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About

ABOUT crAIRsis

Acronym crAIRsis
Duration  January 3rd 2024 – January 2nd 2027
Grant No. 7373
Funded under Science Fund of the Republic of Serbia, Program PRISMA
Project budget € 284,907.86
Coordinated by Prof. Milan Tuba, Singidunum University, Belgrade, Serbia
Participants Singidunum University, Belgrade, Serbia | Institute of Physics Belgrade

The crAIRsis project represents a groundbreaking initiative in the field of environmental science, particularly focused on addressing the complexities of air pollution during various crisis scenarios. This ambitious project harnesses a unique blend of disciplines, cutting-edge technology, and comprehensive strategies to tackle one of the most pressing issues of our times—air quality deterioration during global crises. Below is a detailed overview of the project's core components:

Transdisciplinary Approach 

The crAIRsis project is characterized by its transdisciplinary approach, integrating artificial intelligence, environmental science, data science, and public policy. This fusion is designed to tackle air pollution challenges comprehensively. By leveraging expertise across these disciplines, the project develops innovative solutions that are not only scientifically robust but also viable in public policy and practical applications. This approach ensures that the project's strategies and solutions can effectively address the multifaceted nature of air pollution, particularly in times of crisis.

Research Infrastructure

Software Infrastructure and Open Science: At the core of the crAIRsis project is a sophisticated software infrastructure that plays a critical role in facilitating research and innovation. This infrastructure supports all stages of the research process from data collection and analysis to modeling and dissemination of results. It aligns with open science practices by integrating with the European Open Science Cloud (EOSC), thereby ensuring that the project's findings are accessible, reproducible, and reusable by the global scientific community.

Interactive Resources

Interactive Visualizations and User Engagement: The project utilizes interactive visualizations to make its research accessible and engaging. These tools allow stakeholders to interact with data through customizable graphs and scenario simulations, which not only enhances user engagement but also deepens stakeholders' understanding of the project's findings.
Results Presentation and Access: A dedicated section on the project’s platform adheres to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This section provides access to searchable databases, downloadable datasets, and detailed analyses of the project’s outcomes, ensuring that the data is transparent and accessible to researchers, policymakers, and the public.

Community and Outreach

Workshops and Stakeholder Engagement: The crAIRsis project places a strong emphasis on community and stakeholder engagement. It regularly organizes workshops, seminars, and public events to foster dialogue and collaboration between researchers, policymakers, and the public. These events serve as platforms for disseminating project results, gathering feedback, and refining strategies based on real-world inputs. Resources from these events, such as presentations and feedback reports, are made available for download, providing valuable insights into the project's impact on policy and research.

By integrating these various components, the crAIRsis project not only advances scientific understanding and technological innovation but also ensures that these advancements have a tangible impact on society and policy. It sets a new standard for how research projects can effectively address global challenges through a holistic and integrative approach.

PAST, PRESENT AND FUTURE

Past Developments
The crAIRsis project was launched in response to a critical gap in our understanding of air quality's (AQ) response to concurrent global crises. Historically, suboptimal AQ has been a major public health concern, accountable for millions of fatalities and chronic health issues annually. The advent of rapid global changes, fueled by population growth, has precipitated crises such as the COVID-19 pandemic and the war in Europe. These events have profoundly modified human behaviors and governmental policies, impacting not only health and economic systems but also the environmental matrix, particularly air quality. The simultaneous occurrence of the pandemic and the war has introduced complex challenges including energy shortages, mass migrations, and infrastructural damages, underscoring the urgent need for a sophisticated understanding of air pollution dynamics during crises to promote global sustainability.

Present Knowledge

Current understanding of global air pollution dynamics, encompassing degradation, accumulation, deposition, and dispersion, remains markedly insufficient, particularly within the context of multifaceted crises. There is a notable deficiency in comprehension regarding how these processes are influenced by various factors such as chemical interactions, physicochemical properties, meteorological conditions, and the geographical features of measurement locations. Moreover, shifts in overall contaminant emission fluxes due to environmental alterations significantly affect both ecosystems and human health.

