Emissions of carbon from land use change in sub-Saharan Africa

2006 ◽  
Vol 111 (G2) ◽  
pp. n/a-n/a ◽  
Author(s):  
R. A. Houghton ◽  
J. L. Hackler
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Sub Saharan Africa ◽  
Sub Saharan

The impact of land use change on water resources in sub-Saharan Africa: a modelling study of Lake Malawi

1995 ◽  
Vol 170 (1-4) ◽  
pp. 123-135 ◽  
Author(s):  
Ian R. Calder ◽  
Robin L. Hall ◽  
Heidi G. Bastable ◽  
Henry M. Gunston ◽  
Osborne Shela ◽  
...  
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Land Use Change ◽  
Lake Malawi ◽  
Sub Saharan Africa ◽  
Sub Saharan ◽  
The Impact ◽  
Modelling Study

Land-Use Change and Communal Conflicts in Sub-Saharan Africa

2017 ◽  
Vol 23 (4) ◽  
Author(s):  
Sara Balestri ◽  
Mario A. Maggioni
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Use Changes ◽  
Sub Saharan Africa ◽  
Regular Grid ◽  
Communal Conflict ◽  
Sub Saharan

AbstractThis paper addresses the correlation between land-use changes and communal conflicts in Sub-Saharan Africa. In particular, by articulating the analysis on a 0.5° × 0.5° regular grid, we estimate the probability of a communal conflict event at time

Agricultural households’ adaptation to weather shocks in Sub-Saharan Africa: implications for land-use change and deforestation

2021 ◽  
pp. 1-23
Author(s):  
Julia Girard ◽  
Philippe Delacote ◽  
Antoine Leblois
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Growing Season ◽  
Sub Saharan Africa ◽  
Labor Income ◽  
Weather Shocks ◽  
Land Use Decisions ◽  
Agricultural Households ◽  
Sub Saharan

Abstract Agriculture in Sub-Saharan Africa is regularly threatened by the occurrence of weather shocks. We wonder whether the way farmers respond to shocks can affect land use and induce deforestation. Reviewing the existing literature, we found that this question has only been marginally studied. Drawing from the adaptation and land-use change literatures, we then expose the mechanisms through which weather shocks can push farmers to induce land-use change, or conversely to foster conservation. As farmers cope with shocks, their responses can cause degradations in ecosystems which could, in the long term, encourage deforestation and land-use change. To prepare for the next growing season, or adapt to climate variability and risk in the longer term, farmers also make structural adjustments in their farm and land-use decisions, which may lead to changes in land holding. They also resort to adaptation strategies that can indirectly affect land-use decisions by affecting households’ resources (labor, income).

The Impact of Charcoal Production for Energy on Tropical Rainforest Resources in Nigeria

2020 ◽  
Author(s):  
Angelique Lansu ◽  
Jaap Bos ◽  
Wilfried Ivens
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Population Growth ◽  
Open Data ◽  
Forest Degradation ◽  
Sub Saharan Africa ◽  
Charcoal Production ◽  
Household Energy ◽  
Sub Saharan ◽  
The Impact

<p>In Sub Saharan Africa, many people depend on biomass for their household energy. Charcoal production is a common technique for converting biomass into a useful energy source. Nigeria is the biggest charcoal producer in Sub Saharan Africa. A large amount of wood is harvested from Nigerian forests for this charcoal production for energy. The Nexus of charcoal-land use change-energy imposes a considerable burden on the amount of wood that must be extracted from the forest for charcoal production. Therefore, charcoal production is linked to deforestation and forest degradation. However, it is not clear to what extent the demand for charcoal in Nigeria contributes to deforestation by land use change, and degradation of forests by selected wood logging. In this study, an attempt was made to provide an answer to this and to state which situation could occur by 2030, following the expected population growth in Nigeria. To achieve this, literature and open data on charcoal production, deforestation, forest degradation and population growth in Nigeria have been collected and analysed. Subsequently, calculations were carried out to determine to what extent charcoal production contributed to deforestation in the period 1990-2015. In this period, the share of deforestation due to charcoal production increased from 6% to 14%. If the expected charcoal production in 2030 were to apply to the current situation, this share would be around 20%. The quantity of wood required can also be expressed in numbers of hectares with biomass. In that case, around 80,000 ha would be required in 2030. To validate the findings, further research is needed on the amount of biomass per hectare in Nigerian forests, and on the amount of charcoal exported, not only as source of household energy but also globally as barbecue fuel. A more extensive analysis of open data on the nexus charcoal-land use change-energy at multiple scales will help to project future interlinkages.</p>

Land-use change outweighs projected effects of changing rainfall on tree cover in sub-Saharan Africa

2016 ◽  
Vol 22 (9) ◽  
pp. 3013-3025 ◽  
Author(s):  
Julie C. Aleman ◽  
Olivier Blarquez ◽  
Carla A. Staver
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Sub Saharan Africa ◽  
Tree Cover ◽  
Sub Saharan

