Harnessing the Power of Artificial Intelligence in Climate Change Mitigation: Opportunities and Challenges for Public Health

ANGYIBA ANDIGEMA; NGNOTOUOM NGNOKAM TANIA CYRIELLE; MAFO KAMGA Lethicia Danaëlle; EWANE Ekwelle

doi:10.20944/preprints202403.0360.v1

Submitted:

05 March 2024

Posted:

06 March 2024

You are already at the latest version

Abstract

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

Keywords:

Artificial intelligence

;

climate change

;

public health

;

disaster preparedness

;

disease surveillance

Subject:

Computer Science and Mathematics - Artificial Intelligence and Machine Learning

Introduction

As climate change continues to loom as a grave threat, the need for efficient mitigation strategies becomes increasingly urgent. Within this context, the transformative power of artificial intelligence (AI) has gained recognition for its ability to address complex environmental challenges. With proven success across various industries, AI now holds the potential to revolutionize public health efforts aimed at mitigating the impacts of climate change. By leveraging AI technologies, adaptive capabilities can be enhanced, decision-making processes improved, and resource allocations optimized in the face of global climate-related health pressures.

The objective of this review article is to critically assess the potential benefits and challenges associated with harnessing AI capabilities to alleviate the adverse effects of climate change on human health. By examining existing literature and highlighting current initiatives, we aim to shed light on how AI can be effectively deployed to mitigate climate change and bolster public health initiatives. Furthermore, we will delve into the inherent difficulties, including data constraints, institutional obstacles, and ethical concerns that must be addressed for the successful utilization of AI in public health within the context of climate change.

Through our comprehensive analysis, we endeavor to provide valuable insights for practitioners, researchers, and policymakers, enabling them to adopt AI-driven strategies in the creation of resilient and sustainable public health systems in the face of climate change.

Definition: Climate Change and Public Health

Climate change refers to long-term shifts in weather patterns, including changes in temperature, precipitation, and extreme weather events, caused primarily by human activities, such as the burning of fossil fuels and deforestation [1]. These changes have far-reaching effects on ecosystems, economies, and human health, making it imperative to mitigate climate change to secure a sustainable future.

Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks requiring human intelligence. These systems are capable of learning, reasoning, and making decisions based on data analysis, pattern recognition, and prediction models [2]. Through AI, we can leverage technology for environmental monitoring, policy optimization, and risk assessment in the context of climate change and its impact on public health.

Mitigation involves efforts to reduce greenhouse gas emissions and limit global warming to prevent further climate change. This includes transitioning to renewable energy sources, implementing energy-efficient practices, enhancing sustainable transportation, and promoting afforestation and reforestation initiatives [3]. By implementing effective mitigation strategies, we can minimize the adverse effects of climate change, safeguard public health, and promote sustainable development.

Public health encompasses the collective well-being and health of communities and populations. It involves the prevention, promotion, and protection of health through various interventions, including policy development, disease surveillance, healthcare access, and environmental health. Public health plays a crucial role in addressing the health impacts of climate change, as it aims to reduce vulnerability, build resilience, and ensure equitable health outcomes in the face of changing environmental conditions [9].

Through a nuanced understanding of these terms, we can delve deeper into the opportunities and challenges associated with harnessing AI's power in climate change mitigation, ultimately contributing to a more sustainable and healthier future.

Climate Change-Related Health Issues

As global temperatures continue to rise, the direct and indirect impacts of climate change on human health become increasingly evident and alarming. The urgency and importance of addressing climate change can be better understood by considering the following examples and statistics:

