Treibhausgas-Emissionen in der deutschen Landwirtschaft

At the UN climate change conference in Paris in November 2015, Norway committed itself to a 40% reduction in greenhouse gas (GHG) emissions by 2030 compared to 1990 levels. Agriculture accounts for 8% of Norway’s total GHG emissions. If GHGs from drained and cultivated wetland (categorized under land use, land use change and forestry) are included, the share is 13%; this for a sector that accounts for roughly 0.3% of GDP. As is the case in most countries, agriculture is currently exempt from emission reduction measures, including the European Union’s Emissions Trading System (ETS), in which Norway participates. But the country has recently signaled its intention to include agriculture in future emission reduction efforts. Consideration is being given to how best to achieve GHG reductions in the sector. A recent report by the Norwegian Green Tax Commission, established by the government to evaluate policy options for achieving emission reductions, (Government of Norway, 2015) emphasizes the importance of including agriculture. The Commission suggests that agricultural emissions should be taxed at the same rate as for other sectors. It also recommends that reductions in the production and consumption of red meat should be specifically targeted, through cuts in production grants to farmers and the imposition of consumption taxes. Unsurprisingly, this proposed policy shift is extremely controversial and faces resistance, particularly from the farmers’ unions. Farmers argue that the maintenance of domestic agricultural production is crucial for achieving national food security objectives, in addition to pursuing other aims such as the maintenance of economic activity in rural areas and landscape preservation. Food security, which has been a key policy objective since the end of the Second World War, has been interpreted in Norway as requiring high levels of selfsufficiency in basic agricultural commodities. To achieve this, substantial subsidies are provided to farmers and domestic prices of many commodities are kept at high levels by restricting imports. The Organization for Economic Cooperation and Development (OECD) estimates that the total financial support provided to Norwegian agriculture in 2015 was equivalent to 62% of the value of gross farm receipts, which made Norway (along with Switzerland) a leader in the amount of support provided to agriculture by the 50 OECD member and non-member countries monitored by the Organization (OECD, 2016). In this paper we analyze policy options for achieving a 40% reduction in agricultural GHG emissions, consistent with the economy-wide target, while imposing the restriction that national food production measured in calories should be maintained (the food security target). This is consistent with the way that the Norwegian government identifies the country’s food security objective. In section 2 we outline the current situation with respect to GHG emissions in Norwegian agriculture. In section 3 we illustrate the policy issues involved by considering two product aggregates that are intensive in the use of land for crop production (grainland) and grassland, respectively. The aggregates are based on data for the main commodities in Norwegian agriculture relating to GHG emissions, land use, caloric content, subsidies, and costs per unit of production. We show that even though the opportunity set (i.e., the production combinations that are possible within technical constraints) is narrow, a 40% cut in emissions is achievable by substituting from ruminant products that are intensive in the use of grassland to products based on grainland. We also show that the emissions reduction both reduces government budgetary costs and land use, i.e., ruminant products are characterized by relatively high subsidies and land use. Two-dimensional analysis ignores the fact that per unit emissions from dairy production are low compared to other ruminant products (i.e., beef and sheep production). Both in terms of production value and agricultural employment, dairy farming is the most important component of Norwegian agriculture. Consequently, milk production deserves to be separated from ruminant meat production. Finally in section 4, we present a detailed analysis 3 of policy options derived from a disaggregated model that includes all the major products in Norwegian agriculture. In the model-based analysis, we examine first the imposition of a carbon tax, while maintaining existing agricultural support policies and import protection, and achieving the food security (production of calories) target. Since the imposition of a carbon tax in agriculture presents both technical and political challenges, we then examine an alternative approach of changing the existing structure of agricultural support to approximate the same result. We show that it is possible to change current subsidy rates to mimic the carbon tax and calorie target solution. The explanation for this is that ruminant products not only generate high emissions per produced calorie, but they are also the most highly subsidized products. Meat from ruminants is relatively unimportant in achieving Norway’s food security objective of calorie availability.

Energy-related GHG emission in agriculture of the European countries: An application of the Generalized Divisia Index

