Wastewater treatment plants (WWTPs) are fundamental for water ecosystems conservation but when they are located in the proximity of residential areas may produce odour nuisance. One of the most common odours pollutants emitted in WWTPs is hydrogen sulphide (H2S) and release to the atmosphere (in waste-waterfalls, manholes), producing a strong unpleasant smell. In this work, field olfactometry and H2S measurement enabled to identify the main odour source, located in the inlet of the WWTP.
The maximum H2S concentration in this emission point measured was 15 ppm and odour concentration was D/T 60, enough high to produce odour nuisance despite they were produced in open atmosphere. By means of a thorough data analysis of the essential variables involved, such as wind speed, wind direction and the H2S concentrations in its role as the central pollutant, it could be shown via contrasting annual, monthly and daily patterns, that the probability to be affected for these residential areas is the highest in summer from 19:00 hours.
A. Luckerta, C. Lafitab*, D. Aguadoc, R. Garcíad, N. Franka, F. Andrésb
Competing interests: The author has declared that no competing interests exist.
Academic editor: Carlos N Díaz.
Content quality: This paper has been peer-reviewed by at least two reviewers. See the scientific committee here.
Citation: A. Luckert, C. Lafita*, D. Aguado, R. García, N. Frank, F. Andrés, Dispersion modelling as a tool for assessment and management of odour emissions from a wastewater treatment plant, 9th IWA Odour& VOC/Air Emission Conference, Bilbao, Spain, www.olores.org.
Copyright: 2021 Olores.org. Open Content Creative Commons license. It is allowed to download, reuse, reprint, modify, distribute, and/or copy articles in olores.org website, as long as the original authors and source are cited. No permission is required from the authors or the publishers.
ISBN: 978-84-09-37032-0
Keywords: Dispersion modelling, air quality, WWTP, odour, hydrogen sulphide, field olfactometry.
Video
Abstract
Wastewater treatment plants (WWTPs) are fundamental for water ecosystems conservation but when they are located in the proximity of residential areas may produce odour nuisance. One of the most common odours pollutants emitted in WWTPs is hydrogen sulphide (H2S) and release to the atmosphere (in waste-waterfalls, manholes), producing a strong unpleasant smell. In this work, field olfactometry and H2S measurement enabled to identify the main odour source, located in the inlet of the WWTP. The maximum H2S concentration in this emission point measured was 15 ppm and odour concentration was D/T 60, enough high to produce odour nuisance despite they were produce in open atmosphere. By means of a thorough data analysis of the essential variables involved, such as wind speed, wind direction and the H2S concentrations in its role as the central pollutant, it could be shown via contrasting annual, monthly and daily patterns, that the probability to be affected for these residential areas is the highest in summer from 19:00 hours. Dispersion modelling also enabled to determine the maximum acceptable H2S concentration to avoid odour annoyance in the nearby dwellings which was 10 ppm in the inlet of the WWTP. Upgrades of the WWTP to avoid odour nuisance were evaluated using the dispersion modelling resulting that the modification of inlet pipe was the most adequate modification for odour reduction.
1. Introduction
The anaerobic decomposition of organic sulphur or the reduction of other sulphur compounds present in wastewater that take place in sewers are the cause of the release of hydrogen sulphide (H2S) in sewers. The emission of this compound have historically generated nuisance odours in the surrounding areas of wastewater treatment plants (WWTPs) (Stuetz et al., 2001), which is why public complaints of nearby residents become more frequent (Dinçer et al., 2020). Indeed, the sulphur reduction to H 2S usually cause about 80 – 90 % of the unpleasant environmental odour, creating annoyances from WWTPs (Bylinski et al., 2019; Debrieu et al., 2004) that affects 13 – 20 % of the population in Europe, and reaching values as high as 25 % in cities like Madrid or Barcelona (Lebrero et al., 2011).
Even though odours have always represented a social problem, the public concern over the impact on health have been raised (Conti et al., 2020). Some of these health problems, such as stress, anxiety or irrational attitude, were reported by Brennan (1993) and Gostelow et al. (2001). Additionally, odours from WWTPs may cause poor image of facility manager (Gostelow et al., 2000) and cause effect on human activities (Shusterman, 1992).
Dispersion modelling uses mathematical formulations to quantify the atmospheric processes that disperse a pollutant emitted by a source. Gaussian dispersion models use realistic description of dispersion assuming a concentration profile across the plume to follow Gaussian probability curve in steady-state conditions. For the calculation of plume extent, and the subseq uent evaluation of odour assessment, flow and odour concentration are considered (Capelli et al., 2013; Conti et al., 2020).
