scholarly journals Changes in air-pollution related behaviour measured by Google Trends Search Volume Index in response to reported air quality in Poland

2021 ◽  
Author(s):  
Wojciech Nazar ◽  
Katarzyna Plata-Nazar
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Winter Season ◽  
Google Trends ◽  
Volume Index ◽  
Quality Data ◽  
Coefficient Of Determination ◽  
Pollution Levels ◽  
Search Volume ◽  
Air Quality Data

Abstract Background Decreased air quality is connected to a higher number of hospital admissions and an increase in daily mortality rates. Thus, Poles’ behavioural response to sometimes elevated air pollution levels is vital. The aim of this study was to carry out analysis of changes in air-pollution related information seeking behaviour in response to nationwide reported air quality in Poland. Methods Google Trends Search Volume Index data was used to investigate Poles’ interest in air pollution-related keywords. PM10 and PM2.5 concentrations measured across Poland between 2016 and 2019 were collected from the Chief Inspectorate of Environmental Protection databases. Pearson Product-Moment Correlation and the R2 correlation coefficient of determination were used to measure spatial and seasonal correlations between reported air pollution levels and the popularity of search queries. Results The highest PM10 and PM2.5 concentrations were observed in southern voivodeships and during the winter season. Similar trends were observed for Poles’ interest in air-pollution related keywords. All R2 coefficient of determination values were > 0.5 and all correlations were statistically significant. Conclusion Poland’s air quality does not meet the World Health Organisation guidelines. Also, the air quality is lower in southern Poland and during the winter season. It appears that Poles are aware of this issue and search for daily air quality data in their location. Greater interest in air quality data in Poland strongly correlates with both higher regional and higher seasonal air pollution levels.

scholarly journals Changes in Air Pollution-Related Behaviour Measured by Google Trends Search Volume Index in Response to Reported Air Quality in Poland

2021 ◽  
Vol 18 (21) ◽  
pp. 11709
Author(s):  
Wojciech Nazar ◽  
Katarzyna Plata-Nazar
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Information Seeking ◽  
Google Trends ◽  
Volume Index ◽  
Quality Data ◽  
Pollution Levels ◽  
Search Volume ◽  
Pm10 And Pm2.5 ◽  
Information Seeking Behaviour

Decreased air quality is connected to an increase in daily mortality rates. Thus, people’s behavioural response to sometimes elevated air pollution levels is vital. We aimed to analyse spatial and seasonal changes in air pollution-related information-seeking behaviour in response to nationwide reported air quality in Poland. Google Trends Search Volume Index data was used to investigate Poles’ interest in air pollution-related keywords. PM10 and PM2.5 concentrations measured across Poland between 2016 and 2019 as well as locations of monitoring stations were collected from the Chief Inspectorate of Environmental Protection databases. Pearson Product-Moment Correlation Coefficients were used to measure the strength of spatial and seasonal relationships between reported air pollution levels and the popularity of search queries. The highest PM10 and PM2.5 concentrations were observed in southern voivodeships and during the winter season. Similar trends were observed for Poles’ interest in air pollution-related keywords. Greater interest in air quality data in Poland strongly correlates with both higher regional and higher seasonal air pollution levels. It appears that Poles are socially aware of this issue and that their intensification of the information-seeking behaviour seems to indicate a relevant ad hoc response to variable threat severity levels.

scholarly journals Understanding Public Response to Air Quality Using Tweet Analysis

2019 ◽  
Vol 5 (3) ◽  
pp. 205630511986765
Author(s):  
Supraja Gurajala ◽  
Suresh Dhaniyala ◽  
Jeanna N. Matthews
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Machine Learning Algorithms ◽  
Mitigation Measures ◽  
Quality Data ◽  
Public Health Issue ◽  
New Delhi ◽  
Public Response ◽  
Pollution Levels ◽  
Adverse Health Effects

