Scholarly article on topic 'Organic Versus Conventional Farming: The Case of wheat Production in Wallonia (Belgium)'

Organic Versus Conventional Farming: The Case of wheat Production in Wallonia (Belgium) Academic research paper on "Agriculture, forestry, and fisheries"

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Abstract of research paper on Agriculture, forestry, and fisheries, author of scientific article — Florence Van Stappen, Astrid Loriers, Michaël Mathot, Viviane Planchon, Didier Stilmant, et al.

Abstract The environmental impact of wheat production was assessed through Life Cycle Assessment (LCA). Local data were collected to characterize Walloon conventional and organic wheat production systems. Two functional units (FU) were investigated: 1kg of wheat grains at 15% humidity and 1ha used for wheat cropping. An uncertainty analysis assessed the significance of differences between conventional and organic systems. Using 1kg of grains as FU, results are not significantly different in global warming and cumulative energy demand. Very highly significant differences for soil acidification and eutrophication, and significant differences for agricultural land occupation were found to be in favor of conventional wheat production. Due to the high yield level in conventional farming (8.5 t/ha at 15% humidity against 4.5 t/ha for organic wheat), organic winter wheat has an equivalent or even, in some impact categories, a higher impact than conventional winter wheat. Using 1ha as FU, organic production is less impacting than conventional production, except for soil acidification and eutrophication. The choice of the FU has proven to be very sensitive. This study could be improved by accounting for rotation effects, by using more specific models to calculate emissions due to organic and mineral fertilization, and by accounting for carbon storage in soil.

Academic research paper on topic "Organic Versus Conventional Farming: The Case of wheat Production in Wallonia (Belgium)"

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Agriculture and Agricultural Science Procedia 7 (2015) 272 - 279

Farm Machinery and Processes Management in Sustainable Agriculture, 7th International

Scientific Symposium

Organic versus conventional farming: the case of wheat production

in Wallonia (Belgium)

Florence Van Stappena*, Astrid Loriersb*, Michaël Mathotb, Viviane Planchonb,

Didier Stilmantb, Frédéric Debodec

Agricultural Machines and Facilities Unit, Walloon Agricultural Research Centre (CRA-W), 146 chaussée de Namur, 5030 Gembloux, BelgiumbFarming Systems, Territory and Information Technologies Unit, CRA-W, 100 rue du Serpont, 6800 Libramont, Belgium Authentication and traceability of agricultural productsUnit, CRA-W, 24 chaussée de Namur, 5030 Gembloux, Belgium

Abstract

The environmental impact of wheat production was assessed through Life Cycle Assessment (LCA). Local data were collected to characterize Walloon conventional and organic wheat production systems. Two functional units (FU) were investigated: 1 kg of wheat grains at 15% humidity and 1 ha used for wheat cropping. An uncertainty analysis assessed the significance of differences between conventional and organic systems. Using 1 kg of grains as FU, results are not significantly different in global warming and cumulative energy demand. Very highly significant differences for soil acidification and eutrophication, and significant differences for agricultural land occupation were found to be in favor of conventional wheat production. Due to the high yield level in conventional farming (8.5 t/ha at 15% humidity against 4.5 t/ha for organic wheat), organic winter wheat has an equivalent or even, in some impact categories, a higher impact than conventional winter wheat. Using 1 ha as FU, organic production is less impacting than conventional production, except for soil acidification and eutrophication. The choice of the FU has proven to be very sensitive. This study could be improved by accounting for rotation effects, by using more specific models to calculate emissions due to organic and mineral fertilization, and by accounting for carbon storage in soil. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the Centre wallon de Recherches agronomiques (CRA-W) Keywords:Life cycle assessment (LCA); organic farming; wheat; environmental impact.

* These authors contributed equally to this work. Corresponding author. Tel.: +32-81-627-185; fax: +32-81-615-847. E-mail address:f.vanstappen@cra.wallonie.be

2210-7843 © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the Centre wallon de Recherches agronomiques (CRA-W) doi: 10.1016/j.aaspro.2015.12.047

1. Introduction

There is an increasing awareness among western consumers regarding their behavior matching sustainable development, translated by a modification of some food consumption habits. The demand for organically sourced products is in constant increase in Europe, as in Wallonia (southern Belgium) where, between 2005 and 2011, the number of organic farms has risen of 49% (DGSIE, 2010) and represents up to 7% of the Utilized Agricultural Area (UAA) (Debode et al., 2013). Organic products are often perceived as more environmentally-friendly than their conventional counterparts. Do these prejudices reflect the truth? European consumers ask for more information on environmental impacts of food products (European Commission, 2013). This explains why European countries are eager to promote environmental labeling and sustainable food products.

