Do odour impact criteria of different jurisdictions ensure analogous separation distances for an equivalent level of protection?

Determination of separation distances integrating complaints records analysis and odour dispersion modelling in the Czech Republic

Dispersion models have proven to assist the development of regulation strategies for the mitigation of odour impact. Nevertheless, the complexity derived from the definition of the sources and the replication of the subjective perception of chemical mixtures raise the question whether it is enough to perform an assessment based exclusively on the predictions of models. Furthermore, there is still an ongoing debate on the most appropriate methodology to reproduce sub-hourly peak concentrations. With this in mind, the active participation of the affected community could help to identify better the processes that cause odour annoyance and tune the results obtained with the dispersion models. Recently, the AirQ application has been implemented in the Czech Republic to allow citizens to report odour episodes to the entity in charge. Hence, the goal of this work was to integrate the information collected from the complainants with the simulations from the Gaussian model SYMOS, and the Lagrangian models AUSTAL and GRAL. The evaluation was performed in three sites with different emission characteristics and terrain: a pig farm, a pet food producer, and an edible oil industry. The outcome of this approach allowed to evaluate the suitability of each model depending the characteristics of the source, compare the use of a constant peak-to-mean factor of 4 against the Concentration Variance Model, and determine the applicability of certain odour impact criteria (OIC) for establishing separation distances.

Odor emissions: A public health concern for health risk perception

The olfactory nuisance, due to the emissions of active molecules, is mainly associated with unproperly managed waste disposal and animal farming. Volatile compounds e.g., aromatics, organic and inorganic sulfide compounds, as well as nitrogen and halogenated compounds are the major contributor to odor pollution generated by waste management plants; the most important source of atmospheric ammonia is produced by livestock farming. Although an odorous compound may represent a nuisance rather than a health risk, long-term exposure to a mixture of volatile compounds may represent a risk for different diseases, including asthma, atopic dermatitis, and neurologic damage. Workers and communities living close to odor-producing facilities result directly exposed to irritant air pollutants through inhalation and for this reason the cumulative health risk assessment is recommended. Health effects are related to the concentration and exposure duration to the odorants, as well as to their irritant potency and/or biotransformation in hazardous metabolites. The health effects of a single chemical are well known, while the interactions between molecules with different functional groups have still to be extensively studied. Odor emissions are often due to airborne pollutants at levels below the established toxicity thresholds. The relationship between odor and toxicity does not always occurs but depends on the specific kind of pollutant involved. Indeed, some toxic agents does not induce odor nuisance while untoxic agents do. Accordingly, the relationship between toxicity and odor nuisance should be always analyzed in detail evaluating on the characteristics of the airborne mixture and the type of the source involved.

Environmental Odour

Environmental odour is perceived as a major nuisance by the rural and urban population [...]

Identification of origins and influencing factors of environmental odor episodes using trajectory and proximity analyses

It is challenging for the governmental agencies to provide an instant response and to systematically analyze the huge number of odor complaints which are received frequently by them. This study aimed to establish a data analysis framework featuring trajectory and proximity analyses to confirm odor origins, assess impact areas, and identify determinants and mechanisms of odor episodes based on odor reports. The investigation used 273 odor complaints reported in northern Collierville, Tennessee, between January 1st, 2019 and December 15th, 2020. The location of each complaint was geocoded in Google Map, and the backward wind trajectories were calculated using the web-based Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The nearby Eplex Landfill and Collierville Northwest Sewage Treatment Plant were targeted for the analyses. Odor impacts were evaluated with temporal and spatial characteristics of reported odor episodes. Logistic models were performed to identify weather parameters that significantly influenced odor occurrence. The field inspections indicated two periods targeting different sources. Period 1: from January 1st, 2019 to October 31st, 2020, the landfill appeared as the major source; Period 2: from November 1st, 2020 to December 15th, 2020, the sewage plant emerged as the major source. In Period 1, 65% of the complaints had wind transporting from the landfill, and 88% occurred at residences within 500 m of the landfill. In Period 2, 33% of the complaints had wind that blew from the sewage plant and 85% occurred at residences within 1000 m from the sewage plant. The likelihood of an odor episode day was significantly associated with wind speed [Odds Ratio (OR) = 0.66, 95% Confidence Interval (CI): 0.56-0.77], temperature (OR = 0.97, 95% CI: 0.95-0.98), and rainfall (OR = 1.02, 95% CI: 1.00-1.04). The odor issue in Collierville reflected poor zoning between the odor sources and residential areas. Separation distances of 500 m and 1000 m from the landfill and sewage facilities, respectively, are suggested to prevent odor issues. The proposed data analysis framework can be adopted by governmental agencies for fast responses to odor complaints, odor assessment, and environmental odor management.

