Summary and Overview of the Odour Regulations Worldwide

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarise odour legislation in selected European countries (France, Germany, Austria, Hungary, the UK, Spain, the Netherlands, Italy, Belgium), North America (the USA and Canada), and South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces, and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modelling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application.

SIMULATION OF ODOUR DISPERSION FROM DA PHUOC LANDFILL

The purpose of this research is estimation rate of odorous gas emission from landfills and simulating the odour dispersion. The method used for the study was based on the methane emission model of Intergovermental Panel on Climate change and Gauss Model. The study results showed no discrepancies between calculated and measured data of odorous gas emission, Nash-Sutcliffe coefficient ranged from 0,642 to 0,770. The results of the odour intensity simulations show that there is no significant deviation from the actual data. The difference between the observation and the odor intensity simulation is usually less than one level.

Towards Fast Plume Source Estimation with a Mobile Robot

The estimation of the parameters of an odour source is of high relevance for multiple applications, but it can be a slow and error prone process. This work proposes a fast particle filter-based method for source term estimation with a mobile robot. Two strategies are implemented in order to reduce the computational cost of the filter and increase its accuracy: firstly, the sampling process is adapted by the mobile robot in order to optimise the quality of the data provided to the estimation process; secondly, the filter is initialised only after collecting preliminary data that allow limiting the solution space and use a shorter number of particles than it would be normally necessary. The method assumes a Gaussian plume model for odour dispersion. This models average odour concentrations, but the particle filter was proved adequate to fit instantaneous concentration measurements to that model, while the environment was being sampled. The method was validated in an obstacle free controlled wind tunnel and the validation results show its ability to quickly converge to accurate estimates of the plume’s parameters after a reduced number of plume crossings.

Summary and Evaluation of the Odour Regulations Worldwide

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarize odour legislation in selected European countries (France, Germany, Austria, Hungary, United Kingdom, Spain, The Netherlands, Italy, Belgium), North America (USA and Canada), South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modeling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application.

Impact Analysis of Environmental Conditions on Odour Dispersion Emitted from Pig House with Complex Terrain Using CFD

With the rise in livestock production, the odour concentration emitted from livestock facilities has significantly increased. For this reason, odour complaints have become a major issue. The dispersion of the odour into the atmosphere is affected by various factors (wind speed, wind direction, atmospheric stability, terrain condition, ventilation type, and so on). Thus, a thorough analysis on the factor influencing odour dispersion is necessary to establish regulations and policies for odour management. Therefore, this research aimed to evaluate odour dispersion generated from a pig house with complex terrain using computational fluid dynamics (CFD) and to statistically determine the key factor for odour dispersion. By comparing CFD-computed results with field-measured data, an appropriate grid size, time step, and turbulence model of the CFD model were determined. Considering various factors, case studies were performed using the validated CFD model. The CFD-computed results showed that odour dispersion distance at the level of 1 OU m−3 ranged from 129.7 to 1488.1 m. The prediction of odour dispersion distance varies with the change of factor being analysed. Finally, the statistical analysis showed that the most influential factor that affected odour dispersion distance was the wind speed with a t-value: −9.057.

INFLUENCE OF MODELLING CHOICES ON THE RESULTS OF LANDFILL ODOUR DISPERSION

Landfills are an important source of odour pollution, potentially causing nuisance to adjacent populations. The most commonly used odour impact assessment for this type of plants usually involves a combination of dynamic olfactometry with dispersion modelling. Despite the advantages associated with the use of dispersion models, there are still some important issues related to their uncertainty. The dispersion model requires the Odour Emission Rate (OER) as input, expressed as units of odour emitted per unit time. Source term characterization and the estimation of the OER are typically the most important steps in the model’s implementation, accounting for the highest contribution to the overall uncertainty. Another important element of uncertainty when modelling emissions from landfill surfaces is the geometrical implementation of the emission source in the dispersion model. This entails the definition of the initial dimensions of the emission, which is critical in the case of large area sources. This paper discusses issues related to uncertainty in the use of dispersion models for the evaluation of landfill odour impacts, particularly focusing on the estimation of the OER and the emission’s initial vertical dimension. This study shows that modelling choices may lead to a variance in the resulting modelled odour concentrations at receptors differing by up to a factor 3. This variability should not cause distrust in the method, but rather indicates the importance of having odour dispersion modelling studies carried out by experts with deep knowledge of the physical-chemical mechanisms underlying atmospheric emissions.

Livestock odour dispersion and its implications for rural tourism: case study of Valencian Community (Spain)

Aim of study: To study the relationship between the problem odours caused by livestock farms and the evolution of rural tourism.Area of study: A coastal region in Spain, the Valencian Community.Material and methods: The odour emission rates of 4,984 farms have been calculated, and the ambient odour concentration was determined to assess the odour nuisance. The odour concentration was modelled by applying the Gaussian model based on emission data and the most unfavourable meteorological conditions of the 45 climatic stations distributed throughout the analysis area. The dispersion model was implemented in a geographic information system, deducing the municipalities affected using the odour concentration thresholds. Furthermore, the evolution of rural tourism in municipalities was studied during the period of 2006-2017. The relationship between the evolution of rural tourism and the effects of odours is studied by means of a bivariate spatial correlation analysis.Main results: Pigs are the predominant species in areas with the greatest odour emission problems; ~ 29% of farms can result in annoyances among the population with odour concentrations greater than 5 OU/m3, and 46% of municipalities can be affected by odour problems. These odour nuisances had negative consequences in the municipality where measures were carried out to favour rural development, such as rural tourism. Municipalities were detected in which the problem of odours can be a deterrent to rural tourism, whereas in other municipalities it was observed that minimizing livestock activity can be a method to promote rural tourism.Research highlights: This study provides a methodology that allows modeling the odour dispersion of livestock and relates its implications to rural tourism. Municipalities have been identified where livestock odours can cause a stagnation of the rural tourism income.

A Comparative Study of Bio-Inspired Odour Source Localisation Strategies from the State-Action Perspective

Locating odour sources with robots is an interesting problem with many important real-world applications. In the past years, the robotics community has adapted several bio-inspired strategies to search for odour sources in a variety of environments. This work studies and compares some of the most common strategies from a behavioural perspective with the aim of knowing: (1) how different are the behaviours exhibited by the strategies for the same perceptual state; and (2) which are the most consensual actions for each perceptual state in each environment. The first step of this analysis consists of clustering the perceptual states, and building histograms of the actions taken for each cluster. In case of (1), a histogram is made for each strategy separately, whereas for (2), a single histogram containing the actions of all strategies is produced for each cluster of states. Finally, statistical hypotheses tests are used to find the statistically significant differences between the behaviours of the strategies in each state. The data used for performing this study was gathered from a purpose-built simulator which accurately simulates the real-world phenomena of odour dispersion and air flow, whilst being sufficiently fast to be employed in learning and evolutionary robotics experiments. This paper also proposes an xml-inspired structure for the generated datasets that are used to store the perceptual information of the robots over the course of the simulations. These datasets may be used in learning experiments to estimate the quality of a candidate solution or for measuring its novelty.