It is therefore crucial to be able to determine more precisely the carbon footprint and more globally the environmental impacts of food products. The Life Cycle Assessment (LCA) methodology is appropriate to reach such a goal (Andersson, 2000).

Using the LCA standardized method (ISO 14040, 2006), the aim of this study is to assess and compare the environmental impacts of organic and conventional wheat. It aims at highlighting environmental hotspots of both production modes and identifying limitations of LCAs conducted on organic productions.

2. Methods

The system boundaries of both systems include all production steps from the field to the farm gate, including machinery production and use, inputs (fertilizers, pesticides and seeds) production, transport and use, and land occupation. Two functional units (FU) are investigated and compared: 1 kg fresh matter (FM, 85% of dry matter) of wheat and 1 hectare (ha) of wheat-cropped area.

2.1. Inventory data collection

Data on conventional wheat production in Wallonia (reference year 2010) are provided by Van Stappen et al., (submitted to the International Journal of Life Cycle Assessment). This conventional wheat has a grain yield of 8,350 kgFM/ha and a straw yield of 3,600 kgFM/ha. Generic data are extracted from the ecoinvent database (Nemecek and Kagi, 2007).

Table 1. Itinerary of organic and conventional wheat

Process units Conventional wheat Organic wheat

Area in Wallonia ha 139 488 584

Skim ploughing 1.5 passages, tractor 300 cv, deep 1 passage, tractor 100 cv, disc tiller,

skim ploughing before sowing mounted 3.5m

Seeds kg/ha 160 200

Organic fertilizer kg N/ha 7 144

kg P2O5/ha 3.9 64.8

kg K2O/ha 5.8 145.2

Mineral fertilizer kg N/ha 182 0

kg P2O5/ha 3 0

kg K2O/ha 5 0

Crop protection phytosanitary treatment, 3 passages mechanical weeding, 2 passages,

sprayer spiked chain harrow, 12m

Harvesting 1 passage, tractor 350 cv, combine 1 passage, combine harvester 5m

harvester 7m30

Swath drying 0.5 passage, windrower 4m , 0.5 passage, windrower 4m, tractor

tractor 120 cv 120 cv

Baling 1 passage, 120*7cm, tractor 120 cv 1 passage, 120*7cm, tractor 120 cv

Production data for organic wheat are provided by local studies (Montignies et al., 2011, Debode et al., 2013) (Table 1). Organic wheat has a grain yield of 4,500 kgFM/ha and a straw yield of 2,500 kgFM/ha. Agricultural work processes are based on agricultural pathways defined by experts. Data from the Mecacost tool (Rabier et al., 2008) are used to calculate emissions due to machinery use with the adaptation of fuel consumption, work duration, life duration, nominal and mean powers, and machinery weights. Emission factors for fuel combustion and tire abrasion come from Nemecek and Kagi (2007).

For both conventional and organic wheat production, impacts from the production of organic fertilizers are entirely attributed to animal rearing. Only fertilizers transport and use on field are considered in this study.

Field emissions due to inputs (fertilizers, pesticides, seeds) application during crop cultivation are assessed using emission models, following recommendations by Nemecek (2013). Ammonia (NH3) emissions to air are calculated according to fertilizers nitrogen (N) content and using emissions factors from Tier 2 technology-specific models by EMEP/EEA (2013a, b). Nitrate ion (NO3-) emissions to groundwater are based on the model SALCA-Nitrat by Richner et al. (2006) adapted to local conditions with respect to cropping duration, date of N application, N mineralization potential in soils, N uptake by vegetation and risk of N leaching. Nitrogen oxides (NOx) emissions to air are calculated from EMEP/EEA Tier 1 approach (EMEP/EEA, 2013b) and nitrous oxide (N2O) are estimated from IPCC Tier 1 guidelines (IPCC, 2006). Phosphorous emissions to river (phosphorus (P) and phosphate ion (PO43-)) and to groundwater (PO43-) are based on the SALCA-phosphor model by Prasuhn (2006). Trace metal (cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), mercury (Hg), nickel (Ni), zinc (Zn)) balances and related emissions to groundwater, river and agricultural soil are calculated from the SALCA-Schwermetall model by Freiermuth (2006) adapted to local conditions with respect to trace metal contents of mineral and organic fertilizers (Piazzalunga et al., 2012), soil (Sonnet et al., 2003), and plant material and annual deposition (Koch and Salou, 2013).

