Abstract: Understanding and predicting Taste and Odour events is as difficult as critical for drinking water treatment plants. Following a number of events in recent years, a comprehensive statistical analysis of data from Lake Tingalpa (Queensland, Australia) was conducted. Historical manual sampling data, as well as data remotely collected by a vertical profiler, were collected; regression analysis and self-organising maps were the used to determine correlations between Taste and Odour compounds and potential input variables. Results showed that the predominant Taste and Odour compound was geosmin. Although one of the main predictors was the occurrence of cyanobacteria blooms, it was noticed that the cyanobacteria species was also critical. Additionally, water temperature, reservoir volume and oxidised nitrogen availability, were key inputs determining the occurrence and magnitude of the geosmin peak events. Based on the results of the statistical analysis, a predictive regression model was developed to provide indications on the potential occurrence, and magnitude, of peaks in geosmin concentration. Additionally, it was found that the blue green algae probe of the lake’s vertical profiler has the potential to be used as one of the inputs for an automated geosmin early warning system.
Abstract: Land-use and land-cover changes are driving unprecedented changes in ecosystems and environmental processes at different scales. This study was aimed at identifying the potential land-use drivers in the Jedeb catchment of the Abbay basin by combining statistical analysis, field investigation and remote sensing. To do so, a land-use change model was calibrated and evaluated using the SITE (SImulation of Terrestrial Environment) modelling framework. SITE is cellular automata based multi-criteria decision analysis framework for simulating land-use conversion based on socio-economic and environmental factors. Past land-use trajectories (1986–2009) were evaluated using a reference Landsat-derived map (agreement of 84%). Results show that major land-use change drivers in the study area were population, slope, livestock and distances from various infrastructures (roads, markets and water). It was also found that farmers seem to increasingly prefer plantations of trees such as Eucalyptus by replacing croplands perhaps mainly due to declining crop yield, soil fertility and climate variability. Potential future trajectory of land-use change was also predicted under a business-as-usual scenario (2009–2025). Results show that agricultural land will continue to expand from 69.5% in 2009 to 77.5% in 2025 in the catchment albeit at a declining rate when compared with the period from 1986 to 2009. Plantation forest will also increase at a much higher rate, mainly at the expense of natural vegetation, agricultural land and grasslands. This study provides critical information to land-use planners and policy makers for a more effective and proactive management in this highland catchment.
Abstract: Forests are a vital resource supporting the livelihoods of rural communities in Kenya. In spite of this significant role, human activities have put increased pressure on this resource, leading to continued forest-cover decline. To address forest-cover decline, the Kenyan government introduced Participatory Forest Management (PFM) through its Forest Department in the early 2000s, enabling local communities to form and register Community Forest Associations (CFAs). This study was conducted to examine the impacts of the PFM approach on the Lembus Forest-cover change. Three Landsat satellite images (Landsat 5 TM acquired on 9 January 1985; Landsat 7 ETM+ acquired on 1 February 2002; and Landsat 8 OLI (Operational Land Imager) acquired on 1 March 2015) were used to analyse forest-cover change in the 1st period (1985–2002) and the 2nd period (2002–2015). In analysing the contribution of CFAs in conservation and management of the Lembus Forest, questionnaire sheets were distributed randomly to various residents living adjacent to the Lembus Forest; 327 valid responses were obtained from heads of households. The results of the land-cover change show a decrease in the percentage of forest-cover decline from 11.2%, registered in the 1st period, to 8.2% in the 2nd period. This led to the decrease of the annual rate of the forest-cover decline from 0.4 in the 1st period to 0.2 in the 2nd period. Three CFAs operate in this area, and 75% of the respondents participated in tree planting and 16% participated in tree pruning. This type of community participation is thought to most likely be the cause of the decline of the recent decreasing annual rate of forest-cover loss in the study area. Conversely, we found out that important initiatives, such as a forest patrol, had not been implemented due to lack of funding, and that CFAs and Kenya Forest Service had not yet signed any management agreement.
Abstract: This review of the study “Road to Dawei”, conducted by WWF Greater Mekong, seeks to assess economic, social and environmental impacts of road construction between Kanchanaburi, Thailand and Dawei, Myanmar. It also aims to identify relevant Green Economy policy interventions that would enhance the sustainable use and conservation of natural capital, which is considered to be a foundation for sustainable and inclusive economic development. In particular, the study concentrates on the identification of feedback loops, delays and nonlinearity in order to properly map the socio-economic and environmental system analysed and inform decision making. Results are presented for three different scenarios both for Myanmar and for Thailand. Simulation results show that a conventional approach to road construction is likely to have positive economic impacts in the region, especially in the short term, but also negative consequences for the integrity of the ecosystem, which in turn might also negatively impact on the investment itself and its economic outcomes in the medium and longer term. Further, results indicate that green economy interventions would mitigate environmental risks by creating synergies across sectors, systemically.
Abstract: Islands present sustainable energy growth challenges due to a number of reasons such as remoteness, limited energy resources, vulnerability to external events and strong dependence on international trade agreements. In particular, the Dodecanese Islands of the Aegean Sea cover their electricity needs mostly on the basis of autonomous conventional stations, consuming significant quantities of imported oil annually. Renewable energy sources (RES) penetration increase addresses the global requirements towards a carbon neutral environment, and wind farms (WFs) are among the most well-known green electricity-production alternatives. The study explores wind power installation potential of the Dodecanese Islands and the storage or interconnection options, based on the national and European legislative framework and the international scientific literature. The major finding is that, due to the high wind potential of the area, the National policy and targets focus on the installation of great RES power at Greek islands. Hence, private interests, who are willing to carry out the electrical interconnection of islands to the mainland, serve the same objective. Both scientific and business proposals overcome the local wind power installation capacity and neglect local specifics and needs.
Abstract: Previous field research on the Horqin Sandy Land (China), which has suffered from severe desertification during recent decades, revealed how land use on a sand-dune topography affects both land degradation and restoration. This study aimed to depict the spatial distribution of local land use in order to shed more light on previous field findings regarding policies on a broader scale. We performed the following analyses with Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) and Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) images of Advanced Land Observing Satellite (ALOS): (1) object-based classification to discriminate preliminary classification of land-use types that were approximately differentiated by ordinary pixel-based analysis with spectral information; (2) digital photogrammetry to generate a digital surface model (DSM) with adequately high accuracy to represent undulating sand-dune topography; (3) geographic information system (GIS) analysis to classify major topographic types with the digital surface model (DSM); and (4) overlay of the two classification results to depict the local land-use types. The overall accuracies of the object-based and GIS-based classifications were high, at 93% (kappa statistic: 0.84) and 89% (kappa statistic: 0.81), respectively. The resultant local land-use map represents areas covered in previous field studies, showing where and how land degradation and restoration are likely to occur. This research can contribute to future environmental surveys, models, and policies in the study area.