Using a modified version of Airpacts model for estimating the damage posed by sulfur dioxide emission from power plants to urban and rural building façades (case study: Shahid Rajaee power plant, Qazvin Province, Iran).

This study aimed at upgrading the Air Indicator Report for Public Awareness and Community Tracking (Airpacts) model to evaluate the physical effects of sulfur dioxide (SO2) emissions from Shahid Rajaee power plant on the building façades in Qazvin, Iran in 2018. For this purpose, first, the methodological requirements of the model for the study area, including wind speed, relative humidity, and temperature, were analyzed. Then, the concentration of SO2 emission from the power plant stack was calculated using the Aeroqual Model 200. The obtained data were processed and loaded into the Airpacts model version 1.0. After localization of the costs for reconstruction of 1 m2 of façade, including the costs of purchasing materials, installation, and transport from the power plant, the damage posed by SO2 to the building façades in Qazvin was calculated. Outputs of the modified model suggested that the damage to the building façades included cleansing in contact with SO2 was 494,558,878.12 m2. Based on the calculations, the cost of damage caused by SO2 was estimated to be $0.25 per Megawatt-hour (MWh) electricity generation, reaching an amount of $29,422 annually. Based on the localized results obtained by the modified Airpacts, the external cost of damage to the façades was $0.3 per MWh electricity generation, reaching an amount of $35,720 annually. To overcome the constraints of the original model concerning the constant parameters of mixing height and wind speed in the default model algorithm, the two parameters were considered dynamic variables in the modified model.

Human health risk assessment of organophosphorus pesticide in rice crop from selected districts of Anzali International Wetland basin, Iran.

Low fertility in rice caused by Chilo suppressalis has led to the use of diazinon to control this pest. Residue of pesticide could penetrate products and also food which can affect public health. The aim of this research was to determine health risk assessment of organophosphorus (OP) pesticide in rice, a strategic crop in Iran. Ninety rice samples were collected from 30 points during harvesting seasons from Rasht Area, Guilan Province, Iran from which 30 samples were prepared. The concentration of diazinon, the most common pesticide used in the study area, was determined by high-performance liquid chromatography. The result indicated that the total average of diazinon in rice samples (31.91 mg/kg) is by far higher than the maximum residue limit recommended by the European Union. According to the results, EDAI was 0.051 mg/kg day, while health risk index in rice was 10.2. Results showed that there is a health risk associated with the lifetime consumption of rice polluted by OP pesticide in the study area.

Determining an appropriate method for the purpose of land allocation for ecotourism development (case study: Taleghan County, Iran).

Appropriate management and planning of suitable areas for the development of ecotourism activities can play an important role in ensuring proper use of the environment. Due to the complexity of nature, applying different tools and models-particularly multi-criteria methods-can be useful in order to achieve these goals. In this study, to indicate suitable areas (land allocation) for ecotourism activities in Taleghan county, weighted linear combination (WLC) using geographical information system (GIS), fuzzy logic, and analytical network process (ANP) were used. To compare the applicability of each of these methods in achieving the goal, the results were compared with the previous model presented by Makhdoum. The results showed that the WLC and ANP methods are more efficient than the Makhdoum model in allocating lands for recreational areas and ecotourism purposes since concomitant use of fuzzy logic and ANP for ranking and weighing the criteria provides us with more flexible and logical conditions. Furthermore, the mentioned method makes it possible to involve ecological, economic, and social criteria simultaneously in the evaluation process in order to allocate land for ecotourism purposes.

Heavy metal pollution in water and sediments in the Kabini River, Karnataka, India.

The River Kabini in Karnataka, India carries natural and anthropogenic pollutants, mainly heavy metal concentrations of Cr, Cu, Fe, Mn, Ni, Pb and Zn which are released from industrial effluents, agricultural return flows and domestic sewage. Kabini, which is a tributary of the Cauvery, drains through the industrial area at Nanjangud, Karnataka, India. Heavy metals were determined in waters and sediment (2 µm) of Kabini River. In the present investigation, chemical partitioning studies was carried out to know the association of base metals with various sedimentary phases. The concentrations of heavy metals are higher in loosely bonded fraction than the other studied fractions. Furthermore, the degree of sediment contamination was assessed by geochemical index. It should be pointed out that Cu and Cr show the highest pollution intensity. Cluster analysis was used to know about the inter correlation amongst the studied metals. It is evident that higher concentrations of metals are found in the vicinity of industrial effluents. The concentrations of Cr followed by Zn and Ni are rather higher than the maximum background values in the Kabini River sediment. This is especially true at the influx of paper mill effluents into the River.

Metal pollution assessment of sediment and water in the Shur River.

Intensified industrialization and human activities have resulted in the release of various contaminants into the environment. Among them, heavy metals are often present as a result of mining, milling and industrial manufacturing. In the present investigation, bulk concentrations Pb, Cd, Zn, Cu, Fe, Ca and Al in Shur River (Iran) bed sediments and water around the Sarcheshmeh copper mine were measured from several sample locations. In addition, partitioning was assessed to determine the proportions of metals in different forms. The degree of sediment contamination was evaluated using an Enrichment Factor (EF) and geo-accumulation index (I (geo)) and a newly developed pollution index (I (POLL)). Elevated metals in sediment and water were found to be correlated with areas of the river that were proximal to direct and indirect mining activities. Cadmium and Zn showed the highest pollution index. Cluster analysis was performed in order to assess heavy metal interactions between water and sediment. Chemical partitioning studies revealed that organic metallic bonds were not significantly present in the sediment of the Shur River.