Bio-indicators in cadmium toxicity: Role of HSP27 and HSP70

Environmental Science and Pollution Research - Heat shock proteins (HSPs) are a family of proteins that are expressed by cells in reply to stressors. The changes in concentration of HSPs could be...     

High potential for the formation of haloacetic acids in the Karoon River water in Iran

The impact of the total organic carbon (TOC), chlorine dosage, water temperature, reaction time, pH, and seasonal variation on the formation of haloacetic acids (HAAs) in the Karoon River in Iran was studied. The results showed that dichloroacetic acid and trichloroacetic acid were the most detected HAA₅. The HAA₅ formation potential (HAA₅FP) levels in the Karoon River water in spring time, when the water TOC content exceeded 4 mg/L, were 1.38 times higher than during the winter season, when the water TOC content was below 3.5 mg/L. There was not a strong correlation between the HAA₅FP and the residence time for the Karoon River water. For the range of the water temperatures studied, there was little variation in the HAA₅FP in cold water, but in warmer water, the values of the HAA₅FP varied quickly.     

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF_G) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF_G techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF_G technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.     

Multi-response optimization of Fenton process for applicability assessment in landfill leachate treatment

Fenton process, as a pretreatment method, was found to be effective in the primary treatment of mature/medium landfill leachate. However, the main problem of the process is the large amount of produced sludge that requires an accurate feasibility evaluation for operational applications. In this study, the response surface methodology was applied for the modeling and optimization of Fenton process in three target responses, (1) overall COD removal, (2) sludge to iron ratio (SIR) and (3) organics removal to sludge ratio (ORSR), where the latter two were new self-defined responses for prediction of sludge generation and applicability assessment of the process, respectively. The effective variables included the initial pH, [H₂O₂]/[Fe²⁺] ratio and Fe²⁺ dosage. According to the statistical analysis, all the proposed models were adequate (with adjusted R² of 0.9116–0.9512) and had considerable predictive capability (with prediction R² up to 0.9092 and appropriate adequate precision). It was found that all the variables had significant effects on the responses, specifically by their observed role in dominant oxidation mechanism. The optimum operational conditions obtained by overlay plot, were found to be initial pH of 5.7, [H₂O₂]/[Fe²⁺] ratio of 17.72 and [Fe²⁺] of 195 mM, which led to 69% COD removal, 2.4 (l sludge/consumed mole Fe²⁺) of SIR and 16.5 (gCOD removed/l produced sludge) for ORSR in verification test, in accordance with models-predicted values. Finally, it was observed that [H₂O₂]/[Fe²⁺] ratio and Fe²⁺ dosage had significant influence on COD removal, while Fe²⁺ dosage and [H₂O₂]/[Fe²⁺] ratio had remarkable effects on SIR and ORSR responses, respectively.     

Modelling volatility of growth rate in atmospheric carbon dioxide concentrations in a Bayesian approach

Atmospheric gases, such as carbon dioxide, ozone, methane, nitrous oxide, and etc., create a natural greenhouse effect and cause climate change. Therefore, modelling behavior of these gases could help policy makers to control greenhouse effects. In a Bayesian framework, we analyse and model conditional variance of growth rate in atmospheric carbon dioxide concentrations (ACDC) using monthly data from a subset of the well known Mauna Loa atmosphere carbon dioxide record. The conditional variance of ACDC monthly growth rate is modelled using the autoregressive conditional heteroscedasticity (ARCH), generalized ARCH model (GARCH) and a few variants of stochastic volatility (SV) models. Smooth transition ARCH and GARCH models are shown to be able to capture the dynamics in the conditional variance in ACDC level growth rate and to improve the forecast performance of ACDC growth rate.     

Application of pier waste sludge for catalytic activation of proxy-monosulfate and phenol elimination from a petrochemical wastewater

This investigation aimed to remove phenol from real wastewater (taken from a petrochemical company) by activating peroxy-monosulfate (PMS) using catalysts extracted from pier waste sludge. The physical and chemical properties of the catalyst were evaluated by FE-SEM/EDS, XRD, FTIR, and TGA/DTG tests. The functional groups of O–H, C–H, CO₃^2?, C–H, C–O, N–H, and C–N were identified on the catalyst surface. Also, the crystallinity of the catalyst before and after reaction with petrochemical wastewater was 103.4 nm and 55.8 nm, respectively. Operational parameters of pH (3–9), catalyst dose (0–100 mg/L), phenol concentration (50–250 mg/L), and PMS concentration (0–250 mg/L) were tested to remove phenol. The highest phenol removal rate (94%) was obtained at pH=3, catalyst dose of 80 mg/L, phenol concentration of 50 mg/L, PMS concentration of 150 mg/L, and contact time of 150 min. Phenol decomposition in petrochemical wastewater followed the first-order kinetics (k> 0.008 min^?1, R²> 0.94). Changes in pH factor were very effective on phenol removal efficiency, and maximum efficiency (≈83%) was achieved in pH 3. The catalyst stability test was performed for up to five cycles, and phenol removal in the fifth cycle was reduced to 42%. Also, the energy consumption in this study was 77.69 kW h/m³. According to the results, the pier waste sludge catalyst/PMS system is a critical process for eliminating phenol from petrochemical wastewater.

     

A risk-based decision making approach to determine fireproofing requirements against jet fires

API Publication 2218 is one of the most referred practices for fireproofing of onshore structural supports. Despite the extensive citation, it solely considers the effects of pool fire and rarely addresses jet fire outcomes. This absence of an explicit approach is common among all the other major references. Therefore, the basic objective of this paper is to introduce a new approach for determination of the necessity for fireproofing of structural supports against jet fires. For this purpose, the flame geometry and duration of jet fires are simulated for different leak sizes in identified fire potential sources. Then, following a worst-case analysis, those structures that may be impinged by long enough flames are screened out and then characterized by maximum impingement duration for fireproofing purpose. Moreover, each structure is assigned by a failure rate to estimate the degree of vulnerability through a detailed risk assessment. In this regard a new explanatory term called Structure Failure Rate (SFR) is introduced. This approach also enables researchers to quantify the effect of other protective systems (fire and gas detection, emergency shut-down, depressurization and firewalls) on the level of required fireproofing.     

Domino effect in process-industry accidents - An inventory of past events and identification of some patterns

The paper presents an inventory, perhaps the most comprehensive till date, of the major process-industry accidents involving ‘domino effect’. The inventory includes, among other relevant information, the sequence of accidents that had occurred in each domino episode. The information has been analyzed to identify several patterns which may be useful in further work on understanding domino effect and reducing the probability of its occurrence in future. A concept of ‘local domino effect’ has been introduced.