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Article

Research on Targeted Poverty Alleviation and Eco-Compensation Model in Impoverished Mountainous Areas: A Case Study of Longnan City, China

by
Yuan Qi
1,*,
Xiaoyu Song
2,
Xihong Lian
1,3,
Hongwei Wang
1,
Xiaofang Ma
1 and
Jinlong Zhang
1
1
Key Laboratory of Remote Sensing of Gansu Province, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2
Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(16), 6872; https://doi.org/10.3390/su16166872
Submission received: 18 June 2024 / Revised: 21 July 2024 / Accepted: 2 August 2024 / Published: 10 August 2024
Browse Figures
Figure 1
<p>Topographic map of Longnan City.</p> "> Figure 2
<p>Sustainable Livelihoods Framework.</p> "> Figure 3
<p>Sustainable Livelihoods Evaluation index system.</p> "> Figure 4
<p>Accounting principle of key industries exit losses.</p> "> Figure 5
<p>Severely impoverished areas (<b>a</b>), poverty population (<b>b</b>), and poverty incidence in Longnan City (<b>c</b>).</p> "> Figure 6
<p>Annual mean precipitation and temperature in severely impoverished areas.</p> "> Figure 7
<p>Slope, road network, and drainage density in severely impoverished areas.</p> "> Figure 8
<p>Poverty types and targeted poverty alleviation measures in Longnan City.</p> "> Figure 9
<p>Spatial distribution of ecosystem services in Longnan City. (<b>a</b>) Water yield, (<b>b</b>) nitrogen load, (<b>c</b>) phosphorus load, (<b>d</b>) soil conservation, (<b>e</b>) carbon storage, (<b>f</b>) biodiversity conservation importance.</p> "> Figure 10
<p>Eco-compensation model of Longnan City.</p> ">
Review Reports Versions Notes

Abstract

:
Poverty remains a significant global challenge, particularly in severely impoverished areas where balancing eco-civilization and economic growth is crucial. This study aims to analyze livelihood assets, determine appropriate strategies, and establish an eco-compensation model based on ecological vulnerability in Longnan City. We developed a livelihood evaluation index system using the Sustainable Livelihoods Framework and entropy weight method to assess the vulnerable portfolio of livelihood assets. We examined poverty causes and proposed targeted alleviation measures. Additionally, we created an “Eco-Compensation Model of Longnan City” incorporating the Sloping Land Conversion Program, key industries exit compensation, and cross-provincial water compensation based on incentive and punitive mechanisms. Our findings reveal that severely impoverished areas in Longnan City are primarily in the central, southern, and northwestern regions. Poverty is driven by unfavorable natural conditions, frequent natural disasters, regional economic marginalization, inadequate infrastructure, and a limited agricultural structure. The evaluation shows that natural capital in the five areas is lower than the national average level. We propose targeted measures for different vulnerable livelihood portfolios. The eco-compensation model provides a scientifically calculated compensation standard, offering a crucial funding source for implementing targeted poverty alleviation strategies.

1. Introduction

Poverty is a critical challenge in the world, and in the “Sustainable Development Goals (SDGs) 2030”, the United Nations set its primary goal as eliminating all forms of poverty around the world. The international community has been committing to eliminating poverty [1,2,3]. The understanding of poverty among the people has gradually evolved to a multi-dimensional perspective from the purely monetary perspective [4]. In China, a lot of work has been completed for achieving the goal of poverty alleviation [5,6,7]. Since the implementation of the targeted poverty alleviation policy, China has made remarkable achievements in poverty alleviation and has built a moderately prosperous society in 2020. However, many marginal areas in China are still in poverty, which are mainly concentrated in rural areas, especially mountainous areas [8]. As limited by harsh natural environment, insufficient natural resources, and backward transportation facilities, the mountainous areas are generally severely impoverished and priority support is required. At the same time, such areas are also vulnerable ecological environments, and under the extensive economic development model and interference of unreasonable human activities, they urgently require the construction of eco-civilization. Therefore, in order to resolve the contradiction between severe poverty and vulnerable ecological environments, relieve the ecological construction and poverty alleviation, and realize sustainable development in impoverished mountainous areas, it is of great significance to clarify the spatial patterns of severely impoverished areas and their causes, analyze livelihood assets, determine the targeted livelihood strategy, form an eco-compensation model, and implement the strategy of targeted poverty alleviation.
Livelihood assets refer to the resource base of a community and different types of households [9], and livelihood strategy refers to the means for dealing with external interference and maintaining livelihood [10]. The abundance of livelihood assets can directly reflect the extent and dimension of regional poverty, and an important means to understand the causes and degree of poverty is to evaluate the livelihood assets of an individual region. In view of the spatial difference of residence, the natural endowment of livelihood assets may determine the selection of livelihood strategy [11]. In the case of stable external conditions, different livelihood assets will have different impacts on the livelihood strategy. In a study, the relationship between the livelihood strategy and portfolio of livelihood assets was analyzed, and the integration of agriculture and animal husbandry, stable non-agricultural activities, and flexible individual livelihoods were determined as important livelihood strategies [12]. Based on sustainable livelihood, the current study on livelihood strategies mainly focuses on three aspects, namely the classification, influencing factors, and selection of livelihood strategies [13,14,15]. Previous research has analyzed the relationship between various factors and the economy using different models, such as the multifactor model [16], stepwise regression [17], and panel data model [18]. It could be concluded that few studies have implemented livelihood strategies in severely impoverished areas and highlighted the particularity of impoverished areas while establishing the livelihood indicator system. In addition, many studies on livelihood strategies were only conducted from the perspective of social science, without case analysis from the perspectives of ecological vulnerability and ecological theory; in addition, few studies performed in-depth analysis on the guarantee for implementation of targeted livelihood strategies.
Eco-compensation, as a market mechanism based on economic means, is designed to coordinate the interests of stakeholders, and realize ecological protection and economic development [19], so as to provide a new vision for ecological construction and the implementation of livelihood strategies. As a mechanism motivating local participants, eco-compensation has also attracted widespread attention from the public [20,21]. The core content of eco-compensation is to determine the compensation standard; therefore, in many studies, the eco-compensation standard was discussed in detail [22,23,24]. Regional eco-compensation must emphasize the construction of mechanisms or models, and a single regional eco-compensation policy or measure is not equivalent to a mechanism, for an eco-compensation mechanism must be long-term. For establishing an eco-compensation model, the type, mode, responsibilities, funding sources, and supervision system of compensation must be clarified, and then a compensation standard must be determined on this basis. The current eco-compensation mechanisms mainly include a punitive mechanism and an incentive mechanism, where the incentive mechanism can mobilize the enthusiasm of participants to a large extent, and the punitive mechanism can provide a continuous economic foundation for participants to protect the ecosystem. A better compensation mode is generally a complementary mode of the two above-mentioned mechanisms. In China, the eco-compensation system, initiated in early 1980s, has successively experienced the initial stage, preliminary exploration stage, and rapid development stage. The eco-compensation practice has been carried out at both the national and local levels, and its fiscal compensation and taxation mechanisms are mainly classified in three types, namely the vertical fiscal transfer payment, horizontal fiscal transfer payment, and market-oriented mode. Vertical compensation, as the main tool of the central government, mainly focuses on ecological construction, such as SLCP, with the distinctive feature of serving the nation; for, in a developing country, the participation of government can guarantee the smooth operation of eco-compensation projects. Horizontal compensation, i.e., the transfer of financial resources between local governments, is generally promoted on a pilot basis in view of the weak payment capacity. Enterprises have paid less for the ecosystem. In general, a model of vertical compensation supplemented by horizontal compensation and limited marketization has been established in China. Therefore, in order to alleviate the intertwined contradiction between severe poverty and vulnerable ecological environments at the local level, it is necessary to attract more market stakeholders based on the current eco-compensation model, thus internalizing the environmental externality [25].
In Longnan City, which is located in the Qinling–Daba Mountainous Area in Central China, there are concentrated and contiguous severely impoverished areas, with a large population suffering from severe poverty. As affected by natural conditions and regional economic marginalization, there is conditional poverty and quality poverty in Longnan City. In general, the relative poverty is intertwined with regional absolute poverty, making Longnan typical and specific in the research on measures for targeted poverty alleviation in impoverished areas. Its diverse livelihood assets and vulnerability provide a rich context for our research. The purpose of this study is to analyze livelihood assets, identify effective livelihood strategies, and establish an eco-compensation model tailored to the ecological vulnerability of severely impoverished areas. In this paper, the livelihood evaluation index system in severely impoverished areas of Longnan City was established based on the Sustainable Livelihoods Framework; the causes of poverty in severely impoverished areas were analyzed according to the portfolio of weak livelihood assets in each area; the measures for targeted poverty alleviation were also proposed. In view of the particularity of severely impoverished areas in Longnan, and in combination with the vulnerable ecological environment, the eco-compensation model of Longnan City was established from the aspects of SLCP, key industries exit compensation, and cross-provincial water compensation, which can guarantee the implementation of the targeted poverty alleviation strategy. In this paper, the livelihood strategy was innovatively implemented in the case study of severely impoverished areas based on the perspective of targeted poverty alleviation; meanwhile, the eco-compensation model was involved. The research results obtained the following: (1) Spatial distribution and causes of severely impoverished areas in Longnan City (where are the poverty areas?); (2) livelihood assets and targeted livelihood strategies for severely impoverished areas (what is the degree of poverty, and how to resolve the poverty?); (3) eco-compensation model suitable for severely impoverished areas in Longnan (how to guarantee the implementation of the targeted poverty alleviation strategy, and solve the problems such as the sources of funds?). This research not only bolsters the theoretical framework for sustainable development in Longnan City but also serves as a valuable reference for similar studies on regional livelihood strategies and eco-compensation models. The multifaceted approach adopted here, informed by insights from Longnan, has the potential to shape global poverty alleviation strategies, thereby contributing significantly to sustainable development efforts.

