Risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 over 2017-2022 in Sanandaj, an area of Iran.

The risk of cardiovascular and respiratory diseases attributed to satellite-based PM2.5 has been less investigated. In this study, the attributable risk was estimated in an area of Iran. The predicted air PM2.5 using satellite data and a two-stage regression model was used as the predictor of the diseases. The dose-response linkage between the bias-corrected predictor employing a strong statistical approach and the outcomes was evaluated using the distributed lag nonlinear model. We considered two distinct scenarios of PM2.5 for the risk estimation. Alongside the risk, the attributable risk and number were estimated for different levels of PM2.5 by age and gender categories. The cumulative influence of PM2.5 particles on respiratory illnesses was statistically significant at 13-16 µg/m3 relative to the reference value (median), mostly apparent in the middle delays. The cumulative relative risk of 90th and 95th percentiles were 2.03 (CI 95%: 1.28, 3.19) and 2.25 (CI 95%: 1.28, 3.96), respectively. Nearly 600 cases of the diseases were attributable to the non-optimum values of the pollutant during 2017-2022, of which more than 400 cases were attributed to high values range. The predictor's influence on cardiovascular illnesses was along with uncertainty, indicating that additional research into their relationship is needed. The bias-corrected PM2.5 played an essential role in the prediction of respiratory illnesses, and it may likely be employed as a trigger for a preventative strategy.

Estimation of PM2.5 using high-resolution satellite data and its mortality risk in an area of Iran.

Satellite-based exposure of fine particulate matters has been seldom used as a predictor of mortality. PM2.5 was predicted using Aerosol Optical Depths (AOD) through a two-stage regression model. The predicted PM2.5 was corrected for the bias using two approaches. We estimated the impact by two different scenarios of PM2.5 in the model. We statistically found different distributions of the predicted PM2.5 over the region. Compared to the reference value (5 µg/m3), 90th and 95th percentiles had significant adverse effect on total mortality (RR 90th percentile:1.45; CI 95%: 1.08-1.95 and RR 95th percentile:1.53; CI 95%: 1.11-2.1). Nearly 1050 deaths were attributed to any range of the air pollution (unhealthy range), of which more than half were attributed to high concentration range. Given the adverse effect of extreme values compared to the both scenarios, more efforts are suggested to define local-specific reference values and preventive strategies.

Seasonal variation of Covid-19 incidence and role of land surface and air temperatures: a case study in the west of Iran.

.In this study, we assessed the impact of satellite-based Land Surface Temperature (LST) and Air Temperature (AT) on covid-19. First, we spatio-temporally kriged the LST and applied bias correction. The epidemic shape, timing, and size were compared after and before adjusting for the predictors. Given the non-linear behavior of a pandemic, a semi-parametric regression model was used. In addition, the interaction effect between the predictors and season was assessed. Before adjusting for the predictors, the peak happened at the end of hot season. After adjusting, it was attenuated and slightly moved forward. Moreover, the Attributable Fraction (AF) and Peak to Trough Relative (PTR) were % 23 (95% CI; 15, 32) and 1.62 (95%CI; 1.34, 1.97), respectively. We found that temperature might have changed the seasonal variation of covid-19. However, given the large uncertainty after adjusting for the variables, it was hard to provide conclusive evidence in the region we studied.

Machine learning-based modeling of malachite green adsorption on hydrochar derived from hydrothermal fulvification of wheat straw.

