Source Identification And Sensory Quantitative Assessment Of Malodorous Volatile Organic Compounds Emitted From Municipal Sewage Treatment Plant

The chemical components analysis method of pre-concentration/thermal desorption/gas chromatography coupled with mass spectrometer (GC/MS) and the odor fingerprint analysis method of an electronic nose were established to measure the air samples of Malodorous Volatile Organic Compounds(MVOCs) emitted from a typical municipal sewage treatment plant in Guangzhou. By field observation and laboratory simulation experiments, the chemical compositions and concentrations of the MVOCs samples were investigated, as well as the pollution characteristics of their sensorial odor fingerprints. In addition, the method of sensory quantitative assessment was explored. The results are showed as following:1.80 volatile organic compounds (VOCs) were detected in the studied plant, including alkanes, alkenes, aromatic hydrocarbon, halogenated hydrocarbons, volatile sulphur compounds (VSCs) and oxygen-containing hydrocarbons.54 MVOC species were identified with their composition and concentration closely related with the processing type. Among the six processing units, dehydration room showed the highest level of detected MVOCs. The VOC concentrations of all sampling sites were ranged from 132.36μg/m3 to 905.96μg/m3. The MVOC molecular markers of the plant were identified to be carbon disulfide, dimethyl sulfide (DMS) carbonyl suifide, and aromatic compounds, such as styrene, benzene, toluene, o-xylene, m/p-xylene and ethylbenzene.2. By analyzing the relationship between MVOC concentrations and its odor fingerprints, the optimal sensor of the E-nose for this study was found to be T70/2 sensor since it was of the highest sensitivity to the MVOC emitted from the municipal sewage treatment plant.3. The quantitative evaluation model between the concentrations of chemical composition and sensory odor fingerprints was preliminary established by characterizing the MVOC sensory fingerprints of each processing unit. Good correlation were showed for the models, of which the correlation coefficients(R2) between chemical composition and sensory odor were greater than 85%.4. A combination of PCA and DFA was used to study the sensory differences of each sampling sites and to identify the source of odor in ambient air near the plant. The odor sensory fingerprints of each sampling sites were identical except that of sludge concentration tank. The odorants in ambient air mainly came from biochemical reaction tank with the qualitative recognition rate of 86.4%-100%.5. Using the established quantitative model between key MVOC concentrations and sensory odors to predict the odor concentration and chemical concentration of ambient air. The deviations between predicted and measured concentrations ranged from 28.1% to 50.7%.