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.

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

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.

Assessing the inter-annual variability of separation distances around odour sources to protect the residents from odour annoyance.

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.

Impacts of global warming on confined livestock systems for growing-fattening pigs: simulation of heat stress for 1981 to 2017 in Central Europe.

In the mid-latitudes, pigs and poultry are kept predominantly in confined livestock buildings with a mechanical ventilation system. In the last decades, global warming has already been a challenge which causes hat stress for animals in such systems. Heat stress inside livestock buildings was assessed by a simulation model for the indoor climate, which is driven by meteorological parameters. Besides the meteorological conditions, the thermal environment inside the building depends on the sensible and latent energy release of the animals, the thermal properties of the building and the ventilation system and its control unit. For a site in Austria in the north of the Alpine Ridge, which is representative for confined livestock buildings for growing-fattening pigs in Central Europe, meteorological data between 1981 and 2017 were used for the model calculations of heat stress measures. This business-as-usual simulation over these 37 years resulted in an increase of the mean relative annual heat stress parameters in the range between 0.9 and 6.4% per year since 1981. In order to minimise the negative economic impact as the consequence of this positive trend of heat stress, adaptation measures are needed. The calculations for growing-fattening pigs show that such a simulation model for the indoor climate is an appropriate tool to determine the level of heat stress of livestock inside confined livestock buildings.

Determining methane emissions from biogas plants--Operational and meteorological aspects.

A micrometeorological method, combining an inverse dispersion technique with path-integrated concentration measurements, was applied on an Austrian biogas plant over the period of more than one year to determine emissions of the whole plant. Measurement campaigns were conducted to characterize the emission response to operational activities (e.g. digestate management) and meteorological changes. When digestate storage tanks were filled, an average emission rate of 7.2 kg CH4/h (approx. 4% of the calculated CH4 production) was determined, while 5.4 kg CH4/h of emissions (approx. 3% of the calculated CH4 production) were quantified after the tanks had been emptied. It could be observed that besides the operation mode (e.g. filling level or agitation of the openly stored digestate, maintenance), the meteorological conditions such as wind speed and solar radiation (e.g. heat flux) can also affect the emission rate.

Quantification of methane emissions from full-scale open windrow composting of biowaste using an inverse dispersion technique.

An inverse dispersion technique in conjunction with Open-Path Tunable-Diode-Laser-Spectroscopy (OP-TDLS) and meteorological measurements was applied to characterise methane (CH4) emissions from an Austrian open-windrow composting plant treating source-separated biowaste. Within the measurement campaigns from July to September 2012 different operating conditions (e.g. before, during and after turning and/or sieving events) were considered to reflect the plant-specific process efficiency. In addition, the tracer technique using acetylene (C2H2) was applied during the measurement campaigns as a comparison to the dispersion model. Plant-specific methane emissions varied between 1.7 and 14.3 gCH4/m(3)d (1.3-10.7 kg CH4/h) under real-life management assuming a rotting volume of 18,000 m(3). In addition, emission measurements indicated that the turning frequency of the open windrows appears to be a crucial factor controlling CH4 emissions when composting biowaste. The lowest CH4 emission was measured at a passive state of the windrows without any turning event ("standstill" and "sieving of matured compost"). Not surprisingly, higher CH4 emissions occurred during turning events, which can be mainly attributed to the instant release of trapped CH4. Besides the operation mode, the meteorological conditions (e.g. wind speed, atmospheric stability) may be further factors that likely affect the release of CH4 emissions at an open windrow system. However, the maximum daily CH4 emissions of 1m(3) rotting material of the composting plant are only 0.7-6.5% of the potential daily methane emissions released from 1m(3) of mechanically-biologically treated (MBT) waste being landfilled according to the required limit values given in the Austrian landfill ordinance.

Multisource emission retrieval within a biogas plant based on inverse dispersion calculations--a real-life example.

Open digestate storage tanks were identified as one of the main methane (CH4) emitters of a biogas plant. The main purpose of this paper is to determine these emission rates using an inverse dispersion technique in conjunction with open-path tunable diode laser spectroscopy (OP-TDLS) concentration measurements for multisource reconstruction. Since the condition number, a measure of "ill-conditioned" matrices, strongly influences the accuracy of source reconstruction, it is used as a diagnostic of error sensitivity. The investigations demonstrate that the condition number for a given source-sensor configuration in the highly disturbed flow field within the plant significantly depends on the meteorological conditions (e.g., wind speed, stratification, wind direction, etc.). The CH4 emissions are retrieved by removing unrepresentative periods with high condition numbers, which indicate uncertainty in recovering the individual sources. In a final step, the CH4 emissions are compared with the maximum biological methane potential (BMP) in the digestate analyzed under laboratory conditions. The retrieved methane emission rates represent an average of 50% of the maximum BMP of the stored digestate in the winter months, while they comprised an average of 85% during the measurement campaigns in the summer months. The results indicate that the open tanks have the potential to represent a substantial emission source even during colder periods.

Use of a Monte Carlo technique to complete a fragmented set of H2S emission rates from a wastewater treatment plant.

The impact of ambient concentrations in the vicinity of a plant can only be assessed if the emission rate is known. In this study, based on measurements of ambient H2S concentrations and meteorological parameters, the a priori unknown emission rates of a tannery wastewater treatment plant are calculated by an inverse dispersion technique. The calculations are determined using the Gaussian Austrian regulatory dispersion model. Following this method, emission data can be obtained, though only for a measurement station that is positioned such that the wind direction at the measurement station is leeward of the plant. Using the inverse transform sampling, which is a Monte Carlo technique, the dataset can also be completed for those wind directions for which no ambient concentration measurements are available. For the model validation, the measured ambient concentrations are compared with the calculated ambient concentrations obtained from the synthetic emission data of the Monte Carlo model. The cumulative frequency distribution of this new dataset agrees well with the empirical data. This inverse transform sampling method is thus a useful supplement for calculating emission rates using the inverse dispersion technique.

Comparison of two peak-to-mean approaches for use in odour dispersion models.

In this paper, two approaches to estimate odour concentrations in dispersion models are compared. The approaches differ in the estimation of the momentary (peak) odour concentration for the time interval of a single human breath (approximately 5 s). The Austrian Odour Dispersion Model (AODM) is a Gaussian model with peak-to-mean factors depending on wind speed and atmospheric stability. The German Lagrange code AUSTAL2000 uses a constant factor 4 in all meteorological conditions to derive the maximum odour concentration over a short integration time. As the Lagrange model, in contrast to the Gauss model, can be applied also in complex topography and with isolated buildings, the implementation of the Austrian peak-to-mean approach in AUSTAL2000 would enable for more realistic separation distances in these environments. In a current scientific project, this implementation will be carried out, and a comparison of separation distances with AODM and AUSTAL2000 will be undertaken.