This study investigated the efficiency of hydrochar derived from hydrothermal fulvification of wheat straw in adsorbing malachite green (MG) dye. The characterizations of the hydrochar samples were determined using various analytical techniques like SEM, EDX, FTIR, X-ray spectroscopy, BET surface area analysis, ICP-OES for the determination of inorganic elements, elemental analysis through ultimate analysis, and HPLC for the content of sugars, organic acids, and aromatics. Adsorption experiments demonstrated that hydrochar exhibited superior removal efficiency compared to feedstock. The removal efficiency of 91 % was obtained when a hydrochar dosage of 2 g L-1 was used for 20 mg L-1 of dye concentration in a period of 90 min. The results showed that the study data followed the Freundlich isotherms as well as the pseudo-second order kinetic model. Moreover, the determined activation energy of 7.9 kJ mol-1 indicated that the MG adsorption was a physical and endothermic process that increased at elevated temperatures. The study also employed an artificial neural network (ANN), a machine learning approach that achieved remarkable R2 (0.98 and 0.99) for training and validation dataset, indicating high accuracy in simulating MG adsorption by hydrochar. The model's sensitivity analysis demonstrated that the adsorbent dosage exerted the most substantial influence on the adsorption process, with MG concentration, pH, and time following in decreasing order of impact.

Summer heat waves and their mortality risk over a 14-year period in a western region of Iran.

Compared to previous decade, impact of heat waves (HWs) on mortality in recent years needs to be discussed in Iran. We investigated temporal change in added impact of summer HWs on mortality in eight cities of Iran. The pooled length of HWs was compared between 2015-2022 and 2008-2014 using random and fixed-effects of meta-analysis regression model. The temporal change in impact of HWs was evaluated through interaction effect between crossbasis function of HW and year in a two-stage time varying model. In order to pool the reduced coefficients of each period, multivariate meta-regression model, including city-specific temperature and temperature range as heterogenicity factors, was used. In addition to relative risk (RR), attributable fraction (AF) of HW in the two periods was also estimated in each city. In the last years, the frequency of all HWs was higher and the weak HWs were significantly longer. The only significant RR was related to the lowest and low severe HWs which was observed in the second period. In terms of AF, compared to the strong HWs, all weak HWs caused a considerable excess mortality in all cities and second period. The subgroup analysis revealed that the significant impact in the second period was mainly related to females and elderlies. The increased risk and AF due to more frequent and longer HWs (weak HWs) in the last years highlights the need for mitigation strategies in the region. Because of uncertainty in the results of severe HWs, further elaborately investigation of the HWs is need.

Role of air pollution on seasonal distribution of Covid-19: a case study in the west of Iran.

The seasonal distribution of SARS-CoV-2 might be affected by air pollution. To test the hypothesis, epidemic determinants, namely, shape, timing (Peak and Trough) and size (Peak to Trough Ratio and Excess Risk) of seasonal distribution of the outbreak were compared before and after adjusting for air pollutants in a distributed lag nonlinear model. We controlled for one-lagged outcome and meteorological parameters in the model. We also evaluated interaction effect between air pollutants and season using stratification method. The epidemic determinants were changed after adjusting for PM2.5 and O3 in the model, suggesting the existence of their association with the seasonal distribution of the outbreak. The Excess Risk of season (i.e., the proportion of confirmed Covid-19 cases that were attributed to season; AF) was increased as %4 (%95 CI - 29, 38) after adjusting for PM2.5. Adjusting for O3 in the model resulted in % 1 (%95 CI - 36, 34) decrease in the index. NO, NO2 and SO2 had no association with the seasonal distribution, though the interaction analysis revealed that association of NO2 and SO2 with Covid-19 confirmed cases were significantly higher in fall than winter and spring, respectively. Totally, PM2.5 has negatively associated with the seasonal distribution of the outbreak while O3 has positively associated in the region under study. Although some reasons such as wearing mask and oxidative effect might go before the negative and positive associations, but our results suggests that any association and causation between air pollution and Covid-19 should be carefully interpreted.

Immobilization of microorganisms in activated zeolite beads and alkaline pretreated straws for ammonium-nitrogen removal from urban river water.

