This readme.txt file was generated on <20231119> by Recommended citation for the data: Furuta, Daniel CR; Wilson, Bruce N; Presto, Albert A; Li, Jiayu. (2023). Data and code for "Design and evaluation of a low-cost sensor node for near-background methane measurement". Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/CDVH-E012. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Data and code for "Design and evaluation of a low-cost sensor node for near-background methane measurement" 2. Author Information Principal Investigator Contact Information Name: Jiayu Li Institution: University of Miami, Department of Mechanical and Aerospace Engineering Address: 1251 Memorial Drive, Coral Gables, FL 33146 Email: jiayuli@miami.edu ORCID: 0000-0002-6774-4325 Associate or Co-investigator Contact Information Name: Daniel Furuta Institution: University of Minnesota, Biosystems Engineering Address: 1390 Eckles Ave., St. Paul, MN 55108 Email: furut011@umn.edu ORCID: 0000-0002-9603-9262 Associate or Co-investigator Contact Information Name: Bruce Wilson Institution: University of Minnesota, Biosystems Engineering Address: 1390 Eckles Ave., St. Paul, MN 55108 Email: wilson@umn.edu ORCID: 0000-0003-0921-3136 Associate or Co-investigator Contact Information Name: Albert A. Presto Institution: Carnegie Mellon University, Department of Mechanical Engineering Address: 5000 Forbes Ave., Pittsburgh, PA 15213 Email: apresto@andrew.cmu.edu ORCID: 0000-0002-9156-1094 3. Date published or finalized for release: 2023 4. Date of data collection (single date, range, approximate date) 202207 - 202305 5. Geographic location of data collection (where was data collected?): Minneapolis 6. Information about funding sources that supported the collection of the data: This research has been supported by funding from the U.S. Environmental Protection Agency's Understanding and Control of Municipal Solid Waste Landfill Air Emissions program (Assistance Agreement No. 84062701-0). This dataset was developed in part under Assistance Agreement No. 84062701-0 awarded by the U.S. Environmental Protection Agency to Jiayu Li. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. This research has been supported by the National Energy Technology Laboratory (grant no. S000663-USDOE). 7. Overview of the data (abstract): Cleaned data and supporting code for "Design and evaluation of a low-cost sensor node for near-background methane measurement". The data was collected at two research sites in 2022 and 2023, and the analysis code was used to generate the model and figures in the paper. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: CC0 1.0 Universal (https://creativecommons.org/publicdomain/zero/1.0/) 2. Links to publications that cite or use the data: TBD 3. Was data derived from another source? If yes, list source(s): No 4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/drum/policies/#terms-of-use --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: inside_cleaned.csv Short description: Cleaned data for the inside portion of the experiment. B. Filename: outside_cleaned.csv Short description: Cleaned data for the outside portion of the experiment. C. Filename: paper_analysis.py Short description: Code in Python 3, used to analyze the data and generate the figures for the paper. D. Filename: requirements.txt Short description: A list of required packages to run paper_analysis.py. 2. Relationship between files: inside_cleaned.csv and outside_cleaned.csv are the datasets for the two portions of the experiment. paper_analysis.py is the code used to process and analyze the datasets. -------------------------- METHODOLOGICAL INFORMATION -------------------------- The inside and outside datasets combine records from a novel low-cost methane sensor node (temp_c, rh, tgs2600, tgs2611 variables) and a LICOR 7810 reference methane analyzer (H2O and CH4 variables), and are intended to provide calibration and performance information for the sensor node design. The inside dataset was recorded in the UMN Biosystems Engineering workshop near a classroom-scale anaerobic digester, which provided a range of methane concentrations; the outside dataset was from an urban yard in Minneapolis with predominantly low concentrations. The outside dataset also contains several short intentional methane releases, intended to provide some variance to the data. The TGS2600 and TGS2611 entries are the output of low-cost metal oxide semiconductor sensing elements, which we attempt to correlate to methane levels. The data contains several gaps: one two-week gap in August and September of 2022 due to instrument malfunction, and several short gaps of several hours due to power failures, data retrieval, and related events. The data has been averaged to 10-minute resolution. The included Python script plots the data and performs a calibration and evaluation of the sensor node. For further details, see the related paper. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: inside_cleaned.csv and outside_cleaned.csv ----------------------------------------- 1. Number of variables: 10 2. Number of cases/rows: 15688 (inside) and 14333 (outside) 3. Missing data codes: n/a 4. Variable List A. Name: datetime Description: Date and time, UTC -6. Date in M/DD/YYYY format. B. Name: H2O Description: Water vapor concentration, %v C. Name: CH4 Description: Methane concentration, ppm D. Name: temp_c Description: Temperature, degrees C E. Name: rh Description: Relative humidity, % F. Name: tgs2600 Description: TGS2600 sensor readings, kiloohms G. Name: tgs2611 Description: TGS2611-E00 sensor readings, kiloohms H. Name: time Description: Cumulative time for this dataset, days I. Name: total_time Description: Cumulative time since the start of the experiment, days J. Name: elapsed_time Description: Cumulative time the sensor has been running (not counting system downtime), days