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Climate Change Group 6 - Energy
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Zhang, Nicole; Johnstone, Graham; Coppens, Jarod ; Kawamoto, Cory — 2017-12-09 This is the data from group 6, with a focus on energy in climate change. This dataset contains our excel worksheets, research notebook, podcast file, presentation slides, and final deliverable.
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Elements and omega-3 fatty acids in fishes along a large, dammed river
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Kidd, Karen A. — 2023-08-18 This dataset is used to support the paper submitted to Environmental Pollution titled "Elements and essential fatty acids in fishes along a large, dammed river". The dataset includes levels of Hg, 30 other trace elements, stable isotopes of carbon and nitrogen, and the fatty acids EPA and DHA in four fish species collected from four sites on the Wolastoq | Saint John River (New Brunswick, Canada) that were selected in relation to the Mactaquac Generating Station. It also includes physical characteristics of the fish including length, weight, age, sex and percent moisture.
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T3010 Canadian Charity Returns Version 2
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SEAL Lab, McMaster — 2019-09-16 T3010 Canadian Charities Returns. Includes information about charities and public/private foundations, financial information, trustees and financial transactions between non-profits. The Data Dictionary provides information about variables and other supporting information. A README file explains how to get access to the restricted files which contain the actual data in CSV and Stata formats.
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Contraction and distension during stripes
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Parsons, Sean — 2019-10-11 Left, simultaneous video from two cameras of the same small intestine, corresponding to the two boxed sections of the DMap in Figure 5. Right, corresponding DMaps: the moving green line indicates the temporal position in the video. Vertical green scale bars are 1 cm and horizontal green scale bar is 5 s. During a stripe contracting portions of the intestine force fluid into non-contracting portions, causing them to distend. Upper (proximal) video: dark-light (DL) banded stripes correspond to active contraction followed by distension. Notice the v-wave mid-way through the video. Lower (distal) video: light-dark (LD) banded stripes result purely from passive movement of luminal fluid. The proximal, actively contracting segment forces fluid down into the distal segment, so distending it and creating a light band. As the proximal segment then relaxes, the distal fluid reverses course as it is sucked upward and this suction creates a dark band that follows the light. The downward, then upward movement of fluid with each stripe can be tracked by shed mucosa (moving white material) in the lumen. [CD-1, Trendelenburg, 80 M carbenoxolone].
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Two-chain FHN model
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Parsons, Sean — 2019-11-04 The MATLAB code for the two-chain Fitzhugh-Nagumo oscillator model. The main file to run is FHN_2Layer_run.m
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Regular contractions over a period of two hours.
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Parsons, Sean — 2019-11-18 Near-consecutive DMaps of a small intestine (start times indicated at left) over a period of almost two hours. Note that at 10:46 (the start of the first map) the intestine had already been over 40 minutes in the organ bath and 1.5 hours had elapsed since it was removed from the mouse. The tone of the intestine decreases a little, but regular slow-wave driven contractions continue unabated. [CD-1 mouse; 0.5 mM lidocaine; luminal perfusion].
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Turkey Point Flux Station 1989 Forest (TP2)
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Arain, M. Altaf — 2014-08-21 <p>The ON-TP89 site, also known as the CA-TP2 on Global Fluxnet and ON-WPP89 in some of the Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) publications.</p> <p>ON-TP89 is a young planted white pine (Pinus strobusL.) forest of the Turkey Point Flux Station. It was planted in 1989 (ON-TP89) on a former agricultural land. Meteorological and flux data collection was started in summer 1989. The data documented here includes carbon, water and energy fluxes and meteorological and soil measurements. </p> <p>A unique aspect of Turkey Point Flux Station is its geographic location between the boreal and the broadleaf deciduous forest transition zone. It provides an excellent opportunity to investigate and quantify the strength of the carbon sink or source for planted temperate conifer forests, and its sensitivity to seasonal and annual climate variability. Also white pine is an important species in the North American landscape, because of its ability to adapt to dry enviro nments. It grows efficiently on nutrient poor, dry, sandy soils. Generally, it is the first woody species to flourish after a disturbance such as fire or clearing and over longer time periods helps more native