No abstract

No abstract

No abstract

In this study, a methodology has been developed for the detection of mucilage with the help of remote sensing (UA) techniques by considering the current mucilage formation in the Sea of Marmara. For this purpose, mucilage formation from10.03.2021 to 06.06.2021 was determined by classification of Sentinel-2 (MSI) satellite images using Random Forest (RF) algorithm on Google Earth Engine (GEE) platform. Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), the Modified Normalized Difference Water Index (MNDWI) and the Automated Water Extraction Index (AWEI) indexes were used for classification. In the classification study, 5 different date ranges were determined by considering the availability of satellite images and cloud ratio. In the first date range (10.03.2021-30.03.2021), the first mucilage image was detected in the Dardanelles Strait. In the following dates, the spread of mucilage towards the Gulf of Izmit and the Gulf of Gemlik in addition to the Dardanelles was determined. Finally, in the images dated between 17.05.2021-06.06.2021, it was seen that the density of mucilage increased in the Dardanelles Strait, Izmit Gulf, Gemlik Gulf, Erdek Kapıdağ Peninsula and the north of the Marmara Island. The area covered by mucilage as of the last date range was calculated as 12,741.94 ha, and this value shows that 1.07% of the Sea of Marmara is covered with mucilage. With this developed methodology, it has been seen that mucilage formation can be detected quickly within minutes and with high accuracy from satellite images anywhere in the world.

a b s t r a c tBoron (B) and arsenic (As) are two important contaminants detected in the spring and groundwater around the Bigadiç borate mines in Turkey which have the largest colemanite and ulexite deposits in the world. In this study, electrocoagulation (EC) process was used for the removal of arsenic from waters since EC was capable of removing arsenic to trace levels. The removal efficiencies of arsenic from spring and groundwater samples containing different arsenic concentrations of 36-1021 µg/L at 0.025-0.10 A and operating time of 0-60 min were achieved >97-99.9% at 2-16 min for Fe plate electrodes to meet the permissible level of arsenic effluent concentration of <10 µg/L. Energy and electrode consumptions for arsenic removal efficiency were 0.00429 kWh/m 3 and 0.00372 kg/m 3 for 0.025 A, 0.00529 kWh/m 3 and 0.00496 kg/m 3 for 0.05 A, and 0.00917 kWh/m 3 and 0.00992 kg/m 3 for 0.10 A. However, the EC was unsuccessful for the removal of B. B removal efficiencies at 0.025, 0.05, and 0.10 A were determined as 3.4, 3.9, and 4.6%, respectively. Effluent pH values were noticed to increase from 8 to 10 during the EC process and this was an advantage to remove B from the sample using ion-exchange process at pH 8-11. For that reason, Amberlite IRA-743 ion-exchange resin was selected to treat B in the effluents and effect of resin dosage (0.025-3 g) on the B removal efficiency was performed. A removal efficiency of 99-100% for B in the spring and groundwater samples was obtained. As the resin dosages were increased from 0.025 to 3 g, adsorption capacity was observed to decrease from 60 to 7.4 mg B/g resin. As effluent concentration of 1 mg/L was considered, amount of resin dosage for B removal was 0.75 g to reduce B concentration from 90.11 to 0.56 mg/L. The EC and ion exchange processes together were very successful for the removals of arsenic and boron from natural waters in the boron mining regions.