On dispersion above a forest—Measurements and methods

Data collected over a mixed conifer/deciduous forest at the U.S. Department of Energy’s Savannah River Site in South Carolina using sonic anemometry reveal that on-site and real-time measurements of the velocity component standard deviations, σ_v and σ_w, are preferred for dispersion modeling. Such data are now easily accessible, from the outputs of cost-effective and rugged sonic anemometers. The data streams from these devices allow improvements to conventional methodologies for dispersion modeling. In particular, extrapolation of basic input data from a nearby location to the site of the actual release can be facilitated. In this regard reliance on the velocity statistics σ_v and σ_w appears to be preferred to the conventional σ_θ and σ_?. In the forest situations addressed here, the uncertainties introduced by extrapolating initializing properties (u, θ, σ_θ, and σ_?, or alternatively, σ_v and σ_w) from some location of actual measurement to some nearby location where an actual release occurs are similar to those associated with the spread of the plume itself and must be considered in any prediction of the likelihood of downwind concentration (exposure) exceeding some critical value, i.e., a regulatory standard. Consideration of plume expansion factors related to meander will not necessarily cause predicted downwind maxima within a particular plume to be decreased; however, the probability of exposure to this maximum value at any particular location will be reduced. Three-component sonic anemometers are affordable and reliable, and are now becoming a standard for meteorological monitoring programs subject to regulatory oversight. The time has come for regulatory agencies and the applied dispersion community to replace the traditional discrete sets of dispersion coefficients based on Pasquill stability by the direct input of measured turbulence data.

Implications: The continued endorsement of legacy Pasquill-Gifford stability schemes is presently under discussion among professional groups and regulatory agencies. The present paper is an attempt to introduce some rationality, for the case of a forested environment.     

Minimum turbulence assumptions and u* and L estimation for dispersion models during low-wind stable conditions

The U.S. Environmental Protection Agency (EPA) short-distance dispersion model, AERMOD, has been shown to overpredict by a factor of as much as 10 when compared with observed concentrations from continuous releases at the Oak Ridge, TN (OR), and Idaho Falls, ID (IF), field experiments during stable periods when wind speeds often dropped below 1 m/sec. Some of this overprediction tendency can be reduced by revising AERMOD's meteorological preprocessor's parameterizations of the friction velocity, u _* , during low-wind stable conditions, thus increasing the calculated σ _v and σ _w and hence the lateral and vertical dispersion rates. Observations show that as the mean wind speed approaches zero at night, there is always significant σ _v and σ _w over time periods of 15 to 60 min, while standard Monin–Obukhov Similarity Theory (MOST) predicts that σ _v and σ _w will approach zero. This paper focuses on the u _* estimation methods and the minimum turbulence (σ _v and σ _w ) assumptions in AERMOD (beta option 4) and two widely used U.S. operational dispersion models, AERMOD (v12345) and SCICHEM. The U.S. EPA has provided results of its tests with the OR and IF data, with its base AERMOD version and its December 2012 modified versions, which assume adjustments to the low-wind u _* and increases in the minimum σ _v parameterization. SCICHEM has relatively small mean bias for both data sets. The revised AERMOD shows much less mean bias, agreeing more with SCICHEM.

Implications:

Suggestions are made for improvements to dispersion models such as AERMOD to correct overpredictions during light-wind stable conditions. Methods for estimating u_*, L, and the minimum turbulence parameters (σ_v and σ_w) are reviewed and compared. SCICHEM and the current operational version and an optional beta version (December 2012) of AERMOD are evaluated with tracer data from low-wind stable field experiments in Idaho Falls and Oak Ridge. It is seen that the operational version of AERMOD overpredicts by a factor of 2 to 10, while the optional beta version of AERMOD and SCICHEM have much less bias.     

An experimental investigation of some methods of estimating turbulence parameters for use in dispersion models

The standard deviations of wind fluctuations in the horizontal and vertical directions, σ_θ and σ_φ, are now used in some pollution dispersion models to estimate the plume spread parameters σ_y and σ_z. Methods exist for estimating σ_θ and σ_φ when direct measurements are unavailable, using routine weather observations or wind measurements and temperature profiles from meteorological towers. In this paper such estimates are compared with direct measurements made at a height of 56 m, for a sampling time of 1 h, for a range of meteorological conditions. The work was carried out at a site in relatively irregular terrain. This was flat to rolling with a mixed surface cover within 1 km of the tower, with hills rising beyond that distance. Profile measurements were made with robust instruments rather than research grade sensors.Estimates of σ_φ made during the daytime agreed well with measurements, with a bias in the estimates of less than 0.4°. The r.m.s. differences between estimates and measurements were 1.1° (profile method) and less than 2° (routine weather observations method). Daytime σ_θ estimates were generally too low (bias 5–6°), although they were positively correlated with the measurements. At night σ_θ, was severely underestimated, and σ_φ was also underestimated.     

