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Early assessment
“Measure twice, cut once” is a wise adage beloved of craftsmen and engineers alike, and it has lost none of its relevance to the process engineer or emissions mitigation designer today. Emissions to air, or to water or ground for that matter, from some activities and processes may need to be controlled to prevent adverse impacts on the environment and on the comfort of people nearby, but mitigation can be expensive. Assessment at an early stage can inform the options appraisal and result in the selection of an approach that is effective, proportionate, and sustainable in both financial and environmental terms.
Some activities that have the potential to cause significant pollution are regulated by the Environment Agency in England and Northern Ireland, the Scottish Environmental Protection Agency in Scotland, Natural Resources Wales in Wales or the local authority under the Environmental Permitting Regulations that regulate activities by means of an environmental permit requiring the use of best available techniques to control emissions. Direction on best available techniques is provided in process guidance notes, as there are likely to be several options for most processes and it will be important to select the most appropriate for the process in question.
An assessment of the impacts may be necessary as part of any application for an environmental permit; to accompany an application
for planning consent; or as a formal environmental impact assessment. It may also be due diligence or just good neighbourliness to evaluate the impact of your activity on its surroundings and to mitigate it where necessary, and also avoid potential nuisance action under the Environmental Protection Act 1990.
Best practice
Dispersion modelling is a key technique for predicting the concentration of pollutants at sensitive receptors. Widely used air dispersion models for regulatory purposes include ADMS 5, which was developed in the UK, and AERMOD, which is recommended by the United States Environmental Protection Agency. These are both steady-state Gaussian plume models that use information on emissions, weather, buildings, structures and terrain elevation to predict the concentrations of pollutants over a large radial distance from the emission source, to evaluate the impact’s significance and to determine the mitigation measures required.
When the impact evaluation is over a significantly large area (typically more than 50 km from the emission sources), or across complex terrain, or includes non-uniform land-use patterns or is during calm (very low wind speed) conditions, non-steady puff dispersion models such as CALPUFF are available. Such models are, however, resource intensive.
Impact assessments often use dispersion modelling to predict the:
• Concentrations of combustion emissions such as carbon monoxide, oxides of nitrogen and particulate matter from stationary sources such as gas engines
• Concentrations of exhaust emissions from an increase in vehicles using local roads
• Concentrations and deposition of ammonia from an intensive agricultural facility onto sensitive habitats
• Intensity of odours from wastewater or anaerobic digestion sources
• Optimum stack height to minimise ground-level concentrations
• Effects of alternative mitigation measures to inform selection
Receptors are anything that the pollutant may affect, for example, residential properties, workplaces and schools. These are commonly selected to evaluate the exposure of the occupants to a pollutant that may affect health or comfort. Nitrogen-sensitive habitats may be classed as receptors for the deposition of nitrogen from combustion or ammonia emissions.
The significance of a predicted concentration impact is assessed in the context of the sensitivity of the receptor and the potential effect of the change in pollutant concentration. For some pollutants, there is a clear threshold criterion that should not be exceeded. For example, the annual mean standard for nitrogen dioxide in ambient air is included in the UK National Air Quality Strategy, which is based on World Health Organization research. But, for others, particularly where the dose– response relationship is less well understood, for example, critical levels for nitrogen deposition on a particular habitat or criteria for odour exposure, the threshold should be agreed in consultation with the relevant stakeholders.
“the universe is a complex system and there are more variables in heaven and earth than can be processed in any dispersion model”
Sometimes, the emission characteristics are well understood, for example, manufacturers of engines and natural-gas-fired boilers will have followed a development and testing process and will be able to provide comprehensive information on exhaust gas temperatures, flows and emissions of key pollutants.
For road traffic emissions, Defra publishes the Emissions Factors Toolkit for estimating emission rates for road traffic in the UK for the current year and up to 2030. This considers the expected fleet composition for motorways, urban and rural roads in the UK, European emission standards from pre-Euro 1 to Euro 6 and predicted changes to the fleet.
After having invented the calculating engine, it was said that Charles Babbage was asked, “Pray, Mr Babbage, if you put into the machine wrong figures, will the right answers come out?” to which he is said to have replied, “I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question”. More recently, computer scientists have turned this succinctly into the acronym RIRO standing for “rubbish in, rubbish out”. Dispersion modellers might perhaps state it better as “greater uncertainty in model inputs leads to greater uncertainty in the results”, but the principle holds.
he universe is a complex system and (with apologies to Shakespeare) there are more variables in heaven and earth than can be processed in any dispersion model. Any model is a simplification and any given value is uncertain, so it makes sense to minimise the uncertainty of the parameters that can be controlled to minimise the uncertainty of the model output and maximise the confidence that can be placed on the assessment. After all, models are powerful predictive tools, but processes and impacts happen in the real world.
In the real world: Emissions case study
The new owners of an industrial laundry specialising in solvent-soiled textiles approached RSK with their concerns about the environmental permit consequences of their plans to invest in new premises and plant to increase capacity. There was no history of complaints about emissions from the existing plant; however, that was in an industrial setting, whereas the new premises would handle more laundry and be at a more sensitive location with residential properties in relatively close proximity. The existing operations were not regulated by an environmental permit, but the new owners were not sure whether the increased capacity of the new facility might trigger a requirement for authorisation that would bring with it conditions such as emissions limits that would have to be met.
The first priority was to understand any permitting requirements. Our specialist permitting team reviewed the operations and activities undertaken, consulted with the Environment Agency and the local authority and concluded that the process was outside the scope of The Environmental Permitting (England and Wales) (Amendment) (EU Exit) Regulations 2018, therefore a permit would not be required.
