Frontiers in Business, Economics and Management 
ISSN: 2766-824X | Vol. 16, No. 1, 2024 

 

272 

Characteristics of the Evolution of Resource and 
Environmental Carrying Capacity in Shaanxi Province 

Penghui Dai 

College of Xi'an International Studies University, Xi'an, China 

 

Abstract: This paper constructs a resource and environmental carrying capacity index system based on the DPSIR model, and 
adopts the entropy weight TOPSIS method to analyze the resource and environmental carrying capacity of Shaanxi Province in 

terms of time series and spatial distribution. The results show that from 2010 to 2020, the resource environmental carrying 

capacity of Shaanxi Province in general shows a fluctuating upward trend, and on the whole there is a small decrease in 2017 

compared with 2016 and 2020 compared with 2019, and an increase in 2019 compared with 2018; in terms of the characterization 

value of the resource environmental carrying capacity of each city, Yan'an City is in the first place for a long period of time, and 

it is stable in the top three with Yulin and Xi'an; each The resource environmental carrying capacity of each city shows a gradual 

convergence state, indicating that the difference between their carrying capacity gradually decreases. Finally, this paper makes 

corresponding suggestions for the improvement of the resource and environmental carrying capacity of Shaanxi Province from 

five aspects: economic development, low-carbon development, resource and environmental load reduction, population growth, 

and environmental infrastructure construction. 

Keywords: Resource and environmental carrying capacity, DPSIR model, Entropy weight TOPSIS, Shaanxi Province. 

 

1. Introduction 

Evaluation of resource and environmental carrying 

capacity can comprehensively reflect regional resource and 

environmental endowment and support capacity, and is also 

one of the core contents of territorial spatial planning [1]. 

With the acceleration of China's industrialization and 

urbanization, the contradictions between economy and 

society, resources and environment have gradually come to 

the fore, such as insufficient space for land resources, scarcity 

of water resources, and degradation of ecological service 

functions [2-3]. How to deal with the contradiction between 

resource and environmental support and economic and social 

development, and strengthen the healthy, coordinated and 

sustainable development of land space has gradually become 

a hotspot of concern for all walks of life [4-6]. In 2016, 13 

ministries and commissions, including the National 

Development and Reform Commission (NDRC) and the State 

Oceanic Administration (SOA), jointly issued the “Technical 

Method for Monitoring and Early Warning on Resource and 

Environmental Carrying Capacity (for Trial 

Implementation)”, and in 2019, the Ministry of Natural 

Resources (MNR) issued the “Circular on Comprehensively 

Carrying Out Territorial Notice on Comprehensively 

Carrying Out the Work of Spatial Planning [7], which fully 

illustrates the important theoretical significance and the 

necessity of practical exploration of scientific research on the 

evaluation of regional resource and environmental carrying 

capacity [8]. 

Current research on the evaluation of regional resource and 

environmental carrying capacity mainly focuses on the 

evaluation index system and the selection of research methods. 

Due to the different resource endowment and location 

conditions of different regions, there are differences in the 

definition of the connotation of resource and environmental 

carrying capacity, and there are also differences in the 

construction of the evaluation index system. In 1985, the 

United Nations defined the concept of resource and 

environmental carrying capacity, put forward a series of 

quantitative methods, and was gradually popularized [9-10]. 

The research of foreign scholars on resource and 

environmental carrying capacity is mainly based on the theory 

of sustainable development, such as: Graymore et al [11] 

based on the system theory model to empirically analyze the 

resource and environmental carrying capacity of Southeast 

Queensland, Australia; Brasher et al [12] used multi-stage 

sampling to estimate the energy carrying capacity of active 

and passive management of wetlands in the U.S. state of Ohio; 