2. Materials and Methods

2.1. Study Region

Longnan City is located in the southeast of Gansu Province, China, i.e., the intersection of the Qinling–Daba Mountainous Area, Qinghai–Tibet Plateau, and Loess Plateau (104°01′19″–106°35′20″ E, 32°35′45″–34°32′00″ N). It is about 237 km long from east to west, and 230.5 km wide from north to south, with an area of 2.79 million hm2. Longnan is the only region in Gansu Province that belongs to the Yangtze River System with subtropical climate; in addition, it is also an important water conservation area and water and soil conservation area in the upper reaches of the Yangtze River, as well as an important ecological barrier on the eastern edge of the Qinghai–Tibet Plateau. As a key area of biodiversity conservation in China, it has an important ecological status. In terms of administrative division, Longnan City consists of Wudu District, Dangchang County, Wenxian County, Kangxian County, Chengxian County, Huixian County, Lixian County, Xihe County, and Liangdang County. The terrain is high in the northwest and low in the southeast, with West Qinling and Minshan extending into the territory from the east and west, respectively, thus forming a complex terrain covering high mountains, deep valleys, hills, and basins. Longnan City belongs to the East Asian monsoon climate zone. Due to the special geographical location and orientation of mountains, the climate is complex and diverse, with obvious horizontal and vertical zoning. The minimum perennial mean temperature of all counties (districts) in Longnan City is 3.4–10.2 °C, with the highest temperature of 16.3–21.7 °C, and an average temperature of 9.1–15.1 °C. The perennial mean temperature is high in the northwest and low in the southeast, and the perennial mean precipitation is 440.4–750.8 mm. It is also located on the edge of the rainstorm belt, and there are heavy rains in a concentrated period of time, which would result in intense soil erosion (Figure 1).

2.2. Data Description

2.2.1. Survey Data of Livelihood Assets

The data sources mainly include the existing statistical data (China Rural Statistical Yearbook and Longnan City Statistical Yearbook), household questionnaires, archived databases for impoverished areas, and existing literature results and data. With household questionnaires, the materials, data, and information can be directly obtained from the farmers through a field survey, which covered five livelihood assets and livelihood strategies. An amount of 1–3 administrative villages were randomly selected in each area, and 25 questionnaires were distributed in each area; a total of 625 questionnaires were distributed.

2.2.2. Evaluation Data of Ecological Assets

The meteorological data were collected from the Daily Data Set of China Meteorological Data Service Center, using the factors of temperature and precipitation. The soil attribute data were collected from Harmonized World Soil Database version 1.2 (HWSD). The data of Longnan City were 1:1,000,000 soil data provided by Nanjing Soil Research Institute in the Second National Land Survey. DEM data were collected from Shuttle Radar Topography Mission (SRTM) digital elevation data, with the spatial resolution of 30 m. The data also included the data from related departments and literature data.

2.2.3. Environmental Economic Value of Key Industries and Cross-Provincial Water Data

The key industries exit compensation was determined through calculating the mineral resources, hydropower resources, and fishery resources in Longnan City. In terms of mineral resources, four mineral enterprises in Wudu District, Chengxian County, and Wenxian County were surveyed by questionnaires and interviews, which involved the contents such as reserves, years of exploitation, investment in fixed assets, and compensation of employees. In terms of hydropower resources, the nine hydropower enterprises were surveyed by questionnaires, and the relevant input and output data were obtained. In terms of fishery resources, the aquaculture households, fishery farms, and hatchling bases in key river basins throughout the city were surveyed.
The data of cross-provincial water quality were collected from the monitoring data, with the main monitoring indexes of chemical oxygen demand (COD), ammonia nitrogen, total phosphorus and total nitrogen, and so on.