Increased heatwaves and extreme heat events: As a result of climate change, there has been a significant rise in the frequency and intensity of heatwaves. Heatwaves have been linked to numerous health issues, including heatstroke, dehydration, cardiovascular problems, and respiratory illnesses. For instance, the European heatwave in 2003 was responsible for an estimated 70,000 deaths [5]. Similarly, a study projected that by 2100, extreme heat events could lead to 12,000 additional deaths annually in the United States alone [6].
Changing geographic distribution and prevalence of diseases: Climate change can affect the spread and transmission of diseases. For instance, the expansion of disease-carrying vectors like mosquitoes due to warmer temperatures has contributed to the increased prevalence of vector-borne diseases such as malaria, dengue fever, and Zika virus. In addition, changing rainfall patterns and temperature fluctuations can impact the prevalence and spread of water-borne diseases like cholera, typhoid, and diarrhea. According to the World Health Organization, climate change is projected to cause an additional 250,000 deaths per year between 2030 and 2050 due to malnutrition, malaria, diarrhea, and heat stress [7].
Worsening air quality: Climate change exacerbates air pollution, which has detrimental effects on respiratory health. Rising temperatures can lead to the formation of ground-level ozone, a pollutant that contributes to respiratory conditions such as asthma, bronchitis, and chronic obstructive pulmonary disease (COPD). Heatwaves further worsen air quality by increasing the release of pollutants from industrial sources and wildfires. In 2015, air pollution caused 4.2 million premature deaths worldwide, making it the fourth leading risk factor for premature mortality [8].
Increased frequency and intensity of natural disasters: Climate change has been linked to the occurrence of more frequent and severe natural disasters, including forest fires, hurricanes, and floods. These events directly threaten human lives and health through injuries, displacement, and loss of access to basic necessities like clean water and healthcare facilities. For example, Hurricane Katrina in 2005 resulted in over 1,800 deaths and had long-lasting health effects on the affected population, including increased rates of mental health disorders and respiratory illnesses [9].

These concrete examples and statistics demonstrate the urgent need to address climate change to protect human health. The impacts on health are not theoretical or distant, but rather tangible and immediate. Failure to take effective action to mitigate climate change poses a significant threat to the well-being and survival of individuals and communities worldwide.

Artificial Intelligence and Climate Change Mitigation

Artificial intelligence (AI) holds great promise in mitigating climate change by revolutionizing various sectors. By incorporating current examples and case studies, we can better understand how AI has already made significant contributions to climate change mitigation.

One of the areas where AI has demonstrated its potential is climate modeling and weather forecasting. Improved climate models that utilize AI algorithms provide decision-makers with valuable information about the risks and opportunities associated with climate change. Machine learning algorithms analyze past weather data and identify trends that enable accurate forecasts of future weather patterns. The National Center for Atmospheric Research (NCAR) is developing a machine learning-based system to provide more precise and localized rainfall forecasts, enhancing agricultural yields and minimizing flood damages [10].

In the energy sector, AI is being employed to optimize energy use and reduce carbon emissions. Smart grids and energy management systems equipped with AI algorithms effectively manage renewable energy sources like wind and solar power, thereby reducing the environmental impact of energy production. Google, for instance, utilizes AI algorithms to evaluate data collected by sensors in their data centers, resulting in a 15% reduction in energy consumption and carbon emissions [11].

Transportation networks can also benefit from AI technologies to minimize carbon emissions. Autonomous vehicles, driven by AI algorithms, optimize driving routes, speeds, and fuel efficiency, leading to reduced energy consumption. These advancements contribute to a greener and more sustainable transportation system [12].

Furthermore, AI can facilitate the regulation of natural resource consumption and land use practices. AI algorithms assist in managing forests, agriculture, and fisheries more effectively, thereby reducing carbon emissions and promoting sustainability [13]. Conservation Metrics is using AI algorithms to analyze satellite photographs in real time, allowing forest managers to take timely action and prevent deforestation [14].

By highlighting these current examples and case studies, it becomes evident that AI has proven its practicality and potential in addressing climate change. From improving climate models and optimizing energy use to reducing carbon emissions in transportation and regulating natural resource consumption, AI is a powerful tool in climate change mitigation efforts. However, challenges related to data availability, ethical considerations, and policy implementation need to be addressed to fully harness the power of AI for public health and climate change mitigation.

Potential Benefits and Limitations of using AI in addressing Climate Change

Potential Benefits of AI in addressing Climate Change:

Improved Climate Modeling and Prediction: AI algorithms can analyze vast amounts of data from various sources, such as satellite imagery, weather sensors, and climate models. This enables more accurate predictions of climate patterns, helping us understand the implications of climate change and take proactive measures. For example, AI has been used to improve hurricane tracking and forecasting, allowing communities to better prepare and evacuate if necessary [15].

Optimization of Renewable Energy Systems: AI can optimize the effectiveness and design of renewable energy systems like wind turbines and solar panels. By analyzing data on wind patterns, climate conditions, and energy usage, AI can maximize energy output while reducing waste. For instance, AI has been used to improve the orientation and performance of solar panels, increasing their energy efficiency [16].
Identifying Climate Change Hotspots: AI can identify regions more susceptible to the impacts of climate change, such as sea-level rise, droughts, or extreme weather events. By analyzing data on weather patterns, sea level rise projections, and population density, AI can help stakeholders prioritize and implement mitigation and adaptation measures. For example, AI has been used to identify regions prone to flooding and inform the development of resilient infrastructure [17].
Climate Change Automation Operations for Mitigation and Adaptation: AI can automate various climate change adaptation and mitigation processes, freeing up human resources and enhancing efficiency. For instance, AI can track deforestation in real-time by analyzing satellite imagery, enabling prompt action to prevent further loss of carbon-absorbing forests. AI algorithms can also analyze historical data on natural disasters to predict and forecast future events, aiding in disaster preparedness and response planning [18].