The non-treated wastewater from residential areas contains high concentrations of ammonium-nitrogen (NH4+-N). When discharged into the drainage water system, it deteriorates the water quality in urban rivers. This study used two types of materials to form eco-bags, using activated zeolite bead (AZB) and alkaline pretreated straw (APS), in geotextile bags for easy recovery and reuse. The AZB and APS provided the breeding habitat for the microorganisms that promoted biofilm formation on their surface. The immobilization of engineered denitrification microorganisms facilitated the removal of NH4+-N from the urban river water. The NH4+-N removal in the AZB and APS bags were in the range of 64-73%, and 56-61%, respectively, while the chemical oxygen demand (COD) removal in the AZB and APS bags ranged from 33-36%, and 30-31%, respectively. In addition, as evident from DNA and microbial community analysis, the microorganisms demonstrated a greater proclivity to grow and proliferate on the surface of AZB and APS and improved the water quality of urban rivers.

Photocatalytic removal of 2,4-Dichlorophenoxyacetic acid from aqueous solution using tungsten oxide doped zinc oxide nanoparticles immobilised on glass beads.

Groundwater is the only source of high quality water for human consumption in most parts of the world; however, it can be easily contaminated by domestic, industrial, and agricultural wastes such as fertilisers and pesticides. The main objective of the present research was to study the photocatalytic removal of 2,4-Dichlorophenoxyacetic acid pesticide (2,4-D) from aqueous media. This was a laboratory scale study in which the zinc oxide nanoparticles were doped with 0.5, 1, and 2 molar percent of tungsten oxide. The nanoparticles synthesised were characterised using powder XRD, SEM, FTIR, and UV-Vis Spectroscopy analyses. During the photodegradation of 2,4-D, the operational parameters studied were pH, nanoparticles dosage, initial pesticide concentration, light intensity, contact time, and the mineralisation trend of organic matter. It was found that the doped nanoparticles had a smaller band gap energy, which confirms the effect of doping. The percentage of the dopant can affect the pesticide removal efficiency. The optimal pH value obtained was 7. In addition, the process efficiency, increased from 27% to 78% with increasing UV light intensity from 172 to 505 W/m2 respectively. Moreover, it was found that, with increasing light intensity, contact time and nanoparticle concentration all caused the pesticide removal efficiency to be increased too. In addition, the increase of the pesticide concentration would cause a reduction in the process removal efficiency. This study indicated that the photocatalytic process using tungsten doped zinc oxide nanoparticles can remove the 2,4-D pesticide by around 80% from the aquatic environment.

Evaluation of bio-aerosols type, density, and modeling of dispersion in inside and outside of different wards of educational hospital.

Exposure to bioaerosols in the air of hospitals is associated with a wide range of adverse health effects due to the presence of airborne microorganisms. Intensity and type of health effects depend on many factors such as the type, density, and diversity of bioaerosols in hospital environments. Therefore, identifying and determining their distribution in hospital environment contribute to reduce their adverse effects and maintain the physical health of patients and staff, as well as find the source of infections and possible allergies due to the presence of bioaerosols. Therefore, the present study was conducted to determine the type and concentration of the bacterial and fungal bioaerosols, and their distribution in the indoor and outdoor air of a teaching hospital to establish a reference for future studies or measures. The air samples were collected with a one-stage Anderson sampler and particle mass counter for a period of four months in the fall and winter of 2019. In total, 262 bacterial and fungal samples were collected from the air of the wards of Tohid Hospital, Sanandaj, Iran. Antibiotic resistance test, bacterial identification by PCR method, and modeling the dispersion of concentrations of bio-aerosols were also conducted. In order to identify bacteria and fungi, some biochemical and molecular tests and microscopic and macroscopic characteristic methods were applied, respectively. The results showed that the highest and lowest densities of the bioaerosols were observed in lung and operating wards (336.67 and 15.25 CFU/m3). Moreover, the highest and least concentrations of particles were seen in the emergency and operating wards, respectively. The most common fungi isolated from the hospital air were Penicillium (24.7%), Cladosporium (23. 4%), Aspergillus niger (13.3%), and Aspergillus Flavus (11.4%). Furthermore, the highest concentration of the isolated bacterium was Staphylococcus hemolyticus (31.84%). Most bacteria showed the highest resistance to gentamicin. The overall average hospital air pollution to bioaerosols was slightly higher than the standards proposed by international organizations. Due to the high concentration of bioaerosols and particles in the studied hospital, providing suitable conditions such as temperature, humidity, proper ventilation, and intelligent air conditioning system using efficient ventilation systems, and restricting the entrance of wards can reduce airborne particles in hospital environment.

