The collaborative power of AI and citizen science in advancing the Sustainable Development Goals
International Institute for Applied Systems Analysis (IIASA) – The SDGs were launched in 2015 to guide global efforts toward sustainability by 2030. However, as this deadline nears, many countries still lack the data needed to track SDG progress. For example, data are missing for nearly half of the 92 environmental indicators, only 15% of targets are on track, and all SDG targets suffer from insufficient data. Other challenges include poor data quality, limited data sharing, infrequent data collection, and lack of local data, hindering targeted interventions.
The perspective piece authored by IIASA researchers and published in Nature Sustainability, explores how combining the collaborative strengths of citizen science with AI can enhance both SDG monitoring and achievement.
Citizen science is already contributing to the SDGs by helping to address data gaps through public participation in scientific research. Successful applications have been demonstrated for SDGs 3 (good health and wellbeing), 11 (sustainable cities and communities), 14 (life below water), and 15 (life on land). However, despite increasing interest from the UN, National Statistical Offices (NSOs) and government agencies, challenges around data quality, lack of awareness and legal frameworks continue to limit the integration of citizen science data into SDG monitoring and reporting, and ultimately for informing policy decisions.
In parallel, recent advancements in AI have sparked interest in its potential to support sustainable development and address data challenges faced by NSOs and international organizations. AI’s major contributions to SDG progress include rapid analysis of large datasets, enhanced data accessibility, efficient data collection, task automation, real-time data and insights, and improved data visualization – potentially in a more cost-efficient way. Nonetheless, AI poses challenges and risks, including biases in training data that can produce unreliable results.
The authors propose that citizen science approaches can help mitigate AI risks by providing more localized and disaggregated, thus representative data.
“AI algorithms require large amounts of data, yet many parts of the world, especially the Global South, face data shortages. This lack of data, especially local data, can lead to AI models that don’t reflect specific local contexts, resulting in inaccurate findings, biases, and widening disparities between the Global North and South, as well as within countries,” explains Dilek Fraisl, lead author of the perspective piece and researcher in the Novel Data Ecosystems for Sustainability Research Group of the IIASA Advancing Systems Analysis Program. “Citizen science can help address this gap by providing more local and thus representative data, which can help improve the accuracy of AI results.”
Fraisl further explains that AI models are only as reliable as the data they are trained on, and any biases in this data can cause misleading results. So, while AI has great potential, its benefits will only be fully realized if its biases and limitations are carefully addressed.
The recent adoption of the Global Digital Compact within the UN’s Pact for the Future, a framework outlining principles, objectives, and actions for advancing an open, free, secure and human-centered digital future for all, highlights the need for global cooperation in AI governance. This framework emphasizes AI’s role in achieving sustainable development while also warning of its risks, such as potential threats to human rights. Incorporating citizen science approaches into AI can be a crucial step towards addressing these risks and ensuring that AI serves the common good.
“The integration of citizen science and AI offers a promising path forward in SDG monitoring and achievement. When used together, AI’s analytical power and citizen science’s contextual relevance create synergies that can address sustainability challenges more effectively. However, careful attention to inclusivity, representation, and governance is essential to harnessing these tools in a way that genuinely benefits all,” concludes Fraisl.
Journal Reference:
Dilek Fraisl, Linda See, Steffen Fritz, Mordechai Haklay (Muki) & Ian McCallum, ‘Leveraging the collaborative power of AI and citizen science for sustainable development’, Nature Sustainability (2024). DOI: 10.1038/s41893-024-01489-2
Article Source:
Press Release/Material by IIASA
Plant DNA metabarcoding unlocks vegetation secrets of the Tibetan plateau
Science China Press (SCP) – A recent study led by Dr. Kai Li from Zhejiang Normal University, in collaboration with international researchers, reveals the potential of plant DNA metabarcoding for monitoring plant compositions on the Tibetan Plateau (TP).
The study, published in Science China Earth Sciences, highlights the advantages of sedimentary DNA (sedDNA) extracted from lake sediments over traditional pollen analysis, providing a more detailed and localized perspective on vegetation monitoring and reconstruction.
The study involved the surface sediments from 59 small lakes and ponds located in the southwestern Tibetan Plateau. Using plant DNA metabarcoding, the researchers identified 186 terrestrial plant taxa, with 30.1% of them identified to the species level. In comparison, traditional pollen analysis identified only 75 plant taxa, with just 5.3% identified at the species level.
