TY - JOUR

T1 - Improving odour assessment in LCA—the odour footprint

AU - Peters, Gregory M.

AU - Murphy, Kathleen R.

AU - Adamsen, Anders Peter S.

AU - Bruun, Sander

AU - Svanström, Magdalena

AU - ten Hoeve, Marieke

PY - 2014

Y1 - 2014

N2 - Purpose: Odour is an important aspect of systems for human and agricultural waste management and many technologies are developed with the sole purpose of reducing odour. Compared with greenhouse gas assessment and the assessment of toxicity, odour assessment has received little attention in the life cycle assessment (LCA) community. This article aims to redress this.Results and discussion: We produced a list of 33 linear characterisation factors based on hydrogen sulphide equivalents, analogous to the linear carbon dioxide equivalency factors in use in carbon footprinting, or the dichlorobenzene equivalency factors developed for assessment of toxic impacts in LCA. Like the latter, this odour footprint method does not take local populations and exposure pathway analysis into account—its intent is not to assess regulatory compliance or detailed design. The case study showed that despite the need for materials and energy, large factor reductions in odour footprint and eutrophication potential were achieved at the cost of a smaller factor increase in greenhouse emissions.Conclusions: The odour footprint method is proposed as an improvement on the established midpoint method for odour assessment in LCA. Unlike it, the method presented here considers the persistence of odourants. Over time, we hope to increase the number of characterised odourants, enabling analysts to perform simple site-generic LCA on systems with odourant emissions.Methods: Firstly, a framework for the assessment of odour impacts in LCA was developed considering the classical LCA framework of emissions, midpoint and endpoint indicators. This suggested that an odour footprint midpoint indicator was worth striving for. An approach to calculating an areal indicator we call “odour footprint”, which considers the odour detection threshold, the diffusion rate and the kinetics of degradation of odourants, was implemented in MATLAB. We demonstrated the use of the characterisation factors we calculated in a case study based on odour removal technology applied to a pig barn.

AB - Purpose: Odour is an important aspect of systems for human and agricultural waste management and many technologies are developed with the sole purpose of reducing odour. Compared with greenhouse gas assessment and the assessment of toxicity, odour assessment has received little attention in the life cycle assessment (LCA) community. This article aims to redress this.Results and discussion: We produced a list of 33 linear characterisation factors based on hydrogen sulphide equivalents, analogous to the linear carbon dioxide equivalency factors in use in carbon footprinting, or the dichlorobenzene equivalency factors developed for assessment of toxic impacts in LCA. Like the latter, this odour footprint method does not take local populations and exposure pathway analysis into account—its intent is not to assess regulatory compliance or detailed design. The case study showed that despite the need for materials and energy, large factor reductions in odour footprint and eutrophication potential were achieved at the cost of a smaller factor increase in greenhouse emissions.Conclusions: The odour footprint method is proposed as an improvement on the established midpoint method for odour assessment in LCA. Unlike it, the method presented here considers the persistence of odourants. Over time, we hope to increase the number of characterised odourants, enabling analysts to perform simple site-generic LCA on systems with odourant emissions.Methods: Firstly, a framework for the assessment of odour impacts in LCA was developed considering the classical LCA framework of emissions, midpoint and endpoint indicators. This suggested that an odour footprint midpoint indicator was worth striving for. An approach to calculating an areal indicator we call “odour footprint”, which considers the odour detection threshold, the diffusion rate and the kinetics of degradation of odourants, was implemented in MATLAB. We demonstrated the use of the characterisation factors we calculated in a case study based on odour removal technology applied to a pig barn.

KW - Footprint

KW - LCIA

KW - Midpoint indicator

KW - Odor

KW - Odour

KW - Swine

U2 - 10.1007/s11367-014-0782-6

DO - 10.1007/s11367-014-0782-6

M3 - Journal article

AN - SCOPUS:84911004003

VL - 19

SP - 1891

EP - 1900

JO - International Journal of Life Cycle Assessment

JF - International Journal of Life Cycle Assessment

SN - 0948-3349

IS - 11

ER -