Experiments were conducted in a vertical recirculating wind tunnel at the Experimental Center of Desert Forestry, Chinese Academy of Forestry in Dengkou, Inner Mongolia, China (Fig. 1a). This closed-loop facility, modified from a conventional open-circuit design, enables continuous circulation of air and suspended dust, thereby facilitating long-duration observations of suspended-dust evolution and surface accumulation. The test section measures 13 m in length, with a cross section of 2 m (width) × 2 m (height). Flow is driven by four axial fans positioned downstream of the test section, allowing for continuous adjustment of the mean wind speed from 0 to 20 ms-1. Upstream of the test section, the flow is conditioned by passing through a diffuser, turning vanes, and a settling chamber equipped with honeycombs and screens, collectively ensuring a uniform approach flow with low turbulence intensity and minimal swirl (Liu et al., 2020). The dust used was sourced from the upper 0–5 cm of local cropland soil, which was air-dried and dry-sieved to obtain particles smaller than 63 µm. Before the wind-tunnel experiments, the sieved dust was further oven-dried at 105 °C for 8 h to standardize its moisture condition among experimental runs.

The experimental protocol comprised two sequential stages. (i) Strong-wind loading phase: the wind speed was initially set to 14 ms-1 for about 5 min to erode the soil source, release dust, and establish a recirculating airborne dust load within the closed-circuit tunnel. (ii) Low-wind deposition phase: immediately after the loading phase, the exposed soil source bed was completely covered with steel plates to prevent continued direct emission or re-erosion from the original source. The steel plates remained in place throughout the subsequent low-wind deposition phase. The wind speed was then reduced to a target value of 2, 4 or 6 ms-1. Additional experiments under quiescent conditions (0 ms-1) were performed in the same test section with the fans deactivated.

At the beginning of each low-wind experiment, 25 cylindrical acrylic collection trays (radius: 10 cm, rim height: 3 cm) were placed at predefined positions on the tunnel floor within the test section. Five trays were assigned to each of the five sampling times (30, 60, 90, 120 and 180 min). Each tray was exposed continuously from the beginning of the low-wind phase until its designated sampling time. Five trays were removed at their designated times to obtain the cumulative net deposition sample for a specific wind-speed-time combination, resulting in a progressive reduction in the number of trays remaining in the tunnel. The same initial tray layout, time-specific tray assignments, and retrieval sequence were used for all wind-speed treatments. Thus, the tray configuration at a given sampling time was matched among treatments, although the number of trays decreased progressively within each experimental run.

No water, glass beads, grease, adhesive, or other material was added to suppress particle rebound or re-entrainment from the tray surface. The collected mass therefore represents cumulative tray-retained net accumulation, which integrates particle arrival at the collection surface and subsequent losses through rebound, local re-entrainment, and removal from the tray.

A real-time dust concentration monitor (Fig. 1a; TD2000A-CT, Zhonggong Tiandi Technology (Beijing) Co., Ltd., Beijing, China) was operated continuously during both the loading and deposition phases to track the bulk suspended dust mass concentration in the test section. The sampling inlet was located on the longitudinal centreline of the test section, 7.5 m downstream of the test-section entrance and 1 m above the tunnel floor. The instrument had a measurement range of 0–10 000 mgm-3 (RS485 output; DC 24 V). During the loading phase, the monitor was used as a quality-control indicator to obtain comparable initial suspended dust loadings among experimental runs. The concentration recorded at the start of the low-wind phase was defined as the initial airborne dust concentration (C0). The monitor provided a single-point concentration time series at this fixed sampling location; vertical concentration profiles were not measured. For consistency throughout this study, particles of 1–10, 10–20, and 20–63 µm are referred to as fine, medium-sized, and coarse particles, respectively.