Increased ozone pollution alongside reduced nitrogen dioxide concentrations during Vienna's first COVID-19 lockdown: Significance for air quality management

BACKGROUND

Lockdowns amid the COVID-19 pandemic have offered a real-world opportunity to better understand air quality responses to previously unseen anthropogenic emission reductions.

METHODS AND MAIN OBJECTIVE

This work examines the impact of Vienna's first lockdown on ground-level concentrations of nitrogen dioxide (NO₂), ozone (O₃) and total oxidant (O_x). The analysis runs over January to September 2020 and considers business as usual scenarios created with machine learning models to provide a baseline for robustly diagnosing lockdown-related air quality changes. Models were also developed to normalise the air pollutant time series, enabling facilitated intervention assessment.

CORE FINDINGS

NO₂ concentrations were on average -20.1% [13.7-30.4%] lower during the lockdown. However, this benefit was offset by amplified O₃ pollution of +8.5% [3.7-11.0%] in the same period. The consistency in the direction of change indicates that the NO₂ reductions and O₃ increases were ubiquitous over Vienna. O_x concentrations increased slightly by +4.3% [1.8-6.4%], suggesting that a significant part of the drops in NO₂ was compensated by gains in O₃. Accordingly, 82% of lockdown days with lowered NO₂ were accompanied by 81% of days with amplified O₃. The recovery shapes of the pollutant concentrations were depicted and discussed. The business as usual-related outcomes were broadly consistent with the patterns outlined by the normalised time series. These findings allowed to argue further that the detected changes in air quality were of anthropogenic and not of meteorological reason. Pollutant changes on the machine learning baseline revealed that the impact of the lockdown on urban air quality were lower than the raw measurements show. Besides, measured traffic drops in major Austrian roads were more significant for light-duty than for heavy-duty vehicles. It was also noted that the use of mobility reports based on cell phone movement as activity data can overestimate the reduction of emissions for the road transport sector, particularly for heavy-duty vehicles. As heavy-duty vehicles can make up a large fraction of the fleet emissions of nitrogen oxides, the change in the volume of these vehicles on the roads may be the main driver to explain the change in NO₂ concentrations.

INTERPRETATION AND IMPLICATIONS

A probable future with emissions of volatile organic compounds (VOCs) dropping slower than emissions of nitrogen oxides could risk worsened urban O₃ pollution under a VOC-limited photochemical regime. More holistic policies will be needed to achieve improved air quality levels across different regions and criteria pollutants.

Environmental Odour Nuisance Assessment in Urbanized Area: Analysis and Comparison of Different and Integrated Approaches

Prolonged exposure to odour emissions causes annoyance which leads to nuisance and consequently to complaints. Different methodologies exist in the literature to evaluate odour impacts, but not all are suitable to assess environmental odour nuisance. Information about their applicability criteria and comparison, is scarce and referred to short time analysis. The research presents and discusses the application of different methods to characterize and assess odour nuisance around an industrial plant localized in a sensitive area. Experimental activities are carried out through a long-time analysis programme. Field inspections and predictive methods are investigated and compared. A modification of the traditional dispersion modelling approach is proposed in order to adapt its application for the prediction of the odour nuisance. The offensiveness and location factors are identified as key parameters in the quantification of the perceived nuisance. The integrated dispersion modelling multi-level approach is highlighted as the most suitable for defining the plant strategies. The paper provides useful information to characterize environmental odour problems and identify appropriate solutions for an effective management of odorous sources, with the aim of reducing complaints, restoring the proper relationship between odorous plants and the surrounding communities and increasing the overall quality of the environment.