Antibacterial Activities of Phytofabricated ZnO and CuO NPs by Mentha pulegium Leaf/Flower Mixture Extract against Antibiotic Resistant Bacteria.

Purpose: In this study, leaf/flower aqueous extract of medicinal plant species Mentha pulegium was used to synthesize ZnO and CuO nanoparticles (NPs) as a cost-effective, one-step, and eco-friendly method. Methods: Physicochemical properties of both metal oxide NPs (MONPs) were determined by UV-Vis spectroscopy, X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscope (SEM) and energy dispersive X-ray (EDX) techniques. Results: Phytofabricated ZnONPs and CuNPs illustrated 65.02±7.55 and 26.92±4.7 nm with antibacterial activities against antibiotic-resistant Escherichia coli and Staphylococcus aureus. Higher antibacterial activities were observed for CuONPs compared with ZnONPs. Conclusion: Large surface area and more reactivity resulted from smaller size as well as higher production of reactive oxygen species (ROS) were considered to antibacterial efficiency of CuONPs against antibiotic-resistant E. coli and S. aureus.

Pectin/chitosan/tripolyphosphate encapsulation protects the rat lung from fibrosis and apoptosis induced by paraquat inhalation.

BACKGROUND: Paraquat poisoning leads to lung injury and pulmonary fibrosis. The effect of paraquat encapsulation by previously described Pectin/Chitosan/Tripolyphosphate nanoparticles on its pulmonary toxicity was investigated in present study in a rat model of poison inhalation. MATERIAL AND METHOD: The rats inhaled nebulized different formulation of paraquat (n = 5) for 30 min in various experimental groups. Lung injury and fibrosis scores, Lung tissue enzymatic activities, apoptosis markers were determined compared among groups. RESULTS: Encapsulation of paraquat significantly rescued both lung injury and fibrosis scores. Lung MDA level was reduced by encapsulation. Paraquat poisoning led to lung tissue apoptosis as was evidenced by higher Caspase-3 and Bax/Bcl2 expressions in rats subjected to paraquat inhalation instead of normal saline or free nanoparticles. Again, nanoencapsulation reduced these apoptosis markers significantly. Alpha-SMA expression was also reduced by encapsulation. Nanoparticles per se have no or little toxicity as was evidenced by inflammatory and apoptotic markers and histological scores. CONCLUSION: In a rat model of inhalation toxicity of paraquat, loading of this herbicide on PEC/CS/TPP nanoparticles reduced acute lung injury and fibrosis. The encapsulation also led to lower apoptosis, oxidative stress and alpha-SMA expression in the lung tissue.

Application of an electrochemical sensor using copper oxide nanoparticles/polyalizarin yellow R nanocomposite for hydrogen peroxide.

In this study, copper oxide nanoparticles (CuONPs) were prepared by a simple chemical method and then characterized by scanning electron microscope (SEM). A novel electrochemical sensor for hydrogen peroxide (H2O2) analysis was prepared by immobilizing copper oxide nanoparticles and polyalizarin yellow R (PYAR) on bare glassy carbon electrode (PAYR/CuONPs/GCE). The electrocatalytical behavior of the proposed electrochemical sensor was also studied by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and differential pulse voltammetry (DPV). Based on the results, the PAYR/CuONP nanocomposite had significant electrocatalytic oxidation and reduction properties for the detection and determination of H2O2. Some parameters such as linear range, sensitivity, and detection limit for reduction peak were obtained as 0.1-140 µM, 1.4154 µA cm-2 µM-1, and 0.03 µM, respectively, by the DPV technique. Some advantages of this electrode were having widespread linear range, low detection limit, and, most importantly, ability in simultaneous oxidation and reduction of H2O2 at two applied potentials.

