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India is facing a double burden of malnourishment with co-existences of under- and over-nourishment. Various socioeconomic factors play an essential role in determining dietary choices. Agriculture is one of the major emitters of greenhouse gases (GHGs) in India, contributing 18% of total emissions. It also consumes freshwater and uses land significantly. We identify eleven Indian diets by applying k-means cluster analysis on latest data from the Indian household consumer expenditure survey. The diets vary in calorie intake [2289-3218 kcal/Consumer Unit (CU)/day] and dietary composition. Estimated embodied GHG emissions in the diets range from 1.36 to 3.62 kg CO2eq./CU/day, land footprint from 4 to 5.45 m(2)/CU/day, whereas water footprint varies from 2.13 to 2.97m(3)/CU/day. Indian diets deviate from a healthy reference diet either with too much or too little consumption of certain food groups. Overall, cereals, sugar, and dairy products intake are higher. In contrast, the consumption of fruits and vegetables, pulses, and nuts is lower than recommended. Our study contributes to deriving required polices for the sustainable transformation of food systems in India to eliminate malnourishment and to reduce the environmental implications of the food systems. (c) 2020 Elsevier B.V. All rights reserved.
Agriculture in India accounts for 18% of greenhouse gas (GHG) emissions and uses significant land and water. Various socioeconomic factors and food subsidies influence diets in India. Indian food systems face the challenge of sustainably nourishing the 1.3 billion population. However, existing studies focus on a few food system components, and holistic analysis is still missing. We identify Indian food systems covering six food system components: food consumption, production, processing, policy, environmental footprints, and socioeconomic factors from the latest Indian household consumer expenditure survey. We identify 10 Indian food systems using k-means cluster analysis on 15 food system indicators belonging to the six components. Based on the major source of calorie intake, we classify the ten food systems into production-based (3), subsidy-based (3), and market-based (4) food systems. Home-produced and subsidized food contribute up to 2000 kcal/consumer unit (CU)/day and 1651 kcal/CU/day, respectively, in these food systems. The calorie intake of 2158 to 3530 kcal/CU/day in the food systems reveals issues of malnutrition in India. Environmental footprints are commensurate with calorie intake in the food systems. Embodied GHG, land footprint, and water footprint estimates range from 1.30 to 2.19 kg CO(2)eq/CU/day, 3.89 to 6.04 m(2)/CU/day, and 2.02 to 3.16 m(3)/CU/day, respectively. Our study provides a holistic understanding of Indian food systems for targeted nutritional interventions on household malnutrition in India while also protecting planetary health.
In this paper we report on a long multi-wavelength observational campaign of the supergiant fast X-ray transient prototype IGR J17544-2619. A 150 ks-long observation was carried out simultaneously with XMM-Newton and NuSTAR, catching the source in an initial faint X-ray state and then undergoing a bright X-ray outburst lasting approximately 7 ks. We studied the spectral variability during outburst and quiescence by using a thermal and bulk Comptonization model that is typically adopted to describe the X-ray spectral energy distribution of young pulsars in high mass X-ray binaries. Although the statistics of the collected X-ray data were relatively high, we could neither confirm the presence of a cyclotron line in the broad-band spectrum of the source (0.5-40 keV), nor detect any of the previously reported tentative detections of the source spin period. The monitoring carried out with Swift/XRT during the same orbit of the system observed by XMM-Newton and NuSTAR revealed that the source remained in a low emission state for most of the time, in agreement with the known property of all supergiant fast X-ray transients being significantly sub-luminous compared to other supergiant X-ray binaries. Optical and infrared observations were carried out for a total of a few thousand seconds during the quiescence state of the source detected by XMM-Newton and NuSTAR. The measured optical and infrared magnitudes were slightly lower than previous values reported in the literature, but compatible with the known micro-variability of supergiant stars. UV observations obtained with the UVOT telescope on-board Swift did not reveal significant changes in the magnitude of the source in this energy domain compared to previously reported values.
Reducing greenhouse gas emissions in food systems is becoming more challenging as food is increasingly consumed away from producer regions, highlighting the need to consider emissions embodied in trade in agricultural emissions accounting.
To address this, our study explores recent trends in trade-adjusted agricultural emissions of food items at the global, regional, and national levels.
We find that emissions are largely dependent on a country’s consumption patterns and their agricultural emission intensities relative to their trading partners’.
The absolute differences between the production-based and trade-adjusted emissions accounting approaches are especially apparent for major agricultural exporters and importers and where large shares of emission-intensive items such as ruminant meat, milk products and rice are involved.
In relative terms, some low-income and emerging and developing economies with consumption of high emission intensity food products show large differences between approaches.
Similar trends are also found under various specifications that account for trade and re-exports differently.
These findings could serve as an important element towards constructing national emissions reduction targets that consider trading partners, leading to more effective emissions reductions overall.
Annual greenhouse gas emissions have increased more than threefold between 1950 and 2014, posing a major threat to the integrity of the entire earth system and subsequently to humankind. Consequently, roadmaps towards low-carbon pathways are urgently needed. Our study contributes to a more detailed understanding of the dynamics of country based emission patterns and uses them to discuss prospective low-carbon pathways for countries. As availability of databases on sectoral emissions substantially increased, we employ machine learning techniques to classify emission features and pathways. By doing so, 18 representative emission patterns are derived. Overall emissions from seven sectors and for 167 countries covering the time span from 1950 to 2014 have been used in the analyses. The following significant trends can be observed: a) increasing per capita emissions due to growing fossil fuel use in many parts of the world, b) a decline in per capita emissions in some countries, and c) a shift in the emission shares, i.e., a reduction of agricultural and land use contributions in certain regions. Using the emission patterns, their dynamics, and best performing countries as role models, we show the possibility for gaining a decent human development without significantly increasing per capita emissions.
