Distribution patterns and influencing factors of population exposure risk to particulate matters based on cell phone signaling data

Zhang, Chuyi; Hu, Yuanman; Adams, Matthew D.; Bu, Rencang; Xiong, Zenggang; Liu, Miao; Du, Yan; Li, Binglun; Li, Chunlin

doi:10.1016/j.scs.2022.104346

Cited by 10 publications

(5 citation statements)

References 89 publications

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“…The emergence of the IoT paradigm allows the creation of architectures in which it is easy to integrate all these processes ( Fig 13 ). In addition, some pilots that combine mobile monitoring and modelling have demonstrated that they can reduce costs and improve accuracy [ 14 ].…”

Section: Discussionmentioning

confidence: 99%

“…Sequence analysis is essential for our proposed optimisation because this allows for avoiding population metrics that could be biased by the sampling process. Thus, it allows for performing analyses for different population sectors—for instance, analysing only the persons affected by cardiac issues—or even tracking and optimising the activities of a single individual [ 14 ]. In addition, the classical sensitive analysis should be performed by doing different simulations among the inputs to find the inputs that minimise a set of KPIs.…”

Section: Methodsmentioning

confidence: 99%

“…One alternative consists of asking participants to finish a diary questionnaire that includes time, activities, and location. This approach has been applied in the school context [ 14 ]. On the other hand, a more general strategy is to model this activity data using different strategies [ 8 ].…”

Section: State Of the Artmentioning

confidence: 99%

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Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining

Illueca Fernández,

Fernández Llatas,

Jara Valera

et al. 2023

PLoS ONE

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The World Health Organization has estimated that air pollution will be one of the most significant challenges related to the environment in the following years, and air quality monitoring and climate change mitigation actions have been promoted due to the Paris Agreement because of their impact on mortality risk. Thus, generating a methodology that supports experts in making decisions based on exposure data, identifying exposure-related activities, and proposing mitigation scenarios is essential. In this context, the emergence of Interactive Process Mining—a discipline that has progressed in the last years in healthcare—could help to develop a methodology based on human knowledge. For this reason, we propose a new methodology for a sequence-oriented sensitive analysis to identify the best activities and parameters to offer a mitigation policy. This methodology is innovative in the following points: i) we present in this paper the first application of Interactive Process Mining pollution personal exposure mitigation; ii) our solution reduces the computation cost and time of the traditional sensitive analysis; iii) the methodology is human-oriented in the sense that the process should be done with the environmental expert; and iv) our solution has been tested with synthetic data to explore the viability before the move to physical exposure measurements, taking the city of Valencia as the use case, and overcoming the difficulty of performing exposure measurements. This dataset has been generated with a model that considers the city of Valencia’s demographic and epidemiological statistics. We have demonstrated that the assessments done using sequence-oriented sensitive analysis can identify target activities. The proposed scenarios can improve the initial KPIs—in the best scenario; we reduce the population exposure by 18% and the relative risk by 12%. Consequently, our proposal could be used with real data in future steps, becoming an innovative point for air pollution mitigation and environmental improvement.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining

Illueca Fernández,

Fernández Llatas,

Jara Valera

et al. 2023

PLoS ONE

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“…While the principle is easy to grasp, its capacity to manage complex datasets and account for spatial variations is limited. GWR is a widely used tool for addressing spatial heterogeneity in models by allowing regression coefficients to vary with location [25]. The prerequisite is that it requires a sufficient number of widely distributed observation points for robust results [26,27].…”

Section: Introductionmentioning

confidence: 99%

Spatial Patterns and Determinants of PM2.5 Concentrations: A Land Use Regression Analysis in Shenyang Metropolitan Area, China

Shi,

Zhang,

Yuan

et al. 2024

Sustainability

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Identifying impact factors and spatial variability of pollutants is essential for understanding environmental exposure and devising solutions. This research focused on PM2.5 as the target pollutant and developed land use regression models specific to the Shenyang metropolitan area in 2020. Utilizing the Least Absolute Shrinkage and Selection Operator approach, models were developed for all seasons and for the annual average, explaining 62–70% of the variability in PM2.5 concentrations. Among the predictors, surface pressure exhibited a positive correlation with PM2.5 concentrations throughout most of the year. Conversely, both elevation and tree cover had negative effects on PM2.5 levels. At a 2000 m scale, landscape aggregation decreased PM2.5 levels, while at a larger scale (5000 m), landscape splitting facilitated PM2.5 dispersion. According to the partial R2 results, vegetation-related land use types were significant, with the shrubland proportion positively correlated with local-scale PM2.5 concentrations in spring. Bare vegetation areas were the primary positive factor in autumn, whereas the mitigating effect of tree cover contrasted with this trend, even in winter. The NDVI, an index used to assess vegetation growth, was not determined to be a primary influencing factor. The findings reaffirm the function of vegetation cover in reducing PM2.5. Based on the research, actionable strategies for PM2.5 pollution control were outlined to promote sustainable development in the region.

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“…Additionally, PM 2.5 particles have the ability to easily combine with toxic substances and can serve as carriers for virus transmission [17,18]. PM 2.5 exposure refers to the contact between the human body surface and air pollutants such as PM 2.5 [19]. Extensive research has demonstrated that exposure to PM 2.5 air pollution can have a severe impact on human respiratory and cardiovascular systems, resulting in elevated incidence rates and an increased risk of mortality related to pulmonary and cardiovascular diseases [20][21][22].…”

Section: Introductionmentioning

confidence: 99%

A Review of Global PM2.5 Exposure Research Trends from 1992 to 2022

Jia

Chen

et al. 2023

Sustainability

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Exposure to air pollutants of fine particulate matter (PM2.5) is a major threat to human health. Research on PM2.5 exposure has been on the rise in recent years, but there has been a lack of systematic literature analysis in this field. To address this research gap, we conducted a bibliometric analysis of the existing publications on PM2.5 exposure over the past three decades and analyzed the current state and historical trends of research using the open-access tool, KNIME. Our results show that the number of publications on PM2.5 exposure has been increasing at an accelerating rate over the last 30 years. The authors of the publications are primarily from developed nations, such as countries in North America, Europe, East Asia, and Oceania. Published research is mainly from the fields of Environmental Sciences and Ecology, Environmental Sciences, and Public, Environmental and Occupational Health. The main research hotspots are exposure, air pollution, and PM2.5. Research is trending toward the intersection and integration of multiple subjects. Our results highlight the rapid growth of PM2.5-related research and provide insights into the structure, impact, and trends of this interdisciplinary field.

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Distribution patterns and influencing factors of population exposure risk to particulate matters based on cell phone signaling data

Cited by 10 publications

References 89 publications

Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining

Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining

Spatial Patterns and Determinants of PM2.5 Concentrations: A Land Use Regression Analysis in Shenyang Metropolitan Area, China

A Review of Global PM2.5 Exposure Research Trends from 1992 to 2022

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