Soil Quality and Evaluation of Spatial Variability in a Semi-Arid Ecosystem in a Region of the Southeastern Iberian Peninsula (Spain)

In the last two decades, as the importance of soil has been recognized as a key component of any ecosystem, there has been an increased global demand to establish criteria for determining soil quality and to develop quantitative indices that can be used to classify and compare that quality in different places. The preliminary estimation of the attributes involved in soil quality was made taking into account the opinion of the experts and our own experience in a semi-arid ecosystem. In this study, 16 soil properties have been selected as potential indicators of soil quality, in a region between Campo de Montiel and Sierra de Alcaraz (Spain): sand and clay percentage, pH, electrical conductivity (EC), soil organic carbon (OC), extractables bases of change (Na, K, Ca and Mg), cationic exchange capacity (CEC), carbonate calcium equivalent (CCE), bulk density (BD), water retention at 33 kPa field capacity and 1500 kPa permanent wither point (GWC33 kPa and GWC1500 kPa), coefficient of linear extensibility (COLE) and factor of soil erodibility (K). The main objective has been to develop an adequate index to characterize the quality of the soils in a semi-arid Mediterranean ecosystem. The preliminary estimation of the attributes involved in soil quality was made considering the opinion of the experts and our own experience in semi-arid ecosystems. Two indicator selection approaches have been used to develop the Soil Quality Index (SQI) (total data set -TDS- and minimum data set -MDS-), scoring functions (linear -L- and nonlinear -NL-) and methods (additive -A-, additive weighted -W- and Nemoro -N-. The quality indices have been calculated, considering the properties of the soil control section (between 0 and 100 cm depth), using 185 samples, belonging to horizons A, B and C of 51 soil profiles. The results have shown that the election of the soil properties, both of the topsoil and subsoil, is an important help in establishing a good relationship between quality, soil functions and agricultural management. The Kriging method has been used to determinate the spatial distribution of the soil quality grades. The indices that best reflect the state of soil quality are the TDS-L-W and TDS-L-A should go as sub-indices, as they are the most accurate indices and provide the most consistent results. These indices are especially indicated when carrying out detailed or semi-detailed studies. However, the MDS-L-W and MDS-L-A should go as sub-indices, which use only a limited number of indicators, are best for large-scale studies. The indicators with the greatest influence on soil quality for different land uses and those developed on different rocks, using linear scoring functions, are the following: (Clay), (GWC1500 kPa) and (Ca). These results can also be expressed as follows: the best soils in this region are deep soils, with a clay texture, with high water retention and a neutral or slightly basic pH. However, the indicators with the greatest influence on soil quality, using nonlinear scoring functions, are: (OC Stock), (Ca) and (CaCO3). In other words, the most important indicator is the organic carbon content, which is not logical in the case of a region in which the soils have an excessively low SOC content (0.86%).

Comparison of CP-PC-SAFT and SAFT-VR-Mie in Predicting Phase Equilibria of Binary Systems Comprising Gases and 1-Alkyl-3-methylimidazolium Ionic Liquids

This study compares performances of the Critical Point-based revision of Perturbed-Chain SAFT (CP-PC-SAFT) and the SAFT of Variable Range and Mie Potential (SAFT-VR-Mie) in predicting the available data on VLE, LLVE, critical loci and saturated phase densities of systems comprising CO, O2, CH4, H2S, SO2, propane, the refrigerants R22, R23, R114, R124, R125, R125, R134a, and R1234ze(E) and ionic liquids (ILs) with 1-alkyl-3-methylimidazolium ([Cnmim]+) cations and bis(trifluoromethanesulfonyl)imide ([NTf2]−), tetrafluoroborate ([BF4]−) and hexafluorophosphate ([PF6]−) anions. Both models were implemented in the entirely predictive manner with k12 = 0. The fundamental Global Phase Diagram considerations of the IL systems are discussed. It is demonstrated that despite a number of quantitative inaccuracies, both models are capable of reproducing the regularities characteristic for the considered systems, which makes them suitable for preliminary estimation of selectivity of the ILs in separating various gases.

Developing a framework for evaluating construction project safety levels and optimal cost allocation to safety influential factors

PurposeThis study aimed to explain how a framework could be developed for (1) the preliminary estimation of project safety level (PSL) in current projects, (2) the estimation of the maximum possible PSL using limited financial resources and (3) the estimation of the minimum financial resources required for reaching a specific PSL.Design/methodology/approachThe data of 95 steel structural building projects were collected via a questionnaire to evaluate the proposed framework for the Iranian construction industry. Based on unofficial local construction statistics and literature reviews, six safety influential factors (SIFs) were selected to which a cost could be assigned. The costs associated with various levels were also determined for each SIF through literature reviews and expert interviews. A multiple linear regression (MLR) model was developed as a predictive model to determine PSL for future projects based on the data of previous projects. Moreover, linear programming (LP) was applied to take modeling constraints and project conditions into account.FindingsThe results demonstrated the impacts of all the factors on PSL and the model's potential for the preliminary estimation of PSL using SIFs. The results also indicated that a higher PSL could be achieved by optimizing the allocation of financial resources to each SIF.Originality/valueThis study contributes to the existing body of knowledge by developing a step-by-step framework to identify an optimal safety cost allocation (OSCA) to achieve the maximum possible PSL using a limited safety budget and considering the data of similar projects. The main objective was to promote project safety, decrease construction site injuries and fatalities and help local construction industries exploit potential financial advantages.