Energy and environmental impacts of air-to-air heat pumps in a mid-latitude city.

Heat pumps (HPs) have emerged as a key technology for reducing energy use and greenhouse gas emissions. This study evaluates the potential switch to air-to-air HPs (AAHPs) in Toulouse, France, where conventional space heating is split between electric and gas sources. In this context, we find that AAHPs reduce heating energy consumption by 57% to 76%, with electric heating energy consumption decreasing by 6% to 47%, resulting in virtually no local heating-related CO2 emissions. We observe a slight reduction in near-surface air temperature of up to 0.5 °C during cold spells, attributable to a reduction in sensible heat flux, which is unlikely to compromise AAHPs operational efficiency. While Toulouse's heating energy mix facilitates large energy savings, electric energy consumption may increase in cities where gas or other fossil fuel sources prevail. Furthermore, as AAHPs efficiency varies with internal and external conditions, their impact on the electrical grid is more complex than conventional heating systems. The results underscore the importance of matching heating system transitions with sustainable electricity generation to maximize environmental benefits. The study highlights the intricate balance between technological advancements in heating and their broader environmental and policy implications, offering key insights for urban energy policy and sustainability efforts.

RPCA-based techniques for pattern extraction, hotspot identification and signal correction using data from a dense network of low-cost NO2 sensors in London.

High-density low-cost air quality sensor networks are a promising technology to monitor air quality at high temporal and spatial resolution. However the collected data is high-dimensional and it is not always clear how to best leverage this information, particularly given the lower data quality coming from the sensors. Here we report on the use of robust Principal Component Analysis (RPCA) using nitrogen dioxide data obtained from a recently deployed dense network of 225 air pollution monitoring nodes based on low-cost sensors in the Borough of Camden in London. RPCA addresses the brittleness of singular value decomposition towards outliers by using a decomposition of the data into low-rank and sparse contributions, with the latter containing outliers. The modal decomposition enabled by RPCA identifies major periodic patterns including spatial and temporal bias, dominant spatial variance, and north-south bias. The five most descriptive components capture 98 % of the data's variance, achieving a compression by a factor of 1500. We present a new technique that uses the sparse part of the data to identify hotspots. The data indicates that at the locations of the top 15 % most susceptible nodes in the network, the model identifies 23 % more hotspots than in all other locations combined. Moreover, the median hotspot event at these at-risk locations exceeds the mean NO2concentration by 33µg/m3. We show the potential of RPCA for signal correction; it corrects random errors yielding a reference signal with R2>0.8. Moreover, RPCA successfully reconstructs missing data from a sensor with R2=0.72 from the rest of the sensor network, an improvement upon PCA of around 50 %, allowing air quality estimations even if a sensor is out of use temporarily.

Modification of the swirling well cell culture model to alter shear stress metrics.

Effects of hemodynamic shear stress on endothelial cells have been extensively investigated using the "swirling well" method, in which cells are cultured in dishes or multiwell plates placed on an orbital shaker. A wave rotates around the well, producing complex patterns of shear. The method allows chronic exposure to flow with high throughput at low cost but has two disadvantages: a number of shear stress characteristics change in a broadly similar way from the center to the edge of the well, and cells at one location in the well may release mediators into the medium that affect the behavior of cells at other locations, exposed to different shears. These properties make it challenging to correlate cell properties with shear. The present study investigated simple alterations to ameliorate these issues. Flows were obtained by numerical simulation. Increasing the volume of fluid in the well-altered dimensional but not dimensionless shear metrics. Adding a central cylinder to the base of the well-forced fluid to flow in a square toroidal channel and reduced multidirectionality. Conversely, suspending a cylinder above the base of the well made the flow highly multidirectional. Increasing viscosity in the latter model increased the magnitude of dimensional but not dimensionless metrics. Finally, tilting the well changed the patterns of different wall shear stress metrics in different ways. Collectively, these methods allow similar flows over most of the cells cultured and/or allow the separation of different shear metrics. A combination of the methods overcomes the limitations of the baseline model.

Investigating microscale patchiness of motile microbes under turbulence in a simulated convective mixed layer.

