Project Overview

The urban-air-mitigation-sim project is developed to simulate and evaluate the impact of various urban emission mitigation strategies on air quality. Leveraging the SHERPA (Screening for High Emission Reduction Potential on Air) methodology, this tool allows users to assess how different mitigation measures influence pollutant concentrations in urban environments.

Key Features:

• Integration with Knowledge Graphs: Seamlessly connects with the urban-air-quality-kg to inform simulations with structured air quality data.
• Modular Design: Utilises SHERPA modules (e.g., module1, module3a) for detailed analysis of emission sources and their contributions.
• Support for Multiple Pollutants: Capable of simulating various pollutants, including PM₂.₅, NOx, and others.
• Customizable Scenarios: Users can define specific mitigation measures and assess their outcomes.

System Architecture

The urban-air-mitigation-sim project is structured to simulate the impact of urban emission mitigation strategies on air quality. It leverages the SHERPA (Screening for High Emission Reduction Potential on Air) methodology, integrating various modules to process input data, perform simulations, and generate outputs.

1. Input Data Preparation

Accurate simulations require meticulously prepared input data. The following datasets and configurations are essential:

• Emission Data (path_emission_cdf): NetCDF files containing gridded emission inventories categorized by GNFR sectors and precursors.
• Baseline Concentration Data (path_base_conc_cdf): NetCDF files representing baseline pollutant concentrations, serving as a reference for assessing changes due to mitigation measures.
• Reduction Matrix (path_reduction_txt): Text files defining emission reduction percentages for each precursor and sector, formatted as per SHERPA specifications.
• Area Mask (path_area_cdf): NetCDF files delineating the spatial scope of the study area, ensuring simulations focus on the relevant geographic region.
• Source-Receptor Model (path_model_cdf): NetCDF files containing source-receptor relationships, crucial for linking emission sources to their impact on air quality.

For detailed guidance on preparing these inputs, refer to the SHERPA-simulation documentation.

2. Simulation Modules

The core simulation process is orchestrated through a series of SHERPA modules:

• Module 1 (Scenario Assessment): Simulates the impact on air quality of specific emission reduction scenarios. It applies the defined reduction matrices to the emission data and computes the resulting changes in pollutant concentrations using the source-receptor relationships.
• Module 3 (Source Allocation): Evaluates source contributions by running simulations for all macrosectors and precursors. It utilizes the prepared input data to compute the potential impact of emission reductions.
• Module 4 (Potency Calculation): Calculates the change in pollutant concentrations resulting from specific emission reductions, based on source-receptor relationships.
• Auxiliary Modules: Additional scripts (sherpa_auxiliaries.py, sherpa_globals.py, etc.) support data handling, configuration management, and utility functions essential for the simulation workflow.

3. Output Generation

Post-simulation, the system generates various outputs to aid in analysis:

• Absolute Potential (DC_alpha): Quantifies the change in concentration per unit reduction in emissions, indicating the direct impact of mitigation measures.
• Relative Potential (DC_C_alpha): Represents the proportionate change relative to baseline concentrations, offering insights into the efficiency of emission reductions.
• Result Files: NetCDF files encapsulating the simulation outcomes, suitable for further analysis and visualization.

Acknowledgement

This work was supported by the Built Environment Fellowship awarded to Dr Xiang Xie from the 1851 Royal Commission.

Contributing

Contributions are welcome! Get in touch if you have any queries or would like to collabrate. Email xiang.xie@ncl.ac.uk