Points for Energy Renovation (PointER): A LiDAR-Derived Point Cloud Dataset of One Million English Buildings Linked to Energy Characteristics

Rapid renovation of Europe's inefficient buildings is required to reduce climate change. However, analyzing and evaluating buildings at scale is challenging because every building is unique. In current practice, the energy performance of buildings is assessed during on-site visits, which are slow, costly, and local. This paper presents a building point cloud dataset that promotes a data-driven, large-scale understanding of the 3D representation of buildings and their energy characteristics. We generate building point clouds by intersecting building footprints with geo-referenced LiDAR data and link them with attributes from UK's energy performance database via the Unique Property Reference Number (UPRN). To achieve a representative sample, we select one million buildings from a range of rural and urban regions across England, of which half a million are linked to energy characteristics. Building point clouds in new regions can be generated with the open-source code published alongside the paper. The dataset enables novel research in building energy modeling and can be easily expanded to other research fields by adding building features via the UPRN or geo-location.Comment: The PointER dataset can be downloaded from https://doi.org/10.14459/2023mp1713501. The code used for generating building point clouds is available at https://github.com/kdmayer/PointE

Exploration of Optimal Powertrain Design Using Realistic Load Profiles

The electrification of bus-based public transportation contributes to the goal of reducing the adverse environmental impacts caused by urban transportation. However, the penetration of electric vehicles has been slow due to their lower vehicle range and total costs in comparison to vehicles driven by internal combustion engines. By improving the powertrain efficiency, the total costs can be reduced for the same vehicle range. Therefore, this paper proposes a holistic design exploration approach to investigate and identify the optimal powertrain concept for electric city buses based on the component costs and energy consumption costs. The load profiles of speed, slope, and passenger occupancy profiles are derived for a selected bus route in Singapore, which is used in a powertrain design exploration for a 30-passenger vehicle. Six different powertrain architectures are analyzed, together with single and multi-speed gearbox configurations, to identify the optimal powertrain architecture and the resulting component sizes. The powertrain configurations are further analyzed in terms of their influence on the vehicle characteristics and total costs. Multi-motor configurations were found to have better vehicle characteristics and lower total costs in comparison to single rear motor configurations. Concepts with motors on the front and a rear axle could shift the load points to a higher efficiency region, resulting in lower energy consumption and energy costs. The optimal powertrain concept was a fixed-speed two-motor configuration, with a booster motor on the front axle and a motor on the rear axle. Document type: Articl

Phosphate decreases urine calcium and increases calcium balance: A meta-analysis of the osteoporosis acid-ash diet hypothesis

<p>Abstract</p> <p>Background</p> <p>The acid-ash hypothesis posits that increased excretion of "acidic" ions derived from the diet, such as phosphate, contributes to net acidic ion excretion, urine calcium excretion, demineralization of bone, and osteoporosis. The public is advised by various media to follow an alkaline diet to lower their acidic ion intakes. The objectives of this meta-analysis were to quantify the contribution of phosphate to bone loss in healthy adult subjects; specifically, a) to assess the effect of supplemental dietary phosphate on urine calcium, calcium balance, and markers of bone metabolism; and to assess whether these affects are altered by the b) level of calcium intake, c) the degree of protonation of the phosphate.</p> <p>Methods</p> <p>Literature was identified through computerized searches regarding phosphate with surrogate and/or direct markers of bone health, and was assessed for methodological quality. Multiple linear regression analyses, weighted for sample size, were used to combine the study results. Tests of interaction included stratification by calcium intake and degree of protonation of the phosphate supplement.</p> <p>Results</p> <p>Twelve studies including 30 intervention arms manipulated 269 subjects' phosphate intakes. Three studies reported net acid excretion. All of the meta-analyses demonstrated significant decreases in urine calcium excretion in response to phosphate supplements whether the calcium intake was high or low, regardless of the degree of protonation of the phosphate supplement. None of the meta-analyses revealed lower calcium balance in response to increased phosphate intakes, whether the calcium intake was high or low, or the composition of the phosphate supplement.</p> <p>Conclusion</p> <p>All of the findings from this meta-analysis were contrary to the acid ash hypothesis. Higher phosphate intakes were associated with decreased urine calcium and increased calcium retention. This meta-analysis did not find evidence that phosphate intake contributes to demineralization of bone or to bone calcium excretion in the urine. Dietary advice that dairy products, meats, and grains are detrimental to bone health due to "acidic" phosphate content needs reassessment. There is no evidence that higher phosphate intakes are detrimental to bone health.</p

Reduced anthropogenic aerosol radiative forcing caused by biogenic new particle formation

