Virus, soil, and irrigation water

Cytopathic murine mengovirus strain MC0 (Martin et al. 1996), as surrogate of human enteric viruses (Sano et al. 2015), was kindly provided by Prof. A. Bosch (University of Barcelona). Mengoviruses were propagated on buffalo green monkey kidney (BGMK) cells in Dulbecco’s modified Eagle medium (Gibco®) supplemented with 10 % (v/v) fetal calf serum, 5 % (v/v) nonessential amino acids (Gibco®), and 1 % antifungal-antibiotic (Gibco®, penicillin streptomycin and Fungizone®) under 9 % CO 2 at 37 °C. BGMK cells at 90 % confluence in a 175-cm2 flask were infected for 1 h with 105 mengovirus genomic copies (gc). After 3 days, the culture medium was recovered, sonicated for 10 × 15-s cycles and centrifuged for 5 min at 2700×g at 4 °C. The supernatant containing viruses (approx. 108 gc mL−1) was collected, and aliquots of 35–40 mL were stored at −21 °C. For each wind tunnel experiment, three aliquots were thawed at room temperature for 1 h; 100 mL was then diluted with demineralized water or wastewater to obtain 1 L of viral suspension. This suspension was spread by using a sprayer. Mengoviruses were quantified by RT-qPCR on 60 μL of viral RNA extracted from 140 μL of trapping solution as per the manufacturer’s instructions (QIAamp® Viral RNA Kit (Qiagen)). RT-qPCR was performed by using the RNA UltraSense® One-Step Quantitative RT-PCR System Kit (Life Technologies®) by using the probe and primers described by Pinto et al. (2009). For each viral quantification, one to nine RT-qPCR replicates were performed.

Experiments were led on a calcareous cambisol (FAO classification) from the INRA station (43° 92′ N, 4° 88′ E) near Avignon. Average annual on-station rainfall was 687 mm for the period 1989–2014. The soil had been grassed since 2011. On March 2014, it was tilled first to a depth of 15 cm by using disk harrows and then to a depth of about 10 cm by using a rotary tiller (twice) followed by a power harrow. The soil consisted mainly of 5–40-mm diameter aggregates/clods. For each experiment, the 10-cm top layer contaminated by the previous experiment was replaced with soil from the same field. Soil properties of the 0–10-cm layer were 362 g kg−1 CaCO 3 , and after decarbonation, 238 g kg−1 clay, 227 g kg−1 silt, 169 g kg−1 sand, 14.3 g kg−1 organic C, 1.35 g kg−1 total N, 1.45 mg kg−1 N-NH 4 +, and 6.89 mg kg−1 N-NO 3 −. Soil pH (water) was 8.38. The concentrations of Ca2+, Mg2+, K+, and Na+ extracted by water were 114, 8.9, 65.3, and 10.5 mg kg−1 soil, respectively.

Two types of water were used to spread murine mengoviruses on the soil surface: ultrapure water and treated wastewater reclaimed for agricultural irrigation near Clermont-Ferrand (France). Wastewater samples were successively autoclaved three times at 12–20-h intervals. They contained 10 mg L−1 of suspended matter and 24.1 mg L−1 of organic C. They also contained Ca2+ (93.6 mg L−1), Mg2+ (17.5 mg L−1), K+ (34.4 mg L−1), Na+ (87.5 mg L−1), NH 4 + (4.89 mg N L−1), NO 3 − (0.6 mg N L−1), and Cl− (129 mg L−1). Water pH was 8.34.

Experimental procedure and experimental design

Seven wind tunnel experiments were conducted. They differed in wind speed (28, 11, 22, 26, 25, 26, and 11 km h−1 for experiments #1, #2, #3, #4, #5, #6, and #7, respectively), volumetric moisture of the topsoil layer (9.5 mm of irrigation before soil contamination for experiment #3 only), type of the water used to dilute virus suspensions (ultrapure water for experiments #1 to #5, autoclaved wastewater for experiments #6 and #7), and other uncontrolled variables (soil and air temperatures, air relative humidity, solar radiations).