Vertical wind speed profiles were measured on the longitudinal centreline of the test section, 9 m downstream of the test-section entrance and immediately downstream of the collection-tray array. The complete initial array of 25 trays was present during the profile measurements. The collection trays were arranged in the same fixed layout as in the deposition experiments, with a spacing of 20 cm between adjacent trays, and the same layout was restored before each run. Wind speed was recorded at eight heights (z = 0.02, 0.05, 0.10, 0.20, 0.40, 0.80, 1.20, and 1.60 m) under nominal wind speeds of 2, 4, and 6 ms-1 (Fig. 1b). Friction velocity u∗ was estimated from a log-linear regression of the near-surface wind profile, 1U(z)=Aln⁡zzref+B,2u∗=κA, where U(z) is wind speed at height z, zref = 1 m, A is the fitted slope, B is the intercept, and κ = 0.4. To ensure consistency among treatments, the regression was fitted over the common height interval of 0.05–0.40 m, which is above the tray rim height (0.03 m) and below the upper quasi-uniform portion of the profile. Therefore, the measurements at 0.80, 1.20, and 1.60 m were not included in the u∗ regression. The resulting profile-derived apparent friction velocities were 0.063, 0.089, and 0.154 ms-1 for the 2, 4, and 6 ms-1 treatments, respectively, with corresponding R2 values of 0.921, 0.933, and 0.883.

The boundary-layer thickness (δ) was defined as the first height at which the shape-preserving interpolated profile reached 0.99 U∞, where U∞ was the mean wind speed at 0.80, 1.20, and 1.60 m. Minor reversals in the measured profiles were first removed using isotonic regression before interpolation.

The upper edge of the collection trays was positioned at z = 0.03 m, corresponding to approximately 3.4 %, 4.1 %, and 6.3 % of δ, respectively. Because the profiles were measured after installation of the complete tray array, they incorporated the collective aerodynamic influence of the trays. The profiles characterize the profile-scale mean flow under the complete initial 25-tray configuration. Local flow separation and wakes around individual tray rims, as well as possible changes associated with progressive tray removal, were not resolved.

The mass of dust retained in each tray was determined using an analytical balance with a resolution of 0.0001 g. Particle-size distributions (PSDs) of the deposited dust were analyzed using a laser diffraction particle-size analyzer (Eye Tech, Netherlands). To ensure accuracy and repeatability, the instrument was calibrated before each run using certified reference microspheres (20 µm and 100 nm), requiring agreement between measured and nominal diameters to be within ± 1 %. Ultrapure water blanks were analyzed to confirm background noise levels were below 0.5 %. A standard suspension was analyzed every 4 h during the measurement; if key parameters like the median diameter (D50) deviated by more than ± 2 %, the instrument was recalibrated. All measurements were performed at a circulation speed of 2000 rpm in a temperature-controlled laboratory (23 ± 1 °C). Each tray sample was measured in triplicate, and the average value was used for subsequent analysis. Particle size was reported as a volume-equivalent diameter. Particle morphology, including aspect ratio and sphericity, was not independently characterized, and no shape-dependent correction was applied in the particle-size classification.

For each wind speed (U) and sampling-time (t) combination, the total dust mass retained in each tray was measured and the particle-size distribution (PSD) was recorded. Six cumulative diameter-threshold classes (PM2.5, PM10, PM20, PM30, PM40, and PM63) were defined from the laser-diffraction volume-equivalent diameter as Dv < 2.5, < 10, < 20, < 30, < 40, and < 63 µm, respectively. Throughout this study, the PM labels denote cumulative thresholds of laser-diffraction volume-equivalent diameter. The cumulative retained mass below each diameter threshold was then calculated as the product of the total retained mass and its corresponding cumulative volume fraction, and was then converted to an areal cumulative tray-retained mass M(t) (mgm-2) using the known tray area. For each wind-speed-time combination, five replicate trays were processed; results are summarized by the mean across replicates. The standard error of the mean (SEM, n=5) at each time point was used as the measurement uncertainty for model fitting. Before calculating D50, the differential volume fractions of each PSD were normalized to 100 %. D50 was then determined from the cumulative volume distribution by linear interpolation on the logarithmic diameter scale between the two adjacent diameter channels bracketing 50 %.