Microbes play a primary role in aquatic ecosystems and biogeochemical cycles. Spatial patchiness is a critical factor underlying these activities, influencing biological productivity, nutrient cycling and dynamics across trophic levels. Incorporating spatial dynamics into microbial models is a long-standing challenge, particularly where small-scale turbulence is involved. Here, we combine a fully 3D direct numerical simulation of convective mixed layer turbulence, with an individual-based microbial model to test the key hypothesis that the coupling of gyrotactic motility and turbulence drives intense microscale patchiness. The fluid model simulates turbulent convection caused by heat loss through the fluid surface, for example during the night, during autumnal or winter cooling or during a cold-air outbreak. We find that under such conditions, turbulence-driven patchiness is depth-structured and requires high motility: Near the fluid surface, intense convective turbulence overpowers motility, homogenising motile and non-motile microbes approximately equally. At greater depth, in conditions analogous to a thermocline, highly motile microbes can be over twice as patch-concentrated as non-motile microbes, and can substantially amplify their swimming velocity by efficiently exploiting fast-moving packets of fluid. Our results substantiate the predictions of earlier studies, and demonstrate that turbulence-driven patchiness is not a ubiquitous consequence of motility but rather a delicate balance of motility and turbulent intensity.

Water neutrality framework for systemic design of new urban developments.

The climate emergency and population growth threaten urban water security in cities worldwide. Growth, urbanisation, and changes to way of life have increased housing demand, requiring cities such as London to increase their housing stock by more than 15% over the next 10 years. These new urban developments will increase water demand, urban flood risk, and river water pollution levels; therefore, an integrated systems-based approach to development and water management is needed. Water Neutrality (WN) has emerged as a concept to frame the concerns about escalating water stresses in cities. We frame WN as a planning process for new urban developments that aims to minimise impacts on urban water security and offset any remaining stresses by retrofitting existing housing stock. In this work, we present a novel systemic design framework for future urban planning called CityPlan-Water, which guides how WN might be achieved to tackle current and future water pressures at a city scale. CityPlan-Water integrates spatial data with an integrated urban water management model, enabling urban design at a systems level and systematic assessment of future scenarios. We define a Water Neutrality Index that captures how successful a given urban planning scenario is in achieving WN and how multiple interventions could be combined at a city scale to improve WN. Results from CityPlan-Water suggest that it will be necessary to retrofit almost the same number of existing homes with WN design options to completely offset the impact imposed by proposed new developments. Combining options such as water efficient appliances, water reuse systems, and social awareness campaigns can offset the impact of new development on water demand by 70%, while to neutralise potential flood risk and water pollution at a city scale, interventions such as rainwater harvesting and Blue Green Infrastructure need to be added both in new urban developments and 432,000 existing London households. We see CityPlan-Water as a tool that can support the transition of urban planning towards using data-driven analysis to effectively design water neutral housing and drive sustainable development.

Modelling of instantaneous emissions from diesel vehicles with a special focus on NOx: Insights from machine learning techniques.

Accurate instantaneous vehicle emissions models are vital for evaluating the impacts of road transport on air pollution at high temporal and spatial resolution. In this study, we apply machine learning techniques to a dataset of 70 diesel vehicles tested in real-world driving conditions to: (i) cluster vehicles with similar emissions performance, and (ii) model instantaneous emissions. The application of dynamic time warping and clustering analysis by NOx emissions resulted in 17 clusters capturing 88% of trips in the dataset. We show that clustering effectively groups vehicles with similar emissions profiles, however no significant correlation between emissions and vehicle characteristics (i.e. engine size, vehicle weight) were found. For each cluster, we evaluate three instantaneous emissions models: a look-up table (LT) approach, a non-linear regression (NLR) model and a neural network multi-layer perceptron (MLP) model. The NLR model provides accurate instantaneous NOx predictions, on par with the MLP: relative errors in prediction of emission factors are below 20% for both models, average fractional biases are -0.01 (s.d. 0.02) and -0.0003 (s.d. 0.04), and average normalised mean squared errors are 0.25 (s.d. 0.14) and 0.29 (s.d. 0.16), for the NLR and MLP models respectively. However, neural networks are better able to deal with vehicles not belonging to a specific cluster. The new models that we present rely on simple inputs of vehicle speed and acceleration, which could be extracted from existing sources including traffic cameras and vehicle tracking devices, and can therefore be deployed immediately to enable fast and accurate prediction of vehicle NOx emissions. The speed and the ease of use of these new models make them an ideal operational tool for policy makers aiming to build emission inventories or evaluate emissions mitigation strategies.

Small-scale entrainment in inclined gravity currents.