Hansen et al [13] used biophysical predictor variables to infer 

species richness (SK) across North America, and concluded 

that species richness carrying capacity is highly correlated 

with biodiversity conservation; Brown et al [14] assessed the 

carrying capacity of tourism and local economic, social, 

ecological, and other resources and environments in Mexico 

and Papua New Guinea based on the regional environmental 

resource energy value method; Lorenz et al [15] calculated 

the carrying capacity of a sustainable boating tourism river 

section based on water quality protection and proposed 

management measures to integrate social, tourism and 

ecological aspects. Domestic research on the carrying 

capacity of resources and environment is relatively late, such 

as: Cheng Yuguang [16] used the state-space method to study 

the carrying capacity of resources and environment in Jiangxi 

Province; Miao Junxia et al. [3] constructed an evaluation 

index system of the carrying capacity of resources and 

environment of counties in the Loess Plateau at the levels of 

natural resources, ecological environment, and geologic 

environment; Song Chulin et al. Response” model to 

construct a resource and environmental carrying capacity 

evaluation index system for restricted development areas in 

Jilin Province; Yang Lina et al [5] constructed a resource and 

environmental carrying capacity evaluation index system for 

Chongqing Municipality from six aspects: economy, society, 

nature, water resources, land resources, and ecology; Zhao 

Dongsheng et al [17] constructed a resource and 

environmental carrying capacity evaluation index system for 



 

273 

Chongqing Municipality from the aspects of biological 

population, ecosystem environmental stress, natural resource 

supply, natural environment, socio-economic development, 

and social and economic development; Li Hongmei et al [18] 

constructed a resource and environmental carrying capacity 

evaluation index system along the Yangtze River (Yichang-

Jingzhou section) based on economy and society, resources, 

and the environment; Song Chulin et al [4] utilized a BP 

network model to study the spatial and temporal 

characteristics of the ecological carrying capacity of the urban 

agglomeration of the Rim of Chang-Zhu-Tan City; Song 

Zeming et al [19] used the DPSIR- TOPSIS model to study 

the carrying capacity of marine resources and environment 

and obstacle factors in 11 coastal provinces in China; Li Long 

et al [20] constructed an index system from three aspects of 

ecology, agriculture and construction to evaluate the spatio-

temporal characteristics of resource and environmental 

carrying capacity of Ningyuan County, Hunan Province; Liu 

Jinhua et al [21] constructed an evaluation of the resource and 

environmental carrying capacity of Jinan City from four 

aspects of resources, ecology and environment, and economic 

and social index system, and analyzed the agglomeration 

effect based on the village and town scale. In summary, the 

resource environment system is a composite system covering 

resources, environment, economic and social, scholars around 

the resources, environment, economic and social aspects of 

these three aspects of the selection of evaluation indicators to 

carry out more research [22-23]. Common evaluation 

methods used by scholars at home and abroad include energy 

value method [14, 24], TOPSIS [19], principal component 

analysis method [25], ecological footprint method [26], 

entropy weight method [27], fuzzy comprehensive evaluation 

[28], system dynamics [29], and damping coefficient method 

[30]. From the viewpoint of the study area, there are fewer 

studies on the evaluation of resource and environmental 

carrying capacity of ecologically fragile regions. 

Shaanxi Province is located in the arid and semi-arid region 

in the west of China, and is an important economic 

development zone and ecologically fragile area in the west of 

China, as well as an important ecological barrier construction 

in China and the core area for the implementation of the 

national “One Belt, One Road” initiative. In recent years, with 

the economic and social development, the problem of 

ecological and environmental damage and the contradiction 

of coordinated development of human-land relations have 

become prominent. In order to completely reverse the 

situation of resource and environmental constraints on the 

development of Shaanxi Province, and to promote the high-

quality development of the region, the study of the level of 

resource and environmental carrying capacity and its spatial 

and temporal evolution in Shaanxi Province is of strategic 

significance for realizing the coordinated development of the 

region in Shaanxi Province. Based on this, this paper 

constructs the index system of resource and environmental 

carrying capacity of Shaanxi Province based on the DPSIR 

model, and screens a targeted and relatively unified 

evaluation index system based on the panel data from 2010 to 

2020. The entropy weight method TOPSIS method is used for 

comprehensive evaluation, in order to reflect more 

objectively the level of resource and environmental carrying 

capacity of Shaanxi Province and its temporal and spatial 

evolution, with a view to providing theoretical references for 

improving the level of spatial planning and policy making in 

Shaanxi Province. 

