Regional inventory of methane and nitrous oxide emission from ruminant livestock in the Basque Country

Effects of different land use patterns on soil properties and N2O emissions on a semi-arid Loess Plateau of Central Gansu

Nitrous oxide (N2O) is one of the significant greenhouse gases in the atmosphere. Different land use patterns are the sink or source of N2O, which plays a vigorous role in controlling N2O emissions. Yet, how different land use patterns affect soil N2O emissions in the Loess Plateau of Central Gansu is still not clear. Therefore; in order to fill this gap, six different land use patterns, including Picea asperata (PA), Hippophae rhamnoides (HR), Medicago sativa (MS), No-tillage wheat field (NT) and Conventional tillage wheat field (T) were studied. The objective of this study was to examine the impact of different land use patterns on soil properties and N2O emission flux. Our results showed that compared with other treatments, Picea asperata woodland increased the soil bulk density, organic matter and soil water content, total nitrogen accumulation and microbial biomass nitrogen whilst reduced the soil pH. The wheat field is more favorable to accumulating soil nitrate nitrogen and ammonium nitrogen. Moreover, soil N2O emission rates followed the trend of T>NT>HR>GL>MS>PA. In addition, soil physicochemical properties were closely related to N2O emission flux and soil temperature was the most significant factor affecting N2O emission. General, Picea asperata woodland could significantly increased soil nutrient and reduce N2O emissions. We suggest that more forest land should be selected as the optimal site for nitrogen fixation and emission reduction for sustainable development of the terrestrial ecosystem on the Loess Plateau in Central Gansu.

Milk Quality and Carbon Footprint Indicators of Dairy Sheep Farms Depend on Grazing Level and Identify the Different Management Systems

Currently, there are very few studies in the dairy sheep sector associating milk quality and indicators regarding carbon footprint and their link to grazing levels. For 1 year, monthly milk samples and records related to environmental emissions and management systems were collected through surveys from 17 dairy sheep farms in the region of Castilla y León (Spain), in order to relate this information to the use of natural pastures under free grazing. Indicators were constructed on the collected data and subjected to a multivariate statistical procedure that involved a factor analysis, a cluster analysis and a population canonical analysis. By applying multivariate statistical techniques on milk quality and carbon footprint indicators, it was possible to identify the management system of the farms. From an environmental point of view, farms with a higher grazing level (cluster 4) were more sustainable, as they had the lowest carbon footprint (lower CO₂, N₂O and CO₂ equivalent emissions per sheep and year) and the lowest energy consumption levels, which were gradually lower than those of farms in cluster 3; both indicators were much lower than those of farms in clusters 1 and 2. The milk quality of cluster 1 and 2 farms was significantly lower in terms of total protein and fat content, dry extract, omega-3 fatty acid levels and α-tocopherol content than farms in clusters 3 and 4, which had higher accessibility to grazing resources. In sum, the higher the use of natural resources, the lower the external inputs the farms required and the lower environmental impact and energy costs they have.

Development of a dynamic energy-partitioning model for enteric methane emissions and milk production in goats using energy balance data from indirect calorimetry studies

The main objective of this study was to develop a dynamic energy balance model for dairy goats to describe and quantify energy partitioning between energy used for work (milk) and that lost to the environment. Increasing worldwide concerns regarding livestock contribution to global warming underscore the importance of improving energy efficiency utilization in dairy goats by reducing energy losses in feces, urine and methane (CH4). A dynamic model of CH4 emissions from experimental energy balance data in goats is proposed and parameterized (n = 48 individual animal observations). The model includes DM intake, NDF and lipid content of the diet as explanatory variables for CH4 emissions. An additional data set (n = 122 individual animals) from eight energy balance experiments was used to evaluate the model. The model adequately (root MS prediction error, RMSPE) represented energy in milk (E-milk; RMSPE = 5.6%), heat production (HP; RMSPE = 4.3%) and CH4 emissions (E-CH4; RMSPE = 11.9%). Residual analysis indicated that most of the prediction errors were due to unexplained variations with small mean and slope bias. Some mean bias was detected for HP (1.12%) and E-CH4 (1.27%) but was around zero for E-milk (0.14%). The slope bias was zero for HP (0.01%) and close to zero for E-milk (0.10%) and E-CH4 (0.22%). Random bias was >98% for E-CH4, HP and E-milk, indicating non-systematic errors and that mechanisms in the model are properly represented. As predicted energy increased, the model tended to underpredict E-CH4 and E-milk. The model is a first step toward a mechanistic description of nutrient use by goats and is useful as a research tool for investigating energy partitioning during lactation. The model described in this study could be used as a tool for making enteric CH4 emission inventories for goats.

