Michael S. Corson

Development of a soil compaction indicator in life cycle assessment

PurposeIntegrating soil quality impacts in life cycle assessment (LCA) requires a global approach to assess impacts on soil quality that can be adapted to individual soil and climate contexts. We have developed a framework for quantifying indicators of impact on soil quality, valid for all soil and climate conditions, and considering both on-site and off-site agricultural soils. Herein, we present one of the framework’s impact indicators, which has not yet been quantified in detail in LCA studies: soil compaction.Material and methodsThe method includes guidelines and tools for estimating midpoint compaction impacts in topsoil and subsoil as a loss of soil pore volume (in cubic metre per functional unit). The life cycle inventory (LCI) and life cycle impact assessment are based on simulation modelling, using models simple enough for use by non-experts, general enough to be parameterised with available data at a global scale and already validated. Data must be as site specific and accurate as possible, but if measured data are missing, the method has a standardised framework of rules and recommendations for estimating or finding them. The main model used, COMPSOIL, predicts compaction due to agricultural traffic. Results are illustrated using a case study involving several crops in different soil and climate conditions: a representative pig feed produced in Brittany, France.Results and discussionPredicted compaction impacts result from the combination of site-specific soil, climate and management characteristics. The data necessary to the LCI are readily available from free soil and climate databases and research online. Results are consistent with compaction observed in the field. Within a soil type, predictions are most sensitive to initial bulk density and soil water content.ConclusionsThe method lays the foundation for possible improvement by refining estimates of initial soil conditions or adding models that are simple and robust enough to increase the method’s capacity and accuracy. The soil compaction indicator can be used in LCAs of bio-based materials and of waste management stages that consider composting. The framework includes other operational indicators (i.e. water erosion, soil organic matter change) to assess impact on soil quality. They complement other impact categories, providing increased ability to identify “impact swapping”.

LCA Food 2012—towards sustainable food systems

Among its many wonders, France is famous for its food. The eighth edition of the “International Conference on Life Cycle Assessment in the Agri-Food Sector” was held there for the first time in 2012. The LCA Food conferences are the world’s premier scientific forum on LCA in the agri-food sector. The previous conferences took place in Belgium (1996, 1998), Sweden (2001, 2007), Denmark (2003), Switzerland (2008) and Italy (2010). LCA Food 2012 took place in Saint Malo (western France) from 1–4 October. It was organised by INRA, the French National Institute for Agricultural Research, with the support of ADEME, the French Environment and Energy Management Agency. It was supported by ten sponsors (see conferencewebsite) and our indefatigable INRA colleagues of the organising committee. The 23-person international scientific committee reviewed 362 abstracts and 110 six-page papers.

Collaboration between Mountain and Lowland Farms Decreases Environmental Impacts of Dairy Production: The Case of Swiss Contract Rearing

Mountain farming areas are associated with high nature value and offer attractive landscapes, but farming in these areas is less viable than farming in more favorable regions. Consequently, there is a threat of land abandonment. Additionally, due to lower productivity of mountain farms, their products often bear a higher environmental burden than those from other areas. An optimal division of labor between mountain farms and farms in more favorable regions based on comparative advantages could help maintain attractive landscapes and reduce environmental impacts of agricultural production. An established Swiss contract rearing system, in which dairy farms from the agriculturally favorable lowlands collaborate with heifer rearing farms in the mountains, represents a promising approach for such a division of labor. In this system, the intensive phase of dairy production is performed in the lowlands, while the less intensive phase is performed in the mountains. Here, we analyzed a sample of 16 farms to compare the contract rearing system to a situation in which both, mountain and lowland farms produce milk and rear their own restocking animals. We performed a life cycle assessment to quantify environmental impacts of the dairy production systems, assessing environmental impacts both per kg of milk and per hectare of agricultural area. This assessment was supplemented with analysis of the workload of the farms, since increased work efficiency is one reason that farmers engage in contract rearing. Workload was calculated with a workload budgeting tool. We found that collaboration reduced environmental impacts as well as the workload per kg of milk. Collaboration had no effect on environmental impacts per hectare of agricultural area or the workload on lowland farms, while on mountain farms the environmental impacts and workload were reduced. In particular, reduction in environmental impacts of mountain farms is expected to foster the high nature value of this farmland and the provisioning of important ecosystem services. This case study of a contract rearing system thus illustrates how collaboration based on comparative advantages can benefit both environmental impacts of agricultural products and the high nature value of agriculturally less favorable farmland.

Modelling environmental effects of selected agricultural management strategies with regional statistically-based screening LCA

PurposeDespite the farm being considered by many as the most suitable level of decision-making and strategic management in agriculture, there is an increasing interest in evaluating agricultural management strategies at the regional level. Recent initiatives attempted to aggregate and generalise farm-level lifecycle inventory (LCI) data and lifecycle impact assessment (LCIA) results to describe the environmental performance of agricultural regions. This article describes our development and application of a regional statistics-based approach for constructing virtual representative farms (VRFs), representing dominant farm types for a given region, as a tool for comparing alternative regional agricultural strategies in contexts of insufficient farm (e.g. LCI) data.MethodsBased on statistical sources, we constructed VRFs of the dominant farm types in the largely agricultural region of Brittany, France. Environmental impacts of different agricultural management strategies were estimated at the regional level by modelling the strategies as changes in VRF-based LCIs, calculating LCIAs and extrapolating their mean per-ha impacts to the total land use in the region. Based on this assessment, performed using a regional lifecycle assessment framework, we analysed relative environmental impacts of each management strategy on the region. A strategy-comparison table was built to allow decision makers to understand the potential regional environmental consequences of implementing each strategy.Results and discussionOnce VRFs impact assessment results were extrapolated to the regional level, all strategies show environmental impacts per ha similar to those of the baseline, with differences ranging from −15 to +6%. The scenario featuring centralised fodder drying by 50% of cattle farms (50FOD) is the only one featuring surpluses for all products, due to associated cattle diet adjustments including reduced maize silage intake and partial substitution of concentrate feeds. The scenario featuring grass specialisation by all cattle farms (100GRA) shows a large deficit of grassland products, suggesting that a region-wide extensification strategy would not be self-sufficient.ConclusionsThe method developed enables comparing environmental consequences of region-wide implementation of agricultural strategies, yet, for our case study, it is particularly difficult to identify a “best” one. Nonetheless, the method serves as an initial step for preselecting strategies to investigate at a more detailed level. Prioritisation of a given strategy would likely be based on the environmental pressures considered most pressing by regional decision makers.