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

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.

Comparison between Puff and Lagrangian Particle Dispersion Models at a Complex and Coastal Site

A comparison between a puff atmospheric dispersion model (hereafter: PuM) and a Lagrangian particle model (hereafter: LPM) was conducted for a real case of emissions from an industrial plant, in the context of a complex and coastal site. The PuM’s approach is well-known and widely adopted worldwide, thanks to the authoritative suggestions by the US-EPA for regulatory use as, according to the definitions included in its guidelines, an “alternative” to “preferred” models; LPMs are more advanced models and have gained reliability over the last two decades. Therefore, it is of interest to provide insights into the decision to adopt or recommend, in the field of atmospheric impact assessment, a more advanced, but more knowledge- and resource-intensive, modeling tool, rather than an established albeit less accurate one. An inter-comparison of the two approaches is proposed based on the use of various statistical and comparative parameters with the goal of studying their differences in reproducing maps of ground-level ambient concentration statistics for assessment purposes (annual means, hourly peaks). The models were tested under a year-long simulation. The dispersion from both a point and a volume source, belonging to an existing industrial plant, was analyzed separately. The inter-comparison was performed through the analysis of 2D ground concentration maps, scatterplots, and three classical indices from the 2D maps of annual concentration statistics. To correlate the differences among models with site characteristics, the statistics were analyzed not only globally, but also according to distance from the source, the elevation, and the land-use classification. The analysis shows that around-its-axis plume dispersion in LPM is lower than in PuM over all the land-use types except water surfaces, in agreement with the theoretical basis provided by the models. Because of its more advanced theoretical formulation, e.g., in the interaction of the plume with the complex terrain and the three-dimensional wind field, an LPM used as a comparison term allowed us to highlight the weaknesses of a more traditional approach, such as PuM, in reproducing effects such as plume up-sloping, deflection, channeling, confinement, and wind shear diffusion.

Cannabis Cultivation Facilities: A Review of Their Air Quality Impacts from the Occupational to Community Scale

This review addresses knowledge gaps in cannabis cultivation facility (CCF) air emissions by synthesizing the peer-reviewed and gray literature. Focus areas include compounds emitted, air quality indoors and outdoors, odor assessment, and the potential health effects of emitted compounds. Studies suggest that β-myrcene is a tracer candidate for CCF biogenic volatile organic compounds (BVOCs). Furthermore, β-myrcene, d-limonene, terpinolene, and α-pinene are often reported in air samples collected in and around CCF facilities. The BVOC emission strength per dry weight of plant is higher than most conventional agriculture crops. Nevertheless, reported total CCF BVOC emissions are lower compared with VOCs from other industries. Common descriptors of odors coming from CCFs include "skunky", "herbal", and "pungent". However, there are few peer-reviewed studies addressing the odor impacts of CCFs outdoors. Atmospheric modeling has been limited to back trajectory models of tracers and ozone impact assessment. Health effects of CCFs are mostly related to odor annoyance or occupational hazards. We identify 16 opportunities for future studies, including an emissions database by strain and stage of life (growing cycle) and odor-related setback guidelines. Exploration and implementation of key suggestions presented in this work may help regulators and the industry reduce the environmental footprint of CCF facilities.

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.

Assessment of odour emissions by the use of a dispersion model in the context of the proposed new law in Chile

Chile is looking to define a regulatory framework for the odour emissions of various critical industrial activities. One of these is the sanitary sector, with 300 wastewater treatment plants (WWTP). The basis currently used by the Chilean environmental authority to assess odours is the set of odour emission factors (OEF) taken from the Dutch standard. The aim of this study was to compare these, used as a national reference, with our own OEF calculated from measurements using dynamic olfactometry of 41 WWTP. The dependence of OEF on operational variables such as flow rate and BOD5 was analysed in different plant processes. The current regulations were assessed under the two OEF scenarios for the 95th, 98th and 99.9th percentiles in the Temuco WWTP, using the WRF-CALPUFF modelling protocol. The OEF values of the emission sources showed no strong correlation with operating variables like BOD5 and wastewater flow rates in all plant sections. Our OEF values based on real measurements presented significant differences from the Dutch reference OEF, of the order of 6 UOe/m2/s. The odour emitting-units with the largest differences were the pre-treatment units, flow-splitting chamber and most units of the sludge processing sections. These new OEF offer an alternative paradigm for measuring emissions and an incentive to more accurate calculation of the emissions in critical units such as sludge treatment lines. When the WWTP studied in Temuco was assessed using the OEF calculated in this study, a difference of 1041 OUe/s was found above the odours emissions calculated using the Dutch reference database. Using the Dutch OEF, the odour immission concentrations at nearby receptors were not exceeded for the 95th and 98th percentiles; this might result in deficient environmental assessment under current Chilean laws. We therefore recommend that Chilean institutions should assess projects using the OEF calculated in this study.

Determination of Dose–Response Relationship to Derive Odor Impact Criteria for a Wastewater Treatment Plant

Municipal wastewater treatment plants (WWTPs) inside cities have been the major complained sources of odor pollution in China, whereas there is little knowledge about the dose–response relationship to describe the resident complaints caused by odor exposure. This study explored a dose–response relationship between the modelled exposure and the annoyance surveyed by questionnaires. Firstly, the time series of odor concentrations were preliminarily simulated by a dispersion model. Secondly, the perception-related odor exposures were further calculated by combining with the peak to mean factors (constant value 4 (Germany) and 2.3 (Italy)), different time periods of “a whole year”, “summer”, and “nighttime of summer”, and two approaches of odor impact criterion (OIC) (“odor-hour” and “odor concentration”). Thirdly, binomial logistic regression models were used to compare kinds of perception-related odor exposures and odor annoyance by odds ratio, goodness of fit and predictive ability. All perception-related odor exposures were positively associated with odor annoyance. The best goodness of fit was found when using “nighttime of summer” in predicting odor-annoyance responses, which highlights the importance of the time of the day and the time of the year weighting. The best predictive performance for odor perception was determined when the OIC was 4 ou/m3 at the 99th percentile for the odor exposure over time periods of nighttime of summer. The study of dose–response relationship could be useful for the odor management and control of WWTP to maximize the satisfaction of air quality for the residents inside city.