Inverse Dispersion Method Research Articles

Applicability of the inverse dispersion method to measure emissions from animal housings

Abstract. Emissions from agricultural sources substantially contribute to global warming. The inverse dispersion method (IDM) has been successfully used for emission measurements from various agricultural sources. The IDM has also been validated in multiple studies with artificial gas releases mostly in open fields. Release experiments from buildings have rarely been conducted and were partly affected by additional nearby sources of the target gas. Specific release studies for naturally ventilated animal housings are lacking. In this study, a known and predefined amount of methane (CH4) was released from an artificial source inside a barn that mimicked a naturally ventilated dairy housing, and IDM recovery rates, using a backward Lagrangian stochastic (bLS) model, were determined. For concentration measurements, open-path devices (OPs) with a path length of 110 m were placed in a downwind direction of the barn at fetches of 2.0h, 5.3h, 8.6h, and 12h (h equals the height of the highest obstacle), and a 3D ultrasonic anemometer (UA) was placed in the middle of the first three OP paths. Upwind of the barn, an additional OP and a UA were installed. The median IDM recovery rates determined with the UA placed upwind of the barn and the downwind OP ranged between 0.55–0.75. It is concluded that, for the present study case, the effect of the building and a tree in the main wind axis led to a systematic underestimation of the IDM-derived emission rate probably due to deviations in the wind field and turbulent dispersion from the underlying assumptions of the used dispersion model.

Improvement of inverse dispersion technique for ground roll attenuation in sedimentary environment

Ground roll, often characterized as high energy, low velocity, low frequency and dispersion, which always dominates a large part of shot records and damages the desired reflections. The attenuation of ground roll is important for high data resolution and signal to noise ratio (S/N) in seismic processing. Conventional frequency-wave number (F-K) filter is effective in eliminating linear noise, but they do not deal well with appearance linear noise, like dispersive fan-shape ground roll. In the F-K domain, the components of ground roll and the desired reflection always overlap, which leads to destruction of the low-frequency components during the F-K filtering process. A novel inverse dispersion method is introduced to overcome this disadvantage. The proposed method transforms dispersive ground roll towards non-dispersive, high velocity linear noise. The time delay caused by dispersion is calculated and compensated by using an inverse dispersion operator. Then the ground roll is separated from the desired reflections and can be easily subtracted by the F-K filter. The conventional f-k filter can efficiently attenuate the ground roll without affecting the desired data, thus improve the resolution and S/N of seismic data. Model test and real data application demonstrate the feasibility and efficiency of the proposed method in ground roll attenuation.

Ammonia emissions from a dairy housing and wastewater treatment plant quantified with an inverse dispersion method accounting for deposition loss

ABSTRACT Ammonia (NH3) emissions negatively impact air, soil, and water quality, hence human health and biodiversity. Significant emissions, including the largest sources, originate from single or multiple structures, such as livestock facilities and wastewater treatment plants (WWTPs). The inverse dispersion method (IDM) is effective in measuring total emissions from such sources, although depositional loss between the source and point of measurement is often not accounted for. We applied IDM with a deposition correction to determine total emissions from a representative dairy housing and WWTP during several months in autumn and winter in Switzerland. Total emissions were 1.19 ± 0.48 and 2.27 ± 1.53 kg NH3 d−1 for the dairy housing and WWTP, respectively, which compared well with literature values, despite the paucity of WWTP data. A concurrent comparison with an inhouse tracer ratio method at the dairy housing indicated an offset of the IDM emissions by < 20%. Diurnal emission patterns were evident at both sites mostly driven by changes in air temperature with potential lag effects such as following sludge agitation. Modeled deposition corrections to adjust the concentration loss detected at the measurement point with the associated footprint were 22–28% of the total emissions and the cumulative fraction of deposition to emission modeled with distance from the source was between 7% and 12% for the measurement distances (60–150 m). Although estimates of depositional loss were plausible, the approach is still connected with substantial uncertainty, which calls for future validation measurements. Longer measurement periods encompassing more management activities and environmental conditions are required to assess predictor variable importance on emission dynamics. Combined, IDM with deposition correction will allow the determination of emission factors at reduced efforts and costs, thereby supporting the development and assessment of emission reducing methods and expand the data availability for emission inventories. Implications: Ammonia emissions must be measured to determine emission factors and reporting national inventories. Measurements from structures like farms and industrial plants are complex due to the many different emitting surfaces and the building configuration leading to a poor data availability. Micrometeorological methods provide high resolution emission data from the entire structure, but suffer from uncertainties, as the instruments must be placed at a distance from the structure resulting in a greater loss of the emitted ammonia via dry deposition before it reaches the measurement. This study constrains such emission measurements from a dairy housing and wastewater treatment plant by applying a simple correction to account for the deposition loss and compares the results to other methods.

