LCA Food 2012 in Saint Malo, France! - Manifestations et colloques ...

GROUP 4, SESSION B: CROP PRODUCTION SYSTEMS 8 th Int. Conference on LCA in the
Agri-Food Sector, 1-4 Oct 2012
812
106. Comparison of assessment methods for the environmental
impacts of pesticide production
Kiyotada Hayashi 1,* , Koichi Shobatake 2 , Naoki Makino 2
1 National Agriculture and Food Research Organization, Japan, 2 TCO2 Co. Ltd., Japan, * Corresponding
author. E-mail: hayashi@affrc.go.jp
With regard to the environmental impact of agricultural production systems, the proportion of pesticide production
is smaller than that of, for example, chemical fertiliser production (Hayashi, 2011). Although life
cycle inventory (LCI) analysis of pesticides has been limited, there have been recent development in estimation
techniques for the environmental impacts of pesticide production (Wernet et al., 2008) and for the LCIs
of pesticides (Sutter, 2010). However, the differences between the various assessment methods are not well
understood, and the practical implications for LCI data construction are not known. Therefore, this study
compares different assessment methods for the environmental impacts of pesticide production.
The assessment methods considered in this study include (1) assessment based on ecoinvent 2.2 (hereafter,
ecoinvent), (2) estimation using the Finechem tool (hereafter, Finechem), and (3) estimation using emission
factors derived from input-output tables for Japan (hereafter, IO). We conducted two comparisons, namely,
one between ecoinvent and Finechem, and the other between ecoinvent and IO. Twenty active ingredients
were analysed in the first comparison, and 52 pesticide products (13 active ingredients) were assessed in the
latter. Global warming (IPCC 2007 GWP 100a) was used as the impact category. S-PLUS (TIBCO Spotfire
S+® 8.1J for Windows) was employed for statistical analyses such as regression analysis.
The result of the first comparison showed that it is difficult to find a correlation between the results obtained
from ecoinvent and from Finechem (Fig. 1). In general, the variability (standard deviation) in the case of
Finechem was larger than that in the case of ecoinvent. The result of the second comparison demonstrated
that the determination coefficients of the regression analyses were sufficiently large, and that the regression
coefficients were significant at the 1% or 5% levels. The estimated values based on IO tended to be 5 times
or 10 times larger than those based on ecoinvent (Fig. 2, Table 1).
These results indicate that under the assumption that estimated values based on ecoinvent are reliable, further
study is necessary for developing reliable estimation methods. In addition, although the values obtained from
ecoinvent can be predicted from the values obtained from IO, adjustments may be necessary because of the
tendency to overestimate in the latter. The dependence of the results on the selection of the assessment
method is expected to be resolved by further development of life cycle inventories.
References
Hayashi, K., 2011. Assessing management influence on environmental impacts under uncertainty: a case
study of paddy rice production in Japan, in: Finkbeiner, M. (Ed.), Towards Life Cycle Sustainability
Management. Springer, pp. 331-340.
Sutter, J., 2010. Life cycle inventories of pesticides, Swiss Centre for Life Cycle Inventories, St. Gallen.
Wernet, G., Hellweg, S., Fischer, U., Papadokonstantakis, S., Hungerbühler, K. 2008. Molecular-structurebased
models of chemical inventories using neural networks. Environ. Sci. Technol. 42, pp. 6717-6722.