锌冶炼用氧化锌富集物再生综合效益评价

向治锦; 张庆; 吕庆; 黄国忠; 高学鸿; 司念朋

doi:10.12153/j.issn.1674-991X.20210441

锌冶炼用氧化锌富集物再生综合效益评价

doi: 10.12153/j.issn.1674-991X.20210441

1.
北京科技大学土木与资源工程学院, 大安全科学研究院
2.
中国检验检疫科学研究院

基金项目: 市场监管总局科技计划项目（2019MK127）；国家重点研发计划项目（2018YFF0215500）

详细信息

作者简介:
向治锦（1998—），男，硕士研究生，主要研究方向为环境安全评价，zhijind163@163.com

通讯作者:
司念朋（1984—），男，高级工程师，主要从事工业产品质量安全及再生利用研究，isinp@sina.com

中图分类号: X758
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出版历程
- 收稿日期: 2021-08-21

Comprehensive benefit evaluation of zinc oxide enrichment regeneration for zinc smelting

1.
Research Institute of Macro-Safety Science, School of Civil and Resource Engineering, University of Science and Technology Beijing
2.
Chinese Academy of Inspection and Quarantine

摘要

摘要:
针对锌冶炼用氧化锌富集物的再生效益进行评估，对推动锌再生资源利用的合理规划，支持环境管理的科学决策具有重要意义。以国内企业的调研结果为依据，建立包括经济效益、资源效益、环境效益和社会效益4个层面影响因素的氧化锌富集物再生综合效益评价指标体系；运用层次分析法（AHP）和基于指标相关性的权重确定方法（CRITIC）对指标进行组合赋权，再对采用黄金分割法划分的标准云进行修正，进而构建基于组合赋权-云模型的综合效益评价模型，并对江西某铅锌金属公司进行实例评价。结果表明：该企业氧化锌富集物再生制锌的综合效益水平较高，一级指标中资源效益水平高，环境、社会和经济效益水平较高，且环境效益和社会效益的评价结果不确定性更大。所得结果兼顾评价过程中的模糊性和随机性，提供了更加全面的锌冶炼用氧化锌富集物再生效益评价信息。
- 氧化锌富集物再生 /
- 云模型 /
- 组合赋权 /
- 效益评价
Abstract:
Evaluation of the regeneration benefit of zinc oxide enrichment for zinc smelting is of great significance for promoting rational planning of the utilization of regenerated zinc resources and supporting scientific decision-making of environmental management. Based on the survey results of domestic enterprises, an evaluation index system for the comprehensive benefits of zinc oxide enrichment regeneration was established, considering economic, resource, environmental and social factors, where comprehensive weights were obtained by applying the analytic hierarchy process (AHP) and CRITIC method for weighting, and the standard cloud divided by the golden section method was modified. Then a comprehensive benefit evaluation model based on the combination weighting method and cloud model was constructed. After that, a lead-zinc metal company in Jiangxi Province was used as a case study. The results showed that the comprehensive benefit level of the company's zinc production from zinc oxide enrichment regeneration was at a high level. Regarding the first-level factors, the resource benefit was at the highest level; the environmental, social and economic benefits were at the second high level, and the evaluation results of environmental and social benefits were more uncertain. The fuzziness and randomness were considered in the process of evaluation, which provided more comprehensive evaluation information of the regeneration benefit of zinc oxide enrichment for zinc smelting.
- zinc oxide enrichment regeneration /
- cloud model /
- combination weighting /
- benefit evaluation

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图 1 云模型双向转换示例

Figure 1. Example of bidirectional conversion of cloud model

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图 2 氧化锌富集物再生综合效益评价指标体系

Figure 2. Comprehensive benefit evaluation index system of zinc oxide enrichment regeneration

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图 3 综合效益评价流程

Figure 3. Comprehensive benefit evaluation process

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图 4 指标权重分布

Figure 4. Index weight distribution diagram

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图 5 一级指标评价云图

注：图中红色云团代表评价结果的分布情况。

Figure 5. First-level index evaluation cloud chart

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图 6 综合效益评价云图

注：同图5。

Figure 6. Comprehensive benefit evaluation cloud chart

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表 1 评价标准云特征参数

Table 1. Characteristic parameters of evaluation standard cloud

评价等级	各级指标区间划分	($E{x_i} $, $E{n_i} $, $He_i $)
低水平	[0,20)	(0, 16.915, 0.873)
较低水平	[20,40)	(30.9, 9.094, 0.539)
中等水平	[40,60)	(50, 5.620, 0.2)
较高水平	[60,80)	(69.1, 9.094, 0.539)
高水平	[80,100]	(100, 16.915, 0.873)

