Stream Reasoning (SR) focuses on developing advanced approaches for applying inference to dynamic data streams; it has become increasingly relevant in various application scenarios such as IoT, Smart Cities, Emergency Management, and Healthcare, despite being a relatively new field of research. The current lack of standardized formalisms and benchmarks has been hindering the comparison between different SR approaches. We propose a new benchmark, called EnviroStream, for evaluating SR systems on weather and environmental data from two European cities. The benchmark includes queries and datasets of different sizes. We adopt I-DLV-sr, a recently released SR system based on Answer Set Programming, as a baseline experiment. We illustrate how the queries can be modeled via I-DLV-sr input language and report evaluation times. We also assess continuous online reasoning via a web application. ############################################################################################ Data can and queries can be also downloaded via the GitHub repository: https://github.com/DeMaCS-UNICAL/EnviroStream Real-time data can be visualized via the following link: https://experiments.demacs.unical.it/