Characterization of a High PM2.5 Exposure Group in Seoul Using the Korea Simulation Exposure Model for PM2.5 (KoSEM-PM) Based on Time⁻Activity Patterns and Microenvironmental Measurements

Surrogate-Assisted Fine Particulate Matter Exposure Assessment in an Underground Subway Station

With the increase in subway travelers, the air quality of underground enclosed spaces at subway stations has attracted much more attention. The study of pollutants exposure assessment, especially fine particulate matter, is important in both pollutant control and metro station design. In this paper, combining pedestrian flow analysis (PFA) and computational fluid dynamics (CFD) simulations, a novel surrogate-assisted particulate matter exposure assessment method is proposed, in which PFA is used to analyze the spatial-temporal movement characteristics of pedestrians to simultaneously consider the location and value of the pedestrian particulate generation source and their exposure streamline to particulate matter; the CFD model is used to analyze the airflow field and particulate matter concentration field in detail. To comprehensively consider the differences in the spatial concentration distribution of particulate matter caused by the time-varying characteristics of the airflow organization state in subway stations, surrogate models reflecting the nonlinear relationship between simulated and measured data are trained to perform accurate pedestrian exposure calculations. The actual measurement data proves the validity of the simulation and calculation methods, and the difference between the calculated and experimental values of the exposure is only about 5%.

A model for population exposure to PM2.5: Identification of determinants for high population exposure in Seoul

Outdoor concentrations of particulate matter with an aerodynamic diameter of <2.5 μm (PM_2.5) are often used as a surrogate for population exposure to PM_2.5 in epidemiological studies. However, people spend most of their daily activities indoors; therefore, the relationship between indoor and outdoor PM_2.5 concentrations should be considered in the estimation of population exposure to PM_2.5. In this study, a population exposure model was developed to predict seasonal population exposure to PM_2.5 in Seoul, Korea. The input data for the population exposure model comprised 3984 time-location patterns, outdoor PM_2.5 concentrations, and the microenvironment-to-outdoor PM_2.5 concentrations in seven microenvironments. A probabilistic approach was used to develop the Korea simulation exposure model. The determinants for the population exposure group were identified using a multinomial logistic regression analysis. Population exposure to PM_2.5 varied significantly among the three seasons (p < 0.01). The mean ± standard deviation of population exposures to PM_2.5 was 21.3 ± 4.0 μg/m³ in summer, 9.8 ± 2.7 μg/m³ in autumn, and 29.9 ± 10.6 μg/m³ in winter. Exposure to PM_2.5 higher than 35 μg/m³ mainly occurred in winter. Gender, age, working hours, and health condition were identified as significant determinants in the exposure groups. An "unhealthy" health condition was the most significant determinant. The high PM_2.5 exposure group was characterized as a higher proportion of males of a lower age with longer working hours. The population exposure model for PM_2.5 could be used to implement effective interventions and evaluate the effectiveness of control policies to reduce exposure.

Do Individuals' Activity Structures Influence Their PM2.5 Exposure Levels? Evidence from Human Trajectory Data in Wuhan City

Severe air pollution has become a major risk to human health from a global environmental perspective. It has been recognized that human mobility is an essential component in individual exposure assessment. Activity structure reflects the characteristics of human mobility. Thus, a better understanding of the relationship between human activity structure and individual exposure level is of crucial relevance. This study examines this relationship using a large cell-phone GPS dataset in Wuhan, China. The results indicate that there is a strong linear relationship between people’s activity structures and exposures to PM_2.5. Inter-group comparisons based on the four activity structure groups obtained with K-means clustering found that groups with different activity structures do experience different levels of PM_2.5 exposure. Furthermore, differences in detailed characteristics of activity structure were also found at different exposure levels at the intra-group level. These results show that people’s activity structures do influence their exposure levels. The paper provides a new perspective for understanding individual exposure through human activity structure, which helps move the perspective of research on individual exposure from the semantic of physical location to the semantic of human activity pattern.

Recent advances in process engineering and upcoming applications of metal-organic frameworks

Progress in metal-organic frameworks (MOFs) has advanced from fundamental chemistry to engineering processes and applications, resulting in new industrial opportunities. The unique features of MOFs, such as their permanent porosity, high surface area, and structural flexibility, continue to draw industrial interest outside the traditional MOF field, both to solve existing challenges and to create new businesses. In this context, diverse research has been directed toward commercializing MOFs, but such studies have been performed according to a variety of individual goals. Therefore, there have been limited opportunities to share the challenges, goals, and findings with most of the MOF field. In this review, we examine the issues and demands for MOF commercialization and investigate recent advances in MOF process engineering and applications. Specifically, we discuss the criteria for MOF commercialization from the views of stability, producibility, regulations, and production cost. This review covers progress in the mass production and formation of MOFs along with future applications that are not currently well known but have high potential for new areas of MOF commercialization.