forest species to establish through succession. White pine trees can live for about 350–400 years and their height may reach up to 45–60 m. These characteristics make white pine a preferred plantation (afforestation) species in eastern North America. </p> <p>Fluxes, meteorological and soil measurement conducted at this site help us to explore carbon sequestration potential of chronosequence of planted or afforested white pine stands in southern Ontario. The main objectives are (i) to make year-round measurements of energy, water vapour and carbon dioxide (CO2) fluxes and other meteorological variables over mature, middle-aged, young and seedling white pine plantation forests (established in 1939, 1974, 1989 and 2002) (ii) to relate gross ph otosynthesis and respiration of this stand to environmental factors (iii) determine the effects of seasonal and inter-annual climate variability on net ecosystem productivity, and to better understand the processes of production, storage and transport of soil CO2 and (iv) use these data to further improve process-based photosynthesis and respiration models. </p>
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Turkey Point Flux Station 1974 Forest (TP3)
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Arain, M. Altaf — 2014-08-21 <p>The ON-TP74 site, also known as the CA-TP3 on Global Fluxnet and ON-WPP74 in some of the Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) publications.</p> <p>ON-TP74 is the middle-age eastern white pine (Pinus strobusL.) forest of the Turkey Point Flux Station. It was planted in 1974 (ON-TP74) on cleared oak-savannah land. Meteorological and flux data collection was started in summer 2003. The data set documented here includes carbon, water and energy fluxes and meteorol ogical and soil measurements. </p> <p>A unique aspect of Turkey Point Flux Station is its geographic location between the boreal and the broadleaf deciduous forest transition zone. It provides an excellent opportunity to investigate and quantify the strength of the carbon sink or source for planted temperate conifer forests, and its sensitivity to seasonal and annual climate variability. Also white pine is an important species in the North American landscape, because of its ability to adapt to dry environments. It grows efficiently on nutrient poor, dry, sandy soils. Generally, it is the first woody species to flourish after a disturbance such as fire or clearing and over longer time periods helps more native forest species to establish through succession. White pine trees can live for about 350–400 years and their height may reach up to 45–60 m. These characteristics make white pine a preferred plantation (afforestation) species in eastern North America. </p> <p>Fluxes, meteorological and soil measurement conducted at this site help us to explore carbon sequestration potential of chronosequence of planted or afforested white pine stands in southern Ontario. The main objectives are (i) to make year-round measurements of energy, water vapour and carbon dioxide (CO2) fluxes and other meteorological variables over mature, middle-aged, young and seedling white pine plantation forests (established in 1939, 1974, 1989 and 2002) (ii) to relate gross ph otosynthesis and respiration of this stand to environmental factors (iii) determine the effects of seasonal and inter-annual climate variability on net ecosystem productivity, and to better understand the pro cesses of production, storage and transport of soil CO2 and (iv) use these data to further improve process-based photosynthesis and respiration models. </p>
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Turkey Point Flux Station 2002 Forest (TP1)
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Arain, M. Altaf — 2014-08-21 <p>The ON-TP02 site, also known as the CA-TP1 on Global Fluxnet and ON-WPP02 in some of the Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) publications.</p> <p>ON-TP02 is a recently planted white pine (Pinus strobusL.) forest of the Turkey Point Flux Station. It was planted in 2002 (ON-TP02) on a former agricultural land. Meteorological and flux data collection was started in summer 2002. The data set documented here includes carbon, water and energy fluxes and meteorologi cal and soil measurements. </p> <p>A unique aspect of Turkey Point Flux Station is its geographic location between the boreal and the broadleaf deciduous forest transition zone. It provides an excellent opportunity to investigate and quantify the strength of the carbon sink or source for planted temperate conifer forests, and its sensitivity to seasonal and annual climate variability. Also white pine is an important species in the North American landscape, because of its ability to adapt to dry environments. It grows efficiently on nutrient poor, dry, sandy soils. Generally, it is the first woody species to flourish after a disturbance such as fire or clearing and over longer time periods helps more native forest species to establish through succession. White pine trees can live for about 350–400 years and their height may reach up to 45–60 m. These characteristics make white pine a preferred plantation (afforestation) species in eastern North America. </p> <p>Fluxes, meteorological and soil measurement conducted at this site help us to explore carbon