Sustainability has become an important aspect of livestock production in Europe. It is defined as “… the ability to make development sustainable to ensure that it meets the needs of the present without compromising the ability of future generations to meet their own needs” [1
] and is often described to include three dimensions: economy, environment and social sustainability. The EU Commission has launched its Green Deal, which aims for Europe to be the first climate-neutral continent and includes a farm-to-fork strategy to accelerate the transition to sustainable food systems. This addresses several environmental aspects, such as “to have neutral or positive environmental impacts, to help to mitigate climate change and adapt to its impacts and to reverse the loss of biodiversity” [2
]. Therefore, the EU has clearly stated the need for environmentally friendly agriculture practices.
However, livestock production can have detrimental effects on the environment by producing large amounts of greenhouse gas and ammonia emissions and thus contributing to global warming, acidification and eutrophication. Global pork production is estimated to emit 668 megatons of carbon dioxide equivalent (CO2
-eq) greenhouse gases annually [3
]. Although this is lower than the beef and dairy cattle sectors combined (4623 megatons CO2
-eq annually [3
]), global pork production is forecast to grow by 11 Mt (+10%) until 2029, especially in developing countries [4
]. Further, agricultural expansion and intensification is one of the main drivers for land-use change (e.g., deforestation of large areas in the Amazonas) and biodiversity loss due to increasing demand for animal feed (e.g., soybean, pastures) [5
]. Therefore, environmental assessment of different pig farms and a deeper understanding of underlying driving factors are highly relevant to support strategies for limiting adverse effects on the environment.
One systematic assessment method to quantify the potential environmental impacts of complex systems is the Life Cycle Assessment (LCA), which aims to evaluate the environmental impact generated during the entire life cycle of a product [6
]. In the past years, LCA of pig production systems were used to investigate potential environmental impacts related to farm performance [7
], manure management [9
], or pig diet e.g., crude protein content or amino acid supplementation [10
]. The results are required to support farm management decisions regarding mitigation strategies. However, LCA has limitations. Various environmentally relevant aspects are hard to quantify and are therefore mostly not included in the assessment. Biodiversity, for example, is often omitted [13
] despite its crucial global role [14
]. Therefore, a combination with other environmental assessment methods are needed to address environmental impacts more comprehensively.
Key-Performance-Indicator (KPI) assessment, a semi-quantitative method, is a suitable approach to address such topics. A number of comprehensive sustainability or environmental impact assessment tools are fully or partially based on KPIs, e.g., “Sustainability Monitoring and Assessment RouTine” (SMART) [16
], “Sustainability Assessment of Food and Agriculture Systems” (SAFA) [17
] or the “Response-Inducing Sustainability Evaluation” (RISE) [18
]. KPIs are especially useful for assessing field management measures to promote biodiversity, such as cultivation of endangered crops or growing catch crops. These measures improve the environment locally as well as globally and can directly be implemented on-farm. Some studies have already assessed environmental performance as part of a sustainability assessment using the SAFA tool, for example on organic livestock farming in Sicily [19
] or beef cattle farming in Indonesia [20
]. Others used the SMART tool, for example on coffee farms in Uganda [21
]. However, a combination and on-farm application of LCA and KPI assessment has yet to be undertaken.
Therefore, a novel methodological approach is to combine quantitative LCA assessment with KPI assessment, in order to complement the LCA with a biodiversity assessment. This can serve as a hot-spot analysis for farmers and provide a first overview as the basis for improvements.
Thus, the overall aim of this study was to undertake a methodological evaluation of two environmental sustainability assessments, namely LCA and KPI assessment based on selected European pig farms. Specific objectives of this study were to (1) calculate environmental impacts using LCA methodology considering three different farm types (specialized breeding farms, finishing farms and breeding-to-finishing farms) and to analyse variation within farm types, (2) assess biodiversity performance at farm level using KPIs considering the three farm types and analyse variation, (3) investigate associations between LCA and KPI results and (4) investigate associations between farm management characteristics and environmental impacts (LCA and KPI).
