Automated Collection of Real-Time Alerts of Citizens as a Useful Tool to Continuously Monitor Malodorous Emissions

Development and application of high resolution mass spectrometry analytical method to study and identify the photoinduced transformation products of environmental pollutants

Terpenes are among the major causes of pleasant or unpleasant odors close to active or inactive landfills. We studied R-limonene and p-cymene environmental degradation products using the heterogeneous photocatalysis mediated by titanium dioxide to explore the odor pollution. The aim of the study was the development of mass spectrometry based methods both hyphenated with GC and HPLC to identify and characterize transformation products (TPs) derived from photodegradation of R-limonene and p-cymene. With the GC-MS method we identified three TPs for R-limonene and two for p-cymene comparing the obtained mass spectra with those in the NIST library. While with HPLC-MS method, thanks to the use of the high resolution of MS tool, we recognized four and five TPs for R-limonene and p-cymene respectively. No p-cymene was detected as R-limonene transformation product. The methods developed were then applied to real environmental samples coming from landfills active (Lan1) or inactive (Lan2 and Lan3) located in northern Italy. R-limonene was detected in the active landfill (Lan1 at the concentration of 2.35 μg/mL) together with one of its TPs and one TP derived from p-cymene. p-Cymene was detected in the other two inactive landfills (Lan2 and Lan3 concentrations 0.025 and 0.15 μg/mL, respectively) together with one of its TP and two TPs coming from R-limonene photodegradation. The finding of TPs together with R-limonene and p-cymene both in active and inactive landfills point out the attention on the reduction of these molecules in the environment to reduce pollution and human risks.

Application of Machine Learning for Fenceline Monitoring of Odor Classes and Concentrations at a Wastewater Treatment Plant

The development of low-cost sensors, the introduction of technical performance specifications, and increasingly effective machine learning algorithms for managing big data have led to a growing interest in the use of instrumental odor monitoring systems (IOMS) for odor measurements from industrial plants. The classification and quantification of odor concentration are the main goals of IOMS installed inside industrial plants in order to identify the most important odor sources and to assess whether the regulatory thresholds have been exceeded. This paper illustrates the use of two machine learning algorithms applied to the concurrent classification and quantification of odors. Random Forest was employed, which is a machine learning algorithm that thus far has not been used in the field of odor quantification and classification for complex industrial situations. Furthermore, the results were compared with commonly used algorithms in this field, such as artificial neural network (ANN), which was here employed in the form of a deep neural network. Both techniques were applied to the data collected from an IOMS installed for fenceline monitoring at a wastewater treatment plant. Cohen’s kappa and Normalized RMSE are used as specifical performance indicators for classification and regression: the indicators were calculated for the test dataset, and the results were compared with data in the literature obtained in contexts of similar complexity. A Cohen’s kappa of 97% was reached for the classification task, while the best Normalized RMSE, namely 4%, for the interval 20–2435 ouE/m³ was obtained with Random Forest.

Assessment of H2S and BTEX concentrations in ambient air using passive sampling method and the health risks

Wastewater treatment plants (WWTPs) may be a source of nuisance in neighbouring places due to hydrogen sulphide (H₂S) and BTEX (benzene, toluene, ethylbenzene, and xylenes) emissions. In this study, samples were collected from WWTP workplace ambient air and outdoor ambient air around one of the largest WWTPs in Istanbul with a capacity of 250,000 m³/day to evaluate the effects of H₂S and BTEX emissions. Samples were collected in three seasons for 15-day durations: winter (November 2015), spring (May 2015), and summer (August 2016). Average concentrations of H₂S and BTEX were determined as 1.1 and 56.2 µg/m³, respectively. Average concentrations BTEX components were 4.9, 20.7, 6.4, and 24.2 µg/m³, respectively. Health risk assessment for plant workers and local residents was performed for H₂S and BTEX inhalation exposure using the method by USEPA. Results show that H₂S and BTEX emissions do not have harmful effects on human health.

Impact of Odor Nuisance on Preferred Place of Residence

Context of the research: Research is increasingly carried out to take into account the social behavior of residents, the type of industry located in the area, and perceived preference for the place of residence. The quality of life in urban space is increasingly seen as a problem of cooperation between various stakeholders. These studies not only identify factors and sources of odor emissions, but also serve as the basis for creating systems to alert people living in areas adjacent to industrial areas or harmful and unpleasant industrial emissions. In recent years, environmental issues, particularly unpleasant sensory experiences, have been one of the most important acceptance criteria. Aim of the article: The aim of the study is to assess the impact of odor nuisance in the south-eastern part of Kraków (Płaszów) on the residents’ decision to leave their place of residence. In particular, the research goal was achieved to indicate which of the unpleasant odors may cause a change of residence, as well as to assess the degree of their impact on the decision to move, taking into account the social and demographic characteristics of residents. New in the article: The novelty of the work was the finding out of the residents’ opinions about the quality of life by accepting the place of residence, taking into account the aspect of odor nuisance. Previous studies on odor nuisance have focused on the emission of odors from individual plants. A novelty of this research is its implementation in an urban area, in which numerous industrial plants are located, with various odors emitted. Research methodology: To assess odor nuisance, a measuring tool developed in accordance with VDI 3883 guidelines was used, based on the latest research results on odor and noise nuisance. The questionnaire was developed based on German experience. Conclusions from the research: The data obtained as a result of the research allow us to state that specific smells are so burdensome that they may cause the necessity to leave the place of residence, because the respondents feel various unpleasant smells that have an adverse impact upon the quality of life that they perceive. A possible need for relocation of domiciles out of the current place of residence due to unpleasant smells would affect the perceptible, specific level of grief—the greater it is, the more attached the residents are to their current place of residence.