211 research outputs found

    Urban agriculture: a global analysis of the space constraint to meet urban vegetable demand

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    Urban agriculture (UA) has been drawing a lot of attention recently for several reasons: the majority of the world population has shifted from living in rural to urban areas; the environmental impact of agriculture is a matter of rising concern; and food insecurity, especially the accessibility of food, remains a major challenge. UA has often been proposed as a solution to some of these issues, for example by producing food in places where population density is highest, reducing transportation costs, connecting people directly to food systems and using urban areas efficiently. However, to date no study has examined how much food could actually be produced in urban areas at the global scale. Here we use a simple approach, based on different global-scale datasets, to assess to what extent UA is constrained by the existing amount of urban space. Our results suggest that UA would require roughly one third of the total global urban area to meet the global vegetable consumption of urban dwellers. This estimate does not consider how much urban area may actually be suitable and available for UA, which likely varies substantially around the world and according to the type of UA performed. Further, this global average value masks variations of more than two orders of magnitude among individual countries. The variations in the space required across countries derive mostly from variations in urban population density, and much less from variations in yields or per capita consumption. Overall, the space required is regrettably the highest where UA is most needed, i.e., in more food insecure countries. We also show that smaller urban clusters (i.e., <100 km2 each) together represent about two thirds of the global urban extent; thus UA discourse and policies should not focus on large cities exclusively, but should also target smaller urban areas that offer the greatest potential in terms of physical space

    Meat freshness revealed by visible to near-infrared spectroscopy and principal component analysis

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    Increasing concerns about adulterated meat encouraged industry looking for new non-invasive methods for rapid accurate meat quality assessment. Main meat chromophores (myoglobin, oxy-myoglobin, fat, water, collagen) are characterized by close comparable absorption in visible to near-infrared (NIR) spectral region. Therefore, structural and compositional variations in meat may lead to relative differences in the absorption of light. Utilizing typical fiber-optic probes and integrating sphere, a degradation of pork samples freshness was observed at room temperature referring to the relative changes in absorbance of main meat chromophores. The application of principal component analysis (PCA) used for examination of measured absorbance spectra revealed more detailed sub-stages of freshness, which are not observed by the conventional analysis of the reflectance spectra. The results show a great potential of the combined application of optical-NIR spectroscopy with complementary use of PCA approach for assessing meat quality and monitoring relative absorbance alternation of oxymyoglobin and myoglobin in visible, and fat, water, collagen in NIR spectral ranges

    Nitrogen-neutrality: a step towards sustainability

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    We propose a novel indicator measuring one dimension of the sustainability of an entity in modern societies: Nitrogen-neutrality. N-neutrality strives to offset Nr releases an entity exerts on the environment from the release of reactive nitrogen (Nr) to the environment by reducing it and by offsetting the Nr releases elsewhere. N-neutrality also aims to increase awareness about the consequences of unintentional releases of nitrogen to the environment. N-neutrality is composed of two quantified elements: Nr released by an entity (e.g. on the basis of the N footprint) and Nr reduction from management and offset projects (N offset). It includes management strategies to reduce nitrogen losses before they occur (e.g., through energy conservation). Each of those elements faces specific challenges with regard to data availability and conceptual development. Impacts of Nr releases to the environment are manifold, and the impact profile of one unit of Nr release depends strongly on the compound released and the local susceptibility to Nr. As such, Nneutrality is more difficult to conceptualize and calculate than C-neutrality. We developed a workable conceptual framework for N-neutrality which was adapted for the 6th International Nitrogen Conference (N2013, Kampala, November 2013). Total N footprint of the surveyed meals at N2013 was 66 kg N. A total of US$ 3050 was collected from the participants and used to offset the conference’s N footprint by supporting the UN Millennium Village cluster Ruhiira in South- Western Uganda. The concept needs further development in particular to better incorporate the spatio-temporal variability of impacts and to standardize the methods to quantify the required N offset to neutralize the Nr releases impact. Criteria for compensation projects need to be sharply defined to allow the development of a market for N offset certificates Online supplementary data available from stacks.iop.org/ERL/9/115001/mmediainfo:eu-repo/semantics/publishedVersio

