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Functional relationship of particulate matter (PM) emissions, animal species, and moisture content during manure application

2020, Kabelitz, Tina, Ammon, Christian, Funk, Roger, Münch, Steffen, Biniasch, Oliver, Nübel, Ulrich, Thiel, Nadine, Rösler, Uwe, Siller, Paul, Amon, Barbara, Aarnink, André J.A., Amon, Thomas

Livestock manure is recycled to agricultural land as organic fertilizer. Due to the extensive usage of antibiotics in conventional animal farming, antibiotic-resistant bacteria are highly prevalent in feces and manure. The spread of wind-driven particulate matter (PM) with potentially associated harmful bacteria through manure application may pose a threat to environmental and human health. We studied whether PM was aerosolized during the application of solid and dried livestock manure and the functional relationship between PM release, manure dry matter content (DM), treatment and animal species. In parallel, manure and resulting PM were investigated for the survival of pathogenic and antibiotic-resistant bacterial species. The results showed that from manure with a higher DM smaller particles were generated and more PM was emitted. A positive correlation between manure DM and PM aerosolization rate was observed. There was a species-dependent critical dryness level (poultry: 60% DM, pig: 80% DM) where manure began to release PM into the environment. The maximum PM emission potentials were 1 and 3 kg t−1 of applied poultry and pig manure, respectively. Dried manure and resulting PM contained strongly reduced amounts of investigated pathogenic and antibiotic-resistant microorganisms compared to fresh samples. An optimal manure DM regarding low PM emissions and reduced pathogen viability was defined from our results, which was 55–70% DM for poultry manure and 75–85% DM for pig manure. The novel findings of this study increase our detailed understanding and basic knowledge on manure PM emissions and enable optimization of manure management, aiming a manure DM that reduces PM emissions and pathogenic release into the environment.

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Particulate matter emissions during field application of poultry manure - The influence of moisture content and treatment

2021, Kabelitz, Tina, Biniasch, Oliver, Ammon, Christian, Nübel, Ulrich, Thiel, Nadine, Janke, David, Swaminathan, Senthilathiban, Funk, Roger, Münch, Steffen, Rösler, Uwe, Siller, Paul, Amon, Barbara, Aarnink, André J. A., Amon, Thomas

Along with industry and transportation, agriculture is one of the main sources of primary particulate matter (PM) emissions worldwide. Bioaerosol formation and PM release during livestock manure field application and the associated threats to environmental and human health are rarely investigated. In the temperate climate zone, field fertilization with manure seasonally contributes to local PM air pollution regularly twice per year (spring and autumn). Measurements in a wind tunnel, in the field and computational fluid dynamics (CFD) simulations were performed to analyze PM aerosolization during poultry manure application and the influence of manure moisture content and treatment. A positive correlation between manure dry matter content (DM) and PM release was observed. Therefore, treatments strongly increasing the DM of poultry manure should be avoided. However, high manure DM led to reduced microbial abundance and, therefore, to a lower risk of environmental pathogen dispersion. Considering the findings of PM and microbial measurements, the optimal poultry manure DM range for field fertilization was identified as 50–70%. Maximum PM10 concentrations of approx. 10 mg per m3 of air were measured during the spreading of dried manure (DM 80%), a concentration that is classified as strongly harmful. The modeling of PM aerosolization processes indicated a low health risk beyond a distance of 400 m from the manure application source. The detailed knowledge about PM aerosolization during manure field application was improved with this study, enabling manure management optimization for lower PM aerosolization and pathogenic release into the environment.

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Modelling the effect of feeding management on greenhouse gas and nitrogen emissions in cattle farming systems

2021, Ouatahar, Latifa, Bannink, André, Lanigan, Gary, Amon, Barbara

Feed management decisions are an important element of managing greenhouse gas (GHG) and nitrogen (N) emissions in livestock farming systems. This review aims to a) discuss the impact of feed management practices on emissions in beef and dairy production systems and b) assess different modelling approaches used for quantifying the impact of these abatement measures at different stages of the feed and manure management chain. Statistical and empirical models are well-suited for practical applications when evaluating mitigation strategies, such as GHG calculator tools for farmers and for inventory purposes. Process-based simulation models are more likely to provide insights into the impact of biotic and abiotic drivers on GHG and N emissions. These models are based on equations which mathematically describe processes such as fermentation, aerobic and anaerobic respiration, denitrification, etc. and require a greater number of input parameters. Ultimately, the modelling approach used will be determined by a) the activity input data available, b) the temporal and spatial resolution required and c) the suite of emissions being studied. Simulation models are likely candidates to be able to better explain variation in on-farm GHG and N emissions, and predict with a higher accuracy for a specific mitigation measure under defined farming conditions, due to the fact that they better represent the underlying mechanisms causal for emissions. Integrated farm system models often make use of rather generic values or empirical models to quantify individual emissions sources, whereas combining a whole set of process-based models (or their results) that simulates the variation in GHG and N emissions and the associated whole farm budget has not been used. The latter represents a valuable approach to delineate underlying processes and their drivers within the system and to evaluate the integral effect on GHG emissions with different mitigation options.