有机固体废弃物资源化利用探究

有机废弃物有机质含量高,是一种潜在的资源,将其资源化利用,既可解决资源短缺问题,又可减少碳排放.本文就有机固废的资源化利用分为农业农村有机废弃物和城市有机固废的资源化两方面进行了总结性阐述,以探索有机固废资源化利用的多元模式.     

Heavy metal monitoring of marine algae from the Turkish Coast of the Black Sea, 1998-2000

Concentrations of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn were determined in macroalgae samples collected from the Turkish Coast of the Black Sea. Certain algae species were chosen among the green, brown and red algae species at Sile and Sinop sampling stations from 1998 to 2000. In general, as regards the influence of the collection sites on the whole metal accumulation, Sinop is considered to be more polluted than Sile. The concentrations of the heavy metals in Cystoseira barbata algae are compared with previous studies in the same stations. The results showed that all metal levels have gradually decreased during past years. At the same time, Cd, Co, Cr, Cu, Fe, Ni and Pb levels in the present study are lower than in Bosphorus and Marmara Sea algae. However, Mn and Zn concentrations are higher than Bosphorus but lower than at Marmara. According to these findings the heavy metal pollution decreased in Turkish Coast of the Black Sea during the years investigated.     

Bee pollens as biological indicators: An ecological assessment of pollution in Northern Turkey via ICP-MS and XPS analyses

Environmental Science and Pollution Research - In this study, pollens were collected from 25 different locations of Northern Turkey to investigate pollution monitoring. Surface chemistry of pollen...     

Comparison of hybrid machine learning methods for the prediction of short-term meteorological droughts of Sakarya Meteorological Station in Turkey

Drought is a harmful natural disaster with various negative effects on many aspects of life. In this research, short-term meteorological droughts were predicted with hybrid machine learning models using monthly precipitation data (1960–2020 period) of Sakarya Meteorological Station, located in the northwest of Turkey. Standardized precipitation index (SPI), depending only on precipitation data, was used as the drought index, and 1-, 3-, and 6-month time scales for short-term droughts were considered. In the prediction models, drought index was predicted at t?+?1 output variable by using t, t???1, t???2, and t???3 input variables. Artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), Gaussian process regression (GPR), support vector machine regression (SVMR), k-nearest neighbors (KNN) algorithms were employed as stand-alone machine learning methods. Variation mode decomposition (VMD), discrete wavelet transform (DWT), and empirical mode decomposition (EMD) were utilized as pre-processing techniques to create hybrid models. Six different performance criteria were used to assess model performance. The hybrid models used together with the pre-processing techniques were found to be more successful than the stand-alone models. Hybrid VMD-GPR model yielded the best results (NSE?=?0.9345, OI?=?0.9438, R²?=?0.9367) for 1-month time scale, hybrid VMD-GPR model (NSE?=?0.9528, OI?=?0.9559, R²?=?0.9565) for 3-month time scale, and hybrid DWT-ANN model (NSE?=?0.9398, OI?=?0.9483, R²?=?0.9450) for 6-month time scale. Considering the entire performance criteria, it was determined that the decomposition success of VMD was higher than DWT and EMD.

     

The co-movements between geothermal energy usage and CO2 emissions through high and low frequency cycles

Environmental Science and Pollution Research - Geothermal energy is considered environmentally friendly than fossil fuel sources, and geothermal power plants are expected to have a low carbon...     

DNA damage effect of cyprodinil and thiacloprid in adult zebrafish gills

Cyprodinil and thiacloprid are two of the most commonly used pesticides in Turkey. It is more likely to reach humans or animals due to their widespread use. This study aims to investigate whether there is a DNA damage risk due to cyprodinil and thiacloprid exposure. Zebrafish, which is used as a model organism in health and environmental research, and comet assay were chosen to demonstrate this damage. Ten zebrafish per group were exposed to 2 different concentrations for each pesticides (0.31 and 0.155 mg/L for cyprodinil and 1.64 and 0.82 mg/L for thiacloprid) for 21 days. After, gills were excised and comet assay was performed. Photos of an average of 50 cells per slide were taken and were analyzed with visual evaluation program. DNA damage was found to be increased in the 0.31 mg/L cyprodinil, 0.82 mg/L thiacloprid, and 1.64 mg/L thiacloprid treatment groups when compared to the control group (p < 0.001). Average tail DNA percentage parameter values were 9.45 ± 0.51, 10.30 ± 0.34, 11.17 ± 0.33, and 2.47 ± 0.06 respectively. Cyprodinil and thiacloprid were identified as genotoxic agents that should be investigated further.