We hypothesized that variation within farm types would be higher than across farm types for both LCA and KPI assessment, since the farm sample included very different production systems. Further, we hypothesized that farms with good LCA impacts would have poor performance on biodiversity based on a KPI assessment. The assumption was that farms with good LCA results manage their pig farm on a high productivity and efficiency level, which might be also reflected in intensive field management to produce crops to feed the pigs, which might have few biodiversity measures in place. Furthermore, we hypothesized that combining LCA and KPI assessment provides a more comprehensive environmental sustainability assessment.
So far, environmental impacts of pig farms have been mainly analysed by LCA [4
] and to our knowledge, no study exists that has analysed environmental impacts of a comparable, diverse sample of European pig farms with a KPI assessment based on SAFA guidelines [17
] or the SMART tool [16
]. Therefore, this study combined for the first time quantitative LCA results with a semi-quantitative KPI assessment based on field management characteristics focusing on biodiversity to achieve a more comprehensive and holistic assessment of environmental performance of European pig farms.
4.1. Life Cycle Assessment (LCA)
The first aim was to quantify the environmental impacts of the 63 pig farms surveyed with an attributional LCA and to assess differences between farm types and variability within farm types. As expected, values did not only vary widely within farm types, but also the overall variation was similar for all farm types, i.e. specialized breeding or finishing farms and the respective stage of combined breeding-to-finishing farms (Table 4
). This is in line with a previous study that did not compare different farm types but different organic systems (indoor with outdoor run, partly access to pasture and pasture pigs) and also came to the conclusion that variation was higher within farm systems than between them [24
]. Findings from the current survey can be explained by the large variety of production systems within each farm type expressed in different farm management characteristics including different husbandry, feeding and manure management systems (Table 3
). This inclusion of various, very different farms is in contrast to many other LCA studies, which focused either on environmental impacts of a rather homogenous sample of farms, e.g., conventional farms [39
], organic farms [24
] or traditional Iberian farms [40
], or analysed different management aspects or feeding practices through scenarios based on average values [8
Furthermore, we decided to use kilogram body mass net sold as the functional unit, whereas other studies often used kg live weight [23
] or kg pork [8
]. We chose kilogram body mass net sold as the LCA functional unit, since this allowed us to compare specialized pig farms (breeding, finishing) with the respective stage of breeding-to-finishing farms. Additionally, this functional unit is referring to the main product of pig farms and is therefore of high relevance for farmers from the environmental and economic (gross margin) point of view. However, it has to be kept in mind that using other functional units in LCA might results in different outcomes. For example, the unit “hectare of cultivated land”, might have shown increased LCA results for more intensive farms [23
]. Indeed, including this unit in the present study would have been interesting to avoid one-sided evaluations based on product-related LCA results only. However, in the end we decided not to use the functional unit of ha of cultivated land, as it would have led to higher uncertainty due to the inclusion of a high proportion of default values for crop yields. Furthermore, in most cases pig farmers do not have the possibility to decide on the origin of the bought-in feed.
Since we used a different functional unit and also the methodologies and system boundaries are also slightly different, direct comparison with other studies is not possible [42
]. Nevertheless, it is possible for the results for breeding-to-finishing farms to be set against the range of values found in other studies that focused on this farm type only. For breeding-to-finishing farms in the present study, their functional unit “per kg BMNS” can be compared with the functional unit “per kg live weight” used in most other studies, since for breeding-to-finishing farms it includes the whole process from piglets being born to finishers leaving the farm including bought-in gilts. The results found in the current study were in the same range as described in other studies. For example, GWP and AP (median) of breeding-to-finishing farms were 2.67 kg CO2
-eq and 46.3 g SO2
-eq per kg BMNS (Table 4
), whereas other studies report values ranging from 2.2 to 4.4 kg CO2
-eq per kg live weight (GWP) and from 23 to 186 g SO2
-eq. per kg live weight (AP) [6
When looking at the emission sources we found that feed (bought-in and home-grown) had the highest contribution to almost all impact categories, except for AP (Figure 2
), which is similar to other studies [8
]. This was also reflected in the correlations between farm management characteristics and the LCA results (Table 6
). Thus, FED, GWP and FEP can be especially mitigated by an improved feed conversion ratio, whereas AP and MEP can also be reduced by management improvements regarding the reproductive performance of the farm and emissions deriving from manure.