2. General Situation and Data Source 
of The Research Area 

2.1. Overview of the Research Area 

Shaanxi Province is located in the northwest of China, in 

the middle reaches of the Yellow River, neighboring Shanxi 

and Henan in the east, Ningxia and Gansu in the west, 

Sichuan, Chongqing and Hubei in the south, and Inner 

Mongolia in the north, between the longitude of 105°29'-

111°15' east and the latitude of 31°42'-39°35' north, and the 

landforms of the province are from south to north, including 

the Qinba Mountain Range, the Guanzhong Plain and the 

northern Shaanxi plateau. As an important hub connecting 

east and central China, northwest and southwest China, 

Shaanxi Province is of great significance to the economic 

development of the western region of China. However, the 

region is a typical ecologically fragile and complex area 

because of its high and low elevation fluctuations, diverse 

ecological types, fragile ecological environment, and other 

conditions [31]. 

2.2. Data Sources 

The data for this study come from the 2011-2021 edition of 

the China Urban Statistical Yearbook, the Shaanxi Provincial 

Statistical Yearbook, and the Shaanxi Provincial Water 

Resources Bulletin 2010-2020, as well as data from the 

National Economic and Social Development Statistical 

Bulletin of the corresponding cities for the corresponding 

years. 

3. Indicator System and Evaluation 
Model 

3.1. Shaanxi Province Resource and 
Environmental Carrying Capacity 

Indicator System 

In order to make Shaanxi Province's resource and 

environmental carrying capacity evaluation index system 

more targeted, scientific and rigorous, reference to the index 

system of the General Office of the Ministry of Natural 

Resources on the issuance of the “Guidelines for Evaluation 

of Resource and Environmental Carrying Capacity and 

Suitability of Territorial Spatial Development (for Trial 

Implementation)”, the “Guidelines for Action on 

Development of Ecological Civilization Construction 

Standard System”, the “Outline of Eco-county and Eco-

municipality Construction Plan Preparation (for Trial 

Implementation)” and other official documents, prevailed, 

and based on the DPSIR conceptual model, a total of 18 

indicators were selected from 5 levels of driving force, 

pressure, state, impact and response (Table 1). The attributes 

of the indicators are categorized into positive and negative: 

the larger the value of the positive indicators, the better the 

evaluation results, and the smaller the value of the negative 

indicators, the better the evaluation results. 

 

 

 



 

274 

Table 1. Shaanxi Province Resource and Environmental Carrying Capacity Indicator System 

Level 1 

Indicators 

Level 2 

Indicators 
Level 3 Indicators 

Nature of 

Indicator 
Units 

Environmental 

carrying 

capacity of 

resources 

Driving 

GDP per capita + yuan 

Natural population growth rate + ‰ 

Urbanization level  + % 

Pressure 

Municipal sewage discharges - 10000 cubic meters 

population density - Persons/km2 

Sulfur dioxide emissions - Dons 

Industrial fume (dust) emissions - Dons 

State 

Building land area per capita - People/m2 

Greening coverage in built-up areas + % 

Urban green space per capita + m2 

Urban road space per capita - m2 

Impact 

Ambient air quality excellence rate + % 

Share of tertiary sector + % 

Hospital beds per 10,000 population + Sheets/10,000 persons 

Response 

Centralized treatment rate of urban sewage treatment plants + % 

Non-hazardous treatment rate of domestic waste + % 

Comprehensive utilization rate of industrial solid waste + % 

Afforestation area per capita + m2 

 

