Prediction of gas diffusion in complicated terrain by a potential flow model

A numerical model was developed to simulate gaseous diffusion in complicated terrain. This model calculates the air flow as a potential flow by the Boundary Element Method, and gaseous diffusion by an analytical Gaussian equation in the potential flow. Plume spreads σ_y and σ_z are modified by multiregression equations derived from wind tunnel experiments, and the terrain height is elongated depending on the atmospheric stability.First, tracer data from Cinder Cone Butte in the U.S. measured by the U.S.-EPA were predicted by the model in order to examine the prediction accuracy under stable conditions. The averaged ratio of the observed concentration to predicted concentration for 12 runs was better than a factor of 10. Next, tracer data from the Geysers area in the U.S. measured by the U.S.-DOE were used to examine the prediction accuracy under neutral conditions. The ratio of the observed concentration to predicted concentration for two runs under neutral conditions was better than factor of two at most locations, but prediction capability is poor in blocked or separated flow conditions.     

Verification of the shelter effect of a windbreak on coal piles in the POSCO open storage yards at the Kwang-Yang works

The use of windbreaks to reduce wind-blown coal dust at the POSCO Kwang-Yang open storage yards was studied using wind simulations on a scale model of the yards. Based on these simulation results, a full-scale wind fence was constructed on two sides of the yard. Here, we present results on the wind behavior both for the real yard and for the simulation results that guided its construction. Wind-tunnel simulations were used to study the effect of a porous wind fence of porosity ε=30% on the surface pressure and shear stress on coal piles using a 1/1200 model of the POSCO Kwang-Yang open storage yards. In addition, the shelter effects found in the model system were verified in field measurements on the full-scale system. The storage yard model was fully embedded in an atmospheric surface boundary layer over open terrain. The fence and coal pile model had the same height (12.2 mm) and Reynolds number (Re=1.6×10⁴, based on the model height). The mean and fluctuating surface-pressure distributions on the coal piles, which are closely related to the dust emission from the surface, were measured for several directions of the oncoming wind. The wind directions pertinent to the study were determined by statistical analysis of seasonal wind data over the storage yard. A porous wind fence of porosity ε=30% was found to be useful for reducing the wind speed without the formation of a recirculating bubble behind the fence. In addition, the fence caught the wind-borne particles when it was located behind the coal piles. The wind fence reduced the pressure fluctuations and surface shear stress on the coal piles to less than half of the levels observed in the no fence case. To verify the effectiveness of the porous wind fence installed around the Kwang-Yang open storage yard, the local wind speed and the concentration of suspended particles were measured directly. Full-scale porous fences installed around the Kwang-Yang open storage yard greatly decreased the turbulence intensity of the wind over the coal piles and reduced the total suspension particles by 70–80%.     

Use of CALPUFF for exposure assessment in a near-field,complex terrain setting

CALPUFF is an atmospheric source-receptor model recommended by the U.S. Environmental Protection Agency for use on a case-by-case basis in complex terrain and wind conditions. The ability of the model to provide useful information for exposure assessments in areas with those topographical and meteorological conditions has received little attention. This is an important knowledge gap for use of CALPUFF outside of regulatory applications, such as exposure analyses conducted in support of risk assessments and health studies. We compared deposition of cadmium (Cd), lead (Pb), and zinc (Zn) calculated with CALPUFF as a result of emissions from a zinc smelter with corresponding concentrations of the metals measured in attic dust and soil samples obtained from the surrounding area. On a point-by-point analysis, predictions from CALPUFF explained 11% (lead) to 53% (zinc) of the variability in concentrations measured in attic dust. Levels of heavy metals in soil interpolated to 100 residential addresses from the distribution of concentrations measured in soil samples also agreed well with deposition predicted with CALPUFF: R² of 0.46, 0.76, and 079 for Pb, Cd, and Zn, respectively. Community-average concentrations of Cd, Pb, and Zn measured in soil were significantly (p < 0.0001) and strongly correlated (R² ranged from 0.77 to 0.98) with predicted deposition rates. These findings demonstrate that CALPUFF can provide reasonably accurate predictions of the patterns of long-term air pollutant deposition in the near-field associated with emissions from a discrete source in complex terrain. Because deposition estimates are calculated as a linear function of air concentrations, CALPUFF is expected to be reliable model for prediction of long-term average, near-field ambient air concentrations in complex terrain as well.     

