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Air Quality-Related Equity Implications of U.S. Decarbonization Policy

This repo includes supporting material for the publication: Paul Picciano, Minghao Qiu, Sebastian Eastham, Mei Yuan, John Reilly, Noelle E. Selin. Air Quality-Related Equity Implications of U.S. Decarbonization Policy. Nature Communications (2023). Please download and unzip the file "climate_policy_pollution_equity.zip". Please see README below for a full description of the scripts and data included in this repo.  For correspondence on the publication, please contact Noelle Selin selin@mit.edu. If you have questions about this data repo, please contact Minghao Qiu mhqiu@stanford.edu or Paul Picciano pauldpicciano@gmail.com   README The materials in this repository allow users to reproduce the main results and figures of the paper. The analysis is performed using R (version 4.3.0).  -- Scripts: <ul> <li>initial_setup.R:  Used to load R packages, set up file paths, variable names, and the functions used in other scripts. Please load this script first before running other scripts.</li> <li>Figure1 - 5.R:  Used to generate figures 1 - 5 in the main paper. </li> <li>optimization_scenarios.R: Used to generate the optimization scenarios and 5000 possible emission reduction scenarios that achieve the same level of CO2 reductions. The results generated by this script are then used to generate Figure 5.</li> </ul>   -- Data: <ul> <li>emission_aggregate_scenarios.csv:  Nationally-aggregated emissions of CO2 and non-CO2 species by different sectors under the three main emission scenarios (scenarios number 1 - 3 as labeled in the paper). The unit of CO2 emissions is billion metric tons. Units of non-CO2 emissions are million metric tons. Used to plot Figure 1.</li> <li>InMAP_pm25_conc_scenarios.rds:  PM2.5 concentration for each InMAP grid cell due to emissions from each sector (and combined sectors) under different emission scenarios. InMAP simulates annual mean PM2.5 concentration (unit: μg/m3). Used to plot Figure 2.</li> <li>US_shapefiles.RData: Shape files of US states. Used to plot Figure 2.</li> <li>exposure_main_scenarios.csv: Population-weighted PM2.5 for each population group xxx under different scenarios (i.e. AvgExposure_xxx, units of exposure: μg/m3); disparities in population-weighted PM2.5 between each population group xxx and the total population (i.e. AvgDisparity_xxx, units of disparity: %). Used to plot Figures 3 and 4. Rows 2-4 correspond to the main scenarios (scenario numbers 1 - 3). Rows 5 - 16 correspond to the sensitivity scenarios (scenario number 4 as labeled in the paper).</li> <li>source_emission_baseline_2030.rds: Emissions from each individual source as projected by the baseline 2030 scenario (scenario number 2). Used as input data for the optimization analysis.</li> <li>source_emission_cap50_2030.rds: Emissions from each individual source as projected by the cap50% scenario (scenario number 3). Used as input data for the optimization analysis.</li> <li>minority_exposure_by_sector.rds: Changes in population-weighted PM2.5 exposure and disparities for the racial/ethnic minority group between the cap50% scenario and baseline 2030 scenario. Used to plot Figure 5.</li> <li>optimization_scenarios.rds: Population-weighted PM2.5 exposure and disparities for the racial/ethnic minority group under different optimization scenarios (scenarios number 5 -10). This file is generated by optimization_scenarios.R and further used to plot Figure 5.</li> <li>cap50_nation_total_5000draws.rds: Population-weighted PM2.5 exposure and disparities for the racial/ethnic minority group under 5000 possible scenarios that achieve the same level of CO2 reductions without any constraints (i.e. the same as the "nation-total" scenario). This file is generated by optimization_scenarios.R and further used to plot Figure 5.</li> </ul> <ul> </ul>

Dataset for publication: "Using explainable machine learning to interpret the effects of policies on air pollution: COVID-19 lockdown in London"

This online repository offers supplementary datasets supporting the findings in the research article titled "Using explainable machine learning to interpret the effects of policies on air pollution: COVID-19 lockdown in London," published in Environmental Science & Technology. The dataset contains air quality data from different monitoring sites in London between 2016 and 2020 and weather data for the same period. Additionally, the dataset incorporates 136 features relating to London's Middle Layer Super Output Areas (MSOAs) in the year 2019, which can be used to identify the key factors contributing to the heterogeneous changes in air quality levels at different spatial locations during the pandemic. Please refer to the metadata file for detailed data sources and descriptions.

Lichens as bioindicators of monitoring of the selective air pollution, Zabrze (Poland) - total carbon (TC) and total sulfur (TS) results.

Total carbon (TC) and total sulfur (TS) contents were measured using an Eltra CS-500 IR-analyzer with a TIC module. TC was determined using an infrared cell detector on CO2 gas, which was evolved by combustion under an oxygen atmosphere. Calibration was made by means of the Eltra standards 2.27 % S and 45.14 % C.  Dr Ewa Szram, employed at the Institute of Earth Sciences, Faculty of Natural Sciences, Silesian University in Katowice, carried out the project. This research was funded by the National Science Centre, Poland MINIATURA-6 2022/06/X/ST10/00338 “Lichens as bioindicators of monitoring of the selective air pollution”

Lichens as bioindicators of monitoring of the selective air pollution, Zabrze (Poland) - XRF analysis results.