     

Frequency and determinants of recommended workplace violence prevention measures

PROBLEM: Limited information exists concerning adoption of workplace violence prevention measures by employers and the factors influencing their adoption. METHODS: A weighted sample of North Carolina workplaces (n=210) in operation January 1994 through March 1998 was used to estimate prevalence of 18 measures and identify community and workplace predictors of having >/=5 recommended measures. RESULTS: Location in a metropolitan area most strongly predicted presence of >/=5 administrative safety measures while a history of workplace violence and being in a high crime area were negatively associated. Belonging to an industry considered to be high-risk for workplace homicide was most strongly associated with having >/=5 environmental safety measures. DISCUSSION: Factors influencing high prevalence of violence prevention measures were related to business type, violence history, and location. Knowledge of factors influencing adoption of recommended workplace violence prevention measures can help tailor interventions to diverse industry settings. IMPACT ON INDUSTRY: An important contribution to the understanding and mitigation of workplace homicide is knowledge of the extent of implementation of recommended workplace violence prevention guidelines and factors influencing their adoption. Identifying factors that influence the prevalence and adoption of workplace violence safety interventions can help to tailor development of interventions to address the issue of workplace homicide across diverse industry settings.     

Formulation of a soil-pesticide transport model based on a compartmental approach

A semianalytical soil-pesticide transport model is formulated based on a compartmental approach to determine spatial and temporal variations of pesticide residues across a soil profile. The compartmental model is implemented by drawing an analogy between a series of continuous-flow stirred tank reactors and a soil horizon that consists of multiple perfectly mixed compartments. The analogy is strengthened by exploiting a relation between the compartment series and the conventional convective-dispersive equation (CDE) for vertical transport in the soil. Consequently, the number of compartments in the model formulation is not free, but dictated as a function of transport parameters. The model formulation allows consideration of arbitrary boundary value specifications and also, for some cases, spatially varying initial concentration profiles. Sorption kinetics is represented via a two-site model that involves a linear sorption isotherm and a first-order irreversible sorption or a radial diffusive penetrating model. For these three cases, analysis of the compartmental model allows the resultant concentration profiles to be expressed in terms of the Poisson distribution. When a nonlinear kinetic sorption model is used to simulate the sorption processes, an analytical solution is not found and a numerical approach is required.     

Heavy Metal Levels in Biota and Sediments in the Northern Coast of the Marmara Sea

Concentration of Cd, Co, Cr, Ni, Zn, Fe, Mn, Pb and Cu were determinedin biota and sediment samples collected from the Marmara Sea in Turkey. The levels of Zn, Fe, Mn, Pb and Cu in the macroalgae are higher than previous studies in the Marmara Sea. Moreover, Cu and Zn concentrations at the present study are significantly high than Bosphorus and Black Sea algae. The order heavy metal concentrations in the mussel samples was: Fe > Zn > Ni > Mn > Cu > Pb > Cr > Cd > Co. The metal concentrations are generally lower when compared with the Black Sea mussels except Pb. At the same time, concentrations of Pb, Cu and Zn in the mussel species are lower when compared with the results in the Aegean Sea. The ranges of Mn and Cu in the tested fish samples are higher than Black Sea fish. On the other hand, Cd, Co, Cr, Zn and Pb concentrations are lower. The northern coast of the Marmara Sea having the highest metal concentrations in sediments as follows: Co, Cr, Ni, Fe at ?arköy ; Pb, Cu at M. Ere?li; Cd, Zn, Mn at Menek?e. The heavy metal levels in the sediment samples are lower than other areas in the Marmara Sea.     

Absorption kinetics of NO from simulated flue gas using Fe(II)EDTA solutions

The absorption of NO encountering flue gases in aqueous solutions of Fe(II)EDTA was determined using a semi-batch stirred tank with a plane gas–liquid interface at 50 °C. The concentrations of NO, SO₂ and O₂ in the feeding stream were 300–800 ppm, 500–2200 ppm and 0–20%, respectively. The pH value of the Fe(II)EDTA solutions varied from 3 to 11. The concentrations of Fe(II)EDTA were maintained between 0.01 and 0.05 M. Experiments were performed to evaluate the effect of operating parameters on the NO absorption rate, the reaction kinetics of the reactants in gas and liquid phases, and the effect of competition between various reactants on the mass transfer rate in the NO removal system. Results indicate that the average reaction rate constant is 3.70 × 10⁷ M⁻¹ s⁻¹. Adding NaOH does not increase the absorption capability of Fe(II)EDTA. The presence of O₂ decreases the NO absorption rate with Fe(II)EDTA. The absorption rate of NO with Fe(II)EDTA decreases at low concentrations of SO₂, but increases at high concentrations.