Investigation of air pollution distribution in Linz: case studies to evaluate a K-type diffusion model coupled with a mass-consistent wind model

An Eulerian diffusion model coupled with a refined mass consistent wind model is developed for the operational forecasting of pollution distribution in complex terrain. The model is evaluated for a city situated in complex terrain. The study is carried out for a 20×20 km² area surrounding Linz, one of the industrial cities of Austria. The models are initialized with routinely measured meteorological parameters and topology information derived from the Geographical Information Systems (GIS). Four case studies, representative for major pollution episodes, are presented for model evaluation. The case studies include presence of a thermally induced wind system, presence of cold front an easterly southeasterly flow and a westerly–northwesterly flow. In presence of thermally induced wind systems, the flow field is most complex and existence of a shallow mixed layer with residual layer aloft enhances the pollution levels inside the city. Second case is used to study the development of pollution distribution inside the city in presence of low-level inversions and associated with low surface wind speeds. The low wind speeds in the surface layer lead to less mechanical generation of turbulence and lateral transport. The case studies of easterly and westerly flow fields are carried out to assess the capability of model under most frequently observed meteorological situations. The model is able to reproduce the pollution distribution near the slopes. There were over prediction inside the city in presence of thermally induced wind systems and is attributed to inadequate model physics during convective case. The present model setup is found to be a useful tool for the routine forecasting of pollution and could also be tested for other complex terrains.     

Improving ozone modeling in complex terrain at a fine grid resolution: Part I – examination of analysis nudging and all PBL schemes associated with LSMs in meteorological model

Meteorological variables such as temperature, wind speed, wind directions, and Planetary Boundary Layer (PBL) heights have critical implications for air quality simulations. Sensitivity simulations with five different PBL schemes associated with three different Land Surface Models (LSMs) were conducted to examine the impact of meteorological variables on the predicted ozone concentrations using the Community Multiscale Air Quality (CMAQ) version 4.5 with local perspective. Additionally, the nudging analysis for winds was adopted with three different coefficients to improve the wind fields in the complex terrain at 4-km grid resolution. The simulations focus on complex terrain having valley and mountain areas at 4-km grid resolution. The ETA M–Y (Mellor–Yamada) and G–S (Gayno–Seaman) PBL schemes are identified as favorite options and promote O₃ formation causing the higher temperature, slower winds, and lower mixing height among sensitivity simulations in the area of study. It is found that PX (Pleim–Xiu) simulation does not always give optimal meteorological model performance. We also note that the PBL scheme plays a more important role in predicting daily maximum 8-h O₃ than land surface models. The results of nudging analysis for winds with three different increased coefficients' values (2.5, 4.5, and 6.0 × 10^?4 s^?1) over seven sensitivity simulations show that the meteorological model performance was enhanced due to improved wind fields, indicating the FDDA nudging analysis can improve model performance considerably at 4-km grid resolution. Specifically, the sensitivity simulations with the coefficient value (6.0 × 10^?4) yielded more substantial improvements than with the other values (2.5 and 4.5 × 10^?4). Hence, choosing the nudging coefficient of 6.0 × 10^?4 s^?1 for winds in MM5 may be the best choice to improve wind fields as an input, as well as, better model performance of CMAQ in the complex terrain area. As a result, a finer grid resolution is necessary to evaluate and access of CMAQ results for giving a detailed representation of meteorological and chemical processes in the regulatory modeling. A recommendation of optimal scheme options for simulating meteorological variables in the complex terrain area is made.     