The temporal evolution of M(t) was represented by a first-order approach to an asymptote, 3M(t)=a(1-e-kt), where a (mgm-2) is the fitted asymptotic retained mass as t→∞. k(h-1) is the effective net-accumulation rate coefficient, where larger values indicate a faster approach to the fitted asymptote. The characteristic accumulation timescale was defined as τ=1/k(h), corresponding to the time required for the fitted curve to reach approximately 63 % of a. The initial net accumulation flux is defined as the initial slope of M(t), 4J0=dMdtt=0=ak(mgm-2h-1).

Because M(t), a, and J0 were not normalized by the time-varying concentration C(t), they are reported as tray-based net accumulation metrics. To assess whether small differences in initial airborne dust loading affected the wind-speed comparison, a (C0)-normalized sensitivity check was performed by scaling the retained mass with (Cref/C0), where (Cref) was the mean recorded initial concentration across the four wind-speed treatments.

Model parameters (a, k) were estimated separately for each wind-speed-size combination by weighted non-linear least squares (NLS), with weights wi=1/SEMi2 applied to the mean at time point ti. Positive constraints (a > 0, k > 0) were enforced. Wald 95 % confidence intervals for a and k were obtained from the NLS covariance matrix. Uncertainty in the derived metric J0=a⋅k, defined by Eq. (4), was propagated by the delta method to yield 95 % CIs (used in Fig. 3b).

To quantify wind-speed dependence for each size class, J0 was related to U using linear (J0∼U) and quadratic (J0∼U+U2) models; likelihood-ratio tests (LRTs) and ΔAIC were used to evaluate evidence for non-monotonicity. The wind-speed corresponding to the maximum fitted J0 response was summarized by the quadratic vertex Uopt = -β1/(2β2), with bootstrap 95 % CIs (10 000 resamples of the four (U,J0) pairs).

Many dry-deposition parameterizations describe deposition velocity for a given particle size and surface type as increasing or remaining unchanged with increasing wind speed or friction velocity, while treating resuspension separately. To quantify the departure of the present net-accumulation response from this simplified deposition-only expectation, a non-decreasing reference curve, J0,mono(U) was constructed for each size class by isotonic regression fitted to the four (U,J0) points. Deviations from the monotonic benchmark were summarized as 5R(U)=J0(U)J0,mono(U).

Here, R>1 indicates that the observed initial net accumulation flux exceeds the non-decreasing benchmark, whereas R<1 indicates that it falls below the benchmark.

All analyses were performed in R (R Core Team, 2024) (base stats for NLS, boot for resampling, ggplot2 for graphics).

The first-order exponential model (Eq. 3) provided an excellent description of the cumulative tray-retained accumulation kinetics for all wind-speed-size combinations, with coefficients of determination (R2) ranging from 0.889 to 0.992 and 75 % of fits achieving R2>0.95 (Fig. 2). This result indicates that a single effective timescale adequately characterizes the temporal evolution of dust accumulation under experimental conditions.

Under quiescent conditions (0 ms-1), fine particles (PM2.5, PM10) accumulated slowly, as evidenced by nearly linear cumulative curves, long characteristic times (τ ≈ 4.2 h for PM2.5; 1.4 h for PM10), and small rate coefficients (k = 0.24 h-1 for PM2.5; 0.71 h-1 for PM10) (Table S2). In contrast, coarse particles (PM30–PM63) approached their fitted asymptotes within about 1 h (τ < 1 h, a ≈ 600–750 mgm-2), exhibiting behavior dominated by gravitational settling.

Increasing wind speed from 0 to 2 ms-1 markedly accelerated early net accumulation across all size classes (Table S2). τ for PM2.5 shortened from 4.2 to 0.3 h (an order-of-magnitude faster approach to the fitted asymptote), while k increased from 0.24 to 3 h-1. Similarly, for PM10, τdecreased from 1.4 to 0.3 h and k increased to > 3 h-1. For medium and coarse particles, τ also decreased and k increased by factors of roughly 2–4, whereas their asymptotic loads a remained of the same order as under still air (typically within approximately 20 % of the 0 ms-1 values). In contrast, a for PM2.5 was reduced by roughly one quarter. These changes indicate that 2 ms-1 produced rapid early tray-retained accumulation, particularly for fine particles, while maintaining substantial retained mass for medium and coarse particles.