In this work, air quality measurements of H2S emissions from a WWTP located inside a touristic town in the seaside of the Spanish east coast were conducted during 220 days. Odour complaints from neighbourhood were recorded and a measuring campaign, H2S concentration and field olfactometry, was conducted and used in modelling of odour dispersion for odour assessment and decision making.
2. Materials and methods
2.1. Description of the WWTP
The studied WWTP, which is located in the east coast of Spain at about 335 meters from sea, is serving 1,590 population equivalent and treats 287 m 3/d of domestic like wastewater. All treatment units (aeration reactor, secondary settler and sludge drying area) are open to the atmosphere and aeration is carried out by surface aerators. Sludge drying area basins total 11 x 5 meters per 7 units, diameter of aerated reactor is 22 meters and settle tank is 12 meters and the minimum distance to the dwellings is 14 meters.
2.2. Odour measurements
Odour measuring campaign was carried out in summer due to the increase of organic loads due to the increment in resident numbers owing to tourism and higher temperatures. Gas detector Dräger Polytron 7000 were used for the measurement of H2S concentration. The measurement range was from 1 to 100 ppm, with an accuracy of either ≤±3 % of ≤±5 ppm, whichever was the greater value. Measurements were made at the nodes of a 10x10 meters cells grid. The instruments recorded one measurement per minute that was saved in an external register.
Field olfactometry was carried out with Nasal Ranger® by two calibrated panellists. According to Walgraeve et al. (2015), the Nasal Ranger® generates a series of discrete solutions by mixing odorous air with odour-free air. It uses the breathing rate of the panellist to aspirate and mix the odorous air with odour-free air. The latter is generated by carbon filtration of the odorous air. The different dilution-to threshold (D/T) positions are 60, 30, 15, 7, 5 and 3. D/T is defined as the ratio of carbon-filtered to odorous airflow.
Field olfactometry samples were collected in the inlet, in the opposite side of inlet of the aeration reactor (close to perimetric wall), in the recirculation entrance into the aerated reactor, in the sludge drying area and in three points close to dwellings in front of WWTP perimetric wall during summer time in which higher odour concentrations were expected due to the increase in population and warmer weather.
2.3. Model description
In agreement with EPA and AERMIC (2019), the AERMOD modelling system (version 19191) is a steady-state Gaussian plume model that incorporates air dispersion based on planetary boundary layer turbulence structure and scaling concepts, including treatment of both surface and elevated sources, and both simple and complex terrain. The workflow includes pre-processor models preparing the terrain (AERMAP) and meteorological data inputs (AERMET and AERSURFACE), as well as possible downwash effects (BPIPPRM) caused by buildings close enough to the emission source.
In this study, a rectangular 6400-point receptor grid with cells of 2.5 m x 2.5 m size and a total edge length of 200 m was utilized. Since the maximum time-resolution of AERMOD is 1 hour, all gas and meteorological data with a higher temporal resolution were resampled to the target resolution. Concerning the gas data, taking the hourly maximum was the aggregation function of choice as the worst case scenario is the most relevant for the scope of this work. If the mean or median had been employed, the hourly H 2S concentrations would have remained entirely below perception threshold.
The regulatory default options encompass stack-tip downwash, elevated terrain effects, the processing routine for calm winds of 0 m/s, the missing data processing routine and no exponential decay. More specifically, no gas and particle deposition and no dry or wet depletion was necessary to include. Moreover, a flagpole height of 1.7m was employed for all receptor points of the modelling grid. This means that the results were computed for a height of an average person above ground. Owing to unstable atmospheric conditions at surface-level during summer time, this flagpole height is representative also for housings comprising up to two stories. Finally, rural dispersion was chosen as the target residential area lies around 300 m from the coast with relatively low building density and heights.
2.4. Meteorological and terrain data
The upper air sounding data were obtained from the Integrated Global Radiosonde Archive (NOAA, a) while the hourly surface data stem from the global Integrated Surface Dataset (NOAA, b). The latter data were complemented with other local surface weather stations from the Valencian AVAMET network. In particular, the closest surface weather station to the WWTP site is AVAMET weather station Dénia Platja de Pego, the second closest AVAMET weather station Oliva Poble along with the Windguru station Platja de Piles between Gandia and Oliva and the Windguru station Playa de l’Ahuir north of Gandia. All weather stations lie either directly at the coast or within 3 km from the seashore. Additionally, the cloud base height and cloud fraction data were retrieved from the Sentinel-5P TROPOMI Cloud 1-Orbit L2 data sets available at the NASA Earthdata website (NASA, 2019, 2020).
