides——case study of the Hanwang area in Qinba Mountains

The geological hazards of landslides in Hanwang Town, Ziyang County, Ankang City, Shaanxi Province, have emerged. Yet, the current understanding of the spatial distribution characteristics and influencing factors of landslides in this area remains unclear. Combining the results of remote sensing interpretation and field investigation, seven influencing factors, namely, elevation, slope direction, slope gradient, distance from rivers, distance from faults, engineering geologic lithology, and distance from roads, are selected for the study. The distribution characteristics of landslides in each influencing factor and the influence of the resolution of the Digital Elevation Model(DEM) on the results are statistically and analytically analyzed. Furthermore, two highrisk landslides within the study area were subjected to comprehensive analysis, integrating the findings from drilling and other field investigations in order to examine their deformation mechanisms. Based on this analysis,the following conclusions were derived:(1) 34 landslides in the study area, mainly small earth landslides, with a distribution density of 0.42/km~2, threatening 414 people and property of about 55.87 million Yuan.(2)The landslides in the study area easily occur in the <400 m elevation range;the landslides are developed in all slope directions, the gradient is mainly concentrated in the range of 10°–40°, the distribution density of the landslides is higher in the closer distance from the river and the faults(0–200 m), the landslide-prone strata are mainly the softer and weaker metamorphic rocks, and the landslides are mainly around roads.(3) The resolution of the DEM should be selected based on the specific conditions of the study area, the requirements of the investigation, and the scale of the landslide. Opting for an appropriate DEM resolution is advantageous for understanding the patterns of landslides and conducting risk assessments in the region.(4) The Zhengjiabian landslide is a traction Landslide. The landslide body is a binary structure of gravel soil and slate weathering layer, and the damage process can be divided into three stages:(1)damage to the leading edge and stress release,(2)continuous creep and cracking,(3)rainfall infiltration and damage. The predominant slope material in the Brickyard landslide comprises clay, and the landslide is triggered by a combination of the traction effect resulting from the excavation at the slope's base and the nudging effect caused by the stacking load of the brick factory. Additionally, the Brickyard landslide exhibits persistent creep deformation. The study results provide a scientific basis for disaster prevention and mitigation in the Hanwang Township area.

Spatial distribution and potential poverty-returning factors of former poverty-stricken villages in the Liangshan Mountains,China

Remote mountainous villages are at risk of falling back into poverty,despite having been lifted out of extreme poverty.However,there has been a lack of focus on the factors contributing to povertyreturn in these villages,which making it difficult to understand the risks and their underlying causes.This study investigates the spatial distribution of 546 key assistance villages(KAVs)in the Liangshan mountainous region,a former poverty-stricken area,using the average nearest neighbor(ANN)and kernel density estimation(KDE)methods.Linear regression and geographically weighted regression(GWR)models are then employed to analyze the relationship between the KAVs'economy and potential povertyreturning factors.The results show that KAVs are primarily located in elevation ranges of 1800-2500 m(31.87%),with slopes of 6°-15°(42.67%)and 2-3 km from the township(28.94%).The distribution of KAVs exhibits distinct spatial clustering,forming four gathering areas.Several factors impact the KAVs'economy positively,including the normalized difference vegetation index(NDVI),built-up area,grassland,and education facilities,while elevation has a negative effect.The built-up area has the most critical impact on the rural economy,followed by NDVI and elevation.Additionally,education facilities and grassland areas also have significant effects.The study suggests promoting the Ex-situ Poverty Alleviation Relocation Program(ESPARP)and increasing rural built-up areas,grasslands,and educational facilities as practical measures for preventing poverty return and promoting economic development promotion in remote mountain villages.

