ISSN 1008-5548

CN 37-1316/TU

2023年29卷  第6期
<返回第6期

区域环境工业大气污染物的优化治理工艺和处理成本

Optimal treatment technology and processing cost ofregional environmental industrial air pollutants


祝 颖1, 曹 岩2, 张 倩1, 谭纪聪1, 杜红霞1, 沈振兴3

(1. 西安建筑科技大学环境与市政工程学院, 陕西西安710055;2. 甘肃省陇南市生态环境局, 甘肃陇南 746000;3. 西安交通大学能源与动力工程学院, 陕西西安710049)


引用格式:祝颖, 曹岩, 张倩, 等. 区域环境工业大气污染物的优化治理工艺和处理成本[J]. 中国粉体技术, 2023, 29(6): 101-114.

ZHU Y, CAO Y, ZHANG Q, et al. Optimal treatment technology and processing cost of regional environmental industrial air pollutants[J]. China Powder Science and Technology, 2023, 29(6): 101-114.

DOI:10.13732/j.issn.1008-5548.2023.06.010

收稿日期:2023-04-06,修回日期:2023-09-22,在线出版时间:2023-10-09 11:16。

基金项目:国家重点研发计划大气专项项目,编号: 2016YFC0207800;国家自然科学基金项目,编号:42007193;陕西省教育厅重点项目(智库项目),编号:21JT025;20JT042。

第一作者简介:祝颖(1984—),女(蒙古族),博士,副教授。研究方向为环境系统分析、 大气污染控制。E-mail: zhuyingxauat@163.com。


摘要:以陕西省安康市某工业区水泥厂的环境空气质量控制为例,采用基于析因分析法的区间两阶段随机规划法(factorial analysis-interval two-stage stochastic programming method,FA-ITSP),在考虑环境约束的前提下,建立以工业大气环境质量达标和处理成本最低为目标的数学模型;依据水泥厂的环境治理数据、 行业排放标准以及环境空气质量标准,针对去除工业大气中的主要污染物SO2、 NOx和颗粒物的烟气治理过程,进行治理工艺组合优选、 处理成本分析和数学模型析因分析。结果表明:水泥厂烟气治理的最优工艺组合选择双碱法、 选择性非催化还原法、 选择性催化还原法、 电除尘法和袋式除尘法;在主要参数对数学模型输出的贡献方面, 低效率类治理工艺的贡献率是64.88%~77.88%, 高效率类治理工艺的贡献率是7.87%~16.22%,高、 低效率治理工艺组合交互效应的贡献率是0.003%~16.22%; 使用去除效率不同的工艺组合有助于经济效益和环境保护的双赢; 控制好水泥厂脱硝、 除尘系统中的不确定性, 可有利于实现处理成本最低。

关键词:析因分析法; 区间两阶段随机规划法; 区域环境; 工业大气; 治理工艺; 处理成本

Abstract:Taking the ambient air quality control of a cement factory in an industrial zone in Ankang, Shaanxi province as an example, an interval two-stage stochastic programming method based on factorial analysis(FA-ITSP) was adopted. Under the premise of considering environmental constraints, a mathematical model with the objective of achieving industrial atmospheric environmental quality and minimizing processing cost was established. According to the environmental treatment data of cement plant, industry emission standards and ambient air quality standards, the treatment technology combination optimization, processing cost analysis and mathematical model factorial analysis were carried out for the flue gas treatment technology of removing major pollutants SO2, NOx and particulate matter in the industrial atmosphere. The results show that the optimal process combination of flue gas treatment in cement plant is the double alkali method, selective non-catalytic reduction method, selective catalytic reduction method, electric dust removal method and bag dust removal method. In terms of the contribution of the main parameters to the output of the mathematical model, the contribution rate of low efficiency processing is 64.88%~77.88%, the contribution rate of high efficiency processing is 7.87%~16.22%, and the contribution rate of the interaction effect of the combi-nation of high and low efficiency processing is 0.003%~16.22%. Using a combination of processes with different removal efficiencies contributes to both economic benefits and environmental protection. Controlling the uncertainty in the denitration and dust removal system of cement plant can effectively help to achieve the lowest processing cost.

Keywords:factorial analysis method; interval two-stage stochastic programming method; regional environment; industrial atmosphere; treatment technology; processing cost


参考文献(References):

[1]XU W, SUN J, LIU Y, et al. Spatiotemporal variation and socioeconomic drivers of air pollution in China during 2005-2016[J]. Journal of Environmental Management, 2019, 245: 66-75.

[2]中华人民共和国生态环境部. 2021年中国生态环境统计年报[EB/OL]. (2023-01-18)[2023-08-25]. https://www.mee.gov.cn/hjzl/sthjzk/sthjtjnb/202301/W020230118392178258531.pdf.

Ministry of Ecology and Environment, People’s Republic of China. Annual report of China ecological and environmental statistics 2021[EB/OL]. (2023-01-18) [2023-08-25]. https://www.mee.gov.cn/hjzl/sthjzk/sthjtjnb/202301/W020230118392178258531.pdf.

[3]唐湘博, 陈晓红. 我国区域空气质量精准管理最优决策方法研究[J]. 系统工程理论与实践, 2021, 41(12): 3199-3211.

TAND X B, CHEN X H. Research on the optimal decision method for precise management of regional air quality in China[J]. Systems Engineering: Theory and Practice, 2021, 41(12): 3199-3211.