Limitations of AI in addressing Climate Change:

Data Bias: AI systems heavily rely on the quality and availability of data they are trained on. In the case of climate change, past data may not accurately reflect current or future conditions, potentially leading to inaccurate predictions or recommendations. Addressing data biases and ensuring diverse and robust datasets is crucial for reliable AI outcomes [19].
Technical Restrictions: Despite advancements, AI may still face challenges in accurately predicting complex and dynamic weather patterns. Real-time interpretation of data from multiple sources can also be a technical constraint. Continual improvement of AI algorithms and monitoring systems is required to overcome these limitations [20].
Ethical Concerns: There is a growing concern that AI decision-making may become automated without adequate human oversight. In the context of climate change, decisions with long-term consequences, such as resource allocation or policy implementation, should involve human judgment. Ensuring ethical guidelines and accountability frameworks will be essential to address these concerns [21].
Cost and Accessibility: AI technologies can be costly to research, develop, and deploy, which may hinder their accessibility, especially in developing countries or regions with limited resources. Efforts should be made to make AI technology more affordable and accessible, ensuring equitable distribution and benefits for all communities [22].

Moving forward, it is imperative to prioritize the development and refinement of AI systems that address the multifaceted challenges of climate change while ensuring accessibility, equity, and transparency. Collaborative efforts involving governments, researchers, and communities will be essential to harnessing the full potential of AI in climate change mitigation and adaptation.

Recommendations to accelerate the use ai to greatly enhance climate change mitigation

Place emphasis on open data science: Open data science is essential for encouraging improved research cooperation and supporting reproducibility. By making data openly available, researchers from different disciplines can collaborate more effectively and verify the findings of others. This promotes transparency and ensures that AI-based climate solutions are built on a solid foundation of reliable data. Governments, research institutions, and organizations should actively promote the sharing of data to facilitate data-driven, collaborative decision-making [23].
Create Human Machine Interfaces: AI solutions can be complex and challenging for non-technical workers to navigate. To ensure widespread adoption and usability, scientists should develop user-friendly human-machine interfaces specifically tailored for climate change mitigation [24]. These interfaces should be intuitive and require minimal technical expertise, enabling non-technical workers to engage with AI models and contribute to decision-making processes. This will democratize AI technology and empower a broader range of stakeholders to actively participate in climate change mitigation efforts.
Promote a Multidisciplinary Approach: Climate change is a complex issue that requires a comprehensive strategy considering environmental, social, and economic factors. To address this complexity effectively, it is crucial to promote a multidisciplinary approach that brings together experts from a variety of fields. By involving scientists, policymakers, economists, social scientists, and other stakeholders, we can integrate diverse perspectives, knowledge, and expertise into AI-based climate solutions. This interdisciplinary collaboration will allow for a holistic understanding of climate change challenges and the development of innovative, integrated solutions [25].
Data sharing, user-friendliness, and a multidisciplinary approach are just a few of the numerous obstacles that still need to be solved to fully harness the power of AI in climate change mitigation [26]. Overcoming these challenges requires interdisciplinary research efforts that bridge the gap between AI methodologies and the physical, natural, and economic systems. By integrating the latest AI advancements with domain-specific knowledge, we can unlock the full potential of AI in addressing the complex challenges of climate change. This will enable us to develop effective and scalable solutions that have a tangible impact on mitigating climate change.

Conclusion

Artificial intelligence has the potential to be critical in tackling climate change and its consequences for public health. AI can improve climate modeling accuracy, optimize renewable energy systems, detect climate change hotspots, and automate mitigation and adaptation processes. However, AI is fraught with issues such as data bias, technical limitations, ethical concerns, and accessibility. An interdisciplinary approach that encompasses open data research, human-machine interfaces, and multidisciplinary collaboration is required to fully exploit AI's promise in climate change mitigation. We can create a healthier, more sustainable future for humans and the world by solving these difficulties and promoting the use of AI in climate change mitigation.

Funding

There was no funding for this study.

Institutional Review Board Statement

Not applicable.

Conflicts of Interest

The authors declare no competing interests.

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