3.2. DPSIR Model 

The DPSIR model is evolved from the PSR model and is 

based on the evaluation of ecological, economic, social and 

other elements [32]. The concept of DPSIR was first proposed 

by the European Environment Agency (EEA) in 1998 to 

indicate the threat to the natural environment caused by 

human activities, and at the same time to reflect more 

accurately and comprehensively the relationship between 

human beings and the ecological environment that affects and 

interacts with each other [33]. In the DPSIR model, the 

Driving (D) is the support of economic activities in the 

regional society to the development of other regions; the 

Pressure (P) mainly refers to the consumption of regional 

production activities on the regional resources and ecological 

environment; the State (S) refers to the state of the resource 

and environmental carrying capacity presented under the dual 

role of the above driving force and pressure; the Impact (I) 

refers to the system state of the economic and social 

environment, the ecological brought about by the changes; the 

Response (R) refers to the positive and effective measures and 

countermeasures taken for the sustainable development of the 

region. 

3.3. TOPSIS model of Entropy Weight 

In this paper, the method of Chen Yu et al [31] for assessing 

the carrying capacity of resources and environment, this paper 

adopts the entropy weight TOPSIS method to evaluate the 

level of carrying capacity of resources and environment in 

Shaanxi Province. Different from the traditional TOPSIS 

evaluation method, the entropy weight TOPSIS method has 

the advantages of intuitive geometric significance, less 

information loss and flexible operation. The specific steps are 

as follows: 

(1) Entropy weight method to determine the weights of 

standardized indicators, the formula is: 

𝑒𝑗 = −𝑘 ∑ [(
𝑦𝑖𝑗

∑ 𝑦𝑖𝑗
𝑚
𝑖=1

) • ln (
𝑦𝑖𝑗

∑ 𝑦𝑖𝑗
𝑚
𝑖=1

)] ,𝑚𝑖=1  𝑘 = 1/ln𝑚  (1) 

𝑤𝑗 = (1 − 𝑒𝑗 )/ ∑ (1 − 𝑒𝑗 )
n
𝑗=1           (2) 

Where:𝑤𝑗  is the weight of the 𝑗th indicator; 𝑒𝑗  represents 

the information entropy of the 𝑗th indicator; 𝑚 is the number 
of evaluation years; 𝑘 is Boltzmann's constant. 

(2) Determine the positive and negative ideal solutions and 

compute the Euclidean distance: 

Positive ideal solution 𝑆𝑖
+ = √∑ (𝑚𝑗=1 𝑓𝑖𝑗 − 𝑓𝑗

+)2 (
𝑖=1,2,⋯,𝑛
𝑗=1,2,⋯,𝑚

) (3) 

Negative ideal solution 𝑆𝑖
− = √∑ (

𝑚
𝑗=1 𝑓𝑖𝑗 − 𝑓𝑗

−)2 (
𝑖=1,2,⋯,𝑛
𝑗=1,2,⋯,𝑚

) (4) 

(3) Calculate the C value of the closeness of each indicator 

to the ideal solution, Eq: 

𝐶𝑗 =
𝑆𝑖

−

𝑆𝑖
−+𝑆𝑖

+ (
𝑖 = 1,2, ⋯ , 𝑛
𝑗 = 1,2, ⋯ , 𝑚

)           (5) 

Where: 𝐶𝑗   takes the value range of [0, 1], the larger its 

value, the higher the value of urban ecological resilience of 

the research unit, and vice versa, the lower. 

4. Results & Analysis 

4.1. Calculation Result 

After assigning weights to the indicators through the 

entropy weight method, the TOPSIS model was applied to 

measure the carrying capacity of Shaanxi Province's 

resources and environment from 2010 to 2020 (Table 2). 

