Environmental Justice in Industrially Contaminated Sites. A Review of Scientific Evidence in the WHO European Region
Abstract
:1. Introduction
2. Materials and Methods
- Publication in English;
- Original study (i.e., exclusion of review, editorial, commentaries, studies only with a critical assessment without original data);
- Study analyzing any kind of socio-demographic or socioeconomic characteristic measured at individual or contextual (area) level (e.g., regional deprivation indices) to assess social inequalities [29];
- Study analyzing the association between ‘the presence of contamination’/’the assessment of exposure’ and/or health risk/impact due to industrially contaminated sites and socio-demographic/socioeconomic characteristics of individuals or populations residing in areas (i.e., any geographic area, including those with administrative meaning, e.g., regions, provinces, municipalities, districts) meaning the presence/extent of environmental inequalities;
- A study considering socioeconomic/socio-demographic data not only as confounders in multivariate analysis and indicating quantitative or qualitative results on environmental/health inequalities in the abstract.
3. Results
3.1. Results on Distributive Justice
- The studies on industrial soil and air pollution carried out in Glasgow (Scotland) showed a strong positive correlation between growing level of social deprivation and poor land and air quality [31].
- Of the two studies carried out in Germany, one is focused on the local level [33], while the other provides a national assessment [32]. The first showed that, in the town of Hamburg, toxic release facilities are disproportionately concentrated in, and nearby, neighborhoods with relatively high proportions of foreigners and welfare recipients. The second highlighted a high correlation between percentage of foreigners and exposure to industrial pollution (twice higher in urban areas than rural areas).
- The Czech study [35] on coalfield areas showed a positive correlation between presence of coal power plants and coal mining and unemployment rate and concentration of ethnic minorities, and a negative correlation with average incomes and pensions and level of education, though the analysis was carried out only at the district level (NUTS 4).
- The Scottish study on landfills showed that exposure to municipal landfills is concentrated amongst the most deprived areas, and that environmental inequalities around municipal landfill sites have arisen due to a combination of pre-siting and post-siting processes [31].
- The three French studies regarding incinerators [36,37,38] showed that towns receiving incinerators had higher unemployment and immigrant rates [36] and that a higher proportion of foreigners and persons born abroad in a town is associated with higher odds that the town receives an incinerator. A social gradient was observed with respect to emissions for each of the socioeconomic variables considered: As the proportion of disadvantaged residents increases in a municipality, incinerator emissions also increases [37]. Conversely, in the census period after the opening of the incinerators, no statistically significant effect on employment growth or net migration was observed in populations residing in areas with landfills [38]. The French study on industrial pollution showed that noxious facilities were disproportionately located in higher foreign-born communities. High deprivation also appeared as a predictive factor, although less strongly and less consistently [39].
3.2. Results on Procedural Justice
- Socio-relationships aspects of procedural injustice: communities recognized themselves as poorly informed about the potential impacts and harbored a general distrust of the information provided by the mining companies, corroborated by their inability/impossibility to affect decisions concerning their living environment [43].
- Roots of environmental injustice related to the decision-making process leading to the choice to locate environmentally burdensome facilities in a disadvantaged area. The long-term siting policies were affected by the poor engagement of inhabitants of that disadvantage district in the decision-making process. In the long period, this modality later led to self-reinforcing siting policies. In other words, environmental injustice was sustained through path-dependent development patterns. The concept of path-dependency was used to explain how environmental injustice was reproduced because of past paths of siting policies locked in subsequent decisions and created a negative twist of accumulating environmental burden [42,43].
- Analysis of the residents risk perception of the population living in the contaminated areas to explain how cognitive bias within socio-cultural and economic constrains characterized their choice to live in the contaminated area [40].
