Potentially Toxic Elements' Accumulation in Relation to Sediment Physicochemical Attributes and Microplastic Content in Zayandeh-Rood River, Iran

Microplastics (MPs) are an emerging pollutant whose ability to adsorb potentially toxic elements (PTEs) poses a serious threat to aquatic ecosystems, including rivers. In highly developed basins, the abundance of MPs in river sediment is expected to be high, elevating the sedimentary accumulation of PTEs. This hypothesis was tested in the Zayandeh-Rood River, Central Iran, with 21 sediment sampling stations distributed along the entire river stretch. Results of sediment analysis showed significant variations in the abundance and size of MPs, with concentrations ranked as Ba (270.71 mg/kg) > Li (21.29 mg/kg) > Cs (2.50 mg/kg) > Be (1.44 mg/kg) > Sn (1.17 mg/kg) > Mo (1.06 mg/kg) > Ag (0.76 mg/kg), along with sediment physicochemical attributes such as EC, TOC, pH and grain size. MPs were identified in all sediment samples with a mean of 588 items/kg dry weight. Except for Ag, all other PTEs were classified as uncontaminated but exhibited increased enrichment downstream. According to the results of the generalized additive model (maximum R-sq of 0.766), the sedimentary concentration of the majority of PTEs is nonlinearly and positively associated with smaller and more abundant MPs. This study acknowledges that MPs might influence sediment porosity, permeability and structure, thereby directly affecting the settling dynamics of other particles, especially PTEs.

Health effects of exposure to urban ambient particulate matter: A spatial-statistical study on 3rd-trimester pregnant women

Pregnant women are highly vulnerable to environmental stressors such as ambient particulate matter (PM). Particularly during their 3rd trimester, their bodies undergo significant oxidative stresses. To further consolidate this dialogue into practice, the current study evaluated healthy pregnant women (n = 150 housewives; 18-40 years old; gestation age >36 weeks) from the highly polluted city of Yazd, Iran, from September to November 2021. The aerosol optical depth (AOD) data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) were employed as influencing variables and validated using field-collected PM10 data (r = 0.62, p-value <0.01). The links between blood platelet count, enzymes (SGOT, SGPT, LDH, bilirubin), metabolic products (urea and acid uric) and different combinations of AOD data were assessed using the Generalized Additive Model. The results showed a high temporal variability in AOD (0.94 ± 0.51) but a spatially stable distribution pattern. The mean AOD during the 3rd trimester, followed by that of the three-month peak, were identified as the most significant non-linear predictors, while the mean AOD during the 1st trimester and throughout the entire pregnancy showed no significant associations with any of the biomarkers. Considering the associations found between AOD variables and maternal oxidative stresses, urgent planning is required to improve the urban air quality for sensitive subpopulations.

Sediment-connected Potentially Toxic Element Contamination and Phytoremediation Potential of Native Aquatic Macrophytes along the Jajrood River, Tehran Province, Iran

This study was conducted to analyze Cu, Fe, and Pb contamination in sediments and also phytoremediation ability of bulrush (Typha Latifolia) and one-rowed water-cress (Nasturtium microphyllum) along the Jajrood River, Iran in 2022. In so doing, a total of 60 sediment and macrophyte samples were collected from four sites. The contents of the analyzed elements were determined using inductively coupled plasma-optical emission spectroscopy (ICP-OES). Also, the values of pollution index (PI), pollution load index (PLI), bioconcentration factor (BCF), bioaccumulation factor (BAF), transfer factor (TF) and metal accumulation index (MAI) were calculated. The results demonstrated that the average contents of Cu, Fe, and Pb were lower than those in the background, which presumably demonstrated natural sources of these metals. The greatest concentrations of analyzed elements for all the sediment and macrophyte samples were observed in specimens collected from S4 located at the end of the river, indicating the impact of anthropogenic entries from upstream areas on elemental accumulation in downstream section of the river. The values of PI reflected slight contamination. The higher BCF and lower translocation TF values of Fe and Pb in T. Latifolia and also Cu in N. microphyllum imply that these species could be suitable for their phytostabilization of above-mentioned elements from the sediment. This study provides evidenceas to the efficiency of T. Latifolia and N. microphyllum in bioremediation of Cu, Fe, and Pb in contaminated aquatic environments.

