Developing a Spatial Emission Inventory of Agricultural Machinery in Croatia by Using Large-Scale Survey Data

Šimun Lončarević (), Petar Ilinčić, Zoran Lulić and Darko Kozarac
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Šimun Lončarević: Energy Institute Hrvoje Požar, Savska cesta 163, HR-10000 Zagreb, Croatia
Petar Ilinčić: Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, HR-10000 Zagreb, Croatia
Zoran Lulić: Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, HR-10000 Zagreb, Croatia
Darko Kozarac: Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, HR-10000 Zagreb, Croatia

Agriculture, 2022, vol. 12, issue 11, 1-18

Abstract: Agricultural machinery has an essential impact on climate change. However, its emission data are often missing, which makes it harder to develop policies which could lower its emissions. An emission inventory should first be developed to understand the impact of agricultural machinery on climate change. This article presents a spatial variation of emissions from agricultural machinery in Croatia. Data on agricultural machinery for 2016 was collected via a large-scale survey with 8895 respondents and included machinery type, location data, and fuel consumption by fuel type. Data processing was conducted to optimize the survey results, and the emissions were calculated using the “EEA/EMEP Emission Inventory Guidebook” Tier 1 method. The research shows that two-axle tractors with engine power 61–100 kW had the most significant energy consumption and were responsible for most of the emissions. The highest total emissions were in counties in the Slavonia region, while counties in the Dalmatia region had the highest emissions per hectare of arable land. Results obtained this way enable policies to be developed that will target specific spatial areas and machinery types. Furthermore, this approach could allow precise spatial and temporal emission tracking. A designated institution which could conduct annual surveys and update the agricultural machinery emission data would ensure emission data continuity.

Keywords: climate change; agricultural machinery; emission inventory; non-road emissions; NRMM (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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