Statistical and diagnostic evaluation of a new-generation urban dispersion modelling system against an extensive dataset in the Helsinki area

We have developed a modelling system for predicting the traffic volumes, emissions from stationary and vehicular sources, and atmospheric dispersion of pollution in an urban area. This paper describes a comparison of the NO_x and NO₂ concentrations predicted using this modelling system with the results of an urban air quality monitoring network. We performed a statistical analysis to determine the agreement between predicted and measured hourly time series of concentrations at four permanently located and three mobile monitoring stations in the Helsinki Metropolitan Area in 1996–1997 (at a total of ten urban and suburban measurement locations). At the stations considered, the so-called index of agreement values of the predicted and measured time series of the NO₂ concentrations vary between 0.65 and 0.82, while the fractional bias values range from −0.29 to +0.26. In comparison with corresponding results presented in the literature, the agreement between the measured and predicted datasets is good, as indicated by these statistical parameters. The seasonal variations of the NO₂ concentrations were analysed in terms of the relevant meteorological parameters. We also analysed the difference between model predictions and measured data diagnostically, in terms of meteorological parameters, including wind speed and direction (the latter separately for two wind speed classes), atmospheric stability and ambient temperature, at two monitoring stations in central Helsinki. The modelling system tends to overpredict the measured NO₂ concentrations both at the highest (u⩾6 m s⁻¹) and at the lowest wind speeds (u<2 m s⁻¹). For higher wind speeds, the modelling system overpredicts the measured NO₂ concentrations in certain wind direction intervals; specific ranges were found for both monitoring stations considered. The modelling system tends to underpredict the measured concentrations in convective atmospheric conditions, and overpredict in stable conditions. The possible physico-chemical reasons for these differences are discussed.     

Unsteady characteristics of the dispersion process in the vicinity of a pig barn. Wind tunnel experiments and comparison with field data

Two complementary methods, field experiments and physical modelling in a wind tunnel, have been used to investigate the dispersion of tracer-gas released from the ventilation system of a pig barn, under near-neutral stability conditions. In both cases, concentration fluctuations were measured and the deduced statistical results were compared. The choice of data processing applied to the time series of concentration was motivated by special issues in the assessment of odour annoyances: “where, how often, how long and how strong does it smell?” These features were described by the mean concentration distribution, the intermittency factor, the persistence and the 90-percentile. The good agreement between field and wind tunnel data confirmed the ability to replicate in wind tunnel the unsteady properties of a dispersion process, if the unsteady turbulent behaviour of the atmospheric boundary layer was properly modelled.A parametrical study of the influence on the dispersion process of the ratio between the exhaust velocity from the stack and the wind speed was then performed in wind tunnel. The fundamental outcome was that the near-field dispersion process under neutral stability conditions, despite the strong influence of the building wake, was for the most part driven by the meandering behaviour of the plume and not so much by the diffusion process.This study was also focused on the influence of the averaging time on the statistical results. The scatter generated by using dimensionless averaging times 200<T_a^*<400 (used during field experiments) instead of T_a^*→∞ (averaging time to ensure reproducible statistic results) was quantified in the wind tunnel. A degree of representativity of the results obtained from short-term samples, compared to fully converged statistical results was therefore assessed.     