Noise pollution prediction and seasonal comparison in urban parks using a coupled GIS- artificial neural network model

Noise pollution is a challenging environmental issue in densely built urban areas and requires a holistic understanding of its sources and alleviation processes. Taking Isfahan City in Iran as a typical case, this study developed a combined GIS-artificial neural network (ANN) model to predict the spatio-temporal contribution of low-width parks to poise pollution mitigation. The 30-min equivalent sound level was measured at 100 stations in six urban parks (with a total area of 55.84 ha) under stable and controlled winter and summer conditions. The noise level predicting variables were hypothesized to be the area of vegetation cover; NDVI-based vegetation density and standard deviation (std); vegetation height; and road coverage measured within 100-, 200-, and 300-m radius buffer rings drown around each noise sampling station. These predictors were introduced to a multi-layer perceptron ANN model to identify and compare the most important noise alleviation variables among the selected predictors. The mean noise levels ranged from 67.23 to 70.57 dB. The number of vehicles showed an insignificant temporal difference, indicating that the noise source was relatively constant between the seasons. The ANN model performed satisfactorily in both seasons with SSE values of < 0.03. The Mann-Whitney U test showed a significant difference in the predicted noise levels between summer and winter. This study highlighted the efficiency of the combined GIS-ANN model in predicting distant-dependent urban processes, especially noise pollution whose levels and variability are essential in formulating urban land-use management.

Mangrove habitat suitability modeling: implications for multi-species plantation in an arid estuarine environment

In southern Iran, Sirik Estuary hosts the only two-species (Rhizophora mucronata and Avicennia marina) mangrove forest in the northwesternmost edge of the Indian Ocean mangrove distribution. Aiming to protect its forest reserve and compensate for inevitable losses, this study utilized habitat suitability modeling (the Maxent model) to identify suitable afforestation zones for each species, independently. The model was calibrated using the location of successfully established mangrove saplings as presence points and an array of physical and sediment physio-chemical layers as predictive variables. The model yielded an acceptable training AUC value of 0.963 for A.marina and 0.982 for R.mucronata. Moreover, physical variables had the highest contribution to predicting suitable habitats with different levels of importance for each species. The majority of A.marina suitable habitats were distributed along the in-estuary creek banks, creating mangrove-lined waterways while the R.mucronata suitable habitats were mostly distributed at the base of the main water creeks in the seaward reaches of the estuary. According to the Mann-Whitney U test results, there was a statistically significant spatial niche segregation (z = - 12.14, p = 0.000, sig ≤ .05, 2-tailed) between the species' suitable habitats. The results showed that white mangroves tend to create mangrove-line structures along the water creeks penetrating inside the estuary while red mangroves mostly prefer the seaward side of the existing mangrove patches which are in danger of sea level rise.

How vegetation cover characteristics response to the spread of Prosopis juliflora: a time-series remote sensing analysis in southern Iran

Plant invasion is recognized as the second most severe threat to biodiversity, following habitat loss. As one of the world's worst invasive alien plant species, Prosopis juliflora (Mesquite) has severely affected the majority of the Earth's dry ecosystems. Hence, this study attempted to identify the distribution, dominance, and changes in the vegetation characteristics of Mesquite-invaded regions along a series of coastal ecosystems in Southern Iran. Mesquite and other tree/shrub types were successfully classified using a temporarily-median-filtered Landsat 8-OLI image with acceptable kappa coefficient and overall accuracy values of 80.66 and 84.75, respectively. The multi-resolution segmentation was used to divide the region into spectrally homogenous parcels, then calculating the percentage cover (dominance) of Mesquite relative to other tree/shrub types. Analysis of MODIS NDVI products in highly invaded parcels showed a steady increase in NDVI values from 0.27 to 0.53 during 2000-2020 with a significant difference (z = -3.12, 0.183, sig ≤ .05, 2-tailed) from that of the low-invaded regions whose NDVI values oscillated constantly in a range between 0.15 and 0.28. Mesquite distribution also showed a local invasion pattern from areas with a steady or saturated status to neighboring parcels. In regions susceptible to Mesquite invasion, constant investigation of uncommon changes in NDVI whose vegetation characteristics differ significantly from that expected in poor dry vegetation covers of southern Iran can be considered as a conservation tool to identify and manage areas with early Mesquite establishment.

