Emissions Reporting Maturity Model: supporting cities to leverage
  emissions-related processes through performance indicators and artificial
  intelligence
Victor de A. Xavier Felipe M. G. França Priscila M. V. Lima
Climate change and global warming have been trending topics worldwide since
the Eco-92 conference. However, little progress has been made in reducing
greenhouse gases (GHGs). The problems and challenges related to emissions are
complex and require a concerted and comprehensive effort to address them.
Emissions reporting is a critical component of GHG reduction policy and is
therefore the focus of this work. The main goal of this work is two-fold: (i)
to propose an emission reporting evaluation model to leverage emissions
reporting overall quality and (ii) to use artificial intelligence (AI) to
support the initiatives that improve emissions reporting. Thus, this work
presents an Emissions Reporting Maturity Model (ERMM) for examining,
clustering, and analysing data from emissions reporting initiatives to help the
cities to deal with climate change and global warming challenges. The
Performance Indicator Development Process (PIDP) proposed in this work provides
ways to leverage the quality of the available data necessary for the execution
of the evaluations identified by the ERMM. Hence, the PIDP supports the
preparation of the data from emissions-related databases, the classification of
the data according to similarities highlighted by different clustering
techniques, and the identification of performance indicator candidates, which
are strengthened by a qualitative analysis of selected data samples. Thus, the
main goal of ERRM is to evaluate and classify the cities regarding the emission
reporting processes, pointing out the drawbacks and challenges faced by other
cities from different contexts, and at the end to help them to leverage the
underlying emissions-related processes and emissions mitigation initiatives.