Organic PCMs affect HDPE and PP mechanical properties. HDPE strength is remarkably partly restored by the homogeneous distribution of absorbed PCM.

A methodology to predict PM₁₀ concentrations in urban outdoor environments is developed based on the generalized linear models (GLMs). The methodology is based on the relationship developed between atmospheric concentrations of air pollutants (i.e. CO, NO₂, NO_x, VOCs, SO₂) and meteorological variables (i.e. ambient temperature, relative humidity (RH) and wind speed) for a city (Barreiro) of Portugal. The model uses air pollution and meteorological data from the Portuguese monitoring air quality station networks. The developed GLM considers PM₁₀ concentrations as a dependent variable, and both the gaseous pollutants and meteorological variables as explanatory independent variables. A logarithmic link function was considered with a Poisson probability distribution. Particular attention was given to cases with air temperatures both below and above 25°C. The best performance for modelled results against the measured data was achieved for the model with values of air temperature above 25°C compared with the model considering all ranges of air temperatures and with the model considering only temperature below 25°C. The model was also tested with similar data from another Portuguese city, Oporto, and results found to behave similarly. It is concluded that this model and the methodology could be adopted for other cities to predict PM₁₀ concentrations when these data are not available by measurements from air quality monitoring stations or other acquisition means.

Traditional ewe’s cheese producers face certain challenges caused by fluctuating environmental parameters inside the ripening room, which lead to lack of homogeneity in the final product. The present research discusses the application of computer fluid dynamics for simulating the distribution of environmental parameters, predicting the airflow pattern, and identifying critical areas where such parameters could cause reduced cheese quality. A new monitoring system was developed including presence sensors, temperature and humidity dataloggers, pneumatic actuators, microcontrollers, and microcomputers connected remotely for control, data visualization, and processing. The validation of the computer simulation and monitoring system was made with a batch of 40 ewe’s cheeses distributed in three different zones inside a prototype ripening room and ripened for 35 days. At 35 days, a physical, chemical, and microbiological characterization of cheeses was made for evaluation of the influence of environmental conditions on cheese quality. The comparison between simulated and local measurements showed close agreement, especially concerning air velocity inside the stacks of cheese. The results of Pearson’s correlation analysis and PCA concluded that temperature affected the appearance of the rind, hardness, number and area occupied by holes. Humidity affected a_w and mFeret. Air velocity affected pH and the circularity of gas holes.