Greenhouse emissions and air pollutants pose a global threat to the environment and human health. Emission inventories are a valuable tool in understanding emission sources and their overall impact on the environment. Most cities and countries do not include non-road mobile machinery (NRMM) when compiling emission inventories. Furthermore, little effort has been made to understand better the impact of this source of emissions on the environment. For these reasons, this research examines the data from the existing NRMM emission inventories and other studies concerning NRMM emissions. After careful literature review, three main problems in creating a national NRMM emission inventory are identified and reviewed: lack of a comprehensive list of NRMM and their activity data, lack of emission factor data, and lack of research. The data from the existing inventories show that compared to some emissions, NRMM has a three times larger proportion of emissions compared to the proportion of energy consumption. Furthermore, there are significant differences in total emissions when comparing the same pollutants among different countries. A general lack of data is the common denominator for all these problems and can only be solved by creating national NRMM databases operated by a designated institution. This institution must be able to annually update relevant NRMM data through questionnaires and experimental research on the existing NRMM.

Agricultural tractor emissions have a notable influence on total emissions and climate change. This is especially important when developing an agricultural machinery emission inventory since tractors are the most widely used agricultural machinery. However, as with other agricultural machinery, there is a significant lack of data concerning tractors. This study combined two large-scale datasets to develop a Tier 2 tractor emission inventory for the Republic of Croatia. The first dataset, which was collected via a large-scale survey with 8895 respondents, includes data on fuel consumption by machine and engine type. The second dataset, which is official data of the Ministry of the Interior, includes data on machinery age. Since there is no direct link between datasets, data on fuel consumption were calculated for each of 21 Croatian counties and were then linked to the corresponding municipalities’ tractor age and power rating of the vehicle fleet. The result was used to calculate tractor emissions by with a Tier 2 approach using the method listed in the 2019 EMEP/EEA emissions guidebook. The calculations were made for five exhaust emission components: carbon dioxide (CO₂), carbon monoxide (CO), hydrocarbon (HC), nitrogen oxide (NO_X) and particulate matter (PM). The continental counties had the highest emissions for all emission types, especially the Osječko-baranjska and Vukovarsko-srijemska counties. The Tier 2 emission inventory was compared to data calculated using the Tier 1 method on a county level. There were notable differences between the inventories for HC and PM emissions, which is mainly due to Tier 2 approach having different emission factors depending on vehicle age. The end result was compared to the already existing Tier 1 emission inventory on a county level.

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.

U radu se istražuje odnos Bonifacija Perovića prema liberalizmu, komunizmu i znanstveno-tehnološkoj revoluciji. Pripadajući personalističkom krugu hrvatskih katoličkih intelektualaca, Perović je prije i nakon Drugoga svjetskoga...