Study on the Spatiotemporal Pattern Evolution and Influencing Factors of Population Aging in Henan Province

This study utilized census data from Henan Province for the years 2000,2010,and 2020 to investigate the spatiotemporal evolution of population aging,defined by the proportion of the population aged 65 and above.Employing spatial analysis techniques such as spatial autocorrelation and the standard deviation ellipse,the research mapped out the progression and distribution of aging demographics.Furthermore,the study delved into the influencing factors of aging using an optimal parameters-based geographical detector.Results indicate a deepening degree of population aging in Henan Province,transitioning from an adult type to an old type structure.There is a marked positive spatial correlation among counties,with high-value aging areas initially decreasing,then increasing,and notably spreading from the central to the central and southern regions of the province.The center of gravity for population aging,specifically around Changge City and Xuchang City,exhibits a trajectory moving southeast before shifting northwest.Factor detection reveals that in 2000,2010,and 2020,the elderly dependency ratio predominantly influences the aging trend,with explanatory powers of 88.4%,87.9%,and 90.9%,respectively.Interaction analysis indicates that the interaction between the old-child ratio and the elderly dependency ratio has a strong explanatory power for the aging patterns in Henan Province,reaching 97.3%,97.0%,and 97.4%,respectively.

Structural characteristics and influencing factors of spatial correlation network for regional high-quality development in China

On the basis of measuring the regional high-quality development in China from 2011 to 2020,this study uses gravity model to build spatial correlation network,and uses social network analysis method to analyze the structural characteristics and influencing factors of correlation network.The results are shown as follows.First,from 2011 to 2020,the level of regional high-quality development in China is rising gradually,and the discrete characteristics between regions are gradually obvious,showing a step-like distribution structure decreasing from east to west.Second,the network density of regional high-quality development is generally low and tends to decline,but it has strong stability and correlation strength.Third,the spatial correlation network has an obvious core-edge structure.Shanghai is always at the center of the network and plays a significant intermediary role,while Qinghai and Xinjiang are always at the edge of the network.Fourth,the regional high-quality development association network can be divided into four major sectors:main benefit,net benefit,net spillover,and broker,showing the spatial correlation characteristics of inter-plate contact and intra-plate agglomeration.Fifth,the level of economic development,the level of urbanization and geographical proximity have a significant impact on the formation of regional high-quality development correlation network.

Temporal and spatial distribution of phytoplankton functional groups and role of environment factors in a deep subtropical reservoir

Phytoplankton and environment factors were investigated in 2015 and phytoplankton functional groups were used to understand their temporal and spatial distribution and their driving factors in Wanfeng Reservoir. Seventeen functional groups(B, D, E, F, G, J, Lo, MP, P, S1, T, W1, W2, X1, X2, Xph, Y) were identified based on 34 species. The dominant groups were: J/B/P/D in dry season, X1/J/Xph/G/T in normal season and J in flood season. Phytoplankton abundance ranged from 5.33×10~4 cells/L to 3.65×10~7 cells/L, with the highest value occurring in flood season and lowest in dry season. The vertical profi le of dominant groups showed little differentiation except for P, which dominated surface layers over 20 m as a result of mixing water masses and higher transparency during dry season. However, the surface waters presented higher values of phytoplankton abundance than other layers, possibly because of greater irradiance. The significant explaining variables and their ability to describe the spatial distribution of the phytoplankton community in RDA diff ered seasonally as follows: dry season, NH4-N, NO_3-N, NO_2-N, TN:TP ratio and transparency(SD); normal season, temperature(WT), water depth, TN, NH4-N and NO_3-N; flood season, WT, water depth, NO_3-N and NO_2-N. Furthermore, nitrogen, water temperature, SD and water depth were significant variables explaining the variance of phytoplankton communities when datasets included all samples. The results indicated that water physical conditions and hydrology were important in phytoplankton community dynamics, and nitrogen was more important than phosphorus in modifying phytoplankton communities. Seasonal differences in the relationship between the environment and phytoplankton community should be considered in water quality management.

