Emission Determination by Three Remote Sensing Methods in Two Release Trials

Concentrations of greenhouse gases such as carbon dioxide (CO2), nitrous dioxide (N2O) and methane (CH4) in the atmosphere are rising continuously. The first step to reduce emissions from landfills is to gain better knowledge about the quantities emitted. There are several ways to quantify CH4 emissions at landfills. Comprehensive quality analyses of individual methods for emission rate quantification at landfills are few to date. In the present paper, the authors conducted two field trials with three different remote sensing methods to gain more knowledge about the possibilities and challenges in quantification of CH4 emissions from landfills. One release trial was conducted with released N2O as tracer and CH4 for quality assessment of the methods. In the second trial, the N2O tracer was released on a landfill to gain experience under field conditions. The well-established inverse dispersion modelling method (IDMM) was used based on concentration data of TDLAS (Tunable Diode Laser Absorption Spectroscopy)-instruments and on concentration data of a partly drone based Fourier-Transformation-Infrared-Spectroscopy (FTIR)-instrument. Additionally, a tracer-method with N2O-tracer and FTIR measurements was conducted. In both trials, IDMM based on TDLAS data and FTIR data provided the best results for high emission rates (15% deviation) and low emission rates (47% deviation). However, both methods have advantages, depending on the field of application. IDMM based on TDLAS measurements is the best choice for long-term measurements over several hours with constant wind conditions (8% deviation). The IDMM based on drone based FTIR measurements is the means of choice for measurements under changing wind conditions and where no linear measurement distances are possible.

Focusing Phase Imaging for Lamb Wave Phased Array

In Lamb wave-based Structural Health Monitoring, amplitude damage imaging is commonly used because the defects feature can be easily amplified by summing all the response signals together. However, the grating and side lobes affect the imaging quality and blind areas further restrict the inspection area. Considering that the existing phase-based imaging algorithms are either unfit for dispersive Lamb wave or strict to many requirements to guarantee better performance, inspired by the absence of phase information in focusing phased array, a novel Focusing Phase Imaging (FPI) method for Lamb wave phased array is developed. The main contribution of the paper is introducing the phase information to focusing phased array. By applying the inverse-dispersion effect to the excitation signals and the superposition operation, the energy can be focused at every inspection point. The phase damage index is constructed by directly measuring the degree of consistency and alignment of the instantaneous phases. The experiments for the circular and linear array under various excitation signals with multiple defects verify that the FPI is effective for both surface damage and through-hole damage. The proposed algorithm is superior for its ability in energy focusing for defects, the capability in suppression of grating and side lobes, strong anti-disturbance ability from boundary reflection, the nonexistence of imaging blind area, and its adaptability for various excitation parameters and array layout.

Evaluation of ammonia emissions from filtration of digestate used for fertigation

Fertigation can be a suitable technique for utilizing digestate, minimizing nitrogen losses, and contributing to circularity within a farming system. For this purpose, digestate usually is first processed with a screw-press separator. However, further filtration is required to remove particles that could clog the nozzles of drip or sprinkling irrigation systems. Advanced filtration can be obtained using mechanical separation with screens having openings of 100- 300 μm. This operation can be another source of ammonia emission, but this aspect has not been adequately investigated. This study aimed to address this knowledge gap by evaluating the emissions from three different filtration systems for digestate. The study was conducted in three different farms located in Lombardy (Italy) using digestate to fertigate maize by drip irrigation (two farms) and pivot irrigation (one farm). Ammonia emissions were measured with passive samplers and the fluxes were examined using an inverse dispersion model implemented in Windtrax software. The emissions were measured both when the filtration systems were in operation and when they were switched off. Ammonia emissions (mean values between 375 and 876 μg NH3/m2/s) tended to increase during operation of the filtration systems. However, no significant differences were found in the emissions from active and inactive equipment on any of the farms. The emissions from the filtration systems were higher than from a storage tank (22-67 μg NH3/m2/s). However, the mean emissions amounted to only 0.3% of the nitrogen content of the digestate. These emissions can be considered irrelevant in the context of the whole management scheme for digestate. This work provides a first insight on ammonia emissions arising from advanced filtration of digestate, with specific reference to Po Valley farming systems. Further studies are required to improve knowledge about emissions from the entire digestate management process, including the treatments required for specific application techniques.

