Fatih Evrendilek

Assessing the potential of renewable energy sources in Turkey

To meet Turkey’s growing energy demand, the installed electric power capacity of 27.8 GW in 2001 has to be doubled by 2010 and increased fourfold by 2020. The difference between Turkey’s total primary energy supply (TPES) of from its own sources and total final consumption (TFC) is projected grow from 1 quad (1.06–2.06) in 1999 to 5.71 quads (2.79–8.5) in 2020 (1 quad=293.071 TWh). Turkey’s limited amount of fossil fuels has a present average ratio of proved reserves of 97.38 quads to production rate of 3.2 quads yr−1 of about 30 years. Turkey’s reliance on fossil fuel-based energy systems to meet the growing demand is most likely to exacerbate the issues of energy insecurity, national environmental degradation, and global climate change in increasing proportions. Economically-feasible renewable energy potential in Turkey is estimated at a total of ca. 1.69 quads yr−1 (495.4 TWh yr−1) with the potential for 0.67 quads yr−1 (196.7 TWh yr−1) of biomass energy, 0.42 quads yr−1 (124 TWh yr−1) of hydropower, 0.35 quads yr−1 (102.3 TWh yr−1) of solar energy, 0.17 quads yr−1 (50 TWh yr−1) of wind energy, and 0.08 quads yr−1 (22.4 TWh yr−1) of geothermal energy. Pursuit and implementation of sustainability-based energy policy could provide about 90 and 35% of Turkey’s total energy supply and consumption projected in 2010, respectively. Utilization of renewable energy technologies for electricity generation would necessitate about 23.2 Mha (29.8%) of Turkey’s land resources.

Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies

This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.

Changing Global Climate: Historical Carbon and Nitrogen Budgets and Projected Responses of Ohio’s Cropland Ecosystems

As the evidence of global climate change continues to mount, its consequences for cropland productivity assume particular significance. Against the backdrop of past agricultural practices, simulation models offer a glimpse into the future, showing the effect of temperature changes on crop production. In this study, we first quantified the carbon (C) and nitrogen (N) budgets of Ohio’s cropland ecosystems using inventory yield data of corn for grain, oat, and all wheat for the period 1866–1996 and soybean for the period 1924–96. Then we explored the responses of Ohio’s continuous soybean croplands to changes in temperature, carbon dioxide (CO2) concentration, initial soil organic C and N (SOC-N) pools, soil texture, and management practices by developing a simple cropland ecosystem model (CEM) and performing a long-term sensitivity analysis. Finally, CEM simulations were evaluated against independent observations of SOC values (0–19 cm) averaged over 470 northwest Ohio sites between 1954 and 1987 under conventional tillage and rotations of corn–soybean–winter wheat by using the historical yield data (r2 = 0.8). The C contents per hectare of crop harvests increased by 178% for oats, 300% for corn for grain, and 652% for all wheat between 1866 and 1996 and by 305% for soybean between 1924 and 1996. Ohio croplands acted as C–N sources, releasing average net ecosystem emissions (NEE), including the removal of harvested C–N, of 4,598 kg CO2 ha−1 and 141 kg N ha−1 in 1886 and 205 kg CO2 ha−1 (except for the corn-for-grain cropland) and 39 kg N ha−1 in 1996. The continuous corn croplands continued to become a C sink, sequestering 255 kg C ha−1 in 1996. Results of the sensitivity analysis for Ohio’s continuous soybean croplands revealed that the SOC pool increased by 6.9% and decreased by 7.5% in response to a doubled CO2 concentration and a temperature increase of 2.8°C over 100 years, respectively. The sequestration potential of the SOC pool increased by 6.5% at a rate of 24.6 kg C ha−1 y−1 for the same period with finer soil texture (loam to silty clay loam). The shift from conventional to conservation residue practice led to an 11% increase in the steady-state SOC storage at a rate of 42 kg C ha−1 y−1 for 100 years.

