Linkages among ecotourism,landscape and natural resource management,and livelihood diversification in the region of Suğla Lake,Turkey

The purpose of this study is to evaluate opportunities of the region of Su?la Lake located in Turkey for community-based ecotourism development that enable sustainable landscape and natural resource management as well as livelihood diversification. A participatory research approach was applied by participation of a diverse number of stakeholders (e.g. local communities, local and central governmental bodies and researchers). A set of participatory research tools (e.g. interviews and field surveys), SWOT analysis and the method of Ecotourism Opportunity Spectrum (ECOS) were used to collect and evaluate relevant data. The study consists of four sections. The first section focuses on SWOT analysis by which the advantages and disadvantages of the study area for ecotourism development were examined. In the second section, the most suitable villages for ecotourism development were examined by adapting the method of ECOS based on the 18 parameters by using 1–4 score system. Accordingly, the most suitable five villages for ecotourism development were determined. Major natural and cultural ecotourism resources (e.g. diversity of landforms, spectacular landscapes and traditional lifestyle) of the study area were examined in the third section. In the fourth section, the ecotourism-based livelihood and relevant core capitals were evaluated according to 1–4 score system for the five villages. We hope that the outcomes of this study can draw attention of planners and policymakers to the role of ecotourism for sustainable landscape and natural resource management as well as livelihood diversification in the region and elsewhere.     

In situ evaluation of the genotoxic potential of the river Nile: I. Micronucleus and nuclear lesion tests of erythrocytes of Oreochromis niloticus niloticus (Linnaeus, 1758) and Clarias gariepinus (Burchell, 1822)

This study aimed to investigate the genotoxic potential of chemicals present along the course of the river Nile using frequencies of micronuclei (MN) and nuclear lesions (NL) in erythrocytes of Nile tilapia Oreochromis niloticus niloticus and African catfish Clarias gariepinus, as biomarkers. Results showed that most of the physicochemical parameters detected and heavy metal concentrations were significantly higher in the water collected from the estuaries of the river Nile compared to other sites of the upper Nile. The frequencies of MN and NL in peripheral blood erythrocytes of Nile tilapia and African catfish were significantly higher in estuary sites in Damietta and Rosetta compared to upper sites. The lowest level of genotoxicity was observed at two sites (Aswan and Kena), considered to be less contaminated. Our results suggested that higher frequencies of MN and NL determined at Damietta and Rosetta sites may be indicative of damage produced by pollutants in these areas. The most remarkable result was that MN and NL frequencies appear to be strongly related to water quality at different sites examined, indicating that MN frequencies may serve as a reliable biomarker for testing genotoxicity in situ. The positive correlation between MN and NL induction suggested that NL may be a useful complementary assay for genotoxicity analyses when fish are used as experimental animals. It was also found that seasonal variations in MN and NL frequencies might contribute to a better understanding of genotoxic responses in the field. The use of fish as indicator organisms for monitoring the presence of genotoxic-inducing contaminants in the environment seemed justified because the effects of exposure to a “complex mixture” such as river water were obtained. Nile tilapia appears to be a more suitable bioindicator species than African catfish in studying genotoxic chemical pollution in the river Nile attributed to a higher sensitivity.     

Evaluating sustainable land use for the Değirmendere valley: A case study from northeastern Turkey

Regional land-use development projects are undertaken to protect water resources necessary for agriculture, energy and sustaining human life. The De?irmendere valley, in the province of Trabzon in the Black Sea region of Turkey, provides clean water to the city of Trabzon. The valley is part of the Silk Road from Asia to the Black Sea and contains historical monasteries such as Sumela, Kustul and Vazelon. However, over the years, misuse of the valley has caused freshwater, sea and environmental pollution. In an attempt to overcome these problems, a multilateral project, De?irmendere Vadisi Çevre Düzenlemesi (DEVAÇED), was launched in the region. This paper aims to provide information necessary for engineering projects within the region. Six villages, on both sides of the valley, were selected for this research and evaluated in terms of river basin utilization, topography, cadastral survey of property and ownership, and land readjustment improvements. The study found illegal and improper urbanization, including industrial facilities within the valley causing water pollution. Current cadastral base maps are not sufficiently accurate for engineering projects, and in some places buildings have been constructed on unstable soils that are susceptible to landslides. The research results have helped to generate important recommendations for rehabilitation of the river basin.     

Circular economy strategies for combating climate change and other environmental issues

Global industrialization and excessive dependence on nonrenewable energy sources have led to an increase in solid waste and climate change, calling for strategies to implement a circular economy in all sectors to reduce carbon emissions by 45% by 2030, and to achieve carbon neutrality by 2050. Here we review circular economy strategies with focus on waste management, climate change, energy, air and water quality, land use, industry, food production, life cycle assessment, and cost-effective routes. We observed that increasing the use of bio-based materials is a challenge in terms of land use and land cover. Carbon removal technologies are actually prohibitively expensive, ranging from 100 to 1200 dollars per ton of carbon dioxide. Politically, only few companies worldwide have set climate change goals. While circular economy strategies can be implemented in various sectors such as industry, waste, energy, buildings, and transportation, life cycle assessment is required to optimize new systems. Overall, we provide a theoretical foundation for a sustainable industrial, agricultural, and commercial future by constructing cost-effective routes to a circular economy.

