Research progress in micro-scale environmental monitoring,exposure and individual response in Chinese literature

Technical transition of the traditional monitoring methods

Traditional environmental monitoring primarily relies on macro-scale monitoring methods, such as fixed-site monitoring, fixed stations combined with mathematical model simulation (Tao et al., 2014; Wu et al., 2012), and ground monitoring combined with remote sensing inversion (He et al., 2010; Wu et al., 2012). These methods enable large-scale, long-term monitoring of the spatiotemporal distribution of environmental exposure at a low cost. Previous studies have emphasized the distribution patterns and evolutionary trends of large-scale environmental factors. Among these methods, fixed-site monitoring stands out for its low cost, ease of operation, and suitability for large-scale continuous monitoring. The model simulation method typically utilizes existing data to construct a model that simulates more detailed environmental conditions, requiring less manpower and incurring lower costs. Additionally, remote sensing inversion technology, when combined with ground monitoring data, enables large-scale and fine-grid monitoring of the spatiotemporal distribution of environmental elements (Du et al., 2015).

In recent years, researches in the fields of traditional monitoring have undergone a technical transition, marked by improvements in monitoring accuracy and advancements in simulation methods. Key technological evolutions include:(1) the addition of monitoring stations and enhancement of site density; (2) the integration of traditional remote sensing and geographic information system technology with machine learning methods such as the random forest model, resulting in a more detailed monitoring of the spatial and temporal distribution of environmental exposure (Li et al., 2020a, 2020b); and (3) a thematic transition towards more nuanced content, such as high-temperature exposure and green environmental exposure (Li et al., 2020b). However, the above methods still face challenges such as the inability to precisely monitoring micro-environments and the difficulty of incorporating all influencing factors.

Targeted measurement of environmental exposure through mobile monitoring

The development of mobile monitoring technology has addressed the challenge of inadequate precision in environmental data resulting from the high cost and low density of fixed monitoring stations. One predominant focus of environmental exposure research within the Chinese world has been on the mobile monitoring methods especially the measurement of PM2.5 exposure. In contrast to water and soil pollution, air pollution exhibits conspicuous spatial and temporal heterogeneity and exerts a more direct impact on individuals. Approximately 30% of air pollution in China comes from civil and mobile sources (Ministry of Ecology and Environment of China, 2022) which are often challenging to scrutinize. Among numerous air pollutants, PM2.5 stands as the primary pollutant in most Chinese cities (Wang and Wang, 2014). The escalation of PM2.5 concentration in the air significantly influences air quality. PM2.5 absorbs various harmful and toxic substances, thereby exerting enduring effects on the human respiratory system, cardiovascular system, immune system, fertility, and nervous system. Traditional monitoring methods face challenges in comprehensively covering particulate matter exposure monitoring. This chapter will review the micro-scale transition in environment monitoring, focusing on mobile monitoring of particulate matter.

Utilizing mobile monitoring technology, the researchers investigated the spatiotemporal distribution of particulate matter, achieving a high level of resolution in their analyses. These studies revealed that the distribution of particulate matter in cities was influenced by various factors, including seasons, weekends and holidays, time of day, urban spatial structure, urban roads, and land use.

Previous studies have investigated how particulate matter concentration changes over time on various scales. A study in Shanghai City found that individual PM2.5 exposure levels followed the pattern of autumn > spring > summer > winter (Chen et al., 2021). Additionally, it was observed that the exposure level during the heating period was significantly higher than that during the non-heating period in Taiyuan City (Shi et al., 2008). Another study conducted in the urban area of Xiangyang, utilizing over 180 air quality monitoring micro-stations, revealed the presence of a “weekend effect” and a “Spring Festival effect” on particulate matter exposure. The study further highlighted that the “weekend effect” was more pronounced during winter (Liu et al., 2023). On the basis of the above study, the researchers studied the spatiotemporal changes of air pollution during the Spring Festival in downtown Xiangyang based on multi-year time series data, and evaluated the effectiveness of the implementation of measures to ban fireworks and firecrackers during the Spring Festival in previous years (Liu et al., 2022). This article revealed that the spatial pattern of PM2.5 can be described through a high-density station monitoring network combined with high-temporal-resolution spatial analysis, which could be used for accurate identification and process derivation of local-scale air pollution spatiotemporal changes.