Artificial gauge induced dispersionless coupling for broadband photonic waveguide integration

Coupling among waveguides plays an important role in photonic integration, while it usually suffers from large wavelength dispersion and structural sensitivity that brings difficulties in broadband and robust photonic chip devices. Here, we report a new strategy of dispersion engineering of coupled waveguides by artificial gauge field (AGF) with curved trajectories, which gives rise to a dispersionless broadband coupler function in high-density silicon waveguides (waveguide pitch <λ/2). It is found that the artificial gauge field can generate an inverse dispersion to compensate for the dispersion of conventional waveguide coupling. As such, the coupling between the waveguides can be stable in a broad bandwidth. Based on this design, we demonstrate compact directional and 3dB couplers that show broadband dispersionless coupling of light with wavelength from 1400 to 1650 nm, which also exhibit robustness to considerably large structural variations ~150 nm (75% structural deviation). Furthermore, using the AGF coupler as the building block, we significantly demonstrate a three-level-cascaded waveguide network to route the broadband light to the desired ports, showing a tremendous advantage over the conventional counterparts. Our work exploits the artificial gauge field to integrated photonics and demonstrates the possibility of massive, broadband, robust and dense photonic integrations.

Beef cattle methane emissions measured with tracer-ratio and inverse dispersion modelling techniques

The development and validation of management practices to mitigate greenhouse gas (GHG) emissions from livestock require accurate emission measurements. This study assessed the accuracy of a practical inverse dispersion modelling (IDM) technique to quantify methane (CH4) emitted from a small cattle herd (16 animals) confined to a 63 m × 60 m experimental pen. The IDM technique calculates emissions from the increase in the CH4 concentration measured downwind of the animals. The measurements were conducted for 7 d. Two types of open-path (OP) gas sensors were used to measure concentration in the IDM calculation: a Fourier transform infrared spectrometer (IDM-FTIR) or a CH4 laser (IDM-Laser). The actual cattle emission rate was measured with a tracer-ratio technique using nitrous oxide (N2O) as the tracer gas. We found very good agreement between the two IDM emission estimates (308.1 ± 2.1 – mean ± SE – and 304.4 ± 8.0 g CH4 head−1 d−1 for the IDM-FTIR and IDM-Laser respectively) and the tracer-ratio measurements (301.9 ± 1.5 g CH4 head−1 d−1). This study suggests that a practical IDM measurement approach can provide an accurate method of estimating cattle emissions.

Methane emissions from an oil sands tailings pond: a quantitative comparison of fluxes derived by different methods

Tailings ponds in the Alberta oil sands region are significant sources of fugitive emissions of methane to the atmosphere, but detailed knowledge on spatial and temporal variabilities is lacking due to limitations of the methods deployed under current regulatory compliance monitoring programs. To develop more robust and representative methods for quantifying fugitive emissions, three micrometeorological flux methods (eddy covariance, gradient, and inverse dispersion) were applied along with traditional flux chambers to determine fluxes over a 5-week period. Eddy covariance flux measurements provided the benchmark. A method is presented to directly calculate stability-corrected eddy diffusivities that can be applied to vertical gas profiles for gradient flux estimation. Gradient fluxes were shown to agree with eddy covariance within 18 %, while inverse dispersion model flux estimates were 30 % lower. Fluxes were shown to have only a minor diurnal cycle (15 % variability) and were weakly dependent on wind speed, air, and water surface temperatures. Flux chambers underestimated the fluxes by 64 % in this particular campaign. The results show that the larger footprint together with high temporal resolution of micrometeorological flux measurement methods may result in more robust estimates of the pond greenhouse gas emissions.