Assessment of water quality and identification of priority areas for intervention in Guanabara Bay basin, Rio de Janeiro, Brazil, using nonparametric and multivariate statistical methods.

Autor: da Silva DA; Postgraduate Program in Biosystems Engineering (PGEB), Federal Fluminense University, Rio de Janeiro, Niterói 24210-240, Brazil., de Souza Fraga M; Water Management Institute of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil., Lyra GB; Department of Environmental Sciences, Forest Institute, Federal Rural University of Rio de Janeiro, Seropédica, Rio de Janeiro, Brazil., Cecílio RA; Department of Forest and Wood Sciences, Federal University of Espírito Santo, Jerônimo Monteiro, Espírito Santo, Brazil., Pereira CR; Postgraduate Program in Biosystems Engineering (PGEB), Federal Fluminense University, Rio de Janeiro, Niterói 24210-240, Brazil., Cunha-Zeri G; National Institute for Space Research (INPE), São José Dos Campos, SP, Brazil., Zeri M; National Center for Monitoring and Early Warning of Natural Disasters, São José Dos Campos, São Paulo, Brazil., Abreu MC; Department of Environmental Sciences, Forest Institute, Federal Rural University of Rio de Janeiro, Seropédica, Rio de Janeiro, Brazil. marcelc.abreu@gmail.com.
Jazyk: angličtina
Zdroj: Environmental monitoring and assessment [Environ Monit Assess] 2024 Sep 10; Vol. 196 (10), pp. 912. Date of Electronic Publication: 2024 Sep 10.
DOI: 10.1007/s10661-024-13002-5
Abstrakt: The Guanabara Bay hydrographic region (GBHR) has served as a central hub for human settlement and resource utilization throughout Brazil's history. However, the region's high population density and intense industrial activity have come at a cost, leading to a significant decline in water quality. This work aimed to identify homogeneous regions in GBHR according to water quality parameters in dry and rainy periods. The following water quality monitoring variables were monitored at 49 gauge stations: total phosphorus (TP), nitrate (NO 3 - ), dissolved oxygen (DO), hydrogenionic potential (pH), turbidity (Turb), thermotolerant coliforms (TCol), total dissolved solids (TDS), biochemical oxygen demand (BOD), water temperature (Tw), and air temperature (Ta). The statistical analysis consisted of determining principal components, cluster analysis, seasonal differences, and Spearman's correlation. The water quality parameter correlations were not expressively influenced by seasonality, but there are differences in the concentrations of these parameters in the dry and rainy periods. In the dry period, urban pressure on water quality is mainly due to fecal coliforms. The resulting clusters delimited areas under urban, agricultural, and forestry influence. Clusters located in areas with high demographic density showed high concentrations of TCol and TP, while clusters influenced by forestry and agriculture had better water quality. In the rainy season, clusters with urban influence showed problems with TCol and TP, in addition to some characteristics in each group, such as high TDS, NO 3 - , and BOD. Forested areas showed high DO, and clusters under agricultural influence had higher concentrations of TCol, BOD, and NO 3 - concerning forested regions. The troubling state of sanitation in GBHR occurs in metropolitan regions due to lack of a formal sanitation system.
(© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)
Databáze: MEDLINE
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