2.3. Methods

2.3.1. Sustainable Livelihoods Framework (SLF)

Livelihood assets may directly reflect the extent and dimension of regional poverty, so the evaluation of livelihood assets is an important way to understand the causes and extent of regional poverty. The Sustainable Livelihoods Framework can consider the inherent complexity of poverty and improve people’s understanding of livelihoods of the poor through evaluating influencing factors, constraints, and opportunities of livelihood strategies [26]. Therefore, in this paper, the Sustainable Livelihoods Framework was used to analyze the environmental vulnerability and distribution of the five dimensions of livelihood assets in severely impoverished areas of Longnan City (Figure 2). On the basis of analyzing ecological environment vulnerability of each area, the targeted poverty alleviation measures and Longnan City eco-compensation model were proposed in combination with the conditions of livelihood assets.

2.3.2. Longnan City Sustainable Livelihoods Evaluation Index System

Firstly, in alignment with previous studies [27], we categorized livelihood assets into five distinct types: natural capital, physical capital, financial capital, human capital, and social capital. Secondly, key indexes under each dimension were screened according to geographic identification and type division of multi-dimensional poverty in rural China, and 14 indexes were determined (Figure 3). Thirdly, the indexes were standardized with the mean level as the comparison object. Fourthly, the weight was determined, and, based on which, the composite value of the five major livelihood capitals was calculated.
In order to measure the human capital, we evaluated the quantity and quality based on the evaluation indexes of labor force ratio (H1) and education level (H2). As for financial capital, we evaluated the flow and stock based on the evaluation indexes of rural disposable income (F1) and net property income (F2). Natural capital refers to the stock of natural resources and environmental services for the people [28]; therefore, we evaluated land production potential and ecosystem services (the criterion layers) based on the evaluation indexes of productive areas for different creatures (cultivated land, forest land, grassland, and water bodies) (N1) and ecosystem service value (water yield value, water quality purification value, soil conservation service, carbon sequestration, and oxygen release) (N2). As for social capital, we performed the evaluation based on the urbanization level (S1) representing the location of social relations, and the ratio of rural to urban disposable income (S2) and transfer income (S3) representing the social support level. As for physical capital, we evaluated the infrastructure, residence, durable goods, and large animals (the criterion layers) based on the indexes of road density (P1), per capita residential area (P2), proportion of steel-concrete structure (P3), number of durable goods per hundred households (P4), and number of large animals per capita (P5).

2.3.3. Determination of Index Weight Based on Entropy Weight Method

The entropy weight method is a mathematical method for calculating comprehensive indexes based on the amount of information in various indexes [29]. Compared to traditional weight allocation methods, the entropy weight method uses an objective, data-driven process to determine the weights of indicators. This approach reduces potential biases and enhances the robustness of the results. It can be applied to different regions without requiring prior assumptions about the distribution of indicators, making it particularly suitable for complex and multifaceted issues such as poverty and ecological vulnerability. Therefore, in this paper, the entropy weight method was used to determine the weights of the indexes at the same level. Firstly, the index was standardized, to obtain a standardized matrix. The standardized equation is as follows:
x i j = x i j − m i n ( x j )   m a x ( x j ) − m i n ( x j )
where x i j is index j in region   i , m i n ( x j ) is the minimum value of j , and   m a x ( x j ) is the maximum value of   j .
Then, the information entropy of each index was calculated. The equation for calculating the entropy   H i   of index i is as follows:
H i = − k ∑ j = 1 n f i j l n f i j
where f i j = x i j ∑ j = 1 n x i j and k = 1 l n   n .
After determining the entropy, the entropy weight of index i can be calculated as follows:
ω i = 1 − H i m − ∑ i = 1 m H i
where ω i is the entropy weight, m is the number of evaluation indexes, and H i is the index entropy. The smaller the entropy is, the larger the weight will be, indicating the greater amount of information. Finally, the composite values of the five major livelihood assets were calculated through weighting and were used to reflect the level of livelihood assets.

