Greenhouse gas emissions from four bioenergy crops in England and Wales: Integrating spatial estimates of yield and soil carbon balance in life cycle analyses

Abstract

Accurate estimation of the greenhouse gas (GHG) mitigation potential of bioenergy crops requires the integration of a significant component of spatially varying information. In particular, crop yield and soil carbon (C) stocks are variables which are generally soil type and climate dependent. Since gaseous emissions from soil C depend on current C stocks, which in turn are related to previous land management it is important to consider both previous and proposed future land use in any C accounting assessment. We have conducted a spatially explicit study for England and Wales, coupling empirical yield maps with the RothC soil C turnover model to simulate soil C dynamics. We estimate soil C changes under proposed planting of four bioenergy crops, Miscanthus (Miscanthus  giganteus), short rotation coppice (SRC) poplar (Populus trichocarpa Torr. & Gray  P. trichocarpa, var. Trichobel), winter wheat, and oilseed rape. This is then related to the former land use -arable, pasture, or forest/seminatural, and the outputs are then assessed in the context of a life cycle analysis (LCA) for each crop. By offsetting emissions from management under the previous land use, and considering fossil fuel C displaced, the GHG balance is estimated for each of the 12 land use change transitions associated with replacing arable, grassland, or forest/seminatural land, with each of the four bioenergy crops. Miscanthus and SRC are likely to have a mostly beneficial impact in reducing GHG emissions, while oilseed rape and winter wheat have either a net GHG cost, or only a marginal benefit. Previous land use is important and can make the difference between the bioenergy crop being beneficial or worse than the existing land use in terms of GHG balance.

Life Cycle Assessment (LCA) of Light-Weight Eco-composites

“…Moreover, it introduces a large degree of uncertainty in the estimations of direct/indirect N 2 O emissions because of 1) uncertainty in the EFs themselves (IPCC, 2006), 2) spatial and temporal variability of N 2 O emissions, especially uncertainty in indirect emissions, and 3) regional differrences in climatic and environmental conditions (Hutchinson et al, 2006). On the contrary, only a few studies concern integration of process-oriented models (RothC Daycent) with LCA study (Adler et al, 2007, Hillier et al, 2009. Neither discussion on LCA system boundary expansion by incorporating process-oriented models nor comparisons of different modelling approaches within the LCA context have been found.…”

“…Atmospheric deposition has been modelled in a few studies e.g. the model presented by Williams and Audsley (2008) and although whole crop rotations have been investigated (Hillier et al, 2009, Gelfand et al, 2010 relatively little attention has been given to the effects of previous crops on the crop modelled; in other words, the system boundary expansion by including the interactions between rotated crops has not been addressed. Only one study applied a process-oriented model to estimate soil C emission from wheat farming (Hillier et al, 2009).…”

“…Moreover, methods to integrate land use change in the LCA of agro-ecosystem have also been discussed, e.g. the approach reported by Kloverpris et al (2010), the method and case study presented by Hillier et al (2009) where soil C turnover resulting from land use change was integrated into LCA. In previous studies, estimates for agricultural field emissions of GHGs using IPCC Tier 1 approaches have commonly been applied.…”

“…Thus IPCC is best regarded as a first approximation, applicable worldwide but disregarding of regional or local agro-ecosystem characteristics (Hutchinson et al, 2006, Edwards-Jones et al, 2008. Therefore, DNDC and other process-oriented models have been recommended by LCA experts to more closely approach site specific relevance of, for example, N 2 O estimation than the IPCC approach (HGCA, 2008, Hillier et al, 2009). Only few studies have so far been carried out on the integration of process-oriented models (RothC, Daycent) in LCA studies (Adler et al, 2007, Hillier et al, 2009).…”

“…Therefore, DNDC and other process-oriented models have been recommended by LCA experts to more closely approach site specific relevance of, for example, N 2 O estimation than the IPCC approach (HGCA, 2008, Hillier et al, 2009). Only few studies have so far been carried out on the integration of process-oriented models (RothC, Daycent) in LCA studies (Adler et al, 2007, Hillier et al, 2009). However, these mainly focused on GHGs emitted from agricultural lands at region or country scales and the LCA system boundary expansion issues (e.g.…”