Poor air quality is recognized as a major risk factor for human health globally. Critical to addressing this important public-health issue is the effective dissemination of air quality data, information about adverse health effects, and the necessary mitigation measures. However, recent studies have shown that even when public get data on air quality and understand its importance, people do not necessarily take actions to protect their health or exhibit pro-environmental behaviors to address the problem. Most existing studies on public attitude and response to air quality are based on offline studies, with a limited number of survey participants and over a limited number of geographical locations. For a larger survey size and a wider set of locations, we collected Twitter data for a period of nearly 2 years and analyzed these data for three major cities: Paris, London, and New Delhi. We identify the three hashtags in each city that best correlate the frequency of tweets with local air quality. Using tweets with these hashtags, we determined that people’s response to air quality across all three cities was nearly identical when considering relative changes in air pollution. Using machine-learning algorithms, we determined that health concerns dominated public response when air quality degraded, with the strongest increase in concern being in New Delhi, where pollution levels are the highest among the three cities studied. The public call for political solutions when air quality worsens is consistent with similar findings with offline surveys in other cities. We also conducted an unsupervised learning analysis to extract topics from tweets in Delhi and studied their evolution over time and with changing air quality. Our analysis helped extract relevant words or features associated with different air quality–related topics such as air pollution policy and health. Also, the topic modeling analysis revealed niche topics associated with sporadic air quality events, such as fireworks during festivals and the air quality impact on an outdoor sport event. Our approach shows that a tweet-based analysis can enable social scientists to probe and survey public response to events such as air quality in a timely fashion and help policy makers respond appropriately.

scholarly journals ASSESSING POPULATION SENSITIVITY TO URBAN AIR POLLUTION USING GOOGLE TRENDS AND REMOTE SENSING DATASETS

2020 ◽  
Vol XLII-3/W11 ◽  
pp. 93-100
Author(s):  
P. Misra ◽  
W. Takeuchi
Keyword(s):  
Remote Sensing ◽  
Air Pollution ◽  
Air Quality ◽  
Urban Air Pollution ◽  
Aerosol Concentration ◽  
Google Trends ◽  
Urban Air ◽  
Indirect Measure ◽  
Search Volume ◽  
Fine Aerosol

Abstract. This study demonstrates relationship between remote sensing satellite retrieved fien aerosol concentration and web-based search volumes of air quality related keywords. People’s perception of urban air pollution can verify policy effectiveness and gauge acceptability of policies. As a serious health issue in Asian cities, population may express concern or uncertainty for air pollution risk by performing search on the web to seek answers. A ‘social sensing’ approach that monitors such search queries, may assess people’ perception about air pollution as a risk. We hypothesize that trend and volume of searches show impact of air pollution on general population. The objectives of this research are to identify those atmospheric conditions under which relative search volume (RSV) obtained from Google Trends shows correlation with measured fine aerosol concentration, and to compare search volume sensitivity to rise in aerosol concentration in seven Asian megacities. We considered weekly relative search volumes from Google Trends (GT) for a four year period from January, 2015 to December, 2018 representing diverse PM2.5 concentrations. Search volumes for keywords corresponding to perception of air quality (‘air pollution’) and health effects (‘cough’ and ‘asthma’) were considered. To represent PM2.5 we used fine aerosol indicator developed in an earlier research. The results suggest that tendency to search for ‘air pollution’ and ‘cough’ occurs when AirRGB R is in excess and temperature is below the baseline values. Consistent with this, in cities with high baseline concentrations, sensitivity to rise in AirRGB R is also comparatively lower. The result of this study can used as an indirect measure of awareness in the form of perception and sensitivity of population to air quality. Such an analysis could be useful for forecasting health risks specially in cities lacking dedicated services.

scholarly journals Evidence of air quality data misreporting in China: An impulse indicator saturation model comparison of local government-reported and U.S. embassy-reported PM2.5 concentrations (2015–2017)

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249063
Author(s):  
Jesse S. Turiel ◽  
Robert K. Kaufmann
Keyword(s):  
Air Quality ◽  
Local Government ◽  
Model Comparison ◽  
Quality Data ◽  
Random Chance ◽  
Pollution Levels ◽  
Reported Data ◽  
Impulse Indicator Saturation ◽  
Air Quality Data ◽  
Monitoring Stations