4. Discussion
4.1. Strengths and Limitations
4.2. Critical Analysis of Results
4.3. Studies Outside the WHO European Region
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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#1—Socioeconomic and sociodemographic determinants | (sociological factors[MeSH Terms] OR disadvantaged[All Fields] OR disadvantage[All Fields] OR deprived[All Fields] OR social[All Fields] OR socio * [All Fields] OR vulnerable populations[MeSH Terms] OR vulnerable[All Fields] OR vulnerability[ALL Fields] OR psychosocial[All Fields] OR psycho-social[All Fields] OR socioeconomic factors[MeSH Terms] OR socio-economic[ALL Fields] OR deprivation[All Fields] OR socio-demographic[All Fields]) |
#2—Industrially contaminated sites | (industrial pollution prevention and control sites[Title/Abstract] OR IPPC[Title/Abstract] OR european pollutant emission register[Title/Abstract] OR contaminated land[Title/Abstract] OR contaminated site * [Title/Abstract] OR industrial site * [Title/Abstract] OR industrial pollution[Title/Abstract] OR industrial water pollution[Title/Abstract] OR industrial air pollution[Title/Abstract] OR industrial soil pollution[Title/Abstract] OR superfund[Title/Abstract] OR industrial facilities [Title/Abstract] OR ((industry * [Title/Abstract] OR site[Title/Abstract] OR plant * [Title/Abstract]) AND (steel [Title/Abstract] OR iron [Title/Abstract] OR metallurgic * [Title/Abstract] OR chemical [Title/Abstract] OR petroleum * [Title/Abstract] OR petrochemical * [Title/Abstract] OR oil refinery[Title/Abstract] OR steel[Title/Abstract] OR gas[Title/Abstract] OR power plant[Title/Abstract] OR mining[Title/Abstract] OR quarr * [Title/Abstract] OR waste[Title/Abstract] OR incinerator * [Title/Abstract] OR landfill * [Title/Abstract])) |
#3—Inequalities and inequities | (inequality[Title/Abstract] OR inequity[Title/Abstract] OR inequities[Title/Abstract] OR inequalities[Title/Abstract] OR unequal[Title/Abstract] OR environmental justice[Title/Abstract] OR environmental injustice[Title/Abstract]) |
#4—Period | (“2010/01/01”[Date—Publication]: “2017/12/31”[Date—Publication]) |
Final search | #1 AND #2 AND #3 AND #4 |
Ref. | Type of Contamination | Country | National/Local | Study Design and Analysis | Unit of Analysis | Exposure Assessment | Socioeconomic Characteristics/Social Dimensions |
---|---|---|---|---|---|---|---|
[30] | Soil metal content, air pollution | Scotland. | Local (Glasgow) | Small-area study Bivariate analysis: Person’s correlation coefficient | Aggregated level: areas including 4000 households (Intermediate Geography Zone) | Level of heavy metals in soil and concentration of NO2 and PM10 in air. Index of pollution at area level | Index of multiple deprivation composed by six domains: education, employment, housing, income, access to services, crime |
Results on environmental inequalities: Strong positive correlation between growing level of deprivation and poor land and air quality. | |||||||
Results on health inequalities: Positive correlation between Standardized Incidence Ratio (SIR) for respiratory diseases and soil and air pollution and growing level of deprivation. Significant negative association between least deprived categories and SIR for respiratory diseases. | |||||||
[34] | coalfield areas | England | National | Cross-sectional Data on health outcomes and confounders at individual level, data on socioeconomic variables both at individual and area level (contextual) Multivariate analysis: multilevel logistic models | Individual level: annual representative cross-sectional survey of the English population | Living in a former coalfield area | Individual level: marital status, economic activity, occupation and social class Contextual level: Index of Multiple deprivation and index of social cohesion |
Results on environmental inequalities: All analysis includes the assessment on health (see column ‘results on health inequalities’). | |||||||
Results on health inequalities: Higher odds of reporting less than good health among economically inactive individuals living in coalfield areas in comparison to the same group living in non-coalfield areas. Significant social health inequalities between people living in former coalfield communities are similar to those observed in non-coalfield areas. | |||||||
[35] | coalfield areas | Czech Republic | National | Ecological study Bivariate analysis: Person’s correlation coefficient | Aggregated level: districts (NUTS4) | Presence of coal power plants | Socioeconomic variables associated with the domains of life quality, labor market, social capital, and social cohesion |
Results on environmental inequalities: Positive correlation between the presence of coal power plants and coal mining and unemployment rate and concentration of ethnic minorities. Negative correlation with average incomes and pensions and level of education. | |||||||
Results on health inequalities: Association between the presence of coal power plants and coal mining and higher rates of abortion, higher infant mortality, and lower male life expectancy. | |||||||
[33] | Industrial pollution | Germany | Local (Hanburg) | Small-area study Bivariate: Person’s correlation coefficient Multivariate analysis: Ordinary Least Squared model | Aggregated level: neighborhood | Location of industrial facilities | Proportion of foreigners and population receiving public assistance |
Results on environmental inequalities: Toxic release facilities are disproportionately concentrated in, and nearby, neighborhoods with relatively high proportions of foreigners and population receiving public assistance. | |||||||
[32] | Industrial pollution | Germany | National | Small-area study Multivariate analysis: Ordinary Least Squared model and Spatial Model (SLX) | Aggregated level: areas containing an average of 778 inhabitants | Location of industrial facilities and categorization of their emissions | Proportion of foreigners and vacant houses; living spaces |
Results on environmental inequalities: High correlation between percentage of foreigners and exposure to industrial pollution. Population density of the surrounding area is a significant predictor of pollution only in urban areas. The percentage of vacant houses correlates with pollution only in rural areas | |||||||
