Determining the soil odor control area: A case study of an abandoned organophosphorus pesticide factory in China

Currently, soil odor-active substance screening and evaluation methods for contaminated sites are underdeveloped, with unclear treatment objectives and areas. Consequently, some sites suffer from odor issues during and even after remediation. This study focused on an organophosphorus pesticide factory site in Guangdong Province, China. It established a method of determining the odorant control area using a comprehensive approach combining instrumental and olfactory soil sample analyses. The main odor-active substances identified were ethylbenzene, phenol, m, p-xylene, styrene, toluene, and o-xylene, with odorant control values (the limit of odor-active substance contents) of 35.2, 28.1, 8.0, 11.3, 40.2 and 89.3 mg/kg respectively. Instrumental analysis of soil samples revealed 11 sampling points where the main odor-causing substances exceeded standard levels. Among the substances, ethylbenzene (1.48E+04 mg/kg) had the highest content, exceeding the limit up to 421-fold. Olfactory analysis indicated 14 sampling points with odor intensity surpassing the standard (OI > 2). Based on the instrumental analysis results and the odorant control value, the initial estimated odor control area (area with the risk of odor nuisance) was 5.64E+03 m2. Incorporating the olfactory analysis findings, the control area was adjusted by 1.25E+03 m2, leading to a final calculated soil odor control area of 6.89E+03 m2 for the study site. The comprehensive approach to analyzing soil samples for odor control can help evaluate the extent of soil odor pollution in contaminated sites and provide a scientific basis for effectively removing and managing odor-causing substances in soil.

Combined assessment of health hazard and odour impact of soils at a contaminated site: a case study on a defunct pharmaceuticals factory in China

Surveys and assessments of contaminated sites primarily focus on hazardous pollutants in the soil with less attention paid to odorants. This makes the management of contaminated sites difficult. In this study, hazardous and odorous pollutants in the soil were assessed for a large site that was previously used for production of pharmaceuticals to determine the degree and characteristics of soil contamination at pharmaceutical production sites, for undertaking rational remediation measures. The main hazardous pollutants at the study site were triethylamine, n-butyric acid, benzo(a)pyrene (BaP), N-nitrosodimethylamine (NDMA), dibenzo(a,h)anthracene (DBA), total petroleum hydrocarbons (C10-C40) (TPH), and 1,2-dichloroethane; TEA, BA, and isovaleric acid (IC) were the main odorants. As the type and distribution of hazardous and odorous pollutants differ, it is necessary to separately assess the impact of these pollutants at a contaminated site. Soils in the surface layer pose significant non-carcinogenic (HI = 68.30) and carcinogenic risks (RT = 3.56E-5), whereas those in the lower layer only pose non-carcinogenic risks (HI > 7.43). Odorants were found at considerable concentrations both in the surface and lower layers, with the maximum concentrations being 29,309.91 and 41.27, respectively. The findings of this study should improve our understanding of soil contamination at former pharmaceutical production sites and should inform the assessment of the risks posed by contaminated sites, with problems associated with odour, and possible remediation strategies.

Research on air pollutants and odour emissions from paving hot-mix asphalt with end-of-life tyre rubber

This article discusses different types of pollution from the paving process and the influence of using hot mix asphalt without and including end-of-life tyre rubber. This new composition type is one of the possible solutions to reduce the amount of used transport tyres and a new way to use less valuable raw materials. The research carried out involved analyzers applied under conditions of a mobile laboratory and handheld particle counters. Odour samples were taken using a vacuum chamber in Tedlar containers, and the level of odours was analyzed adopting the olfactometric method. Exposure to gaseous carbon, nitrogen and sulphur oxides and particulate matter up to 10 µm, fractions from 0.3 µm to 10 µm, as well as the odours emitted that cover the soil surface with the hot-mix asphalt-rubber mixture was examined. The average decrease in pollution using the asphalt-rubber mixture is about 3.8-4 % of nitrogen oxides, 10 % of particulate matter of 1.5-10, and an increase is approximately 9 % for particulate matter of 0.8-1 µm and 15 % for sulphur dioxide. The level of odour of compacted asphalt is around 2.8times lower than that in the case of level asphalt.

