Hans-Rudolf Bork

This study investigates the effectiveness of the Lagos Recycle Initiative (LRI) on landfill diversion (LFD) in Lagos, Nigeria, where evidence-based assessments of such initiatives are lacking. It evaluates the recycling diversion rate (RDR) of household recyclables (HSRs) across local government areas using field surveys and population data. Machine learning algorithms (logistic regression, random forest, XGBoost, and CatBoost) refined with Bayesian optimisation were employed to predict household recycling motivation. The findings reveal a low RDR of 0.37%, indicating that only approximately 2.47% (31,554.25 metric tonnes) of recyclables are recovered annually compared to a targeted 50% (638,750 metric tonnes). The optimised CatBoost model (accuracy and F1 score of 0.79) identified collection time and the absence of overflowing HSR bins as key motivators for household recycling via the SHapley Additive exPlanations (SHAP) framework. This study concludes that current LRI efforts are insufficient to meet recycling targets. It recommends expanding recovery efforts and addressing operational challenges faced by registered recyclers to improve recycling outcomes. The policy implications of this study suggest the need for stricter enforcement of recycling regulations, coupled with targeted financial incentives for both recyclers and households to boost recycling participation, thereby enhancing the overall effectiveness of waste diversion efforts under the LRI. This research provides a benchmark for assessing urban recycling initiatives (RIs) in rapidly growing African cities.

The annual volume of waste generated in sub-Saharan Africa (SSA) increased from 81 million tonnes to 174 million tonnes per year between 2012 and 2016 and is projected to reach 269 million tonnes in 2030. In 2018, SSA’s municipal solid waste (MSW) collection coverage was estimated at 44%. Concerned that the waste generation rate outweighs the collection pace, we conducted a systematic review of studies on MSW collection to examine the current situation in the region concerning the waste collection and coverage rates and to highlight the impediments to rapid progress in waste collection using the lens of four cities. Findings reveal that, despite the involvement of private waste collectors, collection and coverage rates are still below the desired 100% with backlogs of uncollected waste in public spaces, especially in low-income neighbourhoods where coverage remains abysmally low. This study fortifies the systematic discussion on MSW collection and coverage rates by conducting a meta-analysis. The result of the analysis shows that the waste collection and coverage rates are 65% and 67% in SSA, respectively. Aside from the paucity of data on waste generation rate and characterisation, most available data are incongruent. The review further shows that although several studies have been carried out on waste disposal, waste treatment and recycling in SSA studies directly focused on MSW collection are still few, leaving room for more research in this area. The review offers suggestions on how collection and coverage rates can be increased and equally proposes a strategy for reducing scavenging activities in the region’s unsanitary landfills, given its concomitant health impacts on the scavengers.

Objective classification of settlement deposits is a prerequisite for understanding human‐environment interactions at habitation sites. This paper presents a novel approach combining a relatively fine‐scale sampling strategy, a multimethod geoarchaeological investigation of cores and multivariate statistics to aid in the classification and interpretation of complex and intricately stratified archaeological deposits. Heterogeneous settlement deposits, buried soils, colluvial, fluvial, and fluvioglacial sediments from cores retrieved in the Viking settlement Hedeby were investigated using six cost‐effectively measurable geoecological parameters: loss on ignition at 550°C, magnetic susceptibility, contents of stones, artifacts, bones, and charcoal with wood. Principal component analysis allowed identifying variables that would sufficiently describe data and cluster analysis enabled the classification of the materials. As a result, 13 classes were distinguished with a detailed and reliable differentiation of materials of natural and cultural genesis. Based on spatial distribution patterns of the classes, hypotheses regarding land use in the adjacent areas were made: Waste disposal in the valley of Hedeby‐brook and metallurgic activities north of it. This approach is valuable for coring‐based research at settlements, in particular at tightly managed heritage sites, and for surveys to identify potential excavation sites, whereas the set of variables must be adjusted according to local conditions.

There are several approaches to assess flood vulnerability as a proactive measure to reduce the risk of flooding. The indicator-based approach is primarily practiced from a policy point of view through the use of composite indicators. Composite indicators can be built from very easy to very complex and sophisticated methods. However, there are two complications that arise with this issue. On the one hand, the flood vulnerability index should be fairly simple, taking into account the interdisciplinary nature of various stakeholders involved in flood risk management. While on the other hand, addressing the issue of subjectivity or prejudice should be scientifically defensible. As there is no a single universally “best” methodological approach for the construction of composite indicator due to its data-specific nature for each individual study. The aim of this study is therefore to construct such an index of flood vulnerability that is not only intuitive to a variety of stakeholders, but also scientifically justified in the context of Khyber Pakhtunkhwa, Pakistan. Therefore, the current study demonstrated a detailed procedure to construct the flood vulnerability indices through different methodological approaches of data rescaling, weighting, and aggregation schemes, along with a fairly simple approach for robustness. For this purpose, data was collected through different (official) portals for the nine highly flood-prone districts of the Khyber Pakhtunkhwa. It was found that the weighting schemes had a greater influence on the flood vulnerability ranking of the selected districts compared to data rescaling and aggregation schemes. The simple model, which is the frequently using approach of building composite indicators in scientific community, was found to be appropriate for the selected data. The methodology adopted in the study can provide decision-makers and relevant authorities with a practical tool to identify and prioritize certain vulnerable areas and measures to mitigate current flood vulnerabilities while preparing for future flood risk mitigation in the province through a fairly simple and methodologically defensible approach.