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This study aims to explore aesthetic atmospheres and their affordances in urban squares to advance knowledge on the research and design of attractive living environments.

Descriptions of pleasant and unpleasant experiences of urban squares were collected using qualitative questionnaires with open-ended questions. The theoretical framework and the lens of aesthetic affordances were applied to pinpoint and understand the connections between the place attributes and experiences.

This study found four distinct aesthetic atmospheres formed by perceived synergies of both the material and immaterial aspects of the environment. It was also found that the atmospheres may shift. A model that shows the aesthetic atmospheres and their potential affordances as layered and emerging is presented.

Everyday aesthetics considered as affordances open new research perspectives for the understanding of what generates attractive living environments – or not.

Aesthetics affordances may provide the design professionals and alike means on how to design places that engender specific aesthetic atmosphere.

Gathering and discussing commonplace aesthetic experiences in everyday life may enhance democratic participation in place development among people with different levels of design expertise.

This study combines theories of place with a novel concept of aesthetic affordances to identify distinct aesthetic atmospheres. A holistic overview structure of how the various constituents of aesthetic atmospheres relate to each other provides new ways of studying and understanding urban aesthetic atmospheres.

Using a combination of the geographical information system (GIS) and the Canadian water quality index (WQI), the current study sought to provide a long-term general assessment of the water quality of the Shatt Al-Arab River (SAAR), focusing on its suitability for living organisms. Likewise, SPSS statistics was used to develop a nonlinear WQI regression model for the study area.

The study required four decades of data collection on some environmental characteristics of river water. After that, calculate the WQI and conduct the spatial analysis. Eight variables in total, including water temperature, dissolved oxygen, potential hydrogen ions, electrical conductivity (EC), biological oxygen demand, turbidity, nitrate and phosphate, were chosen to calculate the WQI.

Throughout the study periods, the WQI values varied from 55.2 to 79.83, falling into the categories of four (marginal) and three (fair), with the sixth period (2007–2008) showing the most decline. The present research demonstrated that the high concentration of phosphates, the high EC values, and minor changes in the other environmental factors are the major causes of the decline in water quality. The variations in ecological variables' overlap are a senior contributor to changes in water quality in general. Notably, using GIS in conjunction with the WQI has shown to be very effective in reducing the time and effort spent on investigating water quality while obtaining precise findings and information at the lowest possible expense. Calibration and validation of the developed model showed that this model had a perfect estimate of the WQI value. Due to its flexibility and impartiality, this study recommends using the proposed model to estimate and predict the WQI in the study area.

Even though the water quality of the SAAR has been the subject of numerous studies, this is the only long-term investigation that has been done to evaluate and predict its water quality.