Deducing Ground-to-Air Emissions from Observed Trace Gas Concentrations: A Field Trial with Wind Disturbance

Abstract Inverse-dispersion techniques allow inference of a gas emission rate Q from measured air concentration. In “ideal surface layer problems,” where Monin–Obukhov similarity theory (MOST) describes the winds transporting the gas, the application of the technique can be straightforward. This study examines the accuracy of an ideal MOST-based inference, but in a nonideal setting. From a 6 m × 6 m synthetic area source surrounded by a 20 m × 20 m square border of a windbreak fence (1.25 m tall), Q is estimated. Open-path lasers gave line-averaged concentration CL at positions downwind of the source, and an idealized backward Lagrangian stochastic (bLS) dispersion model was used to infer QbLS. Despite the disturbance of the mean wind and turbulence caused by the fence, the QbLS estimates were accurate when ambient winds (measured upwind of the plot) were assumed in the bLS model. In the worst cases, with CL measured adjacent to a plot fence, QbLS overestimated Q by an average of 50%. However, if these near-fence locations are eliminated, QbLS averaged within 2% of the true Q over 61 fifteen-minute observations (with a standard deviation σQ/Q = 0.20). Poorer accuracy occurred when in-plot wind measurements were used in the bLS model. The results show that when an inverse-dispersion technique is applied to disturbed flows without accounting for the disturbance, the outcome may still be of acceptable accuracy if judgment is applied in the placement of the concentration detector.

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VOCs emission rate estimate for complicated industrial area source using an inverse-dispersion calculation method: A case study on a petroleum refinery in Northern China

Environmental Pollution ◽

10.1016/j.envpol.2016.07.062 ◽

2016 ◽

Vol 218 ◽

pp. 681-688 ◽

Cited By ~ 27

Author(s):

Wei Wei ◽

Zhaofeng Lv ◽

Gan Yang ◽

Shuiyuan Cheng ◽

Yue Li ◽

...

Keyword(s):

Emission Rate ◽

Petroleum Refinery ◽

Northern China ◽

Industrial Area ◽

Rate Estimate ◽

Area Source ◽

Inverse Dispersion ◽

Vocs Emission ◽

Dispersion Calculation

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Field testing two flux footprint models

Atmospheric Measurement Techniques ◽

10.5194/amt-14-7147-2021 ◽

2021 ◽

Vol 14 (11) ◽

pp. 7147-7152

Author(s):

Trevor W. Coates ◽

Monzurul Alam ◽

Thomas K. Flesch ◽

Guillermo Hernandez-Ramirez

Keyword(s):

Field Study ◽

Release Rate ◽

Emission Rate ◽

Dispersion Model ◽

Field Testing ◽

Gas Emission ◽

Flux Footprint ◽

Model Calculations ◽

Area Source ◽

Large Period

Abstract. A field study was undertaken to investigate the accuracy of two micrometeorological flux footprint models for calculating the gas emission rate from a synthetic 10 × 10 m surface area source, based on the vertical flux of gas measured at fetches of 15 to 50 m downwind of the source. Calculations were made with an easy-to-use tool based on the Kormann–Meixner analytical model and with a more sophisticated Lagrangian stochastic dispersion model. A total of 59 testable 10 min observation periods were measured over 9 d. On average, both models underestimated the actual release rate by approximately 30 %, mostly due to large underestimates at the larger fetches. The accuracy of the model calculations had large period-to-period variability, and no statistical differences were observed between the two models in terms of overall accuracy.