The results indicate that plant DNA metabarcoding captured a significantly higher number of taxa and achieved a greater taxonomic resolution than pollen analysis, especially for herbaceous taxa such as Asteraceae, Poaceae, and Cyperaceae.
“Our findings underscore the utility of plant DNA metabarcoding in accurately reflecting the vegetation composition in the immediate vicinity of lakes, offering a more precise method for vegetation monitoring,” said Dr. Li, lead author of the study. “This method not only improves our understanding of current biodiversity but also provides valuable insights into ecosystem dynamics in regions where conventional fieldwork is difficult.”
The team also found that while pollen analysis captures many regional signals, sedDNA primarily reflects very local plants at the community level. This distinction emphasizes the complementary nature of the two methods, with sedDNA offering superior resolution for local vegetation studies and pollen analysis remaining valuable for regional vegetation reconstructions.
Despite its advantages, the researchers acknowledged limitations in the sedDNA approach, such as the challenges of amplifying DNA from closely related species and the incompleteness of modern reference database. To address these issues, the authors suggest the use of multiple primers and the development of region-specific DNA reference database to enhance the accuracy and applicability of plant DNA metabarcoding.
The study’s findings have significant implications for biodiversity conservation, climate change research, and ecosystem monitoring. As climate change continues to alter environmental conditions on the Tibetan Plateau, understanding shifts in vegetation composition will be essential for assessing ecosystem resilience and biodiversity.
Additionally, plant DNA metabarcoding could play a key role in long-term ecological studies, enabling researchers to track changes in vegetation over time and providing a more comprehensive approach to palaeo-ecological research.
Journal Reference:
Wu, K., Li, K., Jia, W. et al. ‘Application of plant DNA metabarcoding of lake sediments for monitoring vegetation compositions on the Tibetan Plateau’, Science China Earth Sciences 67, 3594–3609 (2024). DOI: 10.1007/s11430-023-1358-0
Article Source:
Press Release/Material by Science China Press
New findings on the North Atlantic Oscillation displacement
University of Barcelona – There are still many unknowns about the causes leading to the North Atlantic Oscillation (NAO) shift — a critical climate phenomenon in the Northern Hemisphere — to the east and west of Iceland. To date, some hypotheses suggested that this process known to the international scientific community might be related to the impact of greenhouse gases on the planet.
Now, a study published in the journal Npj Climate and Atmospheric Science reveals that the NAO shift may be a consequence of natural variability in the atmospheric system rather than anthropogenic effects altering global climatology. The new study is led by experts María Santolaria-Otín and Javier García-Serrano, from the Faculty of Physics and the Group of Meteorology at the University of Barcelona.
Why does the NAO move longitudinally?
The North Atlantic Oscillation was first identified in the early 20th century, although its consequences were known to the people of northern Europe much earlier. The NAO is one of the most studied climate variability phenomena in the scientific community. However, many aspects of the dynamics and processes controlling its variability, both temporally and spatially, are still unknown, and the evidence for its past and expected future trends is still being debated.
Javier García-Serrano, professor at the UB’s Department of Applied Physics, says that “the atmosphere is a fluid system and shows a very chaotic and unpredictable behaviour. The study reveals that we can rule out some factors that explain this NAO pattern, namely anthropogenic forcing — i.e. the impact of greenhouse gases — or ocean coupling. Factors that could help to understand these shifts in the NAO are, for example, the interaction of winds with orography or the land-sea contrast. However, we need more research studies to confirm these hypotheses”.
On a global scale, the effects of this NAO shift are likely to be small, although they could affect Arctic Sea ice variability and, consequently, other remote areas of the planet. According to the findings, this process would not alter anthropogenic global warming trends.
Regional scale effects would be more important, since the NAO explains about half of the climate variability in the area of the European continent and the Mediterranean. “However, its impact on future predictions and projections would mainly be to modulate climate change trends in certain periods”, says García-Serrano.
In this context, the UB team has carried out and analysed simulations over a period of 500 years with a global climate model. María Santolaria-Otín, postdoctoral researcher and first author of the study, notes that “by applying this innovative methodology, it has been possible to isolate the effects of radiative forcing and ocean coupling and thus obtain conclusions that are impossible to reach with observational data alone”.
