Majiwa et al., 2018. Increasing agricultural productivity while reducing greenhouse gas emissions in sub-Saharan Africa: myth or reality?

Majiwa, E., Lee, B.L., Wilson, C., 2018. Increasing agricultural productivity while reducing greenhouse gas emissions in sub-Saharan Africa: myth or reality? Agricultural Economics 49, 183-192.

Abstract

The motivation for this study stems from two major concerns that are interlinked. The first is the decades long food insecurity crisis faced by sub‐Saharan African (SSA) countries which is still prevalent. The second is the negative impact greenhouse gas (GHG) emissions from agriculture may have on future food production and which is likely to worsen the food insecurity problem. The conundrum SSA farmers face is how to increase food output through productivity growth while minimizing GHG emissions. To measure changes in productivity growth and GHG emissions, this study evaluates the agricultural performance of 18 SSA countries by utilizing the Malmquist–Luenberger index to incorporate good and bad outputs for the years 1980–2012. The empirical evidence demonstrates that productivity is overestimated when bad outputs are not considered in the production model. The analysis provides a better understanding of the effectiveness of previous mitigation methods and which informs an appropriate course of action needed to achieve the twin objectives of increasing agriculture productivity while reducing GHG emissions.

Hickman et al., 2017. Nonlinear response of nitric oxide fluxes to fertilizer inputs and the impacts of agricultural intensification on tropospheric ozone pollution in Kenya

Hickman, J.E., Huang, Y., Wu, S., Diru, W., Groffman, P.M., Tully, K.L., Palm, C.A., 2017. Nonlinear response of nitric oxide fluxes to fertilizer inputs and the impacts of agricultural intensification on tropospheric ozone pollution in Kenya. Global Change Biology 23, 3193-3204.

Abstract

Crop yields in sub‐Saharan Africa remain stagnant at 1 ton ha−1, and 260 million people lack access to adequate food resources. Order‐of‐magnitude increases in fertilizer use are seen as a critical step in attaining food security. This increase represents an unprecedented input of nitrogen (N) to African ecosystems and will likely be accompanied by increased soil emissions of nitric oxide (NO). NO is a precursor to tropospheric ozone, an air pollutant and greenhouse gas. Emissions of NO from soils occur primarily during denitrification and nitrification, and N input rates are a key determinant of emission rates. We established experimental maize plots in western Kenya to allow us to quantify the response function relating NO flux to N input rate during the main 2011 and 2012 growing seasons. NO emissions followed a sigmoid response to fertilizer inputs and have emission factors under 1% for the roughly two‐month measurement period in each year, although linear and step relationships could not be excluded in 2011. At fertilization rates above 100 kg N ha−1, NO emissions increased without a concomitant increase in yields. We used the geos‐chem chemical transport model to evaluate local impacts of increased NO emissions on tropospheric ozone concentrations. Mean 4‐hour afternoon tropospheric ozone concentrations in Western Kenya increased by up to roughly 2.63 ppbv under fertilization rates of 150 kg N ha−1or higher. Using AOT40, a metric for assessing crop damage from ozone, we find that the increased ozone concentrations result in an increase in AOT40 exposure of approximately 110 ppbh for inputs of 150 kg N ha−1 during the March–April–May crop growing season, compared with unfertilized simulations, with negligible impacts on crop productivity. Our results suggest that it may be possible to manage Kenyan agricultural systems for high yields while avoiding substantial impacts on air quality.

Ortiz-Gonzalo et al., 2018. Multi-scale measurements show limited soil greenhouse gas emissions in Kenyan smallholder coffee-dairy systems.

Ortiz-Gonzalo, D., de Neergaard, A., Vaast, P., Su찼rez-Villanueva, V., Oelofse, M., Rosenstock, T.S., 2018. Multi-scale measurements show limited soil greenhouse gas emissions in Kenyan smallholder coffee-dairy systems. Science of the Total Environment 626, 328-339.