2.3.4. Evaluation of Ecological Assets

Comprehensive evaluation of ecological assets, the basis of eco-compensation, generally takes the new ecosystem service value (ESV) quantified by currency as the theoretical upper limit of the eco-compensation standard. From the perspective of the supply of ecosystem services, the new service value of eco-compensation through SLCP is the difference between the integrated value of ecosystem services after SLCP and that prior to SLCP, namely the new integrated value of ecosystem services after SLCP, which can be calculated using the following equation:
Δ E = E f − E p
E f = E f w + E f q + E f s + E f c
E p = E p w + E p q + E p s + E p c
where Δ E is the new integrated value of ecosystem services after SLCP; E f and E p refer to the integrated values of ecosystem services of forest land and cultivated land; E f w , E f q , E f s , and E f c respectively refer to water yield value, water purification value, soil conservation value, and carbon sequestration and oxygen release value of forest land; E p w , E p q , E p s , and E p c respectively refer to water yield value, water purification value, soil conservation value, and carbon sequestration and oxygen release value of cultivated land.
  • Water yield value
Water yield can be calculated based on the water balance equation (the difference between precipitation and actual evapotranspiration) using the following equation:
Y x = 1 − A E T x P x × P x
where Y x is the water yield of pixel   x , A E T x is the annual actual evapotranspiration for pixel x , and P x is the annual precipitation on pixel x . A E T x P x   is an approximation of the Budyko curve developed by Zhang et al. [30].
Considering the surplus of water yield value, it is hard to spontaneously form exclusive benefits in the market. In this paper, the shadow engineering approach was used for calculation, i.e., supposing that there was a water conservancy project with the same water storage function and vegetation water conservation quality, the value of water conservation can be calculated by the water price adjusted by the water conservancy project using the following equation:
E w = Y × C
where E w is the water yield value; Y is the amount of water yield; C is the cost of unit capacity of the reservoir.
2.
Water purification value
The water purification function can be evaluated through estimating the amount of nutrients removed by vegetation and soil from runoff and simulating the nutrient retention and output of different land types based on water yield, LUCC, and the nutrient output coefficient [31]. The greater the output of nitrogen and phosphorus is, the poorer the regional water purification function would be.
The nitrogen or phosphorus export can be calculated using the following equations:
A L V x = H S S x ⋅ p o l x
H S S x = λ x λ ¯ w
λ x = log ∑ U Y U
where A L V x is the adjusted loading value on pixel x, H S S x is the hydrologic sensitivity score on pixel x, p o l x is the coefficient on pixel x, λ x is the runoff index on pixel x, λ ¯ w is the average runoff index, and ∑ U Y U is the water yield.
The water purification value can be calculated based on the cost of industrial removal of total nitrogen and total phosphorus using the following equation:
V = Δ Q N × α N + Δ Q P × α P
where Δ Q N and Δ Q P respectively refer to the purified total nitrogen and total phosphorus;   α N and α P refer to the purification values of total nitrogen and total phosphorus.
3.
Soil conservation value
Soil conservation value covers the soil fertility maintenance value and sedimentation reduction value, where the soil fertility maintenance value E a   contains nutrient value E 1 and organic matter value E 2 . The economic value of maintaining soil nutrients can be calculated based on the price of chemical fertilizers, soil conservation, and soil nutrient content; and the economic value of maintaining organic matters in soil can be estimated by the market price of firewood after being converted into an equivalent amount of firewood using the following equations:
E a = E 1 + E 2
E 1 = Q ⋅ ∑ m i ⋅ n i ⋅ p i
E 2 = Q ⋅ D i ⋅ P S ⋅ S
where Q is soil retention, m i is average nutrient content in the soil, n i is the coefficient of converting alkali-hydrolyzale nitrogen into urea, rapidly available phosphorus into superphosphate, and rapidly available potassium into potassium chloride, and   p i   is the average market price of urea, superphosphate, and potassium chloride. D i is the average content of organic carbon in each soil type in the study area, P S is the opportunity cost price of firewood, and S is the coefficient of converting firewood into soil organic matter.
The economic value of sedimentation reduction can be calculated by the shadow engineering method with the cost for excavating and transporting the unit volume of earthwork (replaced with construction cost of the reservoir) using the following equation:
E b = 0.24 × Q × C / ρ
where ρ is the soil bulk density.
4.
Carbon sequestration and oxygen release value
The carbon storage can be estimated based on the four major carbon pools of above-ground biomass, underground biomass, soil biomass, and dead organism biomass [32].
C = C a b o v e + C b e l o w + C d e a d + C s o i l
where C is carbon storage, C a b o v e is above-ground carbon storage, C b e l o w is underground carbon storage, C d e a d is carbon storage of dead organism biomass, and C s o i l is soil carbon storage.
The unit price of carbon sequestration is the price determined with the relevant economic theories and the United Nations SEEA while referring to the carbon trading market price in China, and the carbon sequestration value can be calculated using the following equation:
U = G × C
where U is the terrestrial carbon sequestration value, C is the unit carbon sequestration price, and G is the terrestrial carbon sequestration amount.

2.3.5. Accounting Principle of Key Industries Exit Losses

Key industries exit compensation refers to the compensation for the losses of the original legal operating enterprises due to being shut down for ecological protection. The subjects of losses include the governments, businesses, and individuals, and specific losses include the losses of personal livelihood transformation, net operating profit due to shutdown, depreciation of assets, production tax and other losses, and environmental asset value, whose accounting principle is shown in Figure 4. The accounting process can be determined based on the System of National Accounts (SNA) and System of Economic-Environmental Accounts (SEEA) [33].

3. Results

3.1. Spatial Distribution of Severely Impoverished Areas in Longnan City and Causes of Poverty

3.1.1. Spatial Distribution of Severely Impoverished Areas

The spatial distribution of severely impoverished areas is the spatial description that can clarify the poverty distribution features, and also a basis for revealing the dimension and extent of poverty from the perspective of livelihood assets. In terms of spatial distribution in Longnan City, the severely impoverished areas include Maying (MY), Luotang (LT), Longxing (LX), and Tibetan Settlement (ZZ) in Wudu District; Lichuan (LC), Chela (CL), Xinzhai (XZ), Nanyang (NY), and Xinchengzi Tibetan Settlement (XCZ) in Dangchang County; Taoping (TP), Baihe (BH), Big Beach (DT), and Yacheng (YC) in Lixian County; Daqiao (DQ), Luoyu (LY), and Sun Jing (SJ) in Xihe County; Bikou (BK), Linjiang (LJ), and Tielou Tibetan Settlement (TL) in Wenxian County; Yangba (YB), Dianzi (DZ), and Douping (DP) in Kangxian County; Zhanerxiang (ZEX) in Liangdang County; Mayan (MY) and Yuguan (YG) in Huixian County; and Jifeng (JF) and Erlang (EL) in Chengxian County. It can be seen that the severely impoverished areas are mainly concentrated in the central, southern, and northwestern regions of Longnan City (Figure 5a), and the 27 severely impoverished areas cover 121 towns and 1459 administrative villages, with the proportion of poverty households of 58%. From the perspective of distribution of poverty population, the areas with more than 20,000 poor people are mainly concentrated in Wudu District, Lixian County, and Xihe County (Figure 5b). According to the survey results of the basic situation of severely impoverished areas in Longnan City, the poverty rates of Wudu District, Dangchang County, Lixian County, Xihe County, Wenxian County, Kangxian County, Liangdang County, Huixian County, and Chengxian County poverty were 56.10%, 53.25%, 65.00%, 57.20%, 59.95%, 57.20%, 50.00%, 55.10%, and 52.23%, respectively (Figure 5c).