Implementation of an electronic nose for real -time identification of odour emission peaks at a wastewater treatment plant

This paper proposes a novel approach for the real-time monitoring of odour emissions from a WasteWater Treatment Plant (WWTP) using an Instrumental Odour Monitoring System (IOMS). The plant is characterized by unpredictable odour peaks at its arrival tank (AT), generating nuisance and complaints in the population living nearby the plant. Odour peaks are most likely due to the conferment of non-identified and malodorous wastewaters coming from various industrial activities. Due to the high variability of sources collecting their wastewaters to the WWTP, a new methodology to train the IOMS, based on the use of a one-class classifier (OCC), has been exploited. The OCC enables to detect deviations from a "Normal Operating Region" (NOR), defined as to include odour concentrations levels unlikely to cause nuisance in the citizenship. Such deviations from the NOR thus should be representative of the odour peaks. The results obtained prove that the IOMS is able to detect real-time alterations of odour emissions from the AT with an accuracy on independent validation data of about 90% (CI95% 55-100%). This ability of detecting anomalous conditions at the AT of the WWTP allowed the targeted withdrawal of liquid and gas samples in correspondence of the odour peaks, then subjected to further analyses that in turn enabled to investigate their origin and take proper counteractions to mitigate the WWTP odour impact.

Application of Field Olfactometry to Monitor the Odour Impact of a Municipal Sewage System

Odorant emissions are associated with, among other things, wastewater transport in sewer networks; they contribute to air pollution and result in complaints from residents living close to emission sources. The critical location in terms of the formation of unpleasant odour compounds is the pressure line that connects the pumping station and the expansion well; this is where they are released into the atmosphere. This paper presents comprehensive results of olfactometric and chromatographic tests in the Polish city of Białystok using portable devices that allow for multiple determinations and instant results. The study attempts to investigate the relationship between odour and odorant concentrations and check the suitability of field olfactometry as a tool for the ongoing monitoring of the emission of noxious odours and for verifying complaints submitted by residents. Statistical analysis shows a very high correlation coefficient between cod and the concentrations of individual odorants, ranging from 0.82 to 0.91. This olfactometric research, mainly conducted in situ, can be an appropriate method for the ad hoc monitoring of processes in sewage networks. This method allows the detection of unwanted emissions of odours at individual points in the network in concentrations that are not detected by standard sensors but that nevertheless cause odour nuisances, complaints, and social conflict. The research results provide evidence in favour of the energetic usage of wastewater, which is in line with circular economy conception, since odour nuisance is one of its indicators.

A Heuristic Method for Modeling Odor Emissions from Open Roof Rectangular Tanks

This paper presents heuristic equations for estimating odor emissions from open-roof rectangular tanks as a function of the tank orientation, wind direction, wind speed and distance of the emitting surface from the tank top. These types of equations are important because they may help to improve emission calculations to avoid overestimations, which are damaging to the plant owner, and underestimations, which are negative for the population around the plant. Odor emissions were determined for four tanks with the same area, different shape factors and two different orientations and then used as inputs for a dispersion model in order to calculate separation distances and evaluate their differences. The results show that different separation distances were obtained depending on the tank orientation, shape factor and level of filling. Future field applications to verify and improve the proposed equations are desirable. If the effect of the tank orientation on odor emission is proven, the design of future industrial plants containing open-roof rectangular tanks should consider the results of detailed wind data analysis.

Reduction in VOC emissions by intermittent aeration in bioreactor landfills with gas-water joint regulation

Landfill mining and reclamation is a new strategy for addressing the lack of space available for new landfills and realizing the sustainable development of landfills. A gas-water joint bioreactor landfill is regulated by injecting water and/or recirculating leachate, and a blasting aeration system to optimize waste stabilization. In this study, four landfill reactors were constructed to investigate the effects of ventilation methods, including continuous (20 h d^-1) and intermittent aeration (4 h d^-1 in continuous or 2-h aeration per 12 h, twice a day), on the degradation of organic matter and volatile organic compound (VOC) emissions in comparison with traditional landfills. A total of 62 VOCs were detected in the landfill reactors. Among them, halogenated compounds had the highest abundance (39.8-65.4 %), followed by oxygenated compounds, alkanes and alkenes, and aromatic compounds. Both intermittent and continuous aeration could accelerate the degradation of landfilled waste and increase the volatilization rate of VOCs. Compared with intermittent aeration, the degradation of landfilled waste was more quickly in the landfill reactor with continuous aeration. However, intermittent aeration could create anaerobic-anoxic-aerobic conditions, which were conducive to the growth and metabolism of anaerobic and aerobic microorganisms in landfills and thereby reduced more than 63.4 % of total VOC emissions from the landfill reactor with continuous aeration. Moreover, intermittent aeration could reduce the ventilation rate and decrease the cost of aeration by 80 % relative to continuous aeration. Firmicutes, Bacteroidetes, Proteobacteria and Tenericutes predominated in the landfill reactors. The environmental variables including organic matter and VOCs concentrations had significant influences on microbial community structure in the landfilled waste. These findings indicated that intermittent aeration was an effective way to accelerate the stabilization of landfilled waste and reduce the cost and environmental risks in bioreactor landfills with gas-water joint regulation.

