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22 results for “Air Conditioning”
Count data of air-breathing fauna from visual transect surveys including water temperature, time, sea and weather conditions in Shark Bay Marine Park, Western Australia from February 2008 to July 2014
This dataset provides information on the relative abundances of air breathing fauna (dugongs, dolphins, sea snakes, marine birds, and sea turtles) in the study area of the Eastern Gulf of Shark Bay, Western Australia. The dataset comprises transects that quantify animal abundances in three microhabitats (shallow seagrass banks, seagrass bank edges, and deep sandy channels). These microhabitats vary in their food supply as well as their potential to facilitate or inhibit detection and escape from predators, mainly the tiger shark (Galeocerdo cuvier). As a result these data have been used to examine risk-specific habitat use behaviors of these fauna, in addition to general abundance estimates.
Challenges of high-fidelity air quality modeling in urban environments - PALM sensitivity study during stable conditions (TURBAN)
<h3>Introduction</h3> <p>This dataset contains the PALM model inputs and the source code used to create the simulations for Prague-Legerova scenarios performed in the scope of the <strong>TURBAN</strong> project (<a href="https://www.project-turban.eu/">https://www.project-turban.eu/</a>). Detailed description of the simulations is provided in the referencing scientific paper.</p> <h3>List of simulations</h3> <table> <tbody> <tr> <td><strong>Scenario name</strong></td> <td><strong>Days simulated</strong></td> <td><strong>IBC</strong></td> <td><strong>Configuration changes</strong></td> </tr> <tr> <td>legerovas_s6_sens_base</td> <td>13–15 February 2023</td> <td>ICON</td> <td>-</td> </tr> <tr> <td>legerovas_s6_sens_dtmax</td> <td>13 February 2023</td> <td>ICON</td> <td>dt_max=0.2</td> </tr> <tr> <td>legerovas_s6_sens_heat</td> <td>13 February 2023</td> <td>ICON</td> <td>car anthropogenic heat (custom code)</td> </tr> <tr> <td>legerovas_s6_sens_sgs</td> <td>13 February 2023</td> <td>ICON</td> <td>e_min=0.02</td> </tr> <tr> <td>legerovas_s6_sens_stg</td> <td>13 February 2023</td> <td>ICON</td> <td>STG_PROFILES added</td> </tr> <tr> <td>legerovas_s6_sens_alad</td> <td>13–15 February 2023</td> <td>ALADIN</td> <td>-</td> </tr> <tr> <td>legerovas_s6_sens_alad_heat</td> <td>13 February 2023</td> <td>ALADIN</td> <td>car anthropogenic heat (custom code)</td> </tr> <tr> <td>legerovas_s6_sens_alad_sgs</td> <td>13 February 2023</td> <td>ALADIN</td> <td>e_min=0.02</td> </tr> <tr> <td>legerovas_s6_sens_alad_stg</td> <td>13 February 2023</td> <td>ALADIN</td> <td>STG_PROFILES added</td> </tr> <tr> <td>legerovas_s6_sens_wrf</td> <td>13–15 February 2023</td> <td>WRF</td> <td>-</td> </tr> <tr> <td>legerovas_s6_sens_wrf_heat</td> <td>13 February 2023</td> <td>WRF</td> <td>car anthropogenic heat (custom code)</td> </tr> <tr> <td>legerovas_s6_sens_wrf_sgs</td> <td>13 February 2023</td> <td>WRF</td> <td>e_min=0.02</td> </tr> <tr> <td>legerovas_s6_sens_wrf_stg</td> <td>13 February 2023</td> <td>WRF</td> <td>STG_PROFILES added</td> </tr> </tbody> </table> <h3>Directory structure</h3> <p>The directory inputs contains the model inputs and it is further divided into these subdirectories:</p> <p>- inputs/common: The PALM static driver and the emission drivers for the parent and child domains. These files are common to all simulations</p> <p>- inputs/dynamic/*: These directories contain the dynamic drivers for the parent and child domanis, which contain the initial and boundary conditions (IBC) as well as external radiation data. The three subdirectories aladin, icon and wrf contain IBCs created from the respective mesoscale model outputs. </p> <p>- inputs/legerovas_s6_sens_*: These directories contain the PALM model configuration (p3d) for both domains for each simulation.</p> <p>- inputs/build_config: The included .palm.iofiles configuration file ensures that the files STG_PROFILES are correctly copied from the input directory.</p> <p>The directory palm_sources contains the exact model source used for the simulations. It is derived from the PALM model release 23.04 with additional bugfixes. There are two source archives:</p> <p>- heat.tar.gz: PALM source further modified to include anthropogenic heat from cars, used for the simulations legerovas_s6_sens_*_heat</p> <p>- standard.tar.gz: PALM source used for all other included simulations.</p> <h3>Reproducing the simulations</h3> <p>In order to reproduce the simulations, unpack the respective source code archive and follow the standard installation, configuration and build procedures described in the README.md file within the archive and on the PALM model website http://www.palm-model.org/. Then copy the input files for the respective simulation in the JOBS directory. The common files and the dynamic driver files need to be renamed so that they match the prefix given by the name of the simulation, as is described in the PALM model documentation.</p>