Animal performance, and enteric methane, manure methane and nitrous oxide emissions from Murrah buffalo calves fed diets with different forage-to-concentrate ratios

The present study aimed to evaluate the effects of dietary forage:concentrate ratios on growth performance and enteric and faecal greenhouse-gas emissions from growing buffalo calves. Fifteen Murrah male calves (bodyweight = 233.35 ± 30.92 kg; 8–12 months age) were randomly assigned to three dietary groups that were fed a mixture of berseem fodder, wheat straw and concentrate at the ratios of 20:60:20 (C20), 20:40:40 (C40) and 20:20:60 (C60) respectively, for 120 days. Enteric methane (CH4) production was estimated by the sulfur hexafluoride tracer technique. Faeces were stored for 12 weeks and CH4 and nitrous oxide (N2O) fluxes from stored faeces were estimated every 14 days. Dry-matter intake, feed conversion efficiency and nitrogen retention were not affected (P > 0.05) but average daily gain and urinary nitrogen loss (g/day) were higher for C60 than the C20 diet (P < 0.05). Daily enteric CH4 emission (g/day) was not affected but CH4 yield (g/kg dry-matter intake) and energy loss through CH4 as a proportion of energy intake were lower for C60 than the C20 diet (P < 0.05). Faeces composition was not affected, and large variations of greenhouse-gas emissions were observed for first 10 days of storage. Methane emissions from stored faces were 1.28 ± 0.40, 1.94 ± 0.34 and 3.90 ± 0.27 mg/kg faeces per day for C20, C40 and C60 diets respectively, being higher for C60 than the C40 and C20 diets (P < 0.05). Methane-flux rate from faeces was greater for C60 than the C20 and C40 diets (0.75 vs 0.26 and 0.37 g/animal respectively; P < 0.05). Diet C60 increased N2O fluxes from stored faeces by 63% and 58% respectively, expressed in mg/kg faeces per day and mg/animal per day, compared with C20 diet (P < 0.05). Overall, dietary concentrate proportion of up to 60% in growing buffalo calf diets improved growth performance without increasing enteric CH4 emission, but CH4 and N2O production from faeces were increased. This work has provided information for gas emissions factors from open storage of faeces. More detailed studies on gaseous emissions from open lots on farms are required.

Greenhouse gas emissions from the enteric fermentation and manure storage of dairy and beef cattle in China during 1961-2010

Due to the expanding dairy and beef population in China and their contribution to global CH4 and N2O budgets, a framework considering changes in feed, manure management and herd structure was established to indicate the trends of CH4 and N2O emissions from the enteric formation and manure storage in China׳s beef and dairy production and the underlying driving forces during the period 1961-2010. From 1961 to 2010, annual CH4 and N2O emissions from beef cattle in China increased from 2.18Mt to 5.86Mt and from 7.93kt-29.56kt, respectively, while those from dairy cattle increased from 0.023 to 1.09Mt and 0.12 to 7.90kt, respectively. These increases were attributed to the combined changes in cattle population and management practices in feeds and manure storage. Improvement in cattle genetics during the period increased the bodyweight, required dry matter intake and gross energy and thus resulted in increased enteric CH4 EFs for each category of beef and dairy cattle as well as the overall enteric EFs (i.e., Tier 1 in IPCC). However, for beef cattle, such an impact on the overall enteric EFs was largely offset by the herd structure transition from draft animal-oriented to meat animal-oriented during 1961-2010. Although the CO2-eq of CH4 and N2O from manure storage was less than the enteric emissions during 1961-2010 in China, it tended to increase both in beef and dairy cattle, which was mainly driven by the changes in manure management practices.

