Air pollution and climate change are urgent global problems, with urban areas contributing significantly to both pollutant and greenhouse gas emissions. With more than half of the world's population living in cities, and this proportion is expected to increase to more than two-thirds by 2050, cities are also where the burden of air pollution-related diseases is greatest. Understanding trends and relationships between different pollutants and carbon dioxide emissions is key to assessing the impact of environmental initiatives and informing future strategies.

Recent study focused on monitoring concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), ozone (O3), and fossil carbon dioxide emissions per capita (FFCO2 per capita) in 13,189 urban areas around the world from 2005 to 2019. It used large geospatial datasets and analyzed correlations between trends in these pollutants.

Global status in 2019 and trends 2005-2019

In 2019, average concentrations of pollutants in urban areas around the world were significantly higher than the World Health Organization (WHO) guidelines. The average concentration of PM2.5 (37.7 μg/m³) was 7.5 times higher than the WHO guideline (5 μg/m³). Average levels of NO2 (7.1 ppb) and O3 (51.2 ppb) also exceeded the WHO guidelines by 34% and 67%, respectively.

Regarding temporal trends from 2005 to 2019, the study found that global urban PM2.5 concentrations remained at a similar level (+0%) to 2005-2007, although there was an increase from 2005-2011, followed by a decrease. Global average NO2 concentrations changed only minimally (-1%), while O3 concentrations recorded statistically significant global increase of 6%Per capita FFCO2 emissions globally saw a small, statistically insignificant increase of 4%.

Regional differences and correlations

The study revealed strong geographic patterns and regional differences in pollution trends and levels. In 2019, the highest levels of PM2.5 were observed primarily in India, Bangladesh and Pakistan, with other “hot spots” in Nigeria, Saudi Arabia and China. Elevated levels of NO2 were mainly found in China and high-income countries. The highest levels of O3 were similar to PM2.5 in India and the South and Southeast Asia region overall.

Regional trends varied:

• High-income countries with strict policies to mitigate pollution and CO2 emissions have seen significant reduction of all four monitored pollutants (PM2.5: -19%, NO2: -7%, O3: -4%, FFCO2 per capita: -17%).
• Regions with rapid economic growth and growing populations, such as South Asia a Sub-Saharan Africa, saw an overall increase in pollution. South Asia showed the largest statistically significant increases in PM2.5 (+14%) and O3 (+18%). Sub-Saharan Africa saw simultaneous increases in NO2 (+9%), O3 (+9%) and FFCO2 per capita (+8%).
• In regions like Latin America and the Caribbean a North Africa and the Middle East have manifested different or mutually cancelling trends between pollutants and FFCO2.

Analysis of correlations between time trends showed that over 50% urban areas worldwide had positive correlations for all pairs of pollutants monitored. This reflects the fact that these pollutants and/or their precursors tend to be emitted together, suggesting the potential for their simultaneous reduction through joint measures. The strongest positive correlation was found between PM2.5 and O3. Larger cities had a higher proportion of significant positive correlations. However, the correlation patterns varied regionally, with more negative correlations in regions with separate or opposing trends.

Impact of urban boundary definition and study limitations

The study also compared the impact of two different definitions of city boundaries (GHS-SMOD and C40 Cities) on pollution estimates. It was found that the different definitions had greater impact on estimates of NO2 and FFCO2 concentrations per capita compared to PM2.5 and O3. This underscores the importance of how we define urban areas in research and policy.

The main limitations of the study include the potential inaccuracy of the global datasets used, especially in less monitored regions of the global South, where estimates are likely to be more uncertain. Accuracy can also be affected by model resolution and uncertainties in population and urban boundary data, which change over time.

Conclusion

The study provides important insights into trends in air pollution and CO2 emissions in urban areas around the world. The observed regional differences in trends and correlations point to the influence of local and regional factors, including economic growth, urbanization, and the effectiveness of policies. The finding of a preponderance of positive correlations between pollutants in most cities supports the idea that current solutions to air pollution and greenhouse gas emissions through integrated mitigation strategies. Monitoring this progress is essential for achieving the WHO and UN Sustainable Development Goals. Spring

The study was published nature.com