Global present-day air-conditioning adoption rate
<p>This dataset contains the present-day, global, survey-based, and spatially explicit air-conditioning adoption rate dataset developed in Li et al. (2024), “Enhancing Urban Climate-Energy Modeling in the Community Earth System Model (CESM) through Explicit Representation of Urban Air-conditioning Adoption”, published in <em>Journal of Advances in Modeling Earth Systems</em>. It also contains the simulation results analyzed in the article. Details about this dataset (data sources, data collection and processing methods, simulation setup, etc.) are described in the article. The air-conditioning adoption rate dataset is publicly available in tabular, vector, and gridded formats. It is compatible with CESM, and can also be leveraged in other climate and energy modeling applications and socioeconomic or integrated assessment analyses. This dataset may be useful for multiple scientific communities regarding urban climate and energy, impacts, vulnerability, risks, and adaptation applications. </p> <p>For more detailed description, please refer to the README file (<em>global_AC_adoption_rate_README.txt</em>) included in the dataset.</p>
Operating diagram of larvae hatching module, this installation was used to determine the optimum larvae load during the rearing process and provided additional space for rearing several thousand larvae. It consists of nine 20-litre tanks with a glass panel along the front. They are fitted with an inlet supplying filtrated water at a rate of 100 l/h and an individual air inlet. in Reproduction of Zingel asper (Linnaeus, 1758) in controlled conditions: an assessment of the experiences realized since 2005 at the Besançon Natural History Museum
Operating diagram of larvae hatching module, this installation was used to determine the optimum larvae load during the rearing process and provided additional space for rearing several thousand larvae. It consists of nine 20-litre tanks with a glass panel along the front. They are fitted with an inlet supplying filtrated water at a rate of 100 l/h and an individual air inlet.
Data for: Flexible emulation of the climate warming cooling feedback to globally assess the maladaptation implications of future air conditioning use
<p>This dataset contains the code and the data files needed to create the figures shown in the paper titled "Flexible emulation of the climate warming cooling feedback to globally assess the maladaptation implications of future air conditioning use".</p>
Urban Air Pollution and Child Neurodevelopmental Conditions: A Systematic Bibliometric Review
<p>The dataset for this research was compiled through an advanced PubMed search targeting publications from a one-year period, with keywords focused on air pollution, neurodevelopment, and associated disorders. From an initial pool of 450 publications, filtering based on the co-occurrence of relevant keywords reduced this to approximately 44 papers. The analysis was conducted using VOSviewer to generate a visual map of relationships between air pollution and child neurodevelopment. To ensure consistency, a thesaurus was applied to standardize terminology, refining the final network for a detailed examination of keyword clusters and their interactions. For those seeking to replicate this process, Appendix A provides an in-depth, step-by-step methodology for building the networks and utilizing the data files to recreate the visualizations.</p>
Bluestar air condition dealer in Trivandrum
<p><strong>We ‘Unique’ is an appliance store located in Trivandrum, Kerala with a variety of products from Blue Star, Aquaguard, Western. Etc. Blue Stars is a leading air conditioning company. And a commercial refrigeration company in India. We are the Best <a href="https://uniqueconnect.in/air-conditioner-unique-connect/">Bluestar air condition dealer in Trivandrum. </a>We provide you with attractive design and high-quality products. </strong></p>
Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions
