Safety Evaluation of Sustainable Uranium Development in China Combined with an Analytical GAN Framework

Liangyan LIU; Ming CHENG

doi:10.5814/j.issn.1674-764x.2020.04.008

Journals >Journal of Resources and Ecology >Volume 11 >Issue 4 >Page 394 > Article

Journal of Resources and Ecology
Vol. 11, Issue 4, 394 (2020)

Safety Evaluation of Sustainable Uranium Development in China Combined with an Analytical GAN Framework

Liangyan LIU^{1、1、2、2、*} and Ming CHENG^{1、1、2、2}

Author Affiliations

¹School of Management, Wuhan University of Science and Technology, Wuhan 430081, China

¹武汉科技大学恒大管理学院,武汉430081

²Department of Energy Cycle Technology, Wuhan University of Science and Technology, Wuhan 430081, China

²武汉科技大学新能源技术实验室,武汉430081

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DOI: 10.5814/j.issn.1674-764x.2020.04.008 Cite this Article

Liangyan LIU, Ming CHENG. Safety Evaluation of Sustainable Uranium Development in China Combined with an Analytical GAN Framework[J]. Journal of Resources and Ecology, 2020, 11(4): 394 Copy Citation Text

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Fig. 1. Fig. 1

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Fig. 2. Fig. 2

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Key indicators	Sub-indicators	Cronbach α
Supply indicator	Resources (expected reserves, recovered reserves, recoverable reserves) (X1)	0.802
	Production volume (yield growth rate, storage-production ratio) (X2)
	Imported uranium mine (import concentration, import share, external dependence) (X3)
Demand indicator	Population growth (X4)	0.814
	Lifestyle of residents (X5)
	Economic growth rate (X6)
	Technological advancement (X7)
	Production and consumption structure (X8)
	Alternative levels of other energy sources (X9)
	Supply and demand ratio of uranium resources (X10)
	Uranium resource consumption intensity (X11)
	Industrial structure (X12)
Price indicator	Producer price (X13)	0.898
	International market price (X14)
	Production cost (X15)
	Marginal cost of mining technology (X16)
	Tax rate (X17)
Technical indicator	Mining rate (X18)	0.858
	Uranium comprehensive utilization rate (X19)
	Science and technology contribution rate of uranium mining industry (X20)
	Scientific and technological achievements conversion rate of uranium mining industry (X21)
Environment indicator	Nuclear waste (spent fuel post-processing) stock (Y1)	0.856
	Uranium mine regional distribution (Y2)
	Welfare loss (Y3)
	Uranium mine depletion cost (Y4)
	Environmental degradation cost (Y5)
	Environmental pollution loss (Y6)
Strategic indicator	Control of domestic uranium mines (Y7)	0.842
	Control of international uranium mines (Y8)
	Strategic reserve for uranium mines (Y9)
	Global development strategy (Y10)
Political indicator	External relationship stability (Y11)	0.752
	Domestic political environment stability (Y12)
	Uranium mining industry policy (Y13)
	Consumption habits of nuclear power (Y14)
Management indicator	Human resources (Y15)	0.791
	Equipment integrity rate (Y16)
	Improvement rate of production safety system measures (Y17)
	Safety of import transportation channel (Y18)
	Influence control degree of import transportation channels (Y19)
	Environmental safety (Y20)
	Information identification and processing capabilities (Y21)

Table 1.

Confidence analysis of the overall indicator metrics for evaluating the resource safety of uranium in China

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Method	Variables		Value
Kaiser-Meyer-Olkin	KMO value		0.954
Bartlett’s sphericity test		Approximate chi square	2136.125
		df	162
		Sig.	0.000

Table 2.

Factor analysis fitness test using KMO value and Bartlett’s spherical test

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Chi-square value	P value	AGFI	GFI	RMSEA	CN
197.740	0.000	0.846	0.886	0.175	187

Table 3.

Model fitness index

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Chi-square value	P value	AGFI	GFI	RMSEA	CN
138.682	0.076	0.832	0.938	0.029	194

Table 4.

Revised model fitness index

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Key indicators	Sub-indicators	Technical department	Economic department	Social resident	Environmental department
Supply indicator	Resources (expected reserves, recovered reserves, recoverable reserves) (X1)	0.225	0.337	0.013	0.004
	Production volume (yield growth rate, storage-production ratio) (X2)
	Imported uranium mine (import concentration, import share, external dependence) (X3)
Demand indicator	Population growth (X4)	0.007	0.122	0.006	0.003
	Lifestyle of residents (X5)
	Economic growth rate (X6)
	Technological advancement (X7)
	Production and consumption structure (X8)
	Alternative level of other energy sources (X9)
	Supply and demand ratio of uranium resources (X10)
	Uranium resource consumption intensity (X11)
	Industrial structure (X12)
Priceindicator	Producer price (X13)	0.012	0.203	0.104	0.004
	International market price (X14)
	Production cost (X15)
	Marginal cost of mining technology(X16)
	Tax rate (X17)
Technical indicator	Mining rate (X18)	0.414	0.107	0.013	0.329
	Uranium comprehensive utilization rate (X19)
	Science and technology contribution rate of uranium mining industry (X20)
	Scientific and technological achievements conversion rate of uranium mining industry (X21)
Environmental indicator	Nuclear waste (spent fuel post-processing) stock (Y1)	0.148	0.006	0.512	0.474
	Uranium mine regional distribution (Y2)
	Welfare loss (Y3)
	Uranium mine depletion cost (Y4)
	Environmental degradation cost (Y5)
	Environmental pollution loss (Y6)
Strategicindicator	Control of domestic uranium mines (Y7)	0.009	0.103	0.073	0.049
	Control of international uranium mines (Y8)
	Strategic reserve for uranium mines (Y9)
	Global development strategy (Y10)
Political indicator	External relationship stability (Y11)	0.012	0.015	0.062	0.078
	Domestic political environment stability (Y12)
	Uranium mining industry policy (Y13)
	Consumption habits of nuclear power (Y14)
Management indicator	Human resources (Y15)	0.173	0.107	0.217	0.059
	Equipment integrity rate (Y16)
	Improvement rate of production safety system measures (Y17)
	Safety of import transportation channel (Y18)
	Influence control degree of import transportation channels (Y19)
	Environmental safety (Y20)
	Information identification and processing capabilities (Y21)

Table 5.

Weight values of evaluation indicators from the stakeholders’ perspectives

Liangyan LIU, Ming CHENG. Safety Evaluation of Sustainable Uranium Development in China Combined with an Analytical GAN Framework[J]. Journal of Resources and Ecology, 2020, 11(4): 394

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