The land usage and surface classification data is based on the Copernicus European Land Cover project with CORINE Land Cover (CLC) Data Base (2018). The data are also accessible via the website Centro de Descargas del Centro Nacional de Información Geográfica (CNIG) (2018) provided by the Spanish government.
3. Results and discussion
3.1. Air quality measurements
The measured values of H2S enabled to identify the entrance to the WWTP as the main H2S emission source in the WWTP, in which H 2S concentrations were up to 15 ppm, being the 95th percentile of 3.1 ppm as it is shown in Fig 1. On-site measurements were made at different points within the WWTP following a 10 m grid, notwithstanding values >0 ppm were measured close to the entrance of recirculation, no other significant H2S concentrations were recorded.
Fig. 1.: Empirical cumulative distribution function of H2S concentration (in ppm) in the inlet of the WWTP.
The comparison of average daily pattern of WWTP inlet water flow and H 2S concentrations depicted in Fig 2 show certain relationship between both parameters. Despite this, Spearman correlation indicates a poor relation between both parameters with a value of 0.41, probably caused by instantaneous peaks registered during nights that do not enable the formation H2S in the sewerage due to the short time period into them before arriving to the WWTP. H2S hourly measurements also revealed two peaks of production, one before midday and the other about 22 hours, both associated to domestic routines.
Fig. 2.: Minute average water flow in the inlet of the WWTP and H 2S concentration measured during the first measuring campaign
3.2. Odour measurements results
Field olfactometry measurements (quantity of measurements with odour and odour concentrations) for all the sampling points are presented in Table 1. The number of measurements with odours were double in the entrance of the WWTP in comparison with other sampling points were odour was detected. In this point, average D/T of 13.2 was measurement (with maximum value of 60), which are D/T that can provoke annoyance. In the case of the sampling point ‘Dwelling 2’, the measured odours were associated to food or traffic and there were no considered in the study of annoyances caused by the WWTP. These results corroborated that the inlet of the WWTP was the main source of odours but the emitted odour was not perceived in the surrounding neighbourhood. Sludge drying area was odourless because the high sludge mineralization caused by the oversized of active sludge tank (47.5% utilization) that promotes elevate hourly retention time and low organic loads. In addition to this, during summer period, when high temperatures promote elevate odour emissions, sludge drying area is not used.
Table 1: Field olfactometry results obtained during the study in the inlet of the WWTP
|
Sampling point |
Percentage of measurements with odour, % |
Average D/T |
Maximum D/T |
Minimum D/T |
|
WWTP inlet |
33.3 |
13.2 |
60 |
≤3 |
|
Sludge recirculation |
14.3 |
1.9 |
15 |
≤3 |
|
Aerated reactor-wall References |
14.3 |
2.9 |
7 |
≤3 |
|
Sludge drying area |
0 |
≤3 |
≤3 |
≤3 |
|
Dwelling 1 |
0 |
≤3 |
≤3 |
≤3 |
|
Dwelling 2 |
10.7 |
2.2 |
3 |
≤3 |
|
Dwelling 3 |
0 |
≤3 |
≤3 |
≤3 |
3.3. Modelling results
AERMOD model was used to implement a study of the odour pollution distribution that may be originated in the surrounding living area due to the odour emitted in the activity of the WWTP.
Data analysis of the essential variables involved, such as wind speed, wind direction and the H2S concentrations revealed via contrasting annual, monthly and daily patterns, that the probability of the closest residential areas to be affected by was highest from June to August in the late afternoon (from 19:00).
The modelling results confirmed that the concentrations remain significantly below values hazardous to health at all places of interest, both for the WWTP staff and the local residents. The recommended 15-minute average exposure limit for H2S is 10 ppm, whereas the maxima from the model output around 2.5 m next to the emission source remained significantly below 1 ppm (H2S odour threshold concentration 0.47 ppb).
Comparing with the wind patterns with the on-site olfactometry measurements and model outputs, it could be confirmed that the wind direction was the deciding factor in the question whether or not an odour can be noticed at a specific place.
Simulations of the pollutant dispersion also enabled to assess the effectivity of the modifications made in the WWTP to avoid odour annoyances. The upgrades studied were the installation of a rotary drum screen and the increase of the perimetric wall height. Only the rotary drum screen reduces successfully the odour annoyances in the dwelling area.
Fig. 3.: Contour map with the results of the modelling of odour dispersion from inlet of the WWTP
4. Conclusions
The use of AERMOD dispersion model revealed important information about the odour emission source and the maximum concentration acceptable to avoid neighbourhood complaints which is a useful for decision-making to apply new management strategies. In the studied WWTP, the inlet concentration was the unique odour emission source, causing odour nuisance in the surroundings of the WWTP. Sludge drying area resulted odourless due to the high mineralization of sludge caused by oversized of activated sludge process.