We investigate the effect of buoyancy on the small-scale aspects of turbulent entrainment by performing direct numerical simulation of a gravity current and a wall jet. In both flows, we detect the turbulent/nonturbulent interface separating turbulent from irrotational ambient flow regions using a range of enstrophy iso-levels spanning many orders of magnitude. Conform to expectation, the relative enstrophy isosurface velocity v n in the viscous superlayer scales with the Kolmogorov velocity for both flow cases. We connect the integral entrainment coefficient E to the small-scale entrainment and observe excellent agreement between the two estimates throughout the viscous superlayer. The contribution of baroclinic torque to v n is negligible, and we show that the primary reason for reduced entrainment in the gravity current as compared to the wall-jet are 1) the reduction of v n relative to the integral velocity scale u T ; and 2) the reduction in the surface area of the isosurfaces.

Visualization of three pathways for macromolecule transport across cultured endothelium and their modification by flow.

Transport of macromolecules across vascular endothelium and its modification by fluid mechanical forces are important for normal tissue function and in the development of atherosclerosis. However, the routes by which macromolecules cross endothelium, the hemodynamic stresses that maintain endothelial physiology or trigger disease, and the dependence of transendothelial transport on hemodynamic stresses are controversial. We visualized pathways for macromolecule transport and determined the effect on these pathways of different types of flow. Endothelial monolayers were cultured under static conditions or on an orbital shaker producing different flow profiles in different parts of the wells. Fluorescent tracers that bound to the substrate after crossing the endothelium were used to identify transport pathways. Maps of tracer distribution were compared with numerical simulations of flow to determine effects of different shear stress metrics on permeability. Albumin-sized tracers dominantly crossed the cultured endothelium via junctions between neighboring cells, high-density lipoprotein-sized tracers crossed at tricellular junctions, and low-density lipoprotein-sized tracers crossed through cells. Cells aligned close to the angle that minimized shear stresses across their long axis. The rate of paracellular transport under flow correlated with the magnitude of these minimized transverse stresses, whereas transport across cells was uniformly reduced by all types of flow. These results contradict the long-standing two-pore theory of solute transport across microvessel walls and the consensus view that endothelial cells align with the mean shear vector. They suggest that endothelial cells minimize transverse shear, supporting its postulated proatherogenic role. Preliminary data show that similar tracer techniques are practicable in vivo.NEW & NOTEWORTHY Solutes of increasing size crossed cultured endothelium through intercellular junctions, through tricellular junctions, or transcellularly. Cells aligned to minimize the shear stress acting across their long axis. Paracellular transport correlated with the level of this minimized shear, but transcellular transport was reduced uniformly by flow regardless of the shear profile.

Clustering of particles in turbulence due to phoresis.

We demonstrate that diffusiophoretic, thermophoretic, and chemotactic phenomena in turbulence lead to clustering of particles on multifractal sets that can be described using one single framework, valid when the particle size is much smaller than the smallest length scale of turbulence l_{0}. To quantify the clustering, we derive positive pair correlations and fractal dimensions that hold for scales smaller than l_{0}. For scales larger than l_{0} the pair-correlation function is predicted to show a stretched exponential decay towards 1. In the case of inhomogeneous turbulence we find that the fractal dimension depends on the direction of inhomogeneity. By performing experiments with particles in a turbulent gravity current we demonstrate clustering induced by salinity gradients in conformity to the theory. The particle size in the experiment is comparable to l_{0}, outside the strict validity region of the theory, suggesting that the theoretical predictions transfer to this practically relevant regime. This clustering mechanism may provide the key to the understanding of a multitude of processes such as formation of marine snow in the ocean and population dynamics of chemotactic bacteria.

Systematic investigation of non-Boussinesq effects in variable-density groundwater flow simulations.

