From lockdown to precise prevention: Adjusting epidemic-related spatial regulations from the perspectives of the 15-minute city and spatiotemporal planning.

The COVID-19 pandemic challenged emergency management in cities worldwide. Many municipalities adopted restrictive, one-size-fits-all spatial regulations such as lockdowns without fully considering the inhabitants' daily activities and local economies. The existing epidemic regulations' unintended detrimental effects on socioeconomic sustainability necessitate a transition from the "lockdown" approach to more precise disease prevention. A spatially and temporally precise approach that balances epidemic prevention with the demands of daily activities and local economies is needed. Thus, the aim of this study was to propose a framework and key procedures for determining precise prevention regulations from the perspectives of the 15-minute city concept and spatiotemporal planning. Alternative regulations of lockdowns were determined by delineating 15-minute neighborhoods, identifying and reconfiguring facility supplies and activity demands in both normal and epidemic conditions, and performing cost-benefit analyses. Highly adaptable, spatially- and temporally-precise regulations can match the needs of different types of facilities. We demonstrated the process for determining precise prevention regulations in the case of the Jiulong 15-minute neighborhood in Beijing. Precise prevention regulations-which meet essential activity demands and are adaptable for different facility types, times, and neighborhoods-have implications for long-term urban planning and emergency management.

Examining the association between the built environment and active travel using GPS data: A study of a large residential area (Daju) in Shanghai.

Automobile dependence and physical inactivity have become common health challenges for residents in large suburban residential areas. Limited literature has examined the associations between the built environment and active travel in such residential areas and the differences in these associations among residents from different neighborhoods. To avoid inaccurate results potentially derived from residence-based measures, we adopt a mobility-based approach for environmental exposure assessment. Using GPS data from 530 trips made by 98 participants in a large residential area in Shanghai, we investigate the relationships between neighborhood types, pollution perceptions, built environment features and active travel. The results indicate that residents in affordable and relocation housing make fewer active trips than those in market-rate housing, while the built environment seems to mitigate this difference. Sports facilities promote active travel while commercial facilities and road intersections discourage it. We identify significant interactions between the percentage of green space and neighborhood type, as well as floor area ratio and air pollution perception. Interventions promoting active travel include active-travel-friendly design for commercial facilities and road intersections, the provision of more sports facilities, a careful increase in floor area ratio, and the provision of more green space that is attractive to residents from different neighborhoods.

Comparing Mobility-Based PM2.5 Concentrations and Activity Satisfaction in Beijing between 2012 and 2017.

Although the negative effect of air pollution on life satisfaction has been examined in many studies, comparative analyses of mobility-based exposures to air pollution and momentary wellbeing have been rare to date, despite the fact that they are essential to improve wellbeing. Drawing on individuals' space-time trajectories of two surveys conducted in 2012 and 2017 in Beijing, we investigate the temporal variations in activity satisfaction and mobility-based air pollution from monitoring stations and real-time air pollutant sensors, respectively. Furthermore, we explore how mobility-based air pollution dynamically influences activity satisfaction. The results show that air quality in Beijing improved from 2012 to 2017, and activity satisfaction increased as well. The negative relationship between them is more significant on workdays but insignificant on weekends. Moreover, real-time air pollution data show higher accuracy than monitor-based data, which suggests that future studies should pay more attention to real-time air pollution assessments.

Personalizing the dichotomy of fixed and flexible activities in everyday life: deriving prism anchors from GPS-enabled survey data.

Space-time prism is a fundamental concept in time geography that can model an individual's accessibility to resources under space-time constraints. A prism anchor is often defined by work, school, or home activity with a fixed location and schedule. Trips and other activities are relatively flexible and scheduled between prism anchors. This fixity-flexibility dichotomy may not capture the increasing complexity of human mobility behaviors or variations among individuals. Recent developments in location-aware technologies allow us to collect person-level mobility data with detailed space-time paths and contextual information. This article develops methods to extract prism anchors from these GPS-based survey data and examines whether home, work, and school activities can always be used to define prism anchors for everyone. To illustrate our methods, we use data collected in Minnesota and Beijing as two study cases. Results in both study cases suggest that not everyone has home, work, or school anchors, and people with the same socio-demographic background tend to have similar anchor types. By deriving home, work, and school anchors, we can better understand how a person's everyday schedules are governed by home, work, and school and refine person-based accessibility measures.

Nondestructive measurement of the grain size of laser cladding coatings using a laser ultrasonic method.