5. References
AVAMET weather station Dénia Platja de Pego, .AVAMET weather station "Dénia Platja de Pego". URL: https://www.avamet.org/mx-fitxa.php?id=c30m063e10 (accessed on: 10/05/2021)
AVAMET weather station Oliva Poble, AVAMET weather station "Oliva pople". URL: https://www.avamet.org/mx-fitxa.php?id=c25m181e02 (accessed on: 10/05/2021)
Brennan, B. 1993. Odour nuisance. Water Waste Treat. 36, 30-33.
Bylinski, H., Barczak, R.J., Gebicki, J., Namiesnik, J. 2019. Monitoring of odours emitted from stabilized dewatered sludge subjected to aging using proton transfer reaction-mass spectrometry. Environ. Sci. Res. 26, 5500-5513.
Capelli, L., Sironi, S., Del Rosso, R., Guillot, J.M. 2013. Measuring odours in the environment vs dispersion modelling: A review. Atmos. Env., 79, 731-743.
Centro de Descargas del Centro Nacional de Información Geográfica (CNIG), 2018. CORINE2018 Land Cover - Spanish government access portal. URL: http://centrodedescargas.cnig.es/CentroDescargas/catalogo.do?Serie=SIOSE (accessed on: 10/05/2021)
Conti, C., Guarino, M., Bacenetti, J. 2020. Measurements techniques and models to assess odor annoyance: A review. Environ. Int., 134, 105261.
Copernicus European Land Cover project with CORINE Land Cover (CLC) Data Base, 2018. CORINE Land Cover (CLC) 2018 category nomenclature. URL: https://land.copernicus.eu/user-corner/technical-library/corine-land-cover-nomenclature-guidelines/html/ (accessed on: 10/05/2021)
Debrieu, C. 2004. Lutte contre les odeurs de l’assainament (Fight against sanitation odours). Document Technique, FNDAE, nº13, Ministère de l’Agriculture, de l’Alimentation, de la Pêche et des Affaires Rurales, France.
Dinçer, F., Dinçer, F.K., Sari, D., Ceylan, Ö., Ercan, Ö. 2020. Dispersion modelling and air quality measurements to evaluate the odour impact of a wastewater treatment plant in Izmir. Atmos. Pollut. Res., 11, 12, 2119-2125.
EPA and AERMIC, 2019. AERMOD model on EPA official webpage. URL: https://www.epa.gov/scram/air-quality-dispersion-modeling-preferred-and-recommended-models-aermod (accessed on: 10/05/2021)
Gostelow, P., Parsons, S.A. 2000. Sewage treatment works odour measurement. Wat. Sci. Tech. 41, 6, 33-40.
Gostelow, P., Parsons, S.A., Stuetz, M. 2001. Odour measurements for sewage treatment works. Water Res. 35, 579-597.
Lebrero, R., Bouchy, L., Stuetz, R., Muñoz, R. 2011. Odor assessment and management in wastewater treatment plants: a review. Crit. Rev. Env. Sci. Tec., 41 (10), 915-950.
NASA, 2019, 2020. Sentinel Satellite Cloud data. URL: https://disc.gsfc.nasa.gov/ (accessed on: 10/05/2021)
NOAA, N., a. Integrated Global Radiosonde Archive (IGRA) - Upper air data base. URL: https://www.ncdc.noaa.gov/data-access/weather-balloon/integrated-global-radiosonde-archive (accessed on: 10/05/2021)
NOAA, N., b. Integrated Surface Database (ISD) - Hourly surface weather data. URL: https://www.ncdc.noaa.gov/isd (accessed on: 10/05/2021)
Shusterman, D. 1992. A critical review: the health significance of environmental odour pollution. Arch. Environ. Health., 47, 76-87.
Stuetz, R.M., Gostelow, P., Burgess, J.E. 2001. Odour perception. R. Stuetz and F.B. Frenchen (eds.), Odours in wastewater treatment: measuring, modelling and control. IWA Publishing, Chapter 1, pp. 1-13.
Walgraeve, C., van Huffel, K., Bruneel, J., van Langenhove, H. 2015. Evaluation of the performance of field olfactometers by selected ion flow tube mass spectrometry. Biosyst. Eng., 137, 84-94.
Windguru station Platja de Piles, . Windguru station - Dunes Kite Piles Club / Platja de Piles, DKPiles Meteo. URL: https://www.windguru.cz/station/51 (accessed on: 10/05/2021)
Windguru station Playa de l’Ahuir, . Windguru station - Playa de l’Ahuir, Gandia Surf. URL: https://www.windguru.cz/station/1064 (accessed on: 10/05/2021)