High concentrations of coarse particles emitted from a cattle feeding operation

Hiranuma, Naruki; Brooks, Sarah D.; Gramann, James H.; Auvermann, Brent W.

doi:10.5194/acp-11-8809-2011

Cited by 39 publications

(31 citation statements)

References 48 publications

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“…Techniques for measuring Raman spectra (RS) of atmospheric aerosol particles and the use of RS for particle characterization continue to be developed (Deboudt et al 2010;Hiranuma et al 2011;Ivleva et al 2007;Ivleva, Niessner, and Panne 2005;Rosasco, Etz, and Cassatt 1975;Rosen and Novakov 1977), and include high-throughput techniques and automated analysis methods (Craig, Bondy, and Ault 2017;Doughty and Hill 2017). Peaks in RS indicate the vibrational frequency modes of molecules.…”

Section: Raman Spectroscopymentioning

confidence: 99%

Real-time sensing of bioaerosols: Review and current perspectives

Huffman

Perring

Savage

et al. 2019

Aerosol Science and Technology

190

138

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Detection of bioaerosols, or primary biological aerosol particles (PBAPs), has become increasingly important for a wide variety of research communities and scientific questions. In particular, real-time (RT) techniques for autonomous, online detection and characterization of PBAP properties in both outdoor and indoor environments are becoming more commonplace and have opened avenues of research. With advances in technology, however, come challenges to standardize practices so that results are both reliable and comparable across technologies and users. Here, we present a critical review of major RT instrument classes that have been applied to PBAP research, especially with respect to environmental science, allergy monitoring, agriculture, public health, and national security. Eight major classes of RT techniques are covered, including the following: (i) fluorescence spectroscopy, (ii) elastic scattering, microscopy, and holography, (iii) Raman spectroscopy, (iv) mass spectrometry, (v) breakdown spectroscopy, (vi) remote sensing, (vii) microfluidic techniques, and (viii) paired aqueous techniques. For each class of technology we present technical limitations, misconceptions, and pitfalls, and also summarize best practices for operation, analysis, and reporting. The final section of the article presents pressing scientific questions and grand challenges for RT sensing of PBAP as well as recommendations for future work to encourage high-quality results and increased cross-community collaboration.

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Section: Raman Spectroscopymentioning

confidence: 99%

Real-time sensing of bioaerosols: Review and current perspectives

Huffman

Perring

Savage

et al. 2019

Aerosol Science and Technology

190

138

View full text Add to dashboard Cite

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“…3a and c, is typically due to the presence of complex organic matter with conjugate double bounds, biological material, diesel soot, black and brown carbon, or humic-like substances (Escribano et al, 2001;Sadezky et al, 2005;Ivleva et al, 2007). Therefore, we refer to this broad peak as black or brown carbon (BBC) (Hiranuma et al, 2011). Other than peaks assigned to the specific components mentioned here, spectra showing strong fluorescence in the measured range, as shown in Fig.…”

Section: Individual Particle Analysesmentioning

confidence: 99%

Characterization of individual ice residual particles by the single droplet freezing method: a case study in the Asian dust outflow region

Iwata

Matsuki

2018

Atmos. Chem. Phys.

