恶臭污染排放源指纹谱编制及初步应用

为了识别恶臭污染源排放特征以及了解不同行业恶臭物质排放差异，对恶臭污染排放源指纹谱指标物质进行了筛选，并依据筛选结果对6家典型恶臭排放企业进行样品采集及分析，绘制了各家企业的指纹谱图.结果表明:①通过物质嗅觉阈值与AMGE（ambient multimedia environmental goals，周围环境目标值）和RfC（reference concentration，健康风险参考浓度）对比以及结合国内外恶臭标准受控物质和现有的标准检测方法，最终确定了包括三甲胺、硫化氢、甲硫醇等典型恶臭物质在内的19种物质作为指纹谱指标物质.②依据我国现行的标准监测分析方法对19种恶臭指标物进行检测，初步得到了各家企业的恶臭物质指纹谱数据，绘制了各家企业的指纹谱图.③指纹谱成分分析结果显示，污水处理厂主要的恶臭物质是硫化氢，ρ（硫化氢）为44.566 mg/m3；涂料企业ρ（甲基乙基酮）、ρ（丁醛）和ρ（乙酸乙酯）较高，分别为39.037、28.757、27.840 mg/m3；制药企业ρ（丙醛）较高，为4.791 mg/m3；汽车和家具制造企业ρ（二甲苯）较高，分别为15.209和2.081 mg/m3.④应用分歧系数法分析不同企业指纹谱之间的相似程度，分析结果显示，分歧系数在0.331~0.809之间，不同企业之间指纹谱存在较大差异.研究显示，建立恶臭污染排放源指纹谱可进行恶臭源排放特征识别，为恶臭污染溯源提供基础数据和科学依据. 

Establishment and Application of Odor Pollution Source Fingerprint

In order to identify odor pollution source characteristics and emission differences among industries, we screened out indicators of odor pollution sources. Six typical industries were selected and analyzed. In the end, fingerprint spectrums of typical industries were set up. The results showed that:(1) Nineteen kinds of substances, including trimethylamine, hydrogen sulfide, methanthiol and so on, were chosen as indicators by comparing the substances'' olfactory thresholds with ambient multimedia environmental goals (AMGE) and reference concentrations (RfC), and combining standard controlled substances and existing standard testing methods. (2) Indicators for each industry were detected according to the standard monitoring analysis method, and fingerprint spectrums were set up. (3) Hydrogen sulfide was the main odorous substance in the sewage treatment plant, with a concentration of 44.566 mg/m³. Methyl ethyl ketone, butyl aldehyde and ethyl acetate existed widely in the coating enterprise, with concentrations of 39.037, 28.757 and 27.840 mg/m³, respectively. Propyl aldehyde was a typical compound in the pharmaceutical enterprise, with concentration of 4.791 mg/m³. Xylene was a representative substance in both automobile manufacturing and furniture manufacturing enterprises, with concentrations of 15.209 and 2.081 mg/m³, respectively. (4) The degree of similarity among fingerprints of different enterprises was analyzed by applying the difference coefficient method, which showed that there was a big difference among enterprises when the difference coefficient was between 0.331 and 0.809. The results showed that the establishment of a fingerprint spectrum is good for identifying the emission characteristics of odor sources and provides basic data and scientific basis for tracing odor pollution sources.