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Germany has not yet made significant progress toward achieving SDGs 7 and 13. This challenge can be attributed to the underlying financialization problem in Germany, as well as implementation issues related to energy efficiency, particularly in coal and gas, and renewable energy consumption. Given these circumstances, Germany is facing challenges in reducing greenhouse gas emissions. Addressing this issue may necessitate a policy realignment, which is the primary focus of this study. In this context, our study employs various wavelet-based tools, including wavelet coherence, multivariate wavelet coherence, and wavelet-based causality, to delve into the co-movements, causality, and direction of causality between the load capacity factor (LF) and key factors such as energy efficiency (gas and coal), technological innovation, renewable electricity, and financial development, focusing on Germany during the period from 1990Q1 to 2020Q4. The results from wavelet coherence, corroborated by wavelet cohesion, indicate that in the short and medium term, improvements in coal efficiency, gas efficiency, financial development, and renewable energy are associated with an increase in LF, thereby contributing to ecological quality. Furthermore, the multivariate wavelet coherence results underscore the significant impact of considering or not considering the effect of a third variable in the interrelationship between LF and its determinants, with the effect being more pronounced when the third variable is taken into account. Although this policy framework primarily targets the objectives of SDG 13 and 7, its applicability extends to other EU nations. The primary significance of this study is its proposal of an SDG-focused policy framework. [ABSTRACT FROM AUTHOR]

Following a cradle-to-farm-gate approach, we determined the input of fossil energy and greenhouse gas emissions (GGE) for conventional and agroforestry land use on a farm in a low profit region of Germany. On the basis of a calculation model with a recurring crop rotation of maize, rye, oat, and a catch crop mixture, it was found that a short rotation alley cropping system (SRACS) with a 10% (A10) and a 40% (A40) tree area for bioenergy production consumed 7% and 32% less fossil energy than the conventionally managed site (C). Simultaneously, the net energy gains and energy efficiency of the plant production process were increased by up to 8 and 53%, respectively. Likewise, the operational GGE accumulated to 3.1 Mg ha−1 yr−1 under C farming and could be reduced by 9% and 36% in A10 and A40, respectively. Overall, a multidimensional land use indicator comparison proved that under specific site conditions agroforestry land use can increase the energy output per unit of land area, while the energy input and GGE per metric ton of biomass yield were considerably lower than in C farming. Nominal range sensitivity analysis revealed that the energetic and ecological performance of the system was highly sensitive to the size and productivity of the tree area as well as to the use of fertilisers. Our findings suggest that SRACS may fundamentally improve the environmental and energetic performance of the cultivation process on marginal land, without leading to substantial losses in agricultural livestock production area. [ABSTRACT FROM AUTHOR]

Respiration experiments with high-yielding dairy cows in Northern Ireland have shown higher energy maintenance requirements than those used in the requirements standards of, e.g. France, UK, USA and Germany. Therefore, the current net energy for lactation (NEL) system of Germany was tested by comparing measured NEL intake with calculated NEL requirements based on a comprehensive dataset from feeding trials conducted at nine research institutions in Germany, Austria and Switzerland. The relationship between NEL requirements and NEL intake is described by the equation: N E L r e q u i r e m e n t s M J / d = 26. 6 ± 0. 4 + 0. 82 ± 0. 004 ⋅ N E L i n t a k e M J / d w i t h C o e f f i c i e n t o f D e t e r m i n a t i o n R 2 = 0. 677 , R o o t M e a n S q u a r e E r r o r R M S E = 15. 9 M J N E L. The equation indicates a systematic over-estimation of NEL requirements in the lower performance range and an under-estimation at higher energy intake levels. A multiple regression analysis was conducted by calculating metabolisable energy (ME) requirements [MJ/d] using metabolic body size (MBS) [kg0.75], milk energy performance (LE) [MJ/d] and body weight change (BWC) [kg/d]: ​ ​ ​ ​ ​ ​ ​ ME intake (MEI) [ MJ ] =0. 651 (± 0. 004) ⋅ MBS+1. 37 (± 0. 006) ⋅ LE + 16. 6 (± 0. 31) ⋅ BWC with R 2 = 0. 717 , RMSE=24. 0 MJ. These results indicate that the energy maintenance requirements are markedly higher than presumed in the feed evaluation systems commonly in use but confirm the results from Northern Ireland (0.600–0.660 MJ ME/kg0.75 MBS). ME efficiency for lactation is also higher (kL = 1/1.37 = 0.73) than that used in the systems and is also similar to the results of Northern Ireland with 0.64–0.69. The energy contribution of BWC derived by this equation is 12.1 MJ/kg (16.6 · 0.73) and distinctly lower than that of 21–25 MJ/kg presumed by the feeding standards, e.g. in Germany. Further, maintenance requirements were linked to milk yield (energy corrected milk (ECM) [kg/d]), as is practiced in the standard Australian energy system: ​ ​ ​ ​ ​ ​ ​ (MEI) [ MJ ] =0. 640 + 0. 0070 ⋅ ECM) ] ⋅ MBS+1. 12) ⋅ LE + 16. 7 ⋅ BWC with R 2 = 0. 719 , RMSE=24. 0 MJ. These results demonstrate that maintenance energy requirements are partly dependent on milk yield. A differentiated analysis by stage of lactation showed that the regressions coefficients for MBS, LE and BWC change with lactation month; however, these findings apply especially to the first lactation months (i.e. in phases of intensive mobilisation). [ABSTRACT FROM AUTHOR]

This study analyzes energy efficiency trends in German and Colombian non-energy intensive sectors using data envelopment analysis (DEA) between 1998 and 2005. The results of the DEA show considerable variation in energy efficiency across non-energy intensive sectors during the sample period. At a second stage, regression analysis using panel data analysis reveals that several factors, including labor productivity, enterprise size, and capital input can be considered determinants of differences in energy efficiency among German and Colombian non-energy intensive sectors. Our results also show that different energy policies should apply in non-energy intensive sectors and that they should encourage the importance of energy efficiency in order to improve it, especially in small and medium enterprises and the industrial sector of developing countries. [ABSTRACT FROM PUBLISHER]

In this article, data envelopment analysis (DEA) is employed to study the comparative performance of German and Colombian energy-intensive sectors between 1998 and 2005. The results of the DEA indicate that the great majority of energy-intensive sectors improved on this index during the sample period, demonstrating that energy input is an important variable within the production structure and a key element in technology development. At a second stage, regression analysis using panel data analysis reveals that several factors, including labor productivity, the share of electricity, investments and enterprise size can be considered determinants of differences in energy efficiency among German and Colombian energy-intensive sectors. Our results also show that different energy policies should apply, and that they should encourage the importance of energy efficiency in order to achieve a sustainable economic development and climate stabilization today and in the near future. [ABSTRACT FROM PUBLISHER]