Deriving Vegetation Dynamics of Natural Terrestrial Ecosystems from MODIS NDVI/EVI Data over Turkey

The 16-day composite MODIS vegetation indices (VIs) at 500-m resolution for the period between 2000 to 2007 were seasonally averaged on the basis of the estimated distribution of 16 potential natural terrestrial ecosystems (NTEs) across Turkey. Graphical and statistical analyses of the time-series VIs for the NTEs spatially disaggregated in terms of biogeoclimate zones and land cover types included descriptive statistics, correlations, discrete Fourier transform (DFT), time-series decomposition, and simple linear regression (SLR) models. Our spatio-temporal analyses revealed that both MODIS VIs, on average, depicted similar seasonal variations for the NTEs, with the NDVI values having higher mean and SD values. The seasonal VIs were most correlated in decreasing order for: barren/sparsely vegetated land > grassland > shrubland/woodland > forest; (sub)nival > warm temperate > alpine > cool temperate > boreal = Mediterranean; and summer > spring > autumn > winter. Most pronounced differences between the MODIS VI responses over Turkey occurred in boreal and Mediterranean climate zones and forests, and in winter (the senescence phase of the growing season). Our results showed the potential of the time-series MODIS VI datasets in the estimation and monitoring of seasonal and interannual ecosystem dynamics over Turkey that needs to be further improved and refined through systematic and extensive field measurements and validations across various biomes.

Modeling Spatio-Temporal Dynamics of Optimum Tilt Angles for Solar Collectors in Turkey

Quantifying spatial and temporal variations in optimal tilt angle of a solar collector relative to a horizontal position assists in maximizing its performance for energy collection depending on changes in time and space. In this study, optimal tilt angles were quantified for solar collectors based on the monthly global and diffuse solar radiation on a horizontal surface across Turkey. The dataset of monthly average daily global solar radiation was obtained from 158 places, and monthly diffuse radiation data were estimated using an empirical model in the related literature. Our results showed that high tilt angles during the autumn (September to November) and winter (December to February) and low tilt angles during the summer (March to August) enabled the solar collector surface to absorb the maximum amount of solar radiation. Monthly optimum tilt angles were estimated devising a sinusoidal function of latitude and day of the year, and their validation resulted in a high R2 value of 98.8%, with root mean square error (RMSE) of 2.06°.

Quantifying soil respiration in response to short-term tillage practices: a case study in southern Turkey

Abstract The study aimed at quantifying the rates of soil CO2 efflux under the influence of common tillage systems of moldboard plow (PT), chisel plow (CT), rotary tiller (RT), heavy disc harrow (DT), and no-tillage (NT) for 46 days in October and November in a field left fallow after wheat harvest located in southern Turkey. The NT and DT plots produced the lowest soil CO2 effluxes of 0.3 and 0.7 g m−2 h−1, respectively, relative to the other plots (P < 0.001). Following the highest rainfall amount of 87 mm on the tenth day after the tillage, soil CO2 efflux rates of all the plots peaked on the 12th day, with less influence on soil CO2 efflux in the NT plot than in the conventional tillage plots. Soil evaporation in NT (64 mmol m−2 s−1) was significantly lower than in the PT (85 mmol m−2 s−1) and RT (89 mmol m−2 s−1) tillage treatments (P < 0.01). The best multiple-regression model selected explained 46% of variation in soil respiration rates as a function of the tillage treatments, soil temperature, and soil evaporation (P < 0.001). The tillage systems of RT, PT, and CT led, on average, to 0.23, 0.22, and 0.18 g m−2 h−1 more soil CO2 efflux than the baseline of NT, respectively (P≤0.001).

Modelling long-term C dynamics in croplands in the context of climate change: a case study from Ohio

A simple dynamic model (CBUDGET) was developed to quantify long-term carbon (C) dynamics in croplands. By using independent datasets (on continuous wheat) from the Waite Permanent Rotation Trial (Australia) and from Northwest Ohio, the tests of its performance resulted in R2 values of 0.85 and 0.80, respectively, between observed and simulated values. Our model suggests that the rate of residual C addition into the soil is the primary factor that controls soil organic carbon (SOC) storage for Ohio croplands under continuous corn, wheat and oats for the period 1866–1996 and continuous soybean for the period of 1924–1996. The interaction of CO2-fertilization and a temperature increase of 0.5°C decreased mean SOC levels for the selected crops over the same periods. A multiple linear regression model (MLR) relating carbon dioxide (CO2) emissions to population growth, affluence and energy intensity with an R2 of 0.99 indicates the significance of underlying causes of anticipated climate change. The MLR model thus serves to capture a more complete picture of anthropogenic sources of global climate change than considering agricultural activities only in exploring locally and regionally mitigative and preventive measures towards global climatic stability.

