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.

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.

Assessing Peak-To-Mean Ratios of Odour Intensity in the Atmosphere near Swine Operations

Odour in the atmosphere is usually characterized by an intermittent time series of high peaks and periods of low (or zero) concentrations. The peak-to-mean ratio (PMR) is commonly used to estimate short-term peaks from long-term averages to assess the odour impact. The objective of this study was to quantify the peak-to-mean ratio of odour intensity (PMR_OI) in the atmosphere near swine operations. Fifteen human assessors (sniffers) were trained to use an 8 point odour intensity scale to measure odour intensity in the ambient air near two swine operations. In each measurement session, the sniffers were placed 0° (in the direction of wind), 30°, and 45° from the wind directions at 100, 500, and 1000 m from the swine operations to sniff odour in the air every 10 s for 30 min. The results showed that odour in the atmosphere was intermittent. The intermittency (% of time when odour was detected) increased with the averaging time and decreased with the distance from the odour source and the direction from the wind. The measured intermittency ranged from 13% to 85%. The PMR_OI increased with the averaging time, the distance from the source, and the direction from the wind. In the wind direction, the largest difference in PMR_OI between 1 and 30 min averaging times was 68% (2.5 vs. 4.2), which occurred at 1000 m from the odour source under stability class B. The average PMR_OI increased from 1.5 at 100 m to 3.5 at 1000 m. Atmospheric stability had a noticeable effect on PMR_OI. At 1000 m, the 30 min PMR_OI decreased from 4.2 at stability class B (unstable) to 2.4 at E (slightly stable).

Odorants and Their Contributions to Overall Odour Emission from a Landfill Leachate

As one of the important odour sources, landfill sites have drawn more and more public attentions. Odour emissions from landfill sites depend on the waste buried, operation activities, running conditions, etc. A study for finding out all possible odorous compounds from a landfill was conducted by analysing of on-site gas phase samples and emission samples from a landfill leachate in Sydney, Australia using thermal desorber – gas chromatography – mass spectrometer (TD-GC-MS) and air server – thermal desorber – gas chromatography – sulfur chemiluminoscence detector (AS-TD-GC-SCD). 49 odorants were identified from emission gas samples collected from landfill leachate collection pipe and only 8 odorants were detected from flux hood emission samples of the collected leachate sample. This indicates that more sampling and measurement techniques are always better to acquire all possible pollutants from an unknown odour source. The contributions of these odorants to overall odour emissions were also calculated based on their concentrations and odour thresholds. The top 10 odorants from leachate transportation pipe include methyl mercaptan, ethyl mercaptan, m-xylene, H2S, CS2, 1,2,3,4-tetra-methylbenzene, p-xylene, 1,2,4-trimethylbenzene, ethylbenzene and α-pinene. They contributed more than 95% to the odour in the gas accumulated in the leachate collection pipe.

Tamarixia radiata Behaviour is Influenced by Volatiles from Both Plants and Diaphorina citri Nymphs

Tamarixia radiata (Waterston) is an important ectoparasitoid of the Asian citrus psyllid, Diaphorina citri Kuwayama, a globally destructive pest of citrus. In the present study, a Y-tube olfactometer was employed to investigate whether the parasitoid T. radiata is capable of utilizing the odour source emitted by both plants and insect hosts during its foraging. The odour sources included Murraya paniculata (L.) shoots, 1st, 2nd, 3rd, 4th, and 5th D. citri instar nymphs, both individually and in combinations. Moreover, nymph-stage choice for parasitism, including 3rd, 4th, and 5th D. citri instar nymphs, was carried out. The results indicated that female T. radiata were only significantly attracted to volatiles emitted by M. paniculata shoots, 3rd, 4th, and 5th instar nymphs of D. citri, but could not distinguish between them. T. radiata males were not attracted by odours sourced from any instar D. citri nymphs. Female T. radiata adults exhibited a significant preference to later instar nymphal stages of D. citri for oviposition. The results from this study can be used to guide further investigations on the searching behaviour of this parasitoid and its utilization in D. citri biocontrol.

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.

Mammalian olfaction is a high temporal bandwidth sense

Odours are transported in turbulent plumes resulting locally in highly fluctuating odour concentration (Celani et al., 2014; Murlis et al., 1992; Mylne and Mason, 1991; Shraiman and Siggia, 2000). Yet, whether mammals can make use of the ensuing temporal structure (Celani et al., 2014; Crimaldi and Koseff, 2001; Murlis et al., 1992; Mylne and Mason, 1991; Schmuker et al., 2016; Vickers, 2000) to extract information about the olfactory environment remains unknown. Here, we use dual-energy photoionisation recording with >300 Hz bandwidth to simultaneously determine odour concentrations of two odours in air. We show that temporal correlation of odour concentrations reliably predicts whether odorants emerge from the same or different sources in normal turbulent environments outside and in laboratory conditions. To replicate natural odour dynamics in a reproducible manner we developed a multichannel odour delivery device allowing presentation of several odours with 10 ms temporal resolution. Integrating this device in an automated operant conditioning system we demonstrate that mice can reliably discriminate the correlation structure of odours at frequencies of up to 40 Hz. Consistent with this finding, output neurons in the olfactory bulb show segregated responses depending on the correlation of odour stimuli with populations of 10s of neurons sufficient to reach behavioural performance. Our work thus demonstrates that mammals can perceive temporal structure in odour stimuli at surprisingly fast timescales. This in turn might be useful for key behavioural challenges (Jacobs, 2012) such as odour source separation (Hopfield, 1991), figure-ground separation (Rokni et al., 2014) or odour localisation (Vergassola et al., 2007; Vickers, 2000).