Effect of Covering Deep Litter Stockpiles on Methane and Ammonia Emissions Analyzed by an Inverse Dispersion Method

Ammonia (NH3) and methane (CH4) emission rates from cattle deep litter and horse manure deep litter in farm-scale stockpiles were measured using an inverse dispersion method based on the backward Lagrangian Stochastic (bLS) model. The aims of the study were to (i) evaluate the effects of timing and carefulness of covering a stockpile, (ii) measure emissions from handling and storing deep litter, (iii) compare emissions from manure stored in a container and stockpile, (iv) determine emissions from cattle and horse manure deep litter, and (v) evaluate potential effects of pile temperature on emissions. New emission data with relatively high temporal resolution are provided. High variability in CH4 emissions was observed with no clear effects on the timing of covering, even though the temperatures inside the piles were different. NH3 emissions occur immediately after pile establishment and the emissions were highly influenced by the timing of covering. In the first week of storage, covering reduced NH3 emissions by 92 ± 9% when comparing the emissions from a noncovered and totally covered stockpile. This demonstrates the effect of applying a cover immediately to avoid NH3 emissions. The long-term effects of covering strategies as well as the influence of temperature and season are also discussed. For horse manure deep litter, storage in a closed (covered) container instead of a covered stockpile was observed to reduce CH4 emissions by 50 ± 58% and NH3 emissions by 67 ± 37%.

Full-Scale Investigation of Methane and Ammonia Mitigation by Early Single-Dose Slurry Storage Acidification

The effects of early acidification with sulfuric acid of animal slurry in concrete storage tanks to pH 5 on methane and ammonia emissions have been investigated on two cattle and two pig slurry storage tanks in full scale. The tanks’ up- and down-wind concentrations were measured online by cavity ring-down spectroscopy (CRDS). The inverse-dispersion method (IDM), using a backward Lagrangian stochastic (bLS) model, was used to determine the emission rates. The results show that CH4 emissions after single-dose acidification of slurry tanks in the early summer were reduced by 95 ± 14% and 95% ± 6% for cattle and pig manure, respectively, compared to the emissions measured before acidification. The reductions occurred even though pH increased during the storage with and without addition of fresh slurry. After acidification, NH3 emissions were comparable to or lower than when a natural crust was present. A supplementary experiment on small-scale slurry containers was conducted to investigate the pH development when fresh slurry was added to the acidified slurry. The influence of pH development on the long-term emission dynamics of methane is discussed by comparing the large-scale and small-scale studies. The study presents the first full-scale documentation that slurry acidification is a promising technology for mitigation of methane from slurry storage.

Quantitation study on VOC emissions and their reduction potential for coking industry in China: Based on in-situ measurements on treated and untreated plants

Currently, the characteristics of volatile organic compounds (VOC) released from coking industry are still vague, and the widely used VOC emission factors (EFs) were still from the measurements of 1990s. Hence, focusing on coking industry, we conducted an in-situ measurement campaign in several typical plants, developed a set of VOC EFs for various release units, and estimated the current emission amounts and future reduction potentials of VOC in China. The measurements show that the levels of VOC in stationary units were 63.82–9563.93 μg·m−3, and those surrounding fugitive units were 111.37–1436.36 μg·m−3. VOC emissions from stationary units were directly calculated, which deducing EFs of 11.57, 15.51, 127.13, 0.28, 0.16 g·t−1 coke respectively for coke charging, coke pushing, coke oven chimney, dry quenching, and wastewater treatment processes. Meanwhile, VOC emissions from fugitive units were simulated following the inverse dispersion method, which achieving EFs of 443.34 ± 66.31, 352.12 ± 65.81, and 718.56 ± 132.69 g·t−1 coke respectively for the coke oven leakage, byproduct recovery with VOC treatment system, and byproduct recovery without VOC treatment system. Generally, the coking plants installing VOC treatment system had total VOC EF of 953.76 g·t−1 coke, about 37.1% lower than those never considering VOC treatment (1516.25 g·t−1 coke). According to these developed EFs, the VOC emission amount from coking industry in China were estimated, slightly decreasing from 623.54 to 578.17 Gg per year, although the coke production increasing from 410.86 to 418.26 Tg during 2015–2019. In future, according to the national industrial policies, regulations and standards, technical guidelines, the VOC reduction potential of this industry in China could reach 336.9 Gg, to which headstream adjustment, process improvement, and end-of-pipe control contributed about 21.4%, 31.6%, and 47.0%, respectively.

