Short-term methane emissions from two dairy farms in California estimated by different measurement techniques and US Environmental Protection Agency inventory methodology: A case study

Atmospheric top-down measurements have attributed up to twice the methane (CH4) emissions of bottom-up (BU) inventories to dairy production. We explored this discrepancy by estimating CH4 emissions of two dairy facilities in California with U.S. Environmental Protection Agency (USEPA) methodology, which is used for BU inventories, and three independent measurement techniques: 1) open-path measurements with inverse dispersion modeling (hereafter “open-path”); 2) vehicle measurements with tracer flux ratio method; and 3) aircraft measurements with closed-path method. All three techniques estimated whole farm CH4 emissions during one week in the summer of 2016. In addition, open-path also estimated whole farm CH4 emissions during two months in the winter of 2017. The objectives of the present study were: 1) to compare the different techniques to measure whole farm CH4 emissions from dairies, 2) to estimate CH4 emissions from animal housing and liquid manure storage, and compare them to USEPA inventory estimates, and 3) to compare CH4 emissions between the two dairies. Whole farm CH4 estimates were similar among measurement techniques. No seasonality was detected for CH4 emissions from animal housing, but CH4 emissions from liquid manure storage were three to six times greater during the summer than during the winter. Open-path estimates for liquid manure storage emissions were similar to monthly USEPA estimates during the summer but not during the winter, and neither open-path estimates from summer nor winter were similar to the annual USEPA estimate. Thus, CH4 emissions need to be measured throughout the year to evaluate annual inventories. Methane yields from housing and liquid manure storage were used to compare emissions between the farms. While CH4 yields from animal housing were similar (on average 20.9 g CH4/kg dry matter intake), CH4 yields from liquid manure storage at one dairy were 1.7 and 3.5 times greater than at the other dairy during summer (234 vs. 137 g CH4/kg volatile solids [VS]) and winter (78 vs. 22 g CH4/kg VS), respectively. This greater CH4 yield was attributed to the greater proportion of manure stored in liquid form, which suggests that the promotion of manure management practices that reduce the amount of manure solids stored in liquid form, such as manure separators, could significantly reduce CH4 emissions from dairies. These results demonstrate that multiple techniques for monitoring emissions on these farms were comparable

Response of a Lake Michigan coastal lake to anthropogenic catchment disturbance

A paleolimnological investigation of post-European sediments in a Lake Michigan coastal lake was used to examine the response of Lower Herring Lake to anthropogenic impacts and its role as a processor of watershed inputs. We also compare the timing of this response with that of Lake Michigan to examine the role of marginal lakes as ‘early warning’ indicators of potential changes in the larger connected system and their role in buffering Lake Michigan against anthropogenic changes through biotic interactions and material trapping. Sediment geochemistry, siliceous microfossils and nutrient-related morphological changes in diatoms, identified three major trophic periods in the recent history of the lake. During deforestation and early settlement (pre-1845–1920), lake response to catchment disturbances results in localized increases in diatom abundances with minor changes in existing communities. In this early phase of disturbance, Lower Herring Lake acts as a sediment sink and a biological processor of nutrient inputs. During low-lake levels of the 1930s, the lake goes through a transitional period characterized by increased primary productivity and a major shift in diatom communities. Post-World War II (late 1940s–1989) anthropogenic disturbances push Lower Herring Lake to a new state and a permanent change in diatom community structure dominated by Cyclotella comensis . The dominance of planktonic summer diatom species associated with the deep chlorophyll maximum (DCM) is attributed to epilimnetic nutrient depletion. Declining Si:P ratios are inferred from increased sediment storage of biogenic silica and morphological changes in the silica content of Aulacoseira ambigua and Stephanodiscus niagarae . Beginning in the late 1940s, Lower Herring Lake functions as a biogeochemical processor of catchment inputs and a carbon, nutrient and silica sink. Microfossil response to increased nutrients and increased storage of biogenic silica in Lower Herring Lake and other regional embayments occur approximately 20–25 years earlier than in a nearby Lake Michigan site. Results from this study provide evidence for the role of marginal lakes and bays as nutrient buffering systems, delaying the impact of anthropogenic activities on the larger Lake Michigan system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43091/1/10933_2004_Article_1688.pd

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Assessing wave energy effects on biodiversity: the Wave Hub experience

Marine renewable energy installations harnessing energy from wind, wave and tidal resources are likely to become a large part of the future energy mix worldwide. The potential to gather energy from waves has recently seen increasing interest, with pilot developments in several nations. Although technology to harness wave energy lags behind that of wind and tidal generation, it has the potential to contribute significantly to energy production. As wave energy technology matures and becomes more widespread, it is likely to result in further transformation of our coastal seas. Such changes are accompanied by uncertainty regarding their impacts on biodiversity. To date, impacts have not been assessed, as wave energy converters have yet to be fully developed. Therefore, there is a pressing need to build a framework of understanding regarding the potential impacts of these technologies, underpinned by methodologies that are transferable and scalable across sites to facilitate formal meta-analysis. We first review the potential positive and negative effects of wave energy generation, and then, with specific reference to our work at the Wave Hub (a wave energy test site in southwest England, UK), we set out the methodological approaches needed to assess possible effects of wave energy on biodiversity. We highlight the need for national and international research clusters to accelerate the implementation of wave energy, within a coherent understanding of potential effects—both positive and negative