COVID-19: Rapid detection of the impact of COVID-19 on UK greenhouse gas emissions
- Funded by UK Research and Innovation (UKRI)
- Total publications:0 publications
Grant number: NE/V00963X/1
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Key facts
Disease
COVID-19Known Financial Commitments (USD)
$98,000.49Funder
UK Research and Innovation (UKRI)Principal Investigator
Matthew RigbyResearch Location
United KingdomLead Research Institution
University of BristolResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Other secondary impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
The nationwide restrictions on social interaction brought about by the COVID-19 outbreak have the potential to dramatically change the UK's greenhouse gas (GHG) emissions. However, given the lack of precedent, it is difficult to predict the sign, magnitude, or spatial and temporal change that may occur. Atmospheric GHG observations are sensitive to emissions changes over very short timescales (hours to days), and therefore "top-down" (atmospheric data-based) inference of GHG emissions has the potential to provide rapid updates to climate researchers, the public and stakeholders (e.g. BEIS and the UK's GHG inventory compilers). There have already been reports of reductions in atmospheric concentrations of GHGs and air pollutants in the media from across the world. However, these reports have sometimes lacked scientific rigour, ignoring the critical influence of meteorology and seasonality. Here, we aim to use data from the UK's unique GHG measurement network (the UK DECC network) and adapt our atmospheric modelling and statistical inference frameworks to provide robust information on any rapid changes in UK GHG emissions that occur during the period of COVID-19-related restrictions. Conversely, the change in anthropogenic activity provides an unprecedented opportunity to test top-down (atmospheric data-based) emissions inference frameworks, such as those used to report UK GHG emissions to the United Nations Framework Convention on Climate Change (UNFCCC).