大気汚染緩和に向けた都市緑化戦略のためのＧＡシミュレーションモデルの研究開発

2015 Fiscal Year Annual Research Report

• Project/Area Number: 15F15372
• Research Institution: Toyohashi University of Technology
• Principal Investigator: 浅野 純一郎 豊橋技術科学大学, 工学(系)研究科(研究院), 教授 (10270258)
• Co-Investigator(Kenkyū-buntansha): NEEMA MEHER 豊橋技術科学大学, 工学(系)研究科(研究院), 外国人特別研究員
• Project Period (FY): 2015-11-09 – 2018-03-31
• Keywords: Urbanization / Air-pollution / Carbon sequestration / Multi-type greeneries / Genetic algorithm (GA) / Optimal-distribution / GIS

Outline of Annual Research Achievements

Application of Genetic algorithm (GA) and Geographical Information System (GIS) in green space optimization belong to air pollution minimization has shown to be a unique approach and is highly appropriate for urban and regional planners,etc. Based on our research findings a correlation between GA-based optimization of green spaces and air pollution reduction has been made as case study in Dhaka city. To make the city a sustainable healthy livable city, it is thus necessary to provide adequate and optimal distribution of green spaces.
Firstly, we have shown the number of multi-type green spaces required and then discussed how multi-type green spaces can be located optimally in a city using simple heuristic approach. Then, we estimated amount of multi-type trees to support such multi-type green spaces. Finally, we calculated the amount of carbon sequestration by the proposed multi-type trees in multi-type green spaces. In this preliminary study, based on data available we considered only carbon dioxide reduction as the most important component of air pollution.
In our study, we have quantitatively demonstrated that indeed an urban setting with more greeneries can significantly reduce carbon dioxide. The results thus obtained show that our proposed different sizes of trees in optimal multi-variant green spaces can sequestrate up to about 1.8 Mega-ton of carbon per annum. Thus, an optimal plantation can significantly reduce carbon dioxide pollution in Dhaka and consequently turning the city to become healthier and more suitable for living.

Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

Currently, we are developing GA-based hybrid simulation model incorporating multiple objectives to simulate air pollution reduction by urban greeneries. The reason behind developing hybrid GA-model is that it can find better solution than simple GA-based model. GA-based hybrid model is combined of two algorithms viz. simple GA and a traditional location allocation algorithms.
We are incorporating predetermined multi-criteria objective function into both of the algorithms. GA-based hybrid simulation model is being coded in C++ programming language. After developing the model, we will give input our real data into the model and execute it. For real world data, we will collect air quality data (air temperature, humidity, air pollutants viz. SOx, NOx, CO, SPM etc.) from 50 locations of Dhaka city. For collecting air quality data, we have to use some air quality instrument that we are planning to buy now.

Strategy for Future Research Activity

Improving air quality using greenery as a viable strategy is very interesting, since it allows a natural means of mitigating air pollutants thereby circumventing any expensive mechanical routes.
For future research, we first plan to develop the GA-based hybrid simulation model. The model will be experimented by testing different parameters of GA i.e. population size, crossover, mutation and no. of generations. The GA-based hybrid simulation model will include four incommensurable objective functions namely: 1) air temperature, 2) air humidity, 3) concentration of air pollutants and 4) green space locations i.e. CO, SOx, NOx. Thus, GA-based hybrid simulation model will be a multi-objective model incorporating these data.
As a case study in Dhaka city, at least 50 survey locations will be selected for collecting air quality data using air quality measurement systems. Among these locations, some will be selected from interior of green areas and some will be from exterior of green areas i.e. near roads, busiest areas. Different types of data will be collected from primary and secondary surveys.
Finally, an extensive qualitative and quantitative correlation between urban greenery and air quality will be established. Basically, the extent of air pollution mitigation is highly dependent on the number of trees and their sizes including their types with optimal sitting. It is therefore utmost importance to establish a combination of quantitative and qualitative correlation between urban greenery and urban air quality.