Reducing ammonia emissions is key to meet the UK's new air quality target
Lead Research Organisation:
University of Birmingham
Department Name: Sch of Geography, Earth & Env Sciences
Abstract
Ammonia (NH3) plays a key role in secondary PM2.5 formation (Particulate Matter less than 2.5 micrometres in diameter), however there are large uncertainties in the quantities of NH3 emitted. Current country-wide measurements are limited to monthly averages in the National Ammonia Monitoring Network (NAMN). In Birmingham, London and Manchester there are continuous high-time resolution monitors however these are all urban background sites and there are no continuous ammonia measurements near major sources such as agriculture or road traffic in the UK.
This project aims to produce a comprehensive fixed-station and mobile ammonia dataset across the UK using a high time-resolution, high sensitivity instrument. By employing inversion modelling, we will quantify ammonia sources in the West Midlands and use air quality models to assess how to best reduce ammonia emissions and consequently reduce PM2.5 concentrations. The findings will inform policy recommendations for reducing and controlling ammonia emissions, shared with DEFRA, The Air Quality Expert Group, and WM-Air.
This project provides a unique opportunity to gain a wide range of skills in three key areas: the first in air quality supersite observations through the work of producing a high-quality air pollution data set over a large spatial scale, the second in machine learning for data analysis and to understand what impacts ammonia emissions, and the third in advanced air quality modelling to understand the mechanisms driving the ammonia system, investigate the role of ammonia in PM2.5 formation, update ammonia emission inventories, and to model ammonia emissions and concentrations into the future under different scenarios.
This project aims to produce a comprehensive fixed-station and mobile ammonia dataset across the UK using a high time-resolution, high sensitivity instrument. By employing inversion modelling, we will quantify ammonia sources in the West Midlands and use air quality models to assess how to best reduce ammonia emissions and consequently reduce PM2.5 concentrations. The findings will inform policy recommendations for reducing and controlling ammonia emissions, shared with DEFRA, The Air Quality Expert Group, and WM-Air.
This project provides a unique opportunity to gain a wide range of skills in three key areas: the first in air quality supersite observations through the work of producing a high-quality air pollution data set over a large spatial scale, the second in machine learning for data analysis and to understand what impacts ammonia emissions, and the third in advanced air quality modelling to understand the mechanisms driving the ammonia system, investigate the role of ammonia in PM2.5 formation, update ammonia emission inventories, and to model ammonia emissions and concentrations into the future under different scenarios.
Organisations
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
NE/S007350/1 | 30/09/2019 | 29/09/2028 | |||
2922496 | Studentship | NE/S007350/1 | 30/09/2024 | 28/07/2028 | Thomas Wynn |