Linking river sediment arsenic to catchment spatial attributes in agricultural landscapes

Understanding of the sources and processes involved in the heavy metal accumulation in river sediments is important for measuring the risks associated with human exposure. Hence, an integrated modeling approach was designed to study the linkage between landscape-related natural and anthropogenic features and high arsenic levels at the outlet of six catchments on the Ghareh-Ajagh River, central Iran. Sediment arsenic levels were measured in 8 months from October 2018 to November 2019 when the river sediment and water conditions were stable and ranged from 16.3 to 78.5 mg/kg. Monthly catchment-level agricultural areas were extracted from Landsat 8-OLI images. Predictive variables included NDVI values; area and spatial patterns of agriculture measured using four landscape metrics of NP, PD, MPS, and ENN; length and slope of the streams extended from main agricultural areas to the catchment outlet; and four hydrologic soil groups. The best-fitted multiple regression model (r² = 0.763, p≤ 0.05) with the Akaike information criteria of 105.07 was developed using stream length, soil group C, and area and PD of agricultural areas. Results showed that sediment arsenic levels increase with increasing quantity and density of agricultural activities that were close to the river outlet and increasing proportion of silty loam or loamy soils but are relatively less dependent on agricultural structural patterns. These insights are helpful to inform policy decisions regarding the processes involved in river contamination in central Iran.

Characterization of ambient carbon monoxide and PM 2.5 effects on fetus development, liver enzymes and TSH in Isfahan City, central Iran

Ambient carbon monoxide (CO) and particulate matters (PMs) are two important air pollutants in urban areas with known impacts on fetuses. Hence, this study measured some biochemistry factors of 200 neonates with birth dates from January 19 to October 12, 2020, including the birth weight and height and the serum levels of ALT, AST, ALP, GGT, and TSH. The Support Vector Machine-fitted land-use regression approach was used to predict the spatio-temporal variability of intra-urban PM 2.5 and CO concentrations by month during the pregnancy period of the cases employing 5 variables of Digital Elevation Model (DEM), slope, and distance from Compressed Natural Gas (CNG) stations, Bus Rapid Transit (BRT) stations, and mines and industries. Spearman correlation analysis (p < 0.05) was performed between the neonate indices and mean monthly PM 2.5 and CO concentrations at the exact residential address of maternal cases and their nearby areas in 250, 500, 1000, 1500, and 2000 m-radius buffer rings. All modeling efforts succeeded in predicting CO and PM 2.5 levels with acceptable adjusted r² values. Northern Isfahan had relatively higher CO and PM 2.5 concentrations due to its adjacency to low-vegetated open lands and its high traffic load as compared to southern areas. The correlation results between the neonate biochemistry indices and mean PM 2.5 and CO concentrations were mostly positive in most buffer rings, especially in the >500 m-radius buffer rings for PM 2.5 and in the 2000 m-radius rings for CO. Although the correlation results of PM 2.5 followed a detectable trend in the buffer rings, the associations between CO and the neonate biochemistry indices differed significantly between the buffer rings. Results showed that increasing mean monthly concentration of CO and PM 2.5 may stimulate further production of liver enzymes while decreasing the birth weight and height.

Occurrence, abundance and characteristics of microplastics in some commercial fish of northern coasts of the Persian Gulf

This study assessed the abundance of microplastics (MPs) in muscle, liver, gill, and gastrointestinal tissues of 14 fish species from the Persian Gulf. The quality control showed no significant difference in MPs abundance between blank samples and muscle and liver tissues. The mean abundance of MPs accumulated in gill and gut was 2.85 ± 1.57 and 2.46 ± 1.46 pa/individual, respectively. The maximum mean abundance of MPs was observed in the gill (5.71 pa/ind) of the fish Thunnus tonggol and gut tissue (5.67 pa/ind) of the fish Sphyraena putnamiae. Fiber, black color and size of 23-75 μm were the predominant form of MPs. There was a significant positive correlation between the total fish length and the abundance of MPs. MPs were more abundant in pelagic fish (5.79 ± 5.98) than demersal fish species (3.89 ± 3.53). The level of fish contamination with MPs was low to moderate in comparison to the ranges reported in the literature.

Temporal variability of noise pollution attenuation by vegetation in urban parks

The present study proposed a novel approach to investigate variability in the acoustic behavior of a number of deciduous tree-dominated narrow and long urban parks in Isfahan city, central Iran, between winter leaf fall and summer foliage. Noise levels (Lq30 in dB) were measured along two adjacent sides of the parks: along the road-adjacent side (Ro transect) and the relatively calmer river-adjacent side of the parks (Ri transect) during 4-17 January 2018 and 7-14 August 2019. Using Sentinel-2 images, two NDVI maps were also produced for these two periods to determine how changes in green biomass were associated with changes in noise levels. Using ANOVA, a significant difference was found in Ri-Lq30 and NDVI maps between winter and summer (p = 0.0), while the difference was insignificant for Ri-Lq30 (p = 0.1). We also developed two multiple linear regressions, one for each season, to assess the dependency of Ri-Lq30 to the intensity of vegetation and Ro-Lq30 and compare the two seasons by performing a t test analysis on the intercept and slope of the models, with results suggesting there is a significant difference in the association of green biomass and noise levels measured inside the parks between leaf fall and foliage time (p = 0.04). Our results indicated the temporal variability of park characteristics in providing calmer urban landscapes throughout the year.