 

 

 

 

 

 

 



 

275 

Table 2. Shaanxi Province Resource Environmental Carrying Capacity Score Results (2010-2020) 

Cities 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Mean value 

Xi'an 0.463 0.466 0.469 0.452 0.462 0.467 0.465 0.477 0.463 0.480 0.460 0.466 

Tongchuan 0.420 0.389 0.399 0.408 0.379 0.393 0.426 0.397 0.409 0.453 0.435 0.410 

Baoji 0.329 0.346 0.349 0.349 0.341 0.344 0.375 0.360 0.372 0.389 0.379 0.358 

Xianyang 0.330 0.333 0.349 0.353 0.345 0.366 0.387 0.366 0.366 0.419 0.392 0.364 

Weinan 0.343 0.323 0.313 0.335 0.319 0.337 0.362 0.361 0.348 0.406 0.403 0.350 

Yan'an 0.597 0.620 0.610 0.681 0.684 0.669 0.653 0.622 0.643 0.637 0.549 0.633 

Hanzhong 0.369 0.370 0.372 0.376 0.373 0.371 0.390 0.342 0.367 0.401 0.370 0.373 

Yulin 0.588 0.601 0.623 0.623 0.617 0.552 0.536 0.536 0.550 0.550 0.552 0.575 

Ankang 0.396 0.389 0.414 0.424 0.430 0.424 0.461 0.476 0.464 0.461 0.439 0.434 

Shangluo 0.348 0.337 0.332 0.347 0.351 0.348 0.404 0.387 0.388 0.454 0.438 0.376 

4.2. Analysis of the Evolution of Resource and 
Environmental Carrying Capacity of 

Shaanxi Province 

From 2010 to 2020, the carrying capacity of Shaanxi 

Province's resources and environment generally shows a 

fluctuating upward trend, and overall, there is a small 

decrease in 2017 compared to 2016 and in 2020 compared to 

2019 (Fig. 1), which is mainly due to the decrease in the per 

capita afforestation area and the increase in the emission of 

industrial waste gas. The increase in 2019 compared to 2018 

is due to the overall stable growth of the economy and the 

increasing urbanization level is increasing, etc., resulting 

from this. From the perspective of the characterization value 

of the resource and environmental carrying capacity of each 

city, Yan'an City has been in the first place for a long time, 

and Yulin and Xi'an are steadily in the top three; in the early 

period, Baoji (2010), Weinan (2011-2016) and the late period, 

Hanzhong (2017, 2020) have the lowest level of resource and 

environmental carrying capacity, and Weinan is constantly 

growing, and has been out of the latter three levels in 2020; 

the resource and environmental carrying capacity of each city 

is gradually converging The resource and environmental 

carrying capacity of each city is gradually converging, 

indicating that the difference between their carrying 

capacities is gradually decreasing; from an overall 

perspective, the resource and environmental carrying capacity 

of Shaanxi Province is at the intermediate level and above, 

and shows a trend of decreasing in the areas with low levels 

of resource and environmental carrying capacity. 

The scores of resources environmental carrying capacity of 

some cities fluctuate greatly. Yan'an City and Yulin City have 

long been at the high-quality level of resource environmental 

carrying capacity, but generally show a fluctuating downward 

trend. Among them, Yan'an City rose significantly in 2013, 

mainly due to a significant decrease in industrial emissions 

and a significant increase in per capita afforestation area. 

Yulin City, on the other hand, experienced a significant 

decline in 2015, due to an increase in road area per capita and 

a decrease in afforestation area per capita as a result of 

urbanization. 

 

 

Figure 1. Evolution of Resource and Environmental Carrying Capacity of Cities in Shaanxi Province (2010-2020) 

5. Conclusions and Recommendations 

5.1. Concludes 

This paper takes Shaanxi Province as an example, based on 

the DPSIR model, adopts the entropy weight method TOPSIS 

method to measure the level of resource and environmental 

carrying capacity from 2010 to 2020, and produces a map of 

the evolution of resource and environmental carrying capacity 

of each city from 2010 to 2020, and obtains the following 

conclusions of the study: from 2010 to 2020, the resource and 

environmental carrying capacity of Shaanxi Province in 

general shows a fluctuating upward trend, and on the whole 

There is a small decrease in 2017 compared with 2016 and 

2020 compared with 2019, and an increase in 2019 compared 

with 2018; from the perspective of the characterization value 

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0.7

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

E
n
v
ir

o
n
m

e
n
ta

l 
c
a
rr

y
in

g
 c

a
p

a
c
it

y
 o

f 

re
so

u
rc

e
s

Xi'an Tongchuan Baoji Xianyang Weinan

Yan'an Hanzhong Yulin Ankang Shangluo



 