Exposure to air pollutants and heat stress among resource-poor women entrepreneurs in small-scale cassava processing

Exposure to air pollutants and heat stress from traditional cooking fires is the leading cause of mortality and morbidity in low- and middle-income countries globally and have an adverse effect on the environment. According to the World Health Organization, 3.8 million people die annually prematurely from illness related to household air pollution. Families living in poverty are at the highest risk, especially women and children. In this study, exposure to particulate matter (PM_2.5 and PM₁₀), carbon monoxide (CO) and nitrogen dioxide (NO₂) was measured among resource-poor women cassava processors. The test locations were chosen in the peri-urban settlements of Abeokuta in the Ogun State of Nigeria, where household women entrepreneurs roast garri (granulated cassava) for sale in the local market. The measurements were taken for two types of stoves which are generally existing in the study location. First, a rectangular stove (RS) with two operators and, second, a circular stove (CS) with one operator; both stoves used wood as fuel. The emissions were compared with a modern mechanical liquefied petroleum gas burner-based garri roaster (GS). Hours spent per day in front of garri stoves ranged from 6 to 12 h for both stoves, with a frequency of 1 to 3 days of operation per week. It was found that CS operators were spending significantly more time in producing garri, which is due to the low capacity of the CS. The average PM_2.5 concentrations for RS and CS were 381 and 273 μg/m³, respectively, estimated to be 21 and 41 μg/m³ on an annual mean level basis. Similarly, for PM₁₀, the mean concentration levels were 1580 and 594 μg/m³ for RS and CS, respectively. The annual mean levels for PM₁₀ were about 89 μg/m³ for both types of stoves. CO exposure during garri processing was up to five times higher than the recommended concentrations with a 4-h mean of 48 and 50 mg/m³ for RS and CS, respectively. NO₂ levels were very low, ~ 0 ppm. This investigative research concluded that wood-fired small-scale garri producers in Nigeria are exposed to very unhealthy levels of PM, CO and thermal stress. The concentration levels of both PM and CO were exceeding the global as well as Nigerian ambient air quality standard regulations. Along with air pollution, thermal stress was a significant issue, which is known to exacerbate the negative effect of air pollution on the human body.

Racialized Structural Vulnerability: Neighborhood Racial Composition, Concentrated Disadvantage, and Fine Particulate Matter in California

This study contributes to previous research by advancing a “racialized structural vulnerability” framework and presenting a new empirical analysis of the relationship between neighborhood Asian, Black, and Latinx composition; extrinsic and intrinsic vulnerability; and PM_2.5 exposures in California with secondary data from 2004–2014. Principal component analyses revealed that tract Latinx composition was highly correlated with extrinsic vulnerability (economic disadvantage and limited English-speaking ability), and that tract Black composition was highly correlated with intrinsic vulnerability (elevated prevalence of asthma-related emergency department visits and low birth weight). Spatial lag regression models tested hypotheses regarding the association between Asian, Black, and Latinx population vulnerability factors and the 2009–2011 annual average PM_2.5 percentile rankings, net of emissions and spatial covariates. Results indicated that the percent Latinx population, followed by the regional clustering of PM_2.5, and the percent of non-Latinx Black and non-Latinx Asian population were the strongest positive multivariable correlates of PM_2.5 percentile rankings, net of other factors. Additional analyses suggested that despite shifting demographic and spatial correlates of 2012–2014 PM_2.5 exposures, the tracts’ Black and Latinx composition and location in the San Joaquin Valley remain important vulnerability factors with implications for future research and policy.

Benefit–Cost Analysis of Green Roof Initiative Projects: The Case of Jung-gu, Seoul

Green roofs, which have various economic, environmental and social effects, have been acknowledged as an alternative green space in urban areas. This study aims to investigate the economic feasibility of green roof projects by conducting a benefit–cost analysis on the case of Jung-gu, Seoul. The analysis estimates and compares five different scenarios applied in the study area with a 20-year operation period in all cases. This set of scenarios aims to compare the most idealistic situation with more achievable and realistic situations, to provide policy implications for green roof initiative projects in Seoul. The analysis consists of estimating six cost items and eight benefit items. Among the benefit items, two non-marketable elements are estimated by the contingent valuation method. The scenario with 100% application of a green roof, has benefits exceeding the costs with a benefit–cost ratio of 1.174. However, the other scenarios with certain prerequisites have a benefit–cost ratio that is very close, but still smaller than 1. Therefore, it is possible to claim that green roof initiative projects are economically viable under specific conditions. However, there are many restrictions to engaging in green roof constructions for entire building rooftops.