<p>This repo includes the GEOS-Chem simulations and R scripts that are needed to replicate and evaluate the conclusions from Qiu, Zigler, and Selin, ACP, 2022 "Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions".</p> <p><strong>The GEOS-Chem simulations</strong></p> <ul> <li>For the US (2011-2017): <ul> <li><em>observational_o3_pm_2011_2017_us.rds:</em> the simulated daily PM2.5 and O3 concentrations, and MERRA-2 meteorological features in the observational scenarios (<strong>changing</strong> meteorology, <strong>changing </strong>emissions).</li> <li><em>counterfactual_o3_pm_2011_2017_us.rds</em><em>:</em> the simulated daily PM2.5 and O3 concentrations, and MERRA-2 meteorological features in the counterfactual scenarios (<strong>constant</strong> meteorology, <strong>changing</strong> emissions).</li> <li><em>constant_emis_o3_pm_2012_2017_us.rds: </em>the simulated daily PM2.5 and O3 concentrations in the constant-emission scenarios (<strong>constant</strong> meteorology, <strong>constant</strong> emissions).</li> <li><em>regional_features_2011_2017_4x5_us.rds: </em>the MERRA-2 meteorological features in the observational scenarios (aggregated to 4x5 degrees), inputs for the "RF-regional" model.</li> </ul> </li> <li>For China (2013-2017): <ul> <li><em>observational_o3_pm_2013_2017_china.rds:</em> the simulated daily PM2.5 and O3 concentrations, and MERRA-2 meteorological features in the observational scenarios (<strong>changing</strong> meteorology, <strong>changing </strong>emissions).</li> <li><em>counterfactual_o3_pm_2013_2017_china.rds:</em> the simulated daily PM2.5 and O3 concentrations, and MERRA-2 meteorological features in the counterfactual scenarios (<strong>constant</strong> meteorology, <strong>changing</strong> emissions).</li> <li><em>constant_emis_o3_pm_2014_2017_china.rds</em><em>: </em>the simulated daily PM2.5 and O3 concentrations in the constant-emission scenarios (<strong>constant</strong> meteorology, <strong>constant</strong> emissions).</li> <li><em>regional_features_2013_2017_4x5_china.rds: </em>the MERRA-2 meteorological features in the observational scenarios (aggregated to 4x5 degrees), inputs for the "RF-regional" model.</li> </ul> </li> </ul> <p><strong>R scripts:</strong></p> <ul> <li><a href="https://zenodo.org/api/files/065be469-ef8d-4c9b-9bd8-a6a808275237/main.r">main.r</a>: the main script to perform statistical correction of meteorological variability.</li> <li>main.r uses functions from the other R script files (see below) which perform different statistical correction methods, respectively. </li> <li><a href="https://zenodo.org/api/files/065be469-ef8d-4c9b-9bd8-a6a808275237/parametric_regression_methods.r">parametric_regression_methods.r</a>: performs meteorological correction with parametric regression methods (MLR, polynomial, spline, GAM)</li> <li><a href="https://zenodo.org/api/files/065be469-ef8d-4c9b-9bd8-a6a808275237/tune_RF_regional.r">tune_RF_regional.r</a> and <a href="https://zenodo.org/api/files/065be469-ef8d-4c9b-9bd8-a6a808275237/RF_regional.r">RF_regional.r</a>: perform the meteorological correction with the "RF-regional" model</li> <li><a href="https://zenodo.org/api/files/065be469-ef8d-4c9b-9bd8-a6a808275237/GEOS_Chem_constant_emis.r">GEOS_Chem_constant_emis.r</a>: performs the meteorological correction using the simulations from the constant emission scenarios from the GEOS-Chem model</li> </ul> <p> </p>
Dataset associated to paper: Nanoscaffold effects on the performance of air-cathodes for microbial fuel cells: Sustainable Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions
<p>This file contains the dataset associated to the published research article "Nanoscaffold effects on air-cathode performance in microbial fuel cells: Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions". The dataset contains X-ray powder diffraction, Inductively Coupled Plasma Emission Spectroscopy, elemental analysis, measurements of the specific surface area, transmission electron microscopies, x-ray photoelectron microscopy, electrochemistry and microbial fuel cells power outputs data from their relative instruments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 799175 (HiBriCarbon) and No. 748968 (EDGE-FREEMAB). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains. This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213 and 19/FFP/6761. SI kindly acknowledges support by the Department of Social Justice State Government of Maharashtra, India. </p>
Cool birds: facultative use by an introduced species of mechanical air conditioning systems during extremely hot outdoor conditions
Open the record for dataset details and reuse information.