3.1.2. Analysis on Causes of Poverty in Severely Impoverished Areas

The annual mean temperature in Longnan City is 10.1 °C, with the highest temperature in July (20.4 °C), while the temperature in July in impoverished areas is 15.6–23.5 °C, and the temperature in July in over 50% of the impoverished areas is higher than the mean temperature in July in Longnan City. The annual mean precipitation is 669.9 mm, concentrating in the period from July to September, with the greatest precipitation in July. In the 25 impoverished areas in Longnan City, the precipitation from July to September exceeds half of the annual precipitation (Figure 6). The unfavorable natural and ecological conditions can directly produce the following short-term and long-term effects: On the one hand, in the short term, the frequent disasters may lead to reduction and even crop failure in agricultural production, which would make the income of farmers change greatly, thus causing poverty due to disasters. On the other hand, unfavorable natural and ecological conditions would result in unbalanced distribution of water and soil resources, barren land, and insufficient underground water; in addition, as compared with regions with better water and soil resource allocation conditions, there would be higher costs for the farmers to improve the soil, and for constructing water conservancy facilities.
The topography in Longnan, featured in slopes, is dominated by steep slopes of 15–35°, which account for 50–76% of the area of severely impoverished areas (Figure 7a), and which make it hard to have contact with the outside world and cause great difficulties in agricultural development. In severely impoverished areas, there are complex geological structures, various types of landforms, rugged terrain, weak and broken rocks, and fragile ecological environments; due to the highly concentrated precipitation, there are also various secondary disasters such as collapses, landslides, mudslides, unstable slopes, and ground subsidence; in addition to frequent earthquakes and intense human engineering activities, Longnan has been identified as one of the regions with the most severe geological disasters in China. The frequent natural disasters and poorly constructed agricultural infrastructure affect a large area of farmlands, hinder the increase in household income, and cause a large amount of poverty and poverty-returning people.
The impoverished areas are backward in traffic and have a small density of road network (Figure 7b). The density of road network in the severely impoverished areas such as TP is only 0.28 km/km2. In impoverished areas, the villages can mainly make contact with the outside through gravel roads and earth roads, which are poor in conditions and low in traffic rate; therefore, it is hard to transport the agricultural products out and obtain external market resources, affecting the household income. In particular, there is still no sufficient investment in rural infrastructure construction, the roads and safe drinking water facilities can only cover the village committees, and roads in some villages and towns are severely damaged. The small density of the river network and backward water conservancy facilities further aggravate the difficulties in agricultural production and are important causes of poverty in impoverished areas.
As restricted by topography and geomorphology, the proportion of cultivated land in Longnan City is low, with limited cultivated land resources. The proportion of cultivated land in five areas, including ZEX and YG, is less than 10% and mostly in areas with a slope of more than 15°. In some severely impoverished areas, the area of cultivated land on a slope of above 25° almost accounts for half of the entire cultivated land, which accounts for 62% in BK. The small per capita cultivated land area, steep slope, barren land, poor irrigation conditions, and low land output rate and labor productivity result in the low level of income. The single structure of agricultural planting results in fierce market competition and lowers the prices of agricultural products. Furthermore, the simplification of the planting structure would further reduce soil nutrients, worsen the agricultural production conditions, and thus increase the production cost and lower the agricultural production benefits.

3.2. Current Status of Livelihood Assets and Targeted Poverty Alleviation Strategy in Severely Impoverished Areas

3.2.1. Analysis of Current Status of Livelihood Assets in Severely Impoverished Areas

The livelihood assets can directly reflect the extent and dimension of poverty in a certain region, and the analysis of livelihood assets can provide a basis for developing the targeted poverty alleviation strategy. The value of human capital in impoverished areas of Longnan City is 0.64–1.02, and through cluster analysis, human capital can be divided into three categories: scarce, relatively scarce, and not scarce. The category “scarce” covers TP, the category “relatively scarce” covers 16 areas, and the category “not scarce” covers 10 areas. Financial capital can also be divided into three categories: quite scarce, scarce, and relatively scarce. It is shown that the standardized value of financial capital is 0.13–0.86, which is lower than the national average level, and the entire region is scarce in financial capital. The standardized value of natural capital covers a large range (0.34–14.75), and natural capital can be divided into five categories: quite scarce, not scarce, relatively abundant, abundant, and quite abundant. The standardized value of natural capital is lower than the national per capita level in only five of the 27 areas. The standardized value of physical capital is 0.52–1.04, and that of social capital is 0.35–0.63; through cluster analysis, physical capital and social capital can be divided into three categories: scarce, relatively scarce, and not scarce. Most of the physical capital is lower than the national average level, and the social capital is entirely lower than the national average level; the entire region is scarce in social capital (Table 1).

3.2.2. Targeted Poverty Alleviation Strategy in Severely Impoverished Areas

The ecological environment vulnerability will directly affect the livelihood development model, as well as the targeted poverty alleviation policy and eco-compensation model. Based on regional slope variation, the ecological environment vulnerability can be divided into two categories: vulnerable and not vulnerable. Compared with other livelihood assets, natural capital is more closely related to local natural conditions, geographical environment, and other natural factors; therefore, it is a necessary resource for farmers to engage in agricultural activities, and also a livelihood asset that is hard to be manually changed. The endowment of natural capital determines the risks and uncertainties for the people. In view of the relatively abundant forest and wetland resources in Longnan City, the per capita natural capital is lower than the national average level in five areas only. Therefore, natural capital can be taken as the second factor for the classification of poverty in Longnan City. Natural capital under different vulnerabilities will affect the selection of livelihood strategy, eco-compensation, and targeted poverty alleviation measures.
In regions with a vulnerable ecological environment, there will be severe water and soil loss; the protection in such regions should focus on protecting the environment, implementing the eco-compensation policy, and enhancing compensation, such as implementing the SLCP. On the one hand, in regions with scarce natural capital, including those with scarce human physical capital (HNPSF) and physical capital (NPSF), such as SJ, LY, and LC, which suffered from harsh natural conditions, the ecological restoration program should be implemented, such as the forest vegetation restoration program; the interference of human activities on the natural environment should be reduced, and labor export should be timely increased, to reduce the existing poverty. On the other hand, for areas abundant in natural capital, including those with scarce physical capital (PSF), human physical capital (HNPSF), and human capital (HSF), such as MY, LX, NY, TP, YC, EL, JF, and BH, natural capital should be developed under the premise of protecting the ecological environment; for example, the under-forest economic program and featured agriculture program could be carried out. In regions with scarce human capital, the intellectual support program could be performed to provide education and technical training, and in regions with scarce physical capital, the overall promotion program could be implemented to enhance infrastructure construction.
In regions not vulnerable in ecological environment, different measures for targeted poverty alleviation can be taken based on the difference in natural capital. On the one hand, in regions with scarce natural capital, including those with scarce human capital (HNSF) and natural capital (NSF), such as ZZ and DQ, it would be hard to convert natural capital to financial capital or physical capital. Therefore, labor export or relocation could be implemented to reduce the stress on the natural environment. On the other hand, in regions with abundant natural capital, including those with scarce human physical capital (HPSF), human capital (HSF), and physical capital (PSF), such as YG, CL, XCZ, DT, DZ, YB, DP, LT, BK, LJ, ZEX, MY, TL, and XZ, the under-forest economic program and featured agriculture program could be implemented. Specifically, the poverty alleviation strategies, such as planting economic forests and medicinal materials based on local conditions and supporting e-commerce businesses, could be implemented (Figure 8).
All severely impoverished areas are scarce in financial capital and social capital to varying degrees, and in such areas, the main measure for poverty alleviation is financial poverty alleviation, such as cash assistance, loan assistance, and diversified industry cultivation programs.

