The fuzzy Factor-Comparison-Method (Fuzzy-FCM) is based on the Multi-Criteria-Decision-Making Method which is the paired type comparison method between Key-Performance- Indicators (KPIs) which are the factors affecting air quality in urban regions. This paper aims at the identification of important KPIsaffecting air quality of urban regions of India by using Fuzzy-FCM.Twelve KPIs out of a total of forty-four total identified KPIs have been shortlisted using the FCM technique. These KPIs belong to the six parameters like meteorological, natural, land useand landcover, urbanization, transportation and miscellaneous. Furthermore, the machine learning tool Random Forest (RF) has been applied to identify the weightage of the twelve KPIs in the urbanregion of India.The results indicate that the parameter with the highest impact is "latitude," followed by "population density" and "month of the year," with relative importance percentages of 100%, 96.9%, and 92.1%, respectively. This study also aims to manage high pollution days observed mostly in the Indo-Gangetic plain. As observed in Delhi during winter, the Air-Quality-Index (AQI) value increases to a huge extent thereby creating a hazardous condition which is tremendously harmful for the residents of Delhi. A decision matrix has been developed to find out the feasible option for anthropogenic causes which is responsible for abrupt increase of AQI. This can be mitigated through proper management of the harvested crops through in-situ crop management system. This novel approach shows a better method for managing air quality and will play a key role in creating a model to predict and understand the air quality of urban regions.