225 research outputs found

    The use of disjunct eddy sampling methods for the determination of ecosystem level fluxes of trace gases

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    The concept of disjunct eddy sampling (DES) for use in measuring ecosystem-level micrometeorological fluxes is re-examined. The governing equations are discussed as well as other practical considerations and guidelines concerning this sampling method as it is applied to either the disjunct eddy covariance (DEC) or disjunct eddy accumulation (DEA) techniques. A disjunct eddy sampling system was constructed that could either be combined with relatively slow sensors (response time of 2 to 40 s) to measure fluxes using DEC, or could also be used to accumulate samples in stable reservoirs for later laboratory analysis (DEA technique). Both the DEC and DEA modes of this sampler were tested against conventional eddy covariance (EC) for fluxes of either CO2 (DEC) or isoprene (DEA). Good agreement in both modes was observed relative to the EC systems. However, the uncertainty in a single DEA flux measurement was considerable (40%) due to both the reduced statistical sampling and the analytical precision of the concentration difference measurements. We have also re-investigated the effects of nonzero mean vertical wind velocity on accumulation techniques as it relates to our DEA measurements. Despite the higher uncertainty, disjunct eddy sampling can provide an alternative technique to eddy covariance for determining ecosystem-level fluxes for species where fast sensors do not currently exist

    The bi-directional exchange of oxygenated VOCs between a loblolly pine (<I>Pinus taeda</I>) plantation and the atmosphere

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    International audienceUsing new in-situ field observations of the most abundant oxygenated VOCs (methanol, acetaldehyde, acetone, C3/C4 carbonyls, MVK+MAC and acetic acid) we were able to constrain emission and deposition patterns above and within a loblolly pine (Pinus taeda) plantation with a sweetgum (Liquidambar styraciflua) understory. During the day canopy scale measurements showed significant emission of methanol and acetone, while methyl vinyl ketone and methacrolein, acetaldehyde and acetic acid were mainly deposited during the day. All oxygenated compounds exhibited strong losses during the night that could not be explained by conventional dry deposition parameterizations. Accompanying leaf level measurements indicated substantial methanol and acetone emissions from loblolly pine. The exchange of acetaldehyde was more complex. Laboratory measurements made on loblolly pine needles indicated that acetaldehyde may be either emitted or taken up depending on ambient concentrations, with the compensation point increasing exponentially with temperature, and that mature needles tended to emit more acetaldehyde than younger needles. Canopy scale measurements suggested mostly deposition. Short-term (approx. 2 h) ozone fumigation in the laboratory had no detectable impact on post-exposure emissions of methanol and acetone, but decreased the exchange rates of acetaldehyde. The emission of a variety of oxygenated compounds (e.g. carbonyls and alcohols) was triggered or significantly enhanced during laboratory ozone fumigation experiments. These results suggest that higher ambient ozone levels in the future might enhance the biogenic contribution of some oxygenated compounds. Those with sufficiently low vapor pressures may potentially influence secondary organic aerosol growth. Compounds recently hypothesized to be primarily produced in the canopy atmosphere via ozone plus terpenoid-type reactions can also originate from the oxidation reaction of ozone with leaf surfaces and inside the leaf. This needs to be taken into account when scaling up very reactive biogenic compounds

    An all soft, electro-pneumatic controller for soft robots

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    Printable Flexible Robots for Remote Learning

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    The COVID-19 pandemic has revealed the importance of digital fabrication to enable online learning, which remains a challenge for robotics courses. We introduce a teaching methodology that allows students to participate remotely in a hands-on robotics course involving the design and fabrication of robots. Our methodology employs 3D printing techniques with flexible filaments to create innovative soft robots; robots are made from flexible, as opposed to rigid, materials. Students design flexible robotic components such as actuators, sensors, and controllers using CAD software, upload their designs to a remote 3D printing station, monitor the print with a web camera, and inspect the components with lab staff before being mailed for testing and assembly. At the end of the course, students will have iterated through several designs and created fluidically-driven soft robots. Our remote teaching methodology enables educators to utilize 3D printing resources to teach soft robotics and cultivate creativity among students to design novel and innovative robots. Our methodology seeks to democratize robotics engineering by decoupling hands-on learning experiences from expensive equipment in the learning environment.Comment: 9 pages, 4 figures, peer reviewed and presented paper at American Society of Engineering Education, April 22-23rd, 2022 - Wentworth Institute of Technolog

    Satellite-based global maps are rarely used in forest reference levels submitted to the UNFCCC

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    The Earth observation (EO) community is coordinating a range of activities in support of the Global Stocktake. One objective is to enhance the uptake of satellite-based global-scale maps (hereafter 'EO products') in national greenhouse gas (GHG) inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC). To measure progress towards this objective, we compile information on the use of EO products on land cover, fire, and above-ground biomass to derive carbon flux estimates in forest reference levels from 56 tropical countries submitted to the UNFCCC between 2014–2022. The global forest change (GFC) was the only EO product used to measure land extent and change, and was used by almost half the countries. Only two countries used existing EO products for fire mapping. Four countries used biomass maps, although only indirectly, such as for comparing with biomass estimates from field plot measurements or with IPCC defaults. The uptake is limited but improved the measurement, reporting and verification capacity of 22 countries. The relatively high uptake of the GFC demonstrates the importance of meeting essential conditions in the IPCC guidance when developing EO products, including conditions on spatial and temporal resolution, temporal coverage and consistency, and the flexibility to adapt to biophysical thresholds in national definitions. The limited use of other global land EO products underlines the need for developers of EO products to interact with groups responsible for GHG inventories and experts familiar with IPCC guidance so that their products are suitable for national reporting, and thus contribute to more complete aggregated estimates in the Global Stocktake