Spatial Distribution of Traditional Villages and Influence Factors in Hunan Province

To develop and protect traditional villages reasonably, this paper applied Arc GIS Spatial Analyst Tools to analyze spatial distribution and infl uence factors of 101 traditional villages in Hunan Province. The research showed the agglomerate distribution of traditional villages in Hunan; from the city scale, distribution of traditional villages was concentrated mainly in West Hunan Tujia Nationality Autonomous Prefecture, Chenzhou, Yongzhou, Huaihua and Shaoyang; concentrated distribution of traditional villages in the fi ve major geographic regions showed poor equilibrium, West Hunan had the most concentrated traditional villages, and South Hunan has the second most; relatively closed regional environment, perilous hills, inconvenient transportation, and underdeveloped social economy contributed to the protection of traditional villages, and they were all signifi cant infl uence factors for the distribution of traditional villages in Hunan.

The spatial distribution of commuting CO_2 emissions and the influential factors:A case study in Xi'an,China

As the transport sector is a major source of greenhouse gas emissions, the effect of urbanization on transport CO2 emissions in developing cities has become a key issue under global climate change. Examining the case of Xi＇an, this paper aims to explore the spatial distribution of commuting CO2 emissions and influencing factors in the new, urban industry zones and city centers considering Xi＇an＇s transition from a monocentric to a polycentric city in the process of urbanization. Based on household survey data from 1501 respondents, there are obvious differences in commuting CO2 emissions between new industry zones and city centers： City centers feature lower household emissions of 2.86 kg CO2 per week, whereas new industry zones generally have higher household emissions of 3.20 kg CO2 per week. Contrary to previous research results, not all new industry zones have high levels of CO2 emissions; with the rapid development of various types of industries, even a minimum level of household emissions of 2.53 kg CO2 per week is possible. The uneven distribution of commuting CO2 emissions is not uniformly affected by spatial parameters such as job-housing balance, residential density, employment density, and land use diversity. Optimum combination of the spatial parameters and travel pattern along with corresponding transport infrastructure construction may be an appropriate path to reduction and control of emissions from commuting.

Wellness Tourism in the Qin Mountains Based on Influencing Factors

For wellness tourism destinations,the spatial distribution pattern is influenced by economy,natural environment,as well as other social factors.This study used questionnaire survey to investigate and count the factors influencing the spatial distribution of wellness tourism destination,and tried to analyze the effect of social and natural factors on the benefits of health care center and personnel rehabilitation through Excel.The result showed that the rehabilitation influences of wellness tourism destinations with different spatial distribution advantages on psychiatric patients are significantly different;if there is more investment in material resources,the rehabilitation of patients is comparatively better.The natural environment and humanistic environment have the best effect on the convalescence of psychiatric patients.Therefore,the humanistic factors and natural environment should be given priority during the construction of rehabilitation center,improving the rehabilitation efficiency of patients and reducing the investment cost of rehabilitation center.

THE CHARACTERISTICS OF TEMPORAL AND SPATIAL DISTRIBUTION OF TROPICAL CYCLONE FREQUENCIES OVER THE SOUTH CHINA SEA AND ITS AFFECTING OCEANIC FACTORS IN THE PAST 50 YEARS

The characteristics of temporal and spatial distribution of tropical cyclone frequencies over the South China Sea areas and its affecting factors in the past 50yrs are analyzed based on typhoon data that provided by CMA and Simple Ocean Data Assimilation （SODA）. The results show that the tropical cyclone frequencies from June to October show concentrated geographic distribution, for they mainIy distribute over the SCS area from 15 - 20°N. The characteristics present significant interdecadal changes. The impact of oceanic factors on the tropical cyclone frequencies in the SCS area is mainly realized by La Nina and La Nifia-like events before 1975 but mainly by E1 Nino and E1 Nifio-like events after 1975.