Analysis of air quality data near roadways using a dispersion model

We used a dispersion model to analyze measurements made during a field study conducted by the U.S. EPA in July–August 2006, to estimate the impact of traffic emissions on air quality at distances of tens of meters from an eight-lane highway located in Raleigh, NC. The air quality measurements consisted of long path optical measurements of NO at distances of 7 and 17 m from the edge of the highway. Sonic anemometers were used to measure wind speed and turbulent velocities at 6 and 20 m from the highway. Traffic flow rates were monitored using traffic surveillance cameras. The dispersion model [Venkatram, A., 2004. On estimating emissions through horizontal fluxes. Atmospheric Environment 38, 2439–2446] explained over 60% of the variance of the observed path averaged NO concentrations, and over 90% of the observed concentrations were within a factor of two of the model estimates.Sensitivity tests conducted with the model indicated that the traffic flow rate made the largest contribution to the variance of the observed NO concentrations. The meteorological variable that had the largest impact on the near road NO concentrations was the standard deviation of the vertical velocity fluctuations, σ_w. Wind speed had a relatively minor effect on concentrations. Furthermore, as long as the wind direction was within ±45° from the normal to the road, wind direction had little impact on near road concentrations. The measurements did not allow us to draw conclusions on the impact of traffic-induced turbulence on dispersion. The analysis of air quality and meteorological observations resulted in plausible estimates of on-road emission factors for NO.     

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.     

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.     

Acetamiprid,carbendazim, diuron and thiamethoxam sorption in two Brazilian tropical soils

Sorption of acetamiprid ((E)-N1-[(6-chloro-3-pyridyl)methyl]-N2-cyano-N1-methylacetamidine), carbendazim (methyl benzimidazol-2-ylcarbamate), diuron (N-(3,4-dichlorophenyl)-N, N-dimethyl urea) and thiamethoxam (3-(2-chloro-thiazol-5-ylmethyl)-5-methyl-[1,3,5]oxadiazinan-4-ylidene-N-nitroamine) was evaluated in two Brazilian tropical soils, Oxisol and Entisol, from Primavera do Leste region, Mato Grosso State, Brazil. To describe the sorption process, batch experiments were carried out. Linear and Freundlich isotherm models were used to calculate the K _d and K _f coefficients from experimental data. The K _d values were utilized to calculate the partition coefficient normalized to soil organic carbon (K _oc ). For the pesticides acetamiprid, carbendazim, diuron and thiamenthoxan the K _oc (mL g^{? 1}) values ranged in both soils from 98 – 3235, 1024 – 2644, 145 – 2631 and 104 – 2877, respectively. From the studied pesticides, only carbendazim presented correlation (r² = 0.82 and p < 0.01) with soil organic carbon (OC) content. Acetamiprid and thiamethoxam showed low sorption coefficients, representing a high risk of surface and ground water contamination.     

Influence of the surface microlayer on atmospheric deposition of aerosols and polycyclic aromatic hydrocarbons

Atmospheric dry deposition is an important process for the introduction of aerosols and pollutants to aquatic environments. The objective of this paper is to assess, for the first time, the influence that the aquatic surface microlayer plays as a modifying factor of the magnitude of dry aerosol deposition fluxes. The occurrence of a low surface tension (ST) or a hydrophobic surface microlayer has been generated by spiking milli-Q water or pre-filtered seawater with a surfactant or octanol, respectively. The results show that fine mode (<2.7 μm) aerosol phase PAHs deposit with fluxes 2–3 fold higher when there is a low ST aquatic surface due to enhanced sequestration of colliding particles at the surface. Conversely, for PAHs bound to coarse mode aerosols (>2.7 μm), even though there is an enhanced deposition due to the surface microlayer for some sampling periods, the effect is not observed consistently. This is due to the importance of gravitational settling for large aerosols, rendering a lower influence of the aquatic surface on dry deposition fluxes. ST (mN m⁻¹) is identified as one of the key factor driving the magnitude of PAH dry deposition fluxes (ng m⁻² d⁻¹) by its influence on PAH concentrations in deposited aerosols and deposition velocities (v_d, cm s⁻¹). Indeed, v_d values are a function of ST as obtained by least square fitting and given by Ln(v_d)=−1.77 Ln(ST)+5.74 (r²=0.95) under low wind speed (average 4 m s⁻¹) conditions.     

Mass transfer coefficients for volatilization of polychlorinated biphenyls from the Hudson River,New York measured using micrometeorological approaches

Air–water exchange is an important process controlling the fate of many organic chemicals in the environment. Modeling this process is hampered by the lack of direct observations. Thus, the purpose of this work was to derive direct measurements of the mass transfer coefficients for air–water exchange (v_aw) of polychlorinated biphenyls (PCBs) that may be used to check the validity of values derived from tracer gas experiments. v_aw values for PCBs were determined using previously published turbulent fluxes divided by the corresponding dissolved phase concentrations. The median v_aw values for each homolog decreased with increasing molecular weight and ranged from 0.29 for hexachlorobiphenyls to 2.2 m d^?1 for monochlorobiphenyls with a propagated uncertainty of about 70%, lower than in previous studies. Due to relatively low wind speeds and possible sorption of PCBs to colloids, these numbers may be biased low. These field measurements of v_aw differ by as much as a factor of 23 from predictions based on the widely-used Whitman two-film model. Therefore a new formulation for the calculation of v_aw based on field measurements is needed. This study demonstrates that micrometeorological approaches are a viable option for the measurement of v_aw for hydrophobic organics such as PCBs and should be used to generate enough field data on the air–water exchange of hydrophobic organics to allow the development of new predictive models.     

