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

Bühler, Marcel; Häni, Christoph; Ammann, Christof; Brönnimann, Stefan; Küpper, Thomas

doi:10.1016/j.aeaoa.2022.100161

Cited by 7 publications

(8 citation statements)

References 29 publications

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“…Coordinates of the instruments and source locations are needed for the bLS model and were collected with a handheld GPS (Trimble Pro 6T, Trimble Navigation Limited, Westminster, USA). At both sites methane was also measured and the results were published in Bühler et al (2021;2022).…”

Section: Measurement Campaignsmentioning

confidence: 88%

“…Other R packages used for data processing and plotting included ibts (Häni, 2022), RgoogleMaps Results…”

Section: Data Processing and Assessmentmentioning

confidence: 99%

“…Measuring gas emissions from open structures is challenging due to the source configuration and scale, as emissions are heterogeneous and dynamic in space and time (Bühler et al 2022). The inverse dispersion method (IDM) combines line-integrated concentration measurements up-and downwind of the source with results from modelling the inverse dispersion of the plume, such as from a backward Lagrangian stochastic (bLS) model.…”

Section: Introductionmentioning

confidence: 99%

“…The latter is particularly challenging for Switzerland, where smaller but very densely dispersed emission sources from farms with an average size of 22 dairy cows (Federal Statistical Office 2020) result in weaker emission plumes and high background levels. Despite this and the sometimes non-ideal terrain conditions, we previously demonstrated the effective application of IDM to quantify methane emissions under these constraints by optimising the filtering criteria (Bühler et al 2021;2022). The optimised method yielded a good comparability with an inhouse tracer ratio method (iTRM) as a reference (Mohn et al 2018) with differences in methane emissions of 1 -8%, which were well within the uncertainty range of both methods (i.e., <10% for tracer ratio and <24% for IDM (Mohn et al 2018;Bühler et al 2021)).…”

Section: Introductionmentioning

confidence: 99%

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

Valach¹

2023

Preprint

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Ammonia (NH3) emissions negatively impact air, soil, and water quality, and thus human health and biodiversity. A large share of emissions, including the largest sources, originate from single or multiple source structures, such as livestock facilities, but also wastewater treatment plants (WWTPs). The inverse dispersion method (IDM) has proven to be effective in measuring total emissions from such structures, however depositional loss between the source and point of measurement is not always 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 published emission data for the respective seasons, albeit very few comparable studies exist for WWTPs. A concurrent comparison with an inhouse tracer ratio method at the dairy housing indicated an underestimation of the IDM results by <20%. Diurnal emission patterns were evident at both sites likely driven by changes in air temperature and to a lesser extent wind speed, but possibly also indicating lagged effects of management activities such as sludge tank agitation at the WWTP. Modelled 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 modelled with distance from the source was between 7-9% and 9-12% during unstable and stable meteorological conditions, respectively, for the given measurement distances of 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 ranges of environmental conditions across all seasons are required to assess the effect of predictor variables on emission dynamics. Combined, IDM with deposition correction will allow the determination of emissions factors at reduced efforts and costs and thereby support the development and assessment of structural and operational emission reducing technologies and enlarge the data availability for emission inventories.

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Section: Measurement Campaignsmentioning

confidence: 88%

“…Other R packages used for data processing and plotting included ibts (Häni, 2022), RgoogleMaps Results…”

Section: Data Processing and Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Valach¹

2023

Preprint

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“…Evidence from facilities that were sampled multiple times in the current study revealed no relationship between emissions and environmental variables, such as wind speed and direction, temperature, season, and time of day. Previous research , has shown the existence of a diurnal pattern in CH 4 emissions coinciding with influent flow and/or storage of dewatered solids, with a general increase in emissions during the morning, daytime maxima, and early morning minima. Therefore, more work is needed to quantify the timing and magnitude of diurnal patterns in CH 4 emissions from WWTPs, but we acknowledge that the presented measurements exhibit a daytime bias (Figure S17) that we do not correct.…”

Section: Implications and Future Workmentioning

confidence: 99%

Underestimation of Sector-Wide Methane Emissions from United States Wastewater Treatment

Moore

Wendt

et al. 2023

Environ. Sci. Technol.

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An increasing percentage of US waste methane (CH 4 ) emissions come from wastewater treatment (10% in 1990 to 14% in 2019), although there are limited measurements across the sector, leading to large uncertainties in current inventories. We conducted the largest study of CH 4 emissions from US wastewater treatment, measuring 63 plants with average daily flows ranging from 4.2 × 10 −4 to 8.5 m 3 s −1 (<0.1 to 193 MGD), totaling 2% of the 62.5 billion gallons treated, nationally. We employed Bayesian inference to quantify facilityintegrated emission rates with a mobile laboratory approach (1165 crossplume transects). The median plant-averaged emission rate was 1.1 g CH 4 s −1 (0.1−21.6 g CH 4 s −1 ; 10th/90th percentiles; mean 7.9 g CH 4 s −1 ), and the median emission factor was 3.4 × 10 −2 g CH 4 (g influent 5 day biochemical oxygen demand; BOD 5 ) −1 [0.6−9.9 × 10 −2 g CH 4 (g BOD 5 ) −1 ; 10th/90th percentiles; mean 5.7 × 10 −2 g CH 4 (g BOD 5 ) −1 ]. Using a Monte Carlo-based scaling of measured emission factors, emissions from US centrally treated domestic wastewater are 1.9 (95% CI: 1.5−2.4) times greater than the current US EPA inventory (bias of 5.4 MMT CO 2 -eq). With increasing urbanization and centralized treatment, efforts to identify and mitigate CH 4 emissions are needed.

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Methane losses from different biogas plant technologies

et al. 2023

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

Cited by 7 publications

References 29 publications

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

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

Underestimation of Sector-Wide Methane Emissions from United States Wastewater Treatment

Methane losses from different biogas plant technologies

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