Metal Risk Assessment Study of Canned Fish Available on the Iranian Market.

Iran is the largest fishery producer in the region reaching nearly 1 million tons. Fish provide a good many nutrients that are beneficial for our health. Due to significant deposits of xenobiotics in the water environments, however, fish may also be a source of non-essential metals, causing a variety of disorders. The main challenges to Iranian fisheries are environmental pollution and quality control, so this study aims to estimate the concentration of cadmium (Cd), mercury (Hg), nickel (Ni), and lead (Pb) in canned tuna fish produced and consumed in Iran. We studied four popular brands (N = 4 × 20) with ICP-MS and then looked at the concentrations and calculated the risk assessment parameters. We found that the lowest concentration was observed for Cd (18 µg/kg) and the highest for Ni (132 µg/kg). Among the brands studied, Pb concentrations differed most (42.0 to 113.3 µg/kg) and Hg levels were more consistent (24.0 and 39.4 µg/kg). The concentrations of Cd, Hg, and Pb in all the brands tested were below EU permissible thresholds. The intake estimation risk assessment parameters (EDI, contribution to PTWI, and CR) and non-cancer risk assessment parameters based on reference doses (THQ and HI) demonstrated the safety of tested products in respect to all metal concentrations studied, while the parameters regarding the toxic effects (MoE, and ILCR) showed that the consumption might cause health risks in terms of Cd (ILCR), Ni (ILCR), and Pb (MoE). The consumption of the canned fish studied should therefore be maintained at a reasonable level (2-5 meals containing fish weekly), so that it may provide necessary nutrients, while avoiding the health risk due to metal content.

Human health and ecological risk assessment of heavy metal(loid)s in agricultural soils of rural areas: A case study in Kurdistan Province, Iran.

BACKGROUND: Agricultural soils pollution with heavy metal (loid) s (HMs) can create significant ecological and health problems. The aims of present study were to characterize HMs pollution profile of dry farmland soils in rural areas of Kurdistan province in Iran and evaluate potential associated ecological and health risks. METHODS: Different indices of Geo-accumulation index (IGeo), Individual contamination factor (ICF), Nemerow composite pollution index (NCPI) and Potential Ecological Risk Index (PERI) were employed to assess the bio-accumulation of the HMs and evaluate associated ecological risks. Human health risks estimated with total hazard index (THI) and total carcinogenic risk (TCR) indices based on ingestion, inhalation and dermal exposure pathways for children and adults. RESULTS: As, Cd, Cr, Ni and Pb exceeded the soil standards. The spatial maps of the IGeo showed that As pollution was at severe level in eastern part of the study region. According to the ICF results, the studied soils were extremely contaminated with As, Cd, Cr, Ni and Zn. Furthermore, based on the pollution indices, some of sampling sites were critically polluted by abovementioned HMs. For children and adults groups, the THI values in 13 and 97% of sampling sites were more than 1 and the TCR in 7 and 14% of sampling sites were more than 10-4, respectively. The farmland soil pollution of the study area by As and Cr were found to be quite serious and dangerous. CONCLUSION: The findings of this study suggest that further attention should be paid by decision-makers to control the HMs pollution in the agricultural soils of the study area.

Correction to: Influence of iron mining activity on heavy metal contamination in the sediments of the Aqyazi River, Iran.

The original version of this article unfortunately contained an error in the affiliation section and missing acknowledgment statement.

Influence of iron mining activity on heavy metal contamination in the sediments of the Aqyazi River, Iran.