Error magnitudes in extrapolated approximations of sorbent retention volumes obtained by using temperature-dependent vapor pressures

The temperature dependence of the vapor pressure of a compound can be used to obtain an estimate of the effects of temperature (T, K) on the retention volume of that compound on sorbents used in gas sampling. Since the T-dependence of the vapor pressure depends on the enthalpy of vaporization ΔH_v and not on the enthalpy of desorption ΔH_s from the sorbent surface itself, such an estimate will be subject to error. Let T₂ be the temperature at which an estimate of the retention volume is desired, and let T₁ be the temperature at which the retention volume is known. The magnitude of the error will then increase as the magnitudes of (T₂ − T₁) and (ΔH_s − ΔH_v) increase. If both ΔH_s and ΔH_v are independent of T over the range of interest, then the error will be zero when either (T₂− T₁) or (ΔH_s−ΔH_v) is zero.     

Characterisation of fresh particulate vehicular exhausts near a Paris high flow road

Simultaneous continuous measurements of PM_2.5, PM₁₀, black carbon mass (BCae), Black smoke (BS) and particle number density (N) were conducted in the close vicinity of a high traffic road around Paris during a three-month period beginning in August 1997. In parallel some aerosol collection was performed on filters in order to assess the black carbon (BC), organic carbon (OC) and water soluble organic fractions (WSOC) of the freshly emitted traffic aerosols. The high hourly concentrations of PM_2.5 (39±20 μg m⁻³), BCae (14±7 μg m⁻³), and N (220,000±115,000 cm⁻³), were found to be well correlated with each other. On average PM_2.5 represented 66±13% of PM₁₀ and appears to be composed primarily of BC (43±20%). On the contrary no correlation was found between PM_2.5 and the coarse (PM₁₀–PM_2.5) mass fractions which was attributed to resuspension processes by vehicles. Black carbon mass concentrations obtained from both filter analyses (BC) and Aethalometre data (BCae) show a good agreement suggesting that the Aethalometre calibration based on a black carbon specific attenuation coefficient (σ) of 19 m² g⁻¹ is well adapted to nearby roadside measurements. Daily BC (used as a surrogate for fine particles) concentrations and wind speed were found to be anti-correlated. Average daily variations of BC could be related to traffic intensity and regime as well as to the boundary layer height. As expected for freshly emitted traffic aerosols, filter analyses indicated a high BC/TC ratio (29±5%) and a low mean WSOC/OC ratio (12.5±5%) for the bulk aerosol. For these two ratios no day/night differences were observed, the sampling station being probably too close to traffic to evidence photochemical modification of the aerosol phase. Finally, a linear relationship was found between BC and BS hourly concentrations (BC=0.10×BS+1.18; r²=0.93) which offers interesting perspectives to retrieve BC concentrations from existing BS archives.     

Rapid measurement of indoor mass-transfer coefficients

Indoor air pollutant concentrations can be influenced by how rapidly species are transported to and from surfaces. Consequently, a greater understanding of indoor transport phenomena to surfaces improves estimates of human exposure to indoor air pollutants. Here, we introduce two methods of rapidly and directly measuring species fluxes at indoor surfaces, allowing us to evaluate the transport-limited deposition velocity, v_t (a mass-transfer coefficient). The deposition velocity sensor (DeVS) method employs a small microbalance coated with a pure hydrocarbon, preferably octadecane. We quantify flux (or evaporation rate) of the hydrocarbon into a room by observing the rate of mass loss on the microbalance. The transport-limited deposition velocity, v_t,octadecane, is then obtained by combining the flux with the vapor pressure of the hydrocarbon. Simultaneously, v_t,ozone is quantified using the deposition velocity of ozone (DeVO) method, which acts as a standard to calibrate and evaluate DeVS. Specifically, DeVO evaluates ozone transport to surfaces by quantifying the conversion by ozone of nitrite to nitrate on a glass fiber filter. Simultaneous laboratory chamber experiments demonstrates that v_t for octadecane and ozone are strongly correlated, with the values for ozone 1.5 times greater than that for octadecane. In an office experiments, the DeVS method responds within minutes to step changes in conditions such as occupancy, activities and ventilation. At present, the results are in order-of-magnitude agreement with predicted indoor mass-transfer coefficients.     