2.2. Allocation between co-products

Cereal cultivation is an indivisible multi-output product system delivering two co-products, grain and straw, both having agronomic and economic values. While cereals are generally cultivated for grain production, farmers sometimes choose to crop a few cereal hectares in order to harvest straw for animal litter or feed. Straw has no matter what an undisputable role in soil carbon and soil structure management, whether left on the field or returned to the latter as farmyard manure. For this reason the impacts of wheat production are allocated between grain and straw according to their respective prices on the Walloon market.

2.3. Life Cycle Impact Assessment

The evaluation of the environmental impacts or Life Cycle Impact Assessment (LCIA) is supported by a composite method at mid-point level constructed according to the ILCD handbook (European Commission et al., 2011). The LCA software used is SimaPro 8.0.4.30 (PRé, 2015). Selected impact categories, related indicator units and reference method are listed in Table 2.

Table 2. Selected impact categories, related indicator units and reference method used for LCIA.

Abbreviation Impact category

Indicator Unit

Reference method

Gwp Global warming potential with a timeframe of 100 years

HTP Human toxicity potential

TAP Terrestrial acidification potential

EUP Eutrophication potential

AEP Aquatic ecotoxicity potential

ALO Agricultural land occupation

WDP Water depletion potential

POF Photochemical oxidant formation

kg CO2 eq.

10-6 CTUh (Comparative Toxic Units) 10-6 kg SO2 eq. 10-6 kg PO43- eq.

10-3 CTUe (Comparative Toxic Units) m2y (m2.year) 10-3 m3

10-3 kg NMVOC

(IPCC, 2013)

USEtox (Rosenbaum et al., 2008) (Posch et al., 2008)

CML-IA baseline v4.2 (Guinée et al., 2002) USEtox (Rosenbaum et al., 2008) ReCiPe v1.11 (Goedkoop et al., 2009) ReCiPe v1.11 (Goedkoop et al., 2009) ReCiPe v1.11 (Goedkoop et al., 2009)

Abbreviation Impact category Indicator Unit Reference method

CED Cumulative Energy Demand 10-3 MJ (Frischknecht et al., 2007)

2.4. Uncertainty analyses

Uncertainty analyses aim at determining how uncertainties in data and assumptions progress in the calculations and how they affect the reliability of the results of the LCIA (ISO, 2006b). In this work uncertainty analyses are run using Monte-Carlo (MC) simulations implemented in SimaPro 8.0.4.30 (Hedemann and Konig, 2003, PRe, 2015). MC simulations performed in SimaPro account for uncertainty in input and output inventory data but not for uncertainties tied to impact characterization factors. It is therefore proposed to mitigate our uncertainty results with semiquantitative analysis based on expert judgment as recommended by Jolliet et al. (2010). They recommend minimum 10 % difference in order to declare results are significantly different in GWP and CED categories. For TAP and EUP, this minimum difference has to reach 30 %. Regarding HTP and AEP, one or even two orders of magnitude are necessary to declare two contributions are significantly different, considering the high uncertainty on impact characterization factors and the huge number of substances playing a role in toxicity impacts. In order to account for this uncertainty mitigation in our results, significant differences are invalidated when the above-mentioned minimum difference between compared results is not reached.

3. Results

is 100

70 60 50 40 30 20 -10 0 -10

org conv org conv org conv org conv org conv org conv org conv org conv org conv

Fig. 1. LCIA results by impact category for the production of 1 kgFM of organic (org) and conventional (conv) wheat. • Crop effect (emissions tied to land occupation), • Mechanization, • Transport, • Seeds, • Mineral fertilizers production, • Pesticides production, • Emissions due to mineral fertilizers use, • Emissions due to organic fertilizers use, Pesticides emissions.

