Life cycle assessment of tractors

Lee, Jaewon; Cho, Hyejin; Choi, Bokmoon; Sung, Joonyong; Lee, Sungyoung; Shin, Minjong

doi:10.1007/bf02979361

Cited by 35 publications

(15 citation statements)

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“…Manufacturing the tractor, which includes the production of the materials and final assembly, causes 0.4 to 12.1% of the impact scores, depending on the specific impact category. This result is in agreement with Lee et al (2000), who found that 85% of a small (28 kW) tractor's total environmental impact score was due to the use phase, with 11.3% due to manufacturing and distribution, and the remainder due to the end-of-life disposal of the tractor. Within the use phase, supplying and combusting diesel fuel causes most impacts, while maintenance is of secondary importance.…”

Section: System 1 Impacts and Hot Spotssupporting

confidence: 92%

Environmental hot spot analysis in agricultural life-cycle assessments � three case studies

Piringer¹,

Bauer²,

Gronauer³

et al. 2016

JCEA

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Present-day agricultural technology is facing the challenge of limiting the environmental impacts of agricultural production -such as greenhouse gas emissions and demand for additional land -while meeting growing demands for agricultural products. Using the well-established method of life-cycle assessment (LCA), potential environmental impacts of agricultural production chains can be quantified and analyzed. This study presents three case studies of how the method can pinpoint environmental hot spots at different levels of agricultural production systems. The first case study centers on the tractor as the key source of transportation and traction in modern agriculture. A common Austrian tractor model was investigated over its life-cycle, using primary data from a manufacturer and measured load profiles for field work. In all but one of the impact categories studied, potential impacts were dominated by the operation phase of the tractor's life-cycle (mainly due to diesel fuel consumption), with 84.4-99.6% of total impacts. The production phase (raw materials and final assembly) caused between 0.4% and 12.1% of impacts, while disposal of the tractor was below 1.9% in all impact categories. The second case study shifts the focus to an entire production chain for a common biogas feedstock, maize silage. System boundaries incorporate the effect of auxiliary materials such as fertilizer and pesticides manufacturing and application. The operation of machinery in the silage production chain was found to be critical to its environmental impact. For the climate change indicator GWP100 (global warming potential, 100-year reference period), emissions from tractor operation accounted for 15 g CO 2 -eq per kg silage (64% of total GWP100), followed by field emissions during fertilizer (biogas digestate) application with 6 g CO 2 -eq per kg silage (24% of total GWP100). At a larger system scale that includes a silage-fed biogas plant with electricity generated by a biogas engine, silage cultivation operations are no longer the largest contributor; the most important contributor (49.8%) is methane slip from the exhaust of the biogas engine. In the third case study, the biogas plant model is 1732 incorporated into an even larger system, where the existing waste management and energy system in an Alpine municipality of Western Austria is expanded to include a hypothetical system that uses mainly hay from currently unused alpine grassland in a local biogas plant. Here, the relative environmental impacts depend strongly on the fossil fuels that are assumed to be displaced by the local biogas plant; methane slip emissions from the exhaust dominate the impact of the hypothetical local biogas scenario. Taken together, the case studies demonstrate the potential and limitations of LCA as a technique to support decisions of agricultural stakeholders at a variety of scales. Choosing the proper system scale is key to a successful application of this method. 477Journal of Central European Agriculture, 2016, 17(2), p.477-492 DOI: 1...

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Section: System 1 Impacts and Hot Spotssupporting

confidence: 92%

Environmental hot spot analysis in agricultural life-cycle assessments � three case studies

Piringer¹,

Bauer²,

Gronauer³

et al. 2016

JCEA

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show abstract

“…On the basis of the above, the indirect energy is differentiated between the machinery and repair and maintenance embodied energy (MJ • kg −1 ), as well as the housing embodied energy (MJ • m −2 • y −1 ). The machinery embodied energy refers to the energy required to manufacture the agricultural equipment [20,29]. The embodied energy of repair and maintenance can be either expressed as a percentage of the manufacturing energy requirements [30,31] or can be estimated in absolute numbers, as attempted by Mantoam et al [32].…”

Section: Energy Cost Of Agricultural Operationsmentioning

confidence: 99%

Energy Footprint of Mechanized Agricultural Operations

et al. 2020

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The calculation of the energy cost of a cultivation is a determining factor in the overall assessment of agricultural sustainability. Most studies mainly examine the entire life cycle of the operation, considering reference values and reference databases for the determination of the machinery contribution to the overall energy balance. This study presents a modelling methodology for the precise calculation of the energy cost of performing an agricultural operation. The model incorporates operational management into the calculation, while simultaneously considering the commercially available machinery (implements and tractors). As a case study, the operation of tillage was used considering both primary and secondary tillage (moldboard plow and field cultivator, respectively). The results show the importance of including specific operation parameters and the available machinery as part of determining the accurate total energy consumption, even though the field size and available time do not have a significant effect.

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“…For the tractor and mechanical implement LCA modules, we applied the approach suggested by Lee et al (2000). All stages in the life cycle of tractors from material acquisition to disposal were accounted for ( Figure 1A).…”

Section: Description Of the Systemmentioning

confidence: 99%