Studies have also examined the distribution of particulate matter concentration in urban areas. Mobile particulate monitor was utilized to monitor PM2.5 pollution in the central urban area of Guangzhou Ring Expressway (Song et al., 2020). A high-resolution PM2.5 pollution simulation, with a spatiotemporal resolution of 10 m × 10 m, was conducted for the research area. The results revealed significant spatiotemporal differentiation characteristics of PM2.5 pollution in the central area of Guangzhou. Fixed high-mass concentration areas and low-mass concentration areas were observed during both dry and wet seasons. The targeted spatiotemporal distribution pattern of road PM2.5 was simulated using machine learning techniques and data collected by the mobile PM2.5 monitor (Lin and Zhou, 2023). The proposed fine-grained mapping method for PM2.5 concentration in this study achieved a spatial accuracy of up to 1 m, enabling a more accurate description of spatial heterogeneity. A study installed mobile monitor on express vehicles to collect PM2.5 concentrations in various settings within the southern part of Fuzhou’s main urban area. The study then employed a combination of geographic weighted regression and gradient boosting decision tree methods to propose a PM2.5 concentration simulation and scene analysis model based on Geographic Weighted Regression combined with Gradient Boosting Decision Tree (GWR-GBDT) (Xie et al., 2022). This model enhances the precise monitoring capabilities of urban PM2.5 pollution.

Different groups lead to heterogeneity of environmental exposure due to differences in activity patterns. Therefore, scholars have carried out researches on the particulate matter exposure of key public places in cities, such as urban parks, schools, and residential area. Green space is a key part of the urban ecological environment and a key place for residents’ outdoor activities, which plays an important role in urban ecology, landscape, society, and public health (Mao et al., 2012). Therefore, the environmental exposure in green spaces is worth studying. In a pioneering research, mobile air quality monitors were used to measure the air quality of 33 community parks in the central urban area of Guangzhou, and the result proved that the risk of particulate matter exposure and its spatial pattern distribution in community parks in the central urban area of Guangzhou were quite various. In a study based on questionnaires, more than one-third of residents’ subjectively perceived PM2.5 levels were better than objective observations in green space, indicating that a considerable number of residents overestimated the air quality of community parks (Yang et al., 2021). School is a primary space for the daily activities of children and teenagers, so the air quality of school has an important impact on children’s health. Mobile particulate matter monitor was used to monitor the PM2.5 exposure of a primary school in Guangzhou, and the daily potential exposure levels were estimated. Results showed that traffic pollution source was one of the sources of indoor and outdoor PM2.5 in the primary school (Ke et al., 2011). Some scholars have also carried out real-time particulate matter monitoring in residential areas to study activity satisfaction of air quality, and explored its impact on residents’ quality of life. Through mobile monitoring and daily activity log, one research in Beijing found that subjective exposure assessment could significantly reduce activity satisfaction, while objective exposure had no significant impact (Rao et al., 2022), proving objective environmental exposure had a significant indirect effect on activity satisfaction mainly by influencing subjective pollution evaluation in residential areas.

Mobile measuring of build environment with wearable camera

Besides the mobile monitoring of environmental pollution, in recent years, researchers have started to utilize wearable cameras to monitor individuals’ exposure to the built environment. This research method considers the individual life trajectory and can effectively meet people’s needs for convenience in daily travel, surpassing the traditional built environment assessment method. Studies have demonstrated that the built environment is linked to the occurrence of chronic diseases such as allergies, asthma, obesity, coronary heart disease, hypertension, hyperlipidemia, and type 2 diabetes (Huang et al., 2021; Lu and Tan, 2015). Additionally, it can induce or alleviate individual anxiety, depression, and mental stress (Chen et al., 2016; Wang et al., 2022). Measuring the characteristics of the built environment perceived by people is a key step for evaluating the extent of an individual’s exposure to the built environment.