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Field Testing Two Flux Footprint Models

10.5194/amt-2021-106 ◽

2021 ◽

Author(s):

Trevor W. Coates ◽

Monzurul Alam ◽

Thomas K. Flesch ◽

Guillermo Hernandez-Ramirez

Keyword(s):

Field Study ◽

Surface Area ◽

Analytical Model ◽

Release Rate ◽

Emission Rate ◽

Dispersion Model ◽

Field Testing ◽

Gas Emission ◽

Flux Footprint ◽

Area Source

Abstract. A field study was undertaken to investigate the accuracy of two micrometeorological flux footprint models when calculating the gas emission rate from a 10 × 10 m synthetic surface area source, based on the vertical flux of gas measured 15 to 50 m downwind of the source. Calculations were made with an easy-to-use tool based on the Kormann-Meixner analytical model and with a more sophisticated Lagrangian stochastic dispersion model. A total of 323 10 minute observation periods were measured over 9 days. On average, each of the two models calculated the emission rate to within 10 % of the actual release rate. No clear differences were observed between the two models in terms of overall accuracy.

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Methane and ammonia emissions from a beef feedlot in western Canada for a twelve-day period in the fall

Canadian Journal of Animal Science ◽

10.4141/cjas08034 ◽

2008 ◽

Vol 88 (4) ◽

pp. 641-649 ◽

Cited By ~ 53

Author(s):

R. P. van Haarlem ◽

R. L. Desjardins ◽

Z. Gao ◽

T. K. Flesch ◽

X. Li

Keyword(s):

Dispersion Model ◽

Atmospheric Pollutants ◽

Trace Gas ◽

Beef Industry ◽

Total N ◽

Localized Source ◽

Inverse Dispersion ◽

Trace Gas Emissions ◽

Retention Pond ◽

Gross Energy

Commercial feedlot operations are becoming a mainstay in the Canadian beef industry. These large operations that typically raise thousands of animals at a time represent a large localized source of methane (CH4) and of atmospheric pollutants such as ammonia (NH3) and particulate matter. An inverse dispersion model was utilized to calculate CH4 and NH3 emissions from a commercial cattle feedlot and an adjacent runoff retention pond. The feedlot measurements were collected within the interior of the feedlot enabling a near continuous emissions record over the 12 d of the study period. Average daily emission estimates of CH4 and NH3 were 323 and 318 g animal-1 d-1, respectively. The CH4 emissions represent 4% of the gross energy intake (GEI) and NH3 emissions represent 72% of the total N intake. Emissions from the runoff retention pond associated directly with the feedlot operation were approximately 2.7 and 2% of the daily average feedlot emissions of CH4 and NH3, respectively. Key words: Methane, ammonia, inverse dispersion, ruminant livestock, trace gas emissions

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Influence of the variability of the odour emission rate on its impact range: a case study of the selected industrial source

E3S Web of Conferences ◽

10.1051/e3sconf/201910000070 ◽

2019 ◽

Vol 100 ◽

pp. 00070 ◽

Cited By ~ 2

Author(s):

Elżbieta Romanik ◽

Yaroslav Bezyk ◽

Marcin Pawnuk ◽

Urszula Miller ◽

Agnieszka Grzelka

Keyword(s):

Emission Rate ◽

Dispersion Model ◽

Grid Size ◽

Model Calculations ◽

Gas Treatment ◽

Industrial Source ◽

Odour Concentration ◽

Made In ◽

Dynamic Olfactometry

Odour concentration measurements in a chosen industrial source were made in this study using the method of dynamic olfactometry. The two different scenarios considered the variation of the odour emission rate as input for the dispersion model were compared for the period 2017 (before installation of the equipment for gas treatment) and 2018 (after implementation of purifying technologies). In this paper the odour impact range was determined by applying model calculations conducted in the Polish reference dispersion model – OPERAT FB software for the grid size 2 x 2 km. The conducted research shows a significant improvement in the odour impact range of chosen industrial source in year 2018 compared to 2017.