At the beginning of each experiment (t = 0), a 0.5 × 2-m plot of bare soil was uniformly moistened with 1 L of water containing about 10+10 gc murine mengoviruses (Fig. 1a). The plot was then covered with a Plexiglas® wind tunnel (cross section 0.24 m2) (Fig. 1b). Air was collected at one end through a 2-m-high chimney and expelled at the other end by a fan producing an in-tunnel wind of velocity 11–30 km h−1. Air was sampled through openings in a three-branch system between the tunnel exit and the fan with HX16908 or GR42X25 pumps (ACP Mennecy) (pump flow rate 2.9–4.7 L min−1), and viruses were trapped by an AGI-4 impinger (Ace Glass Incorporated, USA) filled with 20 or 40 mL of trapping solution for collection times shorter or longer than 4 h, respectively (Fig. 1c). The solution was tenfold-diluted PBS for the first two experiments and a culture medium for the other five (9.4 g MEM (Sigma), 14 mL 1 M HEPES (Sigma), 20 mL Na+ bicarbonate 7.5 %, 5 mL antifungal (Gibco®, Fungizone®), 10 mL antibiotic (Gibco®, penicillin streptomycin), 100 μL antifoam B (Sigma), made up to 1 L with MilliQ water). The impingers were replaced several times over, and their solutions were stored at −21 °C for viral quantification. The amount of aerosolized viruses collected by an impinger during a collection period was estimated by using the following equation:

$$ {\widehat{N}}_{\mathrm{a}}\left({t}_{i+1}\right)-{\widehat{N}}_{\mathrm{a}}\left({t}_i\right)=\left(\frac{\widehat{C}\left({t}_{i+1}\right)\times V}{Q\times \left({t}_{i+1}-{t}_i\right)}\right)\times S\times v\times \left({t}_{i+1}-{t}_i\right)\times 1000 $$ (1)

where t i and t i+1 are successive times (h) of biocollector changes, \( {\widehat{N}}_{\mathrm{a}}\left({t}_i\right) \) and \( {\widehat{N}}_{\mathrm{a}}\left({t}_{i+1}\right) \) are estimates of N a (t i ) and N a (t i+1 ), respectively, for cumulative amounts of viruses aerosolized between the beginning of the experiment (t = 0) and times t i and t i+1 , respectively (gc m−2), \( \widehat{C}\left({t}_{i+1}\right) \) is estimate of C(t i + 1 ), the concentration of viruses in the trapping solution (gc L−1) at time t i+1 , V is volume of trapping solution remaining at time t i+1 (L), Q is air flow rate through the impinger (L h−1), v is the wind speed in the wind tunnel (m h−1), and S is the tunnel cross section (m2).

Fig. 1 Characterization of virus aerosolization from a bare soil by using the wind tunnel method. a Soil irrigation with water contaminated with viruses by using a sprayer. b Wind tunnels in operation for aerosolization assessment, with air being collected at one end through a chimney and expelled at the other end by a fan to simulate wind. c Virus trapping in the solution of an impinger. d Illustrative example of virus aerosolization kinetics Full size image

At the same time, we also monitored volumetric moisture of the 3-cm topsoil layer by using five EC-10 soil volumetric moisture probes (Decagon Devices Inc.), soil surface temperature by using five T-type thermocouples (copper–constantan) and a PT100 platinum temperature probe giving temperature of the reference junctions, air temperature by using two T-type thermocouples taped to the Plexiglas® tunnel with their sensitive junctions 50 cm above the soil, and air relative humidity in the tunnel by using a HMP155 probe (HUMICAP®) at the tunnel exit. In-tunnel wind speed was measured with a homemade pulse rate anemometer. A nearby weather station recorded various parameters, including incident global radiation. Each experiment lasted 2–3 days, except for one shorter experiment.