To achieve the goal of "carbon peak and neutrality," the strict requirements for greenhouse gas (GHG) emissions control in the agricultural sector were recommended in relevant plans for Beijing during the 14th Five-Year Plan period. Through collecting agricultural activity data and calculating and screening the emission factors, the amount and emission characteristics of agricultural GHG emissions in Beijing in 2020 were estimated and set as the baseline condition. On this basis, the GHG emissions in 2025 with optimized measurements implemented, which were selected in combination with the natural conditions and planting-breeding mode of Beijing, were set as the reduction condition. The emission reduction potential and its distribution during the 14th Five-Year Plan Period were predicted simultaneously. Meanwhile, the reduction effects on the GHG emissions of optimized measurements were evaluated. In addition, relevant policy recommendations on GHG reduction were proposed accordingly. The results revealed that the total agricultural GHG emissions in Beijing were estimated to be 456000 t (CO2-eq) in 2020, primarily from sources of animal intestinal fermentation and manure management, with contribution rates of 50.7% and 26.7%, respectively. Spatially, it was mainly distributed in districts with large livestock and poultry breeding scales, such as Shunyi District, Miyun District, and Yanqing District, etc. It was predicted that in 2025, the total agricultural GHG emissions would be 349000 t (CO2-eq), and the emission reduction potential in the 14th Five-Year Plan period would be 107000 t (CO2-eq). Animal intestinal fermentation would be the emission source with the largest reduction potential (60000 tons, CO2-eq), followed by the emission source of animal manure management (37000 tons, CO2-eq). Adjusting fodder composition and optimizing manure management were analyzed to be the most effective optimized measurements for agricultural GHG emission reduction. Moreover, the emission reduction potential of CH4 would be greater than that of N2O. The emission reduction potential would be mainly distributed in Miyun District, Shunyi District, Yanqing District, Fangshan District, Tongzhou District, and other suburbs with large livestock and poultry breeding scales, accounting for more than 10% of the total emission reduction potential for each. These regions with large emission reduction potential should be prioritized and then the assessments should be extended to the whole city. The measurements were recommended as follows:① the research and promotion of technologies such as fodder optimization and the efficient treatment of manure should be strengthened, ② the scope of the combination of planting and breeding model should be expanded to promote the development of circular agriculture, and ③ relevant standards, guidelines, and specifications for green and low-carbon agriculture should be formulated, and the regulatory and policy system for synergy reduction of agricultural pollution and GHG should be developed.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

To achieve energy conservation and the reduction of agricultural greenhouse gas (GHG) emissions, the Ministry of Agriculture of the People’s Republic of China in 2015 made Zhejiang Province the first national low-carbon and circular agriculture pilot province. Specialized policies were conducted in Zhejiang Province for reducing agricultural GHG emissions. In this study, we collected the GHG emission sources data of each city in Hubei and Zhejiang Provinces and calculated the estimated agricultural GHG emission of each city from 2011 to 2020 by using the recommended method from the Intergovernmental Panel on Climate Change (IPCC). Following this, we evaluated the impact of the pilot policies on the agricultural GHG emission in the treatment province, Zhejiang, by implementing the difference-in-differences (DID) analysis. The empirical results showed that after considering variables such as income level, rural employment, and average power of agricultural machinery, the agricultural GHG emissions in Zhejiang Province decreased significantly after 2015, compared with Hubei Province, driven by the low-carbon and circular agriculture pilot policies. Furthermore, agricultural GHG emissions can be effectively reduced by increasing national financial investment and administrative orders; however, excessive administrative orders and forced transformation of the agricultural system are likely to harm farmers’ interests in the process of policy implementation.

Greenhouse gas (GHG) emissions from agriculture contribute to climate change. The consequences of unsustainable agricultural activity are polluted water, soil, air, and food. The agricultural sector has become one of the major contributors to global GHG emissions and is the world’s second largest emitter after the energy sector, which includes emissions from power generation and transport. Latvian and Lithuanian agriculture generates about one fifth of GHG emissions, while Estonia generates only about one tenth of the country’s GHG emissions. This paper investigates the GHG trends in agriculture from 1995 to 2019 and the driving forces of changes in GHG emissions from the agricultural sectors in the Baltic States (Lithuania, Latvia, and Estonia), which are helpful for formulating effective carbon reduction policies and strategies. The impact factors have on GHG emissions was analysed by using the Logarithmic Mean Divisia Index (LMDI) method based on Kaya identity. The aim of this study is to assess the dynamics of GHG emissions in agriculture and to identify the factors that have had the greatest impact on emissions. The analysis of the research data showed that in all three Baltic States GHG emissions from agriculture from 1995 to 2001–2002 decreased but later exceeded the level of 1995 (except for Lithuania). The analysis of the research data also revealed that the pollution caused by animal husbandry activities decreased. GHG intensity declined by 2–3% annually, but the structure of agriculture remained relatively stable. The decomposition of GHG emissions in agriculture showed very large temporary changes in the analysed factors and the agriculture of the Baltic States. GHG emissions are mainly increased by pollution due to the growing economy of the sector, and their decrease is mainly influenced by two factors—the decrease in the number of people employed in the agriculture sector and the decreasing intensity of GHGs in agriculture. The dependence of the result on the factors used for the decomposition analysis was investigated by the method of multivariate regression analysis. Regression analysis showed that the highest coefficient of determination (R2 = 0.93) was obtained for Estonian data and the lowest (R2 = 0.54) for Lithuanian data. In the case of Estonia, all factors were statistically significant; in the case of Latvia and Lithuania, one of the factors was statistically insignificant. The identified GHG emission factors allowed us to submit our insights for the reduction of emissions in the agriculture of the Baltic States.