This paper analyzes hourly PM2.5 measurements from government-controlled and U.S. embassy-controlled monitoring stations in five Chinese cities between January 2015 and June 2017. We compare the two datasets with an impulse indicator saturation technique that identifies hours when the relation between Chinese and U.S. reported data diverges in a statistically significant fashion. These temporary divergences, or impulses, are 1) More frequent than expected by random chance; 2) More positive than expected by random chance; and 3) More likely to occur during hours when air pollution concentrations are high. In other words, relative to U.S.-controlled monitoring stations, government-controlled stations systematically under-report pollution levels when local air quality is poor. These results contrast with the findings of other recent studies, which argue that Chinese air quality data misreporting ended after a series of policy reforms beginning in 2012. Our findings provide evidence that local government misreporting did not end after 2012, but instead continued in a different manner. These results suggest that Chinese air quality data, while still useful, should not be taken entirely at face value.

scholarly journals Developing Web-Based 3D Health-Aware Routing for Pedestrians and Cyclists

2020 ◽  
Vol 171 ◽  
pp. 02009
Author(s):  
Rosanny Sihombing ◽  
Sabo Kwada Sini ◽  
Matthias Fitzky
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Health Concern ◽  
Quality Data ◽  
Quality Level ◽  
3D Navigation ◽  
Index Numbers ◽  
Web Based ◽  
Air Quality Data ◽  
Monitoring Stations

As the population of people migrating to cities keeps increasing, concerns have been raised about air quality in cities and how it impacts everyday life. Thus, it is important to demonstrate ways of avoiding polluted areas. The approach described in this paper is intended to draw attention to polluted areas and help pedestrians and cyclists to achieve the lowest possible level of air pollution when planning daily routes. We utilise real-time air quality data which is obtained from monitoring stations across the world. The data consist of the geolocation of monitoring stations as well as index numbers to scale the air quality level in every corresponding monitoring stations. When the air quality level is considered having a moderate health concern for people with respiratory disease, such as asthma, an alternative route that avoid air pollution will be calculated so that pedestrians and cyclists can be informed. The implementation can visualize air quality level in several areas in 3D map as well as informs health-aware route for pedestrian and cyclist. It automatically adjusts the observed air quality areas based on the availability of monitoring stations. The proposed approach results in a prototype of a health-aware 3D navigation system for pedestrian and cyclist.

scholarly journals Trend of Particulate Matter PM 2.5 and PM 10 in Dhaka City

1970 ◽  
Vol 46 (3) ◽  
pp. 389-398 ◽  
Author(s):  
MA Rouf ◽  
M Nasiruddin ◽  
AMS Hossain ◽  
MS Islam
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Winter Season ◽  
Ambient Air ◽  
Quality Data ◽  
Dhaka City ◽  
Monsoon Period ◽  
Pm 2.5 ◽  
Pm 10

Dhaka City has been affecting with severe air pollution particularly by particulate matter. The ambient air quality data for particulate matter were collected during April 2002 to September 2005 at the Continuous Air Quality Monitoring Station (CAMS) located at Sangshad Bhaban, Dhaka. Data reveal that the pollution from particulate matter greatly varies with climatic condition. While the level comes down the limit value in the monsoon period (April-October), it goes beyond the limit during non-monsoon time (November-March). The latest data show that during monsoon period PM 10 concentration varies from 50 μg/m3 to 80 μg/m3 and PM 2.5 concentration from 20 μg/m3 to 60 μg/m3 and during non monsoon period PM 10 varies from 100 μg/m3 to 250 μg/m3 and PM 2.5 varies from 70 μg/m3 to 165 μg/m3. The seasonal variation clearly indicates the severe PM 10 pollution during the dry winter season and also sometime during post-monsoon season in Dhaka City. Keywords: Air pollution; PM 2.5; PM 10; Air quality DOI: http://dx.doi.org/10.3329/bjsir.v46i3.9049 BJSIR 2011; 46(3): 389-398

