Inequality in environmental risk exposure and procedural justice in the Matanza-Riachuelo River Basin

ABSTRACT

Using a capabilities-based perspective on socioenvironmental justice, this paper aims to contribute to the understanding of the interconnection between social equity and care for the earth in the case of the Matanza-Riachuelo – the most industrialized and contaminated river basin in Argentina. First, it uses a spatial regression model to analyse the correlation between multidimensional poverty and potential exposure to three types of environmental risks: environmental hazards of productive establishments, open-air waste dumps, and proximity to contaminated rivers and streams. Second, it analyses inequities in the processes of resettlement of households living in conditions of extreme environmental risk in informal settlements. It shows that higher poverty areas face greater risk of exposure to open-air waste dumps but lower risk of exposure to industrial and commercial environmental hazards. It also demonstrates how enhanced participation of households in decision-making on resettlement contributed to improved outcomes.

KEYWORDS:

• Environmental justice
• spatial analysis
• multidimensional poverty
• water contamination
• Latin America

JEL CLASSIFICATIONS:

• Q53
• Q56
• Q52
• I32

Acknowledgements

We thank Ignacio Duran and Cecilia Miguens for their excellent research assistance.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 $\mathit{EIL}=\mathit{LE}+\mathit{R}+\mathit{EG}+\mathit{Ru}+\mathit{Ri}+\mathit{Di}+\mathit{Lo}$, where $\mathit{LE}$ is a score measuring liquid effluents, $\mathit{R}$ solid waste, $\mathit{GE}$ gaseous effluents, $\mathit{Ru}$ primary products employed in production, $\mathit{Ri}$ diverse risks (explosion, fire, noise, vibration, and chemical substances), $\mathit{Di}$ the establishment’s scale and $\mathit{Lo}$ location-related risks (ACUMAR, 2018b).

2 This approach assumes that environmental risks are distributed homogeneously in space. Although this assumption is not realistic, we cannot use dispersion models, which consider air and water currents and geographic features, due to lack of data on each establishment’s emissions.

3 This survey identified 118 micro, 19 regular and 2 macro waste dumps. Micro dumps have between 15 and 500 m³ of waste, regular dumps between 500 and 15,000 m³ and macro dumps more than 15,000 m³ (UIDET, 2017).

4 While most environmental justice research uses income-based measures of social equity, some recent studies use multidimensional measures (Barnes et al., 2019; Li et al., 2018).

5 This census is the most recent source of spatially disaggregated data for measuring multidimensional poverty. As the MPI is comprised mostly of indicators of structural poverty it evolves slowly and, therefore, 2010 data should provide an adequate measure of the spatial variation in deprivation in the years for which environmental risk exposure data are available (2013–14, 2017 and 2019).

6 Comuna dummies used in the CBA.

7 ACUMAR declares establishments PA when their negative impact on the air, earth, water, or environment in general has been proven or when it has been shown to not comply with regulations on liquid effluents (Art. 24 of ACUMAR, 2019b).

8 We re-estimated $\mathit{H}$ and $M_0$ using three alternative values of $\mathit{k}$ (0.25, 0.375 and 0.5) and four alternative weighting structures (sequentially increasing the weight of one dimension to 0.5 and distributing equally the remaining weights).

9 Based on an interview with an NGO leader on March 31, 2022.

10 Based on interviews with three current or former OPD-CBA lawyers on April 25^th and May 20^th, 2022.

11 Based on interview with a former Housing Institute employee, February 16, 2022.

12 Based on interview with a representative organization delegate, April 21, 2022.

13 Based on interview with a representative organization delegate, April 21, 2022.

14 Based on interview with a representative organization delegate, April 21, 2022.

15 Based on interview with a representative organization delegate, April 21, 2022.

16 Based on an interview with an NGO leader on March 31, 2022.

17 Based on interview with a representative organization delegate, April 21, 2022.

18 Estimates assume an average household size of four.

19 Based on interviews with an NGO leader on March 31, 2022 and with a delegate on April 21, 2022.

Additional information

Funding

The work was supported by the Fundación Universidad Católica Argentina [80020210300030CT].