Several review articles related to inequalities in environmental hazards have been conducted over the years [1–9]. Existing reviews focus on a variety of important topics including: understanding the origins of environmental inequality [6], the policy implications of environmental justice (EJ) research [6], the interaction between the EJ advocacy movement and the research agenda [8], a methodological critique of the research [1] and finally the issue of whether environmental inequalities in the U.S. disproportionately impact racial/ethnic minorities or populations of low socioeconomic status (SES) [7, 9]. The reviews of the existing body of research clearly highlight both the sheer volume of work around environmental inequalities and the complexity of the issues involved.

Although the terms EJ and environmental inequality are often used interchangeably in the literature, they do have distinct meanings. The concept of justice is normative, involving value judgments that can vary over place and time, while equality can be measured empirically and directly compared [10, 11]. Inequalities can be defined across other domains such as process (equal access to the environmental decision making process) and opportunity (equal opportunity to reduce or avoid exposures). These concepts, being difficult to measure, are not often found in empirical research. (See Marshall 2014 [12] and Clark 2014 [13] for papers that move beyond environmental inequality.)

Beyond issues of fairness, environmental inequality research has important health implications. Several reviews focus on the relationship between environmental inequality and health [2–4, 14]. The triple jeopardy hypothesis states that low SES communities face (1) higher exposure to air pollutants and other environmental hazards and (2) increased susceptibility to poor health (primarily as a result of more psychosocial stressors, such as discrimination and chronic stress, fewer opportunities to choose health-promoting behaviors and poorer health status) resulting in (3) health disparities that are driven by environmental factors [15–17].

The purpose of this paper is to review empirical data in the environmental inequality literature from the past ten years and to broaden the scope of previous reviews by including research from around the globe. We define environmental inequality as the distribution of air pollution across different socioeconomic groups, and focus on papers that address this issue, rather than the process or opportunity domains. Our review focuses exclusively on one important environmental hazard, air pollution, and will only review research related to the distribution of air pollutants by SES. We recognize that some researchers will think that the exclusion of research on environmental inequalities by race/ethnicity is a limitation of this work. However, racial/ethnic composition of populations is highly diverse, worldwide, as is patterning of socioeconomic factors by race/ethnicity. Further, some countries do not routinely record race/ethnicity in health data. Additionally, interpretation and conceptualization of research on race/ethnicity can be challenging [18]. Because of these factors, and because we recognize that EJ is emerging as a critical issue in nations around the world, we decided to emphasize socioeconomic factors and not address race/ethnicity to allow for a more inclusive and generalizable global perspective.

Our focus on air pollution is further limited to the criteria air pollutants which are monitored and regulated by the U.S. Environmental Protection Agency (EPA) and governmental agencies in other nations. Air quality standards for concentrations of particulate matter (PM, both particles <2.5 μm in aerodynamic diameter, PM_2.5, and <10 μm in aerodynamic diameter, PM₁₀), carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), sulfur dioxide (SO₂) and lead in outdoor air are set by the World Health Organization and individual governments around the world [19–21]. They are based on a review of the scientific evidence and are established to allow for an adequate margin of human health and safety, in light of the numerous health effects of criteria air pollutant exposure on human health [22–25].

A systematic review was conducted to identify all published studies on SES and ambient air pollution exposure. First, a literature search was performed using Science Direct, Web of Science, Google Scholar, and PubMed for the following keywords: “socioeconomic injustice and air pollution”, “environmental justice and air pollution”, “environmental inequity and air pollution”, “socioeconomic status and air pollution” and “disparity and air pollution and environment”. These keywords yielded a total of 440 published papers after removing duplicates across databases.

We excluded papers from this review if: 1) they were published prior to 2005 2) they were mainly focused on quantifying the association between air pollution and a health outcome, with little attention to inequalities in exposure 3) they did not conduct an empirical analysis (i.e. provided a framework or conceptual model) 4) they evaluated air pollutants other than the criteria air pollutants (e.g. hazardous air pollutants (HAPs), black carbon) 5) they used traffic-related metrics as a proxy for air pollution (e.g. distance to road, traffic density) 6) they combined several air pollutants (criteria and non-criteria) into an index without providing data on the individual ambient air pollutants themselves, and/or 7) they used only race/ethnicity classifications and not other socioeconomic factors to evaluate inequality. All papers were screened and reviewed by two study authors.

Ultimately, 37 studies met the inclusion criteria and were included in this review. Studies were organized by geographic location, with 22 North American studies, 10 European studies and 5 studies from New Zealand, Asia and Africa. Of these, some evaluated both criteria and non-criteria air pollutants and some evaluated both race/ethnicity and SES. Findings related to the non-criteria air pollutants and race/ethnicity are not described in the tables or text of this paper.

