## 1 Introduction  
The importance of proper lighting conditions (i.e., visual comfort) at academic institutions has been emphasized at all levels, from elementary, primary, and secondary education schools [1; 2; 3; 4; 5; 6] to university faculties [7; 8; 9; 10; 11; 12; 13; 14; 15; 16]. In general, it can be said that comfort in academic environments has been widely analyzed as it has important effects on learning. On this subject and attending to the available literature, three main different aspects can be underlined in first place: thermal comfort, noise comfort, and visual comfort [17; 12; 14]. After them, other less relevant aspects such as wall colors, furniture, spatial arrangements, ventilation, etc. can also be added when analyzing the aforementioned comfort in academic institutions [4; 10; 12; 13; 15]. Visual comfort mainly depends on lighting. However, it is somehow affected by thermal and noise levels [17; 14]. In the available literature, some examples were found of lighting analysis in classrooms and other academic environments [8; 18; 19; 20; 21; 22; 23]. Some of these focused mainly on energy costs and efficiency [18; 20; 21; 23], as lighting represents about 20% of the world's demand for electrical energy production [23]. On the other hand, many analyses on visual comfort and the effects of lighting seem to be based on surveys/interviews rather than measuring the illuminance levels [5; 6; 11; 12; 15]. Even those works that reflect lighting measurements include surveys [13; 16; 24; 25], adding subjective (and statistical) factors to the study. Many of the studies on lighting similar to the present one found in the available literature were conducted using DIALux(r)[8; 19; 20; 21; 22; 23], although it seems that there are many possibilities when it comes to lighting simulation tools [26; 27; 28; 29]. However, leaving aside some works related to validation of lighting analysis software [30; 31; 32; 33], there seems to be a lack of studies evaluating the accuracy in the prediction of actual lighting results. Finally, it is worth mentioning the quite high accuracy in artificial lighting simulations (0.5% average error) reported by [PERSON] et al. [33]. This paper discusses the results of research conducted on the current lighting in the classrooms of the _Universidad Politecnica de Madrid_ (UPM) Faculty of Aerospace Engineering (_Escuela Tecnica Superior de Ingenieria Aeronautica y del Espacio_ (ETSIAE), see Section 2) without daylight (that is, during evening/night periods and with the window blinds lowered) and analyzes different proposals for improving it. To this end, illuminance was measured on student desks and blackboards in 39 classrooms, including those used for exams. This study excludes other areas of the faculty with special characteristics, such as the library, computer rooms, laboratories, and other common areas. It was considered relevant to focus on this group of classrooms, where students and instructors spend most of their time and where lighting quality is most crucial. Measurements were carried out by measuring the illuminance levels on the selected surfaces (blackboards and desks) with a lux meter. This is a quite direct and simple technique that allowed a first evaluation of a quite relevant problem. However, it is somehow limited when compared to High Dynamic Range (HDR) imaging technology [24; 25; 34; 35], as it does not give other interesting variables such as glare. In addition, it should also be said that the selection of illuminance as a lighting-quality variable has some drawbacks, as it might not correlate well with perceived brightness or visual comfort. [PERSON] [36] suggested the use of the Perceived Adequacy of Illumination (PAI) as an alternative to minimum illuminance levels in standards, this concept of lighting being quantified by Mean Room Surface Exitance (MRSE) as a control variable.