Spatial Distribution of <i>Anopheles sinensis</i>and Its Relationship with Natural Environmental Factors in Wanning County on Hainan Island, China

Anopheles sinensis is widely distributed in Wanning County, it is necessary to understand the spatial distribution characteristics of Anopheles sinensis in order to maintain the elimination of malaria in Wanning. During May and October 2009, we sampled adult mosquitoes at 36 villages within Wanning County on Hainan island, and collected meteorological and geographical data at each sampling site. We used these data to analyze the spatial distribution of adult Anopheles sinensis mosquitoes, and logistic regression analysis was applied to explore the association of the spatial distribution of Anopheles sinensis with the geographical and meteorological factors. We found that the density of Anopheles sinensis showed a significant positive spatial correlation. From May to October, on the whole, the high-density area was located in the central part of Wanning County. But each month there was a relatively high-density cluster, and their location and range were not exactly the same. From east to west, the density of Anopheles sinensis increased initially and then decreased, but from south to north, there were different trends in the periods of May to August and September to October. Logistic regression analysis showed that the main environmental factors related with the distribution of Anopheles sinensis were land use type, soil type, distance to road, air pressure and relative humidity. These analysis results showed that the distribution of Anopheles sinensis had obvious spatial heterogeneity in Wanning County, which was related with geographical and meteorological factors. The mechanism of these environmental factors on the distribution of Anopheles sinensis needs to be further studied.

Dynamic analysis of agricultural green development efficiency in China: Spatiotemporal evolution and influencing factors

Green development of agriculture is important for achieving coordinated and high-quality regional development for China. Using provincial data from 1990 to 2020, this work explored the dynamics of agricultural green development efficiency of 31 provinces in China, its spatiotemporal characteristics, and its driving factors using a super-efficiency slacks-based measure(Super-SBM), the Malmquist productivity index(MPI), spatial autocorrelation, and a geographic detector. Results showed that the overall agricultural green development efficiency showed a U-shaped trend, suggesting a low level of efficiency. Although a gradient difference was visible among eastern, central, and western regions, the efficiency gap narrowed each year. Technological progress and efficiency both promoted agricultural green development efficiency, especially technological progress. Agricultural green development efficiency had significant spatial aggregation characteristics, but Moran’s Ⅰ result showed a downward trend from 2015 to 2020, indicating a risk of spatial dispersion in the later stage. The provinces with high agricultural green development efficiency were mainly concentrated in the eastern region, while those with low efficiency were concentrated in the central and western regions. Agricultural green development efficiency was influenced by various factors, which showed differences according to time and region. The impact of the labor force’s education level and technological progress increased during the study period, and significantly facilitated agricultural green development efficiency in the eastern region, while the central and western regions were still affected by the scale level and environmental regulation, reflecting the advantages of the eastern region in terms of economy and technology. In the future, strengthening agricultural scientific and technological innovation and deepening interprovincial cooperation can help further improve the level of green agricultural development. In addition, local governments should formulate more precise local agricultural support policies based on macro-level policies and local conditions.

Urban Agglomerations in China: Characteristics and Influencing Factors of Population Agglomeration

Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.

Distribution Characteristics and Influencing Factors of Geological Hazards in Tibet

Tibet is one of the areas with most serious geological hazards in China, and the distribution of disasters has obvious local charac teristics. Tibet can be classified as three parts through zoning the danger degree, the mountain canyon high danger zone of east and southeast Tibet, the plateau mountain lake basin and valley middle danger zone of south Tibet, and the Plateau Mountain lake basin low danger zone of south Tibet. This paper takes the debris flow, collapse, landslide as the key points to analyze the distribution characteristics of geological hazards, and analyze the factors which influence the distribution of geological hazards, such as terrain landform, formation lithology, geologic structure pattern, precipitation, earthquake, human activity and so on. finally, as a conclusion., in whole Tibet, the geological hazards are more in southeast than in northwest, more in mountainous area which in the edge of plateau and river valley than in the interior of plateau and lake basin. And most hazards distribute in the regions where human activity is stronger than in other regions, for example towns or strips along the highway.

Spatial-temporal Evolution Characteristics and Decoupling Analysis of Influencing Factors of China’s Aviation Carbon Emissions

The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.