3.3. Eco-Compensation Model of Longnan City

Based on the intertwined contradiction between severe poverty and vulnerable ecological environment, the eco-compensation model can effectively guarantee the implementation of the targeted poverty alleviation strategy and provide an important source of funds for targeted poverty alleviation. The eco-compensation model of Longnan City contains three compensations: SLCP compensation, key industries exit compensation, and cross-provincial water compensation. The new service value of SLCP compensation is the difference between the comprehensive service value of sloping land after conversion and that before conversion. Therefore, the core for calculating the SLCP compensation is to clarify the spatial distribution and value of ecosystem services in Longnan City. As for key industries exit compensation, the losses can be calculated based on the data collected from questionnaire surveys on mineral enterprises, hydropower enterprises, and aquaculture enterprises. As for cross-provincial water compensation, the compensation standard can be determined according to the accounting standard and sewage treatment cost based on the monitoring indicators of chemical oxygen demand (COD), ammonia nitrogen, total nitrogen, and total phosphorus.

3.3.1. SLCP Compensation

The study showed that the spatial distribution of water yield in Longnan City was relatively unbalanced, with less supply in the southwest and more in the east and northwest (Figure 9a). The total water yield was 5.219 billion m3 in Longnan City, and 1.833 billion m3 in severely impoverished areas, accounting for 35% of total water yield in Longnan City. The total water yield in impoverished areas of Lixian County, Dangchang County, and Wudu District was 456 million m3, 320 million m3, and 320 million m3, respectively, making a great contribution to total water yield in impoverished areas.
The nitrogen and phosphorus output in Longnan City was 0–3311.72 kg/km2 and 0–324.05 kg/km2, respectively, with high nitrogen output in the eastern and northwestern regions (Figure 9b), and high phosphorus output in the central, western, and northwestern regions (Figure 9c). Total nitrogen and phosphorus retention in Longnan City was 3118.80 × 104 kg, 175.50 × 104 kg, 1083.43 × 104 kg, and 66.45 × 104 kg in severely impoverished areas, accounting for 34.74% and 38.29% of total nitrogen and phosphorus retention in Longnan City. There was a large amount of water purification in impoverished areas in Wudu District, Dangchang County, and Lixian County.
The total amount of soil conservation in Longnan City was 28.45 × 108 t, with a higher amount in the south than the north, and with peaks in the east and northwest (Figure 9d). The total amount of soil conservation in severely impoverished areas was 9.66 × 108 t, accounting for 33.95% of the total amount of soil conservation in Longnan City.
The amount of soil conservation in impoverished areas of Wudu District, Lixian County, and Wenxian County was 2.64 × 108 t, 1.65 × 108 t, and 1.55 × 108 t, respectively, making a great contribution to total soil conservation in impoverished areas.
Total carbon sequestration in Longnan City was 70,544.77 × 104 t, with greater carbon sequestration in the center, southeast, southwest, and parts of the northwest (Figure 9e). The total carbon sequestration and oxygen release in severely impoverished areas was 27,855.90 × 104 t, accounting for 39.49% of total carbon sequestration and oxygen release in Longnan City. Carbon sequestration was the highest in LT, followed by LX, and it was the lowest in YG.
Considering the slope characteristics of different cultivated lands, the exit can be implemented by phases. The cultivated lands with a slope of above 25° can be exited in the short term; all cultivated lands in protected areas will exit in the medium term; and cultivated lands with a slope of 15–25° out of the protected areas will be exited in the long term, so as to improve the ecosystem service value in Longnan City. The SLCP compensation standards in the short term, medium term, and long term will be RMB 2.6, 3.3, and 21.9 billion, respectively (Figure 10).

3.3.2. Key Industries Exit Compensation

The accounting of key industries exit compensation covered the losses in exit of mineral enterprises, hydropower enterprises, and aquaculture enterprises in Longnan City. The data about mineral resources were from the questionnaire survey on four mineral enterprises; the data about hydropower energy were from the field surveys on nine hydropower enterprises; and the data about aquaculture resources were from the surveys on aquaculture households, farms, and breeding bases in key river basins. The losses in key industries exit compensation may cover the economic losses of employees, enterprises, and government stakeholders, and the loss in rent of environmental resources. In view of the possible funding constraint and difference in the importance of ecological functions, the short-term, medium-term, and long-term eco-compensation model was determined based on the characteristics, location, and output of the enterprises (Table 2). The short-term exit mainly involved enterprises and traditional aquaculture enterprises located in important ecological function areas such as nature reserves and national parks. The losses of the three key industries reached RMB 0.8 billion. Medium-term exit will mainly involve mineral enterprises and hydropower enterprises, and based on the exit at 50% of the current output, the loss will be RMB 65.9 billion. Long-term exit will also involve mineral enterprises and hydropower enterprises, and the total loss in exit will be RMB 134.1 billion (Figure 10).

3.3.3. Cross-Provincial Water Compensation

All cross-provincial rivers in Longnan City belong to the Yangtze River Basin and Jialing River System, which pass through Gansu Province, and finally flow into Shaanxi Province and Sichuan Province. The cross-provincial sections mainly include those at Dahedian, Yuguan, Tuohe, Maoba, and Guanzigou. The confluence areas of municipal rivers are mainly concentrated in Tianshui City and Gannan Region. The rivers passing through Tianshui City include the Xihanshui River, Baijia River, Mayuan River, Chengjia River, Hongya River, and Liangdang River; and the main river passing through Gannan Region is the Bailong River. According to the monitoring status of water quality at the sections (Table 3) and accounting standards (Table 4), the short-term, mid-term, and long-term compensation schemes and standards of the cross-provincial and cross-municipal water environment in Longnan City were determined. The short-term compensation standard is RMB 0.22 billion, and the mid-term and long-term compensation standards should be calculated according to the actual water quality (Figure 10).
In Longnan City, all funds for eco-compensation are from national transfer payments and horizontal payments between regions. SLCP intends to promote the construction of ecological civilization and improve the quality of the ecological environment. In view of the low compensation standards and inability to achieve the goal of poverty alleviation, the investment should be increased, and the funds should be paid by national transfer payment. Key industries exit compensation intends to protect the downstream ecological environment and water environment. In Longnan located in the upstream, industrial development has been abandoned, so Sichuan Province and Shaanxi Province at the downstream, as the beneficiaries, should pay the corresponding amount of compensation in a horizontal manner as negotiated. Water compensation intends to restrict the activities at the upstream and downstream; if the quality of water from the upstream is lower than the assessment standard, the upstream should pay ecological damage compensation to the downstream, and on the contrary, the downstream should pay ecological protection compensation to the upstream in a horizontal manner between regions.