Given the differing methods used to assess the association between SES and air pollution we did not attempt to quantify the overall magnitude of effect. Instead, we focused on describing the directionality of results to better understand if an overall trend emerges from the literature. We also discuss methodological issues, such as the analytic techniques employed to assess the association between SES and air pollution and the unit of analysis chosen by researchers. Furthermore, the different approaches used in air pollution exposure assessment and the types of SES metrics used are also discussed.

The North American studies are outlined in Table 1. In general, these studies show a consistent finding: lower SES individuals and communities are exposed to higher concentrations of criteria air pollutants. Comparison of magnitude of effects is difficult given differences across studies, but in those studies that used similar data sources and methods we see relatively small increases in pollutant exposures associated with lower SES. For example, PM_2.5 concentrations were 0.14 μg/m³, 0.2 μg/m³, 0.47 μg/m³ and 0.9 μg/m³ higher in census tracts in North Carolina [26], in the northeast U.S. [27], in six U.S. cities [28] and in selected census tracts around the U.S. [29], respectively, with an approximately 15% greater population of persons with less than a high school education. For context, the EPA PM_2.5 standard is 12 μg/m³ and the WHO guidelines aim for 25 μg/m³.

A few exceptions to this pattern were seen. In New York City (NYC), Toronto and Montreal some SES indicators showed the opposite association: higher SES census tracts had higher concentrations of pollutants [28, 30–32]. In NYC, a borough specific analysis revealed that the Bronx and Staten Island had these patterns [31], which is similar to what was found in the Multi-Ethnic Study of Atherosclerosis cohort among study participants who lived in the southern Bronx and northern Manhattan [28]. These results may reflect the fact that these cities developed in such a way that high SES individuals clustered around busy roadways which often run near rivers and lakes offering more scenic views and better access to urban amenities.

Other North American studies found differences by pollutant. For example, high poverty clusters in Los Angeles had similar NO₂ and PM_2.5 concentrations compared to low poverty clusters, but had higher concentrations of other pollutants [33]. These pollutant-specific results were also seen in a study from Montreal, where higher NO₂ concentrations were associated with low income populations, but no differences across populations were found for PM_2.5, CO and NO_x [34]. Several North American studies also found that higher SES groups are exposed to higher concentrations of O₃ compared to lower SES groups [11, 26, 35, 36]. This is likely because of the scavenging of O₃ by nitric oxide (NO) which can result in lower O₃ levels near roadways (where low income populations are more likely to live) and higher levels further away from them. However, two U.S. studies found O₃ levels to be higher among low SES groups [37, 38].

Although research from other parts of the world is limited, studies from New Zealand (NZ), Asia and Africa also showed negative associations between SES and air pollutants (Table 2). The three studies from NZ found that low income and high deprivation neighborhoods had higher concentrations of PM₁₀ compared to higher SES areas [39–41]. The lone study to address air pollution inequalities in Africa was from Ghana [42]. That study found community SES was inversely associated with both PM_2.5 and PM₁₀. Lastly, a study from Hong Kong explored a municipality with a strong social safety net which had direct bearing on air pollution inequalities [43]. The government of Hong Kong provides public housing for low income residents, while higher income families obtain housing through the private housing market. Among those living in private housing, the lower SES population had higher exposure to PM₁₀ compared to the high SES population. No such inequality was found for residences of public housing. The authors indicate similar results were found for several other air pollutants. The differential location of public housing facilities appear to be reducing residents’ exposure to traffic related air pollution.

Findings in the European literature were quite mixed (Table 3). Several studies found non-linear patterns of inequality [44–46]. In Strasbourg, France, only the high SES quintile had lower NO₂ concentrations, compared to the other 4 quintiles that had similar concentrations [45]. Similarly, a European-wide analysis uncovered non-linear trends where middle income populations had lower PM₁₀ concentrations compared to both higher and lower income groups, depending on if analyses focused on Eastern or Western Europe [46]. In London, some high SES groups had similar NO_x concentrations to low SES groups when using a small area SES metric [44]. Other studies found the choice of SES metric was relevant to findings, where some SES measures were positively associated with air pollution and others negatively [44, 47, 48]. A pilot study of several cities in the Czech Republic found pollutant specific results: smaller cities with larger low SES populations had higher PM₁₀ and SO₂ concentrations, while larger cities with larger high SES populations had higher concentrations of NO₂ [49]. Lastly, a Spanish study of pregnant women found no association between individual level SES and NO₂ [50].

A few European studies from England and Sweden found patterns of inequality similar to those seen in the U.S. [51–53]. Two United Kingdom (UK) based studies found low SES groups were exposed to worse air quality [52, 53] and a study of a city in Sweden found that low income children were exposed to higher levels of NO₂ compared to children from higher income families [51]. Patterns similar to those seen in New York and Toronto were also seen in the Netherlands, where low SES groups were exposed to better air quality compared to high SES groups [52].