scholarly journals NO2 Concentration in Banepa Valley, Nepal

1970 ◽  
Vol 4 (1) ◽  
pp. 1-11
Author(s):  
Ahmad Kamruzzaman Majumder ◽  
V Krishna Murthy ◽  
Sanjay Nath Khanal ◽  
Dhiraj Giri
Keyword(s):  
Air Quality ◽  
Winter Season ◽  
Maximum Level ◽  
Ambient Air ◽  
World Health ◽  
Quality Data ◽  
Residential Areas ◽  
Pollution Levels ◽  
Air Sampler ◽  
Commercial Area

This study comprised of air quality monitoring during the day time at three municipalities of Banepa, Dhulikhel and Panauti(Known as Banepa Valley) in Kavre district of Nepal. The study was conducted in order to establish a baseline air quality data for those municipalities as the first time ever in the district. In each of those municipalities three air monitoring stations were established representing predominant industrial, commercial and residential areas. Nitrogen Dioxide (NO2) had been estimated from air sampling programme which spanned 7 months and a total of 126 days reflecting winter, premonsoon and monsoon seasons. Low Volume Air (LVA) Sampler and Personal air sampler were used for sampling. UV spectrophotometer was used for estimation of the NO2. The study found that during winter season the concentration of NO2 was more and among the areas commercial area found to be highest level pollution. The over all mean, minimum and maximum level of NO2 was found to be 24.62μg/m3, 11.26μg/m3, 91.20μg/m3 in the Banepa valley. The seasonal trend in pollution levels show that winter > pre-monsoon > monsoon. The pollution concentration trend noted among the areas was commercial > industrial > residential on almost all the occasions. This finding conclude that, most of the time NO2 level are below the National Ambient Air Quality Standards (NAAQS) and World Health Organization (WHO) guideline representing little risk at present in Banepa Valley however commercial area of Banepa is more polluted and is associated with higher NO2 concentration compared to other areas. Keywords: NO2, Nepal, Banepa, air quality, personal air sampler DOI: 10.3126/kuset.v4i1.2878 Kathmandu University Journal of Science, Engineering and Technology Vol.4, No.1, September 2008, pp 1-11

scholarly journals Environmental justice and air quality in Santiago de Chile

2015 ◽  
Vol 17 (3) ◽  
pp. 337-350 ◽  
Author(s):  
Richelle Rose Perez
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Environmental Justice ◽  
Fine Particles ◽  
Metropolitan Region ◽  
Quality Data ◽  
Policy Makers ◽  
Pollution Levels ◽  
Spatial Differences ◽  
Socioeconomic Data

<p><strong>Objective </strong>The metropolitan region in Santiago, Chile has an air quality problem.  However, the larger issue may lie in the inequities created by the distribution of the air pollution.</p><p><strong>Methods </strong>To assess the inequities created by the spatial differences in air pollution, the author analyzed fine particle pollution levels for 2008-2011 at monitoring stations throughout the region. The author also compared air quality data with socioeconomic data.</p><p><strong>Results </strong>The areas of the Santiago metropolitan region with the worst air quality have lower socioeconomic levels. Pollution in these areas reaches levels higher than the current Chilean 24 hour standard for fine particles. These areas also have longer time periods of unhealthy air and 21 % more days with unhealthy levels of air pollution.</p><p><strong>Discussion </strong>The differences in exposure to pollution create an inequality and environmental injustice among the socioeconomic groups in the metropolitan region. Chilean policymakers have the regulatory tools needed to improve environmental justice. However, they need to improve the implementation of these tools in order to achieve that goal: Chilean policy makers should consider local sources of air pollution in the most polluted municipalities; Government decision makers should make extra efforts to listen to the community and improve access to environmental information; Environmental justice advocates should involve stakeholders from the social justice movement and other related areas; Policy makers should track progress towards environmental justice by evaluating differences in health outcomes related to differential exposure to air pollution in different parts of the Santiago metropolitan area.</p>

