Abstract

Annoyance is a familiar reaction to odours arising from wastewater treatment sites, a reaction which can result in complaints and prosecutions. Odour management plans can be used to assess the extent of nuisance caused and prioritise mitigation measures. Often, these plans have been developed purely on the basis of technical assessments of emission and dispersion, with the general aim of limiting odour concentrations to a specific threshold at some distance from the works. They have often been prepared with inconsistent communication between the site staff and consultant during the development process, and may not directly refer to the affected population. This paper describes a risk-based approach to developing odour management plans, in which mitigation measures are assessed and prioritised on the basis of the likely frequency and intensity of odour exposure. A key element of the approach is the use of knowledge from data gained from key stakeholder groups: customers, staff, and regulators. Emphasis is placed on the development of clear communications between these groups, which helps both in terms of raising awareness amongst operators as to the significance of odour problems, and also in managing the expectations of customers and regulators. The practical application of this approach is demonstrated by the development of odour management plans for wastewater treatment sites by Yorkshire Water Services Ltd. These have used data from staff, customers and regulators to develop risk grids, which are then used to prioritise remediation measures. Involving staff in the data collection operations has been successful in raising awareness of the significance of odours, and has in turn led to low-cost emission reductions through improved housekeeping. Improved communications between operators, customers and regulators has led to more realistic expectations with regard to odour problems, a situation which can reduce conflict and prevent the imposition of stringent and sometimes unrealistic odour standards.

Full Text
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