4. Discussion

4.1. Orientation of Livelihood Assets to Livelihood Strategy

Livelihood assets may affect the livelihood strategy [34]. The low level of human capital would lead to intergenerational poverty. Therefore, for preventing intergenerational poverty, the investment in education must be increased, such as the provision of intellectual support and educational and technical training in regions with scarce human capital. The strengthening of education in the young is of critical significance to the promotion of productivity and efficiency, and for the livelihoods of later generations [35]. The increase in social capital can improve the level of livelihood in impoverished areas [36], and the families with higher social capital would be more likely to get well-paid jobs [37]. Physical capital can stimulate the construction of infrastructure and residences and improve the ownership of animals. The promotion of animal husbandry by policies is quite important for promoting the sustainable use of grassland resources by herding families [38]. Financial capital is the most important capital in non-environmental strategies, and it can guide livelihood strategies with the nature of business [39]. Natural capital refers to the resource of agricultural activities, and its endowment may determine the risks and uncertainties for the people. Under vulnerable ecological environments, the level of natural capital would directly affect the selection of livelihood strategies.
In general, Longnan City lacks financial capital and social capital. Many studies have shown that the expanding of non-agricultural employment is the most effective way to alleviate poverty and increase family income [40,41]. On the one hand, the government should realize the sustainable development of agriculture and animal husbandry and obtain the maximum productivity from less natural capital; in addition, the government should also vigorously develop the medicinal materials industry in Longnan City. The severely impoverished areas in Kangxian County, Wudu District, and Liangdang County can develop competitive industries such as wood fungi with local forest resources; realize large-scale, standardized, and ecological animal husbandry; and build a superior industrial zone of apples in the shallow hills of Longnan. On the other hand, the government should encourage diversified non-agricultural livelihood activities; provide infrastructure for transportation, communication, and the market; improve the talent training system, public service system, and logistics system; vigorously develop e-commerce platforms; and realize poverty alleviation by e-commerce based on featured resources in the regions abundant in natural capital and featured products.
In impoverished areas of Longnan City, like other remote areas around the world, the challenges brought by environmental vulnerability must be reduced or eliminated through improving the overall strength of families by various mechanisms [42]. In this research, it was further confirmed that in impoverished areas abundant in natural resources, family income can be increased while protecting the environment [43]; but, in regions scarce in natural resources, family income can only be increased by other livelihood assets, especially human capital [44].

4.2. Advancements and Limitations of the Eco-Compensation Model

In this paper, an eco-compensation model was established for Longnan City from the aspects of SLCP, key industries exit compensation, and cross-provincial water compensation. Currently, there are mainly two types of compensation mechanisms: punitive and incentive mechanisms. Incentive mechanisms can greatly mobilize the enthusiasm of the participants, and punitive mechanisms can provide a continuous economic basis for the participants to protect the ecosystem. The two mechanisms should be supplementary. Many studies have shown that, if incentive mechanisms and punitive mechanisms can complement each other, the benefits can be increased [45,46]. In the eco-compensation model of Longnan City, SLCP compensation and key industries exit compensation are incentive mechanisms, and cross-provincial water compensation is a punitive mechanism.
The fund for SLCP compensation comes from national transfer payment, and the government’s payment can reduce the economic burden of low-income individuals and activate the eco-compensation mechanism. The fund for key industries exit compensation and cross-provincial water compensation comes from horizontal payments between regions.
At the current stage, the government must participate in eco-compensation, especially in impoverished mountainous areas of Longnan, for the polluters or beneficiaries are limited in the compensation capacity. The cross-provincial water compensation responsibility must be clarified in agreement signed by the government, and a sound supervision mechanism should be established, to achieve dynamic compensation between the upstream and downstream through cross-provincial water environment monitoring. Therefore, the responsibilities, obligations, monitoring index systems, compensation models, and standards should be clarified, and more stringent control measures should be taken [47]. The eco-compensation model of Longnan City conforms to the mainstream model of vertical compensation supplemented by horizontal compensation; in addition, market-oriented compensation was also considered in this research, so as to involve market stakeholders, and thus internalizing the environmental externality.
At present, there is a problem in the compensation model: in cross-provincial water compensation, due to the unequivalence between Longnan City and downstream provinces, it is hard to establish a compensation system and a mutual mechanism, and it is urgent to develop local laws and regulations in Gansu Province. Government compensation may separate ecological beneficiaries from protectors. Therefore, the compensation subjects, compensation scope, and compensation standards must be further clarified in SLCP compensation and key industries exit compensation. In the later period, in addition to incentive compensation, a punitive mechanism should also be established. As for cross-provincial water compensation, the protection and prevention should be integrated into the system, and the compensation and pollutant charge should be combined, so as to further improve the compensation model.
The eco-compensation model, formulated in this study, is predicated on meticulous computations of compensation standards. Nonetheless, the model’s precision may be susceptible to the unpredictable and uncontrollable oscillations in environmental and economic conditions. These fluctuations bear the potential to impact the viability and sustainability of the compensation mechanisms, thereby necessitating periodic recalibrations and updates to the model. To alleviate these risks, it is imperative that future research concentrates on refining evaluation methodologies and maintaining data currency. The fortification of local government and community participation is crucial, as is the enhancement of infrastructure and institutional capacity.

5. Conclusions

In this paper, the livelihood strategies for each region were discussed in detail and the targeted poverty alleviation measures were proposed based on the current targeted poverty alleviation strategy through analyzing livelihood assets in severely impoverished areas in Longnan City. At the same time, an eco-compensation model was established from the aspects of SLCP, key industries exit compensation, and cross-provincial water compensation, which can provide funds for targeted poverty alleviation in Longnan City.
The results showed that the severely impoverished areas are mainly concentrated in central, southern, and northwestern regions in Longnan City. Except for SJ, LY, DQ, LC, and ZZ, natural capital in other areas is relatively high, while human capital, financial capital, physical capital, and social capital are all scarce in Longnan City.
Under the vulnerable ecological environment, the ecological restoration program should be conducted in regions with scarce natural capital, and labor export should be increased in a timely manner. Natural capital should be developed in regions with abundant natural capital under the premise of protecting the ecological environment; the intellectual support program should be conducted in regions with scarce human capital; and the infrastructure construction should be expanded in regions with scarce physical capital. In the ecological environment that is not vulnerable, the stress on the natural environment in regions with scarce natural capital can be lowered through labor export, while in regions with abundant natural capital, the under-forest economic program and featured agriculture program could be implemented.
The short-term, medium-term, and long-term compensation standards for SLCP are, respectively, RMB 2.6, 3.3, and 21.9 billion; those for cross-provincial water quality are, respectively, RMB 0.8, 65.9, and 134.1 billion; and those for key industries exit compensation are, respectively, RMB 9.2, 69.2, and 156.1 billion. The research results can provide theoretical support for understanding the current status of livelihoods and livelihood strategies in Longnan City. The targeted poverty alleviation measures and eco-compensation model can provide an important basis for decision-making from the government and can be of great significance to the sustainable development of Longnan City.