At 4 ms-1, τ remained short for all size classes (often < 0.5 h), and k stayed well above still-air values, indicating a rapid early approach to the fitted asymptote (Table S2). However, the asymptotic retained mass a for all sizes fell below their still-air values, decreasing by roughly 25 %–60 %, especially for fine-to-medium particles.

At 6 ms-1, the suppression in fine-to-medium tray-retained mass became most pronounced. For PM2.5 and PM10, a was reduced by about one order of magnitude relative to still air, indicating near-complete inhibition of effective accumulation despite still-elevated rate coefficients. Accumulation of PM20 and PM30 was also substantially suppressed. In contrast, a for the coarsest fractions (PM40, PM63) was similar to or slightly higher than under still air, but their kinetics were less favorable than at 2–4 ms-1, with longer τ and lower k compared with the low-wind optimum.

The auxiliary screening test identified an apparent critical wind-speed range of 5.87–6.01 ms-1 for marked dust mobilization from the tray surface, placing the 4 ms-1 treatment below and the 6 ms-1 treatment close to this range (Fig. S1 in the Supplement).

Analysis of characteristic times (Table S2) further shows that for most wind-speed-size combinations, τ is less than 0.5 h, indicating rapid mass accumulation during the early part of the experiments. The PSD comparison in Sect. 3.2 therefore uses the cumulative tray-retained samples collected at 0.5 and 3 h.

The concentration records were used to evaluate the comparability of initial airborne dust loading and the persistence of suspended dust during the low-wind phase. The recorded C0 ranged from 178.2 to 191.4 mgm-3, with a coefficient of variation of 3.1 % indicating comparable initial airborne dust loading among treatments. After normalizing by C0, the mean airborne concentration during the final 20 min was 5.32 %, 0.15 %, 9.27 %, and 4.24 % of C0 at 0, 2, 4, and 6 ms-1, respectively (Table S1 in the Supplement). The C0-based rescaling did not change the principal wind-speed ordering of the net-accumulation response. The 2 ms-1 treatment showed the lowest late-stage residual concentration, whereas the 4 and 6 ms-1 treatments maintained higher residual airborne concentrations, especially at 4 ms-1 (Fig. S2). This pattern indicates that the lower tray-retained mass at 4–6 ms-1 was accompanied by greater persistence of suspended dust and reduced effective transfer into stable near-surface retention.

Figure 3 compares net accumulation dynamics across the parameter space and during the initial stage. Figure 3a illustrates the distribution of the effective net-accumulation rate coefficient k. For fine-to-medium particles (PM2.5–PM20), k increased sharply from still air to 2 ms-1 and generally remained high at 4–6 ms-1, although the wind speed corresponding to the largest k varied among size classes. The maximum k occurred at 2, 4, 6 ms-1 for PM10, PM2.5 and PM20, respectively. For PM30–PM63, the largest k occurred at 4 ms-1. Figure 3b shows that J0 was highest at 2 ms-1 among the tested wind speeds for PM2.5–PM30, and was strongly reduced at 6 ms-1 for the fine size classes. Because J0=a⋅k, the maximum initial net accumulation flux did not necessarily coincide with the maximum fitted k. Quadratic fits across the four wind-speed levels yielded a model-implied peak wind speed (Uopt) of approximately 2–3 ms-1 for PM2.5–PM40, with bootstrap 95 % confidence intervals typically spanning approximately 2.3–3.3 ms-1. The most pronounced peaked response was found in the PM₃₀ class, whereas PM63 shows weaker evidence (Table S3).

Synthesizing Fig. 3a and b, a low-wind window centered near 2 ms-1 (model-inferred optimum around 2–3 ms-1) combines relatively high effective net-accumulation rate coefficients (Fig. 3a) with the highest observed J0 values (Fig. 3b) for PM2.5–PM30; stronger winds progressively suppress early net accumulation of these sizes and shift the relative contribution toward the coarse fraction.