Modeling Potential Distribution and Carbon Dynamics of Natural Terrestrial Ecosystems: A Case Study of Turkey

We derived a simple model that relates the classification of biogeoclimate zones, (co)existence and fractional coverage of plant functional types (PFTs), and patterns of ecosystem carbon (C) stocks to long-term average values of biogeoclimatic indices in a time- and space-varying fashion from climate–vegetation equilibrium models. Proposed Dynamic Ecosystem Classification and Productivity (DECP) model is based on the spatial interpolation of annual biogeoclimatic variables through multiple linear regression (MLR) models and inverse distance weighting (IDW) and was applied to the entire Turkey of 780,595 km2 on a 500 m × 500 m grid resolution. Estimated total net primary production (TNPP) values of mutually exclusive PFTs ranged from 108 ± 26 to 891 ± 207 Tg C yr-1 under the optimal conditions and from 16 ± 7 to 58 ± 23 Tg C yr-1 under the growth-limiting conditions for all the natural ecosystems in Turkey. Total NPP values of coexisting PFTs ranged from 178 ± 36 to 1231 ± 253 Tg C yr-1 under the optimal conditions and from 23 ± 8 to 92 ± 31 Tg C yr-1 under the growth-limiting conditions. The national steady state soil organic carbon (SOC) storage in the surface one meter of soil was estimated to range from 7.5 ± 1.8 to 36.7 ± 7.8 Pg C yr-1 under the optimal conditions and from 1.3 ± 0.7 to 5.8 ± 2.6 Pg C yr-1 under the limiting conditions, with the national range of 1.3 to 36.7 Pg C elucidating 0.1% and 2.8% of the global SOC value (1272.4 Pg C), respectively. Our comparisons with literature compilations indicate that estimated patterns of biogeoclimate zones, PFTs, TNPP and SOC storage by the DECP model agree reasonably well with measurements from field and remotely sensed data.

Modeling Forest Productivity Using Envisat MERIS Data

The aim of this study was to derive land cover products with a 300-m pixel resolution of Envisat MERIS (Medium Resolution Imaging Spectrometer) to quantify net primary productivity (NPP) of conifer forests of Taurus Mountain range along the Eastern Mediterranean coast of Turkey. The Carnegie-Ames-Stanford approach (CASA) was used to predict annual and monthly regional NPP as modified by temperature, precipitation, solar radiation, soil texture, fractional tree cover, land cover type, and normalized difference vegetation index (NDVI). Fractional tree cover was estimated using continuous training data and multi-temporal metrics of 47 Envisat MERIS images of March 2003 to September 2005 and was derived by aggregating tree cover estimates made from high-resolution IKONOS imagery to coarser Landsat ETM imagery. A regression tree algorithm was used to estimate response variables of fractional tree cover based on the multi-temporal metrics. This study showed that Envisat MERIS data yield a greater spatial detail in the quantification of NPP over a topographically complex terrain at the regional scale than those used at the global scale such as AVHRR.

Modelling stochastic variability and uncertainty in aroma active compounds of PEF-treated peach nectar as a function of physical and sensory properties, and treatment time

Effects of pulsed electric field (PEF) processing on 28 aroma active compounds, and four physical and eight sensory properties of peach nectar were explored using the best-fit multiple linear regression (MLR) models and Monte Carlo simulations as a function of the treatment times of 0, 66, 131, and 210 μs. The PEF treatment time of 131 μs on average led consistently to the least loss of most compounds. Significantly enhanced or no significant changes in the sensory properties were found as a function of the PEF treatment times. The most influential sensory predictor of the 28 MLR models was flavour, while the aroma compound most influential on the sensory properties of aftertaste, flavour, sweetness, and overall acceptance was octadecanoic acid. Monte Carlo simulations were used for the probabilistic assessments of stochastic variability and uncertainty associated with aroma active compounds of PEF-treated peach nectar.