276 

of the resource and environmental carrying capacity of each 

city, Yan'an City has been in the first place for a long time, 

and it is steadily ranked in the top three with Yulin and Xi'an; 

the resource and environmental carrying capacity of each city 

is in a state of gradual convergence, which indicates that the 

difference between its carrying capacity is gradually 

decreasing. 

5.2. Suggestion 

During the period of 2010-2020, Shaanxi Province's 

resource and environmental carrying capacity has been 

improved as a whole, but it still belongs to a lower level, and 

the growth rate has gradually slowed down, indicating that 

Shaanxi Province's resource and environmental carrying 

capacity still has a large space for improvement, and that there 

is an urgent need to implement relevant measures to promote 

the steady improvement of the resource and environmental 

carrying capacity. The main recommendations are as follows: 

(1) Economic development is closely related to the 

enhancement of the carrying capacity of resources and the 

environment. Economic development drives the 

improvement of the level of environmental governance, thus 

achieving the stable and balanced development of the 

economic-social-ecological complex system. 

(2) Promote low-carbon development and balanced 

development. Strengthen the construction of regional 

integration in Shaanxi Province, strengthen the horizontal 

ecological compensation between regions, concentrate funds, 

technology and manpower to increase the protection of the 

environment, intensively and efficiently utilize resources, 

focus on promoting the balanced development of Shaanxi 

Province's regions, focus on energy conservation and 

emission reduction, reduce industrial pollution and actively 

adjust the industrial structure. Focus on industrial 

transformation and upgrading in each city, and increase the 

proportion of tertiary industry. 

(3) Focus on resource and environmental “load reduction”. 

Should be from the social, economic industry, the 

environment, three aspects of the “load reduction”, reduce or 

limit the pollution of the industry, focus on industrial 

upgrading and improve industrial wastewater, exhaust 

emission standards, improve the relevant laws and regulations, 

strict control of pollution emissions and governance. 

(4) Population and resources are long-term and influential 

factors. The natural population growth rate is the subsequent 

driving force for development. In the long run, policies should 

be introduced to stimulate population growth, and emphasis 

should be placed on the promotion of re-employment of the 

residents and the rationalization of unemployment relief and 

re-employment training. Cities should focus on increasing 

forest coverage, the area of nature reserves, etc., with a view 

to enhancing the service function of Shaanxi Province's 

ecosystems; ensuring a steady increase in the carrying 

capacity of Shaanxi Province's resources and environment. 

(5) Increase investment in environmental infrastructure 

construction. Strengthen ecological and environmental 

governance, build a multi-level, multi-principal grid-based 

coordinated governance organizational framework; improve 

the treatment capacity of manure and industrial and domestic 

garbage; increase the daily treatment capacity of various 

harmless treatment plants; and increase investment in 

environmental protection with a view to forming a synergistic 

socio-economic-ecosystem development situation. 

References 

[1] FENG Zhiming, YOU Zhen, YANG Yanzhao, et al. 
Comprehensive evaluation of resource and environmental 
carrying capacity of Tibet based on three-dimensional 
tetrahedral model [J]. Journal of Geography, 2021, 76(3):645-
662. 

[2] LIU Jiangyi, REN Wenzhen, SUN Yajing. Progress and 
outlook of research on resource and environmental carrying 
capacity evaluation in China [J]. Safety and Environmental 
Engineering, 2021, 28(6):230-236. 