The particle-size distribution (PSD) of net accumulation dust changed between 0.5 and 3 h in a wind-speed-dependent manner (Fig. 4).

Under quiescent conditions (0 ms-1), the cumulative material collected at 0.5 h showed a prominent coarse mode, with D50 = 13.4 µm, modal diameter ≈ 40.7 µm. By 3 h, the relative contribution of particles > 30 µm had decreased markedly, while the 10–20 µm range accounted for a larger fraction of the cumulative retained material (D50 = 10.8 µm, modal diameter ≈ 15.6 µm). This temporal change is consistent with a gravity-dominated regime which coarse particles deposit first, followed by medium-sized particles.

At 2 ms-1, D50 increased from 7.1 µm at 0.5 h to 9.8 µm at 3 h, representing an increase of approximately 38 %. The modal diameter shifted from 4.3 to 18.3 µm, while volume fraction at 18.3 µm increased from 5.3 % to 8.6 %. These changes indicate progressive enrichment of medium-sized particles in the cumulative retained material under weak shear.

At 4 ms-1, the PSDs were nearly identical, both exhibiting a narrow, persistent modal diameter at 4–5 µm, with D50 increasing only slightly from 6.3 µm at 0.5 h to 7.5 µm at 3 h. The similarity between the two distributions indicates that the fine-particle-dominated size spectrum was established early and changed moderately during the remainder of the experiment.

At 6 ms-1, the cumulative material collected at 0.5 h was dominated by 30–40 µm particles, with D50 = 29.3 µm, modal diameter ≈ 34.6 µm. At 3 h, D50 decreased to 17.9 µm and the modal diameter moved to approximately 29.5 µm, accompanied by a broader contribution from particles in the 10–20 µm range. This pattern is consistent with a greater early contribution of coarse particles, followed by an increased relative contribution of finer particles in the cumulative retained material.

In summary, the cumulative PSDs reveal distinct regimes among wind-speed treatments: gravity-controlled sequential settling in still air; shear-enhanced selective enrichment of fine-medium particles at 2 ms-1; rapid establishment of a stable, fine-dominated spectrum at 4 ms-1; and a large early relative contribution of coarse particles followed by a modest shift to finer sizes at 6 ms-1.

These large-scale closed-circuit wind tunnel experiments suggest a non-monotonic tendency and size-selective response of near-surface dust deposition to low wind speeds (0–6 ms-1). The first-order exponential model M(t)=a⋅(1-e-kt) captured the cumulative deposition for all size–wind combinations, indicating that net dust deposition can be approximated as a first-order kinetic process governed by a single effective time scale τ. The rate coefficient k and its reciprocal τ therefore provide robust dynamical metrics for comparing tray-retained accumulation responses across conditions.

Kinetic parameters show a consistent pattern. Deposition in still air is slow and largely controlled by gravitational settling. The introduction of weak turbulence at 2 ms-1 significantly accelerates early net accumulation of fine-to-medium particles without substantially reducing the asymptotic retained mass of medium-to-coarse particles, creating a distinct low-wind “window” for rapid and efficient dust accumulation. Quadratic fits of the initial net accumulation flux J0=ak indicate a low-wind optimum at ≈ 2–3 ms-1, with the strongest response at the experimental level of 2 ms-1.

Size-resolved PSD evolution further elucidates the size-selective nature of this response. In still air, the cumulative retained spectrum evolves sequentially from coarse to finer particles. Under weak shear (2 ms-1), D50 increased from 7.1 to 9.8 µm and the relative contribution near 18.3 µm increased, suggesting that weak turbulence not only accelerates fine-particle deposition but also facilitates their effective “coarsening” during settling, potentially involving aggregation. In contrast, at higher wind speeds (4–6 ms-1), the deposition spectrum is rapidly stabilized after an initial removal phase, entering a quasi-steady state with limited additional tray-retained accumulation and a gradual spectral shift back toward finer sizes, reflecting the strong suppression of net deposition for fine-to-medium particles.