On the other hand, focusing on management improvements to mitigate LCA results might have negative impacts (trade-offs) on other dimensions of sustainability such as animal welfare [43
]. A shorter lactation can result in better LCA results, but increases stress and health issues (e.g., diarrhoea) in early weaned piglets [44
]. Therefore, management improvements to mitigate LCA results should always be improved with due regard to the possible effects on the other sustainability dimensions (economy, social sustainability, animal health and welfare).
4.2. Biodiversity Assessment Based on Key Performance Indicators
The second aim of this study was to undertake a detailed KPI assessment with a focus on biodiversity, which broadened the environmental perspective compared to other studies. Variation in biodiversity subtheme and theme scores was larger within farm types than across farm types, similar to the LCA results (Table 5
). This can also be explained by the large variety of production systems. Nevertheless, across all 56 crop-livestock farms regardless of farm type, scores for ecosystem, species and genetic diversity were scored on a low level so that the overall biodiversity theme score was between 38% and 43% (Table 5
). Another study, assessing biodiversity on various organic farms (farms with different livestock species, mixed crop-livestock farms and crop farms) in Switzerland found median values within the “Good” category (theme scores were between 61% and 80%) [45
]. The lower values found in the present study can be explained by the inclusion of mostly conventional and pig farms of some labels (except organic), many of which have also adopted conventional field management (e.g., use of pesticides). Nevertheless, the large variation with some relatively high values indicates that there is a large potential to implement measures to promote biodiversity on the majority of crop-livestock pig farms. Especially measures such as providing ecological focus areas on agricultural fields [46
], fertilizing based on plant and soil analysis [47
] and growing rare or endangered agricultural crops can be improved on the majority of crop-livestock pig farms in the present study to improve biodiversity.
Improving biodiversity is needed, since biodiversity is highly relevant for food security (e.g., supporting populations of pollinators) but has decreased rapidly in the last decades [15
]. Therefore, biodiversity has been targeted in Sustainable Development Goal #15 of the United Nations, which states to “protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
]. It is even hypothesised that with increasing biodiversity on the fields, inputs such as artificial pesticides can be reduced whilst maintaining yield through ecological control (i.e. with beneficial insects) [40
]. Furthermore, the positive effects of measures to promote biodiversity, such as providing opportunities for pollination or biological pest control, can positively impact crop yields and even farm incomes [49
These effects are part of an ecological intensification, which has received more attention in the last decades, since it is known that conventional intensification leads to a loss of biodiversity [51
]. Ecological intensification is described as “a nature-based alternative that complements or (partially) replaces external inputs, such as agrochemicals, with production-supporting ecological processes, to sustain agricultural production while minimising adverse effects on the environment
]. Ecological intensification makes use of biodiversity and other ecosystem services of agricultural fields. This emphasises to highlight the diversity of ecosystem services so that farmers are aware of the potential benefits that nature provides and thus are willing to implement respective measures [53
Therefore, projects to develop biodiversity assessment schemes, user-friendly tools, education and advice are necessary to raise understanding about the potential benefits of ecosystem services and to engage farmers in biodiversity improvement. Conducting a KPI assessment is one approach, since these measure-orientated indicators are easy to communicate to farmers, as they focus on information, which is known and understood by farmers [54
]. In this way, farmers may be encouraged to implement some steps to promote biodiversity in the future. For further research it would be interesting to also include result-orientated indicators of biodiversity, such as counting numbers of different species [54
]. However, counting species diversity is time- and resource-intensive [54
] and was therefore not suitable for the scope of the current project.
4.3. Correlation of Farm Management Characteristics with LCA and Biodiversity Results
Most farm management characteristics correlated only with the LCA impact categories (as discussed in Section 4.1
. above). Only three farm management characteristics, namely number of litters per sow per year, lactation length and number of finishers sold for slaughter correlated with both LCA and KPI results.