[3] MIAO Junxia, ZHENG Xu, SUN Pingping, et al. Evaluation of 
resource and environmental carrying capacity and coupling 
coordination in loess plateau counties: an example from 
Yanchuan County, Shaanxi Province [J]. Journal of Northwest 
Normal University (Natural Science Edition), 2021, 57(2):94-
100. 

[4] SONG Chulin, Shuai Hong. Spatial and temporal pattern of 
ecological carrying capacity and early warning research in the 
urban agglomeration around ChangZhuTan [J]. Journal of 
Central South Forestry University of Science and Technology 
(Social Science Edition), 2020, 14(3):45-55. 

[5] YANG Lina, HE Xing, YAO Qiusheng, et al. Construction of 
resource and environmental carrying capacity evaluation index 
system and identification of dominant limiting factors in 
counties and districts [J]. Land Resources Science and 
Technology Management, 2020, 37(5):1-12. 

[6] HONG Yang, YE Wenhu. Measurement of sustainable 
environmental carrying capacity and its application [J]. China 
Population-Resources and Environment, 1998, 8(3):54-58. 

[7] SUN Lei, WANG Xiaohui, ZHANG Liu, et al. Analysis of 
ecological environmental protection in Anhui Province in the 
14th Five-Year Plan [J]. Environmental Protection, 2022, 
50(Z2):60-63. 

[8] HUANG Xianjin, ZHOU Yan. An overview of research 
methods on resource and environmental carrying capacity [J]. 
China Environmental Management, 2018, 10(6):36-42, 54. 

[9] UNESCO, FAO. Carrying capacity assessment with a pilot 
study of Kenya: a resource accounting methodology for 
sustainable development [R]. Rome: Food and Agriculture 
Organization of the United Nations, 1985: 115-121. 

[10] HASTOYUANDO E, BRONTOWIYONO W, HASANAH N. 
Environmental carrying capacity analysis based on water 
resources (case study of eastsurabaya area) [J]. Civil and 
Environmental Engineering, 2020, 16(2): 229-237. 
DOI:10.2478/cee-2020-0022. 

[11] GRAYMORE M L M, SIPE N G, RICKSON R E. Sustaining 
human carrying capacity: a tool for regional sustainability 
assessment [J]. Ecological Economics, 2010, 69(3): 459-468. 
DOI:10.1016/j.ecolecon.2009.08.016. 

[12] BRASHER M G, STECKEL J D, GATES R J. Energetic 
carrying capacity of actively and passively managed wetlands 
for migrating ducks in Ohio [J]. The Journal of Wildlife 
Management, 2007, 71(8): 2532-2541. DOI:10.2307/4496373. 

[13] HANSEN A J, PHILLIPS L B, FLATHER C H, et al. Carrying 
capacity for species richness as a context for conservation: a 
case study of North American breeding birds [J]. Global 
Ecology and Biogeography, 2011, 20(6): 817-831. 
DOI:10.1111/j.1466-8238.2011.00670.x. 

[14] BROWN M T, LGIATI S. Emergy measures of carrying 
capacity to evaluate economic investments [J]. Population and 
Environment, 2001, 22(5): 471-501. 

[15] LORENZ S, PUSCH M T. Estimating the recreational carrying 
capacity of a lowland river section [J]. Water Science and 



 

277 

Technology, 2012, 66(9): 2033-2039. 
DOI:10.2166/wst.2012.418. 

[16] Cheng Yuguang. Evaluation of regional resource and 
environmental carrying capacity of Jiangxi Province and its 
implications [D]. Nanchang: Nanchang University, 2007. 

[17] ZHAO Dongsheng, ZHANG Xuemei, DENG Siqi, et al. 
Discussion on the evaluation theory and method of regional 
resources and environment carrying capacity [J]. Journal of 
Applied Ecology, 2022, 33(3):591-602. 

[18] LI Hongmei, LIU Bo, YUAN Qin, et al. Evaluation index 
system and empirical research on resource and environmental 
carrying capacity along the Yangtze River (Yichang-Jingzhou 
section) [J]. Resource Environment and Engineering, 2020, 
34(S2):78-82, 117. 