A review of environmental odor quantification and qualification methods: The question of objectivity in sensory analysis

For several years, various issues have up surged linked to odor nuisances with impacts on health and economic concerns. As awareness grew, recent development in instrumental techniques and sensorial analysis have emerged offering efficient and complementary approaches regarding environmental odor monitoring and control. While chemical analysis faces several obstacles, the sensory approach can help overcome them. Therefore, this latter may be considered as subjective, putting the reliability of the studies at risk. This paper is a review of the most commonly sensory methodology used for quantitative and qualitative environmental assessment of odor intensity (OI), odor concentration (OC), odor nature (ON) and hedonic tone (HT). For each of these odor dimensions, the assessment techniques are presented and compared: panel characteristics are discussed; laboratory and field studies are considered and the objectivity of the results is debated. For odor quantification, the use of a reference scale for OI assessment offers less subjectivity than other techniques but at the expense of ease-of-use. For OC assessment, the use of dynamic olfactometry was shown to be the least biased. For odor qualification, the ON description was less subjective when a reference-based lexicon was used but at the expense of simplicity, cost, and lesser panel-training requirements. Only when assessing HT was subjectivity an accepted feature because it reflects the impacted communities' acceptance of odorous emissions. For all discussed dimensions, field studies were shown to be the least biased due to the absence of air sampling, except for OC, where the dispersion modeling approach also showed great potential. In conclusion, this paper offers the reader a guide for environmental odor sensory analysis with the capacity to choose among different methods depending on the study nature, expectations, and capacities.

Objective odor analysis of incidentally emitted compounds using the Langage des Nez® method: application to the industrial zone of Le Havre

Environmental odor studies are usually done using two approaches: nuisance impact assessment and source identification. The latter may be done using chemical analysis or sensory analysis. While sensory analyses offer many advantages, they also face the main obstacle: odor nature description still uses conventional methods based on subjective evocations as odor descriptors. This makes the sensory method ineffective especially when the expected outcome is the source identification in the context of an industrial accident. This work wants to fulfill this gap proposing to build an objective database including the odor nature description of selected potentially emitted compounds using a promising approach: the Langage des Nez® (LdN). Using definite odorous compounds as odor referents, this work provides the odor nature description of 44 compounds, reported as potential incidentally released chemical compounds in the industrial zone of Le Havre. The city of Le Havre, France, was chosen as a model due to a history of odorous emissions of industrial origins. A trained panel described the odor of each compound using up to three referents of the LdN referents collection and attributed a score to each referent. A data analysis method was developed based on the frequency of citation of the referents and the attributed scores allowing the categorization of each compound in three types of consensus categories. The data analysis results showed that around 80% of compounds were described with a good consensus, showing the LdN as a well-adapted lexicon. This study does not point to any correlation between the chemical structures of the compounds of interest and their relative referents. When compared to conventional methods, LdN revealed a more objective and precise approach. The proposed experimental method and the results provided in this work offer the first insight for time-efficient approaches to objectively describe environmental odors, especially potentially emitted odors during incidents. This work may be supplemented by abatement and mixture effect investigations for a complete understanding of odor dispersion.