A longer lactation resulted in a higher AP (rs
= 0.45) and MEP (rs
= 0.69) and at the same time higher genetic diversity scores (rs
= 0.45; Table 6
). A longer lactation period results in fewer litters per sow per year, which explains why both lactation length and number of litters per sow per year were correlated in the same direction. The effect of improved productivity on the LCA impacts has already been described above. Our explanation for the correlation between a longer lactation period and genetic diversity scores is that organic farms are required to have a lactation length of at least 40 days (Council Directives 2007/834/EC and 2008/889/EC) and at the same time they have to implement several measures regarding genetic diversity, e.g., not allowed to feed GMO feed, must not use chemical pesticides and have to provide ecological focus areas. Such measures highly contribute to the subtheme genetic diversity (Table 2
), whereas species diversity and ecosystem diversity can also be improved by other measures (e.g., cultivation of leguminous or leguminous grassland, forest) and therefore the link with longer lactation length was not confirmed statistically through a significant correlation.
Nevertheless, lactation length is a farm management decision, which reflects the intensity of a pig farm and thus partly confirmed our hypothesis that farms managed on a high productivity and efficiency level might also manage their fields more intensively, which might be less effective concerning biodiversity measures. However, it has to be kept in mind that this relationship was only found with genetic diversity, and the underlying reasons may be likely due to the effect of the organic regulations on both topics.
4.4. Correlation between LCA and Biodiversity Results
Against our hypothesis, no correlations were found between environmental impacts from the LCA and any of the biodiversity subthemes (ecosystem, species and genetic diversity) or the overall biodiversity theme scores (Supplementary Material Table S8
). This shows that farms with a more intensive pig production system and therefore lower LCA impacts (Table 6
) do not necessarily differ from less intensive farms in terms of their field management to promote biodiversity. This can be explained by the fact that many KPIs not only address ecosystem services, e.g., ecological focus areas, but also equally important other field management aspects (e.g., application of fertiliser based on plant or soil analysis). In summary, good management of the pig farm and the associated crop production leads to a reduction of negative and an enhancement of positive environmental impacts.
This clearly emphasises the need to assess environmental sustainability and provide feedback (e.g., in form of benchmarking with peers) to farmers on their farm-specific performance based on both LCA and KPI assessment. Indeed, this was the intention of the SusPigSys project. Farm-specific LCA results, however, should always be provided with information about the main (emission and resource use) sources, in order that farmers can see where the majority of impacts come from (e.g., feed, mortality, electricity) and how they can improve their LCA results [56
]. This is needed, since to the non-specialists, LCA results are complex, so that farmers may not understand the underlying calculations and sources. Making farmers aware of where resources are being wasted is not only important from an environmental point of view, but also critical from an economical point of view [57
]. Such analysis might therefore serve as incentives for improvements to reduce losses and improve efficiency in the short term, whereas bigger investments (e.g., covering slurry tanks to reduce emissions) may need financial support or incentives (subsidies) from government. Similar, since the benefits of an ecological intensification (e.g., natural pest control) may only be reaped in the long-term, financial support (subsidies) of biodiversity measures and regulatory instruments are complementary pathways to accelerate an ecological intensification [52
4.5. Uncertainity and Other Limitations
Performing LCA and KPI assessments also give rise to a degree of uncertainty in the results. One strengths of the present study presents the use of primary data collected on farm, whenever available. However, this was not possible for all data. For example, we did not calculate the N-balance based on farm-specific data, since we rarely obtained data on feed quality (e.g., on crude protein content). Also, data about the origin and therefore the yield of bought-in feed components were missing on most farms, which also forced us to use default values. Furthermore, LCA impact categories such as toxicity were not included in the present study due to missing and a high uncertainty in LCA back-ground data sets.
Uncertainty in the KPI assessment derived mainly through scaling of indicators and the weighing procedure (Delph-like approach) that was used to aggregate the KPIs on theme level. This uncertainty was addressed in the study of [58
], who found that the variability of weights given for theme biodiversity was intermediate. Due to similar use of the Delphi-like approach, uncertainty introduced by subjective expert weights in the current study is expected to be similar to that in [58
Nevertheless, we suggest to include an uncertainty analysis for both LCA and KPI assessment, in the further development of the SusPigSys tool.