Evaluation of heavy metal pollution in the Zayandeh-Rud River as the only permanent river in the central plateau of Iran

Zayandeh-Rud River is the only permanent river in the central plateau of Iran. This river has been subject to an extensive discharge of wastewater and effluents from several point and nonpoint pollution sources. Accordingly, sediment quality of Zayandeh-Rud River in Varzaneh region, were studied. Algae and the sediment were sampled through 3 replications at 6 stations in the downstream after crossing through the Isfahan city and reaching Gavkhuni international wetland. Chlorophyll content and As, Pb, and Cd concentrations were measured in each sample Cladophora sp. and Oscillatoria sp. were identified using standard identification keys. The mean concentrations of metals in all stations exceeded background levels. Mean concentration of arsenic (162.9 mg/kg) in the sediment is about 31 times more than the ISQG standard (5.9 mg/kg) and considerably higher than the similar studies in Iran and other regions of the world. The mean concentration of As in algae samples is higher than the most polluted areas of the world. The mean concentration of Pb in the sediment (19.69 mg/kg) is lower than the ISQGs standard (35 mg/kg) and most of the studied river in north of Iran such as Chalous, Baboul-Rud, Gorgan-Rud (North), Khiav (North West), and Anzali wetland. The mean concentration of Cd in the sediment (2.11 mg/kg) is significantly higher than ISQG standard (0.6 mg/kg and some north highly polluted wetlands of Iran such as Anzali. There is a significant positive correlation between the mean concentrations of As and Pb in the sediment and Cladophora sp. tissue, and a negative one between the mean concentration of Pb in the sediment and chlorophyll b/a. There are significant negative correlations between the mean concentration of As in the sediment and chlorophyll a, and the total chlorophyll concentration in Oscillatoria sp. The results of Muller index indicate that the concentrations of Pb, Cd, and As in all stations occur in the Unpolluted, Moderate/Heavy, and Heavy/Extreme groups, respectively. Degree of contamination and modified degree of contamination show very high degree of pollution in the studied area. RI in all the stations showed very high ecological risk. The bioaccumulation factor for all metals in both algae is less than one. So, these two species may not be described as heavy metal accumulators. This study is an alarm for the Zayandeh-Rud River as the most important freshwater source for the Iranian Plateau. Graphical abstract.

Physiochemical factors and heavy metal pollution, affecting the population abundance of Coenobita scaevola

Hermit crabs (Coenobita scaevola) affect the environmental health. The effects of different physiochemical factors and heavy metals, on the population abundance of hermit crabs, collected from two different coastal stations in the Kish Island of Persian Gulf, Iran, were determined. The non-parametric Kruskal-Wallis test indicated the significant differences between hermit crab density, water pH, organic matter (OM), and slope, in the two stations. The tissue concentrations of Pb were 22.49 ± 5.11 and 19.36 ± 5.66 mg/kg, and of Cd were 2.38 ± 0.38 and 1.8 ± 0.36 mg/kg in the Stations 1 and 2, respectively. The corresponding values in the sediments were equal to 68.75 ± 0.7 and 60.22 ± 16.03 mg/kg for Pb, and 3.25 ± 0.17 and 2.77 ± 0.63 for Cd. PCA results indicated sediment OM, slope, and water pH were the three main parameters significantly affecting C. scaevola density. The significance of C. scaevola for biomonitoring the marine ecosystems, has been presented.

Effect of Cd and Pb Pollutions on Physiological Growth: Wavelet Neural Network (WNN) as a New Approach on Age Determination of Coenobita scaevola

Environmental pollution of aquatic ecosystems leads to an interference in several fundamental biochemical and physiological functions. In this study the interference of Cd and Pb pollutions on the physiological growth and subsequently on the age determination was investigated. The hermit crab, Coenobita scaevola (C.s) was selected as a bioaccumulator in this study. The direct and indirect age determination methods were carried out using annual band counts and carapace length, respectively. The results showed that, there was very low correlation (R² < 0.5) between direct and indirect age determination. Wavelet Neural Network (WNN) was applied to take into account the environmental effects such as the accumulation of Cd and Pb elements in the C.s' tissues. It was observed that WNN successfully enhanced the growth rate model and estimated the C.s' age (R² > 0.95). In addition, it was concluded that the environmental pollution had interaction with the growth physiology such as weight and length.