Dioxin Emission Concentration Measurement Approaches for Municipal Solid Wastes Incineration Process: A Survey
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摘要: 焚烧在城市固体废物(Municipal solid wastes, MSW)的无害化、减量化和资源化处理方面优势显著. MSW焚烧(MSW incineration, MSWI)过程副产品之一的剧毒持久性污染物二噁英(Dioxins, DXN)是造成焚烧建厂“邻避效应”的主要原因. DXN排放浓度难以在线实时检测的工业现状已成为制约MSWI过程运行优化与城市环境污染控制的瓶颈. 首先, 结合典型MSWI过程分析DXN的生成特性与排放控制策略; 接着, 将DXN排放浓度检测方法从测量原理、复杂度和时间尺度等视角分为离线直接检测法、指示物/关联物在线间接检测法和软测量法并进行综述; 然后, 对不同方法的发展阶段和关联性进行分析, 指出各自的优劣性和相互间的互补性, 结合MSWI过程特点归纳基于过程数据进行DXN排放浓度软测量的难点, 并将其提炼为一类面向小样本高维稀疏标记数据的智能建模问题; 最后, 指出进行DXN排放浓度智能软测量的未来研究方向和发展前景.Abstract: Incineration has significant advantages in the harmless, reduction and recycling treatment of municipal solid waste (MSW). Dioxins (DXN), a highly toxic and persistent pollutant that is a by-product of the MSW incineration (MSWI) process, is the main cause of the “not in my back yard” effect of incineration plant construction. The industrial status of DXN emission concentration that is difficult to detect real time online has become a bottleneck restricting the optimization of MSWI process operation and municipal environmental pollution control. First, the generation characteristics and emission control strategies of DXN based on a typical MSWI processes are analyzed. Then, the DXN emission concentration detection methods are divided into offline direct detection method, indicator/association online indirect detection method, and soft measurement method in terms of measurement principle, complexity, and time scale. Further, these methods are reviewed in detail. Thirdly, the development stage and correlation of these different methods are addressed, and their respective advantages and disadvantages and complementarity with each other are indicated. Based on the characteristics of MSWI process, the difficulties of DXN emission concentration soft measurement based on process data are summarized. Moreover, it is refined as a class intelligent modeling problem based on small sample high dimensional sparse labeled data. Finally, the future research direction and development prospects of DXN emission concentration intelligent soft measurement are suggested.
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图 2 中国2010年 ~ 2016年MSW处理能力统计和2016年MSW处理比例