Abstract

Efforts have been made in recent years to improve knowledge about soil greenhouse gas (GHG) fluxes from sub-Saharan Africa. However, data on soil GHG emissions from smallholder coffee-dairy systems have not hitherto been measured experimentally. This study aimed to quantify soil GHG emissions at different spatial and temporal scales in smallholder coffee-dairy farms in Murang'a County, Central Kenya. GHG measurements were carried out for one year, comprising two cropping seasons, using vented static chambers and gas chromatography. Sixty rectangular frames were installed on two farms comprising the three main cropping systems found in the area: 1) coffee (Coffea arabica L.); 2) Napier grass (Pennisetum purpureum); and 3) maize intercropped with beans (Zea mays and Phaseolus vulgaris). Within these fields, chambers were allocated on fertilised and unfertilised locations to capture spatial variability. Cumulative annual fluxes in coffee plots ranged from 1 to 1.9 kg N2O-N ha− 1, 6.5 to 7.6 Mg CO2-C ha− 1 and − 3.4 to − 2.2 kg CH4 -C ha− 1, with 66% to 94% of annual GHG fluxes occurring during rainy seasons. Across the farm plots, coffee received most of the N inputs and had 56% to 89% higher emissions of N2O than Napier grass, maize and beans. Within farm plots, two to six times higher emissions were found in fertilised hotspots – around the perimeter of coffee trees or within planted maize rows – than in unfertilised locations between trees, rows and planting holes. Background and induced soil N2O emissions from fertiliser and manure applications in the three cropping systems were lower than hypothesized from previous studies and empirical models. This study supplements methods and underlying data for the quantification of GHG emissions at multiple spatial and temporal scales in tropical, smallholder farming systems. Advances towards overcoming the dearth of data will facilitate the understanding of synergies and tradeoffs of climate-smart approaches for low emissions development.

Graphical abstract

Pryor et al., 2017. Impact of agricultural practices on energy use and greenhouse gas emissions for South African sugarcane production.

Pryor, S.W., Smithers, J., Lyne, P., van Antwerpen, R., 2017. Impact of agricultural practices on energy use and greenhouse gas emissions for South African sugarcane production. Journal of Cleaner Production 141, 137-145.

Abstract

The environmental footprint of agricultural production can vary significantly both between countries and within a country based on regional conditions and agricultural practices. A life cycle assessment approach was used to model primary fossil fuel energy inputs and greenhouse gas emissions associated with the production of sugarcane in South Africa. Results were calculated for sugarcane produced in two distinct regions, the irrigated North and the non-irrigated North Coast. Regional differences also include terrain, soil, and use of mechanization. Models were adapted to estimate the impacts of burning prior to harvest, leaving a biomass mulch blanket with green cane harvesting, and increasing the level of mechanization for harvest and other field operations. Irrigation contributes to a higher energy input in the irrigated North but differences are mitigated by the lower fertilizer, agro-chemical, and diesel use per ton of sugarcane produced there. Despite higher energy inputs in the irrigated North, greenhouse gas emissions are similar for sugarcane produced in each region. Green cane harvesting reduces energy inputs and greenhouse gas emissions by 4% and 16%, respectively, in both regions. Impacts of mechanization on soil compaction and stool damage result in lower yields and proportionally higher energy inputs and greenhouse gas emissions. Results demonstrate the potential for variability in LCA results based on regional differences in production practices within a country.

Wanyama et al., 2018. Land Use, Land Use History, and Soil Type Affect Soil Greenhouse Gas Fluxes From Agricultural Landscapes of the East African Highlands

Wanyama, I., Rufino, M.C., Pelster, D.E., Wanyama, G., Atzberger, C., Asten, P., Verchot, L.V., Butterbach?륛ahl, K., 2018. Land Use, Land Use History, and Soil Type Affect Soil Greenhouse Gas Fluxes From Agricultural Landscapes of the East African Highlands. Journal of Geophysical Research: Biogeosciences 123, 976-990.

This study aims to explain effects of soil textural class, topography, land use, and land use history on soil greenhouse gas (GHG) fluxes in the Lake Victoria region. We measured GHG fluxes from intact soil cores collected in Rakai, Uganda, an area characterized by low‐input smallholder (<2 ha) farming systems, typical for the East African highlands. The soil cores were air dried and rewetted to water holding capacities (WHCs) of 30, 55, and 80%. Soil CO2, CH4, and N2O fluxes were measured for 48 h following rewetting. Cumulative N2O fluxes were highest from soils under perennial crops and the lowest from soils under annual crops (P < 0.001 for all WHC). At WHC of 55% or 80%, the sandy clay loam soils had lower N2O fluxes than the clay soils (P < 0.001 and P = 0.041, respectively). Cumulative soil CO2 fluxes were highest from eucalyptus plantations and lowest from annual crops across multiple WHC (P = 0.014 at 30% WHC and P < 0.001 at both 55 and 80% WHC). Methane fluxes were below detectable limits, a shortcoming for using soil cores from the top soil. This study reveals that land use and soil type have strong effects on GHG fluxes from agricultural land in the study area. Field monitoring of fluxes is needed to confirm whether these findings are consistent with what happens in situ.

Ortiz-Gonzalo et al., 2017. Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya

Ortiz-Gonzalo, D., Vaast, P., Oelofse, M., de Neergaard, A., Albrecht, A., Rosenstock, T.S., 2017. Farm-scale greenhouse gas balances, hotspots and uncertainties in smallholder crop-livestock systems in Central Kenya. Agriculture, Ecosystems & Environment 248, 58-70.

