Combine Harvester Fuel Consumption and Air Pollution Reduction

被引:11
作者
Savickas, Dainius [1 ]
Steponavicius, Dainius [1 ]
Kliopova, Irina [2 ]
Saldukaite, Lina [1 ]
机构
[1] Vytautas Magnus Univ, Agr Acad, Inst Agr Engn & Safety, Fac Agr Engn, Kaunas, Lithuania
[2] Kaunas Univ Technol, Inst Environm Engn, Kaunas, Lithuania
关键词
Combine harvester; Telematic system; Air pollution; Engine exhaust; Greenhouse gas emissions (GHG); Environmental control system; GREENHOUSE-GAS EMISSIONS; CARBON FOOTPRINT; RICE PRODUCTION; CO2; EMISSION; ENERGY USE; EFFICIENCY; SOUTHERN; TILLAGE;
D O I
10.1007/s11270-020-4466-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Agricultural production has a major impact on the environment. Indeed, the emissions from agricultural machinery have a significantly negative impact on ambient air, thereby contributing to Climate Change. This study analyses combine harvesters and justifies their optimization in order to increase resource efficiency as well as reduce any negative impact on the environment. Data from 90 combine harvesters in Lithuania and Latvia from 2016 to 2018 is collected using telematics, and the parameters that directly influence engine exhaust emissions are analyzed, such as operation time, grain unloading method, fuel consumption, and auto-steering, according to the engine-operating modes of harvesting, transportation, and idling. Statistically reliable strong correlations can be found between harvesting time and idling time, as well as between fuel consumption during harvesting and idling modes. On average, roughly 20% of the operating time consists of idling and roughly 15% of transportation; moreover, roughly 14% of the diesel fuel is used per year in the aforementioned engine modes. In addition, the auto-steering function enables the efficient use of diesel fuel (average cost per combine harvester is reduced by 0.2 t year(-1)), thereby reducing air pollution (pollution per combine harvester is reduced on average by 0.6 t year(-1)). The results suggest telematics system data can be effectively used for data analysis, problem identification, and decision-making with respect to pollution prevention and optimizing combine harvester operation.
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页数:11
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