Fig. 2 Statistical results of MSW processing capacity in China mainland from 2010 to 2016 and the proportion of MSW processing in 2016
图 3 与DXN具有类似结构和特性的DDT生态食物链积聚图
Fig. 3 Schematic diagram of the accumulation of DDT ecological food chain with similar structure and characteristics as DXN
图 4 PCDDs与PCDFs分子结构图
Fig. 4 Schematic diagram of the molecular structure of PCDDs and PCDFs
图 7 DXN排放浓度检测方法分类图
Fig. 7 Schematic diagram of DXN emission concentration detection method classification
图 8 DXN离线直接检测法分类与检测步骤汇总
Fig. 8 DXN offline direct detection method classification and detection steps summary diagram
图 9 基于指示物/关联物的DXN在线间接检测法
Fig. 9 Indirect detection method of DXN based on indicator/associated substance
图 10 低挥发性有机氯(LVOCL)在线测量系统示意图
Fig. 10 Schematic diagram of on-line measurement system for low volatile organic chlorine (LVOCL)
图 14 虚拟样本空间与真实样本空间的关系示意图
Fig. 14 Schematic diagram of the relation between virtual sample space and real sample space
图 15 机理特性分析、数值模拟和软测量模型间的关系
Fig. 15 Relation among mechanism characteristic analysis, numerical simulation and soft sensor model
表 1 DXN生物检测法优缺点的对比[87]
Table 1 Comparison of advantages and disadvantages of DXN bioassay detection method[87]
方法 预处理 检测周期 (天) 检测成本 (美元) 灵敏度 (pg/g) 实验室投入 (美元) 酶活力诱导生物法 简便 3 1 000~1 200 1.000 200 000 酶免疫法 简便 2 200~900 0.500 200 000 荧光素酶法 简便 1 200~900 0.025 200 000 
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表 2 DXN检测标准的发展历程
Table 2 Development of DXN detection standards
序号 标准号 描述 年份 国家 文献 1 EPA 1613 (美) 同位素稀释法测定八氯二噁英及其呋喃 1994年10月 美国 [100] 2 EPA 23 (美) MSWI过程中多氯化二苯并二噁英的测定 1995年12月 美国 [101] 3 EPA 8280 (美) 多氯化二苯并二噁英和呋喃的分析测定, 高分辨气相低分辨质谱法 1996年12月 美国 [102] 4 EPA 1668A (美) 高分辨气质联用测定水、土壤、沉积物、生物体和组织中的多氯联苯 1999年12月 美国 [103] 5 JIS K0311 (日) 排入空气中的PCDDs、PCDFs以及Co-PCBs的气相色谱–质谱联用检测 方法 1999年9月 日本 [104] 6 EN1948-1 (欧盟) DXN排放统一检测标准 2006年 欧盟 [105] 7 HJ/T77-2001 (中) 多氯代二苯并二噁英和多氯代二苯并呋喃的测定, 同位素稀释高分辨毛 细管气相色谱–高分辨质谱法 2001年 中国 [106] 8 HJ 77.3-2008 (中) 固体废物二噁英类的测定, 同位素稀释, 高分辨气相色谱–高分辨质谱法 2008年 中国 [107] 9 HJ/T 365-2007 (中) 规定危险废物焚烧处置设施二噁英排放监测技术要求 2007年 中国 [108] 10 GB 18485-2001 (中) 生活垃圾焚烧污染控制标准 2001年 中国 [109] 11 GB 18485-2014 (中) 生活垃圾焚烧污染控制标准 2014年 中国 [110] 注: 中国的HJ/T 77-2001标准改进于美国的EPA 1613, HJ 77.3-2008改进于美国的EPA 8280.
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表 3 DXN检测方法统计
Table 3 DXN detection method statistics
类别 名称 方法简述 优点和缺点 侧重点 年份与文献 离线直接检测法 色谱法 首先对样本进行采集、提取与净化、同位素标记、色谱柱分离, 然后与检测器联用进行定性与定量分析 优点: 可分离DXN类物质组分
