The population of Turkey has grown rapidly in parallel with the rise in technology and industrialization. The increasing population of the country has triggered urbanization, and environmental problems have drawn attention. One of the issues resulting from urbanization is solid waste. Every object we use in our daily life is transformed into solid waste when its economic life has ended. The processes from the storage of these wastes to their disposal, often referred to as solid waste management, come under the municipalities' authority and responsibility. Waste must be processed with the least environmental impact. This study investigated the solid wastes in Turkey according to the geographic regions and their relationships with the population. Data collected are related to population data. Solid waste materials, their volumes, daily solid waste per capita, and the population of municipalities served by waste management and waste treatment techniques are also discussed in this study.Keywords: Disposal methods, Solid waste, Local government, Turkey

Bu çalışmada arazi kullanım farklılığının toprakların bazı özellikleri ile azot mineralizasyonu üzerindeki etkilerinin belirlenmesi amaçlanmıştır. Bu çalışma kapsamında Rize, Kalkandere'de orman, çay, fındık ve kivi alanlarının her birinden 5 farklı noktada örnekleme yapılmıştır. Her örnekleme alanından birer toprak çukuru açılarak 0-15 cm ve 15-30 cm derinlik kademelerinden 40'ar adet bozulmuş ve bozulmamış toprak örneği alınmıştır. Toprak örneklerinde tekstür, toprak reaksiyonu (pH), organik karbon, toplam azot, karbon/azot oranı, elektriksel iletkenlik (EC), kireç (CaCO 3 ), hacim ağırlığı ve azot mineralizasyonu gibi özellikler belirlenmiştir. Arazi kullanım durumuna göre toprak özelliklerindeki farklılığı belirlemek için nanparametrik Kruskal Wallis testi uygulanmıştır. Arazi kullanım durumuna ilişkin ikili karşılaştırmalarda ise Dunn's Bonferroni test uygulanmıştır. Analiz sonuçlarına göre 0-15 cm derinlik kademesinde kil, pH, organik karbon, elektriksel iletkenlik, hacim ağırlığı, T 0 NO 3 , T0NH 4 +NO 3 , T 63 NH 4 ve T 63 NH 4 +NO 3 gibi toprak özellikleri anlamlı şekilde farklılık gösterirken, 15-30 cm derinlik kademesinde bu özellikler kum, kil, pH, elektriksel iletkenlik, hacim ağırlığı, T 63 NH 4 ve T 63 NH 4 +NO 3 şeklinde ortaya çıkmıştır. Bu çalışmaya göre doğal orman alanları topraklarının diğer arazi kullanım durumu topraklarına göre anlamlı bir şekilde daha az kil (p=0,008), EC (p=0,003), hacim ağırlığı (p=0,003), T 0 NO 3 (p=0,006) ve T 0 NH 4 +NO 3 (p=0,005); daha fazla kum (p=0,006) ve T 63 NH 4 +NO 3 (p=0,007) içerdiği belirlenmiştir.

Many climate models have been developed because of the importance of climatic factors' effects on the physical and biological environment, e.g., rock weathering, species distribution, and growth patterns of plants. Accurate, reliable climate surfaces are necessary, especially for countries such as Turkey, which has a complex terrain and limited monitoring stations. The accuracy of these models mainly depends on the spatial modeling methods used. In this study, Australian National University spline (ANUSPLIN) model was used to develop climate surfaces and was compared with other methods such as inverse distance weighting, Co-Kriging, lapse rate, and multilinear regression. The results from the developed climate surfaces were validated using three methods: (1) diagnostic statistics from the surface fitting model, such as signal, mean, root mean square predictive error, root mean square error estimate, root mean square residual of the spline, and estimate of the standard deviation of the noise in the spline; (2) a comparison of error statistics between interpolated surfaces with and the withheld climate data from 81 stations; and (3) a comparison with other interpolation methods using model performance metrics, such as mean absolute error, mean error, root mean square error, and R2adj. The most accurate results were obtained by the ANUSPLIN model. It explained 95%, 88%, 92%, and 71% of the variance in annual mean, minimum and maximum temperature, and total precipitation, respectively. The mean absolute error of these models was 0.63 °C, 1.16 °C, 0.72 °C, and 54.82 mm. The generated climate surfaces, having a spatial resolution of 0.005º x 0.005º could contribute to the fields of forestry, agriculture, and hydrology.

Aim of study:The present study aimed to model soil physical and chemical properties through multiple linear and regression tree techniques.Area of study: The study area is located between 41,07 -41,33 N latitude and 41,74 -42,27 E longitude in Artvin, which is in the Colchis part of the Black Sea Region of Turkey.Material and methods: The multiple linear regression and regression tree models were used to predict soil properties using topographic and climatic features as independent variables. Besides, the relationships between soil properties and independent variables were determined by Pearson correlation.Main results: The study results revealed that model accuracy by regression tree generally was higher than those of multiple linear regression. Up to 56% and 59% of the variance in soil properties was accounted for by multiple linear regression and regression tree, respectively. The easting, northing, elevation, and minimum temperature parameters were key drivers of both models. Increasing soil depth significantly increased the pH and reduced the organic carbon, total nitrogen, and carbon/nitrogen ratio.Highlights: Topographic and climatic variables accounted for Up to 59% and 56% of the variance in soil properties such as texture, pH, organic carbon, total nitrogen, and carbon/nitrogen ratio by regression tree and multiple linear regression techniques. The most influential factors on soil properties were the minimum temperature, latitude, actual evapotranspiration, mean temperature, distance to the ridge, and radiation index.