Can windcatcher's natural ventilation beat the chill? A view from heat loss and thermal discomfort

Windcatchers provide effective low-energy ventilation and summer passive cooling in temperate climates. However, their use in winter is limited due to significant ventilation heat loss and potential discomfort. Limited research has been conducted on quantifying windcatcher heat loss in cold climates, particularly through field studies. This study aims to evaluate the applicability of windcatchers in low-temperature conditions, with a focus on ventilation heat loss and thermal discomfort. Field experiments were conducted in Nottingham, UK, during an icy period. A 3D-printed prototype windcatcher and a test room were built and tested in such weather conditions. A Computational Fluid Dynamics (CFD) model validated against the field experimental data was employed to investigate the windcatcher's performance in a typical UK primary school classroom. The field experimental results indicate that the indoor airflow patterns are dynamic and continuously change with varying external wind conditions. Using static boundary conditions for ventilation analysis is inadequate, as it may lead to inaccurate predictions due to observed fluctuations and irregular airflow patterns. CFD modelling revealed significant over-ventilation in the classroom at external wind speeds of 3 m/s, despite being previously deemed as “satisfactory”, “adequate”, or “sufficient” ventilation. At wind speeds of 3 m/s or higher, the over-ventilation can cause a minimum 941.4 W heat loss, adding 4.7 kWh heating load and £1.6 electricity cost for a typical-sized single classroom during a 5-h occupied period. The research findings highlighted that control strategies should be introduced to reduce over-ventilation. Integrating heat recovery or thermal storage can enhance winter thermal conditions

Comparison of chemical characteristics of 495 biomass burning plumes intercepted by the NASA DC-8 aircraft during the ARCTAS/CARB-2008 field campaign

This paper compares measurements of gaseous and particulate emissions from a wide range of biomass-burning plumes intercepted by the NASA DC-8 research aircraft during the three phases of the ARCTAS-2008 experiment: ARCTAS-A, based out of Fairbanks, Alaska, USA (3 April to 19 April 2008); ARCTAS-B based out of Cold Lake, Alberta, Canada (29 June to 13 July 2008); and ARCTAS-CARB, based out of Palmdale, California, USA (18 June to 24 June 2008). Approximately 500 smoke plumes from biomass burning emissions that varied in age from minutes to days were segregated by fire source region and urban emission influences. The normalized excess mixing ratios (NEMR) of gaseous (carbon dioxide, acetonitrile, hydrogen cyanide, toluene, benzene, methane, oxides of nitrogen and ozone) and fine aerosol particulate components (nitrate, sulfate, ammonium, chloride, organic aerosols and water soluble organic carbon) of these plumes were compared. A detailed statistical analysis of the different plume categories for different gaseous and aerosol species is presented in this paper. The comparison of NEMR values showed that CH4 concentrations were higher in air-masses that were influenced by urban emissions. Fresh biomass burning plumes mixed with urban emissions showed a higher degree of oxidative processing in comparison with fresh biomass burning only plumes. This was evident in higher concentrations of inorganic aerosol components such as sulfate, nitrate and ammonium, but not reflected in the organic components. Lower NOx NEMRs combined with high sulfate, nitrate and ammonium NEMRs in aerosols of plumes subject to long-range transport, when comparing all plume categories, provided evidence of advanced processing of these plumes

Brown carbon aerosol in the North American continental troposphere: sources, abundance, and radiative forcing

Chemical components of organic aerosol (OA) selectively absorb light at short wavelengths. In this study, the prevalence, sources, and optical importance of this so called brown carbon (BrC) aerosol component are investigated throughout the North American continental tropospheric column during a summer of extensive biomass burning. Spectrophotometric absorption measurements on extracts of bulk aerosol samples collected from an aircraft over the central USA were analyzed to directly quantify BrC abundance. BrC was found to be prevalent throughout the 1 to 12 km altitude measurement range, with dramatic enhancements in biomass-burning plumes. BrC to black carbon (BC) ratios, under background tropospheric conditions, increased with altitude, consistent with a corresponding increase in the absorption Ångström exponent (AAE) determined from a three-wavelength particle soot absorption photometer (PSAP). The sum of inferred BC absorption and measured BrC absorption at 365 nm was within 3 % of the measured PSAP absorption for background conditions and 22 % for biomass burning. A radiative transfer model showed that BrC absorption reduced top-of atmosphere (TOA) aerosol forcing by ∼ 20 % in the background troposphere. Extensive radiative model simulations applying this study background tropospheric conditions provided a look-up chart for determining radiative forcing efficiencies of BrC as a function of a surface-measured BrC : BC ratio and single scattering albedo (SSA). The chart is a first attempt to provide a tool for better assessment of brown carbon’s forcing effect when one is limited to only surface data. These results indicate that BrC is an important contributor to direct aerosol radiative forcing