The NAO is considered one of the most influential patterns of low-frequency variability (teleconnections) in the climate of the Northern Hemisphere. In this challenging scenario, the UB team continues to expand their studies to understand what factors control NAO shifts and their remote effects in the context of global
Journal Reference:
Santolaria-Otín, M., García-Serrano, J., ‘Internal variability of the winter North Atlantic Oscillation longitudinal displacements’, npj Climate and Atmospheric Science 7, 291 (2024). DOI: 10.1038/s41612-024-00842-8
Article Source:
Press Release/Material by University of Barcelona
Towards smart cities: Integrating ground source heat pump systems with energy piles
Shibaura Institute of Technology – Human civilization is currently evolving at an unprecedented rate, with new breakthroughs every single day. This has become possible due to never-tapped-before levels of energy resources. However, the unsustainable development has recently raised concerns about adverse effects on the environment, resulting in a growing urgency to address issues pertaining to energy efficiency and climate change, especially in urban environments.
Notably, rapid urbanization has worsened the urban heat island effect, a phenomenon where a city experiences significantly warmer temperatures than the surrounding rural areas, increasing the energy demand for heating and cooling systems. As a result, conventional air source heat pumps often suffer from reduced efficiency in high-temperature urban environments, prompting higher electricity consumption and operating costs. This pressing issue underscores the need for innovative, sustainable energy solutions.
The integration of ground source heat pump (GSHP) systems with energy piles has emerged as a promising answer to this challenge. Energy piles uniquely combine the structural support of foundation systems with geothermal heat exchange capabilities, providing a dual-purpose solution that aligns with smart city development goals. In addition, advances in geotechnical and energy technologies have made it possible to implement these systems in diverse urban conditions.
In a recent study, a team of researchers, led by Professor Shinya Inazumi from the College of Engineering at the Shibaura Institute of Technology and Associate Professor Apiniti Jotisankasa from Kasetsart University, has comprehensively reviewed the integration of GSHP systems with energy piles.
Their paper was published in Smart Cities.
Prof. Inazumi remarks: “In recent years, there has been an increasing global emphasis on reducing carbon emissions and transitioning to renewable energy sources. This study aimed to provide a practical, scalable solution that bridges geotechnical engineering with renewable energy systems, contributing to sustainable urban infrastructure while addressing critical issues of energy management and environmental impact.”
The combination of GHSP systems and energy piles is a transformative approach to reducing electricity consumption and operating costs in cities facing growing energy demands. It takes advantage of stable ground temperatures to provide efficient heating and cooling, thus outperforming traditional air-source systems. Furthermore, it promotes heat dissipation through optimized groundwater circulation, ensuring the longevity and performance of geothermal systems.
In the review, the researchers emphasize the need for tailored design and adaptive management of the proposed dual-structure infrastructure and advocate site-specific strategies to maximize benefits. In residential, commercial, and industrial buildings, these systems can significantly reduce heating and cooling costs while reducing carbon emissions.
Smart cities can incorporate energy stacks into infrastructure replanning, aligning with climate action goals and improving resilience to the urban heat island effect. Notably, energy piles can be embedded in roads, bridges, and underground transportation systems to manage thermal loads. This integration could optimize the energy efficiency of transportation facilities and extend their structural life. Furthermore, these systems can complement solar and wind energy by providing stable thermal energy storage, improving the overall efficiency of the current energy system.
“Government-backed subsidies or tax rebates could encourage the widespread adoption of this technology, further reducing barriers such as high initial installation costs and promoting sustainable urban growth,” highlights Prof. Inazumi.
Lastly, the researchers encourage scientists and urban planners to explore the GHSP system and the energy pile-based integrated approach to promote sustainable urban development.
By bridging the gap between geotechnical engineering and renewable energy, this work lays the foundation for sustainable urban living, and by addressing energy challenges currently faced by humanity, it aims to pave the way for resilient, energy-efficient urban development!
Journal Reference:
Chanchayanon, T., Chaiprakaikeow, S., Jotisankasa, A., & Inazumi, S., ‘Enhancing Smart City Energy Efficiency with Ground Source Heat Pump Systems and Integrated Energy Piles’, Smart Cities 7 (6), 3547-3586 (2024). DOI: 10.3390/smartcities7060138
Article Source:
Press Release/Material by Shibaura Institute of Technology
Featured image credit: Gerd Altmann | Pixabay
