Potential reservoirs of antimicrobial resistance in livestock waste and treated wastewater that can be disseminated to agricultural land.

Livestock manure, dairy lagoon effluent, and treated wastewater are known reservoirs of antibiotic resistance genes (ARGs), antibiotic-resistant bacteria (ARB), and virulence factor genes (VFGs), and their application to agricultural farmland could be a serious public health threat. However, their dissemination to agricultural lands and impact on important geochemical pathways such as the nitrogen (N) cycle have not been jointly explored. In this study, shotgun metagenomic sequencing and analyses were performed to examine the diversity and composition of microbial communities, ARGs, VFGs, and N cycling genes in different livestock manure/lagoon and treated wastewater collected from concentrated animal feeding operations (CAFOs) and a municipal wastewater treatment plant along the west coast of the United States. Multivariate analysis showed that diversity indices of bacterial taxa from the different microbiomes were not significantly different based on InvSimpson (P = 0.05), but differences in ARG mechanisms were observed between swine manure and other microbiome sources. Comparative resistome profiling showed that ARGs in microbiome samples belonged to four core resistance classes: aminoglycosides (40-55 %), tetracyclines (30-45 %), beta-lactam-resistance (20-35 %), macrolides (18-30 %), and >50 % of the VFGs that the 24 microbiomes harbored were phyletically affiliated with two bacteria, Bacteroidetes fragilis and Enterobacter aerogenes. Network analysis based on Spearman correlation showed co-occurrence patterns between several genes such as transporter-gene and regulator, efflux pump and involved-in-polymyxin- resistance, aminoglycoside, beta-lactam, and macrolide with VFGs and bacterial taxa such as Firmicutes, Candidatus Themoplasmatota, Actinobacteria, and Bacteroidetes. Metabolic reconstruction of metagenome-assembled genome (MAGs) analysis showed that the most prevalent drug resistance mechanisms were associated with carbapenem resistance, multidrug resistance (MDR), and efflux pump. Bacteroidales was the main taxa involved in dissimilatory nitrate reduction (DNRA) in dairy lagoon effluent. This study demonstrates that the dissemination of waste from these sources can increase the spread of ARGs, ARB, and VFGs into agricultural lands, negatively impacting both soil and human health.

Characterization of a novel strain of Tribonema minus demonstrating high biomass productivity in outdoor raceway ponds.

Photosynthetic algae represent a large, diverse bioresource potential. Yellow-green algae of the genus Tribonema are candidates for production of biofuels and other bioproducts. We report on a filamentous isolate from an outdoor raceway polyculture growing on municipal reclaimed wastewater which we classified as T. minus. Over one year of cultivation in 3.5 m2 raceway ponds fed by reclaimed municipal wastewater, T. minus cultures were more productive than the native algal polycultures, with annual average productivities of 15.9 ± 0.3 and 13.4 ± 0.4 g/m2/day, respectively. The biochemical composition of T. minus biomass grown outdoors was constant year-round, with 28.3 ± 0.4% carbohydrates, 37.6 ± 0.7% proteins, and 6.1 ± 0.3% fatty acids (measured as methyl esters), with up to 4.0% of the valuable omega-3 eicosapentaenoic acid, on an ash-free dry-weight basis. In summary, T. minus was more productive, easier to harvest and produced higher quality biomass than the native polycultures.

Estimating exposure to hydrogen sulfide from animal husbandry operations using satellite ammonia as a proxy: Methodology demonstration.

Husbandry trace gases that have climate change implications such as carbon dioxide (CO2), methane (CH4) and ammonia (NH3) can be quantified through remote sensing; however, many husbandry gases with health implications such as hydrogen sulfide (H2S), cannot. This pilot study demonstrates an approach to derive H2S concentrations by coupling in situ and remote sensing data. Using AMOG (AutoMObile trace Gas) Surveyor, a mobile air quality and meteorology laboratory, we measured in situ concentrations of CH4, CO2, NH3, H2S, and wind at a southern California university research dairy. Emissions were 0.13, 1.93, 0.022 and 0.0064 Gg yr-1; emission factors (EF) were 422, 6333, 74, and 21 kg cow-1 yr-1, respectively, for the 306 head herd. Contributing to these strong EF were spillway emissions from a grate between the main cowshed and the waste lagoon identified in airborne remote sensing data acquired by the hyperspectral thermal infrared imager, Mako. NH3 emissions from the Chino Dairy Complex, also in southern California, were calculated from Infrared Atmospheric Sounding Interferometer (IASI) satellite data for 2008-2017 using average morning winds, yielding a flushing time of 2.7 h, and 8.9 Gg yr-1. The ratio of EF(H2S) to EF(NH3) for the research dairy from AMOG data were applied to IASI NH3 emissions to derive H2S exposure concentration maps for the Chino area, which ranged to 10-30 ppb H2S for many populated areas. Combining remote sensing with in situ concentrations of multiple emitted gases can allow derivation of emissions at the sub-facility, facility, and larger scales, providing spatial and temporal coverage that can translate into exposure estimates for use in epidemiology studies and regulation development. Furthermore, with high fidelity information at the sub-facility level we can identify best practices and opportunities to sustainably and holistically reduce husbandry emissions.

