Distribution of trace elements in tissues of two shrimp species from the Persian Gulf and roles of metallothionein in their redistribution

This study investigates the distribution of three trace elements (Cd, Cu and Zn) in tissues (exoskeleton, abdominal muscle and hepatopancreas) of two shrimp species (Penaeus merguiensis and Penaeus semisulcatus). Special emphasis in this study was placed on evaluating the effects of storage conditions on redistribution of the elements and moreover the potential roles of metallothionein in tissue redistribution. The specimens were collected from the northern part of Persian Gulf during September 2001 and January 2002. The concentrations of metals in the tissues were measured using an Inductively Coupled Plasma-Atomic Emission Spectrophotometer (ICP-AES) and an ICP-Mass Spectrometer (ICP-MS). Metallothionein levels were determined using Differential pulse polarography. Results show a similar hierarchy for Cd and Cu concentrations among different tissues as follows: hepatopancreas>exoskeleton>muscle; and for Zn, the hepatopancreas again contained the highest levels, though there were not any significant differences in Zn concentrations between muscle and exoskeleton. Significant differences were found between the species in the case of Cd and Zn concentrations. Cd and Zn levels in P. semisulcatus were markedly higher than in P. merguiensis. In general, there were highly significant differences among the storage conditions from accumulation the selected trace elements and metallothionein in both species point of view, but in most cases, no significant differences could be observed among the fresh, refrigerated and frozen specimens of P. semisulcatus. In regards to Zn and Cu accumulation in edible (muscle) tissues of P. merguiensis, optimum conditions for frozen storage is -30 degrees C as ice-frozen, and in terms of short-term storage, 1-day refrigeration is recommended. The redistribution of Zn and Cu during the storage period can be attributed to the role of metallothionein in their transport from organ(s) to muscle during storage. The variations in pH values measured in the muscle of P. merguiensis in different storage conditions showed a similar trend with metallothionein, Zn and Cu. In contrast, it appears that cadmium is transported from muscle to the other tissues. Exoskeleton is probably one of the recipient tissues of cadmium. The inter-elemental relationships were assessed for each species, separately. A significant positive relationship was observed between the concentrations of Zn and metallothionein in P. semisulcatus, whereas in P. merguiensis, Cd concentrations decreased significantly with increasing metallothionein. Highly significant differences between the sexes in Cu and Zn contents could be detected. The differences between the sexes in the levels of Zn and Cu were significantly greater in P. semisulcatus. Highly significant size-related differences were found in the levels of Cd, Cu and metallothionein in the selected tissues of the shrimp species. Comparison between the mean concentrations of the elements in muscle tissue and existing guidelines indicate that in nearly all cases, the concentrations were well below permissible levels for human consumption. The only exception was observed regarding mean values of Cd, which was somewhat greater than some of the recommended levels.     

Source apportionment of atmospheric polycyclic aromatic hydrocarbons (PAHs) in Palm Beach County,Florida

Due to concerns about adverse health effects associated with inhalation of atmospheric polycyclic aromatic hydrocarbons (PAHs), 30 ambient air samples were obtained at an air quality monitoring station in Palm Beach County, Florida, from March 2013 to March 2014. The ambient PAH concentration measurements and fractional emission rates of known sources were incorporated into a chemical mass balance model, CMB8.2, developed by EPA, to apportion contributions of three major PAH sources including preharvest sugarcane burning, mobile vehicles, and wildland fires. Strong association between the number of benzene rings and source contribution was found, and mobile vehicles were identified to be the prevailing source (contribution ≥56%) for the observed PAHs concentration with lower molecular weights (four or fewer benzene rings) throughout the year. Preharvest sugarcane burning was the primary contributing source for PAHs with relatively higher molecular weights (five or more benzene rings) during the sugarcane burning season (from October to May of the next year). Source contribution of wildland fires varied among PAH compounds but was consistently lower than for sugarcane burning during the sugarcane harvest season. Determining the major sources responsible for ground-level PAHs serves as a tool to improving management strategies for PAH emitting sources and a step toward better protection of the health of residents in terms of exposure to PAHs. The results obtain insight into temporal dominance of PAH polluting sources for those residential areas located near sugarcane burning facilities and have implications beyond Palm Beach County, in areas with high concerns of PAHs and their linked sources.

Implications: Source apportionment of atmospheric polycyclic hydrocarbons (PAHs) in Palm Beach County, Florida, meant to estimate contributions of major sources in PAH concentrations measured at Belle Glade City of Palm Beach County. Number of benzene rings was found to be the key parameter in determining the source with the prevailing contribution. Mobile vehicle sources showed a higher contribution for species with four or fewer benzene rings, whereas sugarcane burning contributed more for species with five or more benzene rings. Results from this study encourage more control for sugarcane burns and help to better manage authorization of the sugarcane burning incidents and more restrictive transportation plans to limit PAH emissions from mobile vehicles.     

Distribution of heavy metals in Penaeus Semisulcatus from Persian Gulf and possible role of metallothionein in their redistribution during storage

The study was conducted between January and December 2002. The main objective of this study was evaluation of effects of refrigerated storage duration on redistribution of three trace elements (Cd, Cu and Zn) in tissues (exoskeleton, abdominal muscle and hepatopancreas) of a shrimp species (Penaeus semisulcatus). Moreover, the possible roles of metallothionein (a kind of metalloprotein) in redistribution of the elements in tissues of the selected species were assessed. The specimens were sampled from northwestern part of the Persian Gulf. The concentrations of metals in the tissues were measured using Inductively Coupled Plasma-Optical Emission Spectrophotometer (ICP-OES). Metallothionein levels were determined by Differential Pulse Polarography (DPP) method. pH of the muscle samples was also measured in different stages. Different statistical methods were used for interpretation of the results. There were no size-dependent differences in metal contents of the species. The results were compared with specimens from other areas of the world and existing guidelines and limits. Concentrations of the metals in the muscle (0.103, 3.418 and 8.977 µg g^–1 wet weight in the case of Cd, Cu and Zn, respectively) samples were below the most guidelines for human consumption. The results were in general agreement with those obtained by some other researchers. There were highly significant differences between sexes in Zn and Cu contents. Levels of Zn in females were significantly higher than males. The reverse case observed for Cu. The highest mean Cu and Zn concentrations (15.939 and 43.394 µg g^–1 wet weight, respectively) were found in hepatopancreas samples, but the highest level of Cd (0.790 µg g^–1 wet weight) was observed in exoskeleton. There were significant differences between the fresh and refrigerated samples from accumulation of Cd and Zn in tissues point of view, which can be attributed to the metal binding properties of metallothioneins as well as their degradation during the storage.     

Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NO_x), nitrogen dioxide (NO₂), nitrogen monoxide (NO), ozone (O₃), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM₁₀) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R ² of more than 0.82 between modeled and observed hourly pollutant levels for CO, NO_x, NO₂, NO, and PM₁₀. However, predicted O₃ levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.