Conventional parameterizations of particle dry deposition commonly calculate deposition velocity as a prescribed function of particle size, friction velocity, surface roughness, and land-cover type, while rebound and resuspension are represented using separate simplified treatments (Petroff and Zhang, 2010; Zhang and He, 2014; Zhang and Shao, 2014; Khan and Perlinger, 2017; Zeng et al., 2020). Classical particle-deposition frameworks account for particle-size-dependent transport and surface collection processes (Slinn, 1982), although the level of process detail differs among parameterizations. Numerical studies of particle-laden turbulent flows further show that predicted deposition rates are sensitive to turbulence closure, boundary conditions, and the treatment of near-wall velocity fluctuations (Tian and Ahmadi, 2007). However, these frameworks provide limited constraints on time-dependent net surface accumulation under low-wind conditions.

Observational studies, parameterization intercomparisons, and model-sensitivity experiments have demonstrated substantial uncertainty in particle dry deposition. Widely used parameterizations may overestimate deposition of accumulation-mode particles while underestimating coarse particle deposition over terrestrial surfaces (Petroff and Zhang, 2010; Adebiyi and Kok, 2020; Emerson et al., 2020; Farmer et al., 2021). Such size-dependent biases can affect simulated aerosol lifetime, atmospheric burden, and radiative forcing (Emerson et al., 2020). In dust simulations, differences in the representation of surface resistance, impaction collection, and particle rebound can also produce large differences in dry-deposition fluxes and atmospheric dust loading (Zeng et al., 2020).

To quantify the departure from a non-decreasing wind-speed response, the observed initial net accumulation flux J0 was compared against a non-decreasing benchmark J0,mono. For the PM2.5–PM40 cumulative classes, the observed J0 values at 2 ms-1 exceeded the benchmark by approximately 15 %–72 % (R = 1.15–1.72; Table S4). At 6 ms-1, J0 falls 45 %–91 % below the benchmark (R = 0.09–0.55), corresponding to an overestimation by factors of approximately 1.8–11 for the affected size classes. Deviations are smaller for PM63 (R ≈ 0.77 at 6 ms-1), suggesting that the non-monotonic response is most pronounced for fine-to-medium particles in the present setup.

This study yields several quantitative insights relevant to dry-deposition parameterizations in the low-wind regime: (i) a distinct peak in the initial net accumulation flux J0 occurs at approximately 2 ms-1 under the experimental conditions, whereas speeds of 4–6 ms-1 substantially reduce net deposition of fine-to-medium particles; (ii) kinetic time scales vary non-monotonically, with the characteristic time τ for fine particles reaching a minimum at 2–4 ms-1 while the fitted asymptotic retained mass a declines sharply at 4–6 ms-1, indicating that deposition rate and eventual deposited fraction do not vary synchronously with wind speed; (iii) distinct temporal evolution of the PSD emerges, with rapid progression toward the 10–20 µm range at 2 ms-1 contrasted against early spectral stabilization at 4–6 ms-1.

These findings complement multi-sampler comparison studies at the Izaña mountain station and evaluations of deposition schemes over rough surfaces (Bergametti et al., 2018; Waza et al., 2019). While previous studies highlighted flux-closure issues from an observation-parameterization discrepancy standpoint, our controlled experiments provide process-level understanding of wind-speed influences.

For numerical simulations, the size-resolved a, k, τ, and J0 values provide empirical constraints on the temporal response of effective surface retention under matched dust and surface conditions. Existing size-resolved dry-deposition schemes describe particle removal as a function of particle size, friction velocity, surface roughness, and surface collection properties, while model evaluations have demonstrated substantial sensitivity to the treatment of collection efficiency and particle rebound (Petroff and Zhang, 2010; Zhang and Shao, 2014; Khan and Perlinger, 2017; Zeng et al., 2020). In a coupled parameterization, k and τ characterize the adjustment timescale, a describes the fitted asymptotic retained mass under a specified initial dust loading, and J0 constrains the initial net surface flux. The observed response supports coupling conventional particle deposition with wind and size-dependent stable retention and a surface-specific, threshold-dependent re-entrainment term. The high J0 near 2 ms-1 and its decline toward 6 ms-1 provide benchmark behavior for evaluating such coupled parameterizations across the low-wind regime.