Due to the processing characteristics of laser cladding, the beads and joints of the laser cladding coatings have different grain sizes. We used the laser ultrasonic (LU) method to measure the distribution of the grain sizes of laser cladding coatings nondestructively. The surface acoustic wave amplitude was influenced by the grain size; hence, the amplitude varied for beads and joints because of their different attenuations. The spatial resolution of LU is higher than that of the traditional ultrasonic testing method, leading to a fringe distribution of the C-scan results in the scanning area. The LU results were verified through metallographic experiments. It was concluded that the LU method can be used to determine the grain sizes of coatings.

Mobility-based environmental justice: Understanding housing disparity in real-time exposure to air pollution and momentary psychological stress in Beijing, China.

Environmental justice is a crucial environmental and social problem. Previous research in the cities of developed countries has found that ethnic minorities and low-income people were disproportionately exposed to the residential environment with more serious environmental risks. This study proposed a transition from the residence-based perspective to a mobility-based and context-aware approach to reinterpret environmental justice with a focus on the air pollution issue in urban China. A novel research protocol combining geographic ecological momentary assessment and portable air pollutant sensors was developed to collect and analyze real-time data of air pollution exposure and psychological stress for residents living in the same residential neighborhood of Beijing, China. The results show that residents of different types of housing were exposed to varying PM2.5 concentrations although they experienced similar levels of air pollution in their residential neighborhoods. Residents of public low-rent housing were the disadvantaged group because of their limited mobility, exposure to serious air pollution at home, and insensitive stress responses to air pollution. These findings not only uncover the mobility-based environmental justice issue in the context of government-led and egalitarianism-pursuing urban China, but also provide references for the residential mix policy on how to narrow the disparity in environmental pollution exposure from the perspective of human mobility.

Associations of co-exposures to air pollution and noise with psychological stress in space and time: A case study in Beijing, China.

Air pollution and noise are both ubiquitous environmental stressors that pose great threats to public health. Emerging evidence has noticed the combined health risks caused by the coexistence of traffic-related air pollutants and noise in the residential context. However, less is known about how mobile individuals are simultaneously exposed to multiple sources of air pollution and noise, and thus respond with more acute psychological responses beyond the residence. This study examines the co-exposures to fine particles (PM2.5) and noise across spatiotemporal contexts where the concurrent exposures are jointly associated with momentary psychological stress. An innovative research protocol, including GPS-equipped activity-travel diaries, air pollutant and noise sensors, and ecological momentary assessment, was adopted to collect real-time data from a sample of residents in Beijing, China. The results showed a minor correlation between PM2.5 and noise exposures after accounting for individual mobility and the spatiotemporal dynamics of these two environmental pollutants. Further, exposure to PM2.5 was more associated with momentary psychological stress given the insignificant independent effect and the weak moderating effect of noise exposure. Three specific spatiotemporal contexts involving the health risks of co-exposures were delineated, including morning rush hours and traveling by public transits with intensified stress risks caused by combined exposures to air pollution and noise, workplaces with counteracting stress effect of both exposures, and evening time at home with stress-induced air pollution and stress-relieving social noise. In conclusion, the mobility-based and context-aware analysis provides a more nuanced understanding of the associations of co-exposures to environmental pollution and synchronous psychological stress in space and time.

Understanding the relationships among individual-based momentary measured noise, perceived noise, and psychological stress: A geographic ecological momentary assessment (GEMA) approach.

This study aims to understand how the relationship between individual-based noise exposure and psychological stress is influenced by perceived noise and context. Using geographic ecological momentary assessment, along with activity-travel diaries, GPS tracking, and portable noise sensors, this study collected real-time data of individuals' daily movement, noise exposure, and self-reported noise perception and psychological stress. Structural equation modeling was used to examine the direct and indirect pathways among context, momentary measured noise, perceived noise, and psychological stress. The study finds that momentary measured noise influences psychological stress through the mediating effect of perceived noise. Further, different activity and travel, social, and temporal contexts significantly influence people's momentary measured noise, perceived noise, and psychological stress. These findings advance our understanding of specific contexts, individual-based objectively measured and subjectively perceived environmental exposures, and their effects on psychological health at a high spatiotemporal resolution.

Assessing personal noise exposure and its relationship with mental health in Beijing based on individuals' space-time behavior.

