Baranowski, Dariusz B. (author), Flatau, Maria K. (author), Flatau, Piotr J. (author), Karnawati, Dwikorita (author), Barabasz, Katarzyna (author), Lubaz, Michal (author), Latos, Beata (author), Schmidt, Jerome M. (author), Paski, Jaka A.I. (author), and Marzuki (author)
Format:
Journal article
Publication Date:
2020-05-19
Published:
UK: Nature Portfolio
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 207 Document Number: D13091
10 pages, Floods are a major contributor to natural disasters in Sumatra. However, atmospheric conditions leading to floods are not well understood due, among other factors, to the lack of a complete record of floods. Here, the 5 year flood record for Sumatra derived from governmental reports, as well as from crowd-sourcing data, based on Twitter messages and local newspapers’ reports, is created and used to analyze atmospheric phenomena responsible for floods. It is shown, that for the majority of analyzed floods, convectively coupled Kelvin waves, large scale precipitation systems propagating at ∼12 m/s along the equator, play the critical role. While seasonal and intraseasonal variability can also create conditions favorable for flooding, the enhanced precipitation related to Kelvin waves was found in over 90% of flood events. In 30% of these events precipitation anomalies were attributed to Kelvin waves only. These results indicate the potential for increased predictability of flood risk.
9 pages, Is there some kind of historical memory and folk wisdom that ensures that a community remembers about very extreme phenomena, such as catastrophic floods, and learns to establish new settlements in safer locations? We tested a unique set of empirical data on 1293 settlements founded in the course of nine centuries, during which time seven extreme floods occurred. For a period of one generation after each flood, new settlements appeared in safer places. However, respect for floods waned in the second generation and new settlements were established closer to the river. We conclude that flood memory depends on living witnesses, and fades away already within two generations. Historical memory is not sufficient to protect human settlements from the consequences of rare catastrophic floods.
Authors tested the hypothesis that our influence on others affects how much we are influenced by them. Findings suggested that participants reciprocated influence with their partner by gravitating toward the susceptible (but not insusceptible) partner's opinion. Further experiments revealed that reciprocity is both a dynamic process and is abolished when people believed that they interacted with a computer.
8 pages, Reducing food waste is widely recognized as critical for improving resource efficiency and meeting the nutritional demand of a growing human population. Here we explore whether the sharing economy can provide meaningful assistance to reducing food waste in a relatively low-impact and environmentally-sound way. Analyzing 170,000 postings on a popular peer-to-peer food-sharing app, we find that over 19 months, 90t of food waste with an equivalent retail value of £0.7 million were collected by secondary consumers and diverted from disposal. An environmental analysis focused on Greater London reveals that these exchanges were responsible for avoiding emission of 87–156t of CO2eq. Our results indicate that most exchanges were among users associated with lower income yet higher levels of education. These findings, together with the high collection rates (60% on average) suggest that the sharing economy may offer powerful means for improving resource efficiency and reducing food waste.
13 pages, No consensus exists regarding which are the most effective mechanisms to promote household action on climate change. We present a meta-analysis of randomised controlled trials comprising 3,092,678 observations, which estimates the effects of behavioural interventions holding other factors constant. Here we show that behavioural interventions promote climate change mitigation to a very small degree while the intervention lasts (d = −0.093 95% CI −0.160, −0.055), with no evidence of sustained positive effects once the intervention ends. With the exception of recycling, most household mitigation behaviours show a low behavioural plasticity. The intervention with the highest average effect size is choice architecture (nudges) but this strategy has been tested in a limited number of behaviours. Our results do not imply behavioural interventions are less effective than alternative strategies such as financial incentives or regulations, nor exclude the possibility that behavioural interventions could have stronger effects when used in combination with alternative strategies.
7pgs, Agricultural subsidies are an important factor for influencing food production and therefore
part of a food system that is seen as neither healthy nor sustainable. Here we analyse options
for reforming agricultural subsidies in line with health and climate-change objectives on one
side, and economic objectives on the other. Using an integrated modelling framework
including economic, environmental, and health assessments, we find that on a global scale
several reform options could lead to reductions in greenhouse gas emissions and improvements in population health without reductions in economic welfare. Those include a repurposing of up to half of agricultural subsidies to support the production of foods with beneficial
health and environmental characteristics, including fruits, vegetables, and other horticultural
products, and combining such repurposing with a more equal distribution of subsidy payments globally. The findings suggest that reforming agricultural subsidy schemes based on
health and climate-change objectives can be economically feasible and contribute to transitions towards healthy and sustainable food systems
6 pages, Advances in machine learning (ML) and artificial intelligence (AI) present an opportunity to build better tools and solutions to help address some of the world’s most pressing challenges, and deliver positive social impact in accordance with the priorities outlined in the United Nations’ 17 Sustainable Development Goals (SDGs). The AI for Social Good (AI4SG) movement aims to establish interdisciplinary partnerships centered around AI applications towards SDGs. We provide a set of guidelines for establishing successful long-term collaborations between AI researchers and application-domain experts, relate them to existing AI4SG projects and identify key opportunities for future AI applications targeted towards social good.