In order to investigate the degree of contamination of heavy metals (As, Cd, Cr, Cu, Fe, Pb, and Ni) in the Aqyazi River in Iran, sediment samples were collected from the river receiving wastewater from an iron-manufacturing plant. For this study, contamination indices, geoaccumulation index (Igeo), contamination factor (CF), and pollution load index (PLI), were used to assess contamination by the heavy metals. The results of the Igeo indicated that the sediments were moderately contaminated by Cu and strongly to extremely contaminated by Cd. Based on spatial distribution of concentrations and the Igeo, mining activity was the source of Cu and Cd in the Aqyazi River. Furthermore, the elevated Igeo of Cd at upmost northern station was not influenced by the mining activity, suggesting that there may be another upstream anthropogenic source of Cd. The CF values indicated the same trend as the Igeo. The PLI was calculated using all the metals analyzed in this study, and displayed that the sediments were not polluted. However, the PLI was re-calculated using only Cu and Cd and indicated that the sediments were polluted. Our results suggest further studies to trace another source of Cd upstream of the Aqyazi River and to investigate influence of the river waters on accumulation of heavy metals in soils and vegetables downstream.

The nitrate content of fresh and cooked vegetables and their health-related risks.

BACKGROUND: Vegetables are the most important source of nitrates in the human diet. During various processes in the body, nitrates are converted into nitrites, which causes various diseases, such as blue baby syndrome and cancer. This study aimed to determine the concentration of nitrates in several vegetable farms in Sanandaj city and to evaluate their health-related risks. METHODS: This descriptive cross-sectional study was conducted from October 2017 to July 2018. A total of 90 samples were taken from nine farms. Soil and water sampling was also carried out. All stages of sample preparation and extraction were carried out according to Food Standards 2-16721, and the nitrate measurements were performed using ion chromatography (Compact IC Plus 882 Model, Metrohm, Switzerland). A health risk assessment was performed using the non-carcinogenic risk assessment. RESULTS: This study's results showed that the nitrate concertation in all vegetables was less than National Iranian Vegetable Nitrate Standard. Nitrate levels in leafy vegetables were higher than in root vegetables, and the root vegetables levels were higher than those in Fruit vegetable. The nitrate level in vegetables in autumn was higher than in spring. The cooking process reduced the raw vegetables' nitrate content from 4.094% to 13.407%, while the frying process increased the vegetables' nitrate content from 12.46% to 29.93%. The highest health risk level in raw, cooked and fried vegetables was parsley, parsley and beet leaves, respectively, and the lowest in all categories was tomatoes. Generally, the highest health risk was related to fried beet leaves, and the lowest was raw tomatoes. In addition, each of the abovementioned relationships between vegetables' nitrate levels and the harvest season, type of processing procedure and type of vegetables was significant (p < 0.05). The irrigation water's nitrate concentration in all fields was between 12.36 and 33.14 mg/l. The soil contained nitrate levels of between 4.35 and 9.7 mg/kg. CONCLUSION: Based on this study, we can conclude that the amount of nitrates in raw vegetables was lower than the standard limit's level and that this level does not cause health problems for consumers.

Construction of manganese oxide nanowire-like cluster arrays on a DNA template: Application to detection of hydrogen peroxide.