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.

Determination of ammonia and hydrogen sulfide emissions from a commercial dairy farm with an exercise yard and the health-related impact for residents

Airborne emissions from concentrated animal feeding operations (CAFOs) have the potential to pose a risk to human health and the environment. Here, we present an assessment of the emission, dispersion, and health-related impact of ammonia and hydrogen sulfide emitted from a 300-head, full-scale dairy farm with an exercise yard in Beijing, China. By monitoring the referred gas emissions with a dynamic flux chamber for seven consecutive days, we examined their emission rates. An annual hourly emission time series was constructed on the basis of the measured emission rates and a release modification model. The health risk of ammonia and hydrogen sulfide emissions around the dairy farm was then determined using atmospheric dispersion modeling and exposure risk assessment. The body mass-related mean emission factors of ammonia and hydrogen sulfide were 2.13 kg a^-1 AU^-1 and 24.9 g a^-1 AU^-1, respectively (one animal unit (AU) is equivalent to 500 kg body mass). A log-normal distribution fitted well to ammonia emission rates. Contour lines of predicted hourly mean concentrations of ammonia and hydrogen sulfide were mainly driven by the meteorological conditions. The concentrations of ammonia and hydrogen sulfide at the fence line were below 10 μg m^-3 and 0.04 μg m^-3, respectively, and were 2-3 orders of magnitude lower than the current Chinese air quality standards for such pollutants. Moreover, the cumulative non-carcinogenic risks (HI) of ammonia and hydrogen sulfide were 4 orders of magnitudes lower than the acceptable risk levels (HI = 1). Considering a health risk criterion of 1E-4, the maximum distance from the farm fence line to meet this criterion was nearly 1000 m towards north-northeast. The encompassed area of the contour lines of the ambient concentration of ammonia is much larger than that of hydrogen sulfide. However, the contour lines of the ammonia health risk are analogous to those of hydrogen sulfide. In general, the ammonia and hydrogen sulfide emissions from the dairy farm are unlikely to cause any health risks for the population living in the neighborhood.

Analysis of Separation Distances under Varying Odour Emission Rates and Meteorology: A WWTP Case Study

A wide variability of odour impact criteria is found around the world. The objective of this research work was to evaluate the influence of the uncertainties related to some individual stages of odour impact assessment in the application of regulatory criteria. The evaluation procedure was established by following the guidelines of the Northern Italian regions. A wastewater treatment plant located in Northern Italy was considered as a case study. Odour dispersion modelling was carried out with the CALPUFF model. The study focused on two phases of the assessment. The first phase was the selection of the meteorology datasets. For low odour concentration thresholds (CT = 1 OU m−3), the results showed that two different years (2018 and 2019) provided similar patterns of the separation distances. The difference between the two years tended to increase by increasing the value of the concentration threshold (CT = 3 OU m−3 and CT = 5 OU m−3). The second phase of the assessment was the selection of the open field correction method for wind velocity used in the calculation of odour emission rates (OERs). Three different relationships were considered: the power law, the logarithmic law and the Deaves–Harris (D–H) law. The results showed that OERs and separation distances varied depending on the selected method. Taking the power law as the reference, the average variability of the separation distances was between −7% (D–H law) and +10% (logarithmic law). Higher variability (up to 25%) was found for single transport distances. The present study provides knowledge towards a better alignment of the concept of the odour impact criteria.