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表 2 对应二级指标的企业调研信息

Table 2. Enterprise survey information corresponding to the second-level indicators

二级指标	指标性质	企业数据	二级指标	指标性质	企业数据
企业再生生产净利润B₁₁/万元	定量	2 853	再生生产污染物减排B₃₁/t	定量	固废,1 444; SO₂,4.75; NO_x,3.89
再生生产净利润率B₁₂/%	定量	6.99	再生生产温室气体（CO₂）减排B₃₂/t	定量	886
节省废弃富集物处理费用B₁₃/万元	定量	>1 000	避免采矿对环境影响B₃₃	定性	专家参考实地调研情况打分
对政府财政收入贡献B₁₄/万元	定量	623	避免含锌废物对环境影响B₃₄	定性	专家参考实地调研情况打分
节省能耗B₂₁/kg(以标煤计)	定量	8.937×10⁶	创造就业岗位B₄₁	定量	相关岗位110～130个
节省等量锌精矿消耗B₂₂/t	定量	43 215	提高公众环境满意度B₄₂	定性	专家参考调查问卷结果打分
回收富集物资源总量B₂₃/t	定量	51 377	减少对锌精矿依赖度B₄₃	定性	专家参考实地调研情况打分
富集物投入产出比B₂₄	定量	2.378	综合利用管理及技术的示范带头作用B₄₄	定性	专家参考实地调研情况打分

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表 3 效益指标权重

Table 3. Weight values of benefit indexes

目标层	一级指标				二级指标
目标层	指标	主观权重	客观权重	组合权重	指标	主观权重	客观权重	组合权重
B	B₁	0.125	0.235	0.174	B₁₁	0.052	0.049	0.054
					B₁₂	0.028	0.065	0.045
					B₁₃	0.013	0.049	0.027
					B₁₄	0.032	0.071	0.050
	B₂	0.366	0.268	0.318	B₂₁	0.107	0.075	0.095
					B₂₂	0.160	0.049	0.093
					B₂₃	0.028	0.069	0.046
					B₂₄	0.071	0.075	0.076
	B₃	0.277	0.242	0.262	B₃₁	0.076	0.059	0.070
					B₃₂	0.067	0.075	0.075
					B₃₃	0.072	0.049	0.062
					B₃₄	0.062	0.059	0.063
	B₄	0.231	0.255	0.246	B₄₁	0.033	0.066	0.049
					B₄₂	0.064	0.082	0.076
					B₄₃	0.104	0.049	0.075
					B₄₄	0.029	0.059	0.044

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表 4 二级指标评分值的云特征参数

Table 4. Cloud feature parameters of second-level index scores

指标	组合权重	(Ex, En, He)	指标	组合权重	(Ex, En, He)
B₁₁	0.054	(78.125,3.917,1.225)	B₃₁	0.070	(78.750,4.700,1.564)
B₁₂	0.045	(66.875,2.937,1.290)	B₃₂	0.075	(70.625,4.112,0.706)
B₁₃	0.027	(71.875,4.504,0.834)	B₃₃	0.062	(81.250,5.092,0.928)
B₁₄	0.050	(71.250,3.525,0.273)	B₃₄	0.063	(78.125,5.483,1.393)
B₂₁	0.095	(84.375,4.112,0.706)	B₄₁	0.049	(71.250,4.700,1.564)
B₂₂	0.093	(83.750,3.525,0.273)	B₄₂	0.076	(65.000,4.700,2.546)
B₂₃	0.046	(75.625,2.742,1.659)	B₄₃	0.075	(81.875,5.483,1.393)
B₂₄	0.076	(73.125,2.937,1.390)	B₄₄	0.044	(73.750,4.700,1.564)

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表 5 效益评价的云特征参数

Table 5. Cloud characteristic parameters of benefit evaluation

效益类型	(Ex,En,He)
B₁	(72.324,3.680,0.936)
B₂	(80.115,3.483,0.887)
B₃	(76.939,4.839,1.141)
B₄	(73.026,4.954,1.817)
B	(76.160,4.297,1.191)

