Long-term onsite monitoring of a sewage sludge drying pan finds methane emissions consistent with IPCC default emission factor.

As the wastewater sector moves towards achieving net zero greenhouse gas (GHG) emissions, quantifying and understanding fugitive emissions from various sewage treatment steps is crucial for developing effective GHG abatement strategies. Methane (CH) emissions from a sludge drying pan (SDP) were measured at a wastewater treatment plant in Australia for more than a year, using a micrometeorological technique paired with open-path lasers. The emission rate was tightly associated with sludge additions, climatology, and operational processes.

Ammonia emissions and dispersion from broiler production.

Ammonia (NH ) has been used as a target gas for nuisance complaints to restrict or close poultry operations near encroaching rural development. There are conflicting data on NH emissions from broiler production across the United States. The purpose of this research is to compare emission rates from a Georgia broiler operation across seasons and with other geographical areas in the United States.

Gas emissions during cattle manure composting and stockpiling.

Manure composting is a common management practice for cattle feedlots, but gaseous emissions from composting are poorly understood. The objective of this study was to quantify ammonia (NH ), nitrous oxide (N O), carbon dioxide (CO ), and methane (CH ) emissions from windrow composting (turning) and static stockpiling (nonturning) of manure at a commercial feedlot in Australia. An inverse-dispersion technique using an open-path Fourier transform infrared (OP-FTIR) spectrometer gas sensor was deployed to measure emissions of NH , N O, CO , and CH over a 165-d study period, and 29 and 15% of the total data intervals were actually used to calculate the fluxes for the windrow and stockpile, respectively.

Lignite effects on NH, NO, CO and CH emissions during composting of manure.

Production of compost from cattle manure results in ammonia (NH) and greenhouse gas emissions, causing the loss of valuable nitrogen (N) and having negative environmental impacts. Lignite addition to cattle pens has been reported to reduce NH emissions from manure by approximately 60%. However, the effect of lignite additions during the manure composting process, in terms of gaseous emissions of NH, nitrous oxide (NO), carbon dioxide (CO), and methane (CH) is not clear.

Applicability of Eddy Covariance to Estimate Methane Emissions from Grazing Cattle.

Grazing systems represent a significant source of enteric methane (CH), but available techniques for quantifying herd scale emissions are limited. This study explores the capability of an eddy covariance (EC) measurement system for long-term monitoring of CH emissions from grazing cattle. Measurements were made in two pasture settings: in the center of a large grazing paddock, and near a watering point where animals congregated during the day.

A Snapshot of Greenhouse Gas Emissions from a Cattle Feedlot.

Beef cattle feedlots emit large amounts of the greenhouse gases (GHG) methane (CH) and nitrous oxide (NO), as well as ammonia (NH), which contributes to NO emission when NH is deposited to land. However, there is a lack of simultaneous, in situ, and nondisturbed measurements of the major GHG gas components from beef cattle feedlots, or measurements from different feedlot sources. A short-term campaign at a beef cattle feedlot in Victoria, Australia, quantified CH, NO, and NH emissions from the feedlot pens, manure stockpiles, and surface run-off pond.

Optimal sensor locations for the backward lagrangian stochastic technique in measuring lagoon gas emission.

This study evaluated the impact of gas concentration and wind sensor locations on the accuracy of measuring gas emission rates from a lagoon environment using the backward Lagrangian stochastic (bLS) inverse-dispersion technique. Path-integrated concentrations (PICs) and three-dimensional (3D) wind vector data were collected at different locations within the lagoon landscape. A floating 45 m × 45 m perforated pipe network on an irrigation pond was used as a synthetic distributed emission source for the controlled release of methane.

Evaluating dispersion modeling options to estimate methane emissions from grazing beef cattle.

Enteric methane (CH) emission from cattle is a source of greenhouse gas and is an energy loss that contributes to production inefficiency for cattle. Direct measurements of enteric CH emissions are useful to quantify the magnitude and variation and to evaluate mitigation of this important greenhouse gas source. The objectives of this study were to evaluate the impact of stocking density of cattle and source configuration (i.

The effect of biofuel production on swine farm methane and ammonia emissions.

Methane (CH) and ammonia (NH3) are emitted to the atmosphere during anaerobic processing of organic matter, and both gases have detrimental environmental effects. Methane conversion to biofuel production has been suggested to reduce CH4 emissions from animal manure processing systems. The purpose of this research is to evaluate the change in CH4 and NH3 emissions in an animal feeding operation due to biofuel production from the animal manure.

Inference of emission rates from multiple sources using Bayesian probability theory.

The determination of atmospheric emission rates from multiple sources using inversion (regularized least-squares or best-fit technique) is known to be very susceptible to measurement and model errors in the problem, rendering the solution unusable. In this paper, a new perspective is offered for this problem: namely, it is argued that the problem should be addressed as one of inference rather than inversion. Towards this objective, Bayesian probability theory is used to estimate the emission rates from multiple sources.

Estimating gas emissions from multiple sources using a backward Lagrangian stochastic model.

Manure storage tanks and animals in barns are important agricultural sources of methane. To examine the possibility of using an inverse dispersion technique based on a backward Lagrangian Stochastic (bLS) model to quantify methane (CH4) emissions from multiple on-farm sources, a series of tests were carried out with four possible source configurations and three controlled area sources. The simulated configurations were: (C1) three spatially separate ground-level sources, (C2) three spatially separate sources with wind-flow disturbance, (C3) three adjacent ground-level sources to simulate a group of adjacent sources with different emission rates, and (C4) a configuration with a ground level and two elevated sources.