The emergence of wearable cameras has provided new possibilities for monitoring individual behavior in space and creating individual ‘life logs’. By wearing a camera and capturing photos of the built environment, researchers can evaluate these photos and obtain participants’ exposure measurements through statistical evaluations. In terms of theoretical research, two new methods can be employed to measure exposure to the built environment. One method involves overlaying the spatiotemporal movement trajectories of individuals and evaluating the characteristics of the built environment reflected in Street View images to obtain measurement results. The other method entails individuals wearing a wearable camera, and the images captured by these cameras can reflect the features of the built environment to which individuals are exposed (Li and Long, 2021). In practical studies, wearable cameras are worn by individuals to collect photos along their daily trajectories, allowing for the exploration of the spatiotemporal distribution of individual behavioral characteristics and environmental exposure scenes (Zhang and Long, 2019). The large number of images collected by wearable cameras contain abundant information on individual behavior and spatiotemporal dynamics. These images effectively describe the characteristics of individual behavior in space, and hold great potential for studying the relationship between individual behavior and the built environment.

Exposure measurements for different populations

Significant differences exist in particulate matter exposure among sociodemographic attribute groups. Gender, age, education, and other factors are correlated with the difference in residents’ environmental exposure level. Scholars have been paying attention to comparative studies of environmental exposure of different groups and research on environmental fairness in the care of vulnerable groups. There are significant differences in air pollution exposure among different socioeconomic attribute groups (Guo et al., 2015). Car ownership, real estate ownership, and middle income are potential causes for environmental exposure differences. Social groups experience distinct environmental exposures due to their diverse work-life rhythms. Responsively, scholars have been paying attention to residents’ socioeconomic attributes, specifically focusing on the adverse environmental impact experienced by different social groups (Ma et al., 2017).

Some literature focused on vulnerable groups such as the elderly and children, highlighting the importance of environmental justice and health inequality. Due to the decline in physical function and metabolism, the elderly population are more susceptible to air pollutant particles. With the acceleration of China’s aging population, the number of elderly living in cities continues to rise. As of 2020, China’s population aged 65 and above accounted for 13.52%, indicating the country’s transition into a moderately aging society. Therefore, some research focused on the assessment of air pollution exposure in the elderly population and its influencing factors. An environmental exposure research in Shanghai conducted four times of follow-up visits to the same elderly group in four seasons, and conducted activity and household questionnaire surveys. It was found that season, climate, and behavior pattern could affect the deviation between official Air Quality Index (AQI) and elderly’s individual exposure (Chen et al., 2021). Childhood is a critical period of growth and development, and children’ resistance to particulate matter is poor. Studies have shown that particulate matter not only increase the prevalence of children’s respiratory system, but also reduce children’s lung function and immune function (Wang et al., 2007). Mobile monitors were utilized to evaluate the PM2.5 concentration of children’s main activity places and calculated the exposure level of individuals based on children’s activity log (Deng et al., 2009). The results showed a strong correlation between the PM2.5 index and the exposure level of individual children. One interesting finding was that the distance from children’s living rooms to traffic arteries was negatively correlated with exposure levels.

Due to the contact of particulate matter in working environment, special occupational groups are often exposed to highly polluted environment in the long term, and the relative health damage is serious. Scholars have begun to pay attention to the level of pollution exposure of special groups such as traffic police and painting workers. Using staff who work indoors as the control group, a research found that the PM2.5 exposure of traffic police in Taiyuan was significantly higher than which of the control group, and the decline in lung function of male traffic police may relate to long-term motor vehicle exhaust exposure (Xu et al., 2013). Through comparative analysis, researcher found that volatile organic compound pollution in newly renovated residences was in high concentration, and the exposure of painting workers was much higher than that of non-occupational groups (Gao et al., 2006).