XRF analyses were performed by the BRUKER S8 TIGER series 2 WD-XRF spectrometer with a 1kW Rh X-ray tube. The system is equipped with five analyzing crystals (LiF200, PET, XS–55, LIF-220  & Ge) and two detectors (flow and scintillation counter). The samples were measured by best detection mode (18min analysis time), and the results were evaluated in Quant-Express (fundamental parameters) and SPECTRAplus Software. Dr Ewa Szram, employed at the Institute of Earth Sciences, Faculty of Natural Sciences, Silesian University in Katowice, carried out the project. This research was funded by the National Science Centre, Poland MINIATURA-6 2022/06/X/ST10/00338 “Lichens as bioindicators of monitoring of the selective air pollution”

Lichens as bioindicators of monitoring of the selective air pollution, Zaabrze (Poland) - chromatograms of GC-MS

Detailed geochemical analyses were performed on 21 powdered samples after their extraction using ultrasound Elmasonic Easy with a dichloromethane (DCM) and methanol (MeOH) mixture (1:1 vol). Extracts were separated into aliphatic-, aromatic-, semipolar- and polar fractions by column chromatography. Silica-gel was first activated at 120 °C for 24 h, cooled, and poured into Pasteur pipettes. Foour eluents were used for fraction collection, namely, n-pentane for the aliphatic fraction, n-pentane and DCM (7:3) for the aromatic fraction, acetone and DCM (1:1) for the semipolar fraction, and DCM and methanol (1:1) for the polar fraction. The semipolar - and polar fraction was derivatized with MTBSTFA (N-tertbutyldimethylsilyl-N-methyltrifluoroacetamide). Samples were derivatized with MTBSTFA dissolved in super-dehydrated n-hexane, and heated at 70 °C for 3 h. The composition of the separated extracts was analyzed by gas chromatography–mass spectrometry (GC–MS) using an Agilent gas chromatograph 7890A coupled with a mass spectrometer 5975C XL MDS. A DB-5UI column was applied (60 m × 250 μm id, 0.25 μm stationary phase film), with He (purity of 99.9999%) as a carrier gas. The experimental conditions were as follows: injection volume of 1 μL; split/splitless mode; initial temperature of 45 ◦C (isothermal for 1 min); heating rate up to 100 ◦C at 20 ◦C/min, then 3 ◦C/min to 280 ◦C for 66.25 min. The mass spectrometer worked in electron ionization (EI) mode at 70 eV in full scan mode and scanned from 50 to 650 Da. Dr Ewa Szram, employed at the Institute of Earth Sciences, Faculty of Natural Sciences, Silesian University in Katowice, carried out the project. This research was funded by the National Science Centre, Poland MINIATURA-6 2022/06/X/ST10/00338 “Lichens as bioindicators of monitoring of the selective air pollution”

opencc-zeroSep 2023View details →

dryad36/100

Great Basin National Park, NV air temperature and relative humidity

Hourly air temperature and relative humidity data has been collected from a network of 29 data-logging sensors installed within radiation shields ~1.5 m above ground level at discrete sites within the Great Basin National Park (GBNP), NV, USA from August 2006 to August 2023. The sensors are "embedded" – suspended in trees or atop wooden stakes – within diverse ecosystem types spanning over 2,000 m of elevation, and are maintained/downloaded during annual visitations by collaborating teams of students and staff from the Ohio State University, University of Georgia, and Sinclair Community College, assisted by GBNP staff. This dataset can be utilized to assess the microclimates and weather patterns within the GBNP. The dataset comprises daily mean, maximum, and minimum temperature and relative humidity collected between Aug 2006 – Aug 2023. Hourly, raw data are available upon request.

opencc-by-4.0Sep 2023View details →

Global LAke Surface water Temperature (GLAST): Global lakes are warming slower than surface air temperature due to accelerated evaporation

This repository houses a dataset, known as the Global LAke Surface water Temperature (GLAST), which provides both temporal and spatial details at high resolution for 92,245 lakes worldwide during the period of 1981-2099, with 36% of them situated in Arctic regions. The dataset was established based on four decades (1982-2020) of Landsat satellite images and a physical model (FLake). For a comprehensive overview of the dataset's production methodology, please refer to the paper titled 'Global lakes are warming slower than surface air temperature due to accelerated evaporation' (Tong et al., 2023, Nature Water). Detailed information regarding each data file can be found in the 'readme.docx' file.

opencc-by-4.0Sep 2023View details →

Data for: Sources, pathways and behaviour of cave air CO2 using carbon isotopes

Raw data for all figures in the manuscript by Krajnc et al. to be published by Geochimica et Cosmochimica Acta as "Sources, pathways and behaviour of cave air CO2 using carbon isotopes".

