Airborne bacterial emission fluxes from manure-fertilized agricultural soil

Abstract

This is the first study to quantify the dependence on wind velocity of airborne bacterial emission fluxes from soil. It demonstrates that manure bacteria get aerosolized from fertilized soil more easily than soil bacteria, and it applies bacterial genomic sequencing for the first time to trace environmental faecal contamination back to its source in the chicken barn. We report quantitative, airborne emission fluxes of bacteria during and following the fertilization of agricultural soil with manure from broiler chickens. During the fertilization process, the concentration of airborne bacteria culturable on blood agar medium increased more than 600 000-fold, and 1 m³ of air carried 2.9 × 10⁵ viable enterococci, i.e. indicators of faecal contamination which had been undetectable in background air samples. Trajectory modelling suggested that atmospheric residence times and dispersion pathways were dependent on the time of day at which fertilization was performed. Measurements in a wind tunnel indicated that airborne bacterial emission fluxes from freshly fertilized soil under local climatic conditions on average were 100-fold higher than a previous estimate of average emissions from land. Faecal bacteria collected from soil and dust up to seven weeks after fertilization could be traced to their origins in the poultry barn by genomic sequencing. Comparative analyses of 16S rRNA gene sequences from manure, soil and dust showed that manure bacteria got aerosolized preferably, likely due to their attachment to low-density manure particles. Our data show that fertilization with manure may cause substantial increases of bacterial emissions from agricultural land. After mechanical incorporation of manure into soil, however, the associated risk of airborne infection is low.

Fig. 1

PM₁₀ (top) and microbial emissions (bottom) captured by the measuring instruments during manure application and incorporation processes at increasing distances to the tractor engine. Air samples were collected over 10 min for each distance, and particulate concentrations were monitored in parallel at a height of 1.5 m. Total bacteria were determined as microscopic cell counts, culturable bacteria as blood agar counts and enterococci as counts on KAA medium.

Fig. 2

Simulation of dust transport during field experiment. Probability densities for the height over ground and the distance from the emission source are shown. A. Simulation for emissions during manure application in the morning (10:49–12:15) of 31 May 2017. B. Simulation for emissions during incorporation of manure into soil (13:33–14:45).

Fig. 3

Wind tunnel simulation of wind‐driven release of bacteria from soil four weeks after fertilization. PM₁₀ concentrations, microscopic cell counts and CFU for bacteria on blood agar and for enterococci at four different wind velocities and for background measurements (at 0 m s⁻¹) are depicted; means and standard deviations from three replicate experiments.

Fig. 4

Emissions of PM₁₀ from the test field. (A) Calculated PM₁₀ emission from wind tunnel experiments was plotted against wind velocity. (B,C) Estimated PM₁₀ emissions from the test field (2.1 ha) in the last 26 years. (B) Annual sum, the dashed line indicates the mean annual emission, (C) monthly mean.

Fig. 5

Survival of enterococci in soil after fertilization. Mean bacterial counts from samples collected from three distinct spots on the field site; error bars: standard deviation. LoD, limit of detection; LoQ, limit of quantification.

Fig. 6

Genome‐based phylogenetic relationships among Ent. faecium isolates. A neighbour‐joining tree was reconstructed from a matrix of core‐genome allelic distances. Colours indicate the sampling sources as indicated. Six clusters with multiple near‐identical genomes each (distance ≤ 1 core‐genome allele) are labelled with roman numerals.

Fig. 7

Diversity analyses based on 16S rRNA gene sequencing. Colours indicate types of samples. A. Alpha diversity measures. B. Principal coordinate analysis of weighted UniFrac distances between samples.

Fig. 8

Aggregated abundances of 47 sequence variants that each accounted for > 0.1% of 16S rRNA sequencing reads in chicken manure. These sequence variants were affiliated to Staphylococcaceae, Lactobacillaceae, Leuconostocaceae, Brevibacteriaceae, Corynebacteriaceae, Dermabacteraceae, Nocardiopsaceae, Bacillaceae, Enterobacteriaceae, Ruminococcaceae and Streptococcaceae (in the order of their proportional abundance in manure).