Environmental impacts results per kg of organic wheat (Table 3 and Fig. 1) show the major contribution of emissions due to organic fertilizer use in most impact categories. These emissions contribute to 51 %, 91%, 97%, 89%, 86% and 53% of the total impact in GWP, HTP, TAP, EUP, AEP and POF, respectively. Among these, we note that NH3 emissions are directly responsible for 96% and 49% of the total impact in TAP and EUP, respectively, and indirectly, via N2O emissions, responsible for 20% of the total GWP impact.

Regarding the conventional production of 1 kgFM of wheat, mineral fertilization is the most impacting step representing 74% of GWP, 94% of HTP, 95% of TAP, 69% of EUP, 63% of AEP, 87% of WDP, 87% of POF and

69% of CED. Mechanization has also a substantial impact in organic and conventional wheat production in the categories GWP (26 and 9%), WDP (16 and 9%), POF (43 and 8%) and CED (75 and 26%). In conventional cropping, the impact of pesticides production and application is limited to AEP (32%), WDP (1.8%) and CED (3%).

Table 3. LCIA results for organic and conventional wheat production, using 1 kgFM and 1 ha as functional unit (FU).

FU Production mode GWP kg CO2 eq. HTP 10-6 CTUh TAP 10-6 kg SO2 eq. EUP 10-6 kg PO43- eq. AEP 10-3 CTUe ALO m2y WDP 10-3 m3 POF 10-3 kg NMVOC CED 10-3 MJ

Org 0.307 2.246 0.103 0.013 0.004 1.6 0.149 1.3 0.001

1 kgFM

Conv 0.349 0.150 0.015 0.002 0.007 0.868 0.861 0.993 0.002

Org 1382 10109 462.7 56.6 18.6 7270 672 5793 6.7

Conv 2991 1283 141.7 19.4 59.4 7419 7360 8489 163.6

Org: organic; Conv: conventional

MC simulations (Table 4) have been conducted to identify significant differences between organic and conventional wheat production. Using 1 kgFM as FU, MC simulations reveal very highly significant differences (p <0.001) for TAP and EUP, and significant differences (p<0.05) for ALO and POF. MC simulations using 1 ha as FU conclude to very highly significant differences in GWP, TAP, EUP and CED, and highly significant differences in POF. Organic production shows lower impacts than conventional production in GWP, POF and CED, but higher impacts in TAP and EUP.

Table 4. Monte-Carlo (MC) simulations comparing organic and conventional wheat production, using 1 kgFM and 1 ha as functional unit

FU GWP HTP TAP EUP AEP ALO WDP POF CED

1 kgFM 0.133 (**) *** *** (***) ** 0.418 * 0.054

1 ha *** 0.222 *** *** (***) 0.468 0.456 ** ***

*** p<0.001: very highly significant differences; ** p<0.01: highly significant differences; * p<0.05: significant differences; p values for not significant differences (p>0.05) are indicated; invalidated results (see section 2.4) are displayed between brackets.

4. Discussion

When using 1 kgFM as FU, organically produced wheat has significantly higher environmental impacts than conventional wheat in TAP, EUP, ALO and POF categories. This better performance of conventional wheat production is partly explained by yield differences: 8.5 tFM/ha for conventional wheat (DGSIE, 2010) against 4.5 tMF/ha for organic wheat (Montignies et al., 2013).

Additionally, for an equivalent nutrient supply, organic fertilization induces more important impacts than mineral fertilization. This is explained by model emissions factors for NH3 volatilization which are higher for organic N fertilizers than for mineral fertilizers (EMEP/EEA, 2013b, IPCC, 2006, Nemecek and Schnetzer, 2011). These factors affect NH3 and NOx emissions and indirect N2O emissions, contributing to TAP, EUP and GWP. Considering the important contribution of NH3 emissions to these impact categories, a more accurate evaluation of those emissions is crucial.

Nitrogenous and phosphorous emissions from mineral and organic fertilizers application on field are calculated from Tier 1 or Tier 2 emission models accounting partly for specific soil, practices, crop rotations or climate conditions. Even though those models are recommended by widely used databases such as ecoinvent, they introduce uncertainty in the results. More specific crop models have proven their relevance (Bessou et al., 2012, Godard et al., 2012, Williams et al., 2010) and may be transposed to our region in order to refine our conclusions.

