Workers’ satisfaction vis-à-vis environmental and socio-morphological aspects for sustainability and decent work

This study examines worker satisfaction vis-à-vis outdoor places in terms of their environmental and socio-morphological aspects. Numerous studies have considered decent work as the eighth goal of sustainable development. However, it is worth investigating outdoor workers’ satisfaction with a view to the practical design of the surrounding context that supports their work in outdoor places. Using bibliometric analysis, this study investigates possible approaches toward providing decent work in a public place in Cairo as a case study, focusing on outdoor workers’ satisfaction. In the bibliometric analysis, this study used query settings in the Scimago database to search for manuscripts published in the previous five years. The result yielded 195 manuscripts that were filtered down to 50 manuscripts and then grouped using VOSviewr Software. Environmental noise and heat assessment analyses were performed using noise level measurements, remote sensing, and the Grasshopper platform. Further, we conducted an ethnographic study employing 77 participant observations. The results show that work hours and time affect worker satisfaction, as do environmental conditions, particularly noise and heat. However, unexpected findings from participant observation in this study do not accord with findings in other scholarly sources, where other observers find workers neither satisfied nor dissatisfied with the spatial morphology in the case study. Per this study, the alignment of worker satisfaction with convenient socio-morphological tangible elements of the workplace and with other environmental aspects should be attained in both specified replicable methods to engender decent work for outdoor workers

Identifying Flow Networks in a Karstified Aquifer by Application of the Cellular Automata-Based Deterministic Inversion Method (Lez Aquifer, France)

International audienceThe distributed modeling of flow paths within karstic and fractured fields remains a complex task because of the high dependence of the hydraulic responses to the relative locations between observational boreholes and interconnected fractures and karstic conduits that control the main flow of the hydrosystem. The inverse problem in a distributed model is one alternative approach to interpret the hydraulic test data by mapping the karstic networks and fractured areas. In this work, we developed a Bayesian inversion approach, the Cellular Automata‐based Deterministic Inversion (CADI) algorithm to infer the spatial distribution of hydraulic properties in a structurally constrained model. This method distributes hydraulic properties along linear structures (i.e., flow conduits) and iteratively modifies the structural geometry of this conduit network to progressively match the observed hydraulic data to the modeled ones. As a result, this method produces a conductivity model that is composed of a discrete conduit network embedded in the background matrix, capable of producing the same flow behavior as the investigated hydrologic system. The method is applied to invert a set of multiborehole hydraulic tests collected from a hydraulic tomography experiment conducted at the Terrieu field site in the Lez aquifer, Southern France. The emergent model shows a high consistency to field observation of hydraulic connections between boreholes. Furthermore, it provides a geologically realistic pattern of flow conduits. This method is therefore of considerable value toward an enhanced distributed modeling of the fractured and karstified aquifers