[19] SONG Zeming, NING Ling. Evaluation of marine resources 
and environmental carrying capacity of China's coastal 
provinces based on DPSIR-TOPSIS model and study of 
obstacle factors [J]. Ecological Economy, 2020, 36(8):154-160, 
212. 

[20] LI Long, WU Dafang, LIU Yanyan, et al. Evaluation of 
resource and environmental carrying capacity of counties under 
multifunctional perspective:taking Ningyuan County of Hunan 
Province as an example [J]. Ecological Economy, 2020, 
36(8):146-153. 

[21] LIU Jinhua, LI Xiang, ZHENG Xinqi. Evaluation of resource 
and environmental carrying capacity and its spatial 
characterization under multi-scale perspective: taking Jinan 
City as an example [J]. Geographic Research and Development, 
2019, 38(4):115-121. 

[22] WANG Qin, LI Wei. Progress and outlook of research on 
evaluation of regional resource and environmental carrying 
capacity [J]. Journal of Ecological Environment, 2020, 
29(7):1487-1498. 

[23] WANG Ying, YU Yanghua, SUN Bo. Research on resource 
and environmental carrying capacity of Anshun City, Guizhou 
Province [J]. Environmental Science and Technology, 2019, 
42(S1):253-260. 

[24] SHEN Dan, ZHOU Dequan, FU Lian, et al. Research on the 
evaluation of resource and environmental carrying capacity 
based on PCA: Taking Zunyi City in Guizhou Province as an 
example [J]. Value Engineering, 2018, 37(34):191-193. 

[25] FANG K, HEIJUNGS R, DE SNOO G R. Theoretical 
exploration for the combination of the ecological, energy, 
carbon, and water footprints: Overview of a footprint family [J]. 
Ecological Indicators, 2014, 36(jan.): 508-518. 
DOI:10.1016/j.ecolind.2013.08.017. 

[26] Zeng Hao, Shen Jun, Jiang Jing. Study on the evaluation of 
resource and environmental carrying capacity and the evolution 
of spatial and temporal patterns in the Yangtze River Economic 
Belt [J]. South-to-North Water Diversion and Water Science 
and Technology, 2019, 17(3):89-96. 

[27] Jiang Renwei. Research on the carrying capacity of mining 
geological environment in West Panzhi region [D]. Kunming: 
Yunnan University,2019. 

[28] Lv Yizheng, Tian Jinping, Chen Lujun. Reflections on the 
green development of China's industrial parks based on human-
land relationship [J]. China Environmental Management, 2021, 
13(2):55-62. 

[29] XU Wenhao, LU Tao, LIU Jiang. Evaluation of system 
dynamics of county resources and environmental carrying 
capacity [J]. Environmental Science and Technology, 2020, 
43(8):192-199. 

[30] XIA Haibin, LIU Min. Simulation and prediction of IPCC 
composite scenarios (SSPs-RCPs) for the Hu Huanyong Line 
based on an integrated geographic perspective [J]. Geography 
Research, 2021, 40(10):2838-2855. 

[31] CHEN Yu, DING Ning, ZHAO Yunxia. Dynamic evaluation 
of resource and environmental carrying capacity of Northwest 
China based on entropy weight TOPSIS model [J]. Land 
Resources Science and Technology Management, 2022, 
39(03):1-13. 

[32] WANG Kueifeng, LI Na, YU Xuefeng, et al. Research on the 
evaluation index system of ecological environment carrying 
capacity based on P-S-R conceptual model-Taking Shandong 
Peninsula as an example [J]. Journal of Environmental Science, 
2014, 34(8):2133-2139. 

[33] TANG Jianxiong, ZENG Fang. Spatial and temporal evolution 
of the strength of ecological environment response to 
urbanization in the Yangtze River Economic Zone [J]. Journal 
of Central South Forestry University of Science and 
Technology (Social Science Edition) 2021, 15(4):43-52.