    Water soluble aerosols and gases at a UK background site. Part 1: Controls of PM2.5 and PM10 aerosol composition

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    There is limited availability of long-term, high temporal resolution, chemically speciated aerosol measurements which can provide further insight into the health and environmental impacts of particulate matter. The Monitor for AeRosols and Gases (MARGA, Applikon B.V., NL) allows for the characterisation of the inorganic components of PM10 and PM2.5 (NH4+, NO3-, SO42-, Cl-, Na+, K+, Ca2+, Mg2+) and inorganic reactive gases (NH3, SO2, HCl, HONO and HNO3) at hourly resolution. The following study presents 6.5 years (June 2006 to December 2012) of quasi-continuous observations of PM2.5 and PM10 using the MARGA at the UK EMEP supersite, Auchencorth Moss, SE Scotland. Auchencorth Moss was found to be representative of a remote European site with average total water soluble inorganic mass of PM2.5 of 3.82 μg m−3. Anthropogenically derived secondary inorganic aerosols (sum of NH4+, NO3- and nss-SO42−) were the dominating species (63 %) of PM2.5. In terms of equivalent concentrations, NH4+ provided the single largest contribution to PM2.5 fraction in all seasons. Sea salt was the main component (73 %) of the PMcoarse fraction (PM10-PM2.5), though NO3- was also found to make a relatively large contribution to the measured mass (17 %) providing evidence of considerable processing of sea salt in the coarse mode. There was on occasions evidence of aerosol from combustion events being transported to the site in 2012 as high K+ concentrations (deviating from the known ratio in sea salt) coincided with increases in black carbon at the site. Pollution events in PM10 (defined as concentrations > 12 μg m−3) were on average dominated by NH4+ and NO3-, where smaller loadings at the site tended to be dominated by sea salt. As with other western European sites, the charge balance of the inorganic components resolved were biased towards cations, suggesting the aerosol was basic or more likely that organic acids contributed to the charge balance. This study demonstrates the UK background atmospheric composition is primarily driven by meteorology with sea salt dominating air masses from the Atlantic Ocean and the Arctic, whereas secondary inorganic aerosols tended to dominate air masses from continental Europe

    Reduced-form and complex Actm modelling for air quality policy development: a model inter-comparison

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    Simulation models can be valuable tools in supporting development of air pollution policy. However, exploration of future scenarios depends on reliable and robust modelling to provide confidence in outcomes which cannot be tested against measurements. Here we focus on the UK Integrated Assessment Model, a fast reduced-form model with a purpose to support policy development with modelling of multiple alternative future scenarios, and the EMEP4UK model which is a complex Eulerian Atmospheric Chemistry Transport Model requiring significant computing resources. The EMEP4UK model has been used to model selected core scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years. This model intercomparison addresses total PM2.5, primary PM2.5 and Secondary Inorganic Aerosol concentrations for a baseline of 2018 and selected scenarios for projections to 2040. This work has confirmed the robustness of the UK Integrated Assessment Model for assessing alternative futures through a direct comparison with EMEP4UK. Both models have shown good agreement with measurements, and EMEP4UK shows an ability to replicate past trends. These comparisons highlight how a combination of reduced-form modelling (UKIAM) and complex chemical transport modelling (EMEP4UK) can be effectively used in support of air pollution policy development, informing understanding of projected futures in the context of emerging evidence and uncertainties

    Neural Network Analysis to Evaluate Ozone Damage to Vegetation Under Different Climatic Conditions

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    Tropospheric ozone (O-3) is probably the air pollutant most damaging to vegetation. Understanding how plants respond to O(3)pollution under different climate conditions is of central importance for predicting the interactions between climate change, ozone impact and vegetation. This work analyses the effect of O(3)fluxes on net ecosystem productivity (NEP), measured directly at the ecosystem level with the eddy covariance (EC) technique. The relationship was explored with artificial neural networks (ANNs), which were used to model NEP using environmental and phenological variables as inputs in addition to stomatal O(3)uptake in Spring and Summer, when O(3)pollution is expected to be highest. A sensitivity analysis allowed us to isolate the effect of O-3, visualize the shape of the O-3-NEP functional relationship and explore how climatic variables affect NEP response to O-3. This approach has been applied to eleven ecosystems covering a range of climatic areas. The analysis highlighted that O(3)effects over NEP are highly non-linear and site-specific. A significant but small NEP reduction was found during Spring in a Scottish shrubland (-0.67%), in two Italian forests (up to -1.37%) and during Summer in a Californian orange orchard (-1.25%). Although the overall seasonal effect of O(3)on NEP was not found to be negative for the other sites, with episodic O(3)detrimental effect still identified. These episodes were correlated with meteorological variables showing that O(3)damage depends on weather conditions. By identifying O(3)damage under field conditions and the environmental factors influencing to that damage, this work provides an insight into O(3)pollution, climate and weather conditions.Peer reviewe

    Organic aerosol concentration and composition over Europe: insights from comparison of regional model predictions with aerosol mass spectrometer factor analysis

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    A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93% to total OA during May, 87% during winter and 96% during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 μg m−3, mean bias = −0.2 μg m−3). The model systematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 μg m−3). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C* ≤ 0.1 μg m−3 and semivolatile OOA against the OA with C* > 0.1 μg m−3
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