Modeling regional aerosol variability over California and its sensitivity to emissions and long-range transport during the 2010 CalNex and CARES campaigns

Abstract. The performance of the Weather Research and Forecasting regional model with chemistry (WRF-Chem) in simulating the spatial and temporal variations in aerosol mass, composition, and size over California is quantified using measurements collected during the California Nexus of Air Quality and Climate Experiment (CalNex) and the Carbonaceous Aerosol and Radiative Effects Study (CARES) conducted during May and June of 2010. The extensive meteorological, trace gas, and aerosol measurements collected at surface sites and along aircraft and ship transects during CalNex and CARES were combined with operational monitoring network measurements to create a single dataset that was used to evaluate the one configuration of the model. Simulations were performed that examined the sensitivity of regional variations in aerosol concentrations to anthropogenic emissions and to long-range transport of aerosols into the domain obtained from a global model. The configuration of WRF-Chem used in this study is shown to reproduce the overall synoptic conditions, thermally-driven circulations, and boundary layer structure observed in region that controls the transport and mixing of trace gases and aerosols. However, sub-grid scale variability in the meteorology and emissions as well as uncertainties in the treatment of secondary organic aerosol chemistry likely contribute to errors at a primary surface sampling site located at the edge of the Los Angeles basin. Differences among the sensitivity simulations demonstrate that the aerosol layers over the central valley detected by lidar measurements likely resulted from lofting and recirculation of local anthropogenic emissions along the Sierra Nevada. Reducing the default emissions inventory by 50% led to an overall improvement in many simulated trace gases and black carbon aerosol at most sites and along most aircraft flight paths; however, simulated organic aerosol was closer to observed when there were no adjustments to the primary organic aerosol emissions. The model performance for some aerosol species was not uniform over the region, and we found that sulfate was better simulated over northern California whereas nitrate was better simulated over southern California. While the overall spatial and temporal variability of aerosols and their precursors were simulated reasonably well, we show cases where the local transport of some aerosol plumes were either too slow or too fast, which adversely affects the statistics regarding the differences between observed and simulated quantities. Comparisons with lidar and in-situ measurements indicate that long-range transport of aerosols from the global model was likely too high in the free troposphere even though their concentrations were relatively low. This bias led to an over-prediction in aerosol optical depth by as much as a factor of two that offset the under-predictions of boundary-layer extinction resulting primarily from local emissions. Lowering the boundary conditions of aerosol concentrations by 50% greatly reduced the bias in simulated aerosol optical depth for all regions of California. This study shows that quantifying regional-scale variations in aerosol radiative forcing and determining the relative role of emissions from local and distant sources is challenging during "clean" conditions and that a wide array of measurements are needed to ensure model predictions are correct for the right reasons. In this regard, the combined CalNex and CARES datasets are an ideal testbed that can be used to evaluate aerosol models in great detail and develop improved treatments for aerosol processes

Evolution of brown carbon in wildfire plumes

Particulate brown carbon (BrC) in the atmosphere absorbs light at subvisible wavelengths and has poorly constrained but potentially large climate forcing impacts. BrC from biomass burning has virtually unknown lifecycle and atmospheric stability. Here, BrC emitted from intense wildfires was measured in plumes transported over 2 days from two main fires, during the 2013 NASA SEAC4RS mission. Concurrent measurements of organic aerosol (OA) and black carbon (BC) mass concentration, BC coating thickness, absorption Ångström exponent, and OA oxidation state reveal that the initial BrC emitted from the fires was largely unstable. Using back trajectories to estimate the transport time indicates that BrC aerosol light absorption decayed in the plumes with a half-life of 9 to 15 h, measured over day and night. Although most BrC was lost within a day, possibly through chemical loss and/or evaporation, the remaining persistent fraction likely determines the background BrC levels most relevant for climate forcing