和准确度量
缺点: 周期长、费用高、对操
作人员与设备要求高DXN类物质的超痕量分析 1993[146] DXN类物质萃取方法 1994[147] MSWI过程DXN排放浓度检测 1992[148] 空气中DXN浓度的检测 1989[149], 1996[150] 论述DXN的提取方法 1995[151], 1996[152] 检测土壤中的DXN 1994[153] 激光质谱法 基于激光波长选择性电离, 再采用飞行时间质谱仪进行质量选择 优点: 快速、高灵敏度
缺点: 前期准备过程复杂指出DXN同类物具有独特光谱结构和较窄带宽 2010[88] 简述激光质谱法原理 1998[89] 激光质谱法在环境监测中的应用 2001[90] 可移动式激光质谱仪对MSWI过程中产生的DXN排放浓度进行检测 1996[154] 生物法 酶活力诱导生物法: 通过特殊受体芳香烃测量DXN毒性 优点: 周期短、成本低、大量样品可同时测定
缺点: 仅能测总体的毒性当量简述酶活力诱导生物法 1985[155], 1989[156] 简述酶活力诱导生物法在国内DXN检测中的应用 1996[91] 酶免疫分析法: 单克隆或复合克隆抗体与DXN同类物高度结合的特性, 建立竞争抑制酶免疫方法 优点: 分析简便、易操作、测定周期较短
缺点: 不能测出DXN同类物的具体量值、需测定标准曲线、样品量大时误差较大简述酶免疫分析法 1987[157], 1997[92], 1999[93] 简述酶免疫法在国内DXN检测方面的应用 1997[158] 提出酶免疫法与光谱法联合使用 2006[94] 与酶活力免疫法进行比较, 其准确性较高 2001[95] 荧光素酶法: 利用基因工程, 重组染色体配体复合物, 进一步合成荧光素 优点: 灵敏度高、检测时间短
缺点: 无法测出DXN同类物的具体量值简述荧光素酶法 1984[96] 荧光素酶法与其他生物法的比较 2001[97], 2001[98] 对MSWI过程DXN的排放进行检测, 并与色谱法比较 2011[99] 免疫法 基于DXN类抗体获得样本毒性当量, 计算出DXN含量 优点: 操作简便, 检测仪器要求低
缺点: 抗体制作复杂, DXN同类物检测种类有限采用单克隆抗体对DXN进行检测 1980[159] 采用单克隆与血清蛋白结合, 缩短检测时间 1986[160] 指示物/
关联物在
线间接检
测法基于氯苯与DXN映射关系进行检测 研究多种氯苯与DXN之间的映射关系 优点: 检测周期短
缺点: 不够稳定, 映射模型本身存在误差, 存在时间滞后性六氯苯与DXN映射关系 1985[114] 五氯苯与DXN映射关系 2006[115] 多氯联苯与DXN映射关系 1994[116] 其他氯苯与DXN映射关系 1996[118], 1999[121], 2001[122], 2002[117], 2005[48], 2005[119], 2010[123], 2012[51], 2016[124], 2017[120], 2018[39] 基于多环芳烃与DXN映射关系进行检测 研究多环芳烃与DXN映射关系 同上 多环芳烃与DXN映射关系 2003[125], 2006[126], 2009[127] 实时在线跟踪多环芳烃的质谱仪 1999[128] 基于氯酚与DXN映射关系进行检测 研究氯酚与DXN映射关系 同上 氯酚与DXN之间的映射关系 2002[117], 1999[129] 氯苯和氯酚与DXN映射关系 2000[131], 2001[130], 2016[133] 氯苯与氯酚与DXN之间的映射关系的精度对比 1987[132], 2005[48] 其他指示物与DXN映射关系进行检测 研究其他指示物与DXN映射关系 同上 有机卤素化合物与DXN之间的映射关系 2010[134] 松针表面DXN浓度检测 2018[135] 低挥发性有机氯与DXN之间的映射关系 2010[136] 软测量法 回归分析法 构建线性映射关系模型 优点: 周期短, 成本低;
缺点: 无法描述非线性映射关系温度与DXN之间的回归模型 1989[137] 焚烧尾气CO含量与DXN之间的回归模型 2002[138], 2002[117] 过量空气与DXN之间的回归模型 1989[139] 烟气处理设备前的烟气与DXN之间的回归模型 2013[140] 神经网络 构建非线性单模型 优点: 周期短, 成本低;
缺点: 基于小样本的神经网络模型稳定性差, 泛化能力差欧美研究结构收集的焚烧炉数据, 单神经网络模型 1995[59], 2018[141] 中国实验规模的焚烧炉, 单神经网络与集成神经网络模型 2008[62], 2012[63] 中国台湾地区焚烧炉, 单神经网络模型 2003[142] 遗传编程 构建非线性模型 优点: 周期短, 检测成本低;
缺点: 泛化能力差, 计算复杂度高欧美研究结构收集的3种类型焚烧炉数据, 基于遗传编程构建非线性模型 2000[60] 支持向量机 构建非线性模型 优点: 周期短, 成本低;
缺点: 泛化能力差, 样本有限
未进行特征选择中国华南地区某焚烧炉, 单模型 2017[143] 欧美研究结构收集的焚烧炉数据, 选择性集成模型 2019[144]
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