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Long term precipitation chemistry and wet deposition in a remote dry savanna site in Africa (Niger)

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-1579-2009 ◽

2009 ◽

Vol 9 (5) ◽

pp. 1579-1595 ◽

Cited By ~ 50

Author(s):

C. Galy-Lacaux ◽

D. Laouali ◽

L. Descroix ◽

N. Gobron ◽

C. Liousse

Keyword(s):

Wet Deposition ◽

Ph Value ◽

Precipitation Chemistry ◽

Annual Rainfall ◽

Deposition Flux ◽

Air Concentration ◽

Ionic Charge ◽

Rainfall Gradient ◽

The Mean

Abstract. Long-term precipitation chemistry have been recorded in the rural area of Banizoumbou (Niger), representative of a semi-arid savanna ecosystem. A total of 305 rainfall samples ~90% of the total annual rainfall) were collected from June 1994 to September 2005. From ionic chromatography, pH major inorganic and organic ions were detected. Rainwater chemistry is controlled by soil/dust emissions associated with terrigeneous elements represented by SO42−, Ca2+, Carbonates, K+ and Mg2+. It is found that calcium and carbonates represent ~40% of the total ionic charge. The second highest contribution is nitrogenous, with annual Volume Weighed Mean (VWM) for NO3− and NH4+ concentrations of 11.6 and 18.1 μeq.l−1, respectively. This is the signature of ammonia sources from animals and NOx emissions from savannas soil-particles rain-induced. The mean annual NH3 and NO2 air concentration are of 6 ppbv and 2.6 ppbv, respectively. The annual VWM precipitation concentration of sodium and chloride are both of 8.7 μeq.l−1 which reflects the marine signature of monsoonal and humid air masses. The median pH value is of 6.05. Acidity is neutralized by mineral dust, mainly carbonates, and/or dissolved gases such NH3. High level of organic acidity with 8μeq.l−1 and 5.2 μeq.l−1 of formate and acetate were also found. The analysis of monthly Black Carbon emissions and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) values show that both biogenic emission from vegetation and biomass burning could explain the rainfall organic acidity content. The interannual variability of the VWM concentrations around the mean (1994–2005) is between ±5% and ±30% and mainly due to variations of sources strength and rainfall spatio-temporal distribution. From 1994 to 2005, the total mean wet deposition flux in the Sahelian region is of 60.1 mmol.m−2.yr−1 ±25%. Finally, Banizoumbou measurements are compared to other long-term measurements of precipitation chemistry in the wet savanna of Lamto (Côte d'Ivoire) and in the forested zone of Zoétélé (Cameroon). The total chemical loading presents a maximum in the dry savanna and a minimum in the forest (from 143.7, 100.2 to 86.6 μeq.l−1), associated with the gradient of terrigeneous sources. The wet deposition fluxes present an opposite trend, with 60.0 mmol.m−2.yr−1 in Banizoumbou, 108.6 mmol.m−2.yr−1 in Lamto and 162.9 mmol.m−2.yr−1 in Zoétélé, controlled by rainfall gradient along the ecosystems transect.

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Inverse AERMOD and SCIPUFF Dispersion Modeling for Farm-Level PM10 Emission Rate Assessment

Transactions of the ASABE ◽

10.13031/trans.14311 ◽

2021 ◽

Vol 64 (3) ◽

pp. 801-817

Author(s):

Bin Cheng ◽

Aditya Padavagod Shiv Kumar ◽

Lingjuan Wang-Li

Keyword(s):

