Spatio-temporal patterns of energy consumption-related GHG emissions in China's crop production systems

Abstract Easy-to-use tools using modern data analysis techniques are needed to handle spatio-temporal agri-data. This research proposes a novel pattern recognition-based method, Multi-temporal Yield Pattern Analysis (MYPA), to reveal long-term (> 10 years) spatio-temporal variations in multi-temporal yield data. The specific objectives are: i) synthesis of information within multiple yield maps into a single understandable and interpretable layer that is indicative of the variability and stability in yield over a 10 + years period, and ii) evaluation of the hypothesis that the MYPA enhances multi-temporal yield interpretation compared to commonly-used statistical approaches. The MYPA method automatically identifies potential erroneous yield maps; detects yield patterns using principal component analysis; evaluates temporal yield pattern stability using a per-pixel analysis; and generates productivity-stability units based on k-means clustering and zonal statistics. The MYPA method was applied to two commercial cereal fields in Australian dryland systems and two commercial fields in a UK cool-climate system. To evaluate the MYPA, its output was compared to results from a classic, statistical yield analysis on the same data sets. The MYPA explained more of the variance in the yield data and generated larger and more coherent yield zones that are more amenable to site-specific management. Detected yield patterns were associated with varying production conditions, such as soil properties, precipitation patterns and management decisions. The MYPA was demonstrated as a robust approach that can be encoded into an easy-to-use tool to produce information layers from a time-series of yield data to support management.

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Study of energy consumption and greenhouse gas (GHG) emissions in corn production systems: influence of different tillage systems and use of fertilizer

Communications in Soil Science and Plant Analysis ◽

10.1080/00103624.2020.1729373 ◽

2020 ◽

Vol 51 (6) ◽

pp. 769-778

Author(s):

Amin Fathi ◽

Davood Barari Tari ◽

Hormoz Fallah Amoli ◽

Yousef Niknejad

Keyword(s):

Energy Consumption ◽

Greenhouse Gas ◽

Production Systems ◽

Ghg Emissions ◽

Tillage Systems ◽

Corn Production

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Optimizing Energy Consumption in Internal Transportation Using Dynamic Transportation Vehicles Assignment Model: Case Study in Printing Company

Energies ◽

10.3390/en14154557 ◽

2021 ◽

Vol 14 (15) ◽

pp. 4557

Author(s):

Vitalii Naumov ◽

Daniel Kubek ◽

Paweł Więcek ◽

Iwona Skalna ◽

Jerzy Duda ◽

...

Keyword(s):

Energy Consumption ◽

Production Systems ◽

Significant Proportion ◽

Ghg Emissions ◽

Production Environment ◽

Model Case ◽

Heterogeneous Fleet ◽

Proposed Model ◽

Delivery Routes ◽

Reduction Of Energy Consumption

Energy costs account for a significant proportion of total costs in production systems. Since energy is becoming an increasingly expensive resource, therefore, it is critical to consume it as efficiently as possible. Focusing on energy efficiency is also important in terms of reducing greenhouse gas (GHG) emissions and the effects of other pollutants on the environment. One of the possible ways for businesses to reduce energy consumption is to use available transportation means as efficiently as possible. In the operational phase, this can be achieved by reducing unnecessary transport, selecting the most efficient delivery routes, and by optimized assignment of available vehicles to transportation orders. We present in this article a novel dynamic assignment of transportation orders to fleet with energy minimization criterion in internal transport system of a printing company. The novelty of the proposed model is that, in contrast to most existing models, it can handle a heterogeneous fleet of human-operated and autonomous mobile robots (AMRs). The minimization of the energy consumption by transportation vehicles was modeled with reference to VDI 2198 standard. The need for such a model is justified by the fact that it better reflects a real production environment in many companies. The proposed optimization model was tested in simulation experiments imitating real production conditions in a large web printing house. The obtained results show that the proposed model allows for a significant reduction of energy consumption in internal transportation. The proposed model is general enough to be used in various companies with a heterogeneous fleet of internal transportation vehicles. In addition, the energy consumption factor VDI for AMRs has been determined, which can be useful in solving various problems related to energy optimization of internal transportation.

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Analysis of spatio-temporal patterns of carbon emission from energy consumption by rural residents in China

Acta Ecologica Sinica ◽

10.5846/stxb201607191466 ◽

2017 ◽

Vol 37 (19) ◽

Author(s):

万文玉 WAN Wenyu ◽

赵雪雁 ZHAO Xueyan ◽

王伟军 WANG Weijun ◽

薛冰 XUE Bing

Keyword(s):

Energy Consumption ◽

Carbon Emission ◽

Temporal Patterns ◽

Rural Residents ◽

Spatio Temporal

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Examining Farmers’ Adoption Decisions towards Precision-Agricultural Practices in Greek Dairy Cattle Farms

Sustainability ◽

10.3390/su14010411 ◽

2021 ◽

Vol 14 (1) ◽

pp. 411

Author(s):

Georgios Kleftodimos ◽

Leonidas Sotirios Kyrgiakos ◽

Christina Kleisiari ◽

Aristotelis C. Tagarakis ◽

Dionysis Bochtis

Keyword(s):