Household accessibility to heat refuges: Residential air conditioning, public cooled space, and walkability
Access to air conditioned space has been identified as a critical protective element that can mitigate the adverse health effects of heat waves. However, there is limited knowledge of where this resource exists in cities. While many cities have deployed networks of sponsored cooling centers their location is likely to be inadequately informed with respect to the location of existing resources. This study explores the distribution of in-home air-conditioning and household access to public cooling resources in Maricopa County, AZ. There are significant variations in the distribution of private and public air conditioned space and there are areas where access to these spaces is limited which could increase health risks during periods of extreme heat.
The dataset of the manuscript "Numerical study of the initial condition and emission on simulating PM2.5 concentrations in Comprehensive Air Quality Model with extensions version 6.1 (CAMx v6.1): Taking Xi'an as example"
<ul> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/bcfile.rar?versionId=4909d094-5877-408e-bd4f-0c969c54e585">bcfile.rar</a>: the clean initial and boundary condition files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/Emis_forNov.rar?versionId=0a1e8b66-5157-4819-8c03-20fb7797d8ef">Emis_forNov.rar</a> and <a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/Emis_forDec.rar?versionId=d4db00f1-ec1b-4096-973e-6a87133e4eac">Emis_forDec.rar</a>: the emission files in November and December 2016.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/tuvfile.rar?versionId=5dcf0977-e416-466e-9089-bbf0726c788d">tuvfile.rar</a> and <a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/o3mapfile.rar?versionId=9c25cae9-f00e-4ad3-b4dc-7a721f7f44d7">o3mapfile.rar</a>: the photolysis files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.cp1.rar?versionId=09ded31b-4c42-4e40-a21c-0f18877e9e41">camx.cp[1-5].rar</a>: the results of sensitivity experiments for using clean initial condition files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.r1120p1.rar?versionId=45d6e209-8e66-43ed-bc0b-dc8af5521352">camx.r1120p[1-3].rar</a>: the results of sensitivity experiments for R1120.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.r1124.rar?versionId=c138e436-0416-4701-948d-ce761cf6c5cf">camx.r1124.rar</a>: the results of sensitivity experiments for R1124.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/contnuous_B12.rar?versionId=34485c43-77ac-4001-8a6d-a57b7ff821e3">contnuous_B12.rar</a>: the results of sensitivity experiments for CT12.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/contnuous_B24.rar?versionId=0f325a61-f19c-4bac-b8b4-7e229c332bf9">contnuous_B24.rar</a>: the results of sensitivity experiments for CT24.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/scripts.zip?versionId=b030444c-51a5-4673-b9d1-7e80ec42a3b9">scripts.zip</a>: all scripts covering every data processing action for all the results reported in the paper.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/data.zip?versionId=52917a53-fca7-4a72-ba2f-a2ce7593adc4">data.zip</a>: final data tables used to plot figures and tables.</li> </ul>
DatabaseNH3 : EOM ammonia emission factor measured with INRAE Caract'Air device (under controlled conditions)
<p>This dataset includes ammonia volatilization measurements led by ECOSYS INRAE with Caract’Air device. Ammonia measurements, based on the principle of a mass balance in dynamic chambers are performed under thoroughly controlled and replicative conditions. Caract’Air was designed to be as close as possible to field conditions (in situ soil cores) while optimizing ambient conditions (temperature, air humidity and soil water content) and exchange conditions (flow rate, head volume, air circulation conditions) (Génermont et al., 2021; Décuq et al., 2023). A variety of EOMs are represented ranging from historic livestock effluents and manure to emerging biowastes produced by human urban and agro-industrial activities, all these biowastes having undergone a variety of treatments: raw, separated, composted, anaerobically stored slurries, farm yard manure, sewage sludges, municipal and domestic wastes; various digestats from mechanization; urine based fertilizers; etc. The types and origins of the EOM are reported. The physico-chemical properties of the EOM as well as soils on which the EOM were applied are detailed, leading to 20 and 30 parameters accompanied by information on analytical methods. Measurement conditions are also described including the application dose, the experimental set duration, the ambient conditions, and also the reproductibily conditions, etc. Finally, ammonia volatilization data are compiled, in terms of total cumulative loss (kg N/ha) or volatilization rates (% N and % N-NH4 applied).</p>
