An Urban System Optimization Model Based on CO2 Sequestration Index: A Big Data Analytics Approach

Vasile Dogaru,Marian Cristescu,Claudiu Brandas

doi:10.3390/su11184821

Vasile Dogaru, Marian Cristescu + Show 1 more

Open Access

https://doi.org/10.3390/su11184821

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Abstract

Urban development in recent decades has had a significant impact on climate change. Cities have implemented traffic monitoring systems to sustain the new building code in meeting the target for environmental indicators. Timisoara is the second city in Romania and manages over 60% of the development and pollution of Timis County. The analysis of large volumes of data provided by local sensors and databases requires big data analytics. In this research, for the first time, we simultaneously developed two parallel scenario-based decision-making support models to assess a CO2 sequestration index. The model is based on a tree inventory for traffic area and car flow using Roegenian processes with borders. The first scenario (dt1) analyzes the real O2-pollution car flows for process streets as receivers of pollution. The second scenario (dt2) analyzes O2-pollution flows for the same streets from the perspective of streets that garage the cars. We modeled the parallel integration of actual O2 production and pollution flows for 160 main streets that account for over 50% of the urban mileage of Timisoara city. The carbon sequestration indexes of the streets are in the range of 0.0000043–0.437 (dt1) and 0.0000092–11.78 (dt2). The results can be used to support local decision making regarding the environment CO2-O2 balances by optimizing the local fiscal policies. The research could be extended to secondary streets and separately for the pollution of heating-cooling devices for residential building areas.

Highlights

Cities are becoming vulnerable to climate change [1]
We modeled the metrics for a CO2 sequestration index based on the big data analytics (BDA) approach
Through data mining clustering for the dt1 scenario, we discovered that cluster #1 and cluster #2 contain streets with lower CO2 sequestration index

Summary

Introduction

Cities are becoming vulnerable to climate change [1]. Analytical efforts to model a city with a neutral CO2 indicator, noticed for maintaining pollution relative to a fixed year, are expanding in Europe [2]. Some cities started to perform a green inventory for traffic and residential areas. The integrated inventory for over 35 characteristics of trees was done for all the street areas with a significant leaf area index (LAI) in Timisoara [3]. Main streets are the highest traffic polluter [4]. In other regions of the world, researchers have analyzed and highlighted the street greenery and the capabilities of trees to produce oxygen for carbon sequestration [5,6,7,8,9]

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