Banca de DEFESA: NICOLE GE FREIRE DANTAS AROUCA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : NICOLE GE FREIRE DANTAS AROUCA
DATE: 28/01/2021
TIME: 09:00
LOCAL: videoconferência
TITLE:

Heavy metal distribution on Road-Deposited Sediment (RDS) in a global perspective: a metaanalysis. 

KEY WORDS:

Road deposited sediments. SDR, heavy metals, population, traffic.  

PAGES: 75
BIG AREA: Engenharias
AREA: Engenharia Sanitária
SUBÁREA: Recursos Hídricos
SUMMARY:

Road-deposited sediments (RDS) are composed of a complex set of elements accumulated on the road surface which have the ability to adsorb a wide variety of contaminants from various sources, especially traffic. Their contact with the human being poses serious risks to human health, therefore study RDS contamination is important to create pollution control mechanisms. Thus, the aim of this study is to analyze the correlation between the contamination of RDS by toxic heavy metals (Cd, Pb, Hg, Cr, As, Cu, Zn) and socioeconomic factors (population, population density, land use, HDI, energetic matrix and number of vehicles). To accomplish that, a collection of data published in high impact journals worldwide was used, as well as additional information of each city was gathered. The meta-analysis was performed using principal component analysis (PCA) and Multivariate Regression. PCA results shows a tendency of increasing contamination levels in cities with a higher number of inhabitants and for commercial and industrial uses. In this way, cities with high level of urbanization (London, New York and Madrid) showed high levels of contamination. Although, outliers were found. Some cities showed anomalous contamination data (Shenzhen, Halifax, Huludao and Singapore), possibly associated with local characteristics. Correlations obtained on multiple linear regression (R²=0,30 when applied to each individual factor and R²=0,41 when done with all factors simultaneously) indicated that only one factor is not enough to establish a strong relation with contamination, the factor must be analysed concomitantly, further adding new factors. The second order regression, in turn, generated better correlations (R²=0,70). Therefore, results indicate there is a relationship between the RDS contamination levels and the aforementioned factors. Besides, results suggest that de addition of factor may elevate the correlation levels in a way it could be used on a model development that allow predict pollution conditions based on local characteristics. The data presented show RDS as a potential pollution indicator, indicating sources and critical places, the analysis of its contamination can be used by government agencies on elaboration of cleaning public policies and pollution management.  

BANKING MEMBERS:
Presidente - 1242829 - LUCIO FLAVIO FERREIRA MOREIRA
Interna - 1759777 - ADELENA GONCALVES MAIA
Externo ao Programa - 1913849 - EDGAR PERIN MORAES
Externo à Instituição - José Anderson do Nascimento Batista - UNICAMP