sequestration potential of chronosequence of planted or afforested white pine stands in southern Ontario. The main objectives are (i) to make year-round measurements of energy, water vapour and carbon dioxide (CO2) fluxes and other meteorological variables over mature, middle-aged, young and seedling white pine plantation forests (established in 1939, 1974, 1989 and 2002) (ii) to relate gross ph otosynthesis and respiration of this stand to environmental factors (iii) determine the effects of seasonal and inter-annual climate variability on net ecosystem productivity, and to better understand the processes of production, storage and transport of soil CO2 and (iv) use these data to further improve process-based photosynthesis and respiration models. </p> <p>More information about the site and associated data can be found in the metadata documentation.</p>
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McMaster Weather Station (MUWS) Data
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Jason Brodeur — 2014-01-24 Introduction McMaster Weather Station is operated by the Hydrometeorology and Climatology Lab in the School of Geography and Earth Sciences, McMaster University, Hamilton, Ontario, Canada. It is being supervised by Dr. Altaf Arain, Professor in the School. The primary purpose of this weather station is to support undergraduate and graduate teaching and serve the campus and surrounding community in west Hamilton. The station was established in October 2007 and a number of meteorological variables are being measured. Those using data are encouraged to check sensor details. Note: A large open space free of surrounding obstacles was not available at McMaster University campus to install this weather station. General Science Building roof top was the most appropriate location, available. ================================================================ * Station location: McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada. Latitude: 43°15' 42.93" N Longitude: 79° 55' 11.86" W Ground elevation: 90 m above sea level Roof surface elevation: 114 m above sea level ================================================================ * Sensor descriptions and heights: 1. Wind sensor at 7m above the roof surface - Wind speed and wind direction are measured using R.M. Young Wind Monitor, model 05103. The wind speed sensor is a helicoid-shaped, four-blade propeller-type, anemometer, with fuselage and tail wind vane. (http://ww w.campbellsci.com/05103-l) 2. Radiation sensor at 2m above the roof surface - Measured using four-sensor net radiometer, manufactured by the Kipp and Zonen, model CNR1. The radiometer measures the energy balance between incoming short-wave (CM3 sensor) and long-wave (CG3 sensor) radiation versus surface reflected shortwave and outgoing longwave radiation. The CNR1 also includes a sensor to measure the radiometer's internal temperature and a heater that is used to prevent condensation. ( http://www.kippzonen.com/Product/33/CNR-1) 3. Air temperature and humidity sensors at 2 m above the roof surface - Air temperature and relative humidity are measured using Vaisala RH and Temperature Probe, model HMP45C. Probe is covered with a radiation shield. The probe uses a capacitive polymer H chip to measure RH and a PRT to measure temperature. (http://www.campbellsci.com/hmp45c-l) 4. Barometer at 1.5 m above the roof surface - Atmospheric pressure is measured by R.M. Young Baro metric Pressure Sensor, model 61205. 5. Rain gauge at 1 m above the roof surface - Precipitation is measured by a R.M. Young Tipping Bucket Rain Gauge, model 52202, which meets the specifications of the World Meteorological Organization (WMO). It is heated for operation in cold temperatures. (http://www.campbellsci.ca/52202) Data File Description: - Data are available as comma-separated, ASCII-encoded files, produced separately for each year. Three files are created for each year, wh ich reflect the time step of measurements: 1. 15-minute files (e.g. MCM_WX_Met_Stn_Met2_2010.csv) are time series of variables, calculated by the data logging software as the average (or sum) value for all 5-second sample measurements within that period. The values reported represent the mean for the preceding 15 minutes. 2*. Hourly files (e.g. MCM_WX_Met_Stn_Met2_2010_Hourly.csv) are aggregated at hourly time steps from the 15-minute files. 3*. Daily files (e.g. MCM_WX_Met_Stn_Met2_2010_ Daily.csv) are aggregated at daily time steps from the 15-minute files. * Note that some variables (e.g. Albedo) are not well-represented by the hourly and daily aggregation. Therefore, it is recommended for the 15-minute files to be used as the bases for further analyses ================================================================ * Descriptions of Variables Year (EST) JulianDay (EST) - Day of year (1-365 or 366) End_Time (HrMn_EST) -ending Hour and Minute of samples used to make average Month (EST) Day (EST) CM3_DownSW_Avg (W/m2) - Mean dow n-welling shortwave radiation CM3_DownSW_Max (W/m2) - Maximum down-welling shortwave radiation CM3_DownSW_Min (W/m2) - Minimum down-welling shortwave radiation CM3_UpSW_Avg (W/m2) - Mean up-welling shortwave radiation CM3_UpSW_Max (W/m2) - Maximum up-welling shortwave radiation CM3_UpSW_Min (W/m2) - Minimum up-welling shortwave radiation CNR1_DownLW_Avg (W/m2) - Mean