Developments in micrometeorological methods for methane measurements

Assessment of Ammonia Emissions and Greenhouse Gases in Dairy Cattle Facilities: A Bibliometric Analysis

A deeper understanding of gas emissions in milk production is crucial for promoting productive efficiency, sustainable resource use, and animal welfare. This paper aims to analyze ammonia and greenhouse gas emissions in dairy farming using bibliometric methods. A total of 187 English-language articles with experimental data from the Scopus and Web of Science databases (January 1987 to April 2024) were reviewed. Publications notably increased from 1997, with the highest number of papers published in 2022. Research mainly focuses on ammonia and methane emissions, including quantification, volatilization, and mitigation strategies. Other gases like carbon dioxide, nitrous oxide, and hydrogen sulfide were also studied. Key institutions include the University of California-Davis and Aarhus University. Bibliometric analysis revealed research evolution, identifying trends, gaps, and future research opportunities. This bibliometric analysis offers insights into emissions, air quality, sustainability, and animal welfare in dairy farming, highlighting areas for innovative mitigation strategies to enhance production sustainability. This research contributes to academia, enhancing agricultural practices, and informing environmental policies. It is possible to conclude that this research is a valuable tool for understanding the evolution of research on gas emissions in dairy cattle facilities, providing guidance for future studies and interventions to promote more sustainable production.

Technical note: validation of the GreenFeed system for measuring enteric gas emissions from cattle

There are knowledge gaps in animal agriculture on how to best mitigate greenhouse gas emissions while maintaining animal productivity. One reason for these gaps is the uncertainties associated with methods used to derive emission rates. This study compared emission rates of methane (CH4) and carbon dioxide (CO2) measured by a commercially available GreenFeed (GF) system with those from (1) a mass flow controller (MFC) that released known quantities of gas over time (i.e., emission rate) and (2) a respiration chamber (RC). The GF and MFC differed by only 1% for CH4 (P = 0.726) and 3% for CO2 (P = 0.013). The difference between the GF and RC was 1% (P = 0.019) for CH4 and 2% for CO2 (P = 0.007). Further investigation revealed that the difference in emission rate for CO2 was due to a small systematic offset error indicating a correction factor could be applied. We conclude that the GF system accurately estimated enteric CH4 and CO2 emission rates of cattle over a short measurement period, but additional factors would need to be considered in determining the 24-hr emission rate of an animal.

Review: Precision nutrition of ruminants: approaches, challenges and potential gains

A plethora of sensors and information technologies with applications to the precision nutrition of herbivores have been developed and continue to be developed. The nutritional processes start outside of the animal body with the available feed (quantity and quality) and continue inside it once the feed is consumed, degraded in the gastrointestinal tract and metabolised by organs and tissues. Finally, some nutrients are wasted via urination, defecation and gaseous emissions through breathing and belching whereas remaining nutrients ensure maintenance and production. Nowadays, several processes can be monitored in real-time using new technologies, but although these provide valuable data 'as is', further gains could be obtained using this information as inputs to nutrition simulation models to predict unmeasurable variables in real-time and to forecast outcomes of interest. Data provided by sensors can create synergies with simulation models and this approach has the potential to expand current applications. In addition, data provided by sensors could be used with advanced analytical techniques such as data fusion, optimisation techniques and machine learning to improve their value for applications in precision animal nutrition. The present paper reviews technologies that can monitor different nutritional processes relevant to animal production, profitability, environmental management and welfare. We discussed the model-data fusion approach in which data provided by sensor technologies can be used as input of nutrition simulation models in near-real time to produce more accurate, certain and timely predictions. We also discuss some examples that have taken this model-data fusion approach to complement the capabilities of both models and sensor data, and provided examples such as predicting feed intake and methane emissions. Challenges with automatising the nutritional management of individual animals include monitoring and predicting of the flow of nutrients including nutrient intake, quantity and composition of body growth and milk production, gestation, maintenance and physical activities at the individual animal level. We concluded that the livestock industries are already seeing benefits from the development of sensor and information technologies, and this benefit is expected to grow exponentially soon with the integration of nutrition simulation models and techniques for big data analysis. However, this approach may need re-evaluating or performing new empirical research in both fields of animal nutrition and simulation modelling to accommodate a new type of data provided by the sensor technologies.

Accuracy of vertical radial plume mapping technique in measuring lagoon gas emissions

Recently, the U.S. Environmental Protection Agency (EPA) posted a ground-based optical remote sensing method on its Web site called Other Test Method (OTM) 10 for measuring fugitive gas emission flux from area sources such as closed landfills. The OTM 10 utilizes the vertical radial plume mapping (VRPM) technique to calculate fugitive gas emission mass rates based on measured wind speed profiles and path-integrated gas concentrations (PICs). This study evaluates the accuracy of the VRPM technique in measuring gas emission from animal waste treatment lagoons. A field trial was designed to evaluate the accuracy of the VRPM technique. Control releases of methane (CH4) were made from a 45 m×45 m floating perforated pipe network located on an irrigation pond that resembled typical treatment lagoon environments. The accuracy of the VRPM technique was expressed by the ratio of the calculated emission rates (QVRPM) to actual emission rates (Q). Under an ideal condition of having mean wind directions mostly normal to a downwind vertical plane, the average VRPM accuracy was 0.77±0.32. However, when mean wind direction was mostly not normal to the downwind vertical plane, the emission plume was not adequately captured resulting in lower accuracies. The accuracies of these nonideal wind conditions could be significantly improved if we relaxed the VRPM wind direction criteria and combined the emission rates determined from two adjacent downwind vertical planes surrounding the lagoon. With this modification, the VRPM accuracy improved to 0.97±0.44, whereas the number of valid data sets also increased from 113 to 186.

IMPLICATIONS

The need for developing accurate and feasible measuring techniques for fugitive gas emission from animal waste lagoons is vital for livestock gas inventories and implementation of mitigation strategies. This field lagoon gas emission study demonstrated that the EPA's vertical radial plume mapping (VRPM) technique can be used to accurately measure lagoon gas emission with two downwind vertical concentration planes surrounding the lagoon.