Agriculture plays a central role in maintaining food security and achieving sustainable development for human society. It is a challenge for the agricultural sector to mitigate greenhouse gas (GHG) emissions and maintain agricultural production. However, dual-level uncertainties exist in the processes of agricultural GHG accounting and emission reduction management. In this research, an integrated approach for identifying adaptation strategies in agricultural GHG emission reduction management was developed through incorporating life cycle analysis (LCA) of agricultural production into a general mathematical programming model. This approach strengthened the applicability of LCA and the comprehensiveness of programming models in generating agricultural adaptive actions under different GHG emission restriction targets. Also, dual-level uncertainties of LCA and adaptation management can be effectively addressed. A case study was proposed to illustrate application of the approach in Dalian City, China. The results indicated that farming patterns in eight districts would change significantly. The total area of maize fields would account for the primary proportion (i.e., 40–45 %) in its agricultural sector. Rice, peanut and cabbage fields would be the minor contributors in terms of GHG emissions. In addition to effective rainfall (i.e., [156, 259] mm/ha), a certain amount of water would be supplied for agricultural irrigation to maximize the city’s agricultural yields. Compared with other agricultural crops, rice fields would need the largest amount of irrigation water (i.e., [153.72, 277.98] Mt) to meet the requirements of local government plans.

Gaining Acceptance of Novel Plant Breeding Technologies.

Simple SummaryLivestock accounts for an estimated 80% of total agricultural greenhouse gas emissions, making abatement of greenhouse gas emissions from livestock a high-priority challenge facing animal nutritionists. Mitigating greenhouse gases in ruminants without reducing animal production is desirable both as a strategy to reduce global greenhouse gas emissions and as a way of improving dietary feed efficiency. The inclusion of feed additives in the diets of ruminants can reduce energy losses as methane, which typically reduces animal performance and contributes to greenhouse gas emissions. The present study evaluated the abatement potential of nine essential oil blends to mitigate greenhouse gas emissions. The inclusion of the blends resulted in a reduction in greenhouse gas emissions and in vitro apparent dry matter digestibility with higher values noted for the control treatment. A similar trend was noted for in vitro truly dry matter digestibility with higher values noted in the control treatment. The efficiency of microbial production was greater for the blends. The inclusion of the blends affected the total and molar proportion of volatile fatty acid concentrations. Overall, inclusion of the blends modified the rumen function resulting in improved efficiency of microbial production.The current study evaluated nine essential oil blends (EOBs) for their effects on ruminal in vitro dry matter digestibility (IVDMD), efficiency of microbial production, total short-chain fatty acid concentration (SCFA), total gas, and greenhouse gas (GHG) emissions using two dietary substrates (high forage and high concentrate). The study was arranged as a 2 × 2 × 9 + 1 factorial design to evaluate the effects of the nine EOBs on the two dietary substrates at two time points (6 and 24 h). The inclusion levels of the EOBs were 0 µL (control) and 100 µL with three laboratory replicates. Substrate × EOBs × time interactions were not significant (p > 0.05) for total gas and greenhouse gas emissions. The inclusion of EOBs in the diets resulted in a reduction (p < 0.001) in GHG emissions, except for EOB1 and EOB8 in the high concentrate diet at 6 h and for EOB8 in the high forage diet at 24 h of incubation. Diet type had no effect on apparent IVDMD (IVADMD) whereas the inclusion of EOBs reduced (p < 0.05) IVADMD with higher values noted for the control treatment. The efficiency of microbial production was greater (p < 0.001) for EOB treatments except for EOB1 inclusion in the high forage diet. The inclusion of EOBs affected (p < 0.001) the total and molar proportion of volatile fatty acid concentrations. Overall, the inclusion of the EOBs modified the rumen function resulting in improved efficiency of microbial production. Both the apparent and truly degraded DM was reduced in the EOB treatments. The inclusion of EOBs also resulted in reduced GHG emissions in both diets, except for EOB8 in the high forage diet which was slightly higher than the control treatment.