Land-Use Management and Carbon Sequestering in Sub-Saharan Africa

1992 ◽  
Vol 22 (3) ◽  
pp. 199-210 ◽  
Author(s):  
R. D. Perlack ◽  
R. L. Graham ◽  
A. M. G. Prasad
Keyword(s):  
Land Use ◽  
Sub Saharan Africa ◽  
Land Use Management ◽  
Carbon Sequestering ◽  
Sub Saharan

scholarly journals Key Challenges for Land Use Planning and Its Environmental Assessments in the Abuja City-Region, Nigeria

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 443
Author(s):  
Evidence Chinedu Enoguanbhor ◽  
Florian Gollnow ◽  
Blake Byron Walker ◽  
Jonas Ostergaard Nielsen ◽  
Tobia Lakes
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Environmental Assessment ◽  
Land Use Planning ◽  
Environmental Sustainability ◽  
Sub Saharan Africa ◽  
Environmental Assessments ◽  
City Regions ◽  
Sub Saharan ◽  
Land Cover Maps

Land use planning as strategic instruments to guide urban dynamics faces particular challenges in the Global South, including Sub-Saharan Africa, where urgent interventions are required to improve urban and environmental sustainability. This study investigated and identified key challenges of land use planning and its environmental assessments to improve the urban and environmental sustainability of city-regions. In doing so, we combined expert interviews and questionnaires with spatial analyses of urban and regional land use plans, as well as current and future urban land cover maps derived from Geographic Information Systems and remote sensing. By overlaying and contrasting land use plans and land cover maps, we investigated spatial inconsistencies between urban and regional plans and the associated urban land dynamics and used expert surveys to identify the causes of such inconsistencies. We furthermore identified and interrogated key challenges facing land use planning, including its environmental assessment procedures, and explored means for overcoming these barriers to rapid, yet environmentally sound urban growth. The results illuminated multiple inconsistencies (e.g., spatial conflicts) between urban and regional plans, most prominently stemming from conflicts in administrative boundaries and a lack of interdepartmental coordination. Key findings identified a lack of Strategic Environmental Assessment and inadequate implementation of land use plans caused by e.g., insufficient funding, lack of political will, political interference, corruption as challenges facing land use planning strategies for urban and environmental sustainability. The baseline information provided in this study is crucial to improve strategic planning and urban/environmental sustainability of city-regions in Sub-Saharan Africa and across the Global South, where land use planning faces similar challenges to address haphazard urban expansion patterns.

scholarly journals Using a Network of Locally Developed Low Cost Particulate Matter Sensors for Land Use Regression Modeling of PM2.5 in Urban Uganda

2020 ◽  
Author(s):  
Eric S. Coker ◽  
Ssematimba Joel ◽  
Engineer Bainomugisha
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Low Cost ◽  
Additive Models ◽  
Pollution Monitoring ◽  
Sub Saharan Africa ◽  
Land Use Regression ◽  
Sub Saharan

Background: There are major air pollution monitoring gaps in sub-Saharan Africa. Developing capacity in the region to conduct air monitoring in the region can help estimate exposure to air pollution for epidemiology research. The purpose of our study is to develop a land use regression (LUR) model using low-cost air quality sensors developed by a research group in Uganda (AirQo). Methods: Using these low-cost sensors, we collected continuous measurements of fine particulate matter (PM2.5) between May 1, 2019 and February 29, 2020 at 22 monitoring sites across urban municipalities of Uganda. We compared average monthly PM2.5 concentrations from the AirQo sensors with measurements from a BAM-1020 reference monitor operated at the US Embassy in Kampala. Monthly PM2.5 concentrations were used for LUR modeling. We used eight Machine Learning (ML) algorithms and ensemble modeling; using 10-fold cross validation and root mean squared error (RMSE) to evaluate model performance. Results: Monthly PM2.5 concentration was 60.2 µg/m3 (IQR: 45.4-73.0 µg/m3; median= 57.5 µg/m3). For the ML LUR models, RMSE values ranged between 5.43 µg/m3 - 15.43 µg/m3 and explained between 28% and 92% of monthly PM2.5 variability. Generalized additive models explained the largest amount of PM2.5 variability (R2=0.92) and produced the lowest RMSE (5.43 µg/m3) in the held-out test set. The most important predictors of monthly PM2.5 concentrations included monthly precipitation, major roadway density, population density, latitude, greenness, and percentage of households using solid fuels. Conclusion: To our knowledge, ours is the first study to model the spatial distribution of urban air pollution in sub-Saharan Africa using air monitors developed from the region itself. Non-parametric ML for LUR modeling performed with high accuracy for prediction of monthly PM2.5 levels. Our analysis suggests that locally produced low-cost air quality sensors can help build capacity to conduct air pollution epidemiology research in the region.

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