The use of wind fields in a land use regression model to predict air pollution concentrations for health exposure studies

A methodology is developed to include wind flow effects in land use regression (LUR) models for predicting nitrogen dioxide (NO₂) concentrations for health exposure studies. NO₂ is widely used in health studies as an indicator of traffic-generated air pollution in urban areas. Incorporation of high-resolution interpolated observed wind direction from a network of 38 weather stations in a LUR model improved NO₂ concentration estimates in densely populated, high traffic and industrial/business areas in Toronto-Hamilton urban airshed (THUA) of Ontario, Canada. These small-area variations in air pollution concentrations that are probably more important for health exposure studies may not be detected by sparse continuous air pollution monitoring network or conventional interpolation methods. Observed wind fields were also compared with wind fields generated by Global Environmental Multiscale-High resolution Model Application Project (GEM-HiMAP) to explore the feasibility of using regional weather forecasting model simulated wind fields in LUR models when observed data are either sparse or not available. While GEM-HiMAP predicted wind fields well at large scales, it was unable to resolve wind flow patterns at smaller scales. These results suggest caution and careful evaluation of regional weather forecasting model simulated wind fields before incorporating into human exposure models for health studies. This study has demonstrated that wind fields may be integrated into the land use regression framework. Such integration has a discernable influence on both the overall model prediction and perhaps more importantly for health effects assessment on the relative spatial distribution of traffic pollution throughout the THUA. Methodology developed in this study may be applied in other large urban areas across the world.     

A model of wet deposition to complex terrain

A two dimensional model of the seeder-feeder mechanism of orographic rainfall enhancement has been developed. The model has been extended to include the deposition of aerosol material incorporated into the orographic feeder cloud by nucleation scavenging. Parameterizations of any changes in the concentration of SO₄²⁻ in the cloud due to chemical reactions have also been included. The model is used to predict the rainfall enhancement and SO₄²⁻ deposition over terrain consisting of two parallel ridges oriented perpendicular to the wind. A wide range of spatial scales has been used of up to 150 km. It is found that the patterns of rainfall enhancement and deposition are strongly dependent on the spatial scales, the atmospheric structure and the cloud chemistry.     

Numerical study of atmospheric dispersion of a substance released from an industrial complex in the southern coast of Korea

Diurnal variations of wind field and pollutant dispersion in a complex terrain with a shoreline were investigated under the insolation conditions of summer and winter. The area is located in the south of the Korean Peninsula and includes a large petrochemical industrial complex. The Regional Atmospheric Modeling System (RAMS) was used in the simulation study. Initially, horizontally homogeneous wind fields were assumed on the basis of sounding data at the nearby upper-air station for days with morning wind speeds below 2 m s⁻¹. On these days, the sea breeze prevailed in summer while the land breeze lasted for a few hours in the morning; the effect of synoptic winds was strong in winter with some inclusion of wind variations owing to the interaction between sea and land. The predicted wind direction at the location of the weather station captured an important change of the sea/land breeze of the observed one. In the morning, both in summer and winter, complicated wind fields with low wind speeds resulted in high pollutant concentrations almost all over the area. On the other hand, in the afternoon, the wind field was rather uniform and the terrain effects were not significant even in the mountainous area with the development of a mixing layer.     

Estimating dust emission from a sandbank on the downstream Jhuoshuei River under strong wind conditions

An empirical emission model based on experimental data was proposed. The total suspended particulates (TSP) emission model obtained by using stepwise multiple-regression analysis was significant (p<0.001); moreover, the relatively high value of R-squared (R²=0.85), which indicated that four parameters included in the model (air temperature, soil silt content, soil moisture content, and wind speed) accounted for the particulate emissions from a sandbank. The results of the multiple-regression analysis demonstrated that the TSP emission factors increased with increase in air temperature, soil silt content and wind speed, but were inversely affected by the soil moisture content. The model equation verified the experimental results and proved itself to be an important tool in predicting the dust emissions from a sandbank under strong wind conditions.     

