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Publication of the month - July 2026

3 balloons in the sky representing Co2

Wrexham University researchers have developed a community-scale map of atmospheric carbon dioxide (CO₂) concentrations across Wrexham County Borough, offering new visual insights into local patterns of emissions in North Wales.

Using satellite-derived air quality data, geospatial analysis and interactive mapping tools, the study identified persistent CO₂ hotspots across Wrexham which could be used to support evidence-based planning at a local level and further drive the net-zero targets.

Adekunle Oladiji, Graduate Teaching Assistant in Cyber & Computing, co-authored a paper on the research findings titled “Tracking Carbon Emissions: Mapping CO2 in North Wales”. The paper, written with Dr Phoey Lee Teh and Dr Colin Kuka, was recently published in the Journal of Social Computing.

  Head shot of research wearing a cream blazerAdekunle Oladiji

The Approach

Wrexham is made up of urban, peri-urban, and rural communities, yet the data used to support CO₂ reduction measures is based on combined statistics which can hide local hotspots and hinder climate goals. The research aimed to address the gap in community-level monitoring to help reveal where interventions may be most beneficial.

The research consisted of:

  • Data collection
  • Geospatial processing
  • Statistical and spatial analysis
  • Interactive visualisation and hotspot identification

Demographic data was mapped against geospatial administrative boundaries (including neighbouring Flintshire) to ensure spatial accuracy, and air pollution and atmospheric data (1 January–30 June 2025) was analysed for CO2 concentration. The data was then processed (cleansed and verified) and analysed (correlations, trends and regional comparisons) to develop a reproducible framework for community-scale carbon monitoring. The research utilised publicly available data and various computing software to produce visualisation charts, a folium map and a choropleth map.

Findings

The research identified a number of key findings that could inform local environmental decisions:

  • CO₂ hotspots: Rossett and Holt in Wrexham, located in the North-East of the county, recorded the highest average CO₂ concentrations in the dataset that was analysed
  • Other North-East communities (Llay, Gresford, Gwersyllt, Broughton, Rhosddu, and Acton) had elevated CO₂ concentrations
  • Large populations are not a stand-alone pre-determinant of higher CO₂ concentrations, as local geography, infrastructure, and economic activity also play a part
  • Seasonal changes can influence CO₂ concentrations and hotspots, with the weather, atmospheric changes, and farming/industrial activities being potential contributing factors.

The research also revealed continuity in emission patterns across the Wrexham-Flintshire border, suggesting opportunity for coordinated regional approaches to climate action. Some limitations were also noted by the authors, including that the dataset used only represented 6 months of the year, meaning the full seasonal cycle was not observed in the research.

The software used by the researchers to visually represent the data findings supports a broad shift toward open-source geospatial platforms for environmental monitoring with the paper detailing that “browser-based visualisation tools enhance public engagement and interpretability”.

Recommendations

The study and interactive map development could serve to support actionable insights for environmental governance and public engagement in North Wales, including geographically targeted and seasonally adjusted interventions.

Ecological citizenship and education are a key focus for many authorities currently, with Wrexham Borough Council being no exception to this. The approach, findings, and interactive resource of this study may support the educational and citizen science agenda across Wrexham.

Future research could expand the timeframe and the geographical coverage of the datasets, incorporate additional datasets, and utilise advanced predictive techniques to improve source identification and forecasting.

You can read the article in full.