Odour impact assessment by considering short-term ambient concentrations: A multi-model and two-site comparison

Short-term events are one of the specific aspects that differentiate odour nuisance problems from conventional air quality pollutants. Atmospheric dispersion modelling has been considered the gold standard to realise odour impact assessments and to calculate separation distances. Most of these models provide predictions of concentrations of a pollutant in ambient air on an hourly basis. Even when the hourly mean odour concentration is lower than the perception threshold, concentration peaks above the threshold may occur during this period. The constant peak-to-mean factor is nowadays the most widespread method for evaluating short-term concentrations from the long-term ones. Different approaches have been proposed in the scientific literature to consider non-constant peak-to-mean factors. Two prominent approaches to do so are the i) variable peak-to-mean factor which considers the distance from the source and atmospheric stability and the ii) concentration-variance transport. In this sense, the aim of this work is to compare the results of three different freely available dispersion models (namely, CALPUFF, LAPMOD and GRAL), which implement three distinct ways to evaluate the short-term concentration values. Two sites, one in Austria and the other in Italy, were selected for the investigation. Dispersion model results were compared and discussed both in terms of long-term (hourly) concentrations and short-term. An important outcome of this work is that the dispersion models provided more equivalent results for hourly mean concentrations, in particular in the far-field. On the contrary, the method to evaluate short-term concentrations can deliver disparate results, thereby revealing a potential risk of poor assessment conclusions. The utilistion of a multiangle methodological approach (dispersion models, study site locations, algorithms to incorporate short-term concentrations) allowed providing useful information for future studies and policymaking in this field. Accordingly, our findings call for awareness on how the use of a particular dispersion model and its sub-hourly peak calculation method can affect odour impact assessment conclusions and compliance demonstrations.

Odor Annoyance Assessment by Using Logistic Regression on an Example of the Municipal Sector

Around the sewage treatment plant, in the area affected by a large number of complaints about odor annoyance, field measurements of odor properties and questionnaires were carried out. It was confirmed that the inhabitants of the zone closest to the plant are most exposed to the smell, the most intense smell comes from the sludge dryer building, and smells from primary settling tanks and sediment plots are perceived as unpleasant. The analysis of surveys confirmed the problem of odor nuisance, especially in the immediate vicinity, where over 50% of respondents considered odor annoyance as extreme. A division of respondents was introduced into those experiencing severe nuisance and those for whom the smell was not annoying. Then, to relate the probability of occurrence of odor nuisance with a group of independent variables, logistic regression was used to describe the impact of independent variables on the dichotomous dependent variable. It has been shown that the likelihood of experiencing odor nuisance increases with the increase in the intensity of current odors, the parallel noise, and in people who focus on the existing smell, and decreases with increasing satisfaction with their health and in the case of regularly occurring odor.

Fecal Malodor Detection Using Low-Cost Electrochemical Sensors

Technology innovation in sanitation is needed for the 4.2 billion people worldwide, lacking safely managed sanitation services. A major requirement for the adoption of these technologies is the management of malodor around toilet and treatment systems. There is an unmet need for a low-cost instrumented technology for detecting the onset of sanitation malodor and triggering corrective actions. This study combines sensory data with low-cost gas sensor data on malodor emanating from feces. The response of 10 commercial electrochemical gas sensors was collected alongside olfactometric measurements. Odor from fecal specimens at different relevant dilution as well as specimens with pleasant odors as a control were evaluated for a total of 64 responses. Several of the sensors responded positively to the fecal odor, with the formaldehyde, hydrogen sulfide, and ammonia sensors featuring the highest signal to noise ratio. A positive trend was observed between the sensors' responses and the concentration of the odorant and with odor intensity, but no clear correspondence with dilution to threshold (D/T) values was found. Selected sensors were responsive both above and below the intensity values used as the cutoff for offensive odor, suggesting the possibility of using those sensors to differentiate odor offensiveness based just on the magnitude of their response. The specificity of the sensors suggested that discrimination between the selected non-fecal and fecal odors was possible. This study demonstrates that some of the evaluated sensors could be used to assemble a low-cost malodor warning system.