From a global dust cycle perspective, this non-monotonicity implies that net dry deposition in source regions under low post-dust wind conditions may be substantially higher than currently modeled, resulting in more rapid atmospheric dust load reduction and shorter effective transport distances. Conversely, under elevated background winds or complex topography, resuspension can extend fine particle residence time and enhance long-range transport fractions. These interpretations align with recent observationally constrained reassessments of dust size distributions and climatic impacts (Kok et al., 2017; Adebiyi and Kok, 2020; Emerson et al., 2020; Kok et al., 2021, 2023), which consistently identify model tendencies to underestimate coarse dust and near-source deposition while overestimating long-range transport and remote ocean dust burdens. Systematic underestimation of accumulation-mode and coarse particle deposition under weak-to-moderate turbulence would weaken near-source depositional sinks in models, likely resulting in overestimated dust load and radiative effects in remote oceanic and high-latitude regions.

First, the use of a single agricultural soil dust (< 63 µm) limits immediate generalization of the present results to dust from other origins, such as desert crusts, loess, or urban construction materials. Differences among dust materials may influence the observed kinetics through variations in airborne particle-size distribution, particle density and morphology, mineral composition, interparticle cohesion, and initial aggregation state. Coarser or denser particles would generally be expected to settle more rapidly, potentially producing a larger initial net accumulation flux J0, a shorter characteristic time τ, and a more gravity-dominated response. Finer, lower-density, or more porous particles may remain suspended for longer periods (Richards-Thomas and McKenna-Neuman, 2020). Mineralogy, specific surface area, and surface chemistry may further modify particle cohesion and aggregation. A stronger tendency to aggregate under weak shear could increase the effective settling size, whereas aggregate breakup under stronger shear could reduce retained mass (Mietta et al., 2009; Yu et al., 2022; Penlou et al., 2023). Consequently, both the magnitude of the observed low-wind maximum and the wind speed at which it occurs may vary among dust types.

Second, tray-retained mass characterizes effective near-surface retention under the present closed-circuit wind-tunnel and collector configuration. Particles outside the tray-retained fraction may have remained in recirculation or deposited on the side walls, ceiling, turning vanes, fan assembly, steel cover plate, and other internal surfaces, which were not quantified. The tray dimensions, 3 cm rim, smooth acrylic surface, and progressive removal of trays may also have affected local flow separation, particle rebound, and re-entrainment. The same initial layout, time-specific tray assignments, and retrieval sequence were used for all treatments, supporting comparisons among wind speeds. Absolute retained masses may vary for natural surfaces or other collector geometries.

Third, soil moisture was not investigated as an independent experimental variable. The sieved dust was oven-dried at 105 °C for 8 h before each experiment, and the reported kinetics therefore represent dry dust conditions. Residual gravimetric water content was not measured after oven drying. Soil moisture can modify interparticle cohesion, the threshold wind speed for particle mobilization, aggregation, particle-surface adhesion, and resistance to re-entrainment (Fécan et al., 1999; Shao, 2008; Kok et al., 2012). Because the same dust batch and drying procedure were used for all wind-speed treatments, moisture differences are unlikely to explain the observed differences among treatments. However, the magnitude of the low-wind maximum and the wind speed at which it occurs may differ under moist field conditions.

Finally, particle shape was not independently characterized. Mineral dust particles are commonly non-spherical, and their flatness, elongation, and orientation can alter aerodynamic drag and settling velocity (Ginoux, 2003; Bagheri and Bonadonna, 2016). Consequently, volume-equivalent diameter alone does not fully describe the aerodynamic behavior of particles within each cumulative diameter-threshold class. Particle shape may have influenced aerodynamic transport, settling velocity, and surface retention, thereby affecting the absolute retained mass and fitted kinetic descriptors. Future experiments combining laser diffraction with microscopic measurements of aspect ratio and sphericity would allow this effect to be quantified.