Using the inverse dispersion method to determine methane emissions from biogas plants and wastewater treatment plants with complex source configurations

Wastewater treatment plants (WWTPs) and biogas plants (BGPs) are significant sources of methane (CH4), with a combined share of around 40% within the waste sector of the Swiss national emission inventory. We conducted whole-plant CH4 emission measurements at two WWTPs and four agricultural BGPs in Switzerland using the inverse dispersion method (IDM). This involved open-path concentration measurements up- and downwind of the plant in combination with a backward Lagrangian stochastic (bLS) model. WWTPs in particular consist of multiple CH4 sources with different areas and emission strengths. For the combination of the individual emission sources in the bLS modelling, three different calculation approaches with different levels of detail were applied: (i) single source over enveloping polygon area, (ii) uniform emission density for all individual source areas, (iii) specified relative weighting of individual sources based on literature data. Average CH4 emissions for WWTP-1 and WWTP-2 were 0.82 kg h−1 and 0.61 kg h−1 and scaled to population equivalents (PE) 166 g PE−1 y−1 and 381 g PE−1 y−1, respectively. BGPs CH4 emissions varied between 0.39 kg h−1 and 2.22 kg h−1, corresponding to less than 5% of the plants’ CH4 production. The highest numbers were due to measurements during other than normal operating conditions. The emissions of WWTPs and BGPs comply with literature values. Approach (iii) with source weighting led to a difference of up to 43% for the two WWTPs compared to the assumption of uniform emissions. Furthermore, we demonstrate how multiple open-path concentration measurements can be combined and how the measurements can be corrected for nearby external CH4 sources not belonging to the investigated plants. The results of the present study contribute to improved emission data from the waste sector.

Assessment of the inverse dispersion method for the determination of methane emissions from a dairy housing

Methane (CH4) emissions from dairy housings, mainly originating from enteric fermentation of ruminating animals, are a significant source of greenhouse gases. The quantification of emissions from naturally ventilated dairy housings is challenging due to the spatial distribution of sources (animals, housing areas) and variable air exchange. The inverse dispersion method (IDM) is a promising option, which is increasingly used to determine gaseous emissions from stationary sources, as it offers high flexibility in the application at reasonable costs. We used a backward Lagrangian stochastic model combined with concentration measurements by open-path tunable diode laser spectrometers placed up- and downwind of a naturally ventilated housing with 40 dairy cows to determine the CH4 emissions. The average emissions per livestock unit (LU) were 317 (±44) g LU−1 d−1 and 267 (±43) g LU−1 d−1 for the first and second campaign, in September – October and November – December, respectively. For each campaign, inhouse tracer ratio measurements (iTRM) were conducted in parallel during two subperiods. For simultaneous measurements, IDM showed average emissions which were lower by 8% and 1% than that of iTRM, respectively, for the two campaigns. The differences are within the uncertainty range of any of the two methods. The IDM CH4 emissions were further analysed by wind direction and atmospheric stability and no differences in emissions were found. Overall, IDM showed its aptitude to accurately determine CH4 emissions from dairy housings or other stationary sources if the site allows adequate placement of sensors up- and downwind in the prevailing wind direction. To acquire reliable emission data, depending on the data loss during measurements due to quality filtering or instrument failure, a measuring time of at least 10 days is required.

Performance of open-path GasFinder3 devices for CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt; concentration measurements close to ambient levels

Abstract. Open-path measurements of methane (CH4) with the use of GasFinder systems (Boreal Laser Inc, Edmonton Canada) have been frequently used for emission estimation with the inverse dispersion method (IDM), particularly from agricultural sources. It is common to many IDM applications that the concentration enhancement related to CH4 sources is small, typically between 0.05 and 0.5 ppm, and accurate measurements of CH4 concentrations are needed at concentrations close to ambient levels. The GasFinder3-OP (GF3) device for open-path CH4 measurements is the latest version of the commercial GasFinder systems by Boreal Laser Inc. We investigated the uncertainty of six GF3 devices from side-by-side intercomparison measurements and comparisons to a closed-path quantum cascade laser device. The comparisons were made at near-ambient levels of CH4 (85 % of measurements below 2.5 ppm) with occasional phases of elevated concentrations (max. 8.3 ppm). Relative biases as high as 8.3 % were found, and a precision for half-hourly data between 2.1 and 10.6 ppm-m (half width of the 95 % confidence interval) was estimated. These results deviate from the respective manufacturer specifications of 2 % and 0.5 ppm-m. Intercalibration of the GF3 devices by linear regression to remove measurement bias was shown to be of limited value due to drifts and step changes in the recorded GF3 concentrations.