    Predicting the deforestation-trend under different carbon-prices

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    BACKGROUND: Global carbon stocks in forest biomass are decreasing by 1.1 Gt of carbon annually, owing to continued deforestation and forest degradation. Deforestation emissions are partly offset by forest expansion and increases in growing stock primarily in the extra-tropical north. Innovative financial mechanisms would be required to help reducing deforestation. Using a spatially explicit integrated biophysical and socio-economic land use model we estimated the impact of carbon price incentive schemes and payment modalities on deforestation. One payment modality is adding costs for carbon emission, the other is to pay incentives for keeping the forest carbon stock intact. RESULTS: Baseline scenario calculations show that close to 200 mil ha or around 5% of todays forest area will be lost between 2006 and 2025, resulting in a release of additional 17.5 GtC. Today's forest cover will shrink by around 500 million hectares, which is 1/8 of the current forest cover, within the next 100 years. The accumulated carbon release during the next 100 years amounts to 45 GtC, which is 15% of the total carbon stored in forests today. Incentives of 6 US/tCforvulnerablestandingbiomasspayedevery5yearwillbringdeforestationdownby50/tC for vulnerable standing biomass payed every 5 year will bring deforestation down by 50%. This will cause costs of 34 billion US/year. On the other hand a carbon tax of 12 /tCharvestedforestbiomasswillalsocutdeforestationbyhalf.Thetaxincomewill,ifenforced,decreasefrom6billionUS/tC harvested forest biomass will also cut deforestation by half. The tax income will, if enforced, decrease from 6 billion US in 2005 to 4.3 billion USin2025and0.7billionUS in 2025 and 0.7 billion US in 2100 due to decreasing deforestation speed. CONCLUSION: Avoiding deforestation requires financial mechanisms that make retention of forests economically competitive with the currently often preferred option to seek profits from other land uses. Incentive payments need to be at a very high level to be effective against deforestation. Taxes on the other hand will extract budgetary revenues from the regions which are already poor. A combination of incentives and taxes could turn out to be a viable solution for this problem. Increasing the value of forest land and thereby make it less easily prone to deforestation would act as a strong incentive to increase productivity of agricultural and fuelwood production, which could be supported by revenues generated by the deforestation tax

    Integrating place-specific livelihood and equity outcomes into global assessments of bioenergy deployment

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    __Abstract__ Integrated assessment models suggest that the large-scale deployment of bioenergy could contribute to ambitious climate change mitigation efforts. However, such a shift would intensify the global competition for land, with possible consequences for 1.5 billion smallholder livelihoods that these models do not consider. Maintaining and enhancing robust livelihoods upon bioenergy deployment is an equally important sustainability goal that warrants greater attention. The social implications of biofuel production are complex, varied and place-specific, difficult to model, operationalize and quantify. However, a rapidly developing body of social science literature is advancing the understanding of these interactions. In this letter we link human geography research on the interaction between biofuel crops and livelihoods in developing countries to integrated assessments on biofuels. We review case-study research focused on first-generation biofuel crops to demonstrate that food, income, land and other assets such as health are key livelihood dimensions that can be impacted by such crops and we highlight how place-specific and global dynamics influence both aggregate and distributional outcomes across these livelihood dimensions. We argue that place-specific production models and land tenure regimes mediate livelihood outcomes, which are also in turn affected by global and regional markets and their resulting equilibrium dynamics. The place-specific perspective suggests that distributional consequences are a crucial complement to aggregate outcomes; this has not been given enough weight in comprehensive assessments to date. By narrowing the gap between place-specific case studies and global models, our discussion offers a route towards integrating livelihood and equity considerations into scenarios of future bioenergy deployment, thus contributing to a key challenge in sustainability sciences

    Global wetland contribution to 2000-2012 atmospheric methane growth rate dynamics