Methane and nitrous oxide emissions from livestock agriculture in 16 local administrative districts of Korea

This study was conducted to evaluate methane (CH4) and nitrous oxide (N2O) emissions from livestock agriculture in 16 local administrative districts of Korea from 1990 to 2030. National Inventory Report used 3 yr averaged livestock population but this study used 1 yr livestock population to find yearly emission fluctuations. Extrapolation of the livestock population from 1990 to 2009 was used to forecast future livestock population from 2010 to 2030. Past (yr 1990 to 2009) and forecasted (yr 2010 to 2030) averaged enteric CH4 emissions and CH4 and N2O emissions from manure treatment were estimated. In the section of enteric fermentation, forecasted average CH4 emissions from 16 local administrative districts were estimated to increase by 4%-114% compared to that of the past except for Daejeon (-63%), Seoul (-36%) and Gyeonggi (-7%). As for manure treatment, forecasted average CH4 emissions from the 16 local administrative districts were estimated to increase by 3%-124% compared to past average except for Daejeon (-77%), Busan (-60%), Gwangju (-48%) and Seoul (-8%). For manure treatment, forecasted average N2O emissions from the 16 local administrative districts were estimated to increase by 10%-153% compared to past average CH4 emissions except for Daejeon (-60%), Seoul (-4.0%), and Gwangju (-0.2%). With the carbon dioxide equivalent emissions (CO2-Eq), forecasted average CO2-Eq from the 16 local administrative districts were estimated to increase by 31%-120% compared to past average CH4 emissions except Daejeon (-65%), Seoul (-24%), Busan (-18%), Gwangju (-8%) and Gyeonggi (-1%). The decreased CO2-Eq from 5 local administrative districts was only 34 kt, which was insignificantly small compared to increase of 2,809 kt from other 11 local administrative districts. Annual growth rates of enteric CH4 emissions, CH4 and N2O emissions from manure management in Korea from 1990 to 2009 were 1.7%, 2.6%, and 3.2%, respectively. The annual growth rate of total CO2-Eq was 2.2%. Efforts by the local administrative offices to improve the accuracy of activity data are essential to improve GHG inventories. Direct measurements of GHG emissions from enteric fermentation and manure treatment systems will further enhance the accuracy of the GHG data. (Key Words: Greenhouse Gas, Methane, Nitrous Oxide, Carbon Dioxide Equivalent Emission, Climate Change).

Modelling the interactions between C and N farm balances and GHG emissions from confinement dairy farms in northern Spain

There is world-wide concern for the contribution of dairy farming to global warming. However, there is still a need to improve the quantification of the C-footprint of dairy farming systems under different production systems and locations since most of the studies (e.g. at farm-scale or using LCA) have been carried out using too simplistic and generalised approaches. A modelling approach integrating existing and new sub-models has been developed and used to simulate the C and N flows and to predict the GHG burden of milk production (from the cradle to the farm gate) from 17 commercial confinement dairy farms in the Basque Country (northern Spain). We studied the relationship between their GHG emissions, and their management and economic performance. Additionally, we explored some of the effects on the GHG results of the modelling methodology choice. The GHG burden values resulting from this study (0.84-2.07 kg CO2-eq kg(-l) milk ECM), although variable, were within the range of values of existing studies. It was evidenced, however, that the methodology choice used for prediction had a large effect on the results. Methane from the rumen and manures, and N2O emissions from soils comprised most of the GHG emissions for milk production. Diet was the strongest factor explaining differences in GHG emissions from milk production. Moreover, the proportion of feed from the total cattle diet that could have directly been used to feed humans (e.g. cereals) was a good indicator to predict the C-footprint of milk. Not only were some other indicators, such as those in relation with farm N use efficiency, good proxies to estimate GHG emissions per ha or per kg milk ECM (C-footprint of milk) but they were also positively linked with farm economic performance.