Broiler production in modern poultry farms commonly uses mechanical ventilation systems. This mechanical ventilation requires an amount of electric energy and a high level of investment in technology. Nevertheless, broiler production is affected by periodic problems of mortality because of thermal stress, thus being crucial to explore the ventilation efficiency. In this article, we analyze a cross-mechanical ventilation system focusing on air velocity distribution. In this way, two methodologies were used to explore indoor environment in livestock buildings: Computational Fluid Dynamics (CFD) simulations and direct measurements for verification and validation (V&V) of CFD. In this study, a validation model using a Generalized Linear Model (GLM) was conducted to compare these methodologies. The results showed that both methodologies were similar in results: the average of air velocities values were 0.60 ± 0.56 m s⁻¹ for CFD and 0.64 ± 0.54 m s⁻¹ for direct measurements. In conclusion, the air velocity was not affected by the methodology (CFD or direct measurements), and the CFD simulations were therefore validated to analyze indoor environment of poultry farms and its operations. A better knowledge of the indoor environment may contribute to reduce the demand of electric energy, increasing benefits and improving the thermal comfort of broilers.

Monitoring temperature and relative humidity of the environment to which artefacts are exposed is fundamental in preventive conservation studies. The common approach in setting measuring instruments is the choice of a high sampling rate to detect short fluctuations and increase the accuracy of statistical analysis. However, in recent cultural heritage standards the evaluation of variability is based on moving average and short fluctuations and therefore massive acquisition of data in slowly-changing indoor environments could end up being redundant. In this research, the sampling frequency to set a datalogger in a museum room and inside a microclimate frame is investigated by comparing the outcomes obtained from datasheets associated with different sampling conditions. Thermo-hygrometric data collected in the Sorolla room of the Pio V Museum of Valencia (Spain) were used and the widely consulted recommendations issued in UNI 10829:1999 and EN 15757:2010 standards and in the American Society of Heating, Air-Conditioning and Refrigerating Engineers (ASHRAE) guidelines were applied. Hourly sampling proved effective in obtaining highly reliable results. Furthermore, it was found that in some instances daily means of data sampled every hour can lead to the same conclusions as those of high frequency. This allows us to improve data logging design and manageability of the resulting datasheets.

The mudéjar church of Santa María (Ateca) is valuable for its architecture and the altarpiece contained inside. Ateca is a village with continental climate characterized by cold winters and hot summers. In this paper we are interested in analysing the effect of temperature and relative humidity (RH) changes produced by the heating system on the altarpiece. Therefore, a monitoring system of 15 temperature and 15 relative humidity sensors was installed with a recording frequency of a data point per minute. The main contribution of this paper is the quantitative study of the effect of the heating system on the thermo-hygrometric parameters using statistical techniques such as ANOVA, mean daily trajectories or bivariate plots, and the proposal of an innovative dynamic contour plot. As results, the heating system produces a substantial increase (decrease) of temperature (RH) causing an hourly variation of these physical parameters detrimental to the conservation of the altarpiece, especially in its higher areas.

The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization of the thermo-hygrometric conditions of Casa di Diana (Ostia Antica, Italy) is carried out analyzing the data of temperature and relative humidity recorded by a system of sensors with high monitoring frequency. Sensors are installed in parallel, calibrated and synchronized with a microcontroller. A data set of 793,620 data, arranged in a matrix with 66,135 rows and 12 columns, was used. Furthermore, the influence of human impact (visitors) is evaluated through a multiple linear regression model and a logistic regression model. The visitors do not affect the environmental humidity as it is very high and constant all the year. The results show a significant influence of the visitors in the upset of the thermal balance. When a tourist guide takes place, the probability that the hourly temperature variation reaches values higher than its monthly average is 10.64 times higher than it remains equal or less to its monthly average. The analysis of the regression residuals shows the influence of outdoor climatic variables in the thermal balance, such as solar radiation or ventilation.

Preventive conservation requires monitoring and control of the parameters involved in the deterioration process, mainly temperature and relative humidity. It is important to characterise an archaeological site prior to carrying out comparative studies in the future for preventive conservation, either by regular studies to verify whether the conditions are constant, or occasional ones when the boundary conditions are altered. There are numerous covered archaeological sites, but few preventive conservation works that give special attention to the type of cover installed. In particular, there is no background of microclimatic studies in sites that are in the ground and, as in the Plaza de l’Almoina (Valencia, Spain), are buried and partially covered by a transparent roof. A large effect of the transparent cover was found by the sensors located below this area, with substantial increases in temperature and a decrease in the relative humidity during the day. Surrounding zones also have values above the recommended temperature values. On the other hand, the influence of a buried water drainage line near the site is notable, causing an increase in relative humidity levels in the surrounding areas. Multivariate statistical analyses enabled us to characterise the microclimate of the archaeological site, allowing future testing to determine whether the conservation conditions have been altered.

Cultural Heritage preventive conservation requires the monitoring of the parameters involved in the process of deterioration of artworks. Thus, both long-term monitoring of the environmental parameters as well as further analysis of the recorded data are necessary. The long-term monitoring at frequencies higher than 1 data point/day generates large volumes of data that are difficult to store, manage and analyze. This paper presents software which uses a free open source database engine that allows managing and interacting with huge amounts of data from environmental monitoring of cultural heritage sites. It is of simple operation and offers multiple capabilities, such as detection of anomalous data, inquiries, graph plotting and mean trajectories. It is also possible to export the data to a spreadsheet for analyses with more advanced statistical methods (principal component analysis, ANOVA, linear regression, etc.). This paper also deals with a practical application developed for the Renaissance frescoes of the Cathedral of Valencia. The results suggest infiltration of rainwater in the vault and weekly relative humidity changes related with the religious service schedules.