Globally, agriculture is directly responsible for 14% of annual greenhouse gas(GHG) emissions and induces an additional 17% through land use change, mostlyin developing countries (Vermeulen et al 2012). Agricultural intensification andexpansion in these regions is expected to catalyze the most significant relativeincreases in agricultural GHG emissions over the next decade (Smith et al 2008,Tilman et al 2011). Farms in the developing countries of sub-Saharan Africa andAsia are predominately managed by smallholders, with 80% of land holdingssmaller than ten hectares (FAO 2012). One can therefore posit that smallholderfarming significantly impacts the GHG balance of these regions today and willcontinue to do so in the near future.However, our understanding of the effect smallholder farming has on theEarth’s climate system is remarkably limited. Data quantifying existing andreduced GHG emissions and removals of smallholder production systems areavailable for only a handful of crops, livestock, and agroecosystems (Herrero et al2008, Verchot et al 2008, Palm et al 2010). For example, fewer than fifteenstudies of nitrous oxide emissions from soils have taken place in sub-SaharanAfrica, leaving the rate of emissions virtually undocumented. Due to a scarcity ofdata on GHG sources and sinks, most developing countries currently quantifyagricultural emissions and reductions using IPCC Tier 1 emissions factors.However, current Tier 1 emissions factors are either calibrated to data primarilyderived from developed countries, where agricultural production conditions aredissimilar to that in which the majority of smallholders operate, or from data thatare sparse or of mixed quality in developing countries (IPCC 2006). For the mostpart, there are insufficient emissions data characterizing smallholder agricultureto evaluate the level of accuracy or inaccuracy of current emissions estimates.Consequentially, there is no reliable information on the agricultural GHG budgetsfor developing economies. This dearth of information constrains the capacity totransition to low-carbon agricultural development, opportunities for smallholdersto capitalize on carbon markets, and the negotiating position of developingcountries in global climate policy discourse.Concerns over the poor state of information, in terms of data availability andrepresentation, have fueled appeals for new approaches to quantifying GHGemissions and removals from smallholder agriculture, for both existing conditionsand mitigation interventions (Berry and Ryan 2013, Olander et al 2013).Considering the dependence of quantification approaches on data and the currentdata deficit for smallholder systems, it is clear that in situ measurements must bea core part of initial and future strategies to improve GHG inventories and

Energy-related activities are a major contributor of greenhouse gas (GHG) emissions. A growing body of knowledge clearly depicts the links between human activities and climate change. Over the last century the burning of fossil fuels such as coal and oil and other human activities has released carbon dioxide (CO2) emissions and other heat-trapping GHG emissions into the atmosphere and thus increased the concentration of atmospheric CO2 emissions. The main human activities that emit CO2 emissions are (1) the combustion of fossil fuels to generate electricity, accounting for about 37% of total U.S. CO2 emissions and 31% of total U.S. GHG emissions in 2013, (2) the combustion of fossil fuels such as gasoline and diesel to transport people and goods, accounting for about 31% of total U.S. CO2 emissions and 26% of total U.S. GHG emissions in 2013, and (3) industrial processes such as the production and consumption of minerals and chemicals, accounting for about 15% of total U.S. CO2 emissions and 12% of total ...

Searching for solutions to mitigate greenhouse gas emissions by agricultural policy decisions — Application of system dynamics modeling for the case of Latvia

Nexus of embodied land use and greenhouse gas emissions in global agricultural trade: A quasi-input–output analysis

For many developing countries, the land use sector, particularly agriculture and forestry, represents a large proportion of their greenhouse gas (GHG) emissions, making this sector a priority for GHG mitigation activities. Previous global surveys (e.g., IPCC 2000) as well as the most recent IPCC assessment report clearly indicate that the greatest technical potential for carbon sequestration and reductions of non-CO2 GHG emissions from the land use sector is in developing countries. Estimates that consider economic feasibility suggest that agriculture and forestry together provide among the greatest opportunities for short-term and low-cost mitigation measures across all sectors of the global economy1 (IPCC 2007). In addition, it is widely recognized that the ecosystem changes entailed by most mitigation practices, i.e., building soil organic matter, reducing losses and tightening nutrient cycles, more efficient production systems and preserving native vegetation, are well aligned with goals of increasing food security and rural development as well as buffering land use systems against climate change (Lal 2004). Hence, there is growing interest in jump-starting the capacity for broad-based engagement in agriculturally-based GHG mitigation projects in developing countries.

The increase of agricultural greenhouse gas (GHG) emissions has become a significant issue for China, affecting the achievement of its Nationally Determined Contributions under the Paris Agreement. Expansion of the large-scale multiple cropping system as a consequence of climate warming could be a major driving force of this increase. In this study, life cycle assessment was employed to identify agricultural GHG emissions due to the expansion of the multiple cropping system in the North China Plain and neighboring regions. We found that agricultural greenhouse gas emissions have increased from 41.34 to 120.87 Tg CO2-eq/yr over the past 30 years, and the expansion of the multiple cropping system has contributed to 13.89% of this increment. Furthermore, the increases in straw handling and agricultural inputs which are related to multiple cropping systems have also played an important role. Results of our study demonstrate that the expansion of the multiple cropping system contributes considerably to increases in agricultural GHG emissions in the North China Plain and neighboring regions. Therefore, it can be concluded that the sustained northward expansion of the multiple cropping system will further elevate agricultural GHG emissions in China, and this should be considered while formulating policies to reduce GHG emissions from agriculture.