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表 6 效益评价结果及对比

Table 6. Benefit evaluation results and comparison

评价方法	效益类型	评价等级云相似度（确定度）					评价等级
评价方法	效益类型	低水平	较低水平	中等水平	较高水平	高水平	评价等级
本研究方法	经济效益	0	0	0.003	0.763	0.234	较高
	资源效益	0	0	0	0.497	0.503	高
	环境效益	0	0	0.001	0.622	0.377	较高
	社会效益	0	0	0.006	0.732	0.262	较高
	综合效益	0	0	0.001	0.652	0.347	较高
模糊综合评价法	经济效益	0	0	0.040	0.804	0.156	较高
	资源效益	0	0	0	0.494	0.506	高
	环境效益	0	0	0	0.653	0.347	较高
	社会效益	0	0	0.078	0.693	0.229	较高
	综合效益	0	0	0.026	0.640	0.334	较高

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参考文献(24)

[1]	工业和信息化部. 锌冶炼用氧化锌富集物: YS/T 1343—2019[S]. 北京: 冶金工业出版社, 2019.
[2]	潘志君, 夏鹏, 朱清, 等.中国锌矿资源开发利用形势分析[J]. 地球学报,2021,42(2):258-264. doi: 10.3975/cagsb.2020.110203 PAN Z J, XIA P, ZHU Q, et al. An analysis of the development and utilization situation of China's zinc ore resources[J]. Acta Geoscientica Sinica,2021,42(2):258-264. doi: 10.3975/cagsb.2020.110203
[3]	王菲, 张曼丽, 王雪娇, 等. 我国铜、铅和锌冶炼过程中危险废物产生与污染特性[J]. 环境工程技术学报, 2021, 11(5): 1012-1019. WANG F, ZHANG M L, WANG X J, et al.Generation and pollution characteristics of hazardous wastes from smelting of copper, lead and zinc in China[J]. Journal of Environmental Engineering Technology, 2021, 11(5): 1012-1019.
[4]	KIM J, JEONG S. Economic and environmental cost analysis of incineration and recovery alternatives for flammable industrial waste: the case of South Korea[J]. Sustainability,2017,9(9):1638. doi: 10.3390/su9091638
[5]	张晋豫, 阮久莉, 刘才田, 等.基于MFCA的典型再生锌工艺成本优化分析[J]. 环境工程技术学报,2020,10(2):310-315. doi: 10.12153/j.issn.1674-991X.20190109 ZHANG J Y, RUAN J L, LIU C T, et al. MFCA-based cost optimization analysis for typical secondary zinc production process[J]. Journal of Environmental Engineering Technology,2020,10(2):310-315. doi: 10.12153/j.issn.1674-991X.20190109
[6]	亓聪聪. 我国湿法冶锌制备生命周期评价[D]. 济南: 山东大学, 2018.
[7]	宋海燕, 牛建刚, 崔宝霞.钢铁工业固体废弃物利用效益综合评价[J]. 钢铁,2017,52(2):85-90. SONG H Y, NIU J G, CUI B X. Comprehensive evaluation of solid waste utilization benefit in iron and steel industry[J]. Iron & Steel,2017,52(2):85-90.
[8]	杨洁, 王国胤, 刘群, 等.正态云模型研究回顾与展望[J]. 计算机学报,2018,41(3):724-744. doi: 10.11897/SP.J.1016.2018.00724 YANG J, WANG G Y, LIU Q, et al. Retrospect and prospect of research of normal cloud model[J]. Chinese Journal of Computers,2018,41(3):724-744. doi: 10.11897/SP.J.1016.2018.00724
[9]	杨恒, 刘永强.基于PP-云模型的河道治理工程效益评价研究[J]. 水利水电技术,2020,51(5):118-125. YANG H, LIU Y Q. Study on benefit evaluation of river regulation project based on PP-cloud model[J]. Water Resources and Hydropower Engineering,2020,51(5):118-125.
[10]	ZHANG L H, CHAI J X, XIN H, et al. Evaluating the comprehensive benefit of hybrid energy system for ecological civilization construction in China[J]. Journal of Cleaner Production,2021,278:123769. doi: 10.1016/j.jclepro.2020.123769
[11]	YANG Z T, HUANG X F, FANG G H, et al. Benefit evaluation of East Route Project of South to North Water Transfer based on trapezoid cloud model[J]. Agricultural Water Management,2021,254:106960. doi: 10.1016/j.agwat.2021.106960
