Wildfire PM2.5 Solar Power Loss Assessment

This package provides tools for processing and visualizing wildfire PM2.5 data and its impact on solar energy potential. It uses climate model data from the Community Earth System Model (CESM) to analyze how wildfire-generated particulate matter affects solar radiation potential.

Features

• Process PM2.5 data from wildfire smoke by subtracting no-fire scenarios from standard scenarios
• Calculate impacts on solar power potential using established relationships between PM2.5 and solar radiation

Installation

1. Clone this repository:

git clone https://github.com/yourusername/wildfire_pm25_visualization.git
cd wildfire_pm25_visualization

2. Install required dependencies:

pip install numpy pandas xarray matplotlib seaborn cartopy

Data Requirements

The package requires NetCDF files with PM2.5 concentration data. The expected files are:

• CESM_09x125_PM25_2000_Baseline.nc - Baseline scenario for year 2000
• CESM_09x125_PM25_2000_BaseLine_NoFire.nc - No-fire scenario for year 2000
• CESM_09x125_PM25_2050_RCP45.nc - RCP 4.5 scenario for year 2050
• CESM_09x125_PM25_2050_RCP45_NoFire.nc - RCP 4.5 no-fire scenario for year 2050
• CESM_09x125_PM25_2050_RCP85.nc - RCP 8.5 scenario for year 2050
• CESM_09x125_PM25_2050_RCP85_NoFire.nc - RCP 8.5 no-fire scenario for year 2050
• CESM_09x125_PM25_2100_RCP45.nc - RCP 4.5 scenario for year 2100
• CESM_09x125_PM25_2100_RCP45_NoFire.nc - RCP 4.5 no-fire scenario for year 2100
• CESM_09x125_PM25_2100_RCP85.nc - RCP 8.5 scenario for year 2100
• CESM_09x125_PM25_2100_RCP85_NoFire.nc - RCP 8.5 no-fire scenario for year 2100

By default these files are located in the data/ directory.

Usage

Run the visualization script:

python run_visualization.py

This will:

1. Process the PM2.5 data using functions from wildfire_pm25_processing.py
2. Generate visualizations using functions from wildfire_pm25_visualization.py
3. Save all figures to the figures/ directory

You can specify a custom output directory:

python run_visualization.py /path/to/output/directory

Output

The package generates several types of visualizations:

1. PM2.5 Concentration Maps:

   • Individual maps for each scenario
   • Scenario comparison
   • Temporal changes

2. Solar Potential Loss Maps:

   • Individual maps for each scenario
   • Scenario comparison
   • Temporal changes

3. Regional Analysis:

   • Regional PM2.5 concentration
   • Regional solar potential loss
   • Regional changes over time

File Structure

• wildfire_pm25_processing.py - Core data processing functions
• wildfire_pm25_visualization.py - Visualization functions
• run_visualization.py - Main script to run the visualization process
• data/ - Directory for input data files
• figures/ - Directory for output figures

Methodology

The package calculates wildfire contributions to PM2.5 by subtracting no-fire scenarios from standard scenarios. It then uses the relationship between PM2.5 concentration and solar radiation reduction to estimate the impact on solar power potential. The relationship used in this assessment comes from Song et al. (2022) https://pmc.ncbi.nlm.nih.gov/articles/PMC10114768/ but can be easily replaced with alternate equations.

The solar potential change is calculated using the equation:

potential_change (%) = 100 * (-0.48 * pm2.5_concentration / 17.71)

Contact

For questions or feedback, please open an issue on GitHub or contact the author Daniel Baldassare at dbaldassare@woodwellclimate.org