Prediction of changes in war-induced population and CO2 emissions in Ukraine using social media

Abstract Monitoring the changes in population and anthropogenic CO2 emissions caused by geopolitical conflicts is significant for humanitarian assistance and also for revealing the CO2 emission patterns of human activities. However, the changes in population and anthropogenic CO2 emissions are highly dynamic, and representative survey data are generally unavailable. We monitor the near-real-time and fine-grained changes in war-induced population and anthropogenic CO2 emissions in Ukraine through social media data. One year after the invasion, over 11 million Ukrainians are displaced from the baseline $${0.1}^{\circ}\,*\,{0.1}^{\circ}$$ 0.1 ∘ * 0.1 ∘ gridded regions. There is a significant correlation between the estimated changes and the reference changes for each month in all CO2 emission sectors, with R2 respectively ranging from 0.57 to 0.93, 0.41 to 0.9, 0.74 to 0.99 for residential consumption, ground transport, and industry sectors. Overall, the proposed method provides a new perspective to monitor Ukrainian refugee crisis and measure the spatio-temporal response of anthropogenic CO2 emissions.