[12]	LI D Y, LIU C Y, GAN W Y. A new cognitive model: cloud model[J]. International Journal of Intelligent Systems,2009,24(3):357-375.
[13]	ZHANG L M, WU X G, CHEN Q Q, et al. Developing a cloud model based risk assessment methodology for tunnel-induced damage to existing pipelines[J]. Stochastic Environmental Research and Risk Assessment,2015,29(2):513-526. doi: 10.1007/s00477-014-0878-3
[14]	WU Y N, TAO Y, DENG Z Q, et al. A fuzzy analysis framework for waste incineration power plant comprehensive benefit evaluation from refuse classification perspective[J]. Journal of Cleaner Production,2020,258:120734. doi: 10.1016/j.jclepro.2020.120734
[15]	田金枝. 建筑垃圾生产再生骨料的综合效益分析[D]. 重庆: 重庆大学, 2019.
[16]	DIAKOULAKI D, MAVROTAS G, PAPAYANNAKIS L. Determining objective weights in multiple criteria problems: the critic method[J]. Computers & Operations Research,1995,22(7):763-770.
[17]	荀志远, 张丽敏, 赵资源, 等.基于组合赋权云模型的装配式建筑成本风险评价[J]. 土木工程与管理学报,2020,37(6):8-13. doi: 10.3969/j.issn.2095-0985.2020.06.002 XUN Z Y, ZHANG L M, ZHAO Z Y, et al. Cost risk evaluation of prefabricated buildings based on combined weighted cloud model[J]. Journal of Civil Engineering and Management,2020,37(6):8-13. doi: 10.3969/j.issn.2095-0985.2020.06.002
[18]	MIAO C, TENG J K, WANG J, et al. Population vulnerability assessment of geological disasters in China using CRITIC-GRA methods[J]. Arabian Journal of Geosciences,2018,11(11):1-12.
[19]	赵书强, 汤善发.基于改进层次分析法、CRITIC法与逼近理想解排序法的输电网规划方案综合评价[J]. 电力自动化设备,2019,39(3):143-148. ZHAO S Q, TANG S F. Comprehensive evaluation of transmission network planning scheme based on improved analytic hierarchy process, CRITIC method and TOPSIS[J]. Electric Power Automation Equipment,2019,39(3):143-148.
[20]	徐选华, 吴慧迪.基于改进云模型的语言偏好信息多属性大群体决策方法[J]. 管理工程学报,2018,32(1):117-125. XU X H, WU H D. Approach for multi-attribute large group decision-making with linguistic preference information based on improved cloud model[J]. Journal of Industrial Engineering and Engineering Management,2018,32(1):117-125.
[21]	周雪, 左忠义, 程伟.基于组合赋权云模型的铁路旅客运输安全评价[J]. 中国安全科学学报,2020,30(增刊1):158-164. ZHOU X, ZUO Z Y, CHENG W. Safety evaluation of railway passenger transportation based on combined weighting cloud model[J]. China Safety Science Journal,2020,30(Suppl 1):158-164.
[22]	胡长明, 刘林, 王晓华, 等.基于模糊熵-云理论的二维深基坑施工风险评价[J]. 安全与环境学报,2021,21(2):521-528. HU C M, LIU L, WANG X H, et al. Risk assessment for the 2-D deep foundation pit based on the fuzzy entropy-cloud theory[J]. Journal of Safety and Environment,2021,21(2):521-528.
[23]	史小棒, 赵云胜, 罗聪, 等.基于云模型的地勘行业安全生产标准化等级评价[J]. 安全与环境工程,2019,26(2):124-128. SHI X B, ZHAO Y S, LUO C, et al. Evaluation of safety production standardization level in geological prospecting industry based on cloud model[J]. Safety and Environmental Engineering,2019,26(2):124-128.
[24]	梁力, 邢观华, 吴凤元.基于云理论的评估模型和方法[J]. 东北大学学报(自然科学版),2019,40(6):881-885. doi: 10.12068/j.issn.1005-3026.2019.06.022 LIANG L, XING G H, WU F Y. The evaluation model and method based on cloud theory[J]. Journal of Northeastern University (Natural Science),2019,40(6):881-885. ⊗ doi: 10.12068/j.issn.1005-3026.2019.06.022