In addition to particulate matter exposure, noise exposure studies in general population and certain groups are also research focus,. Researchers conducted a series of studies to examine the relationship between noise exposure level and health outcomes. These studies identified that cumulative noise exposure raised the incidence of hearing loss (Xie et al., 2015), kidney damage (Chen et al., 2022), and the risk of hypertension (Su et al., 2020). For certain occupational groups, such as workers in urban transportation departments (Zhu et al., 2007), oil enterprises (Li et al., 2004), and hydropower stations (Li and Li, 2016), noise is the primary occupational hazard factor, exposing them to a greater risk of noise pollution compared to the general population. Scholars have employed mobile noise meters to investigate the noise exposure of these specific occupational groups. The findings revealed that a significant number of staff members in subway station halls, computer rooms, traffic patrols, and drilling enterprises were subjected to noise intensities exceeding 80 dB(A), indicating a relatively high level of noise exposure. Noise exposure not only has a detrimental impact on mental health but also contributes to hearing loss and increases the risk of cardiovascular diseases.

Currently, the latest research trend has shifted the focus of environmental exposure measurement from specific group to all the citizen, yielding more valuable research results. A recent study found that residents’ exposure to noise and particulate matter could reduce their momentary happiness (Su et al., 2024).

Residents’ travel modes and environmental exposure measurement

Mobile particulate matter monitor enables the collection of exposure data during traveling process. Exposure to particulate matter during travel is significant, with individuals experiencing 2 to 5 times higher exposure levels in public transport micro-environments compared to residential and other activity spaces (Moreno et al., 2015) The choice of travel mode is a key factor influencing differences in exposure levels. Examining variations in exposure levels across different travel modes can provide guidance for the public to make informed choices and avoid high exposure risks.

Researchers used mobile monitors to explore particulate exposure in different travel modes in the same city (Li et al., 2015). This study revealed that walking could cause the highest individual exposure amount, whereas taxis caused the lowest. An assessment system was established to evaluate travelers’ intake quantity of particulate matter when traveling with different travel mode (Zhu et al., 2022). Analysis results based on experimental data from Xi’an showed that compared to data from environment monitoring stations, there was a significant difference for the PM concentration detected in taxi, bus carriage and subway carriage, while the difference was not significant for the PM concentration detected in sidewalk, non-motor taxi stop, bus stop, subway station hall, and subway platform.

Bus micro-environmental pollution and its adverse impacts on passengers’ health has become an increasing concern. In Guangzhou, a study successfully evaluated the air quality of six typical bus lines in real-time. Through the implementation of the random forest algorithm, researchers examined the relationship between the bus micro-environment and passenger comfort (Zhang et al., 2021). The study revealed that PM2.5 concentrations in buses had the greatest impact on passenger comfort, compared to temperature, relative humidity, and noise.

In regards of metro, online monitor was used to measure individual black carbon exposure on both underground and ground metro lines in Shanghai (Lei et al., 2016). The study found that black carbon exposure in the underground lines was significantly higher than that in the surface lines. Additionally, meteorological conditions such as rainfall and wind speed had a certain impact on the black carbon exposure level of the subway station, with a greater impact on the surface lines compared to the underground lines.

The aforementioned investigations focused on the natural environmental exposures encountered by individuals. Within contemporary urban landscapes in China, the diverse built environment plays a significant role in influencing individual behavior, and exerts direct or indirect impacts on the physical and mental health of residents. The mechanisms and effects associated with such impacts are often multifaceted. Notably, certain scholars have started the explorations of built environment exposure and its influences on individuals, employing novel technologies like VR and mobile physiological monitors. Subsequent chapter will provide a comprehensive review of relevant research in this domain.

