Assessing air quality index awareness and use in Mexico City

Borbet, Timothy C.; Gladson, Laura A.; Cromar, Kevin

doi:10.1186/s12889-018-5418-5

Cited by 42 publications

(42 citation statements)

References 26 publications

(25 reference statements)

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“…On one hand, we can account for the effect of air pollution on people movements in the location model. Indeed, some empirical studies have recently appeared in the literature with the aim of assessing whether people change their behavior in response to poor air quality (Welch et al ., ; Borbet et al ., ). Alerts reported by public/private agencies during severe pollution events may affect people behavior, since guidelines to reduce outdoor activities are often published during poor air quality episodes.…”

Section: Discussionmentioning

confidence: 97%

Quantifying Personal Exposure to Air Pollution from Smartphone-Based Location Data

Finazzi

Paci

2019

Biometrics

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Personal exposure assessment is a challenging task that requires both measurements of the state of the environment as well as the individual's movements. In this paper, we show how location data collected by smartphone applications can be exploited to quantify the personal exposure of a large group of people to air pollution. A Bayesian approach that blends air quality monitoring data with individual location data is proposed to assess the individual exposure over time, under uncertainty of both the pollutant level and the individual location. A comparison with personal exposure obtained assuming fixed locations for the individuals is also provided. Location data collected by the Earthquake Network research project are employed to quantify the dynamic personal exposure to fine particulate matter of around 2500 people living in Santiago (Chile) over a 4-month period. For around 30% of individuals, the personal exposure based on people movements emerges significantly different over the static exposure. On the basis of this result and thanks to a simulation study, we claim that even when the individual location is known with nonnegligible error, this helps to better assess personal exposure to air pollution. The approach is flexible and can be adopted to quantify the personal exposure based on any location-aware smartphone application. K E Y W O R D SDynamic models, Markov chain Monte Carlo, particulate matter, space-time modeling

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Section: Discussionmentioning

confidence: 97%

Quantifying Personal Exposure to Air Pollution from Smartphone-Based Location Data

Finazzi

Paci

2019

Biometrics

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“…Due to factors such as educational level [33,34], income level [35,36], and information disclosure [37,38], urban and suburban residents may have different behavioral and emotional responses to air pollution. Compared with NO 2 , SO 2 , and O 3 , particulate matter is more easily perceived.…”

Section: Hypothesis 3 Air Pollution Could Have Different Effects On mentioning

confidence: 99%

Impacts of Different Air Pollutants on Dining-Out Activities and Satisfaction of Urban and Suburban Residents

Rong

Hong-mei

et al. 2020

Sustainability

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Air pollution has become a global environmental problem that directly affects the living quality of city residents. It not only does damages to the physical health of the human body but also has adverse effects on mood, outdoor activities, and social interactions, which further reduces the vitality of the city. Dining out is an important way of social interaction for city residents. Using Beijing as an example, this paper aims to study the impacts of different air pollutants on dining-out activities and satisfaction of urban and suburban residents. The results show that: (1) Air pollution can significantly reduce dining-out frequency and satisfaction; (2) Due to differences in environmental and health awareness, the impact of air pollution on dining-out behaviors varies among urban and suburban residents; and (3) O3 pollution has a greater emotional impact on suburban residents than urban residents, possibly because of the differences in defense strategies and levels of pollution exposure in the workplace. The findings imply that improving air quality can obtain not only health benefits but also long-term social and economic vitality. The publicity of environment and health information should be strengthened on key urban air pollutants, especially on particulate matter and O3, and on disadvantaged groups to enhance environmental justice.

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“…The Air Quality Indexes evaluate the overall air pollution level based on multiple air pollutants, to measure the air quality with respect to its effects on human health [61][62][63][64][65][66][67].…”

Section: Air Quality Indexmentioning

confidence: 99%

Assessment and Mapping Green Areas Ecosystem Services and Socio-Demographic Characteristics in Turin Neighborhoods (Italy)

Battisti

Pomatto

Larcher

2019

Forests

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The ecosystem services (ES) and human well-being are keywords that guide the Italian strategy on urban greening. The development of ES priorities linked to specific land uses help to guide the drafting of management plans. The aim of the research was to assess and map green areas ecosystem services and socio-demographic characteristics in Turin neighborhoods in order to identify where to improve the provision of ecosystem services and the socio-demographic conditions. The Preliminary Assessment Method (PAM) was used for the assessment of provision and regulating services based on land use. The Species-specific Air Quality index (S-AQI) was used to assess the regulating services provided by trees. Three socio-demographic characteristics were analyzed at the neighborhood level-age index, housing density, and % of economically assisted citizens. PAM results show that Turin provides more ecosystem services in peripheral areas of the city. Trees with high S-AQI values represent 21% of the censed trees. Not recommended trees are 18%. The neighborhoods with higher S-AQI values are not always characterized by a higher number of trees/km 2 or species richness. Results show that the northern part of the city is characterized by higher values of ES and socio-demographic conditions than the central-southern part. This aspect is related to the conspicuous presence of agricultural land uses and water bodies, together with the presence of tree species with a high S-AQI values and high or medium socio-demographic conditions. 57% of the neighborhoods present low results for both aspects. Actions to improve the quality of green spaces in those neighborhoods could have great effects on liveability. Future management and planning strategies for increasing citizens' well-being through urban greening should consider the proposed approach.Forests 2020, 11, 25 2 of 19 (ES), beneficiaries and potential mismatches with their location of supply, as well as on the quality and quantity of ES, are essential to make informed decisions for the proper management of natural resources [5]. Moreover, human well-being is positively influenced by the level of biodiversity present in urban and peri-urban green spaces [6], which must be maintained or increased through effective management of plant and animal species, improving the quality of existing habitats through management [7]. In addition, socioeconomic inequalities in health are less pronounced in people with greater exposure to green space than in those with less exposure [8].As many ecosystem services are provided by urban green spaces, these will need to be better managed and planned to ensure a high standard of living in urban areas [9]. For the assessment of ecosystem services in urban areas, several methods can be applied [10][11][12]. Some of them are based on spatially explicit biophysical indicators to analyze the spatial distribution of ES delivery [13], others on suite of models or web-based modeling platforms for the spatially-explicit assessment of ecosystem services [14,15], and fi...

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Assessing air quality index awareness and use in Mexico City

Cited by 42 publications

References 26 publications

Quantifying Personal Exposure to Air Pollution from Smartphone-Based Location Data

Quantifying Personal Exposure to Air Pollution from Smartphone-Based Location Data

Impacts of Different Air Pollutants on Dining-Out Activities and Satisfaction of Urban and Suburban Residents

Assessment and Mapping Green Areas Ecosystem Services and Socio-Demographic Characteristics in Turin Neighborhoods (Italy)

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