Determination of noise levels and effects in noise sensitive areas case study: Sakarya province Serdivan district of Turkey.

Noise pollution has become an important type of environmental pollution, especially in populated areas, due to changes in transportation preferences and industry development. The World Health Organization reports that noise, along with air and water pollution, poses one of the most dangerous pollution threats in big cities. In this study, noise pollution measurements were carried in two different regions of a major city, focusing on sensitive points such as hospitals and schools.

Circular Utilization of Coffee Grounds as a Bio-Nutrient through Microbial Transformation for Leafy Vegetables.

This study explores the production of bio-nutrients from bioactive compound-rich spent coffee grounds (SCG) and biochar (BC) through composting after inoculation with a biological agent and its impact on the growth performance of garden cress and spinach. The SCG was composted with six doses of BC (0, 5, 10, 15, 20, and 25%). The compost with 10% BC exhibited the best maturity, humification, and phytotoxicity index values of dissolved organic carbon (DOC), humification index (E4/E6), and germination index (GI).

Generic foresight model in changing hygiene habits with the pandemic: use of wet wipes in next generations.

The vast use of wet wipes has now become a habitude, particularly following the altered perception of cleanliness during the pandemic and the encouragement towards using WW (wet wipe) to ensure parent's and children's hygiene. This study primarily aims to create a projection of the WW waste that will emerge in Turkey as a result of the promoted consumption by children who are predicted to retain the WW usage practices of their parents. In line with this habit adopted by children, the number of daily WW usage which is currently around 210 million is expected to rise to over 250 million between the years 2040 and 2060, depending on how the children are guided by their parent's existing habits.

Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique.

Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resources' variables. The feed-forward neural network modeling technique is the most widely used ANN type in water resources applications. The main purpose of the study is to investigate the abilities of an artificial neural networks' (ANNs) model to improve the accuracy of the biological oxygen demand (BOD) estimation.