Observations and predictions of jet diffusion flame behaviour

A simple model has been developed for jet diffusion flames to estimate flame height (h_f) and angle of the flame to the vertical (α_B). The model is based upon the assumption that flame behaviour is dominated by momentum effects. Buoyancy influences on behaviour are assumed to be negligible.Predictions of the model were assessed against flame parameters as observed in a wind tunnel and during field tests with an industrial flare. The wind tunnel studies involved experiments with hydrocarbon (methane, propane, ethylene, butane) diffusion flames. Field experiments involved measuring h_f and α_B of flames resulting from the combustion of acid gas-fuel gas mixtures possessing molecular weights of about 37 g mol⁻¹.The one-to-one correlation coefficient between predicted and observed behaviour resulting from combustion of all hydrocarbon fuels, except methane, was about 0.85. The model significantly underestimated flame heights for methane. This seems to have been due to the neglect of buoyancy effects which could be appreciable for this relatively light gas.Evaluation of results from the tests conducted with the industrial flare showed a one-to-one correlation coefficient between observed and predicted values of h_f to be 0.92. The corresponding magnitude for the correlation coefficient between observed and predicted values of α_B was only 0.71. A partial explanation for this relatively low correlation coefficient lies in the small range of α_B values contained in the population sample.     

The effects of meteorology on ozone in urban areas and their use in assessing ozone trends

The United States Environmental Protection Agency issues periodic reports that describe air quality trends in the US. For some pollutants, such as ozone, both observed and meteorologically adjusted trends are displayed. This paper describes an improved statistical methodology for meteorologically adjusting ozone trends as well as characterizes the relationships between individual meteorological parameters and ozone. A generalized linear model that accommodates the nonlinear effects of the meteorological variables was fit to data collected for 39 major eastern US urban areas. Overall, the model performs very well, yielding R² statistics as high as 0.80. The analysis confirms that ozone is generally increasing with increasing temperature and decreasing with increasing relative humidity. Examination of the spatial gradients of these responses show that the effect of temperature on ozone is most pronounced in the north while the opposite is true of relative humidity. By including HYSPLIT-derived transport wind direction and distance in the model, it is shown that the largest incremental impact of wind direction on ozone occurs along the periphery of the study domain, which encompasses major NO_x emission sources.     

CFD modelling of small particle dispersion: The influence of the turbulence kinetic energy in the atmospheric boundary layer

When considering the modelling of small particle dispersion in the lower part of the Atmospheric Boundary Layer (ABL) using Reynolds Averaged Navier Stokes simulations, the particle paths depend on the velocity profile and on the turbulence kinetic energy, from which the fluctuating velocity components are derived to predict turbulent dispersion. It is therefore important to correctly reproduce the ABL, both for the velocity profile and the turbulence kinetic energy profile.For RANS simulations with the standard k–ε model, Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the k–ε turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 46–47, 145–153.) proposed a set of boundary conditions which result in horizontally homogeneous profiles. The drawback of this method is that it assumes a constant profile of turbulence kinetic energy, which is not always consistent with field or wind tunnel measurements. Therefore, a method was developed which allows the modelling of a horizontally homogeneous turbulence kinetic energy profile that is varying with height.By comparing simulations performed with the proposed method to simulations performed with the boundary conditions described by Richards and Hoxey (1993. Appropriate boundary conditions for computational wind engineering models using the k–ε turbulence model. Journal of Wind Engineering and Industrial Aerodynamics 46–47, 145–153.), the influence of the turbulence kinetic energy on the dispersion of small particles over flat terrain is quantified.     

Numerical simulation of flow and dispersion around an isolated cubical building: The effect of the atmospheric stratification

The aim of this work is to investigate atmospheric flow and dispersion of contaminants in the vicinity of single buildings under different stability conditions. The mathematical model used is based on the solution of equations of conservation of mass, linear momentum and energy with the use of a non-standard κ–? turbulence model. The modifications proposed in the κ–? model are the inclusion of the Kato and Launder correction in the production of turbulent kinetic energy and the use of a modified wall function. Results are presented of numerical simulations of dispersion around a cubical obstacle, under neutral, stable and unstable atmospheric conditions. Experimental data from wind tunnel and field trials obtained by previous authors are used to validate the numerical results. The numerical simulation results show a reasonable level of agreement with field and wind tunnel concentration data. The deviation between model results and field experimental data is of the same order as the deviation between field and wind tunnel data.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.     

