PRAISE-HK: A personalized real-time air quality informatics system for citizen participation in exposure and health risk management

Che, Wenwei; Frey, H. Christopher; Fung, Jimmy Chi Hung; Ning, Zhi; Qu, Huamin; Lo, Hong Kam; Chen, Lei; Wong, Tze-Wai; Wong, Michael; Lee, Ophelia C.W.; Carruthers, David; Cheung, Freeman; Chan, Jimmy W.M.; Yeung, David W. K.; Fung, Yik Him; Zhang, Xuguo; Stocker, Jenny; Hood, Christina; Hohenberger, Tilman Leo; Leung, King Wai; Louie, Phillip Y.K.; Li, Alison T.Y.; Sun, Li; Wei, Peng; Li, Zhiyuan; Zhang, Yumiao; Wang, Meilan; Shen, Qiaomu; Huang, Wei; Lee, Enoch; Patwary, Ashraf; Lei, Xiayu; Cheng, Steven Y.; Hossain, Shakhaoat; Tang, Kimberly Tasha Jiayi; Lao, Xiang Qian; Leung, R.W.M.; Chan, Diana; Liu, Ying; Yuan, Zibing; Lau, Alexis K.H.

doi:10.1016/j.scs.2019.101986

Cited by 37 publications

(25 citation statements)

References 82 publications

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“…long been recognized as one of the top environmental challenges by both governments and academia due to its widespread, severe impact on climate change and human health (An et al, 2019;Chang et al, 2020;Che et al, 2020;G. Wang et al, 2016).…”

Section: Research Articlementioning

confidence: 99%

“…Of the above‐mentioned assimilation approaches, the 3D‐Var method, which minimizes a cost function depending on the error covariance matrix, is the most computationally efficient (Feng et al., 2018; Z. Jiang et al., 2013; Z. Li et al., 2013). Frequent and long‐lasting air pollution has long been recognized as one of the top environmental challenges by both governments and academia due to its widespread, severe impact on climate change and human health (An et al., 2019; Chang et al., 2020; Che et al., 2020; G. Wang et al., 2016). The spatiotemporal distribution of air pollutants is a rich source of information for policymaking (Cai et al., 2017; Zhang, Fung, Lau, et al., 2020; Zhang, Fung, Zhang, et al., 2020), health benefit calculation (Chang et al., 2020; R. Wu et al., 2019; Xue, Zhu, et al., 2019), and chemical mechanism‐driven simulation (Glasius & Goldstein, 2016; Jathar et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

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Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method

et al. 2021

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Section: Research Articlementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method

et al. 2021

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“…The development of smartphone and mobile health (mHealth) apps to support general health, fitness and specific medical conditions has grown significantly in recent years [ 19 ]. These include a number of mHealth apps designed to provide timely and accessible data on environmental hazards, such as air quality, to support health decision-making [ 20 , 21 , 22 ]. Studies investigating individual adherence to information and/or alerts on environmental hazards report mixed results, however many consistently conclude that individuals with pre-existing health conditions are more likely to use such information to inform health decision-making [ 23 , 24 , 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Licskai et al (2013) reported improvements in symptom criteria for uncontrolled asthma through the provision of access to current and forecast air quality health index information to support asthma self-management [ 21 ]. More recently, Che et al (2020) developed the Personalized Real-Time Air Quality Informatics System for Exposure—Hong Kong (PRAISE-HK), to provide air quality health index information to assist individuals to manage their exposure to air pollution [ 20 ]. While results on the validity of PRAISE-HK are forthcoming, its development clearly demonstrates a research interest in exploring apps as an alternative, and potentially more effective, information source and communication avenue for air quality-related information.…”

Section: Introductionmentioning

confidence: 99%

Environmental Hazards and Behavior Change: User Perspectives on the Usability and Effectiveness of the AirRater Smartphone App

Workman

Jones

Wheeler

et al. 2021

IJERPH

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AirRater is a free smartphone app developed in 2015, supporting individuals to protect their health from environmental hazards. It does this by providing (i) location-specific and near real-time air quality, pollen and temperature information and (ii) personal symptom tracking functionality. This research sought to evaluate user perceptions of AirRater’s usability and effectiveness. We collected demographic data and completed semi-structured interviews with 42 AirRater users, identified emergent themes, and used two frameworks designed to understand and support behavior change—the Behavior Change Wheel (BCW) and the Protective Action Decision Model (PADM)—to interpret results. Of the 42 participants, almost half indicated that experiencing symptoms acted as a prompt for app use. Information provided by the app supported a majority of the 42 participants to make decisions and implement behaviors to protect their health irrespective of their location or context. The majority of participants also indicated that they shared information provided by the app with family, friends and/or colleagues. The evaluation also identified opportunities to improve the app. Several study limitations were identified, which impacts the generalizability of results beyond the populations studied. Despite these limitations, findings facilitated new insights into motivations for behavior change, and contribute to the existing literature investigating the potential for smartphone apps to support health protection from environmental hazards in a changing climate.

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“…Certain members of the local society (e.g., homemakers, elderly citizens) may be spending most of their time at home (indoors) while other individuals who remain mobile may be exposed to various levels of BC in diverse outdoor and transport MEs apart from home microenvironments. Therefore, it is important to gain a better understanding of home-based versus mobility-based PE to BC in urban environments so that effective air quality management strategies can be formulated to improve ambient and indoor air quality (IAQ) and more importantly to protect public health [ 53 ]. Such PE studies across MEs over 24 h are seldom conducted in cities [ 54 ].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Home-Based and Mobility-Based Exposure to Black Carbon in an Urban Environment: A Pilot Study

Adam

Tran

Cheong

et al. 2021

IJERPH

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The combustion of fossil fuels is a significant source of particulate-bound black carbon (BC) in urban environments. The personal exposure (PE) of urban dwellers to BC and subsequent health impacts remain poorly understood due to a lack of observational data. In this study, we assessed and quantified the levels of PE to BC under two exposure scenarios (home-based and mobility-based exposure) in the city of Trivandrum in India. In the home-based scenario, the PE to BC was assessed in a naturally ventilated building over 24 h each day during the study period while in the mobility-based scenario, the PE to BC was monitored across diverse microenvironments (MEs) during the day using the same study protocol for consistency. Elevated BC concentrations were observed during the transport by motorcycle (26.23 ± 2.33 µg/m3) and car (17.49 ± 2.37 µg/m3). The BC concentrations observed in the MEs decreased in the following order: 16.58 ± 1.38 µg/m3 (temple), 13.78 ± 2.07 µg/m3 (restaurant), 11.44 ± 1.37 µg/m3 (bus stop), and 8.27 ± 1.88 µg/m3 (home); the standard deviations represent the temporal and spatial variations of BC concentrations. Overall, a relatively larger inhaled dose of BC in the range of 148.98–163.87 µg/day was observed for the mobility-based scenario compared to the home-based one (118.10–137.03 µg/day). This work highlights the importance of reducing PE to fossil fuel-related particulate emissions in cities for which BC is a good indicator. The study outcome could be used to formulate effective strategies to improve the urban air quality as well as public health.

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PRAISE-HK: A personalized real-time air quality informatics system for citizen participation in exposure and health risk management

Cited by 37 publications

References 82 publications

Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method

Improved Modeling of Spatiotemporal Variations of Fine Particulate Matter Using a Three‐Dimensional Variational Data Fusion Method

Environmental Hazards and Behavior Change: User Perspectives on the Usability and Effectiveness of the AirRater Smartphone App

Assessment of Home-Based and Mobility-Based Exposure to Black Carbon in an Urban Environment: A Pilot Study

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