The effect of biochar and acid activated biochar on ammonia emissions during manure storage.

Animal manure contains valuable plant nutrients which need to be stored until field application. A significant proportion of slurry nitrogen is volatilized in the form of ammonia (NH3) during storage. This impacts human health, biodiversity, air and water quality and thus urgent action is needed to reduce NH3 emissions. In this experiment, we evaluated the NH3 emission mitigation potential of biochars derived from miscanthus (MB) and solid separated anaerobic digestate (DB), and orthophosphoric acid activated MB (AMB) and DB (ADB) as well as lightweight expanded clay aggregate (LECA) during four months of liquid manure storage. A slurry without amendment was included as a control (Ctrl). Acid activated and non-activated biochars were applied on top of the slurry maintaining a 7 mm thick surface layer, while LECA was applied in a 2 cm thick layer. NH3 emissions were measured by photoacoustic analyzer. In comparison to Ctrl, acid activated biochar decreased (p < 0.05) NH3 emissions during the slurry storage. Activated biochar reduced the emissions by 37-51% within the first month of slurry storage and achieved a 25-28% emissions reduction efficiency throughout the four month period due to the reduction in emission mitigation efficiency as the storage period progressed. LECA reduced NH3 emissions by 21% during storage. Losses of NH3 as a percentage of total ammoniacal N were 29-31% for activated biochars, 35-39% for non-activated biochars and 33% for LECA. In conclusion, acid activated biochars and LECA could be good floating-covers to mitigate NH3 emissions during manure storage, but activated biochars may have better mitigation potential than LECA.

Assessing the effect of data pretreatment procedures for principal components analysis of chromatographic data.

Following publication of the National Academy of Sciences report "Strengthening Forensic Science in the United States: A Path Forward", there has been increasing interest in the application of multivariate statistical procedures for the evaluation of forensic evidence. However, prior to statistical analysis, variance from sources other than the sample must be minimized through application of data pretreatment procedures. This is necessary to ensure that subsequent statistical analysis of the data provides meaningful results. The purpose of this work was to evaluate the effect of pretreatment procedures on multivariate statistical analysis of chromatographic data obtained for a reference set of diesel fuels. Diesel was selected due to its chemical complexity and forensic relevance, both for fire debris and environmental forensic applications. Principal components analysis (PCA) was applied to the untreated chromatograms to assess association of replicates and discrimination among the different diesel samples. The chromatograms were then pretreated by sequentially applying the following procedures: background correction, smoothing, retention-time alignment, and normalization. The effect of each procedure on association and discrimination was evaluated based on the association of replicates in the PCA scores plot. For these data, background correction and smoothing offered minimal improvement, whereas alignment and normalization offered the greatest improvement in the association of replicates and discrimination among highly similar samples. Further, prior to pretreatment, the first principal component accounted for only non-sample sources of variance. Following pretreatment, these sources were minimized and the first principal component accounted for significant chemical differences among the diesel samples. These results highlight the need for pretreatment procedures and provide a metric to assess the effect of pretreatment on subsequent multivariate statistical analysis of complex data.

Association and discrimination of diesel fuels using chemometric procedures.

Five neat diesel samples were analyzed by gas chromatography-mass spectrometry and total ion chromatograms as well as extracted ion profiles of the alkane and aromatic compound classes were generated. A retention time alignment algorithm was employed to align chromatograms prior to peak area normalization. Pearson product moment correlation coefficients and principal components analysis were then employed to investigate association and discrimination among the diesel samples. The same procedures were also used to investigate the association of a diesel residue to its neat counterpart. Current limitations in the retention time alignment algorithm and the subsequent effect on the association and discrimination of the diesel samples are discussed. An understanding of these issues is crucial to ensure the accuracy of data interpretation based on such chemometric procedures.

Atypically diffuse functional connectivity between caudate nuclei and cerebral cortex in autism.

BACKGROUND: Autism is a neurodevelopmental disorder affecting sociocommunicative behavior, but also sensorimotor skill learning, oculomotor control, and executive functioning. Some of these impairments may be related to abnormalities of the caudate nuclei, which have been reported for autism. METHODS: Our sample was comprised of 8 high-functioning males with autism and 8 handedness, sex, and age-matched controls. Subjects underwent functional MRI scanning during performance on simple visuomotor coordination tasks. Functional connectivity MRI (fcMRI) effects were identified as interregional blood oxygenation level dependent (BOLD) signal cross-correlation, using the caudate nuclei as seed volumes. RESULTS: In the control group, fcMRI effects were found in circuits with known participation of the caudate nuclei (associative, orbitofrontal, oculomotor, motor circuits). Although in the autism group fcMRI effects within these circuits were less pronounced or absent, autistic subjects showed diffusely increased connectivity mostly in pericentral regions, but also in brain areas outside expected anatomical circuits (such as visual cortex). CONCLUSION: These atypical connectivity patterns may be linked to developmental brain growth disturbances recently reported in autism and suggest inefficiently organized functional connectivity between caudate nuclei and cerebral cortex, potentially accounting for stereotypic behaviors and executive impairments.