Assessment of transboundary mass fluxes of air pollutants by aircraft measurements: A preliminary survey with reference to a case study

A technique has been employed by which transboundary mass fluxes of SO², SO₄²⁻, NO_x, NO₃⁻, and O₃ are assessed. As an example the results of one measuring flight are presented. This flight was carried out along the eastern and western border of the Netherlands. An uncertainty analysis yields that the accuracy of calculated transboundary mass fluxes is most dependent on the accuracy of the values for the depth of the mixing layer and the wind velocity. Mass fluxes calculated in this case study appear to be accurate within ± 55 %, apart from inaccuracies due to non-representativity of concentration and wind data with respect to the mixing layer. On the basis of the uncertainty analysis, recommendations for further improvement of the method are made so that a reduction of this ± 55 % to ± 20 % can be achieved. Finally, conclusions about the origin of the observed pollution are drawn.     

A Lagrangian stochastic model for predicting concentration fluctuations in urban areas

A combined Lagrangian stochastic model with a micromixing sub-model is used to estimate the fluctuating concentrations observed in two wind tunnel experiments. The Lagrangian stochastic model allows fluid trajectories to be simulated in the inhomogeneous flow, while the mixing model accounts for the dissipation of fluctuations using the interaction by exchange with the mean (IEM) mechanism. The model is first tested against the open terrain, wind tunnel data of Fackrell, J.E. and Robins, A.E. [1982. Concentration fluctuations and fluxes in plumes from point sources in a turbulent boundary layer. Journal of Fluid Mechanics 117, 1–26] and shows good agreement with the observed mean concentrations and fluctuation intensities. The model is then compared with the wind tunnel simulation of a two-dimensional street canyon by Pavageau, M. and Schatzmann, M. [1999. Wind tunnel measurements of concentration fluctuations in an urban street canyon. Atmospheric Environment 33, 3961–3971]. Despite the limitations of the k–ε turbulence scheme and the IEM mixing mechanism, the model reproduces the fluctuation intensity pattern within the canyon well. Overall, the comparison with both sets of wind tunnel experiments are encouraging, and the simplicity of the model means that predictions in a complex, three-dimensional geometry can be produced in a practicable amount of time.     

System design for a real-time atmospheric dispersion model

An interactive, real-time simulation model has been commissioned at the Koeberg nuclear power station near Cape Town. Use of sheared puffs, solved using only the C₀₀, C₀₁, C₁₀, C₀₂, C₂₀ and C₁₁ horizontal moments, reduced computation and allowed arbitrary variation of the wind vector with height. Wind profiles and diffusivity were given spatial definition about the coastal interface by interpolation between six telemetered mast locations within 20 km of Koeberg. Specific design for a real-time environment revealed important principles concerning division into asynchronous tasks, protection against data failures, and on-line operator interaction. With a grid resolution of 300 m in a 40 km × 40 km map area, the model runs at least three times faster than real-time on a HP3000 minicomputer.     

Evaluation of a Gaussian and a Lagrangian model against a roadside data set,with emphasis on low wind speed conditions

The evaluation of the high percentiles of concentration distributions is required by most national air quality guidelines, as well as the EU directives. However, it is problematic to compute such high percentiles in stable, low wind speed or calm conditions. This study utilizes the results of a previous measurement campaign near a major road at Elimäki in southern Finland in 1995, a campaign specifically designed for model evaluation purposes. In this study, numerical simulations were performed with a Gaussian finite line source dispersion model CAR-FMI and a Lagrangian dispersion model GRAL, and model predictions were compared with the field measurements. In comparison with corresponding results presented previously in the literature, the agreement of measured and predicted data sets was good for both models considered, as measured using various statistical parameters. For instance, considering all NO_x data (N=587), the so-called index of agreement values varied from 0.76 to 0.87 and from 0.81 to 1.00 for the CAR-FMI and GRAL models, respectively. The CAR-FMI model tends to slightly overestimate the NO_x concentrations (fractional bias FB=+14%), while the GRAL model has a tendency to underestimate NO_x concentrations (FB=−16%). The GRAL model provides special treatment to account for enhanced horizontal dispersion in low wind speed conditions; while such adjustments have not been included in the CAR-FMI model. This type of Lagrangian model therefore predicts lower concentrations, in conditions of low wind speeds and stable stratification, in comparison with a standard Lagrangian model. In low wind speed conditions the meandering of the flow can be quite significant, leading to enhanced horizontal dispersion. We also analyzed the difference between the model predictions and measured data in terms of the wind speed and direction. The performance of the CAR-FMI model deteriorated as the wind direction approached a direction parallel to the road, and for the lowest wind speeds. However, the performance of the GRAL model varied less with wind speed and direction; the model simulated better the cases of low wind speed and those with the wind nearly parallel to the road.     

