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Ausbreitungsmodelle liefern in der Regel Stundenwerte von Immissionskonzentrationen. Für die Geruchswahrnehmung sind jedoch Spitzen im Zeitbereich eines menschlichen Atemzuges von wenigen Sekunden entscheidend. In den letzten Jahrzehnten wurden verschiedene Ansätze zur Berücksichtigung dieser kurzfristigen Spitzenwerte in Ausbreitungsmodellen entwickelt. In dieser Untersuchung werden drei Methoden, nämlich der konstante Faktor 4 der Technischen Anleitung zur Reinhaltung der Luft (TA Luft), der stabilitätsabhängige peak-to-mean-Ansatz nach Schauberger und Piringer sowie das Konzentrations-Varianz-Modell von Öttl und Ferrero verwendet, um mit dem Ausbreitungsmodell LASAT richtungsabhängige Schutzabstände unter gegenwärtigen und zukünftigen klimatischen Bedingungen zu berechnen und zu vergleichen. Die meteorologischen Daten wurden mit einem regionalen Klimamodell für das gegenwärtige und das künftige Klima ermittelt. Betrachtet werden zwei Bereiche nördlich und südlich des österreichischen Alpenhauptkamms. Erwartungsgemäß werden mit dem Faktor 4 die größten Schutzabstände errechnet, gefolgt vom Konzentrations-Varianz-Ansatz und dem stabilitätsabhängigen peak-to-mean-Ansatz. In Österreich wird in Zukunft bei Geruchsexpertisen und in Genehmigungsverfahren der Konzentrations-Varianz-Ansatz in Kombination mit einem Lagrange-Ausbreitungsmodell verwendet werden.

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.

Regarding air quality, odours have been repeatedly ranked as the number one reason for public complaints to authorities. The most widely used method for assessing odour impacts is dispersion modelling. However, the entire impact assessment chain is permeated with uncertainty, and the role of different sources of uncertainty is not well understood. A critical component of this chain is the emission, the focus of this work. Here we develop modelling analyses for examining the influence of variable emissions against constant emissions on the outcomes of impact assessments. The analyses are built upon six hourly-resolved emission scenarios and one time-invariant scenario applied for the fattening phase of pig production systems. All seven scenarios are configured to treat total emissions due to a mechanically ventilated shed as coming from an elevated point source with an unobstructed vertical release. A total of 378 impact maps from three sites in two countries (Austria and the U.S.) over relatively flat terrain are scrutinised. The influence and relevance of accounting for variability in odour emissions over time depend strongly on the nature of the emissions (e.g., temporal pattern, presence of stochastic and deterministic components) as well as other factors such as building downwash, odour impact criterion and stack height. Altogether, the results suggest that using hourly odour emission rates can improve the confidence in impact assessments compared with the simulations driven by constant emissions. For odour impact criteria based on high-end percentiles, the assumption of constant emissions can be more easily compromised. In contrast, lower percentiles are found to be more robust in offsetting the source emission variability. Results also indicate that the variability in odour emissions might become less of an issue for releases under the influence of downwash than those without obstacle effects. This systematic work is the largest investigation to date on the consequences of incorporating variable emissions when modelling odour impacts. Our findings demonstrate that the emission scenario used as input to dispersion models can play a central role in dictating the conclusions of odour impact assessments.

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.

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 (Ox). 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. Ox 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.

Atmospheric particulate matter (APM) monitoring is a fundamental tool for air pollution management and control. However, the limited amount of an APM sample that is typically available upon collection using specific devices may be a limiting factor to promote reliable chemical analysis. Direct solid analysis is thus a cost-effective alternative to be applied for this purpose, since it simplifies the handling of samples, combining faster analysis to maximum detectability with minimum sample consumption. This study presents the development of methods for the determination of beryllium, cadmium and lead in inhalable particulate matter (PM10) using direct solid analysis and high-resolution continuum source electrothermal atomic absorption spectrometry. The temperature program and the use of chemical modifiers were optimized for each individual analyte. Zirconium was used as a permanent modifier for the determination of Be, whereas Pd and Mg were co-injected as chemical modifiers for the determination of Cd and Pb. The potential interferences and calibration strategies were also evaluated. Under optimized conditions, calibration against aqueous standards was proven feasible and detection limits of 0.001, 0.001 and 0.004 ng m−3 for Be, Cd and Pb, respectively, were achieved. The methods were applied to the determination of the referred analytes in 28 samples of PM10 collected at an urban site in the city of Florianopolis, in the State of Santa Catarina, Brazil. Chemometric treatment of data considering analyte content in addition to meteorological parameters (accumulated rainfall, sunlight incidence and wind speed) showed a detectable correlation between these parameters. Samples could be statistically differentiated based on separate loadings for Cd and Pb, which was opposite to Be, for instance. Hence, there is the possibility to correlate these parameters in order to establish a relationship between the origin of the elements in the PM10 samples and the impact of meteorological conditions on their distribution in solid atmospheric particles.

