Dairy cattle of different ages experience different living conditions and varied frequency of antibiotic administration that likely influence the distribution of microbiome and resistome in ways that reflect different risks of microbial transmission. To assess the degree of variance in these distributions, fecal and soil samples were collected from six distinct housing areas on commercial dairy farms (n = 7) in Washington State. 16S rRNA gene sequencing indicated that the microbiota differed between different on-farm locations in feces and soil, and in both cases, the microbiota of dairy calves was often distinct from others (P < 0.05). Thirty-two specific antibiotic resistance genes (ARGs) were widely distributed on dairies, of which several clinically relevant ARGs (including cfr, cfrB, and optrA) were identified for the first time at U.S. dairies. Overall, ARGs were observed more frequently in feces and soil from dairy calves and heifers than from hospital, fresh, lactation and dry pens. Droplet-digital PCR demonstrated that the absolute abundance of floR varied greatly across housing areas and this gene was enriched the most in calves and heifers. Furthermore, in an extended analysis with 14 dairies, environmental soils in calf pens had the most antibiotic-resistant Escherichia coli followed by heifer and hospital pens. All soil E. coli isolates (n = 1,905) are resistant to at least 4 different antibiotics, and the PFGE analysis indicated that florfenicol-resistant E. coli is probably shared across geographically-separated farms. This study identified a discrete but predictable distribution of antibiotic resistance genes and organisms, which is important for designing mitigation for higher risk areas on dairy farms.

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.

Methane (CH4) and ammonia (NH3) directly and indirectly affect the atmospheric radiative balance with the latter leading to aerosol generation. Both have important spectral features in the Thermal InfraRed (TIR) that can be studied by remote sensing, with NH3 allowing discrimination of husbandry from other CH4 sources. Airborne hyperspectral imagery was collected for the Chino Dairy Complex in the Los Angeles Basin as well as in situ CH4, carbon dioxide (CO2) and NH3 data. TIR data showed good spatial agreement with in situ measurements and showed significant emissions heterogeneity between dairies. Airborne remote sensing mapped plume transport for ∼20 km downwind, documenting topographic effects on plume advection. Repeated multiple gas in situ measurements showed that emissions were persistent on half-year timescales. Inversion of one dairy plume found annual emissions of 4.1 × 10⁵ kg CH4, 2.2 × 10⁵ kg NH3, and 2.3 × 10⁷ kg CO2, suggesting 2300, 4000, and 2100 head of cattle, respectively, and Chino Dairy Complex emissions of 42 Gg CH4 and 8.4 Gg NH3 implying ∼200k cows, ∼30% more than Peischl et al. (2013) estimated for June 2010. Far-field data showed chemical conversion and/or deposition of Chino NH3 occurs within the confines of the Los Angeles Basin on a four to six h timescale, faster than most published rates, and likely from higher Los Angeles oxidant loads. Satellite observations from 2011 to 2014 confirmed that observed in situ transport patterns were representative and suggests much of the Chino Dairy Complex emissions are driven towards eastern Orange County, with a lesser amount transported to Palm Springs, CA. Given interest in mitigating husbandry health impacts from air pollution emissions, this study highlights how satellite observations can be leveraged to understand exposure and how multiple gas in situ emissions studies can inform on best practices given that emissions reduction of one gas could increase those of others.

In view of the significance of transportation management and logistics in the economic concept and raising the productivity of production systems, well-timed procurement of perishable materials and goods is determined as a pivotal prerequisite for economic and environmental development. Since the perishable goods produced must be made delivered to consumers as early as possible on account of the limited lifespan, thus, the vulnerability of these products is extremely high, owing to the high cost of transportation as well as the environmental impacts. So that solves this problem, this study represents a problem of dynamic green vehicle routing of perishable products in green traffic conditions that optimizes the total cost for a dynamic transportation network and minimizes environmental influences, and increases customer satisfaction. The introduced model is implemented in light of time windows as a trustworthy solution for monitoring the dynamic logistics process and attaining instantaneous information on the basis of the green traffic situation and travel duration, which is commonly known by the Logit function. Assuming the three-objective programming model, we consider a new improved algorithm developed for a novel augmented ε-constraint heuristic approach. Furthermore, robust optimization has been conducted for the established problem to tackle with uncertainties. Uncertainties are included demand and economic parameters. Eventually, to validate the proposed model, a case study was carried out at Kaleh Amol Dairy Company in Iran. The conclusions of sensitivity analysis by implementing the model in the real world indicate that the model and approach presented in various uncertainty scenarios have high flexibility.

