Call for Papers: Environmental Science and Policy - Special Issue on “AI/Big Data Approaches for Environmental Decision-Making: Theoretical and Empirical Studies with Policy Implications”

We are all entitled to live with dignity in a pollution-free environment. Unfortunately, with the continuous generation of health threatening pollutants, such as fine particulates, NO2, SO2, ozone, etc., humanity is facing unprecedented threats. With big data and AI technologies, it is possible to collect complex, heterogeneous, high resolution environmental data, which may be used to estimate and forecast environmental quality, such as air quality, enabling the generation of personalized alert and advice to improve the health and well-being of individual citizens to facilitate environmental and personal decision-making.

However, the utilization of AI in environmental decision-making is not without challenges. What are the governing conditions for AI to work effectively? What are the approaches, types of datasets, statistical and model assumptions that characterize AI?

Further questions concern the kinds of policy implications that are sought by AI: How to govern the use of AI/big data in environmental decision-making? How to facilitate the use of AI/big data in environmental decision-making? Are current policies effective in governing AI/big data use in environmental decision-making? Do AI/big data serve those most at risk of environmental pollution? Who owns and governs big data? How does the use of AI in environmental decision-making relate to the broader concerns about data privacy and security?

This special issue will bring together top academic and industrial researchers from around the world to tackle this important and timely topic. Both theoretical and applied papers will be included. We are particularly interested in case studies with policy implications/recommendations.

Research topics include the following, and each submission must include a section on policy implications/recommendations:
1. Big data and AI technologies for environmental decision-making
2. Case studies of actual deployment of environmental monitoring and health with policy recommendations
3. Ethical challenges of using Big Data/AI technologies
4. Effects of big data/AI approaches on the quality and structure/practices of future environmental decision-making

Submission Guidelines:

Manuscripts should conform to the standard format as indicated in the Guide for Authors of Environmental Science and Policy:

https://www.elsevier.com/journals/environmental-science-and-policy/14629011/guide-for-authors

All manuscripts to be considered for publication must be submitted by the deadline (Aug 1 2019) at the following website:

http://www.evise.com/evise/jrnl/envsci

It is important that authors select the name of the special issue when they upload their manuscripts: VSI: AI for the Environment

Important Dates:

Aug 1, 2019: Due date for manuscript submission
Feb 1, 2020: Notification of paper acceptance to authors
Mar 1, 2020: Final version of accepted papers due
July 1, 2020: Special issue published

Guest Editors:

1. Prof. Victor OK Li, The University of Hong Kong (vli@eee.hku.hk)
2. Dr. Jacqueline CK Lam, The University of Hong Kong (jcklam@eee.hku.hk)
3. Dr. Theo Damoulas, University of Warwick, UK (T.Damoulas@warwick.ac.uk)