## 1 Introduction
This method aims to reduce the combinations between stressors and represents a trade-off between the accuracy of the assessment, which requires the use of specific data, which are often unavailable, and the bias introduced by incorrect assumptions regarding the contribution of stressors. The authors applied the method to assess aggravation of the exposure of wild animals and their habitat generated by stressors caused by human activities and climate change. The major difficulty of this approach, however, is the determination of the priority set of stressors and stressor combinations. In this study, a new approach to assess stressors generated by the presence of epidemics/pandemics in urban settlements during heatwaves is tested. These stressors are assessed in terms of increased exposure by evaluating the level of discomfort of the population, which is measured in terms of the relevance of unpleasant emotional states expressed in posts on a social network. This model has the advantage of improving the imprecision of the assessment of the aggravating contribution of the stressor. In fact, in order to assess this contribution, it would be necessary to determine the variation of exposure due to the increase in citizens' discomfort in the presence of stressors, such as, for example, in periods of pandemic crisis. However, this information is difficult to estimate, as it could be generated by numerous factors, such as, for example, an increase in energy poverty due to job losses, increases in costs caused by the pandemic, or the proliferation of respiratory or cardiovascular diseases generated by the disease, which increase the discomfort of the population during heatwaves. The model evaluates the contribution of stressors generated by a pandemic/epidemic on the impact of heatwave scenarios in urban settlements in terms of variations in the population exposed to risk. The fuzzy-based emotion detection model FREDoC [10] is applied to extract, for each subzone in which the urban settlement is partitioned, the relevance of pleasant and unpleasant emotions, as established by examining posts published by users on social media that dealt with pandemic and heatwave scenarios. The relevance of unpleasant emotional categories is used to assess the contribution of pandemic stressors during the heatwave in terms of increased/decreased heatwave exposure. Exposure may have increased or decreased depending on whether unpleasant or pleasant emotions of the citizens prevailed. We propose an index of discomfort calculated by considering the relevance of unpleasant and pleasant emotions. It represents an aggravating or mitigating factor of exposure, which contributes to amplifying or reducing the impacts of heatwave scenarios compared to those assessed if the urban heatwave occurred in normal periods. Section 2 describes the adopted method. A brief discussion is included regarding the climate risk assessment models and the FREDoC framework for document classification by prevalent emotional categories. Subsequently, the proposed model for assessing exposure in the presence of stressors is synthesized and described in detail, and the case study used to test the model is discussed. The results of the comparative tests are presented and discussed in Section 3. Section 4 includes concluding remarks and future research perspectives.