Some laboratory experiments not shown in this paper were performed on three impingers in series containing 10 % (v/v) PBS and a pump driving air downstream of the third impinger to characterize (i) trapping efficiency from the ratio of virus concentrations in the second and third impingers during the first 2 h and (ii) virus reaerosolization from virus losses after 6 h in the first impinger. Our results are consistent with those in the review of Verreault et al. (2008), but uncertainties in RNA quantification led to large uncertainties in the proportion of trapped viruses reaerosolized from the first impinger each hour (mean 0.11 and standard deviation 0.07) and in the fraction of aerosolized viruses trapped in the impinger solution (mean 0.75 and standard deviation 0.24). The effect of virus trapping and reaerosolization on virus concentration in the impinger was described with the equation:

$$ \frac{\partial C(t)}{\partial t}={k}_p\times \left(\frac{A}{V}\right)-{k}_h\times C(t) $$ (2)

where k p is a trapping coefficient (gc gc−1) varying from 0 to 1, A is the amount of viruses flowing through the impinger per unit time (gc h−1), and k h is a coefficient of reaerosolization ranging from 0 to any positive value (h−1). For real impingers, Eq. (1) has to be multiplied by the correction factor f c :

$$ {f}_{\mathrm{c}}=\frac{1}{k_p}\times \frac{k_h\times \left({t}_{i+1}-{t}_{\mathrm{i}}\right)}{1-{e}^{-{k}_h\times \left({t}_{i+1}-{t}_{\mathrm{i}}\right)}} $$ (3)

Assuming k p = 0.75 and k h = 0.11 h−1, f c can range from 1.4 to 2.4 for 0.5 to 12-h collection, respectively. Given the large uncertainties on k p and k h , we opted for data processing without correction, as widely performed (e.g., Lin et al. 1997; Harstad 1965).

Process modeling, uncertainty analysis, and experimental data analysis

We considered N t viruses (gc m−2) carried to the soil by irrigation, of which N a (t = ∞) could be aerosolized in defined conditions. As long as their probability of aerosolization during a time interval was only dependent on environmental conditions, viruses were assumed to belong to one group, for which aerosolization rate at time t was proportional to the aerosolizable virus quantity on the soil:

$$ \frac{\partial {N}_a(t)}{\partial t}=+{k}_a\times \left({N}_a\left(t=\infty \right)-{N}_a(t)\right) $$ (4)

where N a (t) is the cumulative quantity of viruses (gc m−2) aerosolized up to time t and k a an aerosolization kinetic coefficient (h−1). In stable conditions, its integration yielded

$$ {N}_a(t)={N}_a\left(t=\infty \right)\times \left(1- \exp \left(-{k}_a\times t\right)\right) $$ (5)

Equation (5) can be extended to n g groups of mengoviruses that differ according to aggregation to other viruses and/or soil solid particles:

$$ {N}_a(t)={\displaystyle \sum_{j=1}^{n_{\mathrm{g}}}{N}_{a,j}\left(t=\infty \right)\times \left(1- \exp \left(-{k}_{a,j}\times t\right)\right)} $$ (6)

where j is the group number. Preliminary analysis led us to consider a volatile group of N ia viruses (gc m−2) that are near-instantaneously aerosolized and a kinetic group of N a,2 (t = ∞) viruses (gc m−2) more slowly aerosolized, with an aerosolization kinetic coefficient k a,2 :

$$ {N}_a(t)={N}_{ia}+{N}_{\mathrm{a},2}\left(t=\infty \right)\times \left(1- \exp \left(-{k}_{a,2}\times t\right)\right) $$ (7)

At any point in time, rate of virus aerosolization can be correctly approximated from the amount of viruses aerosolized during the impinger collection time [t i ; t i+1 ], even long times (data not shown):

$$ \frac{\partial {N}_a}{\partial t}\left(\frac{t_i+{t}_{i+1}}{2}\right)={N}_a\left(t=\infty \right)\times {k}_a\times \exp \left(-{k}_a\times t\right)\approx \frac{\left({N}_{\mathrm{a}}\left({t}_{i+1}\right)-{N}_{\mathrm{a}}\left({t}_i\right)\right)}{t_{i+1}-{t}_i} $$ (8)

