Are empirical equations an appropriate tool to assess separation distances to avoid odour annoyance?

Annoyance due to environmental odour exposure is in many jurisdictions evaluated by a yes/no decision. Such a binary decision has been typically achieved via odour impact criteria (OIC) and, when applicable, the resultant separation distances between emission sources and residential areas. If the receptors lie inside the required separation distance, odour exposure is characterised with the potential of causing excessive annoyance. The state-of-the-art methodology to determine separation distances is based on two general steps: (i) calculation of the odour exposure (time series of ambient odour concentrations) using dispersion models and (ii) determination of separation distances through the evaluation of this odour exposure by OIC. Regarding meteorological input data, dispersion models need standard meteorological observations and/or atmospheric stability typically on an hourly basis, which requires expertise in this field. In the planning phase, and as a screening tool, an educated guess of the necessary separation distances to avoid annoyance is in some cases sufficient. Therefore, empirical equations (EQs) are in use to substitute the more time-consuming and costly application of dispersion models. Because the separation distance shape often resembles the wind distribution of a site, wind data should be included in such approaches. Otherwise, the resultant separation distance shape is simply given by a circle around the emission source. Here, an outline of selected empirical equations is given, and it is shown that only a few of them properly reflect the meteorological situation of a site. Furthermore, for three case studies, separation distances as calculated from empirical equations were compared against those from Gaussian plume and Lagrangian particle dispersion models. Overall, our results suggest that some empirical equations reach their limitation in the sense that they are not successful in capturing the inherent complexity of dispersion models. However, empirical equations, developed for Germany and Austria, have the potential to deliver reasonable results, especially if used within the conditions for which they were designed. The main advantage of empirical equations lies in the simplification of the meteorological input data and their use in a fast and straightforward approach

An urban parameterization for a global climate model. Part I: Formulation and evaluation for two cities

Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities

Local and central evaluation of HER2 positivity and clinical outcome in advanced gastric and gastroesophageal cancer: results from the AGMT GASTRIC-5 Registry

Trastuzumab in combination with a platinum and fluorouracil is the treatment of choice for patients with advanced human epidermal growth factor receptor 2 (HER2) positive gastric cancer and gastroesophageal junction (GEJ) cancer. Pathological assessment of the HER2 status in gastric/GEJ cancer, however, still remains difficult. However, it is a crucial prerequisite for optimal treatment. The GASTRIC-5 registry was designed as an observational, multi-center research initiative comparing local and central HER2 testing. HER2 status was assessed by immunohistochemistry (IHC) and in equivocal cases (IHC score 2+) by additional in-situ hybridization. Between May 2011 and August 2018, tumor samples of 183 patients were tested in local and central pathology laboratories, respectively. Central testing revealed HER2 positivity in 38 samples (21%). Discordant HER2 results were found in 12% (22 out of 183) with locally HER2 positive/centrally HER2 negative results (9%, 17 out of 183), exceeding locally HER2 negative/centrally HER2 positive results (3%, 5 out of 183). Centrally confirmed HER2 positive patients receiving trastuzumab-based palliative first-line therapy showed a longer median overall survival compared to centrally HER2 positive patients not receiving trastuzumab (17.7 months (95% CI: 10,870-24,530) vs. 6.9 months (95% CI: 3.980-9.820), p = 0.016). The findings of the GASTRIC-5 registry corroborate the challenge of HER2 testing in gastric/GEJ cancer and highlight the necessity for central quality control to optimize individual treatment options. Centrally HER2 positive patients not receiving trastuzumab had the worst outcome in a Western real-world gastric/GEJ cancer cohort

A Power Sequence Interaction Function for Liquid Phase Particles

In this manuscript, a function is derived that allows the interactions between the atoms/molecules in nanoparticles, nanodrops, and macroscopic liquid phases to be modeled. One goal of molecular theories is the development of expressions to predict specific physical properties of liquids for which no experimental data are available. A big limitation of reliable applications of known expressions is that they are based on the interactions between pairs of molecules. There is no reason to suppose that the energy of interaction of three or more molecules is the sum of the pairwise interaction energies alone. Here, an interaction function with the limit value w = e2π/e is presented, which allows for the derivation of the atomic mass unit and acts as a bridge between properties of elementary particles and emergent properties of macroscopic systems. The following properties of liquids are presented using the introduced interaction function: melting temperatures of n-alkanes, nanocrystals of polyethylene, melting temperatures of metal nanoparticles, solid–liquid phase transition temperatures for water in nanopores, critical temperatures and critical pressures of n-alkanes, vapor pressures in liquids and liquid droplets, self-diffusion coefficients of compounds in liquids, binary liquid diffusion coefficients, diffusion coefficients in liquids at infinite dilution, diffusion in polymers, and viscosities in liquids

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

Qualitätsminderung von verpackten Lebensmitteln durch unerwünschte sensorische Störstoffe

For sensory nuisance substances, the correlation of sensory- and instrumental analytical results of packaged foodstuffs is necessary, in order to find a limit, at which sensory nuisance substances, such as the environment contaminant trichloroanisole, for example, lead to the rejection of the product by the consumer. With known permeabilities of films, the best-before date for a packaged food with known sensory nuisance substances can be predicted or even the maximum concentration, which an off-aroma may have in the environment at a given best-before date