Dairy Cattle ◽

Precision Agriculture ◽

Crop Production ◽

Production Systems ◽

Management Strategies ◽

Ghg Emissions ◽

Agricultural Practices ◽

Adoption Decisions ◽

Alternative Practices ◽

Cattle Farms

Nowadays, the sustainability of Greek dairy cattle farms is questionable due to low competitiveness and high GHG emissions. In this context, the BIOCIRCULAR project, funded by the EYDE ETAK, developed a series of alternative practices focusing on precision agriculture principles. However, the adoption of any practice from farmers is not a given, and depends on several determinants. Hence, the objective of this study is to examine farmers’ adoption decisions regarding precision-agricultural practices in Greek dairy production systems, as well as the economic and environmental impacts of this adoption. In order to achieve this, a bio-economic model was developed based on mathematical programming methods. The proposed model simulates a large number of dairy cattle farms with or without crop production, including different management strategies and their relevant costs, and provides an environmental assessment of the adopted practices based on GHG emissions. Moreover, in order to analyze farmers’ adoption decisions, different policy measures, linked to various environmental outcomes, were examined. The results highlighted that the adoption of precision-agricultural practices led to significantly better economic and environmental outcomes. Furthermore, it was found that different levels of incentives can be efficiently targeted to encourage the adoption of new feeds and, more broadly, to secure the sustainability of the sector.

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Life Cycle Assessment of Sustainable Broiler Production Systems: Effects of Low-Protein Diet and Litter Incineration

Agriculture ◽

10.3390/agriculture11100921 ◽

2021 ◽

Vol 11 (10) ◽

pp. 921

Author(s):

Akifumi Ogino ◽

Kazato Oishi ◽

Akira Setoguchi ◽

Takashi Osada

Keyword(s):

Climate Change ◽

Life Cycle Assessment ◽

Energy Consumption ◽

Environmental Impacts ◽

Broiler Chicken ◽

Production Systems ◽

Ghg Emissions ◽

Manure Management ◽

Low Protein ◽

Broiler Production

We conducted a life cycle assessment (LCA) to compare environmental impacts of conventional (CNV) broiler chicken production in Japan with those of three mitigation options: a low-protein diet supplemented with more crystalline amino acids (LP), incineration of broiler litter (IC), and their combination (LP + IC). Feed production, feed transport, broiler housing, and manure management were included in the LCA, with 1 kg of liveweight of broiler chicken as the functional unit. The CNV environmental impacts were: climate change, 1.86 kg CO2e; acidification, 52.6 g SO2e; eutrophication, 18.3 g PO4e; energy consumption, 18.8 MJ. Since broiler manure management has a lower N2O emission factor, the LP diet’s effects on greenhouse gas (GHG) emissions were limited. Because a large amount of ammonia is emitted from broiler-litter composting and the LP diet reduced nitrogen excretion and consequent NH3 emission, the LP showed lower acidification and eutrophication potentials than CNV. The IC system reduced fuel consumption by utilizing the generated heat for broiler-house heating and thus had lower GHG emissions and energy consumption; it reduced ammonia emission from the manure-management process by incineration and thus had lower acidification and eutrophication potentials even when including NOX generation by litter incineration. The LP + IC system had lower environmental impacts than CNV: for climate change (by 16%), acidification (48%), eutrophication (24%), and energy consumption (15%). Mitigation opportunities for broiler chickens remain, and broiler production systems with mitigation options help produce chickens more sustainably.

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Spatio-Temporal Patterns of CO2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM

Mathematics ◽

10.3390/math9212711 ◽

2021 ◽

Vol 9 (21) ◽

pp. 2711

Author(s):

Bin Wang ◽

Qiuxia Zheng ◽

Ao Sun ◽

Jie Bao ◽

Dianting Wu

Keyword(s):

Economic Growth ◽

Energy Consumption ◽

Co2 Emissions ◽

Structural Equation ◽

Structural Model ◽

Industrial Structure ◽

Reliability And Validity ◽

Temporal Patterns ◽

Measurement Model ◽

Spatio Temporal

Controlling carbon dioxide (CO2) emissions is the foundation of China’s goals to reach its carbon peak by 2030 and carbon neutrality by 2060. This study aimed to explore the spatial and temporal patterns and driving factors of CO2 emissions in China. First, we constructed a conceptual model of the factors influencing CO2 emissions, including economic growth, industrial structure, energy consumption, urban development, foreign trade, and government management. Second, we selected 30 provinces in China from 2006 to 2019 as research objects and adopted exploratory spatial data analysis (ESDA) methods to analyse the spatio-temporal patterns and agglomeration characteristics of CO2 emissions. Third, on the basis of 420 data samples from China, we used partial least squares structural equation modelling (PLS-SEM) to verify the validity of the conceptual model, analyse the reliability and validity of the measurement model, calculate the path coefficient, test the hypothesis, and estimate the predictive power of the structural model. Fourth, multigroup analysis (MGA) was used to compare differences in the influencing factors for CO2 emissions during different periods and in various regions of China. The results and conclusions are as follows: (1) CO2 emissions in China increased year by year from 2006 to 2019 but gradually decreased in the eastern, central, and western regions. The eastern coastal provinces show spatial agglomeration and CO2 emission hotspots. (2) Confirmatory analysis showed that the measurement model had high reliability and validity; four latent variables (industrial structure, energy consumption, economic growth, and government management) passed the hypothesis test in the structural model and are the determinants of CO2 emissions in China. Meanwhile, economic growth is a mediating variable of industrial structure, energy consumption, foreign trade, and government administration on CO2 emissions. (3) The calculated results of the R2 and Q2 values were 76.3 and 75.4%, respectively, indicating that the structural equation model had substantial explanatory and high predictive power. (4) Taking two development stages and three main regions as control groups, we found significant differences between the paths affecting CO2 emissions, which is consistent with China’s actual development and regional economic pattern. This study provides policy suggestions for CO2 emission reduction and sustainable development in China.

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