Solid waste generation indicators, per capita, in Amazonian countries

被引:3
作者
Reyes Flores, Carlos Armando [1 ,2 ]
da Cunha, Alan Cavalcanti [1 ,2 ,3 ]
Albuquerque Cunha, Helenilza Ferreira [1 ,2 ,4 ]
机构
[1] Univ Fed Amapa, Postgrad Program Trop Biodivers PPGBIO, Av Walter Banhos 270, BR-68903516 Amapa, Macapa, Brazil
[2] Univ Fed Amapa, Postgrad Program Environm Sci PPGCA, Av Walter Banhos 270, BR-68903516 Amapa, Macapa, Brazil
[3] Univ Fed Amapa, Civil Engn Dept, Rodovia JK Km 02 S-N, BR-66900000 Amapa, Macapa, Brazil
[4] Univ Fed Amapa, Environm & Dev Dept, Rodovia JK Km 02 S-N, BR-66900000 Amapa, Jardim Marco Ze, Brazil
关键词
Municipal solid waste; Waste management; Final disposal; Socioeconomic indicators; Regional development; Statistical analysis; MANAGEMENT; STATE; EMISSIONS; MODEL;
D O I
10.1007/s11356-022-18509-3
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Countries participating in the Amazon Cooperation Treaty Organization have few options for the environmentally appropriate final disposal of municipal solid waste. Thus, sustainable practices aimed at reducing the negative effects of such a disposal on the environment are complex and hard to accomplish, since solid waste generation per capita proportionally increases as populations grow (approximate to 2.7% > world average), mainly in countries inserted in Amazon Cooperation Treaty Organization. Thus, demographic, socioeconomic, management, and ecological factors represented by 18 independent variables were statistically analyzed to explain waste per capita variation in Amazonian countries and sub-regions. Multiple Kruskal-Wallis tests were applied; 13 of them recorded significant results (p < 0.05). Subsequently, simple and multivariate regression analyses were carried out by taking into consideration waste per capita and significant variables. Simple regression results recorded for variables "IAC" and "Gini index" were significant (R-I(AC)2 = 60.09%, R-Gini(2) = 30.83%), with emphasis on "Amazon biome" (DF = 33, p < 0.01, R-Biome(2) = 5.34%). Multivariate models resulted in wide explainability variation, depending on the number and type of available variable (54.47% <= R-aj(2) <= 70.83%), with emphasis on "IAC," "Ptot," "Purb," "Wton," "Lon," Area, "HDI," "Gini," and "SDG11" (p < 0.01). In conclusion, waste per capita estimation models can present variations and geographical interdependencies due to different variables and factors that reflect the current public policies and municipal solid waste management practices.
引用
收藏
页码:33138 / 33151
页数:14
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