Author Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Y.Q., X.S., H.W., X.M., and J.Z. The first draft of the manuscript was written by Y.Q. and X.L., and all authors commented on previous versions of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA20100101) and supported by the National Key Research and Development Program of China (Grant No. 2019YFC0507404).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used to support the findings of this study are available from the corresponding author upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Topographic map of Longnan City.
Figure 1. Topographic map of Longnan City.
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Figure 2. Sustainable Livelihoods Framework.
Figure 2. Sustainable Livelihoods Framework.
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Figure 3. Sustainable Livelihoods Evaluation index system.
Figure 3. Sustainable Livelihoods Evaluation index system.
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Figure 4. Accounting principle of key industries exit losses.
Figure 4. Accounting principle of key industries exit losses.
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Figure 5. Severely impoverished areas (a), poverty population (b), and poverty incidence in Longnan City (c).
Figure 5. Severely impoverished areas (a), poverty population (b), and poverty incidence in Longnan City (c).
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Figure 6. Annual mean precipitation and temperature in severely impoverished areas.
Figure 6. Annual mean precipitation and temperature in severely impoverished areas.
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Figure 7. Slope, road network, and drainage density in severely impoverished areas.
Figure 7. Slope, road network, and drainage density in severely impoverished areas.
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Figure 8. Poverty types and targeted poverty alleviation measures in Longnan City.
Figure 8. Poverty types and targeted poverty alleviation measures in Longnan City.
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Figure 9. Spatial distribution of ecosystem services in Longnan City. (a) Water yield, (b) nitrogen load, (c) phosphorus load, (d) soil conservation, (e) carbon storage, (f) biodiversity conservation importance.
Figure 9. Spatial distribution of ecosystem services in Longnan City. (a) Water yield, (b) nitrogen load, (c) phosphorus load, (d) soil conservation, (e) carbon storage, (f) biodiversity conservation importance.
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Figure 10. Eco-compensation model of Longnan City.
Figure 10. Eco-compensation model of Longnan City.
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Table 1. Distribution of livelihood assets in Longnan city.
Table 1. Distribution of livelihood assets in Longnan city.
Livelihood AssetsTypesNormalized ValueDistrict
Human capitalScarce0.64TP
Comparatively deficient0.75–0.87JF, EL; DZ, YB, DP; LX, ZZ; CL, XCZ, NY; LY, SJ; DT, YC, BH; YG
Wantless0.90–1.02XZ, LC; LJ, TL, BK; LT, MY; MY; DQ; ZEX
Financial capitalExtremely scarce0.13–0.35TP, DT, YC, BH, DQ, LY; LX, MY, ZZ, LT; TL, LJ, BK; SJ; ZEX; EL, JF; LC, NY, CL, XZ
Scarce0.49–0.59DZ, YB; XCZ; YG
Comparatively deficient0.73–0.86DP; MY
Natural capitalExtremely scarce0.34–0.89SJ, LY, DQ; LC; ZZ
Wantless1.10–1.54XZ; YG; MY; TL
Abundant1.87–2.38CL, NY, XCZ; LX; YC, BH; DP, DZ; EL
Relatively abundant2.87–3.40DT, TP; LT; MY; JF; YB; LJ
Extremely abundant5.18–14.75BK; ZEX
Physical capitalScarce0.52–0.72XCZ, NY, XZ, CL; TP, YC; ZEX; EL; YB, DZ; LX, LT; TL, LJ; MY, YG
Comparatively deficient0.77–0.86LC; BK; JF; MY; LY, SJ; DT
Wantless0.95–1.04ZZ; BH; DQ; DP
Social capitalScarce0.35–0.37LC, NY, CL, XZ
Comparatively deficient0.40–0.50DZ, YB, DP; XCZ; TL, LJ, BK; SJ, DQ, LY; LX, MY, ZZ, LT; YG
Wantless0.55–0.63TP, DT, YC, BH; MY; EL, JF; ZEX
Table 2. Key industries exit compensation.
Table 2. Key industries exit compensation.
IndustriesShort TermMedium TermLong Term
Mineral enterpriseEmployee0.2617.9935.97
Enterprise1.83125.22250.43
Government0.67371.1764.71
Sum2.76514.311051.11
Hydropower enterpriseEmployee0.185.4610.91
Enterprise3.1395.48190.95
Government0.4344.4788.94
Sum3.74145.41290.8
Aquaculture enterpriseEmployee0.08
Enterprise1.07
Government0.51
Sum1.66
Note: Unit is 10−1 RMB.
Table 3. Discharge standards for major pollutants in various water bodies.
Table 3. Discharge standards for major pollutants in various water bodies.
NumberIndicators IIIIIIIVV
1COD ≤ 1515203040
2Ammonia nitrogen ≤ 0.150.511.52
3Total phosphorus ≤ 0.010.0250.050.10.2
4Total nitrogen ≤ 0.20.511.52
Note: Unit is mg/L.
Table 4. Ecological compensation scheme of the cross-provincial water.
Table 4. Ecological compensation scheme of the cross-provincial water.
Draining SectionCurrent SituationTargetCompensation Amount
DahedianIIII594.13
YuguanIII39.81
TuoheIII81.92
MaobaIIII3186.53
GuanzigouIIII18,142.03
Longnan 22,044.4
Note: Unit is 104 RMB.
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Qi, Y.; Song, X.; Lian, X.; Wang, H.; Ma, X.; Zhang, J. Research on Targeted Poverty Alleviation and Eco-Compensation Model in Impoverished Mountainous Areas: A Case Study of Longnan City, China. Sustainability 2024, 16, 6872. https://doi.org/10.3390/su16166872

AMA Style

Qi Y, Song X, Lian X, Wang H, Ma X, Zhang J. Research on Targeted Poverty Alleviation and Eco-Compensation Model in Impoverished Mountainous Areas: A Case Study of Longnan City, China. Sustainability. 2024; 16(16):6872. https://doi.org/10.3390/su16166872

Chicago/Turabian Style

Qi, Yuan, Xiaoyu Song, Xihong Lian, Hongwei Wang, Xiaofang Ma, and Jinlong Zhang. 2024. "Research on Targeted Poverty Alleviation and Eco-Compensation Model in Impoverished Mountainous Areas: A Case Study of Longnan City, China" Sustainability 16, no. 16: 6872. https://doi.org/10.3390/su16166872

APA Style

Qi, Y., Song, X., Lian, X., Wang, H., Ma, X., & Zhang, J. (2024). Research on Targeted Poverty Alleviation and Eco-Compensation Model in Impoverished Mountainous Areas: A Case Study of Longnan City, China. Sustainability, 16(16), 6872. https://doi.org/10.3390/su16166872

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