Temporal variations of fine and coarse particulate matter sources in Jeddah,Saudi Arabia

This study provides the first comprehensive analysis of the seasonal variations and weekday/weekend differences in fine (aerodynamic diameter <2.5 μm; PM_2.5) and coarse (aerodynamic diameter 2.5–10 μm; PM_2.5–10) particulate matter mass concentrations, elemental constituents, and potential source origins in Jeddah, Saudi Arabia. Air quality samples were collected over 1 yr, from June 2011 to May 2012 at a frequency of three times per week, and analyzed. The average mass concentrations of PM_2.5 (21.9 μg/m³) and PM₁₀ (107.8 μg/m³) during the sampling period exceeded the recommended annual average levels by the World Health Organization (WHO) for PM_2.5 (10 μg/m³) and PM₁₀ (20 μg/m³), respectively. Similar to other Middle Eastern locales, PM_2.5–10 is the prevailing mass component of atmospheric particulate matter at Jeddah, accounting for approximately 80% of the PM₁₀ mass. Considerations of enrichment factors, absolute principal component analysis (APCA), concentration roses, and backward trajectories identified the following source categories for both PM_2.5 and PM_2.5–10: (1) soil/road dust, (2) incineration, and (3) traffic; and for PM_2.5 only, (4) residual oil burning. Soil/road dust accounted for a major portion of both the PM_2.5 (27%) and PM_2.5–10 (77%) mass, and the largest source contributor for PM_2.5 was from residual oil burning (63%). Temporal variations of PM_2.5–10 and PM_2.5 were observed, with the elevated concentration levels observed for mass during the spring (due to increased dust storm frequency) and on weekdays (due to increased traffic). The predominant role of windblown soil and road dust in both the PM_2.5 and PM_2.5–10 masses in this city may have implications regarding the toxicity of these particles versus those in the Western world where most PM health assessments have been made in the past. These results support the need for region-specific epidemiological investigations to be conducted and considered in future PM standard setting.

Implications: Temporal variations of fine and coarse PM mass, elemental constituents, and sources were examined in Jeddah, Saudi Arabia, for the first time. The main source of PM_2.5–10 is natural windblown soil and road dust, whereas the predominant source of PM_2.5 is residual oil burning, generated from the port and oil refinery located west of the air sampler, suggesting that targeted emission controls could significantly improve the air quality in the city. The compositional differences point to a need for health effect studies to be conducted in this region, so as to directly assess the applicability of the existing guidelines to the Middle East air pollution.     

Photocatalytic oxidation of the textile dye basic red 18 with irradiated titanium dioxide

One of the major problems of textile wastewater is the presence of dye materials, because colour is visible to the public even if the dye concentration is lower than other pollutants, and needs therefore to be removed from the wastewater before it is discharged. Techniques based on “advanced oxidative processes” such as photocatalysed oxidation seem to be very promising for industrial wastewater treatment, especially for decolourization of textile effluents. In this work, we describe the photocatalytic degradation of the textile dye Basic Red 18 (BR 18) in aqueous solution using two different types of TiO₂ as photocatalyst: Degussa P25 (80% anatase) and Framitalia (100% anatase). Photooxidation of BR 18 was followed by HPLC analysis, and kinetic parameters were evaluated in order to optimise the treatment procedure. The results obtained in this work showed that the colour became virtually zero and the chemical oxygen demand (COD) is strongly reduced at the end of the treatment. The obtained results are compared with the efficiency of decolourization using the H₂O₂/UV System. Finally, marine mussel test was used to evaluate the efficiency of photocatalytic oxidation with TiO₂ in terms of ecotoxicity. A significant reduction of cumulative mortality was observed for the treated effluent.     

