Circular Economy: Nigeria Perspective

Nigeria is a lower middle-income country and is ranked as the largest economy in Africa with a gross domestic product of 444.92 billion (www.imf.org). The country is located on the western coast of Africa, has an area of 923, 763 km2 and is bounded by Benin Republic in the west, Niger Republic in the north, Cameroun in the east and Gulf of Guinea in the south

Understanding the political ecology of forced migration and deforestation through a multi-algorithm classification approach: the case of Rohingya displacement in the southeastern border region of Bangladesh

Compared with numerous existing forced migration scenarios across the globe, migration from Myanmar to Bangladesh through southeastern border region is unique at least for three reasons – (i) very large number of migrants have been displaced to (ii) a very small area in (iii) a relatively short period of time, creating an obvious cumulative impact on forest cover area of the host country. Therefore, this study aims to analyze the dynamics of refugee migration and deforestation in Bangladesh. Satellite images of Landsat-5 & 8 and Sentinel-2 were classified via four different classification algorithms (SVM, Random Forest, CART, and Max Entropy) to measure major land use and land cover changes, namely, (i) dense forest, (ii) sparse forest, (iii) open area, and (iv) settlement from 1988 to 2018. The analysis revealed a declining trend of dense forest area, majority of which took place from 2016 to 2018 triggered by Rohingya migration. As a whole, the dense forest cover has been effectively halved (8531 ha in 2016 to 4498 ha in 2018) in the span of just two years while refugee settlement has increased nine-folds (271 ha in 2016 to 2679 ha in 2018). Aggregated and indisputable conclusion has been derived indicating that forced Rohingya migration and deforestation are indeed positively correlated

Targeted intervention strategies to optimise diversion of BMW in the Dublin, Ireland region

Urgent transformation is required in Ireland to divert biodegradable municipal waste (BMW) from landfill and prevent increases in overall waste generation. When BMW is optimally managed, it becomes a resource with value instead of an unwanted by-product requiring disposal. An analysis of survey responses from commercial and residential sectors for the Dublin region in previous research by the authors proved that attitudes towards and behaviour regarding municipal solid waste is spatially variable. This finding indicates that targeted intervention strategies designed for specific geographic areas should lead to improved diversion rates of BMW from landfill, a requirement of the Landfill Directive 1999/31/EC. In the research described in this paper, survey responses and GIS model predictions from previous research were the basis for goal setting, after which logic modelling and behavioural research were employed to develop site-specific waste management intervention strategies. The main strategies devised include (a) roll out of the Brown Bin (Organics) Collection and Community Workshops in Dún Laoghaire Rathdown, (b) initiation of a Community Composting Project in Dublin City (c) implementation of a Waste Promotion and Motivation Scheme in South Dublin (d) development and distribution of a Waste Booklet to promote waste reduction activities in Fingal (e) region wide distribution of a Waste Booklet to the commercial sector and (f) Greening Irish Pubs Initiative. Each of these strategies was devised after interviews with both the residential and commercial sectors to help make optimal waste management the norm for both sectors. Strategy (b), (e) and (f) are detailed in this paper. By integrating a human element into accepted waste management approaches, these strategies will make optimal waste behaviour easier to achieve. Ultimately this will help divert waste from landfill and improve waste management practice as a whole for the region. This method of devising targeted intervention strategies can be adapted for many other regions.Deposited by bulk importTS 23.02.1