However, a hydrocarbon odour was apparent at the existing premises and air emissions of volatile organic compounds (VOC) can have the potential to affect human health. These emissions could also contribute to low-level ozone formation, photochemical smog and secondary organic aerosols, and emissions to air and odour may cause a statutory nuisance under the Environmental Protection Act 1990.
These facts provided a driver for assessing the potential odour and air quality impacts to ensure laundry operations were not adversely affecting local residents, particularly in view of the residential properties near the proposed relocation site.
“hydrocarbon odour was apparent at the existing premises. These emissions could contribute to low-level ozone formation, photochemical smog and secondary organic aerosols”
The new facility would be a purpose-designed modern laundry plant, including new continuous batch washers and tumble dryers with conveyors. It would also feature a used-water treatment system that included an air stripper column in which the water passes over a largesurface-area matrix through which air is blown to strip VOCs from the water. Air from the washers, dryers and process areas was to be extracted and ducted to discharge above the building’s roof. The principal emission sources were likely to be the air extract discharges and the water treatment solvent-stripper discharge.
Emissions from the process were not well understood; however, the process was expected to be similar to that carried out at the existing facility. We therefore proposed to sample the emissions to air from the existing plant and scale these up to predict the emissions from the new facility.
A representative selection of laundry was washed, and samples of air from the existing washer air extract system and the process area were collected.
Samples for odour analysis were collected by a specialist odour laboratory using odour-free polytetrafluoroethylene sampling tubes and Nalophan sample bags fitted in a ridged barrel that was partially evacuated to draw air along the sample tube into the bags (the lung principle). The samples were transported to the specialist odour laboratory for the determination of odour concentration in accordance with the British Standard for olfactometry, BS EN 13725: 2003. Odour concentration results were expressed in European odour units per cubic metre (OUE/m³), which equate to the number of dilutions to the detection threshold.
Samples for VOC analysis were collected using a calibrated sampling pump to draw air through a charcoal sorbent tube that was then analysed at a UKAS-accredited laboratory for VOCs.
The results, along with measurements of air flow and temperature in the ducting, were used to estimate emissions of odour and VOC per kilogramme of laundry that was then used with information on the proposed air extract system to estimate the emissions from the planned new facility.
Emissions to air from the water treatment solvent stripping plant were estimated from sampling and analysis of the solvent loading of wastewater from the existing plant and based on the mass of soiling removed from the laundry at the existing plant.
The resulting emission rates were used with dispersion modelling package ADMS 5 to model the concentrations of odour and total and individual VOCs in the area around the plant and at the locations of the residential properties. The model used hourly sequential meteorological data from a nearby weather station considered representative of the conditions at the proposed site and took account of the terrain and the potential influence of buildings on the dispersion profile of the emissions (wake and downwash effects).
Our modelling suggested that, although concentrations of individual VOCs were predicted to be very low, the cumulative total VOC concentrations and odour intensities were relatively high. A regenerative thermal oxidation unit was proposed for the water treatment plant solvent stripper; however, source apportionment suggested that the greatest contribution to concentrations at the receptors was the air-extract discharge. Therefore, in consultation with the engineering team, we proposed to increase the capacity of the regenerative thermal oxidation unit to also treat the extracted air, thereby mitigating the potential air quality and odour impacts at the receptors.
“we proposed to increase the capacity of the regenerative thermal oxidation unit to also treat the extracted air, thereby mitigating the potential air quality and odour impacts at the receptors”
Introducing new receptors
Assessments can also be carried out to evaluate the impact of existing facilities on proposed new receptors. We used dispersion sampling and in-situ emissions rate sampling to help a company that had an area of surplus land surrounding an anaerobic digestion facility and was considering selling it for residential or commercial development. Odour from the anaerobic digestion plant could potentially affect amenity in some parts of the land, thereby constraining potential development or making some uses more appropriate than others.
“odour is something of a special case because it gives a subjective experience based on the perception and interpretation of an often-complex mixture of chemicals”
Odour is something of a special case because it gives a subjective experience based on the perception and interpretation of an oftencomplex mixture of chemicals. The technology behind electronic noses has developed greatly in the past few decades, but truffle hunters still use a pig! Even human noses are highly sensitive and specific and can detect very low concentrations of odorous substances or mixtures.
Odorous air can be sampled and the odour intensity can be determined by a specialist laboratory using dynamic dilution olfactometry according to method BS EN 13725, which is based on the number of dilutions after which the odour can just be detected by a panel of human sniffers.
Because of the subjective nature of odour, a mixed strategy combining several techniques is often useful. To assess the impact of odours from the site, we initially used dispersion modelling based on typical emission rates. This suggested that a rather large area, including some existing residential properties, would be significantly affected: something of a paradox because, historically, there had been very few complaints.
To explore this apparent contradiction, we carried out a field odour assessment to attempt to corroborate or ground truth the modelling and in-situ sampling of the odour emission rates from the principal sources with the help of a specialist odour-sampling and analysis laboratory. The measured emission rates enabled the model to be refined, and the field odour survey provided increased confidence in the predictions of the modelling. This informed our considerations of which, if any, sources would offer the greatest benefit if we could reduce the odour impacts and increase the land available for development in comparison with the costs of mitigation.
An assessment in time
Mitigation measures can be costly and disruptive, so investing a little bit of time in understanding the potential impacts and the efficacy of mitigation options may help to avoid problems in the long run. Or “a stitch in time saves nine”, as they used to say.