Using Google Trends to Identify Seasonal Variation in Foot and Ankle Pathology

2021 ◽  
Vol 111 (4) ◽  
Author(s):  
Jana Olivova ◽  
Bibi N. Singh ◽  
Dominick J. Casciato
Keyword(s):  
Seasonal Variation ◽  
Temporal Trends ◽  
Winter Season ◽  
Google Trends ◽  
Volume Index ◽  
Rank Test ◽  
Trend Test ◽  
Foot Pain ◽  
Search Volume ◽  
Significant Difference

Background Google Trends proves to be a novel tool to ascertain the level of public interest in pathology and treatments. From anticipating nascent epidemics with data-driven prevention campaigns to identifying interest in cosmetic or bariatric surgery, Google Trends provides physicians real-time insight into the latest consumer trends. Methods We used Google Trends to identify temporal trends and variation in the search volume index of four groups of keywords that assessed practitioner-nomenclature inquiries, in addition to podiatric-specific searches for pain, traumatic injury, and common podiatric pathology over a 10-year period. The Mann-Kendall trend test was used to determine a trend in the series, and the Wilcoxon signed-rank test was used to determine whether there was a significant difference between summer and winter season inquiries. Significance was set at P ≤ .05. Results The terms “podiatrist” and “foot doctor” experienced increasing Search Volume Index (SVI) and seasonal variation, whereas the terms “foot surgeon” and “podiatric surgeon” experienced no such increase. “Foot pain,” “heel pain,” “toe pain,” and “ankle pain” experienced a significant increase in SVI, with “foot pain” maintaining the highest SVI at all times. Similar results were seen with the terms “foot fractures,” “bunion,” “ingrown toenail,” and “heel spur.” These terms all experienced statistically significant increasing trends; moreover, the SVI was significantly higher in the summer than in the winter for each of these terms. Conclusions The results of this study show the utility in illustrating seasonal variation in Internet interest of pathologies today's podiatrist commonly encounters. By identifying the popularity and seasonal variation of practitioner- and pathology-specific search inquiries, resources can be allocated to effectively address current public inquiries. With this knowledge, providers can learn what podiatric-specific interests are trending in their local communities and market their practice accordingly throughout the year.

scholarly journals Impacts of the COVID-19 lockdown on air quality and its association with human mortality trends in megapolis Mexico City

2020 ◽  
Author(s):  
Gurusamy Kutralam-Muniasamy ◽  
Fermín Pérez-Guevara ◽  
Priyadarsi D. Roy ◽  
I. Elizalde-Martínez ◽  
V.C. Shruti
Keyword(s):  
Air Pollution ◽  
Latin America ◽  
Air Quality ◽  
Mexico City ◽  
Air Pollutants ◽  
Mortality Rates ◽  
Quality Data ◽  
Mortality Trends ◽  
Human Mortality ◽  
Air Quality Data

Abstract Mexico City is the second most populated city in Latin America, and it went through two partial lockdowns between April 1 and May 31, 2020 for reducing the COVID-19 propagation. The present study assessed air quality and its association with human mortality rates during the lockdown by estimating changes observed in air pollutants (CO, NO2, O3, SO2, PM10 and PM2.5) between the lockdown (April 1 - May 31) and pre-lockdown (January 1 – March 31) periods, as well as by comparing the air quality data of lockdown period with the same interval of previous five-years (2015-2019). Concentrations of NO2 (-29%), SO2 (-55%) and PM10 (-11%) declined and the contents of CO (+1.1%), PM2.5 (+19%) and O3 (+63%) increased during the lockdown compared to the pre-lockdown period. This study also estimated that NO2, SO2, CO, PM10 and PM2.5 reduced by 19-36%, and O3 enhanced by 14% compared to the average of 2015-2019. Reduction in traffic as well as less emission from vehicle exhausts led to remarkable decline in NO2, SO2 and PM10. The significant positive associations of PM2.5, CO and O3 with the numbers of COVID-19 infections and deaths, however, underscored the necessity to enforce air pollution regulations to protect human health in one of the important cities of the northern hemisphere.

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