Facial Features of Air Gun Array Wavelets in the Time-Frequency Domain under Practical Conditions
<p>The data in folder (a) include mass of air in the bubble, variation in the temperature of the gas inside the bubble, bubble radius, bubble wall velocity, notional signature and far-field signature simulated by Van der Waals air-gun model. The actual data in folder (b) are the far-field wavelets at different locations measured by China Ocean University on the northern slope of the South China Sea in April 2017. The simulated data are the far-field wavelets corresponding to the actual locations simulated by Van der Waals air-gun model. The data in the folder (c) includes simulated three dimensional acoustic field and facial evaluation data for long array, square array, simultaneously fired vertical array, and time-delayed vertical array.</p>
PLEIAData:consumption, HVAC (Heating, Ventilation & Air Conditioning), temperature, weather and motion sensor data for smart buildings applications
<p>This dataset presents detailed building operation data from the three blocks (A, B and C) of the Pleiades building of the University of Murcia, which is a pilot building of the European project PHOENIX. The aim of PHOENIX is to improve buildings efficiency, and therefore we included information of:<br> (i) consumption data, aggregated by block in kWh; (ii) HVAC (Heating, Ventilation and Air Conditioning) data with several features, such as state (ON=1, OFF=0), operation mode (None=0, Heating=1, Cooling=2), setpoint and device type; (iii) indoor temperature per room; (iv) weather data, including temperature, humidity, radiation, dew point, wind direction and precipitation; (v) carbon dioxide and presence data for few rooms; (vi) relationships between HVAC, temperature, carbon dioxide and presence sensors identifiers with their respective rooms and blocks. Weather data was acquired from the IMIDA (Instituto Murciano de Investigación y Desarrollo Agrario y Alimentario).</p>
AIR-program and HUS Internet Therapy Compared to Treatment as Usual in Functional Disorders and Post Covid-19 Condition
ClinicalTrials.gov study NCT05212467. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Ligand-Free Pd-Catalyzed Direct C-H Arylation of Aryl Iodides under Ambient Air Conditions
Open the record for dataset details and reuse information.
Dataset associated to: Nanoscaffold effects on the performance of air-cathodes for microbial fuel cells: Sustainable Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions
<p>This file contains the dataset associated to the published research article "Nanoscaffold effects on air-cathode performance in microbial fuel cells: Fe/N-carbon electrocatalysts for the oxygen reduction reaction under neutral pH conditions". The dataset contains X-ray powder diffraction, Inductively Coupled Plasma Emission Spectroscopy, elemental analysis, measurements of the specific surface area, transmission electron microscopies, x-ray photoelectron microscopy, electrochemistry and microbial fuel cells power outputs data from their relative instruments. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No. 799175 (HiBriCarbon) and No. 748968 (EDGE-FREEMAB). The results of this publication reflect only the authors' view and the Commission is not responsible for any use that may be made of the information it contains. This publication has also emanated from research conducted with the financial support of Science Foundation Ireland under Grant No. 13/CDA/2213 and 19/FFP/6761. SI kindly acknowledges support by the Department of Social Justice State Government of Maharashtra, India. </p>
Ischemic Conditioning During Air tRansport Save penUmbral Tissue
ClinicalTrials.gov study NCT03481205. IPD Sharing: NO. Countries: 1. Publications: 0.
RNA-seq analysis identifies the effect of PM2.5 on human nasal epithelial cells cultured under air-liquid interface (ALI) conditions until differentiated.
GEO Series GSE243618. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.