Abstract

Climate-smart approaches have gained momentum in tropical, agricultural development. However, to date, few studies have examined whole-farm greenhouse gas (GHG) balances in smallholder crop-livestock systems. This study aimed to quantify GHG balances at farm-scale, identify GHG hotspots and assess mitigation options in coffee-dairy farms undergoing agricultural intensification in Central Kenya. In recent decades, decreasing farm size has forced the shift from extensive practices to zero-grazing systems and higher nitrogen (N) inputs. We hypothesised that different farm strategies and intensification levels determine the farm’s GHG balance. A farm typology was constructed through principal component analysis (PCA) and hierarchical clustering from 125 farms surveyed. Four farm types were identified ranging relatively from small to large farms, low to high livestock intensities, and low to high N input rates. Whole-farm GHG balances were estimated using an adapted version of the Cool Farm Tool (CFT). Farms were found to be net sources of GHG, averaging from 4.5 t CO2 eq ha−1 yr−1 in less intensive farms to 12.5 t CO2 eq ha−1 yr−1 in high intensive farms. Within the farm GHG hotspots identified, methane (CH4) from enteric fermentation processes accounted for 26–39% of total farm GHG emissions; nitrous oxide (N2O) and CH4 from manure management systems (MMS) for 26–38%; soil background and fertilizer induced N2O emissions for 24–29%; off-farm production of feeds and agrochemicals for 10–22%; and crop residue management (CRM) for the remaining 1–3%. Within the mitigation practices assessed, zero-grazing stalls already lowered the livestock maintenance energy requirements, reducing enteric fermentation emissions. Stall-feeding, however, brings the necessity-opportunity to manage the manure and our results showed that MMS can be a determining factor in the GHG balance. Increasing the frequency of manure collection from stalls in favour of solid storage systems can reduce N2O emissions by up to 75%. Furthermore, dry manure storage reduced the CH4emissions of liquid slurry systems by more than 70%. Further benefits in terms of carbon (C) sequestration were identified along farm types from manure and crop residues applications in soils (with averages of −1.3 to −2.3 t CO2 eq ha−1 yr−1) and biomass growth in agroforestry systems (−1.2 to −2 t CO2 eq ha−1 yr−1). Together, soils and woody biomass offset 25–36% of farm emissions. We conclude that reduced farm size and increased livestock density lead to higher emissions per unit area, though this increase is smoothed by larger negative fluxes in soils (by higher C inputs) and woody biomass (by higher tree densities) until a steady state is reached. Average yield-scaled emissions, or product carbon footprints (CFs), resulted in 1.08 kg CO2 eq kg coffee berry−1, 0.64 kg CO2 eq kg maize−1 and 1.05 kg CO2 eq kg milk−1 on average. CFs did not always differ between farm types and intensification levels, meaning that increases in productivity were not higher than increases in GHG fluxes from intensification. This may be due to: 1) increases in productivity are the result of more processes other than N inputs; and/or 2) emissions from N inputs are overestimated by EFs and GHG calculators. Smallholders may benefit in the near future from climate initiatives and further field characterisation, models calibration and monitoring are required to overcome critical levels of uncertainty and provide more accurate estimations of GHG balances at farm-scale.

Graphical abstract

Farm-scale livelihood activities, greenhouse gas emissions (GHG) and carbon (C) sequestration in integrated smallholder crop-livestock system of Kenya. The numbers (1–5) represent farm components: (1) livestock, (2) manure management systems (MMS), (3) soil, (4) crops and (5) trees. The letters (a–e) are associated with fluxes of C and N: (a) fodder, crop residues and concentrates, (b) dung, urine and bedding materials, (c) inorganic fertiliser, manure and crop residues, (d) nitrogen uptake by crops, (e) the biomass harvested that can follow different pathways: livestock feed, compost heap or mulch.

Six, J., 2017. Greenhouse gas emissions from forest and agroecosystems in Sub-Saharan Africa

Six, J., 2017. Greenhouse gas emissions from forest and agroecosystems in Sub-Saharan Africa. EGU General Assembly Conference Abstracts, vol 19, p. 19401.

The Sub-Saharan African (SSA) landscape is vulnerable to ongoing land use change and climatic variability, which significantly influences carbon and greenhouse gas (GHG) dynamics. However, empirical data on GHG emissions from SSA ecosystems is lacking; hence, limiting our understanding of the potential effects of rapid land use and climate change. Here, I will present information on GHG dynamics in agroecosystems, aquatic ecosystems and forest ecosystems across multiple spatial and temporal scales to elucidate key drivers of GHG emissions from plots to regions.