We alternatively considered one kinetic group of viruses only and then estimated N a (t = ∞) and k a or one volatile group and one kinetic group of viruses and then estimated N ia , N a,2 (t = ∞), and k a,2 , according to the following two methods:

Method 1: We fitted the model of cumulative quantities of viruses aerosolized over time N a ( t ) (Eq. (5) or (7)) to the corresponding experimental amounts \( {\widehat{N}}_a(t) \);

Method 2: First, we fitted the model of ∂N a (t)/∂t (Eq. (8)) to the aerosolization rates estimated over the periods of use of an impinger except the first 30-min period to estimate either N a (t = ∞) and k a or N a,2 (t = ∞) and k a,2 . Then, when simultaneously considering one volatile group and one kinetic group of viruses, we estimated the size of the volatile group N ia by splitting virus aerosolization during the first 30 min into kinetic and near-instantaneous aerosolizations.

Fittings were performed by minimizing the sum of squared deviations between the logarithms of simulations and numerical experiments. In method 2, we considered linear variations of the logarithm of ∂N a (t)/∂t with t (slope −k a ; y-intercept ln(k a × N a (t = ∞)).

To compare the methods, we generated 100 numerical experiments corresponding to realizations of one experiment with only one kinetic group characterized by N a (t = ∞) = 108 gc m−2 and k a = 0.07 h−1 that were in the range of values estimated from actual wind tunnel experiments and at each date t i+1 three replicates of RT-qPCR measurements \( \widehat{C}\left({t}_{i+1}\right) \) following a log-normal distribution, the standard deviation of their natural logarithm σ a-ln being constant and their mean obeying the following equation:

$$ E\left( \log \left(\widehat{C}\left({t}_{i+1}\right)\right)\right)= \log \left(C\left({t}_{i+1}\right)\right)-\frac{\sigma_{a- \ln}^2}{2} $$ (9)

σ a-ln = 0.81 enabled us to simulate a distribution of standard deviation estimates similar to the observed distribution, but with less dispersion (data not shown). The standard deviations of \( {\widehat{N}}_a\left(t=\infty \right) \) and \( {\widehat{k}}_a \) derived from method 2 were 2.3 and 2.6 times lower than those derived from method 1, respectively. According to method 2, most of the \( {\widehat{N}}_a\left(t=\infty \right) \) estimates were between 0.5 and 2 times the actual value N a (t = ∞) and most of the \( {\widehat{k}}_a \) estimates were between 0.7 and 1.4 times the actual value k a .

The values of \( {\widehat{N}}_{ia} \), \( {\widehat{N}}_{a,2}\left(t=\infty \right) \), and \( {\widehat{k}}_{a,2} \) estimated by method 2 from actual experiments were analyzed relative to wind speed, solar radiation, air temperature and relative humidity, soil surface temperature and moisture, and irrigation water quality. The trends between \( {\widehat{N}}_{a,2}\left(t=\infty \right) \) estimates from method 2 and environmental variables prompted us to simultaneously fit simulations to all the experiments considering seven \( {\widehat{N}}_{ia} \) values, seven \( {\widehat{k}}_{a,2} \) values, and a single relationship between N a,2 (t = ∞) and wind speed, soil surface temperature, and irrigation water quality:

$$ {N}_{a,2}\left(t=\infty \right)=\left(a\times {{\overline{v}}_{\mathrm{wind}}}^2\times \exp \left(-b\times \overline{T}\right)\right)+c\times I $$ (10)

where \( \overline{v} \) and \( \overline{T} \) are mean wind speed (km h−1) and temperature (°C) throughout the experiment, I is an index of irrigation water quality (0 for pure water; 1 for wastewater), and a, b, and c are coefficients.