Definition of yearly emission factor of dust and greenhouse gases through continuous measurements in swine husbandry

The object of this study was to develop an accurate estimation method to evaluate the contribution of the various compartments of swine husbandry to dust and GHG (greenhouse gases, CO₂, CH₄ and N₂O) emission into the atmosphere during one year of observation.A weaning, a gestation, a farrowing and a fattening room in an intensive pig house were observed in three different periods (Autumn–Winter, Springtime and Summer, monitoring at least 60% of each period (20% at the beginning, in the middle and at the end) of each cycle).During monitoring, live weight, average live weight gain, number of animals and its variation, type of feed and feeding time were taken into account to evaluate their influence on PM₁₀, or the fraction of suspended particulate matter with an aerodynamic diameter less than or equal to 10 μm [Emission Inventory Guidebook, 2007. B1100 Particle Emissions from Animal Husbandry Activities. Available from: <http://reports.eea.europa.eu/EMEPCORINAIR5/en/B1100vs1.pdf> (accessed October 2008)] and to define GHG emission.The selected piggery had a ventilation control system using a free running impeller to monitor continuously real-time environmental and management parameters with an accuracy of 5%.PM₁₀ concentration was monitored by a sampler (Haz Dust EPAM 5000), either continuously or through traditional gravimetric technique, and the mean value of dust amount collected on the membranes was utilized as a correction factor to be applied to continuously collected data.PM₁₀ concentration amount incoming from inlets was removed from PM₁₀ emission calculation, to estimate the real contribution of pig house dust pollution into atmosphere.Mean yearly emission factor of PM₁₀ was measured in 2 g d^?1 LU^?1 for the weaning room, 0.09 g d^?1 LU^?1 for the farrowing room, 2.59 g d^?1 LU^?1 for the fattening room and 1.23 g d^?1 LU^?1 for the gestation room. The highest PM₁₀ concentration and emission per LU was recorded in the fattening compartment while the lowest value was recorded in the farrowing room.CO₂, CH₄ and N₂O concentrations were continuously measured in the exhaust ducts using an infrared photoacoustic detector IPD (Brüel & Kjaer, Multi-gas Monitor Type 1302, Multipoint Sampler and Doser Type 1303) sampling data every 15 min, for the 60% of the cycles.Yearly emission factor for CO₂ was measured in 5997 g d^?1 LU^?1 for the weaning room, 1278 g d^?1 LU^?1 for the farrowing room, 13,636 g d^?1 LU^?1 for the fattening room and 8851 g d^?1 LU^?1 for the gestation room.Yearly emission factor for CH₄ was measured in 24.57 g d^?1 LU^?1 for the weaning room, 4.68 g d^?1 LU^?1 for the farrowing room, 189.82 g d^?1 LU^?1 for the fattening room and 132.12 g d^?1 LU^?1 for the gestation room.Yearly emission factor for N₂O was measured in 3.62 g d^?1 LU^?1 for the weaning room, 0.66 g d^?1 LU^?1 for the farrowing room, 3.26 g d^?1 LU^?1 for the fattening room and 2.72 g d^?1 LU^?1 for the gestation room.     

Evaluation of the CAR-FMI model against measurements near a major road

A field measurement campaign was conducted near a major road in southern Finland from September 15 to October 30, 1995. The concentrations of NO, NO₂ and O₃ were measured simultaneously at three locations, at three heights (3.5, 6 and 10 m) on both sides of the road. Traffic densities and relevant meteorological parameters were also measured on-site. We have compared measured concentration data with the predictions of the road network dispersion model CAR-FMI, used in combination with a meteorological pre-processing model MPP-FMI. In comparison with corresponding results presented previously in the literature, the agreement of measured and predicted datasets was good, as measured using various statistical parameters. For all data (N=587), the index of agreement (IA) was 0.83, 0.82 and 0.89 for the measurements of NO_x, NO₂ and O₃, respectively. The IA is a statistical measure of the correlation of the predicted and measured time series of concentrations. However, the modelling system overpredicts NO_x concentrations with a fractional bias FB=+13%, and O₃ concentrations with FB=+8%, while for NO₂ concentrations FB=−2%. We also analyzed the difference between model predictions and measured data in terms of meteorological parameters. Model performance clearly deteriorated as the wind direction approached a direction parallel to the road, and for the lowest wind speeds. The range of variability concerning atmospheric stability, ambient temperature and the amount of solar radiation was modest during the measurement campaign. As expected, no clear dependencies of model performance were therefore detected in terms of these parameters. The experimental dataset is available for the evaluation of other roadside dispersion models.     

