This ongoing work attempts to understand and address the requirements of UNICEF, a leading organization working in children's welfare, where they aim to tackle the problem of air quality for children at a global level . We are motivated by the lack of a proper model to account for heavily fluctuating air quality levels across the world in the wake of the COVID-19 pandemic, leading to uncertainty among public health professionals on the exact levels of children's exposure to air pollutants . We create an initial model as per the agency's requirement to generate insights through a combination of virtual meetups and online presentations . Our research team comprised of UNICEF's researchers and a group of volunteer data scientists . The presentations were delivered to a number of scientists and domain experts from UNICEF and community champions working with open data . We highlight their feedback and possible avenues to develop this research further.