Animal wastes are commonly used in a sustainable manner to fertilize crops. However, manures contain numerous pathogenic bacteria that can impact animal and human health. Treatment of animal waste by anaerobic digestion has the potential to reduce pathogen loading to land. This study was conducted to determine the fate of bacteria applied in raw and anaerobically digested dairy slurries that were broadcast and subsurface applied in a field of forage grasses. Digested slurry had significantly fewer indicator bacteria, Escherichia coli and fecal coliform at time of application. Anaerobic digestion did not increase the survivability of indicator bacteria. Waste treatment and application method did not affect the rate of bacteria die-off. There were fewer E. coli and fecal coliform at the end of each trial in the soils that received digested slurry. Anaerobic digestion of dairy waste has the potential to reduce pathogenic bacteria loading to cropland.

The aim of the present study was to evaluate the influence of the recirculation rate on the efficiency of a 1,000-L pilot anaerobic sequencing batch biofilm reactor (ASBBR) treating effluent from a small dairy plant over a long-term period (570 days). Three operational conditions were studied, in which recirculation rates were varied, resulting in upflow velocities of 0.2, 3.8, and 6.4 m h⁻¹and the cycle time of 48 h. The biomass was immobilized on plastic supports containing polyurethane foam. The organic loading rate varied according to the operations occurring in the dairy plant. After system stability had been verified, temporal profiles of the substrate and metabolite concentrations were obtained, allowing kinetic parameter inference. Sludge samples from the inoculum and from the reactor were analyzed through microscopic examination, molecular biology analyses, and specific methanogenic activity assays. The average efficiencies of organic matter removal were 82 ± 11, 84 ± 9, and 87 ± 9 % at velocities of 0.2, 3.8, and 6.4 m h⁻¹, respectively. Microscopic examinations indicated that the fluorescent microorganisms decreased throughout the experiment, and they were not detected in the last condition. Homoacetogenesis was inferred as a possible pathway for H₂removal and for maintenance of the methanogenic process. Specific methanogenic activity increased throughout the monitoring period. It was possible to conclude that the ASBBR was efficient, robust, and reliable in treating dairy effluents under the conditions used.

Water quantity and quality were monitored for 3 years in a 360-m-long wetland with riparian fences and plants in a pastoral dairy farming catchment. Concentrations of total nitrogen (TN), total phosphorus (TP) and Escherichia coli were 210–75,200 g N m−3, 12–58,200 g P m−3 and 2–20,000 most probable number (MPN)/100 ml, respectively. Average retentions (±standard error) for the wetland over 3 years were 5 ± 1%, 93 ± 13% and 65 ± 9% for TN, TP and E. coli, respectively. Retentions for nitrate–N, ammonium–N, filterable reactive P and particulate C were respectively −29 ± 5%, 32 ± 10%, −53 ± 24% and 96 ± 19%. Aerobic conditions within the wetland supported nitrification but not denitrification and it is likely that there was a high conversion rate from dissolved inputs of N and P in groundwater, to particulate N and P and refractory dissolved forms in the wetland. The wetland was notable for its capacity to promote the formation of particulate forms and retain them or to provide conditions suitable for retention (e.g. binding of phosphate to cations). Nitrogen retention was generally low because about 60% was in dissolved forms (DON and NOX–N) that were not readily trapped or removed. Specific yields for N, P and E. coli were c. 10–11 kg N ha−1 year−1, 0.2 kg P ha−1 year−1 and ≤109 MPN ha−1 year−1, respectively, and generally much less than ranges for typical dairy pasture catchments in New Zealand. Further mitigation of catchment runoff losses might be achieved if the upland wetland was coupled with a downslope wetland in which anoxic conditions would promote denitrification.