Future Directions

To navigate these challenges, it is paramount to embrace a revolutionary methodological paradigm. This paradigm must harness big-data-driven insights to elucidate issues, facilitate informed decision-making, and adapt strategies promptly in our dynamic world. The crAIRsis project is poised to bridge this knowledge gap by developing the inaugural AI-driven framework designed to detect, characterize, and predict alterations in air pollution precipitated by global crises. This framework will amalgamate diverse data streams, including governmental and international agency inputs, applying cutting-edge big data analytics. This initiative not only aims to enhance our scientific understanding but also strives to fortify global public health strategies against the backdrop of increasing environmental crises.

PIONEERING THE FUTURE OF ENVIRONMENTAL SCIENCE

Environmental science is at a pivotal moment in its mission to secure a sustainable future in a world that is increasingly complex, rapidly changing, and burdened by crises and overpopulation. The challenges facing this mission include the intricate interconnectivity of environmental phenomena, a shortfall in data-driven knowledge, especially on a global scale, asymmetric access to data and information, the absence of robust infrastructure for managing environmental big data, and gaps in access to technological innovation, particularly in advanced data science and artificial intelligence (AI).


Standing at the forefront of addressing these challenges, the crAIRsis project, coordinated by Prof. Milan Tuba at Singidunum University and funded under the Science Fund of the Republic of Serbia, drives interdisciplinary, evidence-based research and innovation. It emphasizes the necessity of employing the most advanced statistical and AI-based methods, supported by data-centric, efficient, scalable, and robust infrastructure. This approach is crucial for understanding the crisis-induced evolution of air pollution (AP) at local, regional, and global levels, anticipating future trends, and confronting global sustainability challenges.


Recognizing the need for a novel approach, crAIRsis is dedicated to enhancing environmental information and knowledge, thereby aiding environmental science in overcoming current challenges related to AP. It also aims to facilitate air quality-protective decision-making and action in times of crisis. By achieving these goals, crAIRsis will significantly elevate the scientific understanding of AP-related processes during crises through multi-disciplinary, in-depth data exploration and AI-based modeling. Furthermore, it will foster institutional, national, and international cooperation, engaging stakeholders across various levels and sectors for collaborative innovation.

REVOLUTIONIZING AIR POLLUTION ANALYSIS THROUGH AI

Marking a departure from the status quo, crAIRsis is set to offer the first framework capable of modeling AP alterations caused by crises. This framework uniquely combines explainable AI (XAI) components with profound optimization algorithms, addressing a gap where previous research in environmental science often fell short. The project, set to run from January 2024 to January 2027 with a budget of €284,907.86, is poised to break new ground in error estimation and data analysis, leveraging an unprecedented volume, variety, and veracity of data.


Ambitiously, crAIRsis seeks to:


  • Enhance global understanding of the environmental fate of monitored AP in crises, identifying key factors and processes. 
  • Integrate environmental science with other disciplines, notably AI, fostering scientific breakthroughs and informed environmental practices and policies.
  • Provide concepts for in-depth, large-scale, global crisis-related AP studies, utilizing advanced AI methods like ML, metaheuristics, and XAI to improve model transparency, performance, and decision-making under uncertainty.

  • Facilitate data access and manage the exploration and exploitation of results.

  • Develop AI-based software for processing complex spatio-temporal data, ensuring continuous improvement and cost-effective scientific software development.

  • Introduce novel, interactive visualization designs to reveal new data patterns and insights.

  • Set the stage for large-scale flagship projects addressing various scientific fields, potentially extending the crAIRsis project to encompass other AI methods, environmental data, regions, and research areas, including pollutant exposure and health effect assessment.

  • Lay a foundation for federating scientific research and services at community, institutional, national, and international levels.

crAIRsis is not just a project; it is a vision for a new era of environmental science, where data-driven, AI-enhanced research paves the way for sustainable, informed responses to the world's most pressing environmental challenges.