Prediction of odor complaints at a large composite reservoir in a highly urbanized area: A machine learning approach

Odorous compound emissions and odor complaints from the public are rising concerns for agricultural, industrial, and water resource recovery facilities (WRRFs) near urban areas. Many facilities are deploying sensors that measure malodorous compounds and other factors related to odor creation and dispersion. Focusing on the Metropolitan Water Reclamation District of Greater Chicago's (MWRDGCs) Thornton Composite Reservoir (7.9 billion gallon capacity), we used meteorological, operational, and H2S sensor data to train a 3-day advance-warning predictor of local odor complaints, so as to implement targeted odor prevention measures. Using a machine learning approach, we bypassed difficulties in modeling both physical dispersion and human perception of odors. Utilizing random forest algorithms with varied settings and input attributes, we find that a small network of H2S sensors, meteorological data, and operational data are able to predict odor complaints three days in advance with greater than 60% accuracy and less than 25% false-positive rates, exceeding MWRDGC's standards required for full-scale deployment. PRACTITIONER POINTS: A random forest algorithm trained on H₂ S, weather, and operations data successfully predicted odor complaints surrounding a large composite reservoir. Thirty-two data attribute combinations were tested. It was found that H₂ S sensor data alone are insufficient for predicting odor complaints. The best predictor was a Random Forest Classifier trained on weather, operational, and H₂ S readings from the reservoir corner locations. This study demonstrates odor complaint prediction capability utilizing a limited set of data sources and open-source machine learning techniques. Given a small network of H₂ S sensors and organized data management, WRRFs and similar facilities can conduct advance-warning odor complaint prediction.

Olfactory Characterization of Typical Odorous Pollutants Part I: Relationship Between the Hedonic Tone and Odor Concentration

The hedonic tone is a suitable evaluation index which can truly reflect the psychological impact of an odor. To find out the relationship between the odor concentration (OC) and hedonic tone (H), dimethyl disulfide, limonene and butyl acetate were presented as typical odorants with different characters. A panel of 16 persons was engaged to rate the hedonic tone of a series sample with various concentrations according to the nine-point scale. The relationship between the hedonic tone and OC was established based on a multivariate logistic regression analysis. The research results demonstrated that the smell of dimethyl disulfide is unpleasant at various concentration levels, and its perceived unpleasantness is increased with OC, and at the critical point (H = −0.5), the odor index of dimethyl disulfide is 0.5 (OC = 3 OUE·m−3). For limonene, its smell is pleasant when the odor index is between 1.4 and 3.3 (OC = 25~1995 OUE·m−3). For butyl acetate, the average results showed an unpleasant character with the corresponding odor index of 1.87 (OC = 74 OUE·m−3). Each odorant has a unique hedonic behavior curve from which the annoyance potential of different odorants can be clearly discriminated, with the order of dimethyl disulfide > butyl acetate > limonene. The regression equations showed a quadratic nonlinear function between the hedonic tone and OC.

Exposure-complaint relationships of various environmental odor sources in Styria, Austria

In the planning and authorization process of industrial plants or agricultural buildings, it needs to be ensured that odor emissions do not annoy nearby residents in an unacceptable way. Previous studies have shown that odor-hour frequency is an important predictor for odor annoyance. However, odor-hour frequencies can be assessed for day and night separately. The present study relates complaint rates with different odor types and different metrics of frequency calculated via a dispersion model. Binary logistic regression analyses show that odor type and frequency of odor-hours are important predictors for complaints, while type of residential area does not increase the predictive value of the model. The combination of calculated frequency of day time odor-hours and type of odor explains complaint rates best. It is recommended to keep odor emissions as low as possible, especially for highly annoying odor types.

A case study of odour nuisance evaluation in the context of integrated urban planning

Odour nuisance poses a serious problem in many urban areas, yet its evaluation and mitigation is often omitted in the urban planning process. By identifying its range and spatio-temporal variations, it could be taken into consideration by planners in urban development strategies and land use decisions. The aim of the study was to present the application of odour evaluation techniques in the improvement of the quality of life in the built environment. The problem of odours is discussed in regard to human health, social aspects and current practices in the management of spatial development. The application possibilities of field olfactometry are demonstrated based on a case study of a municipal landfill which is a major source of odour nuisance for the adjacent areas. The results of odour nuisance measurements were field olfactometry combined with topographical and meteorological data. Using dispersion modelling (non-steady-state Lagrangian Gaussian puff model CALPUFF with dedicated meteorological pre-processor CALMET) it was possible to calculate odour concentrations and to place the measured odour concentrations in a specific spatial context. The obtained results were juxtaposed with local development strategies and discussed in the context of environmental-based planning. We suggest that odour evaluation and dispersion modelling are valid tools in managing the dynamics of urban growth.