When using 1 ha as FU, organic wheat is more environmentally-friendly than conventional wheat in GWP, POF and CED impact categories.

Results are highly sensitive towards the choice of the functional unit, as already observed in other studies comparing organic and conventional farming (Hayashi, 2013, Mondelaers et al., 2009). Mass (kg) can be selected because this FU reflects more accurately the role of agriculture which is to provide biomass for food and non-food uses rather than to occupy land. Production is indeed the central purpose of agricultural systems, while landscape upkeep comes secondary (Charles et al., 2006). The land area unit (ha) could be a suitable choice if the goal of the study is to assess which agricultural practices (organic or conventional) put less environmental pressure on land (land being seen as a finite and fragile resource) (Jolliet et al., 2010). The area FU brings information on the intensity in the use of agricultural inputs, while the efficiency of production systems is taken into account by a mass FU (Charles et al., 2006). It is therefore essential to define the product function in a study comparing organic with conventional farming.

Results are also highly dependent on input application and on organic fertilization in particular. Any change in organic fertilization would therefore alter results substantially. In the definition of the cropping plan for organic wheat production used in this study, solid cattle manure has been considered as the sole organic fertilizer. However Abras (2014) showed that the organic fertilizer type, and its related N, P and K contents, influences wheat yields.

Furthermore, no information on nutrient and trace metal contents of organic fertilizers was available and conventional data were used. According to Cooper et al. (2011), it seems, however, that, in the case of wheat production among others, fertilization practices in organic production would decrease trace metal export by grains by 42% for Cd, 11% for Cu and 18% for Zn, but on the contrary increase Ni export by 23%. Trace metal contents of animal diets and manure are consequently influenced by agricultural practices (organic or conventional). Field emissions from organic fertilizer application may therefore have been overestimated. Laboratory analyses of nutrient and trace metal contents of organic fertilizers would be useful to refine those emission calculations.

Finally considering whole rotations and not only the annual wheat crop would enable to account for nutrient leftovers by preceding and for subsequent crops. It is indeed likely that subsequent crops benefit from cattle manure applied on organic wheat (van Zeijts et al. 1999). Besides, wheat crops do not generally come first in the rotation scheme and as such do not receive P and K nutrition. However they benefit from leftovers from preceding crops and these nutrients influence their yields. Allocating the organic fertilization at the rotation level would enable to consider the impacts attributable to the considered crop only and may reduce estimated impacts from the fertilization of organic wheat.

For lack of specific data, stock changes in soil organic carbon (SOC) were not accounted for. However, in future works, accounting for SOC stock changes using IPCC (2003) Tier 3 or other methods already tested in agricultural LCAs in Western Europe (Godard et al., 2012, Godard et al., 2013, Saffih-Hdadi and Mary, 2008) would be an asset, especially for assessing SOC changes induced by management practices such as reduced tillage or no-till (Snyder et al., 2009) used in conventional or organic farming.

5. Conclusion

Using the LCA methodology, this study aimed at comparing the environmental impacts of organic and conventional production of wheat.

Results are very sensitive to the choice of the functional unit. When compared on the basis of the mass (kg), organically cropped wheat seems to induce more environmental impacts than conventionally cropped wheat in terms of acidification, eutrophication, land occupation and photo-oxidants formation. Overall the most influential parameter seems to be the yield. With yields among the highest in the world, the well mastered production of conventional wheat in Wallonia shows smaller impacts than lower yielding organic wheat. However, on the basis of the land area (ha), organic wheat is more environmentally-friendly than conventional wheat in terms of global warming, photo-oxidants formation and energy demand.

Emissions from fertilizer application on field predominate in the results. Using more specific emission models would improve the quality of the results. Specific data for nutrient and trace metal contents would also enable to enhance results precision.

Accounting for the whole rotation would also help to allocate more accurately fertilizers applied for the whole rotation and benefiting to successive crops. Considering organic carbon storage from managed soils would also help refine results.

Beside environmental criteria, taking account of social and economic impacts, such as working conditions and added value distribution all along the processing chain, would allow to encompass other aspects of the sustainability of organic and conventional wheat production in Wallonia.

Acknowledgements

The authors wish to thank the Walloon Agricultural Research Centre (CRA-W) who finances this research. They are grateful to the numerous agricultural advisors and experts who patiently gave their time during data collection.

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