Water quality of Lake Okeechobee has been a major environmental concern for many years. Transport of dissolved organic matter (DOM) in runoff water from watershed is critical to the increased inputs of nutrients (N and P) and metals (Cu and Zn). In this study, 124 soil samples were collected with varying soil types, land uses, and soil depths in Lake Okeechobee watershed and analyzed for water-extractable C, N, P, and metals to examine the relationship between dissolved organic carbon (DOC) and water soluble nutrients (N and P) and metals in the soils. DOC in the soils was in 27.64–400 mg kg⁻¹ (69.30 mg kg⁻¹ in average) and varied with soil types, land uses, and soil depth. The highest water-extractable DOC was found in soils collected in sugar cane and field crops (277 and 244 mg kg⁻¹ in average, respectively). Water soluble concentrations of N and P were in the range of 6.46–129 and 0.02–60.79 mg kg⁻¹, respectively. The ratios of water-extractable C/N and C/P in soils were in 0.68–12.52 (3.23 in average) and 3.19–2,329 (216 in average), and varied with land uses. The lowest water-extractable C/N was observed in the soils from dairy (1.66), resident (1.79), and coniferous forest (4.49), whereas the lowest water-extractable C/P was with the land uses of dairy (13.1) and citrus (33.7). Therefore, N and P in the soils under these land uses may have high availability and leaching potential. The concentrations of water soluble Co, Cr, Cu, Ni, and Zn were in the ranges of < method detection limit (MDL)–0.33, <MDL–0.53, 0.04–2.42, <MDL–0.71, and 0.09–1.13 mg kg⁻¹, with corresponding mean values of 0.02, 0.01, 0.50, 0.07, and 0.37 mg kg⁻¹, respectively. The highest water soluble Co (0.10 mg kg⁻¹), Cr (0.26 mg kg⁻¹), Ni (0.31 mg kg⁻¹), and Zn (0.80 mg kg⁻¹) were observed in soils under the land use of sugar cane, whereas the highest Cu (1.50 mg kg⁻¹) was with field crop. The concentration of DOC was positively correlated with total organic carbon (TOC) (P <0.01), water soluble N (P <0.01), electrical conductivity (EC, P <0.01), and water soluble Co, Cr, Ni, and Zn (P <0.01), and Cu (P <0.05), whereas water soluble N was positively correlated with water soluble P, Cu, and Zn (P <0.01) in soils. These results indicate that the transport of DOC from land to water bodies may correlate with the loss of macro-nutrients (N, P), micro-nutrients (Cu, Zn, and Ni), and contaminants (Cr and Co) as well.

Dairy cattle manure has been implicated as a major source of fecal contamination in non-point source agricultural runoff in watersheds. Four different dairy farms in central Texas, each utilizing a different dairy manure management practice, in the Leon River watershed were sampled for E. coli using EPA Method 1603, with a percentage of isolates genotyped and phylotyped using the Clermont quadruplex PCR method. E. coli concentration was reduced as manure moved through the management process with tiered management systems lowering concentration the most. E. coli genotypes showed no correlation with sampling season or management practice. The highest percentage of unique genotypes was observed in dairy 2, which consisted of a settling basin then lagoon. One genotype was seen across all dairies and composed 15% of all genotypes characterized. E. coli phylotypes showed no seasonal or management practice trend. B1 was the most common phylotype isolated from all dairies and time periods, which was expected. Potentially pathogenic phylotypes were rarely observed, which could indicate isolation from pathogenic E. coli introduction. Dairy manure management practices that separate solid from liquid waste reduced E. coli concentrations the most based on these results.

Milk supplied to a dairy plant in Brescia City (Northern Italy) was found to be contaminated by dioxin like PCBs at levels above the European (EU) action limit (2 pg WHO-TEQ/g fat). As a consequence, 14 dairy farms were sampled individually, in order to identify and possibly eliminate the source of contamination. All the farms were located in Brescia or just nearby, an area that is characterized by a strong industrialization. Four out of the 14 farms showed contamination levels above the legal maximum limit set by European Commission at 5.5 pg WHO-TEQ/g fat for the sum of dioxins and DL-PCBs. Concentrations of 8.16, 6.83, 5.71 and 5.65 pg WHO-TEQ/g fat were detected. In the three most polluted farms, cow ration was substituted with feed coming from uncontaminated areas and the time needed to reduce milk pollution was evaluated. In all the three farms, contamination levels dropped below the EU legal limit after only 1 month from the removal of the pollution source. In each sampled farm, DL-PCBs were the major contributors to the total WHO-TEQ level, with percentages up to 87 % in the most contaminated one. PCB 126 WHO-TEQ value explained by itself large part of this contamination, and its decrease was fundamental for the reduction of milk contamination levels. This study provides an example of an on-field successful emergency intervention that succeeded in decontamination of dairy cows, allowing a fast restart of their production activity.