<p>Maintaining environmental balance and reducing the damages caused by climate change anomalies are the basic pillars of sustainable agricultural competitiveness. Applying agricultural sector life cycle assessment (LCA) to achieve both internal (comparative) and external (efficiency enhancing) benefits is a priority.</p><p>The investigated area (Lajta-Project) is located in Kisalföld plain, specifically in the southern part of Mosoni-sík (plain). </p><p>The main cultivated plant species in this agricultural land (2678-2768 ha) are cereals, maize, hemp and canola. There are, on average, 10-15 crops present during a single cultivation cycle. The area is divided into 56 parcels measuring between 20 and 105 ha. The investigation covers the two decade period between 1991 and 2011. We analysed the cultivation data of 5 crops: canola, winter barley, winter wheat, green maize and maize.</p><p>We applied the following methods and models in our life cycle impact assessment: CML2001 (January 2016) method, carbon footprint analysis according to the standard ISO 14067, GaBi impact assessment model for land use and GaBi model for water. In order to represent the overall environmental impact, we used the method of CML2001, Experts IKP (Central Europe).</p><p>Significant impact categories resulted from the average cultivated plant values calculated on 1 ha (territorial approach) were: abiotic depletion pot. (ADP fossil), global warming (GWP 100 years) and marine aquatic ecotoxicity pot. (MAETP inf). </p><p>We compared the yearly time series values on 1 ha and the average yearly values of cultivated plants. According to the resulted ratio, we could define the year of above-average level emission and the year of lower level environmental impact. This provides opportunity to draw further conclusions in the time series assessments of the resulting changes in the local flora and fauna.</p><p>We also summarized the indicator results of appropriate impact categories according to CML2001 method in the studied area by crops which resulted in the territorial environmental footprints of crops for the total time period, namely the ’super footprint’ values. The calculated carbon footprint value specific to the area was 307,000 kg CO<sub>2</sub>-equiv. according to ’super footprint’ approach. The calculated values are clear to interpret by comparison with the similar data or average values of other areas or time periods.</p><p>The obtained results help to better assess environmental impacts, climate risks, and climate change as they pertain to arable crop production technologies, which advances the selection of appropriate technologies that have been adjusted to environmental sensitivities.</p><p>Acknowledgement: Our research was supported by the „Lajta-Project”.</p>

<p>Crop production is applied on about half of Hungary’s land area, which amounts to approximately 4.5 million hectares. The agricultural activity has significant environmental impacts.</p><p>Our work aims the time series investigation of the impacts of large-scale agricultural cultivation<strong> </strong>on environment and primarily on climate change in<strong> </strong>the test area by applying environmental life cycle assessment (LCA) method.</p><p>The investigated area of Lajta Project can be found in the triangle formed by the settlements Mosonszolnok, Jánossomorja and Várbalog, in the north-western corner of Hungary, in Győr-Moson-Sopron county. The area has intense agri-environment characteristics, almost entirely lacking of grasslands and meadows.</p><p>We were looking for the answer to the question “To what extent does agricultural activity on this area impact the environment and how can it contribute to climate change during a given period?” The selection of the plants included in the analysis was justified by their significant growing area. We analysed the cultivation data of 5 crops: canola, winter barley, winter wheat, green maize and maize. Material flows of arable crop production technologies were defined in time series by the agricultural parcel register data. These covered the size of the area actually cultivated, the operational processes, records on seeds, fertilizer and pesticide use and harvest data by parcels. The examined environmental inventory database contained also the fuel consumption and lubricating oil usage of machine operations, and the water usage of chemical utilization.</p><p>In the life cycle modelling of cultivation, we examined 13 years of maize, 20 years of green maize, 20 years of winter barley, 18 years of winter wheat and 15 years of canola data calculated on 1 ha unit using GaBi life cycle analysis software.</p><p>In addition, we also calculated by an average cultivation model for all cultivated plants with reference data to 1 ha and 1 year period.</p><p>We applied methods and models in our life cycle impact assessment. According to the values of the impact categories, we set up the following increasing environmental ranking of plant cultivation: (1) canola has minimum environmental impacts followed by (2) green maize and (3) maize with slightly higher values, (4) winter barley has 6 times higher values preceded by (5) winter wheat with a slight difference. The previous environmental ranking of the specific cultivated plants’ contribution was also confirmed as regards the overall environmental impact: canola (1.0%) – green maize (4.9%) – maize (7.1%) – winter barley (43.1%) – winter wheat (44.0%).</p><p>Environmental impact category indicator results cumulated to total cultivation periods and total crop growing areas (quantitative approach) display the specific environmental footprints by crops. Increasing environmental ranking of environmental impacts resulted from cultivating the sample area is the following: (1) canola – (2) maize – (3) green maize – (4) winter barley – (5) winter wheat. The slight difference resulted in the rankings in quantitative approach according to the rankings of territorial approach on the investigated area is due to the diversity of cultivation time factor and the crop-growing parameter of the specific crops.</p><p>Acknowledgement: Our research was supported by the „Lajta-Project”.</p>