opencc-by-4.0Sep 2023View details →

A suspended hot drop of 1,3-propanediol with 4.1 mm base diameter, 190oC core temperature, and approaching air flow at 0.34 m/s, recorded at 10,000 fps and 99 ms exposure time, with default video playback speed 30 fps

A suspended hot drop of 1,3-propanediol with 4.1 mm base diameter, 190oC core temperature, and approaching air flow at 0.34 m/s, recorded at 10,000 fps and 99 ms exposure time, with default video playback speed 30 fps

opencc-by-4.0Jul 2023View details →

Ultrasonic Pulse Transmission Tests: Datasets - Test Series 3, Reference Tests on Air

The test series was created to receive information about the impact of the behaviour of two different piezoelectric shear wave sensors on the measurement results of ultrasonic pulse transmission tests. The approach for the test series was to vary the parameters pulse-width and the shear-wave-sensor-type. This results in a two-dimensional test parameter grid (pulse-width versus shear-wave-sensor-type). Tests were performed for each grid point in order to receive information needed to optimize the pulse width, but also a possible dependency between material and sensor behaviour. The material tested was the air of the laboratory environment. The test method used was the ultrasonic pulse transmission method with combined compression- and shear wave measurements. All test data and metadata are summarized into datasets using GNU Octave's open binary file format.

opencc-by-4.0Jul 2023View details →

Ultrasonic Pulse Transmission Tests: Datasets - Test Series 5, Reference Tests on Air

The test series was created in order to validate the stability and functionality of the test device and to create a data reference for aeriform materials (air). The approach for the test series was to vary the parameters number-of-samples-recorded, pulse-voltage and distance-between-actuator-and-sensor. This results in a three-dimensional test parameter grid. Tests were performed several times for each grid point (number-of-samples-recorded versus pulse-voltage versus distance-between-actuator-and-sensor) in order to receive statistical information about the stability of the test results. The material tested was the air in the laboratory room. The test method used was the ultrasonic pulse transmission method with combined compression- and shear wave measurements. All test data and metadata are summarized into datasets using GNU Octave's open binary file format.

opencc-by-4.0Oct 2023View details →

Indoor Air Temperature and Occupant Behavior in Classroom of higher education building in Mediterranean climate

Data collection Include the measurement of indoor and outdoor environmental parameters (air temperature and relative humidity) and occupant interactions with building systems (window and door status: open/closed, blind state, and thermostat/air-conditioning adjustment).The outdoor air temperature, relative humidity, and wind speed were collected as potential control variables to indicate different outdoor conditions.The indoor air temperature and relative humidity in the classroom were monitored using wireless sensors. Six RHT sensors were placed at different locations: one in the center (F98), two on the ceiling next to grilles (FA1 et F9B), one on the carpentry of one of the windows (F9D), one near the writing board (F94), and one in the corridor outside the classroom (F96). Indoor parameters were recorded at ten minutes intervals.The number of occupants was determined hourly (morning and afternoon) by counting and surveying (attendance sheets). The usage schedules of the classroom were 8:30–18:00. The number of occupants varied from 0 to 31.The states of doors and windows (open or close) were monitored using magnetic sensor that detects the opening of doors and windows. The states of the door and windows were recorded at ten minute intervals.The window-blind closing rate was determined by visual observation. The closing rates were 0%, 25%, 50%, 75%, and 100%. Observations were conducted throughout the day in the morning and afternoon at 1 h intervals.The state of the heating/air-conditioning system was determined to be off or on every hour (in the morning and afternoon) using the HVAC control panel (HMI)

controlledIPD-YESFeb 2026View details →

The Effect of Bristle Brush, Rubber Cup, and Air Polishing on Tooth Surface Roughness of Scaled Teeth

ClinicalTrials.gov study NCT06857474. IPD Sharing: YES. Countries: 1. Publications: 5.

Evaluating Cross-Cutting Prevention at the U.S. Air Force Academy

ClinicalTrials.gov study NCT06875284. IPD Sharing: NO. Countries: 1. Publications: 3.

controlledIPD-YESFeb 2026View details →

Bronchiolitis Recovery and the Use of High Efficiency Particulate Air (HEPA) Filters

ClinicalTrials.gov study NCT05615870. IPD Sharing: YES. Countries: 1. Publications: 1.

Comparative Efficacy of Water & Indigo Carmine vs. Water or Air Method on Adenoma Detection Rate (ADR) - a Randomized Controlled Trial (RCT)

ClinicalTrials.gov study NCT01607255. IPD Sharing: NO. Countries: 1. Publications: 13.

Progel® Pleural Air Leak Sealant (PALS) in Video and Robotic Assisted Thoracoscopic Surgery

ClinicalTrials.gov study NCT01867658. IPD Sharing: NO. Countries: 1. Publications: 1.

Smoke-free Air Coalitions in Georgia and Armenia

ClinicalTrials.gov study NCT03447912. IPD Sharing: NO. Countries: 2. Publications: 3.

Can SIS Using Air Bubbles Replace HSG for Fallopian Tubal Patency After Essure Placement

ClinicalTrials.gov study NCT02628873. IPD Sharing: NO. Countries: 1. Publications: 51.