[39] | Industrial pollution | France | Local (Franche-Comte’ region) | Small-area study Multivariate analysis: Bayesian hierarchical logistic regression | Aggregated level: areas with a mean population of 569 (IRISes) | Location of industrial facilities (areas whose borders intersected circles with a radius of 2 km from industrial facilities) | Index of multiple deprivation composed by four domains: unemployment, house ownership, car ownership, overcrowding Persons born abroad |
Results on environmental inequalities: Noxious facilities are disproportionately located in higher foreign-born communities after controlling for deprivation, population density and rural/urban status. High deprivation also appears as apredictive factor, although less strongly and less consistently. | |||||||
[36] | Incinerators | France | National | Ecological study Descriptive analysis Multivariate analysis: Spatial logistic regression | Aggregated level: communes | Presence or absence of an incinerator in the communes | Unemployment rate, proportion of foreigners and person born abroad |
Results on environmental inequalities: Towns receiving incinerators had higher unemployment and immigrant rates. | |||||||
[37] | Incinerators | France | National | Ecological study Multivariate analysis: Multilevel linear models with random effects | Aggregated level: communes | Total annual emissions from incinerators in communes with more than one incinerator | Proportion of unemployed people, immigrants, and persons born abroad |
Results on environmental inequalities: A social gradient was observed with respect to emissions for each of the three considered socioeconomic variables. | |||||||
[38] | Incinerators | France | National | Ecological study Differences in differences | Aggregated level: communes | Presence or absence of an incinerator | Unemployment rate proportion of foreigners and person born abroad |
Results on environmental inequalities: Incinerators had no statistically significant effect on employment growth or net migration of the established population in the census period after they opened. | |||||||
[31] | landfills | Scotland | National | Small-area study Multivariate analysis: Ordinary least squares regression and Logistic regression | Aggregated level: areas with approximately 500 persons (Continuous Areas Through Time) | Air pollution from landfills in each area modeling exposure using a landfill exposure index incorporating site specific emissions and local wind conditions | Index of multiple deprivation composed by: lack of car ownership, low occupational social class, overcrowded household, and male unemployment |
Results on environmental inequalities: Exposure to municipal landfill in Scotland is concentrated amongst the most deprived areas. Environmental inequalities around municipal landfill sites in Scotland have arisen due to a combination of presiting and postsiting processes. |
Ref. | Type of Contamination | Country | National/Local | Study Design and Methods | Unit of Analysis | Socioeconomic Characteristics/Social Dimensions |
---|---|---|---|---|---|---|
[40] | Heavy industry: Chemical (Seveso plants) | France | Local (Mardyck village within the urban area of Dunkirk) | Socio-environmental study Interviews | Individual level: Adults (People aged at least 16); N. 158 as fraction of the total population N. 270 | Occupation (Socio-professional class and Unemployment), Education, house ownership |
Results on environmental inequalities: Economic and social contains, cognitive and cultural bias. Quite low educational level and intermediate professional levels. Higher unemployment than in France average. Perception of residents: the majority emphasized the availability of quiet and pleasant public space, while a minority declared lack of choice relating to living in the village due to economic constraints (unable to move from the village). | ||||||
[41] | Mining | Sweden | Local (Gállok, area in Jokkmok municipality) | Socio-environmental study Interviews, unstructured non-participant observations and documents | Individual level different stakeholders; N. 13 | Ethnicity (Sami indigenous population) |
Results on environmental inequalities: Asymmetric power relations among stakeholders. Historical mis-recognition of the indigenous population (Sami) as relevant stakeholder, resulting in lack of influence in decisions concerning land-use. | ||||||
[42] | Industrial facilities (power plants, waste disposal) | Finland | Local (Helsinki, Sörnäinen district) | Historical analysis Information from archival sources and documents | - | Socioeconomic class |
Results on environmental inequalities: Social and environmental living conditions were poor. Disadvantaged area. Environmental inequities were due to land-use. Siting decisions and related decision-making processes resulted in a trend of accumulating environmental burden (self-reinforcing siting policies). | ||||||
[43] | Mining | Northern Europe | Local (8 communities living in areas around contamination source in Norway, Sweden, Finland and Murmansk region in Norwest Russia) | Socio-environmental study Interviews and focus groups | Individual level. Different stakeholders; N. 85 | Socioeconomic status associated with cultural values (i.e., way of life) |
Results on environmental inequalities: Inhabitants of the communities have no power to influence the development of the areas where they live in respect to State-led or international companies (glocal phenomena). Lack of information and participation in decisions. Loss of their own cultural way of life. |
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Pasetto, R.; Mattioli, B.; Marsili, D. Environmental Justice in Industrially Contaminated Sites. A Review of Scientific Evidence in the WHO European Region. Int. J. Environ. Res. Public Health 2019, 16, 998. https://doi.org/10.3390/ijerph16060998
Pasetto R, Mattioli B, Marsili D. Environmental Justice in Industrially Contaminated Sites. A Review of Scientific Evidence in the WHO European Region. International Journal of Environmental Research and Public Health. 2019; 16(6):998. https://doi.org/10.3390/ijerph16060998
Chicago/Turabian StylePasetto, Roberto, Benedetta Mattioli, and Daniela Marsili. 2019. "Environmental Justice in Industrially Contaminated Sites. A Review of Scientific Evidence in the WHO European Region" International Journal of Environmental Research and Public Health 16, no. 6: 998. https://doi.org/10.3390/ijerph16060998
APA StylePasetto, R., Mattioli, B., & Marsili, D. (2019). Environmental Justice in Industrially Contaminated Sites. A Review of Scientific Evidence in the WHO European Region. International Journal of Environmental Research and Public Health, 16(6), 998. https://doi.org/10.3390/ijerph16060998