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Abstract. In order to better characterize ice nucleating (IN) aerosol particles in the atmosphere, we investigated the chemical composition, mixing state, and morphology of atmospheric aerosols that nucleate ice under conditions relevant for mixed-phase clouds. Five standard mineral dust samples (quartz, K-feldspar, Na-feldspar, Arizona test dust, and Asian dust source particles) were compared with actual aerosol particles collected from the west coast of Japan (the city of Kanazawa) during Asian dust events in February and April 2016. Following droplet activation by particles deposited on a hydrophobic Si (silicon) wafer substrate under supersaturated air, individual IN particles were located using an optical microscope by gradually cooling the temperature to −30 • C. For the aerosol samples, both the IN active particles and non-active particles were analyzed individually by atomic force microscopy (AFM), micro-Raman spectroscopy, and scanning electron microscopy (SEM) coupled with energy dispersive X-ray spectroscopy (EDX). Heterogeneous ice nucleation in all standard mineral dust samples tested in this study was observed at consistently higher temperatures (e.g., −22.2 to −24.2 • C with K-feldspar) than the homogeneous freezing temperature (−36.5 • C). Meanwhile, most of the IN active atmospheric particles formed ice below −28 • C, i.e., at lower temperatures than the standard mineral dust samples of pure components. The most abundant IN active particles above −30 • C were predominantly irregular solid particles that showed clay mineral characteristics (or mixtures of several mineral components). Other than clay, Ca-rich particles internally mixed with other components, such as sulfate, were also regarded as IN active particle types. Moreover, sea salt particles were predominantly found in the non-active fraction, and internal mixing with sea salt clearly acted as a significant inhibiting agent for the ice nucleation activity of mineral dust particles. Also, relatively pure or fresh calcite, Ca(NO 3 ) 2 , and (NH 4 ) 2 SO 4 particles were more often found in the non-active fraction. In this study, we demonstrated the capability of the combined single droplet freezing method and thorough individual particle analysis to characterize the ice nucleation activity of atmospheric aerosols. We also found that dramatic changes in the particle mixing states during long-range transport had a complex effect on the ice nucleation activity of the host aerosol particles. A case study in the Asian dust outflow region highlighted the need to consider particle mixing states, which can dramatically influence ice nucleation activity.

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“…Particulate matter (PM) collected downwind from cattle feeding yards has been shown to contain antibiotics, bacteria, and antibiotic resistant genes (McEachran et al 2015). Further, PM less than 10µm in diameter (PM 10 ) has been measured as far as 3.5 km downwind of these facilities (Hiranuma et al 2011), suggesting that animal operations may serve as exposure sources for neighboring communities. A case-control study of methicillin-resistant Staphylococcus aureus (MRSA) in Pennsylvania (Casey et al 2013) found a significant positive association between MRSA and density of swine livestock operations around homes, but no association with dairy/veal livestock operation density.…”

Section: Discussionmentioning

confidence: 99%

Livestock and poultry density and childhood cancer incidence in nine states in the USA

Booth

Jones

Turyk

et al. 2017

Environmental Research

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Background Parental occupational and childhood exposures to farm animals have been positively associated with childhood brain tumors, whereas associations with childhood leukemia are equivocal. The developing immune system may be influenced by allergen, virus, or other exposures from animal sources, which may contribute to childhood cancer incidence. Methods Incident cancers (acute lymphoblastic leukemia [ALL], acute myeloid leukemia [AML], central nervous system [CNS], peripheral nervous system [PNS]) for children aged 0–4 diagnosed between 2003 and 2008 were obtained from nine National Cancer Institute Surveillance, Epidemiology and End Results (SEER) registries and were linked to U.S. Census of Agriculture data from 2002 and 2007 by county of diagnosis. Animal densities (animal units [AU]/km2; one animal unit is 1,000 pounds of animal weight) were estimated for hogs, cattle, chickens (layers and broilers, separately), equine (horses, ponies, mules, burros, donkeys), goats, sheep, turkeys, and total animals. Animal density was examined in models as both continuous (AU per km2) and categorical variables (quartiles). Animal operation densities (per km2) by size of operation (cattle, hogs, chickens, sheep) were modeled continuously. Rate ratios and 95% confidence intervals were estimated using Poisson regression. Results We found positive associations between AML and broiler chicken densities (RRper 10 AU/km2=1.14, 95% CI=1.02–1.26). ALL rates increased with densities of hog operations (RRper operation/100 km2=1.06, 95% CI=1.02–1.11). PNS cancer rates were inversely associated with layer chicken density (RRper log of AU/km2=0.94, 95% CI=0.89–0.99). No association was found between any cancer type and densities of cattle, equine, or goats. Conclusions Although limited by the ecologic study design, some of our findings are novel and should be examined in epidemiological studies with individual level data.

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High concentrations of coarse particles emitted from a cattle feeding operation

Cited by 39 publications

References 48 publications

Real-time sensing of bioaerosols: Review and current perspectives

Real-time sensing of bioaerosols: Review and current perspectives

Characterization of individual ice residual particles by the single droplet freezing method: a case study in the Asian dust outflow region

Livestock and poultry density and childhood cancer incidence in nine states in the USA

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