A new approach for estimating emissions of organic solutes and organic solvents under wind speeds

A new approach is developed to predict the volatilization loss of the pure liquid and the volatilization rates of organic solutes with different Henry's law constants (H) under wind speed. The tested compounds include eight volatile organic compounds for pure liquid and the forty-one organic solutes with different H compounds are divided into three groups that span seven H orders. The wind speed is set from 0 to 6.0 ms^?1. A characteristic parameter ε was established to estimate volatilization loss of pure organic compounds. The mass transfer coefficient (K_OL) ratios of the organic solutes, under both wind speed and still conditions, are applied to describe the volatilization characteristics of the selected solutes. The curve profile for K_OL ratios and ε values relative to the selected wind speed can be divided into two stages, the sharp-rise stage and the stable-linearity stage. The critical finding is the ε values for the different organic compounds under a specific wind speed approach a constant. The changes in the curve profile of the K_OL ratios are similar to the ε values of the pure organic compounds. It is also found the relatively lower H compounds exhibit a sensitive wind effect on the K_OL ratios. The K_OL ratios of the relatively higher H compounds indicate a similar linear increase with the increasing wind speed in the two stages. Accordingly, concentrations of the organic compounds at the interface are thought to the primary factor. The obtained results could be a good reference to estimate volatilization loss of the organic solutes or the organic solvents under different wind speed conditions.     

The effect of humidity and state of water surfaces on deposition of aerosol particles onto a water surface

Deposition processes of particles with dry diameter larger than about 10 μm are dominated by gravitational settling, while molecular diffusion and Brownian motion predominate the deposition processes of particles smaller than 0.1 μm in dry diameter. Many air pollution derived elements exhibit characteristics common to sub-micron particles. The objective of the present study is to examine the effects of meteorological conditions within the turbulent transfer layer on the deposition velocity of particles with dry diameter between 0.1 and 1 μm. It is for these sub-micron particles that particle growth by condensation in the deposition layer, the broken water surface effect and the enhanced transfer process due to atmospheric turbulence in the turbulent transfer layer play important roles in controlling the particle deposition velocity. Results of the present study show that the `dry air’ assumption of Williams’ model is unrealistic. Effects of ambient air relative humidity and water surface temperature cannot be ignored in determining the deposition velocity over a water surface. Neglecting effects of ambient air relative humidity and water surface temperature will result in defining atmospheric stability incorrectly. It is found that the largest effect of air relative humidity on deposition velocity occurs at an air–water temperature difference corresponding to the point of `displaced neutral stability'. For a given wind speed of U=5 m s⁻¹ the additive effects of water surface temperature, T_w, changes from 5 to 25°C and ambient air relative humidity variations from 85 to 60%, respectively, lead to a maximum difference in v_d of about 20%. For a higher wind speed of 10 m s⁻¹, however, the corresponding change in v_d reduces to less than 5%. This is further confirmation that wind speed is one of the strongest variables that governs the magnitude of v_d. The present study also found that the broken surface transfer coefficient, k_bs, given as a multiple of the smooth surface transfer coefficient, k_ss, is physically more meaningful than assigning it a constant value independent of particle size. The method used in this study requires only a single level of atmospheric data coupled with the surface temperature measurement. The present method is applicable for determining deposition velocity not only at the conventional measurement height of 10 m but also at any other heights that are different from the measurement height.