The validity of three mathematical models describing variable-density groundwater flow is systematically evaluated: (i) a model which invokes the Oberbeck-Boussinesq approximation (OB approximation), (ii) a model of intermediate complexity (NOB1) and (iii) a model which solves the full set of equations (NOB2). The NOB1 and NOB2 descriptions have been added to the HydroGeoSphere (HGS) model, which originally contained an implementation of the OB description. We define the Boussinesq parameter ερ=ßω Δω where ßω is the solutal expansivity and Δω is the characteristic difference in solute mass fraction. The Boussinesq parameter ερ is used to systematically investigate three flow scenarios covering a range of free and mixed convection problems: 1) the low Rayleigh number Elder problem (Van Reeuwijk et al., 2009), 2) a convective fingering problem (Xie et al., 2011) and 3) a mixed convective problem (Schincariol et al., 1994). Results indicate that small density differences (ερ≤ 0.05) produce no apparent changes in the total solute mass in the system, plume penetration depth, center of mass and mass flux independent of the mathematical model used. Deviations between OB, NOB1 and NOB2 occur for large density differences (ερ>0.12), where lower description levels will underestimate the vertical plume position and overestimate mass flux. Based on the cases considered here, we suggest the following guidelines for saline convection: the OB approximation is valid for cases with ερ<0.05, and the full NOB set of equations needs to be used for cases with ερ>0.10. Whether NOB effects are important in the intermediate region differ from case to case.

Wind and boundary layers in Rayleigh-Bénard convection. I. Analysis and modeling.

The aim of this paper is to contribute to the understanding of and to model the processes controlling the amplitude of the wind of Rayleigh-Bénard convection. We analyze results from direct simulation of an L/H=4 aspect-ratio domain with periodic sidewalls at Ra=(10(5), 10(6), 10(7), 10(8)) and at Pr=1 by decomposing independent realizations into wind and fluctuations. It is shown that, deep inside the thermal boundary layer, horizontal heat fluxes exceed the average vertical heat flux by a factor of 3 due to the interaction between the wind and the mean temperature field. These large horizontal heat fluxes are responsible for spatial temperature differences that drive the wind by creating pressure gradients. The wall fluxes and turbulent mixing in the bulk provide damping. Using the direct numerical simulation results to parametrize the unclosed terms, a simple model capturing the essential processes governing the wind structure is derived. The model consists of two coupled differential equations for wind velocity and temperature amplitude. The equations indicate that the formation of a wind structure is inevitable due to the positive feedback resulting from the interaction between the wind and temperature field. Furthermore, the wind velocity is largely determined by the turbulence in the bulk rather than by the wall-shear stress. The model reproduces the Ra dependence of wind Reynolds number and temperature amplitude.

Wind and boundary layers in Rayleigh-Bénard convection. II. Boundary layer character and scaling.

The scaling of the kinematic boundary layer thickness lambda(u) and the friction factor C(f) at the top and bottom walls of Rayleigh-Bénard convection is studied by direct numerical simulation (DNS). By a detailed analysis of the friction factor, a new parameterisation for C(f) and lambda(u) is proposed. The simulations were made of an L/H=4 aspect-ratio domain with periodic lateral boundary conditions at Ra=(10(5), 10(6), 10(7), 10(8)) and Pr=1. The continuous spectrum, as well as significant forcing due to Reynolds stresses, clearly indicates a turbulent character of the boundary layer, while viscous effects cannot be neglected, judging from the scaling of classical integral boundary layer parameters with Reynolds number. Using a conceptual wind model, we find that the friction factor C(f) should scale proportionally to the thermal boundary layer thickness as C(f) proportional variant lambda(Theta)/H, while the kinetic boundary layer thickness lambda(u) scales inversely proportionally to the thermal boundary layer thickness and wind Reynolds number lambda(u)/H proportional variant (lambda(Theta)/H)(-1)Re(-1). The predicted trends for C(f) and lambda(u) are in agreement with DNS results.

Spectral analysis of boundary layers in Rayleigh-Bénard convection.

A combined experimental and numerical study of the boundary layer in a 4:1 aspect-ratio Rayleigh-Bénard cell over a four-decade range of Rayleigh numbers has been undertaken aimed at gaining a better insight into the character of the boundary layers. The experiments involved the simultaneous laser Doppler anemometry measurements of fluid velocity at two locations, i.e., in the boundary layer and far away from it in the bulk, for Rayleigh numbers varying between 1.6x10(7) and 2.4x10(9) . In parallel, direct numerical simulations have been performed for the same configuration for Rayleigh numbers between 7.0x10(4) and 7.7x10(7) . The temperature and velocity probability density functions and the power spectra of the horizontal velocity fluctuations measured in the boundary layer and in the bulk flow are found to be practically identical. Except for the smallest Rayleigh numbers, the spectra in the boundary layer and in the bulk central region are continuous and have a wide range of active scales. This indicates that both the bulk and the boundary layers are turbulent in the Ra number range considered. However, molecular effects can still be observed and the boundary layer does not behave like a classical shear-driven turbulent boundary layer.