Much, but not all, of the environmental inequality literature from North America, NZ, Asia and Africa to date has shown that low SES communities face higher concentrations of criteria air pollutants. The European research, on the other hand, is quite mixed. Some studies found SES was positively associated with air pollution, while others found a negative association and still others found patterns suggesting similar levels regardless of social class. These results suggest the need for further, more rigorous examination of the air pollution - SES association in Europe. Overall there is a paucity of environmental inequality research from nations outside the U.S., but the concepts of environmental justice and inequality are taking hold around the world and we anticipate more research in years to come. In particular, rapidly developing nations like India and China are understudied; assessing if economic development distributes air pollution unequally across these population may have sizeable impacts for population health.

Although several methodological advances in this body of research have occurred, future researchers may want to consider some methodological areas of particular importance. First, understanding the spatial structure of the air pollution data is a critical first step in choosing an analytic approach. Secondly, researchers may want to explore the possibility of confounders of the air pollution - SES association. Methodological improvements in both these areas will provide more accurate point estimates and standard errors.

Environmental inequality research has implications for health effects analyses. First, it is important for health researchers to know if individual and/or area level SES confound the air pollution - health outcome association. SES, like air pollution, can be highly variable from place to place and researchers should carefully consider what it represents in the context of health studies. Environmental inequality studies can provide an in-depth look at one piece of the confounding triangle but only if both individual and area level SES are explored. Few studies to date have tackled this question [28, 44, 51].

More importantly, the question of whether differential exposure to air pollution is driving environmental health disparities is relevant from a regulatory and public health perspective. In the US, evidence supports that many (but not all) low SES communities bear a disproportionate burden of air pollution. For these communities, it is plausible that differential exposure to air pollution may be a contributor to higher associations between air pollution and health than seen in better-off populations. In some European studies, however, higher air pollution concentrations were found among higher SES populations, but the health effects of air pollution were still distributed disproportionately among the poor [71–74]. The observation that communities where high SES groups live have higher concentrations of air pollution does not necessarily mean that the residents are more exposed. High SES individuals have access to more resources that can protect them from increased exposure, such as private transportation versus public, indoor versus outdoor work environments, better constructed housing and potentially, access to climate control, including filtration, for indoor environments [71, 75]. Alternatively, environmental health disparities in Europe could be driven by other environmental hazards, such as noise, second-hand smoke or other work or housing related indicators many of which are also linked to the social environment and disproportionately impact the poor [19]. Additional research into the social distribution of air pollution in Europe will require a rigorous, area-specific approach to shed light on what is likely to be a quite nuanced reality.

Understanding how environmental inequality is created may help explain air pollution and inequality research and has implications for policy. It has been hypothesized that low SES communities with limited political power and influence are unable to stop locally undesirably land uses (LULU), such as factories and roads, from being built in their communities. That is, poor communities lack social capital, a necessary prerequisite for mounting an effective campaign against placing a LULU in one’s community. On the other hand, it has been suggested that industry is motivated solely by economic factors: building a LULU on cheap land is economically prudent. The presence of a LULU will then result in the decline in property values which makes an area more accessible for low SES and minority populations [6, 76]. Both of these theories point to the importance of class- and race-based residential segregation in creating inequality in air pollution concentrations across space. It should be noted that much of the research about causes of environmental inequalities has focused on the U.S. context. Given the importance of historical, economic and social contexts in understanding inequality, other nations may have very different explanations for why environmental inequalities exist.

One strength of the environmental inequality literature as reviewed here is its truly interdisciplinary nature. Researchers from a diverse set of fields bring their own tools and lenses to the question of inequality, making this body of research primed for innovation. In the studies reviewed here, authors were from a wide array of disciplines including: geography, sociology, economics, epidemiology, urban studies, environmental health sciences, environmental studies and civil engineering.

Several open research areas and knowledge gaps exist. First, very few studies have examined changes in inequality over time [37, 48]. Since levels of air pollution have declined over time, particularly in North America, it is of interest to understand if the unequal distribution of air pollution is widening or narrowing. Specifically, as air pollution policies and regulations (both related and unrelated to inequality) are put into place, it is important to understand if these policies impact inequality. Another policy relevant issue is that of which sources or components are most unequally distributed. Although a few studies have begun to examine this question, inequalities may be driven by local sources of pollution, thus necessitating more research. Finally, although this review did not specifically address race/ethnicity, understanding how these factors relate to socioeconomic factors in terms of location-based variability in air pollution concentrations is important for EJ.

Research that pursues these and other questions that directly inform policy changes to enhance environmental quality and health equity is essential in continuing global efforts to improve health and provide safe environments for all.