A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry

Natural gas plants demand high amount of energy provided through immense fuel gas units that may suffer risk hazards. Implementing a safety management system is the most efficient way of allocating resources for safety. This paper adopts The Layer of Protection Analysis (LOPA) risk Management associated with Fuzzy Logic methodology to prevent or limit industrial accidents. We provide an innovative cascaded fuzzy-LOPA model for certain hazardous scenarios and at different frequencies of occurrence. The introduced model is tested at moderate and high risk levels controlled in its practical limits through the use of Safety Integrity Functions (SIF). Obtained results show how this fuzzy-LOPA achieves better results to maintain the Safety Integrity Level (SIL) rating to acceptable limits.     

A Parallel Computation Tool to Enable Dynamic Sensitivity and Model Performance Analysis of APEX: Evapotranspiration Modeling

Global sensitivity analysis can be used for assessing the relative importance of model parameters on model outputs. The sensitivity of parameters usually indicates a temporal variation due to variation in the environmental conditions (e.g., variation in weather or plant growth). In addition, the size of averaging window by which the outputs of a model are aggregated or averaged may impact parameter sensitivities. In this study, temporal variation of parameters sensitives, model performance, as well as the impact of the size of time‐averaging window on evapotranspiration (ET) prediction using the Agricultural Policy/Environmental eXtender (APEX) model are investigated. To achieve these goals, an open‐source package named PARAPEX was developed in R and used to perform dynamic sensitivity and model performance analysis of APEX using parallel computation. PARAPEX reduced the computation time from 5,939 to 379 s (using 20 and 1 computation nodes, respectively). The sensitivity analysis results indicated the parameters accounting for the reducing effect of plant cover on evaporation from the soil surface, the effect of soil on the plant root growth, and the effect of cycling and transformation dynamics of organic matter at the top soil layer as the top sensitive parameters based on the mean daily simulated ET and the Nash–Sutcliffe model performance measure. The dynamic performance analysis indicated poor ET predictions by APEX during the growing seasons. Editor's note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

Anti-angiogenic effects of aqueous extract from Agrostemma githago L. seed in human umbilical vein endothelial cells via regulating Notch/VEGF,MMP2/9, ANG2, and VEGFR2

Environmental Science and Pollution Research - Abnormal angiogenesis contributes to the pathogenesis of various diseases. The medicinal usage of Agrostemma githago L. seed (A. githago herein) has...     

Subnational exposure to secondhand smoke in Iran from 1990 to 2013: a systematic review

Environmental Science and Pollution Research - Every year, almost eight million people die from tobacco-related diseases, among which around 1.2 million die from secondhand smoke (SHS) exposure....     

Sustainable rangeland management using a multi-fuzzy model: how to deal with heterogeneous experts' knowledge

While fuzzy specialists commonly use homogeneous experts' knowledge to construct fuzzy models, it is much more difficult to deal with knowledge elicited from a heterogeneous group of experts. This issue is exemplified in the area of sustainable rangeland management (SRM). One way to deal with the diversity of opinions is to develop a fuzzy system for all experts and to combine all these, the so-called primary systems, into one multi-fuzzy model. To derive each of the primary fuzzy systems, several semi-structured interviews were held in three different areas of the Fars province in Southwest Iran using the knowledge of a group of administrative experts. To obtain the final output of the multi-fuzzy model, we applied different 'voting' methods. The first method simply uses the arithmetic average of the primary outputs as the final output of the multi-fuzzy model. This final output represents an estimation of the right rate of stocking (RRS). We also propose other (un)supervised voting methods. Most importantly, by harmonising the primary outputs such that outliers get less emphasis, we introduce an unsupervised voting method for calculating a weighted estimate of the RRS. This harmonising method is expected to provide a new useful tool for policymakers dealing with heterogenity in experts' opinions: it is especially useful where limited field data are available and one is forced to rely on experts' knowledge only. By constructing the three fuzzy models based on the elicitation of heterogeneous experts' knowledge, our study shows the multidimensional vaguenesses that exist in SRM. Finally, by comparing the final RRS with its common values, this study strongly points to the existence of overgrazing in pastures in the three regions of the Fars province in Southwest Iran.