Micrometeorological Methods for Measuring Methane Emission Reduction at Beef Cattle Feedlots: Evaluation of 3-Nitrooxypropanol Feed Additive.

It is highly desirable to test agricultural emission mitigation strategies in a whole-farm environment to ensure that all aspects of management and production operations are included. However, the large spatial scale of commercial operations makes the dual measurements of control and treatment(s) difficult. We evaluated the application of two micrometeorological methods, a novel concentration ratio method and an inverse dispersion method, where both were used to measure methane (CH) emission reductions in cattle fed the compound 3-nitrooxypropanol compared with cattle fed just the basal diet. In total, there were 1344 cattle used that were located in six pens (∼222 animals per pen). Three adjacent pens to the east and three to the west were designated as the treatment and control blocks, respectively. Underlying the emission reduction method was the assumption of site symmetry between the treatment and control pen blocks in the feedlot. There was, on average, a large CH emission reduction of ∼70% (±18%) due to the additive as found by both micrometeorological methods. Both methods also show a change in the diel distribution (peak emissions after initial morning feeding) and seasonal pattern (a decrease in emission reduction of 7.5 and 26.1% over 90 d). The simplicity of the developed concentration ratio method is expected to have applications for evaluating other mitigation strategies at large commercial scales (e.g., the application of manure additives to pens to reduce odors and ammonia emissions).

Dispersive Rayleigh wave attenuation using inverse-dispersion method

Reflections provide the most valuable information about the stratigraphy in seismic exploration. On land reflections are always contaminated by surface waves, high amplitude, low frequency, and low velocity and also dispersive. All these characteristics enable surface wave to be separated from reflections. A particular complication is that surface waves are dispersive. Then, frequencies of surface waves and reflections are overlapped in the spectral domain, the same can be found in the f-k domain. Traditional processing from doing surgical muting may cause damage to the data such as waveform distortion and narrowing the spectral band of the signal, especially when the surface waves are strongly dispersive. In this paper, a new method named inversedispersion algorithm is presented to suppress surface waves that overlap with reflections in frequency. We use the linear Radon transform and Fourier transform to find the dispersion curve of surface wave. With the help of dispersion curve and offset information, phases of every trace are moved. The phase-moving step is named the inverse-dispersion method. After the inverse-dispersion step, surface waves with different frequencies are transformed to be nearly parallel and away from reflections, which are easily separated. As it should be, the phase is moved back after surface wave elimination. In this paper the method is tested on field data, showing a good result with excellent protection of the reflections.

Ammonia and greenhouse gas emissions at beef cattle feedlots in Alberta Canada

This study was conducted at beef cattle feedlots, over two years in southern Alberta Canada, and focused on deriving the ammonia, methane, nitrous oxide and carbon dioxide emissions from two feedlots from June/July to October. Line-averaging sensors were used to measure ambient gas concentrations in the vicinity of the feedlots, and an inverse dispersion method was used to calculate emissions. Results show that ammonia and methane emissions were consistent with that measured from other studies. Both feedlots lost about 40% of the nitrogen feed intake as ammonia. The emission of nitrous oxide, when compared on a greenhouse gas bases, was similar to the methane emission. A diet difference between feedlots coincided with a slight difference in feedlot methane emission. There was good agreement between previously reported ammonia and methane emission rates and those derived in our feedlot study. Further evaluation of the underlying relationships causing variation in emissions should follow. A key to understanding emissions at commercial feedlots is to fully engage the management data available.