BACKGROUND: Most prior studies adopted a static residence-based approach in the assessment of noise exposure, which may lead to biased exposure estimates and misleading findings in noise-health relationships. Relatively little is known about personal noise exposure based on individuals' space-time behavior and its effect on mental health. OBJECTIVES: This study aims to analyze and geo-visualize personal exposure to noise in various microenvironments based on individuals' space-time trajectories at a very fine resolution and to further investigate the relationships between mental health and personal noise exposure at both the activity/travel episode level and the entire day level. METHODS: Individual-level real-time data were collected with portable noise sensors and GPS trackers from a sample of 117 residents aged 18-60 years old from December 2017 to February 2018 in Beijing, China. Descriptive statistics and geo-visualization methods were used to examine how personal noise exposure varied across different activity types, travel modes, and among residents living in the same residential neighborhood on workdays and weekends based on individuals' space-time behaviors. Logistic regression models were applied to examine the relationships between personal noise exposure and self-reported mental health. RESULTS: We observed substantial differences in personal noise exposure across different activity types. The equivalent sound levels (Leq, dB(A)) for sleeping were the lowest, while the average Leq for work-related activities was the highest in indoor environments. The noise exposure levels for activities in outdoor environments were higher than indoor noise levels but differed between workdays and weekends. Variations in noise exposure associated with different travel modes were also evident, with the average Leq for public transport being much higher than that of other travel modes. A-weighted equivalent sound pressure level measured over 24 h for each individual (Leq,24h, dB(A)) varied significantly for residents living in the same residential neighborhood, ranging from 36 to 97 dB(A), with the majority of respondents being exposed to noise levels above 55 dB(A) on both workdays and weekends. Regarding the noise-health relationships, the modeling results showed that individual-level objective noise exposure based on space-time behaviors measured over a 24-h period (Leq,24h) was strongly associated with residents' self-reported mental health. Higher exposure to noise was significantly associated with worse mental health. However, personal noise exposure at the activity/travel episode level (Leq) was not significantly associated with mental health on weekdays, but this link turned out to be significant in the weekend model. CONCLUSIONS: There were large variations in personal noise exposure associated with different activity types and travel modes, and the individual-level noise exposure varied significantly across time of day and between residents living in the same residential neighborhood. Variations in personal exposure strongly depend on different space-time behaviors and individual-specific microenvironments experienced in daily life, and they were significantly correlated with mental health.

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).

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.

The Anatomy of Health-Supportive Neighborhoods: A Multilevel Analysis of Built Environment, Perceived Disorder, Social Interaction and Mental Health in Beijing.

Mental health is an exceedingly prevalent concern for the urban population. Mounting evidence has confirmed the plausibility of high incidences of mental disorders in socioeconomically disadvantaged neighborhoods. However, the association between the neighborhood built environment and individual mental health is understudied and far from conclusive, especially in developing countries such as China. The underlying mechanism requires in-depth analysis combining potential intermediates such as perceived environmental disorder and supportive social relationships. Using a health survey conducted in Beijing in 2017, this study investigates for the first time a socio-environmental pathway through which perceived disorder and social interaction account for the relationship between the built environment and mental health under the very notion of the neighborhood effect. The results from multilevel structural equation models indicate that individual mental health is influenced by the neighborhood-scale built environment through three pathways, independent of neighborhood socioeconomic disadvantages: (1) proximity to parks is the sole indicator directly linked to mental health; (2) population density, road connectivity and proximity to parks are indirectly associated with mental health through interactions with neighbors; and (3) population density, road connectivity and facility diversity are partially associated with perceived neighborhood disorder, which is indirectly correlated with mental health through interactions with neighbors. This study is a preliminary attempt to disentangle the complex relationships among the neighborhood environment, social interaction and mental health in the context of developing megacities. The relevant findings provide an important reference for urban planners and administrators regarding how to build health-supportive neighborhoods and healthy cities.

A Multilevel Analysis of Perceived Noise Pollution, Geographic Contexts and Mental Health in Beijing.