Mind the numt: Finding informative mitochondrial markers in a giant grasshopper genome

H2020 Marie Sklodowska-Curie Actions, Grant/Award Number: 658706; Ministerio de Ciencia, Innovacion y Universidades, Grant/Award Number: PID2019-104952GB-I00/AEI/10.13039/501100011033The barcoding of the mitochondrial COX1 gene has been instrumental in cataloguing the tree of life, and in providing insights in the phylogeographic history of species. Yet, this strategy has encountered difficulties in major clades characterized by large genomes, which contain a high frequency of nuclear pseudogenes originating from the mitochondrial genome (numts). Here, we use the meadow grasshopper (Chorthippus parallelus), which possesses a giant genome of ~13 Gb, to identify mitochondrial genes that are underrepresented as numts, and test their use as informative phylogeographic markers. We recover the same full mitochondrial sequence using both whole genome and transcriptome sequencing, including functional protein‐coding genes and tRNAs. We show that a region of the mitogenome containing the COX1 gene, typically used in DNA barcoding, has disproportionally higher diversity and coverage than the rest of the mitogenome, consistent with multiple insertions of that region into the nuclear genome. By designing new markers in regions of less elevated diversity and coverage, we identify two mitochondrial genes that are less likely to be duplicated as numts. We show that, while these markers show high levels of incomplete lineage sorting between subspecies, as expected for mitochondrial genes, genetic variation reflects their phylogeographic history accurately. These findings allow us to identify useful mitochondrial markers for future studies in C. parallelus, an important biological system for evolutionary biology. More generally, this study exemplifies how non‐PCR‐based methods using next‐generation sequencing can be used to avoid numts in species characterized by large genomes, which have remained challenging to study in taxonomy and evolution.H2020 Marie Sklodowska-Curie Actions 658706Ministerio de Ciencia, Innovacion y Universidades PID2019-104952GB-I00/AEI/10.13039/50110001103

Force-clamp analysis techniques reveal stretched exponential unfolding kinetics in ubiquitin

Force-clamp spectroscopy reveals the unfolding and disulfide bond rupture times of single protein molecules as a function of the stretching force, point mutations and solvent conditions. The statistics of these times reveal whether the protein domains are independent of one another, the mechanical hierarchy in the polyprotein chain, and the functional form of the probability distribution from which they originate. It is therefore important to use robust statistical tests to decipher the correct theoretical model underlying the process. Here we develop multiple techniques to compare the well-established experimental data set on ubiquitin with existing theoretical models as a case study. We show that robustness against filtering, agreement with a maximum likelihood function that takes into account experimental artifacts, the Kuiper statistic test and alignment with synthetic data all identify the Weibull or stretched exponential distribution as the best fitting model. Our results are inconsistent with recently proposed models of Gaussian disorder in the energy landscape or noise in the applied force as explanations for the observed non-exponential kinetics. Since the physical model in the fit affects the characteristic unfolding time, these results have important implications on our understanding of the biological function of proteins

A Neuro-Inspired Spike-Based PID Motor Controller for Multi-Motor Robots with Low Cost FPGAs

In this paper we present a neuro-inspired spike-based close-loop controller written in VHDL and implemented for FPGAs. This controller has been focused on controlling a DC motor speed, but only using spikes for information representation, processing and DC motor driving. It could be applied to other motors with proper driver adaptation. This controller architecture represents one of the latest layers in a Spiking Neural Network (SNN), which implements a bridge between robotics actuators and spike-based processing layers and sensors. The presented control system fuses actuation and sensors information as spikes streams, processing these spikes in hard real-time, implementing a massively parallel information processing system, through specialized spike-based circuits. This spike-based close-loop controller has been implemented into an AER platform, designed in our labs, that allows direct control of DC motors: the AER-Robot. Experimental results evidence the viability of the implementation of spike-based controllers, and hardware synthesis denotes low hardware requirements that allow replicating this controller in a high number of parallel controllers working together to allow a real-time robot control