Validation of mobile in situ measurements of dairy husbandry emissions by fusion of airborne/surface remote sensing with seasonal context from the Chino Dairy Complex.

Mobile in situ concentration and meteorology data were collected for the Chino Dairy Complex in the Los Angeles Basin by AMOG (AutoMObile trace Gas) Surveyor on 25 June 2015 to characterize husbandry emissions in the near and far field in convoy mode with MISTIR (Mobile Infrared Sensor for Tactical Incident Response), a mobile upwards-looking, column remote sensing spectrometer. MISTIR reference flux validated AMOG plume inversions at different information levels including multiple gases, GoogleEarth imagery, and airborne trace gas remote sensing data. Long-term (9-yr.) Infrared Atmospheric Sounding Interferometer satellite data provided spatial and trace gas temporal context. For the Chino dairies, MISTIR-AMOG ammonia (NH3) agreement was within 5% (15.7 versus 14.9 Gg yr-1, respectively) using all information. Methane (CH4) emissions were 30 Gg yr-1 for a 45,200 herd size, indicating that Chino emission factors are greater than previously reported. Single dairy inversions were much less successful. AMOG-MISTIR agreement was 57% due to wind heterogeneity from downwind structures in these near-field measurements and emissions unsteadiness. AMOG CH4, NH3, and CO2 emissions were 91, 209, and 8200 Mg yr-1, implying 2480, 1870, and 1720 head using published emission factors. Plumes fingerprinting identified likely sources including manure storage, cowsheds, and a structure with likely natural gas combustion. NH3 downwind of Chino showed a seasonal variation of a factor of ten, three times larger than literature suggests. Chino husbandry practices and trends in herd size and production were reviewed and unlikely to add seasonality. Higher emission seasonality was proposed as legacy soil emissions, the results of a century of husbandry, supported by airborne remote sensing data showing widespread emissions from neighborhoods that were dairies 15 years prior, and AMOG and MISTIR observations. Seasonal variations provide insights into the implications of global climate change and must be considered when comparing surveys from different seasons.

Integral microalgae-bacteria model (BIO_ALGAE): Application to wastewater high rate algal ponds.

An integral mechanistic model describing the complex interactions in mixed algal-bacterial systems was developed. The model includes crucial physical, chemical and biokinetic processes of microalgae as well as bacteria in wastewater. Carbon-limited microalgae and autotrophic bacteria growth, light attenuation, photorespiration, temperature and pH dependency are some of the new features included. The model named BIO_ALGAE was built using the general formulation and structure of activated sludge models (ASM), and it was implemented in COMSOL Multiphysics™ platform. Calibration and validation were conducted with experimental data from two identical pilot HRAPs receiving real wastewater. The model was able to simulate the dynamics of different components in the ponds, and to predict the relative proportion of microalgae (58-68% in average of total suspended solids (TSS) and bacteria (30-20% in average of TSS). Microalgae growth resulted strongly influenced by the light factor fL(I), decreasing microalgae concentrations from 40 to 60%. Furthermore, reducing the influent organic matter concentration of 50% and 70%, model predictions indicated that microalgae production increased from (8.7gTSSm-2d-1 to 13.5gTSSm-2d-1) due to the new distribution of particulate components. The proposed model could be an efficient tool for industry to predict the production of microalgae, as well as to design and optimize HRAPs.

Life cycle GHG emissions from microalgal biodiesel--a CA-GREET model.

A life cycle assessment (LCA) focused on greenhouse gas (GHG) emissions from the production of microalgal biodiesel was carried out based on a detailed engineering and economic analysis. This LCA applies the methodology of the California Low Carbon Fuel Standard (CA LCFS) and uses life cycle inventory (LCI) data for process inputs, based on the California-Modified Greenhouse Gases, Regulated Emissions, and Energy use in Transportation (CA GREET) model. Based on detailed mass and energy balances, calculated GHG emissions from this algal biodiesel system are 70% lower than those of conventional diesel fuel, meeting the minimum 50% GHG reduction requirements under the EPA RFS2 and 60% for the European Union Renewable Energy Directive. This LCA study provides a guide to the research and development objectives that must be achieved to meet both economic and environmental goals for microalgae biodiesel production.