Who Could Not Avoid Exposure to High Levels of Residence-Based Pollution by Daily Mobility? Evidence of Air Pollution Exposure from the Perspective of the Neighborhood Effect Averaging Problem (NEAP)

Abstract

It has been widely acknowledged that air pollution has a considerable adverse impact on people’s health. Disadvantaged groups such as low-income people are often found to experience greater negative effects of environmental pollution. Thus, improving the accuracy of air pollution exposure assessment might be essential to policy-making. Recently, the neighborhood effect averaging problem (NEAP) has been identified as a specific form of possible bias when assessing individual exposure to air pollution and its health impacts. In this paper, we assessed the real-time air pollution exposure and residential-based exposure of 106 participants in a high-pollution community in Beijing, China. The study found that: (1) there are significant differences between the two assessments; (2) most participants experienced the NEAP and could lower their exposure by their daily mobility; (3) three vulnerable groups with low daily mobility and could not avoid the high pollution in their residential neighborhoods were identified as exceptions to this: low-income people who have low levels of daily mobility and limited travel outside their residential neighborhoods, blue-collar workers who spend long hours at low-end workplaces, and elderly people who face many household constraints. Public policies thus need to focus on the hidden environmental injustice revealed by the NEAP in order to improve the well-being of these environmentally vulnerable groups.

Examining Ethnic Exposure through the Perspective of the Neighborhood Effect Averaging Problem: A Case Study of Xining, China

“…This study also advances our understanding of the NEAP in important ways. For instance, although recent studies found strong evidence that the NEAP exists when assessing individual exposures to air pollution, its extent is associated with people's daily mobility, and certain social groups (e.g., high-income) are associated with higher levels of neighborhood effect averaging because of their higher levels of daily mobility [9,10]; their results are obtained based solely on observing the distribution patterns of the low and high exposures. This study, however, identified specific social and cultural factors (e.g., participation in religious activities and patronage of restaurants affected by the availability of religiously permissible food) that contribute to neighborhood effect averaging in the assessment of ethnic exposures or racial/ethnic segregation.…”

“…Further, using residence-based neighborhoods to estimate individual exposures will lead to biased estimations by exaggerating the disparities in exposures among individuals ( Figure 1). Several recent studies not only provided strong evidence that the NEAP exists when examining mobility-dependent exposure but also showed that different social groups may be associated with different levels of the NEAP [6][7][8][9][10]. For instance, using mobile phone data in Belgium, Dewulf et al [6] found that individuals with low residence-based NO2 exposures witness a considerable increase in NO2 exposure when their travel patterns are considered.…”

“…In recent decades, there has been a rise of scholarly interest in framing socio-spatial segregation in terms of locations where individuals conduct everyday activities, and thus have opportunities to encounter other social groups, based on the assumption that such encounters are conducive to higher levels of inter-group interactions [12][13][14][15]29]. Several recent studies not only provided strong evidence that the NEAP exists when examining mobility-dependent exposure but also showed that different social groups may be associated with different levels of the NEAP [6][7][8][9][10]. For instance, using mobile phone data in Belgium, Dewulf et al [6] found that individuals with low residence-based NO 2 exposures witness a considerable increase in NO 2 exposure when their travel patterns are considered.…”

“…Similar findings are obtained by Yu et al [8] in their study of individual exposure to air pollution in Shenzhen: the residence-based exposure estimates have greater variability than the mobility-based exposure estimates, and individuals with high residence-based exposures tend to have lower mobility-based exposures, while individuals with low residence-based exposures tend to have higher mobility-based exposures. X. Ma et al [9] assessed the real-time air pollution exposure and residence-based exposure of the residents in a high-pollution neighborhood in Beijing. They found that, owing to the NEAP, participants may have lower exposures due to their daily mobility.…”

“…It suggests that if people's daily activities are ignored, mobility-dependent exposures could be overestimated for people with high residence-based exposures and underestimated for people with low residence-based exposures. Since its articulation in 2018, there are only a few empirical studies on the NEAP, and all of these studies focused on individual exposure to air pollution [9][10][11]. More empirical evidence on the NEAP based on examining other types of mobility-dependent exposures is thus sorely needed.…”