Citizens in dense built environments are susceptible to the simultaneous occurrence of Slow Onset Disaster (SLOD) events, being particularly prone to increasing temperatures and air pollution. Previous research works have assessed these events’ arousal separately and have identified when their intensity is critical. However, few have integrated their analysis, possibly limited by the quality and granularity of available data, the accessibility and distribution of sensors, and measurements not emulating the surroundings of a pedestrian. Thus, this work performed an outdoor meso-scale multi-hazard-based risk analysis to study the aggregated effects of the SLODs mentioned above. The study was carried out to narrow down the time-frames within 2019 in which these two events could have affected citizens’ health the most. A weighted fuzzy logic was applied to superimpose climatic (temperature, humidity, wind speed, and solar irradiance) and air quality (particulate matter, ozone, and ammonium) distress (true risk) on an hourly basis, allocated using set healthy and comfortable ranges for a specific dense urban climate context within Milan (Italy), processing data from Milano via Juvara station. The findings show that sensitive groups were at risk of high temperature and pollution separately during 26% and 29% of summer and mid-season hours, respectively; while multi-hazard risk would arise during 10.93% of summer and mid-season hours, concentrated mainly between 14:00 and 20:00.