down-welling longwave radiation CNR1_UpLW_Avg (W/m2) - Mean up-welling longwave radiation CNR1_Temp_Avg (degC) - M ean CNR1 correction temperature (not air temperature) CNR1_NetRad_SW_Avg (W/m2) - Mean net shortwave radiation CNR1_NetRad_LW_Avg (W/m2) - Mean net longwave radiation Albedo_Avg (n/a) - Mean albedo CNR1_DownSW_Avg (W/m2) - Mean down-welling shortwave radiation CNR1_UpSW_Avg (W/m2) - Mean up-welling shortwave radiation CNR1_NetRad_Avg (W/m2) - Mean net radiation PanelTemp_Avg (degC) - Mean datalogger panel temperature (not air temperature) HMP45C_AirTemp_Avg (degC) - Mean air te mperature HMP45C_AirTemp_Max (degC) - Maximum air temperature HMP45C_AirTemp_Min (degC) - Minimum air temperature WindChill_Avg (degC) - Mean wind chill temperature HMP45C_RelHum_Avg (%) - Mean relative humidity HMP45C_RelHum_Max (%) - Maximum relative humidity HMP45C_RelHum_Min (%) - Minimum relative humidity DewPoint_Avg (degC) - Mean Dewpoint temperature VapPres_Avg (kPa) - Mean vapour pressure SatVapPres_Avg (kPa) - Mean saturation vapour pressure Humidex_Avg (degC ) - Mean humidex WindSpd_m/s_Avg (m/s) - Mean wind speed WindDir_Avg (deg) - Mean wind direction WindDir_Std_Avg (deg) - Mean wind direction WindSpd_k/h_Avg (k/h) - Mean wind speed WindDir2_Avg (deg) - Mean wind direction WindDir_Std2_Avg (deg) - Mean wind direction WindSpd_k/h_Max (k/h) - Maximum wind speed WindDir_WindSpd_Max (deg) - Wind direction at maximum wind speed WindSpd_k/h_Min (k/h) - Minimum wind speed WindDir_WindSpd_Min (deg) - Wind direction at mini mum wind speed Pressure_Raw_Avg (kPa) - Mean barometric pressure (uncorrected) Pressure (kPa) - Mean barometric pressure (corrected) Pressure_Max (kPa) - Maximum barometric pressure Pressure_Min (kPa) - Minimum barometric pressure Precipitation_Sum (mm) - Summed precipitation CertificationCode (n/a) - RevisionDate (YYYYMMDD) - Last date of update
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Immune Biomarkers Predictive of Respiratory Viral Infection in Elderly Nursing Home Residents
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Johnstone, Jennie — 2014-08-18 These data helped to determine whether immune phenotypes associated with immunosenescence predicted risk of respiratory viral infection in elderly nursing home residents. To this end, peripheral blood mononuclear cells (PBMCs) were obtained and analysed by flow cytometry for T-regs, CD4+ and CD8+ T-cell subsets (naive [CCR7+CD45RA+], terminally differentiated [CCR7-CD45RA+] and senescent [CD28-CD57+]) and CMV-reactive CD4+ and CD8+ T-cells. We hypothesized that the following immune phenotypes associated with immunosenescence would be associated with increased risk of infection: low CD4+ and CD8+ naïve T-cells and high CD4+ and CD8+ terminally differentiated and senescent T-cells as well as high CMV-reactive CD4+ and CD8+ T-cells and high T-regs. Low was defined as immune phenotypes in the first quartile of the distribution and high was defined as immune phenotypes in the fourth quartile of the distribution. Nasopharyngeal swabs were obtained and tested for viruses in symptomatic residents. Models were adjusted for age, sex and frailty.
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Yasa P400 Electric Traction Machine Characterization and Efficiency Data
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Allca-Pekarovic, Alex; Phillip J. Kollmeyer; Forsyth, Alexander; Emadi, Ali — 2024-03-27 This dataset has results from various tests performed on the YASA P400HC motor from YASA Motors. The first tabs in the spreadsheet are results of measurements performed in a lab setting to characterize the motor's parameters over a wide operating range across four DC bus voltages. From these measurements, analyses have been made and plots are shown which mimic or are the source of many of the figures found in the associated publication. The last tabs of the spreadsheet are results from simulated and experimental drive cycles performed on a dynamometer.
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Fast Charging and Characterization Dataset for Porsche Taycan LG E66 Battery Cell and Module
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Uwalaka, Lucia; Yao, Qi; Duque, Josimar; Phillip J. Kollmeyer — 2024-10-10 An LG E66 pouch cell and a battery module containing twelve E66 cells (6p2s) were tested. Both the cell and module were taken from a Porsche Taycan EV from a low mileage vehicle. Characterization tests, including numerous drive cycles, constant current discharge rates, and an OCV and HPPC test, were performed at -20, -10, 0, 10, 25, and 40degC. These tests are useful for creating battery terminal voltage models and for creating SOC estimation algorithms using machine learning and filter based techniques. The battery module was opened and instrumented with a battery management system to measure cell voltages and perform cell balancing. The module was also instrumented with numerous temperature sensors, including across the face of the cells so that temperature distribution throughout the module could be measured. The module was placed on a liquid cooling plate, like that in the vehicle, and tested for fast charging rates of 0.5, 1, 1.5, and 2C, as well as with the profile used in the Porsche Taycan vehicle.

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