Food system innovations will be instrumental to achieving multiple Sustainable Development Goals (SDGs). However, major innovation breakthroughs can trigger profound and disruptive changes, leading to simultaneous and interlinked reconfigurations of multiple parts of the global food system. The emergence of new technologies or social solutions, therefore, have very different impact profiles, with favourable consequences for some SDGs and unintended adverse side-effects for others. Stand-alone innovations seldom achieve positive outcomes over multiple sustainability dimensions. Instead, they should be embedded as part of systemic changes that facilitate the implementation of the SDGs. Emerging trade-offs need to be intentionally addressed to achieve true sustainability, particularly those involving social aspects like inequality in its many forms, social justice, and strong institutions, which remain challenging. Trade-offs with undesirable consequences are manageable through the development of well planned transition pathways, careful monitoring of key indicators, and through the implementation of transparent science targets at the local level.
Avoiding food loss and waste may counteract the increasing food demand and reduce greenhouse gas (GHG) emissions from the agricultural sector. This is crucial because of limited options available to increase food production. In the year 2010, food availability was 20% higher than was required on a global scale. Thus, a more sustainable food production and adjusted consumption would have positive environmental effects. This study provides a systematic approach to estimate consumer level food waste on a country scale and globally, based on food availability and requirements. The food requirement estimation considers demographic development, body weights, and physical activity levels. Surplus between food availability and requirements of a given country is considered as food waste. The global food requirement changed from 2,300 kcal/cap/day to 2,400 kcal/cap/day during the last 50 years, while food surplus grew from 310 kcal/cap/day to 510 kcal/cap/day. Similarly, GHG emissions related to the food surplus increased from 130 Mt CO2eq/yr to 530 Mt CO2eq/yr, an increase of more than 300%. Moreover, the global food surplus may increase up to 850 kcal/cap/day, while the total food requirement will increase only by 2%-20% by 2050. Consequently, GHG emissions associated with the food waste may also increase tremendously to 1.9-2.5 Gt CO2eq/yr.
Hungry cities: how local food self-sufficiency relates to climate change, diets, and urbanisation
(2019)
Using a newly developed model approach and combining it with remote sensing, population, and climate data, first insights are provided into how local diets, urbanisation, and climate change relates to local urban food self-sufficiency. In plain terms, by utilizing the global peri-urban (PU) food production potential approximately lbn urban residents (30% of global urban population) can be locally nourished, whereby further urbanisation is by far the largest pressure factor on PU agriculture, followed by a change of diets, and climate change. A simple global food transport model which optimizes transport and neglects differences in local emission intensities indicates that CO2 emissions related to food transport can be reduced by a factor of 10.
Armed conflicts trigger region-specific mechanisms that affect land use change. Deforestation is presented as one of the most common negative environmental impacts resulting from armed conflicts, with relevant consequences in terms of greenhouse gas emissions and loss of ecosystem services. However, the impact of armed conflict on forests is complex and may simultaneously lead to positive and negative environmental outcomes, i.e. forest regrowth and deforestation, in different regions even within a country. We investigate the impact that armed conflict exerted over forest dynamics at different spatial scales in Colombia and for the global tropics during the period 1992–2015. Through the analysis of its internally displaced population (departures) our results suggest that, albeit finding forest regrowth in some municipalities, the Colombian conflict predominantly exerted a negative impact on its forests. A further examination of georeferenced fighting locations in Colombia and across the globe shows that conflict areas were 8 and 4 times more likely to undergo deforestation, respectively, in the following years in relation to average deforestation rates. This study represents a municipality level, long-term spatial analysis of the diverging effects the Colombian conflict exerted over its forest dynamics over two distinct periods of increasing and decreasing conflict intensity. Moreover, it presents the first quantified estimate of conflict's negative impact on forest ecosystems across the globe. The relationship between armed conflict and land use change is of global relevance given the recent increase of armed conflicts across the world and the importance of a possible exacerbation of armed conflicts and migration as climate change impacts increase.
Colombia's agriculture, forestry and other land use sector accounts for nearly half of its total greenhouse gas (GHG) emissions. The importance of smallholder deforestation is comparatively high in relation to its regional counterparts, and livestock agriculture represents the largest driver of primary forest depletion. Silvopastoral systems (SPSs) are presented as agroecological solutions that synergistically enhance livestock productivity, improve local farmers' livelihoods and hold the potential to reduce pressure on forest conversion. The department of Caquetá represents Colombia's most important deforestation hotspot. Targeting smallholder livestock farms through survey data, in this work we investigate the GHG mitigation potential of implementing SPSs for smallholder farms in this region. Specifically, we assess whether the carbon sequestration taking place in the soil and biomass of SPSs is sufficient to offset the per-hectare increase in livestock GHG emissions resulting from higher stocking rates. To address these questions we use data on livestock population characteristics and historic land cover changes reported from a survey covering 158 farms and model the carbon sequestration occurring in three different scenarios of progressively-increased SPS complexity using the CO2 fix model. We find that, even with moderate tree planting densities, the implementation of SPSs can reduce GHG emissions by 2.6 Mg CO2e ha−1 yr−1 in relation to current practices, while increasing agriculture productivity and contributing to the restoration of severely degraded landscapes.