Methane emissions from cattle grazing under diverse conditions: An examination of field configurations appropriate for line-averaging sensors

Micrometeorological techniques offer the possibility of a non-interfering measurement of enteric emissions from cattle in their natural environment, where animals do not need to be encumbered or handled. However, the grazing environment is a difficult application for these techniques. This study reports on an experimental design using an inverse dispersion method (IDM) to measure enteric methane (CH4) emissions, and its application to 15 rather distinct cattle trials in three types of feeding situations: summer grazing, winter swath grazing, and winter feeding. The IDM design was based on long and narrow animal paddocks with line-averaging sensors measuring CH4 concentration alongside the long axes of the paddock. Emissions were calculated based on the difference in concentration between the two measurement paths. The narrow paddock has many advantages for an IDM calculation: it avoids the need to monitor animal positions; it helps ensure measurable downwind concentration; and it increases the range of useable wind directions. Four different sensor configurations were used in the trials, differing in the number of concentration sensors (one or two) and sensor paths (two or four). Some configurations used sensor aiming motors to give multiple measurement paths and others used mirrors to create segmented paths (i.e., to go around a paddock corner). Cattle emissions measured with the IDM design showed good agreement across the 15 trials, consistent with high forage diets. When expressed in terms of CH4 yield (g/kg dry matter intake), the three feeding situations averaged 21.3 (summer grazing), 23.4 (winter grazing), and 23.9 (winter feeding). Based on the trial-to-trial consistency of the results, the similarity with other literature studies, and the success of a previous tracer-release study, we conclude that the narrow paddock IDM design provides a flexible and accurate method for calculating CH4 emissions from grazing cattle.

Refining an inverse dispersion method to quantify gas sources on rolling terrain

This paper analyses a trace gas dispersion experiment with multiple point sources and line-averaging laser gas detectors on gently rolling terrain. The objective of the experiment was to establish how well emission rate can be inferred by “inverse dispersion” (ID), using a Lagrangian stochastic wind transport model (WindTrax) that (strictly) is appropriate only in horizontally-homogeneous winds. Measured mean wind speeds at fixed height above ground revealed spatial variation of order ±10% over the site. However the results of the inversion to estimate source strength Q from the concentration field suggest that the unwanted impact of the terrain is adequately compensated by representing detector light paths as curves, approximating their true height above ground. Under that treatment the mean and standard deviation of the ratio QIDM/Q of inferred to true source strength, over an ensemble of 96 fifteen minute intervals, were respectively 〈QIDM/Q〉=1.04 and σQ|Q=0.15, with little distinction between outcomes under unstable and stable stratification. We also used the measurements to study the influence (on the accuracy of retrieved source strength) of discretionary elements of inverse dispersion procedure: data quality criteria; optimal placement of detectors relative to the source(s); and the impact of alternative spatial representations of the source, supposing one had but partial information in that regard. Because the sources were always rather close to the downwind detector, the quality of the inversions was less sensitive to extremes of stratification than has been reported for other trials. Inversions that treated the actual point sources as an aggregate area source proved acceptable, provided this was placed at or near the height of the (true) point sources. An idealized distribution of elevated point sources can also be satisfactory, but bad inversions may result if placement of the token sources is biased in the cross-plot direction relative to the actual source(s).

Inverse dispersion method for calculation of complex photonic band diagram andPTsymmetry

We suggest an inverse dispersion method for calculating photonic band diagram for materials with arbitrary frequency-dependent dielectric functions. The method is able to calculate the complex wave vector for a given frequency by solving the eigenvalue problem with a non-Hermitian operator. The analogy with $\cal{PT}$-symmetric Hamiltonians reveals that the operator corresponds to the momentum as a physical quantity and the singularities at the band edges are related to the branch points and responses for the features on the band edges. The method is realized using plane wave expansion technique for two-dimensional periodical structure in the case of TE- and TM-polarization. We illustrate the applicability of the method by calculation of the photonic band diagrams of an infinite two-dimension square lattice composed of dielectric cylinders using the measured frequency dependent dielectric functions of different materials (amorphous hydrogenated carbon, silicon, and chalcogenide glass). We show that the method allows to distinguish unambiguously between Bragg and Mie gaps in the spectra.