The magnitude of aerosol radiative forcing caused by anthropogenic emissions depends on the baseline state of the atmosphere under pristine preindustrial conditions. Measurements show that particle formation in atmospheric conditions can occur solely from biogenic vapors. Here, we evaluate the potential effect of this source of particles on preindustrial cloud condensation nuclei (CCN) concentrations and aerosol-cloud radiative forcing over the industrial period. Model simulations show that the pure biogenic particle formation mechanism has a much larger relative effect on CCN concentrations in the preindustrial atmosphere than in the present atmosphere because of the lower aerosol concentrations. Consequently, preindustrial cloud albedo is increased more than under present day conditions, and therefore the cooling forcing of anthropogenic aerosols is reduced. The mechanism increases CCN concentrations by 20-100% over a large fraction of the preindustrial lower atmosphere, and the magnitude of annual global mean radiative forcing caused by changes of cloud albedo since 1750 is reduced by 0.22 W m-2 (27%) to -0.60 W m-2. Model uncertainties, relatively slow formation rates, and limited available ambient measurements make it difficult to establish the significance of a mechanism that has its dominant effect under preindustrial conditions. Our simulations predict more particle formation in the Amazon than is observed. However, the first observation of pure organic nucleation has now been reported for the free troposphere. Given the potentially significant effect on anthropogenic forcing, effort should be made to better understand such naturally driven aerosol processes

RID&mdash;Roof Information Dataset for Computer Vision-Based Photovoltaic Potential Assessment

Computer vision has great potential to accelerate the global scale of photovoltaic potential analysis by extracting detailed roof information from high-resolution aerial images, but the lack of existing deep learning datasets is a major barrier. Therefore, we present the Roof Information Dataset for semantic segmentation of roof segments and roof superstructures. We assessed the label quality of initial roof superstructure annotations by conducting an annotation experiment and identified annotator agreements of 0.15&ndash;0.70 mean intersection over union, depending on the class. We discuss associated the implications on the training and evaluation of two convolutional neural networks and found that the quality of the prediction behaved similarly to the annotator agreement for most classes. The class photovoltaic module was predicted to be best with a class-specific mean intersection over union of 0.69. By providing the datasets in initial and reviewed versions, we promote a data-centric approach for the semantic segmentation of roof information. Finally, we conducted a photovoltaic potential analysis case study and demonstrated the high impact of roof superstructures as well as the viability of the computer vision approach to increase accuracy. While this paper&rsquo;s primary use case was roof information extraction for photovoltaic potential analysis, its implications can be transferred to other computer vision applications in remote sensing and beyond

Improving electric city bus powertrain efficiency and costs using design space exploration

The electrification of the bus-based public transportation contributes to the goal of reducing the environmental impact caused by mobility in urban areas. This paper proposes a holistic design exploration approach to investigate and identify the optimal powertrain concept for electric city buses based on the total costs – energy consumption and component costs. A 30-passenger vehicle with a pre-defined driving cycle is investigated to identify the optimal electric powertrain architecture and the resulting component sizes and type. The most cost-effective concept was found to be one with a four-wheel drive configuration with a PMSM motor and a fixed gear transmission on each axle with a power distribution of 22% at the front axle and 78% at the rear axle

Placing BEV Charging Infrastructure: Influencing Factors, Metrics, and Their Influence on Observed Charger Utilization

The automotive sector&rsquo;s transition to Battery Electric Vehicles (BEVs) requires extensive deployment of additional charging infrastructure. To determine optimal new locations, planners consider and rate a multitude of factors that influence the charging demand at candidate sites. Researchers have proposed a variety of placement criteria and methods to automate site selection. However, no common set of criteria has emerged. In addition, due to the lack of usage data, the applicability of existing criteria remains unclear. Therefore, the goals of this article are to extract the most relevant factors from literature and to evaluate their ability to characterize charging point usage. First, we review the literature base to collect, analyze, and cluster existing influencing factors and to analyze how they affect charging demand. Second, we conduct a case study using real-life charging station data from Hamburg, Germany. Based on the extracted influencing factors, we identify four clusters within Hamburg&rsquo;s public charging infrastructure. While the mean performance indicators duration, daily transactions, and connection ratio hardly differ among these clusters, the temporal occupancy curves clearly show distinct charging behavior for each cluster. This work contributes to the state of the art by structuring the diverse landscape of charging station location placement criteria, by deriving a set of measurable influencing factors, and by analyzing their effect on a location&rsquo;s charging demand, yielding an open source data set of charging point usage

Charge transfer through the nucleosome: A theoretical approach

In this work, we approach the problem of charge transfer in deoxyribonucleic acid (DNA) from a theoretical and numerical perspective. We focus on a DNA geometry characteristic of the eukaryotic genome and study transport along a superhelix that contains 292 nucleobases. The electronic structure is described within the Su-Schrieffer-Heeger model in an atomistic parameterization, which has been extended by a nonretarded reaction field to take dielectric polarization effects into account. The emerging potential energy surface is analyzed using the Marcus theory of electron transfer. The computed reaction coefficients are compared to their counterparts originating from idealized geometries and to experimental findings. This comparison and the palindromic nature of the DNA sequence used here permit the assessment of fluctuations in the local orientation of the bases and their impact upon transport properties