Airborne Emissions from Livestock Farms and Exposure of Nearby Residents using an Atmospheric Dispersion Model

Abstract

To estimate the exposure of local residents to substances emitted by livestock farms, we applied a dispersion model to calculate the air concentrations in the surroundings following from these emissions. At several livestock farms, indoor air measurements were performed to determine emission strengths, while ambient measurements were carried out to compare with model results. Measured substances were particulate matter (PM), endotoxins and micro-organisms. The dispersion model only simulated PM concentrations, which were used as a proxy to determine the dispersion concentrations of endotoxins and micro-organisms. For the living micro-organisms, the process of inactivation has to be taken into account. Here we describe the followed methodology and preliminary results.

Questions and Answers

Questioner: Douw Steyn

Question: Your model evaluation approach, using a log concentration scale, seems unreasonably demanding. How much better (visually at least) would the model appear if you used a linear scale?

Answer: Indeed I also had to get used to using a log concentration scale, but this is actually very common in the science of micro-biology. As the amount of micro-organisms can decrease very rapidly, a linear scale would only show distinguishable output for very small distances close to the emission point, while we are also interested in concentrations further away.

Questioner: Heinke Schlünzen

Question: How did you consider the impact of the building on this close-to-scale dispersion and did you consider the heat emission resulting from the densely packed animal stock?

Answer: We do not consider the impact of the buildings as this is currently not available in the model, though we agree that this might impact the dispersion at these local scales. Therefore, for now, measurements were only performed on days with a certain wind direction criterion where the direction of the emissions had to be aligned with the wind direction to avoid a large influence of the building.

We also did not include the heat emission resulting from the densely packed animal stock. Though this is an option in the model, the actual heat emission was unknown, while furthermore we expect this to be more important for industrial sources with significantly higher temperatures.

Questioner: Jaakko Kukkonen

Question: Regarding the transport of micro-organisms in the atmosphere, it is challenging to model their viability, due to the large number of possible micro-organisms. There are millions of different species of micro-organisms, viruses and bacteria, some of which are harmless, some extremely hazardous. Would you like to comment, please?

Answer: Indeed, there are many, many micro-organisms with each different behavior regarding inactivation for example. In this study, several pathogenic micro-organisms were selected for which their presence in livestock farms was investigated. As indicator micro-organisms, which can occur in higher concentrations and are therefore more easily measured, Staphylococcus spp. and E. coli were chosen. These represent two groups of bacteria, namely the gram positive (Staphylococcus spp.) and gram negative (E. coli) bacteria which have quite distinct characteristics. Gram positive bacteria have a thicker cell wall for instance and are therefore less easily inactivated.

To determine the inactivation rate, a literature study was carried out after which several results from literature were combined on which a regression analysis was performed to determine the function for the inactivation rate. This is hence based on more micro-organisms than just Staphylococcus spp. and E. coli, though of course not all existing micro-organisms can be included as there are simply way too many while additionally they may be difficult to measure. But by distinguishing between gram positive and gram negative bacteria, we do take into account an important characteristic of the micro-organism species. As such, the inactivation rate is also a function of the bacteria type, besides for example temperature.