[4]ZHU Y, YAN X X, CHEN C, et al. Analysis of industry-air quality control in ecologically fragile coal-dependent cities by an uncertain Gaussian diffusion-Hurwicz criterion model[J]. Energy Policy, 2019, 132: 1191-1205.

[5]ZHU Y, WEI Z, LI Y X, et al. Energy and atmosphere system planning of coal-dependent cities based on an interval minimax-regret coupled joint-probabilistic cost-benefit approach[J]. Energy, 2021, 239: 122154.

[6]LI Y P, HUANG G H, VEAWAB A, et al. Two-stage fuzzy-stochastic robust programming: a hybrid model for regional air quality management[J]. Journal of the Air and Waste Management Association, 2006, 56(8): 1070-1082.

[7]HUANG G H, LOUCKS D P. An inexact two-stage stochastic programming model for water resources management under uncertainty[J]. Civil Engineering and Environmental Systems, 2000, 17(2): 95-118.

[8]CHEN W T, LI Y P, HUANG G H, et al. A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty[J]. Applied Energy, 2010, 87(3): 1033-1047.

[9]GUO S S, ZHANG F, ZHANG C L, et al. An improved intuitionistic fuzzy interval two-stage stochastic programming for resources planning management integrating recourse penalty from resources scarcity and surplus[J]. Journal of Cleaner Production, 2019, 234: 185-199.

[10]JIN S W, LI Y P, NIE S. An integrated bi-level optimization model for air quality management of Beijing’s energy system under uncertainty[J]. Journal of Hazardous Materials, 2018, 350: 27-37.

[11]KHOSROJERDI T, MOOSAVIRAD S H, ARIAFAR S, et al. Optimal allocation of water resources using a two-stage stochastic programming method with interval and fuzzy parameters[J]. Natural Resources Research, 2019, 28: 1107-1124.

[12]WANG P P, LI Y P, HUANG G H, et al. A multi-scenario factorial analysis and multi-regional input-output model for analyzing CO2 emission reduction path in Jing-Jin-Ji Region[J]. Journal of Cleaner Production, 2021, 2: 126782.

[13]WANG S, HUANG G H, VEAWAB A. A sequential factorial analysis approach to characterize the effects of uncertainties for supporting air quality management[J]. Atmospheric Environment, 2013, 67: 304-312.

[14]LIU H X, LI Y P, YU L. Urban Agglomeration (Guangzhou-Foshan-Zhaoqing) ecosystem management under uncertainty: a factorial fuzzy chance-constrained programming method[J]. Environmental Research, 2019, 173: 97-111.

[15]ZHANG X Y ,HUANG G H, XIE Y L, et al. A coupled non-deterministic optimization and mixed-level factorial analysis model for power generation expansion planning: a case study of Jing-Jin-Ji Metropolitan Region, China[J]. Applied Energy, 2022, 311: 118621.

[16]JAMES E, JUAN S M, JORGE E P, et al. Air quality modeling to inform pollution mitigation strategies in a Latin American Megacity[J]. Science of the Total Environment, 2021, 776: 145894.

[17]LV Y, HUANG G H , LI Y P, et al. A two-stage inexact joint-probabilistic programming method for air quality management under uncertainty[J]. Journal of Environmental Management, 2011, 92(3): 813-826.

[18]WANG S, HUANG G H. A coupled factorial-analysis-based interval programming approach and its application to air quality management[J]. Journal of the Air and Waste Management Association, 2013, 63(2): 179-189.

[19]WANG S, HUANG G H, ZHOU Y. A fractional-factorial probabilistic-possibilistic optimization framework for planning water resources management systems with multi-level parametric interactions[J]. Journal of Environmental Management, 2016 ,172: 97-106.

[20]洪巧巧. 燃煤电厂烟气脱硫脱硝除尘技术生命周期评价[D]. 杭州: 浙江大学, 2015: 71-76.

HONG Q Q. Life cycle evaluation of flue gas desulfurization, denitrification and dust removal technology in coal-fired power plants[D]. Hangzhou: Zhejiang University, 2015: 71-76.

[21]中国环境科学研究院, 合肥水泥研究设计院. 水泥工业大气污染物排放标准: GB 4915—2013[S]. 北京: 中国环境科学出版社, 2014.

Chinese Academy of Environmental Sciences,Hefei Cement Research and Design Institute. Emission standard of air pollutants for cement industry: GB 4915—2013[S].Beijing: China Environmental Science Press, 2014.

[22]中国环境科学研究院, 中国环境监测总站. 环境空气质量标准: GB 3095—2012[S].中国环境科学出版社, 2019.

Chinese Academy of Environmental Sciences, China Environmental Monitoring Station. Ambient air quality standards: GB 3095—2012[S]. Beijing: China Environmental Science Press,2019.

[23]LU H W, HUANG G H, LIU L, et al. An interval-parameter fuzzy-stochastic programming approach for air quality management under uncertainty[J]. Environmental Engineering Science, 2008, 25(6): 895-910.

[24]LV Y, HUANG G H, LI Y P, et al. Interval-based air quality index optimization model for regional environmental management under uncertainty[J]. Environmental Engineering Science, 2009, 26(11): 1585-1597.

[25]LI, Y P, HUANG, G H. An inexact two-stage mixed integer linear programming method for solid waste management in the city of Regina[J]. Journal of Environmental Management, 2005, 81(3): 188-209.