Wind Speed ◽

Egg Production ◽

Single Point ◽

Dispersion Modeling ◽

Emission Rates ◽

Farm Level ◽

Area Source ◽

Inverse Dispersion ◽

Pm10 Emission ◽

Inverse Dispersion Modeling

HighlightsAERMOD and SCIPUFF were employed to back-calculate farm-level PM10 emission rates based on inverse modeling.Both AERMOD and SCIPUFF did not capture the diurnal and seasonal variations of farm-level PM10 emission rates.AERMOD modeling results were affected by wind speed, with higher wind speed leading to higher emission rates.Higher numbers of receptors and PM10 measurements with greater time resolution may be recommended in the future.Abstract. Air pollutant emissions from animal feeding operations (AFOs) have become a serious concern for public health and ambient air quality. Particulate matter with aerodynamic equivalent diameter less than or equal to 10 µm (PM10) is one of the major air pollutants emitted from AFOs. To assess the impacts of PM10 emissions from AFOs, knowledge about farm-level PM10 emission rates is needed but is challenging to obtain through field measurements. The inverse dispersion modeling approach provides an alternative way to estimate farm-level PM10 emission rates. In this study, two dispersion models, AERMOD and SCIPUFF, were employed to back-calculate farm-level PM10 emission rates based on hourly PM10 concentration measurements at four downwind locations in the vicinity of a commercial egg production farm in the southeast U.S. Onsite meteorological data were simultaneously recorded using a 10 m weather tower to facilitate the dispersion modeling. The modeling results were compared with PM10 emission measurements from two layer houses on the farm. Single-area source, double-area source, and double-volume source were used in AERMOD, while only single-point source was used in SCIPUFF. The inverse modeling results indicated that both SCIPUFF and AERMOD did not capture the diurnal and seasonal variations of the farm-level PM10 emission rates. In addition, the AERMOD modeling results were affected by wind speed, and higher emission rates may be predicted at higher wind speeds. The single-point source for SCIPUFF, the plume rise simplification for AERMOD, and insufficient concentration measurement resolution in response to temporal changes in wind direction may have added uncertainties to the modeling results. The results of this study suggest that more receptors covering more representative downwind locations should be considered in future modeling for farm-level emissions assessment. Moreover, ambient data collection with greater time resolution (e.g., less than one hour) is recommended to capture diurnal and seasonal patterns more rigorously. Only in this way can researchers achieve a better understanding of the effectiveness of inverse dispersion modeling for estimation of pollutant emission rates. Keywords: AERMOD, Animal feeding operations, Egg production, Farm-level emission rate, Inverse dispersion modeling, PM10, SCIPUFF.

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A Comprehensive Assessment of Tropical Stratospheric Upwelling in Specified Dynamics CESM1.2.2 (WACCM)

10.5194/gmd-2019-238 ◽

2019 ◽

Author(s):

Nicholas A. Davis ◽

Sean M. Davis ◽

Robert W. Portmann ◽

Eric Ray ◽

Karen H. Rosenlof ◽

...

Keyword(s):

Best Practices ◽

Climate Models ◽

Climate Model ◽

Meridional Circulation ◽

Trace Gas ◽

Mean Meridional Circulation ◽

Community Earth System Model ◽

Free Running ◽

The Mean ◽

Wave Momentum

Abstract. Specified dynamics (SD) schemes relax the circulation in climate models toward a reference meteorology to simulate historical variability. These simulations are widely used to isolate the dynamical contributions to variability and trends in trace gas species. However, it is not clear if trends in the stratospheric overturning circulation are properly reproduced by SD schemes. This study assesses numerous SD schemes and modeling choices in the Community Earth System Model (CESM) Whole Atmosphere Chemistry Climate Model (WACCM) to determine a set of best practices for reproducing interannual variability and trends in tropical stratospheric upwelling estimated by reanalyses. Nudging toward the reanalysis meteorology as is typically done in SD simulations expectedly changes the model’s mean upwelling compared to its free-running state, but does not accurately reproduce upwelling trends present in the underlying reanalysis. In contrast, nudging to anomalies from the climatological winds or from the zonal mean winds and temperatures preserves WACCM’s climatology and better reproduces trends in stratospheric upwelling. An SD scheme’s performance in simulating the acceleration of the shallow branch of the mean meridional circulation from 1980–2017 hinges on its ability to simulate the downward shift of subtropical lower stratospheric wave momentum forcing. Key to this is not nudging the zonal-mean temperature field. Gravity wave momentum forcing, which drives a substantial fraction of the upwelling in WACCM, cannot be constrained by nudging and presents an upper-limit on the performance of these schemes.

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