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    Increasing atmospheric methane (CH4) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH4 as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999–2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH4 emissions from wetlands, the largest natural global CH4 source, for 2000–2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000–2012, boreal wetland CH4 emissions increased by 1.2 Tg yr−1 (−0.2–3.5 Tg yr−1), tropical emissions decreased by 0.9 Tg yr−1 (−3.2−1.1 Tg yr−1), yet globally, emissions remained unchanged at 184 ± 22 Tg yr−1. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH4 emissions have not contributed significantly to the period of renewed atmospheric CH4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH4 emissions, and a decrease in the atmospheric oxidative sink

    Simulating long-term carbon nitrogen and phosphorus biogeochemical cycling in agricultural environments

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    Understanding how agricultural practices alter biogeochemical cycles is vital for maintaining land productivity, food security, and other ecosystem services such as carbon sequestration. However, these are complex, highly coupled long-term processes that are difficult to observe or explore through empirical science alone. Models are required that capture the main anthropogenic disturbances, whilst operating across regions and long timescales, simulating both natural and agricultural environments, and shifts among these. Many biogeochemical models neglect agriculture or interactions between carbon and nutrient cycles, which is surprising given the scale of intervention in nitrogen and phosphorus cycles introduced by agriculture. This gap is addressed here, using a plant-soil model that simulates integrated soil carbon, nitrogen and phosphorus (CNP) cycling across natural, semi-natural and agricultural environments. The model is rigorously tested both spatially and temporally using data from long-term agricultural experiments across temperate environments. The model proved capable of reproducing the magnitude of and trends in soil nutrient stocks, and yield responses to nutrient addition. The model has potential to simulate anthropogenic effects on biogeochemical cycles across northern Europe, for long timescales (centuries) without site-specific calibration, using easily accessible input data. The results demonstrate that weatherable P from parent material has a considerable effect on modern pools of soil C and N, despite significant perturbation of nutrient cycling from agricultural practices, highlighting the need to integrate both geological and agricultural processes to understand effects of land-use change on food security, C storage and nutrient sustainability. The results suggest that an important process or source of P is currently missing in our understanding of agricultural biogeochemical cycles. The model could not explain how yields were sustained in plots with low P fertiliser addition. We suggest that plant access to organic P is a key uncertainty warranting further research, particularly given sustainability concerns surrounding rock sources of P fertiliser

    Pyrosequencing-Based Assessment of Bacterial Community Structure Along Different Management Types in German Forest and Grassland Soils

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    BACKGROUND: Soil bacteria are important drivers for nearly all biogeochemical cycles in terrestrial ecosystems and participate in most nutrient transformations in soil. In contrast to the importance of soil bacteria for ecosystem functioning, we understand little how different management types affect the soil bacterial community composition. METHODOLOGY/PRINCIPAL FINDINGS: We used pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to identify changes in bacterial diversity and community structure in nine forest and nine grassland soils from the Schwäbische Alb that covered six different management types. The dataset comprised 598,962 sequences that were affiliated to the domain Bacteria. The number of classified sequences per sample ranged from 23,515 to 39,259. Bacterial diversity was more phylum rich in grassland soils than in forest soils. The dominant taxonomic groups across all samples (>1% of all sequences) were Acidobacteria, Alphaproteobacteria, Actinobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Firmicutes. Significant variations in relative abundances of bacterial phyla and proteobacterial classes, including Actinobacteria, Firmicutes, Verrucomicrobia, Cyanobacteria, Gemmatimonadetes and Alphaproteobacteria, between the land use types forest and grassland were observed. At the genus level, significant differences were also recorded for the dominant genera Phenylobacter, Bacillus, Kribbella, Streptomyces, Agromyces, and Defluviicoccus. In addition, soil bacterial community structure showed significant differences between beech and spruce forest soils. The relative abundances of bacterial groups at different taxonomic levels correlated with soil pH, but little or no relationships to management type and other soil properties were found. CONCLUSIONS/SIGNIFICANCE: Soil bacterial community composition and diversity of the six analyzed management types showed significant differences between the land use types grassland and forest. Furthermore, bacterial community structure was largely driven by tree species and soil pH
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