Improved electron transfer properties and catalytic activity of manganese oxide (MnOx) was demonstrated following its electrochemical deposition on a deoxyribonucleic acid (DNA) modified glassy carbon electrode. The MnOx showed different morphologies, electrocatalytic properties and electrochemical kinetics. Scanning electron microscopy showed that electrodeposition of MnOx on a bare glassy carbon electrode led to the formation of irregular-shapes while a nanowire cluster (NWC) was formed on a GCE/DNA due to the DNA serving as a template. Electrochemical impedance spectroscopy (EIS) revealed lower charge transfer resistance of the MnOxNWC compared with MnOx. A new mechanism is presented for the electrodeposition of MnOx on the surface of a GC/DNA electrode. An electrochemical biosensor was fabricated based on depositing MnOx onto a glassy carbon /DNA electrode (GCE/DNA/MnOxNWC) and was used to detect hydrogen peroxide (H2O2). The MnOx nanowire cluster and DNA exhibited significant electrocatalytic activity for simultaneous electrocatalytic oxidation at two oxidation potentials (0.6 V and 0.98 V vs Ag/AgCl) and one reduction potential (-0.5 V vs Ag/AgCl) for H2O2 at pH 6.0. A new mechanism for the detection of H2O2 is presented. Excellent electrocatalytic activity, stability and facility for simultaneous detection of H2O2 at different of applied potentials are proposed advantages of the proposed electrochemical biosensor.

Arsenate removal from aqueous solutions using micellar-enhanced ultrafiltration.

In this study, arsenate (As-V) removal using micellar enhanced ultrafiltration (MEUF) modified by cationic surfactants was studied by a dead-end polyacrylonitrile (PAN) membrane apparatus. The UF membrane has been produced by a phase inversion process. The prepared membrane was characterized and analyzed for morphology and membrane properties. The influence of operating parameters such as initial concentrations of As-V, surfactants, pH, membrane thickness, and co-existing anions on the removal of As-V, surfactant rejection, and permeate flux have been studied. The experimental results show that from the two different cationic surfactants used the CPC (cetyl-pyridinium chloride) efficiency (91.7%) was higher than that of HTAB (hexadecyltrimethyl-ammonium bromide) (83.7%). The highest As-V removal was 100%, and was achieved using initial feed concentrations of 100-1000 µg/L, at pH 7 with a membrane thickness of 150 µm in a dead-end filtration system. This efficiency for As-V removal was similar to that obtained using a cross-flow system. Nevertheless, this flux reduction was less than the reduction achieved in the dead-end filtration process. The PAN fabricated membrane in comparison to the RO and NF processes selectively removed the arsenic and the anions, in the water taken from the well, and had no substantial effect on the cations.

Effects of doping zinc oxide nanoparticles with transition metals (Ag, Cu, Mn) on photocatalytic degradation of Direct Blue 15 dye under UV and visible light irradiation.

BACKGROUND: Azo dyes represent the most commonly used group of dyes in the textile industry. These organic dyes are mainly resistant to biodegradation and may exhibit toxic and carcinogenic properties. The purpose of this study was to investigate the effects of doping zinc oxide (ZnO) nanoparticles (NPs) with transition metals (silver, manganese, and copper) on the photocatalytic efficiency of ZnO NPs in the removal of Direct Blue 15 dye from aqueous environments under ultraviolet (UV) radiation and visible light irradiation. METHODS: One or two metals were used for doping the NPs. In total, seven types of undoped and transition metal-doped NPs were synthesized using the thermal solvent method with ZnO precursors and transition metal salts. The characteristics of the synthesized NPs were determined based on the scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, dynamic light scattering (DLS), atomic force microscopy (AFM), and zeta potential measurements. RESULTS: The produced ZnO NPs did not exhibit any particular photocatalytic activities under UV radiation and visible light irradiation. The highest removal efficiency under UV radiation was about 74% in the presence of silver-doped ZnO NPs, while the maximum efficiency under visible light was 70% in the presence of copper-doped ZnO NPs. The lowest removal efficiency was related to pure ZnO, which was 18.4% and 14.6% under UV and visible light irradiation, respectively. Although the efficiency of dye removal under visible light was not high compared to UV radiation, this efficiency was noteworthy in terms of both practical and economic aspects since it was achieved without the presence of ultraviolet radiation. CONCLUSIONS: The synthesis of transition metal-doped ZnO nanophotocatalysts (with one or two metals) under UV radiation or visible light irradiation could be used as an efficient and promising technology for the photocatalytic removal of Direct Blue 15 dye from aqueous environments.