Comprehensive evaluation of regional resources and environmental carrying capacity using a PS-DR-DP theoretical model

doi:10.1007/s11442-019-1603-4

Abstract

Abstract:

The concepts of regional resources and environmental carrying capacity are important aspects of both academic inquiry and government policy. Although notable results have been achieved in terms of evaluating both these variables, most researchers have utilized a traditional analytical method that incorporates the “pressure-state-response” model. A new approach is proposed in this study for the comprehensive evaluation of regional resources and environmental carrying capacity; applying a “pressure-support”, “destructiveness-resilience”, and “degradation-promotion” (“PS-DR-DP”) hexagon interaction theoretical model, we divided carrying capacity into these three pairs of interactive forces which correspond with resource supporting ability, environmental capacity, and risk-disaster resisting ability, respectively. Negative carrying capacity load in this context was defined to include pressure, destructiveness, and degradation, while support, resilience, and promotion comprised positive attributes. The status of regional carrying capacity was then determined via the ratio between positive and negative contribution values, expressed in terms of changes in both hexagonal shape and area that result from interactive forces. In order to test our “PS-DR-DP” theory-based model, we carried out a further empirical study on Beijing over the period between 2010 and 2015. Analytical results also revealed that the city is now close to attaining a perfect state for both resources and environmental carrying capacity; the latter state in Beijing increased from 1.0143 to 1.1411 between 2010 and 2015, an improved carrying capacity despite the fact that population increased by two million. The average contribution value also reached 0.7025 in 2015, indicating that the city approached an optimal loading threshold at this time but still had space for additional carrying capacity. The findings of our analysis provide theoretical support to enable the city of Beijing to control population levels below 23 million by 2020.

Key words: resources and environmental carrying capacity, “pressure-support”, “destructiveness-resilience” and “degradation-promotion” model;, evaluation, Beijing

Liang WANG, Hui LIU. Comprehensive evaluation of regional resources and environmental carrying capacity using a PS-DR-DP theoretical model[J].Journal of Geographical Sciences, 2019, 29(3): 363-376.

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References 52

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Rank	Mean contribution value	Carrying capacity state
Ⅰ	≤ 0.30	Balance load at lower level with an approximate stable state
Ⅱ	0.30-0.70	Unstable state developing at high speed
Ⅲ	0.70-0.85	An ideal carrying capacity close to the stable state
Ⅳ	≥ 0.85	A fully loaded state with the system collapsing

Force	Influencing factor	Index	No.
Pressure	Water	Average water consumption (m³) Total water consumption (10⁸ m³)	K¹₁ K¹₂
	Land	Requisition of cultivated area (km²) Requisition of industrial and mining land (km²)	K¹₃ K¹₄
	Energy	Coal consumption (10⁸ ton) Oil consumption (10⁴ ton) Gas consumption (10⁸ m³) Electricity consumption (10⁸ kw·h) Energy consumption per unit of GDP (ton of standard coal/10⁴ yuan)	K¹₅ K¹₆ K¹₇ K¹₈ K¹₉
	Population	Population density (person/km²) Total population at year-end (10⁴) Population growth rate (‰) Urban unemployment rate (%) GDP (10⁴ yuan)	K¹₁₀ K¹₁₁ K¹₁₂ K¹₁₃ K¹₁₄
Support	Resources	Water resource per capita (m³/per capita) Total water resources (10⁸ m³) Total land area (km²) Cultivated land increments of a year (km²) Cultivated land area (km²) Per capita food production (kg) Hydropower generation (10⁸ kw·h) Coal reserves (10⁸ ton) Crude oil production (10⁴ ton) Gas production (10⁸ m³) Electrical energy production (10⁸ kw·h)	K¹₁₅ K¹₁₆ K¹₁₇ K¹₁₈ K¹₁₉ K¹₂₀ K¹₂₁ K¹₂₂ K¹₂₃ K¹₂₄ K¹₂₅
Support	Socioeconomy	Whole-society productivity (10⁴ yuan/per capita) Disposable income per capita for urban citizens (10⁴ yuan) Rural per capita net income (10⁴ yuan)	K¹₂₆ K¹₂₇ K¹₂₈

Force	Influencing factor	Index	No.
Destructiveness	Atmospheric environment	Sulfur dioxide emission (10⁴ ton) Flue dust emission (ton)	K²₁ K²₂
	Water environment	Wastewater discharge (10⁴ ton) Chemical oxygen demand (10⁴ ton)	K²₃ K²₄
	Soil environment	Dangerous industrial solid waste output (10⁴ ton) General industrial solid waste output (10⁴ ton)	K²₅ K²₆
	Major disaster	Fatality rate of class A and class B infectious diseases (1/10⁵) Number of geological disasters Number of sudden environmental accidents	K²₇ K²₈ K²₉
Resilience	Pollutant treatment	Proportion of environmental pollution control costs in GDP (%) Amount of industrial sulfur dioxide removal (10⁴ ton) Disposal of general industrial solid waste (10⁴ ton) Disposal of dangerous industrial solid waste (10⁴ ton) City sewage treatment rate (%)	K²₁₀ K²₁₁ K²₁₂ K²₁₃ K²₁₄
Resilience	Disaster prevention	Number of disease control centers Number of automatic meteorological stations Number of seismological stations Number of emergency shelters	K²₁₅ K²₁₆ K²₁₇ K²₁₈

Force	Influencing factor	Index	No.
Degradation	Desertification	Desertification land area (hm²)	K³₁
	Forest degradation	Area of plantation forestry (hm²) Forest disease and insect pest and rodent disaster area (hm²)	K³₂ K³₃
	Water and soil erosion	Increased area of water and soil erosion (hm²) Scope of responsibility for soil erosion control (hm²)	K³₄ K³₅
Promotion	Protection and governance	Forest area (hm²) Wetland area (hm²) Afforestation area (hm²)	K³₆ K³₇ K³₈
Promotion		Small watershed management area (hm²) Control rate of forest disease and insect pest and rodent disaster (%) Control area of water and soil erosion (hm²) Natural reserve area (hm²)	K³₉ K³₁₀ K³₁₁ K³₁₂

Evaluation index system	Cronbachs Alpha	Sample size
Pressure and support	0.949	28
Destructiveness and resilience	0.998	18
Degradation and promotion	0.999	12