Quantification on source/receptor relationship of primary pollutants and secondary aerosols from ground sources—Part I. Theory

A new algorithm has been derived for trajectory models to determine the transfer coefficient of each source along or adjacent to a trajectory and to calculate the concentrations of SO₂, NO_x, sulfate, nitrate, fine particulate matter (PM) and coarse PM at a receptor. The transfer coefficient t_f (s m⁻¹) is defined to be the ratio between the contributed concentration ΔC (μg m⁻³) to the receptor from a ground source and the emission rate of the source q (μg m⁻² s⁻¹) at a grid, i.e. t_f≡ΔC/q. The model is developed by combining with a backward trajectory scheme and a circuit-type's parameterization. First, the transfer coefficients of grids along or adjacent a back-trajectory are calculated. Then, the contributed concentration of each emission grid is determined by multiplying its emission rate with the transfer coefficient of the grid. Finally, the concentration at the receptor is determined by the summation of all the contributed concentrations within the domain of simulation.     

Adsorption and desorption variability of four herbicides used in paddy rice production

This investigation was performed to determine the effect of physicochemical soil properties on penoxsulam, molinate, bentazon, and MCPA adsorption–desorption processes. Four soils from Melozal (35° 43′ S; 71° 41′ W), Parral (36° 08′ S; 71° 52′ W), San Carlos (36° 24′ S; 71° 57′ W), and Panimavida (35° 44′ S; 71° 24′ W) were utilized. Herbicide adsorption reached equilibrium after 4 h in all soils. The Freundlich L-type isotherm described the adsorption process, which showed a high affinity between herbicides and sorption sites mainly because of hydrophobic and H-bonds interaction. Penoxsulam showed the highest adsorption coefficients (4.23 ± 0.72 to 10.69 ± 1.58 mL g^?1) and were related to soil pH. Molinate showed K_d values between 1.72 ± 0.01 and 2.3 ± 0.01 mL g^?1and were related to soil pH and organic matter, specifically to the amount of humic substances. Bentazon had a high relationship with pH and humic substances and its K_d values were the lowest, ranging from 0.11 ± 0.01 to 0.42 ± 0.01 mL g^?1. MCPA K_d ranged from 0.14 ± 0.02 to 2.72 ± 0.01 mL g^?1, however its adsorption was related to humic acids and clay content. According to these results, the soil factors that could explain the sorption process of the studied herbicides under paddy rice soil conditions, were principally humic substances and soil pH. Considering the sorption variability observed in this study and the potential risk for groundwater contamination, it is necessary to develop weed rice management strategies that limit use of herbicides that exhibit low soil adsorption in areas with predisposing conditions to soil leaching.     

Experimental investigation of the residence of contaminants in the wake of an obstacle under different stability conditions

The detrainment behaviour of contaminants in the wake of an isolated building was investigated in the field under atmospheric stability conditions ranging from very stable to very unstable. The model building used was a 2 m cube and two orientations were investigated, with the cube either normal or at 45° to the wind. Tracer gas was first entrained into the wake from a source located a short distance upwind of the cube, the gas being released continuously for a limited period in order to fill the wake. Thereafter, the source was switched off, and the concentration (measured using several fast-response gas detectors located in the wake) was observed to decay in an exponential manner. This procedure was repeated in a total of 118 experiments to provide confidence in statistics. The residence time (T_d), which is defined as the time it takes for the concentration to decay to 1/e of its original value, was measured. The decay duration (t), which is the time it takes for the gas to become fully detrained from the wake, was found to be greater in stable atmospheric conditions, mainly due to the lower wind speeds and higher concentrations observed under these conditions. However, the non-dimensional residence time (τ) was found to be independent of atmospheric stability. The values of τ for a cube normal (τ=6.2) or at 45° to the flow (τ=9.5) are in very good agreement with values calculated using empirical formulae derived from wind tunnel experiments.