With rapid urbanization and increase in car ownership, ambient noise pollution resulting from diversified sources (e.g., road traffic, railway, commercial services) has become a severe environmental problem in the populated areas in China. However, research on the spatial variation of noise pollution and its potential effects on urban residents' mental health has to date been quite scarce in developing countries like China. Using a health survey conducted in Beijing in 2017, we for the first time investigated the spatial distributions of multiple noise pollution perceived by residents in Beijing, including road traffic noise, railway (or subway) noise, commercial noise, and housing renovation (or construction) noise. Our results indicate that there is geographic variability in noise pollution at the neighborhood scale, and road traffic and housing renovation/construction are the principal sources of noise pollution in Beijing. We then employed Bayesian multilevel logistic models to examine the associations between diversified noise pollution and urban residents' mental health symptoms, including anxiety, stress, fatigue, headache, and sleep disturbance, while controlling for a wide range of confounding factors such as socio-demographics, objective built environment characteristics, social environment and geographic context. The results show that perceived higher noise-pollution exposure is significantly associated with worse mental health, while physical environment variables seem to contribute little to variations in self-reported mental disorders, except for proximity to the main road. Social factors or socio-demographic attributes, such as age and income, are significant covariates of urban residents' mental health, while the social environment (i.e., community attachment) and housing satisfaction are significantly correlated with anxiety and stress. This study provides empirical evidence on the noise-health relationships in the Chinese context and sheds light on the policy implications for environmental pollution mitigation and healthy city development in China.

An Innovative Context-Based Crystal-Growth Activity Space Method for Environmental Exposure Assessment: A Study Using GIS and GPS Trajectory Data Collected in Chicago.

Scholars in the fields of health geography, urban planning, and transportation studies have long attempted to understand the relationships among human movement, environmental context, and accessibility. One fundamental question for this research area is how to measure individual activity space, which is an indicator of where and how people have contact with their social and physical environments. Conventionally, standard deviational ellipses, road network buffers, minimum convex polygons, and kernel density surfaces have been used to represent people's activity space, but they all have shortcomings. Inconsistent findings of the effects of environmental exposures on health behaviors/outcomes suggest that the reliability of existing studies may be affected by the uncertain geographic context problem (UGCoP). This paper proposes the context-based crystal-growth activity space as an innovative method for generating individual activity space based on both GPS trajectories and the environmental context. This method not only considers people's actual daily activity patterns based on GPS tracks but also takes into account the environmental context which either constrains or encourages people's daily activity. Using GPS trajectory data collected in Chicago, the results indicate that the proposed new method generates more reasonable activity space when compared to other existing methods. This can help mitigate the UGCoP in environmental health studies.

Interaction between amylose and tea polyphenols modulates the postprandial glycemic response to high-amylose maize starch.

High-amylose maize starch (HAM) is a common source material to make resistant starch with its high content of amylose (>70%). In the current investigation, the self-assembly of amylose in the presence of bioactive tea polyphenols (TPLs) and resulting slow digestion property of starch were explored. The experimental results using a mouse model showed a slow digestion property can be achieved with an extended and moderate glycemic response to HAM starch cocooked with TPLs. Further studies using a dilute aqueous amylose solution (0.1%, w/v) revealed an increased hydrodynamic radius of amylose molecules, indicating that TPLs could bridge them together, leading to increased molecular sizes. On the other hand, the bound TPLs interrupted the normal process of amylose recrystallizaiton evidenced by a decreased viscosity and storage modulus (G') of HAM (5%) gel, a rough surface of the cross-section of HAM film, and decreased short-range orders examined by Fourier transform infrared spectral analysis. Single-step degradation curves in the thermal gravimetric profile demonstrated the existence of a self-assembled amylose-TPL complex, which is mainly formed through hydrogen bonding interaction according to the results of iodine binding and X-ray powder diffraction analysis. Collectively, the amylose-TPL complexation influences the normal self-assembling process of amylose, leading to a low-ordered crystalline structure, which is the basis for TPLs' function in modulating the digestion property of HAM starch to produce a slowly digestible starch material that is beneficial to postprandial glycemic control and related health effects.

Synergistic effect of oleic acid and glycerol on zein film plasticization.

Oleic acid and glycerol are two different molecules with different plasticization mechanisms, and their effects on the mechanical properties of zein film were investigated. The mechanical parameters of tensile strength (TS) and elongation to break (E) were improved by either oleic acid or glycerol in a dose-dependent manner up to 20%. When a combination of the two plasticizers in different ratios was used to make zein films, the highest TS was observed at a ratio of 3:1 of oleic acid to glycerol, and a synergy between them was revealed through a statistical analysis. A significant decrease of glass transition temperature (Tg) and different microscopic patterns examined by scanning electronic microscopy (SEM) indicate the supramolecular structure was changed by the plasticizers. A combination of plasticizers with different plasticization mechanisms might be a better way to synergistically improve the mechanical properties of biopolymer-based films for practical applications.