Estimating ammonia emissions from a winter wheat cropland in North China Plain with field experiments and inverse dispersion modeling

A field-scale experiment was conducted in the spring of 2012 at a winter wheat cropland, aiming to quantify ammonia (NH3) emissions from surface fertilization under realistic cultivation conditions. Since the fertilization lasted about 20 days for hundreds of divided plots and three types of fertilizers were used (i.e., urea, ammonium sulfate and compound nitrogen-phosphorous-potassium fertilizer), the heterogeneity was one of the significant characteristics of the cropland NH3 emissions during the experiment, which is a great challenge for the classical micrometeorological methods to calculate NH3 fluxes. Based on continuous measurements of NH3 concentrations at two heights (2.5 m and 8 m) and detailed records of the fertilization plot by plot, an inverse dispersion method was employed to derive the heterogeneous NH3 emissions and the corresponding emission factors (EFs). The EFs derived from this experiment for urea, ammonium sulfate and compound fertilizer were 12.0% ± 3.1%, 8.5% ± 1.6% and 4.5% ± 1.7%, respectively. The EF of urea we obtained was lower than most of other domestic measurements and those used in the NH3 emission inventories in China. Measurements on EFs of ammonium sulfate and compound fertilizer are not available in China. However, the EFs of ammonium sulfate and compound fertilizer we obtained were comparable to those used in NH3 emission inventories of China.

Konjac glucomannan microspheres for low-cost desalting of protein solution

In this study, low-cost konjac glucomannan (KGM) microspheres used for desalting were developed by an inverse dispersion method. High concentration of KGM was pretreated to reduce viscosity by acid hydrolysis method under the condition of high temperature and pressure. The selectivity of the obtained cross-linked KGM gels with different degree of crosslinking was studied by constructing calibration curves (Kav) of standard molecular weight substances. The stability of the gels was investigated, which showed that the KGM microspheres are tolerant to a wide range of pH and stable in all commonly used aqueous buffers, and insensitive to autoclaving as well. Furthermore, protein-desalting performances of GM-1250, a cross-linked KGM microsphere, were evaluated with two proteins, bovine serum albumin and filamentous hemagglutinin, which turned out that GM-1250 is comparable to the widely used commercial product – Sephadex G25 Fine. From economic considerations, KGM gel is a prospective alternative for dextran gels in protein desalting process.

Inference of emission rate using the inverse-dispersion method for the multi-source problem

The inverse-dispersion method (IDM) has been widely used to infer the emission rate of a spatially homogeneous and well-defined source (referred to as the single-source problem). To infer the emission rate of a spatially heterogeneous source (referred to as the multi-source problem), a large number of downwind concentration measurements usually need to be conducted. In this paper, with the evapotranspiration (ET) data obtained in a field-scale experiment, we evaluated the feasibility and accuracy of IDM for multi-source strength inference with only two downwind concentration measurements. Field ET in this experiment exhibited typical multi-source characteristics due to sequential irrigation plot by plot. Under such conditions, large errors existed in the ET estimation via conventional methods, such as the gradient method. This heterogeneous ET was inferred by IDM with two assumptions: (1) the magnitude of the plot ET decays exponentially with the date after irrigation, having a characteristic decay timescale τ; (2) the daily variation pattern of ET obeys normal distribution with an expectation μ and a standard deviation σ. The accuracy of the inferred ET was validated by the measured water vapor fluxes via eddy covariance system. Then, sensitivity analysis on τ and σ was conducted. We found that only σ had an obvious effect on the accuracy of the ET inference. Moreover, our analysis showed that it was better to make accurate measurements on the upwind concentration, which was essential to the reliability of the implementation of IDM.

Ground-to-Air Gas Emission Rate Inferred from Measured Concentration Rise within a Disturbed Atmospheric Surface Layer

Abstract In reference to previously observed concentrations of methane released from a source enclosed by a windbreak, this paper examines a refined “inverse dispersion” approach for estimating the rate of emission Q from a small ground-level source, when the surface-layer winds near that source are highly disturbed. The inverse dispersion method under investigation is based on simulation of turbulent trajectories between sources and detectors, using a Lagrangian stochastic (LS) model. At issue is whether it is advantageous to recognize the flow as being disturbed and use a computed approximation to that disturbed flow to drive a fully three-dimensional LS model (3D-LS), or whether it suffices to ignore flow disturbance and adopt an LS model attuned to the horizontally homogeneous upwind flow (MO-LS, as Monin–Obukhov similarity theory describes the vertical inhomogeneity). It is demonstrated that both approaches estimate the source strength to within a factor of 2 of the true value, irrespectively of the location of the concentration measurement, and moreover that both approaches estimate the source strength correctly (to within the experimental uncertainty), when based on concentrations measured far away from the immediate influence of obstacles in the flow. However, if the concentration detector is positioned close to the flow-disturbing obstacles, then inverse dispersion based on 3D-LS provides a better estimate of source strength than does MO-LS.