Constructing virtual spaces and evaluating built environments through virtual reality technology

The virtual world created by VR technology can integrate various real-world experiences and enable researchers to conduct environmental exposure experiments in a laboratory setting. In comparison to videos and photos, VR technology offers interactivity and immersion, making itself an essential tool for studying human response to environment. More recently, the planning and urban design community has started utilizing VR technology to explore individuals’ perceptions of the environment and the effects of the environment on individuals. Subsequently, they provide recommendations for planning and design practices.

The researchers conducted studies assessing the built environment on various spatial scales, ranging from the urban road network to individual buildings. The street network space constructed using VR technology can be utilized to conduct cognitive experiments and study people’s response to environmental exposure in urban areas. VR enables the establishment of a correlation between the spatial form of the street network and subjective cognition (Yuan and Zhang, 2012). By summarizing relevant VR experiments, this study provided insights into the methods and workflow of applying virtual reality technology in urban design and architectural research. Good walkability can encourage residents to choose non-motorized modes of travel. By employing the Mars VR evaluation engine and visual stated-preference method, the utility level of various street spatial features in terms of walkability could be calculated by comparing the old and new urban areas in Guangzhou (Chen et al., 2022). Additionally, the assessment of the built environment was complemented by the use of physiological monitoring devices, providing supplementary conclusions to the aforementioned VR experiment. In another major city in China, Shanghai, a case study was conducted focusing on the streets of Jing’an District. Through the modeling of virtual reality scenes and the visualized stated-preference method, the researcher compared the influence of various design interventions on pedestrians’ walking suitability. Furthermore, a decision tree-based machine learning algorithm was employed to measure the influence of street spatial interface feature elements on walking suitability evaluation (Shi et al., 2020). The urban underground space has become an integral part of the urban built environment, and individuals’ activities in underground spaces have become a part of their daily routines. A virtual environment pathfinding experiment conducted in a subway station scene demonstrated the feasibility of a pedestrian simulation and traffic behavior data acquisition platform based on VR systems. The experimental results aligned with the behavioral characteristics of pedestrians in the actual environment and could accurately assess the detailed traffic behaviors of pedestrians (Wang et al., 2021). By focusing on the scale of individual buildings, VR technology can be utilized to conduct quantitative research on the social utility of lower public spaces in tall buildings (Ye et al., 2019). In a case study conducted in Shanghai, over 200 volunteers made their preferences based on their experiences within a VR model. The experimental results obtained can be used to design lower public spaces in tall buildings and provide targeted guidance for the specific areas in question.

Exploring individual responses to environmental exposure through physiological monitoring studies

Physiological monitoring encompasses various observation targets, such as eyeballs (eye movement), skin (electrodermal activity), and the brain (electroencephalography, magnetic resonance, etc.), which can record physical functional activities and emotional cognitive processes during environmental exposure. Devices such as Electroencephalogram (EEG) monitors, electrodermal activity monitors, and eye movement trackers can provide more detailed physiological response data of the human body under specific environmental exposure conditions such as: road, tunnel and indoor environment. They facilitate studies that were challenging to conduct using previous research methods.

The physiological and psychological factors of drivers fluctuate with changes in road environmental factors, which can impact driving safety. The combination of EEG monitors and simulated cockpits can be used to investigate the relationship between road environment monotony and driver fatigue. One study discovered a significant decline in the driver’s heart rate in a monotonous driving environment, revealing a notable pattern of heart rate changes (Zhao et al., 2011). During night-time driving, the mental load on drivers increases to a certain extent, making it more challenging for them to process environmental information and affecting driving safety. Researchers conducted driving experiments using driving simulators and wearable physiological instruments. The results showed that compared to daytime driving, drivers experienced significantly increased subjective pressure during night driving experiments, with the subjective pressure being directly proportional to the driving difficulty. Additionally, physiological indices such as power spectrum density of heart rate variability and EEG load level exhibited significant differences, and respiratory frequency also showed changes. However, respiratory amplitude and Electrocardiogram (ECG) indices did not exhibit significant changes. These research findings can be used for quantitative safety evaluations of night-time road traffic (Wang et al., 2017). Given that China is a mountainous country with numerous roads featuring twists and slopes in mountainous areas, road safety is a significant concern. The results of a study involving the use of wearable physiological and psychological instruments to collect drivers’ physiological data indicated that additional safety facilities and warning signs had positive effects on driving safety (Qin et al., 2022).

