Greenhouse Gas Emissions in Norwegian Agriculture: The Regional and Structural Dimension

Mittenzwei, Klaus

doi:10.3390/su12062506

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…Correlation analysis of variance data was used to extract key structural dimensional parameters by distinguishing the differences between test results caused by changes in sample values of structural dimensional parameters of complex products from changes in test errors [21][22][23]. The sample data of each structural dimensional parameter sampled by the multilevel uniform description sampling method were solved by calculating the statistical matrix of the multiparameter response function after the Nawaf transformation.…”

Section: Dimensional Parameter Extractionmentioning

confidence: 99%

Research on multi-objective collaborative control of complex product development in equipment manufacturing industry

Hao

Yun-xiu

Ren³

2023

Applied Mathematics and Nonlinear Sciences

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Equipment manufacturing involves the integration of multiple technologies and is a complex product system. In the independent innovation of complex product systems, product development is the most important way. Multi-objective cooperative control has been applied to various industries with remarkable results. In this paper, high quality research and development of complex products in equipment manufacturing industry is the main goal. Inspired by the dimensional parameters of the key structures of the product and the structure of the endocrine regulation network, a multi-objective collaborative controller consisting of a speed and position coordinator, a module consisting of a speed and position coordinator, a hormone discriminator, a hormone optimizer, and a controller is designed. The data from the cooperative control study shows that when the controller parameters [3, 1, 2] are used, the velocity parameter is 0.7, the differential parameter is 0.04, and the controller output parameter is 0.8. The force control parameter is 2, the differential parameter is 0.05, and the controller output parameter is 0.7. In the multi-objective cooperative control experiment, the navigator makes a uniform circular or uniform linear motion with [v 1, w 1] T = [0.06,0.09] T . The vector forms r 2 d = [0.4,0.4] T, r 3 d =[−0.1,0.2] T ,. Both the red curve and the blue curve of the follower appear jittered. The experimental curves and control trajectories illustrate that the controller has good control over the vibration and shock phenomena that occur during the position and speed as well as force control of the product. And exhibits good tracking performance. It shows that the multi-objective collaborative controller plays a role in improving the quality of the development of complex products in the equipment manufacturing industry.

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Section: Dimensional Parameter Extractionmentioning

confidence: 99%

Research on multi-objective collaborative control of complex product development in equipment manufacturing industry

Hao

Yun-xiu

Ren³

2023

Applied Mathematics and Nonlinear Sciences

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“…Peter et al (2017) utilized an environmental assessment calculator for the measurement of greenhouse gas emissions from agricultural products [ 30 ]. Mittenzwei (2020) calculated greenhouse gas emissions systematically for different types and sizes of farms in 32 regions with the use of the Jordmod model [ 31 ]. Using farmer survey data and factor coefficients, Chen et al (2020) estimated the carbon footprint of farmers’ agricultural production with a multisystem boundary scenario approach [ 32 ].…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China

Guo

Xie

Pan

2021

IJERPH

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This paper focuses on the impact of changes in planting industry structure on carbon emissions. Based on the statistical data of the planting industry in three provinces in Northeast China from 1999 to 2018, the study calculated the carbon emissions, carbon absorptions and net carbon sinks of the planting industry by using crop parameter estimation and carbon emissions inventory estimation methods. In addition, the multiple linear regression model and panel data model were used to analyze and test the carbon emissions and net carbon sinks of the planting industry. The results show that: (1). The increase of the planting area of rice, corn, and peanuts in the three northeastern provinces of China will promote carbon emissions, while the increase of the planting area of wheat, sorghum, soybeans, and vegetables will reduce carbon emissions; (2). Fertilizer application, technological progress, and planting structure factors have a significant positive effect on net carbon sinks, among which the changes in the planting industry structure have the greatest impact on net carbon sinks. Based on the comprehensive analysis, it is suggested that, under the guidance of the government, resource endowment and location advantages should be given full play to, and the internal planting structure of crops should be reasonably adjusted so as to promote the development of low-carbon agriculture and accelerate the development process of agricultural modernization.

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“…The environmental impacts of the entire agri-food system are multi-faceted and wide-ranging. The negative aspects include primarily greenhouse gas (GHG) emissions and loss of biodiversity [9][10][11][12][13]. Environmental threats are associated with livestock production, which is a major contributor to climate change.…”

Section: Introductionmentioning

confidence: 99%

“…Ruminant production systems contribute to varying greenhouse gas emissions, which depend on the country and region [12,18,23]. Therefore, the IPCC encourages the development of country-specific methane emission estimates, which is crucial to improving the precision of overall global methane emission estimates [18,24].…”

Section: Introductionmentioning

confidence: 99%

Variability of Greenhouse Gas Emissions in Relation to Economic and Ecological Indicators from Cattle Farms

Sieczko,

Koloszko-Chomentowska,

Sieczko

2024

Energies

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Agricultural production, including animal husbandry, is associated with greenhouse gas (GHG) emissions, which have a negative impact on the environment. The purpose of this study was to determine methane and nitrous oxide emissions at the level of individual farms and to identify differences in emissions by type of production. Analyses were conducted using data from the FADN agricultural accounting system, covering the farms in Poland engaged in dairy production and the breeding of other grazing livestock for the period from 2012 to 2021. The relationships and trends of the indicators during the study period were also analyzed. The statistical analysis confirmed the relationship between greenhouse gas emissions and economic performance. In the case of dairy farms, the emissions averaged 137.09 kg·ha−1 of methane and 94.05 kg·ha−1 of nitrous oxide, which were found to increase as the net-added value and farm income increased. The results of the presented research highlight the existence of a link between economic goals and GHG emissions, which is an important contribution to the development of mitigation strategies in livestock production.

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Greenhouse Gas Emissions in Norwegian Agriculture: The Regional and Structural Dimension

Cited by 5 publications

References 14 publications

Research on multi-objective collaborative control of complex product development in equipment manufacturing industry

Research on multi-objective collaborative control of complex product development in equipment manufacturing industry

The Impact of Planting Industry Structural Changes on Carbon Emissions in the Three Northeast Provinces of China

Variability of Greenhouse Gas Emissions in Relation to Economic and Ecological Indicators from Cattle Farms

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