     

Seaweed for climate mitigation,wastewater treatment,bioenergy, bioplastic,biochar, food,pharmaceuticals, and cosmetics: a review

The development and recycling of biomass production can partly solve issues of energy, climate change, population growth, food and feed shortages, and environmental pollution. For instance, the use of seaweeds as feedstocks can reduce our reliance on fossil fuel resources, ensure the synthesis of cost-effective and eco-friendly products and biofuels, and develop sustainable biorefinery processes. Nonetheless, seaweeds use in several biorefineries is still in the infancy stage compared to terrestrial plants-based lignocellulosic biomass. Therefore, here we review seaweed biorefineries with focus on seaweed production, economical benefits, and seaweed use as feedstock for anaerobic digestion, biochar, bioplastics, crop health, food, livestock feed, pharmaceuticals and cosmetics. Globally, seaweeds could sequester between 61 and 268 megatonnes of carbon per year, with an average of 173 megatonnes. Nearly 90% of carbon is sequestered by exporting biomass to deep water, while the remaining 10% is buried in coastal sediments. 500 gigatonnes of seaweeds could replace nearly 40% of the current soy protein production. Seaweeds contain valuable bioactive molecules that could be applied as antimicrobial, antioxidant, antiviral, antifungal, anticancer, contraceptive, anti-inflammatory, anti-coagulants, and in other cosmetics and skincare products.

     

Social,environmental, and economic consequences of integrating renewable energies in the electricity sector: a review

The global shift from a fossil fuel-based to an electrical-based society is commonly viewed as an ecological improvement. However, the electrical power industry is a major source of carbon dioxide emissions, and incorporating renewable energy can still negatively impact the environment. Despite rising research in renewable energy, the impact of renewable energy consumption on the environment is poorly known. Here, we review the integration of renewable energies into the electricity sector from social, environmental, and economic perspectives. We found that implementing solar photovoltaic, battery storage, wind, hydropower, and bioenergy can provide 504,000 jobs in 2030 and 4.18 million jobs in 2050. For desalinization, photovoltaic/wind/battery storage systems supported by a diesel generator can reduce the cost of water production by 69% and adverse environmental effects by 90%, compared to full fossil fuel systems. The potential of carbon emission reduction increases with the percentage of renewable energy sources utilized. The photovoltaic/wind/hydroelectric system is the most effective in addressing climate change, producing a 2.11–5.46% increase in power generation and a 3.74–71.61% guarantee in share ratios. Compared to single energy systems, hybrid energy systems are more reliable and better equipped to withstand the impacts of climate change on the power supply.

     

Artificial intelligence for waste management in smart cities: a review

Environmental Chemistry Letters - The rising amount of waste generated worldwide is inducing issues of pollution, waste management, and recycling, calling for new strategies to improve the waste...     

Machine learning and computational chemistry to improve biochar fertilizers: a review

Traditional fertilizers are highly inefficient, with a major loss of nutrients and associated pollution. Alternatively, biochar loaded with phosphorous is a sustainable fertilizer that improves soil structure, stores carbon in soils, and provides plant nutrients in the long run, yet most biochars are not optimal because mechanisms ruling biochar properties are poorly known. This issue can be solved by recent developments in machine learning and computational chemistry. Here we review phosphorus-loaded biochar with emphasis on computational chemistry, machine learning, organic acids, drawbacks of classical fertilizers, biochar production, phosphorus loading, and mechanisms of phosphorous release. Modeling techniques allow for deciphering the influence of individual variables on biochar, employing various supervised learning models tailored to different biochar types. Computational chemistry provides knowledge on factors that control phosphorus binding, e.g., the type of phosphorus compound, soil constituents, mineral surfaces, binding motifs, water, solution pH, and redox potential. Phosphorus release from biochar is controlled by coexisting anions, pH, adsorbent dosage, initial phosphorus concentration, and temperature. Pyrolysis temperatures below 600 °C enhance functional group retention, while temperatures below 450 °C increase plant-available phosphorus. Lower pH values promote phosphorus release, while higher pH values hinder it. Physical modifications, such as increasing surface area and pore volume, can maximize the adsorption capacity of phosphorus-loaded biochar. Furthermore, the type of organic acid affects phosphorus release, with low molecular weight organic acids being advantageous for soil utilization. Lastly, biochar-based fertilizers release nutrients 2–4 times slower than conventional fertilizers.

     

Can tree species diversity be assessed with Landsat data in a temperate forest?

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20 m × 20 m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7 cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2 × 2 pixels and 3 × 3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freely available since June 2015.