The improvement of the tunnel environment can help improve road safety, and wearable devices can assist in monitoring drivers’ health indicators in tunnel environments. In practice, paintings on tunnel sidewall are often used to influence driver behavior (Liu, 2019). The effect of side wall patterns was tested through simulation experiments, collecting behavioral and physiological data (ECG, EEG, electromyography, and other electrophysiological signals). Undersea tunnel environments are characterized by enclosed spaces, poor visibility, and monotonous road landscapes, which can impact drivers’ physiological and psychological factors, leading to traffic accidents. Researchers utilized wearable eye trackers, video recorders, and other devices to collect real-time data on drivers’ eye movement characteristics, driving speed, and position. Based on this data, the characteristics of drivers’ eye movement and variations in vehicle speed were analyzed, and corresponding mathematical models were established (Pan et al., 2022). Indoor environmental exposure is a new focus of Chinese research in recent years. Wearable physiological devices can assist researchers in conducting exposure studies in indoor environments. An experiment involving pathfinding was conducted in an airport departure hall, where physiological data and eye movement data of participants were collected to analyze visual efficacy and comfort. The study aimed to explore the influence of the light environment on airport passengers (Liu et al., 2021). Wearable eye trackers can also contribute to interior design research. The Tobii Pro Glass eye tracker was utilized in large shopping malls to record participants’ eye movement data in the real visual field during the pathfinding process (Sun and Yang, 2019). The study investigated the visual salience of different markers and the influence of these markers on users’ psychology. The findings of this study can help analyze the weak points in visual observation during the pathfinding process and provide theoretical support and additional data for the design and optimization of complex building interiors.

When Chinese cities enter the stage of stock development, urban renewal has become the main work in the current urban planning, and urban renewal needs a light but effective intervention means. Physiological monitoring is also applied to the exploration of urban renewal in response to China’s urban design transformation. Compared with the traditional methods, this method has the characteristics of universality and embodiment, and comprehensively improves the objectivity and accuracy of the study of street spatial quality (Chen, 2023; Kang et al., 2023). An urban renewal project in Shanghai adopted this method and derived guidelines for the design of walking and activity spaces. To address the problem of excessive building setbacks in specific locations, it is proposed to profile these sections, optimize the layout of landscape greenery and various facilities, strengthen path guidance, improve the visibility of shop signs, and create streets that offer a good walking experience. To enhance the vitality of open spaces in specific locations, it is suggested to design them as pocket parks or civic leisure squares, and to arrange urban furniture to improve the quality of these spaces.

Based on the understanding individuals’ response mechanisms to the environment, planners can solidly apply health concepts in urban planning and management practices. A possible approach is to integrate residents’ spatiotemporal behavior data, environmental data, and health response data to understand the interactions between daily activities, urban spaces, environmental exposure, and health. This approach can guide residents in reducing exposure risks during daily activities and movements. It is also crucial to focus on the provision and construction of relevant community facilities tailored to the exposure characteristics of different groups.

The integration of mobile physiology monitoring and virtual reality holds considerable ability to advance research into individual behavioral processes and public health. The research results have started to play a crucial role in areas such as environmental health, urban planning, and traffic safety. Prospectively, the integration of real-time physiological data and long-term data promises to enhance the effectiveness of environmental health research, enabling thorough explorations of relevant issues in the field.