Governments are increasingly introducing odour impact criteria (OIC) to determine separation distances between odour sources and residential areas. Previous studies have shown the wide range of OIC available for this purpose, depending on the desired level of protection against odour annoyance. However, it is unclear whether OIC with similar levels of protection can ensure analogous separation distances, which would reasonably be expected. This study presents a comparative analysis of separation distances calculated at two sites for different OIC, but all related to an equivalent level of protection. Here, the equivalent level of protection was defined for urban residential areas (land use), swine odour (hedonic tone) and new facilities (facility type). In this manner, the regulatory criteria currently enforced in Germany, Ireland, and Queensland (Australia) were selected as references for the investigation. The results clearly show that, even for an equivalent level of protection, disparate separation distances can be obtained. Differences in separation distances were found to be greater in prevailing wind directions compared to distances in additional wind directions. Overall, the results demonstrate a risk of poor conclusions in odour assessments. This means that care must be taken when adopting OIC for decision making, principally in those countries that have not yet established specific regulations to manage environmental odours. Concomitantly, the results stress the need for better harmonisation of the concept of the odour impact criterion and components thereof. By using perturbation analysis, it has also been found that the stack exit temperature influences the separation distances in a distinct way, reliant on the criteria used to determine the distances. This finding is of significance for input data collection in future odour modelling studies. Furthermore, approaches used to derive OIC, equivalence between dispersion modelling and field inspections (European standard EN 16841-1), as well as implications of the findings for regulatory practice are summarised and discussed.

In recent years, there has been a growing concern about potential impacts on public health and wellbeing due to exposure to environmental odour. Separation distances between odour-emitting sources and residential areas can be calculated using dispersion models, as a means of protecting the neighbourhood from odour annoyance. This study investigates the suitability of using one single year of meteorological input data to calculate reliable direction-dependent separation distances. Accordingly, we assessed and quantified the inter-annual variability of separation distances at two sites with different meteorological conditions, one in Brazil and the other in Austria. A 5-year dataset of hourly meteorological observations was used for each site. Two odour impact criteria set in current regulations were selected to explore their effect on the separation distances. The coefficient of variation was used as a statistical measure to characterise the amount of annual variation. Overall, for all scenarios, the separation distances had a low degree of inter-annual variability (mean coefficient of variation values from 8% to 21%). Reasonable agreements from year to year were therefore observed at the two sites under investigation, showing that one year of meteorological data is a good compromise to achieve reliable accuracy. This finding can provide a more cost-effective solution to calculate separation distances in the vicinity of odour sources.

Odour annoyances are considered a major cause of public complaints to regulatory agencies regarding air quality and represent a growing social problem, especially in industrialized countries. In view of the need to diagnose odour sources for control and mitigation of possible impacts on communities, was assessed, through a case study, the odorous emissions from an open biofilter. The equipment was responsible for gas treatment generated in the wastewater plant treatment of a textile industry. Sampling was conducted in the inlet duct of the biofilter using direct sampling and on the emission surface (output) using a hood (VDI 3477:2004). Samples were stored in plastic bags manufactured in polyvinyl fluoride (Tedlar®) and transported to the laboratory, where the odour concentration (in UO m-3) was determined based on the dynamic olfactometry dilution procedure (EN 13725:2003). To calculate the odour emission rate (OER) (in UO h-1), the volumetric flow rate (in m3 h-1) was measured in the inlet duct of the biofilter. The values obtained for the efficiency and the OER were 98.7 % and 0.34 x 106 UO h-1, respectively. Comparing the efficiency value with the criterion established by Article 12 of Resolution SEMA No 054:2006 (State of Paraná, Brazil), adopted as reference, the biofiltration system meets the minimum efficiency rating of 85 % required in removing odour.

Exposure to environmental odour can result in annoyance, health effects and depreciation of property values. Therefore, many jurisdictions classify odour as an atmospheric pollutant and regulate emissions and/or impacts from odour generating activities at a national, state or municipal level. In this work, a critical review of odour regulations in selected jurisdictions of 28 countries is presented. Individual approaches were identified as: comparing ambient air odour concentration and individual chemicals statistics against impact criteria (maximum impact standard); using fixed and variable separation distances (separation distance standard); maximum emission rate for mixtures of odorants and individual chemical species (maximum emission standard); number of complaints received or annoyance level determined via community surveys (maximum annoyance standard); and requiring use of best available technologies (BAT) to minimize odour emissions (technology standard). The comparison of model-predicted odour concentration statistics against odour impact criteria (OIC) is identified as one of the most common tools used by regulators to evaluate the risk of odour impacts in planning stage assessments and is also used to inform assessment of odour impacts of existing facilities. Special emphasis is given to summarizing OIC (concentration percentile and threshold) and the manner in which they are applied. The way short term odour peak to model time-step mean (peak-to-mean) effects is also captured. Furthermore, the fundamentals of odorant properties, dimensions of nuisance odour, odour sampling and analysis methods and dispersion modelling guidance are provided. Common elements of mature and effective odour regulation frameworks are identified and an integrated multi-tool strategy is recommended.

To promote the photocatalytic oxidation (PCO) of hydrogen sulfide (H2S) in the gas phase, TiO2-coated glass fiber filters were packed in an annular photoreactor. Glass fibers coated with TiO2 thin films were characterized structurally and morphologically by field emission gun scanning electron microscopy (FEG-SEM), scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDS) and X-ray diffractometry (XRD). Flow rate and H2S inlet concentration were evaluated to determine the performance of the reactor. Removal efficiencies up to 99% were achieved for flow rate of 25 L h(-1) (residence time of 121 s) and H2S inlet concentration from 12 to 14 ppmv. The long-term experiment presented H2S removal of 89% for 16 h. After 28 h of continuous use, H2S degradation was observed at 64%, which suggests that the photocatalyst was losing activity due to deactivation. Moreover, the kinetics of the PCO of H2S according to the Langmuir-Hinshelwood (L-H) approach along with the mass balance of a plug-flow reactor was modeled. The reaction constant (k) was calculated at approximately 10.5 μmol m(-3) s(-1) and the adsorption constant (K) of approximately 5263 m(-3) mol with linearity (R2) of 0.98.