Modelled air pollution levels versus EC air quality legislation - results from high resolution simulation

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.

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High resolution modelling of aerosol dispersion regimes during the CAPITOUL field experiment: from regional to local scale interactions

Atmospheric Chemistry and Physics ◽

10.5194/acp-11-7547-2011 ◽

2011 ◽

Vol 11 (15) ◽

pp. 7547-7560 ◽

Cited By ~ 4

Author(s):

B. Aouizerats ◽

P. Tulet ◽

G. Pigeon ◽

V. Masson ◽

L. Gomes

Keyword(s):

Air Quality ◽

High Resolution ◽

Field Experiment ◽

Aerosol Particle ◽

Pollutant Dispersion ◽

Local Scale ◽

Plume Dispersion ◽

Urban Dynamics ◽

The Impact ◽

Resolution Simulation

Abstract. High resolution simulation of complex aerosol particle evolution and gaseous chemistry over an atmospheric urban area is of great interest for understanding air quality and processes. In this context, the CAPITOUL (Canopy and Aerosol Particle Interactions in the Toulouse Urban Layer) field experiment aims at a better understanding of the interactions between the urban dynamics and the aerosol plumes. During a two-day Intensive Observational Period, a numerical model experiment was set up to reproduce the spatial distribution of specific particle pollutants, from the regional scales and the interactions between different cities, to the local scales with specific turbulent structures. Observations show that local dynamics depends on the day-regime, and may lead to different mesoscale dynamical structures. This study focuses on reproducing these fine scale dynamical structures, and investigate the impact on the aerosol plume dispersion. The 500-m resolution simulation manages to reproduce convective rolls at local scale, which concentrate most of the aerosol particles and can locally affect the pollutant dispersion and air quality.

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Air Pollution and Seasonality Effects on Mode Choice in China

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2634-15 ◽

2017 ◽

Vol 2634 (1) ◽

pp. 101-109 ◽

Cited By ~ 6

Author(s):

Weibo Li ◽

Maria Kamargianni

Keyword(s):

Air Pollution ◽

Developing Countries ◽

Air Quality ◽

Positive Impact ◽

Mode Choice ◽

Urban Transport ◽

Modal Shift ◽

Pollution Levels ◽

Study Results ◽

The Impact

A modal shift from motorized to nonmotorized vehicles is imperative to reduce air pollution in developing countries. Nevertheless, whether better air quality will improve the willingness to use nonmotorized transport remains unclear. If such a reciprocal effect could be identified, a sort of virtuous circle could be created (i.e., better air quality could result in higher nonmotorized transport demand, which in turn could further reduce air pollution). Developing countries may, therefore, be more incentivized to work on air pollution reduction from other sources to exploit the extra gains in urban transport. This study investigated the impact of air pollution on mode choices and whether nonmotorized transport was preferred when air quality was better. Revealed preference data about the mode choice behavior of the same individuals was collected during two seasons (summer and winter) with different air pollution levels. Two discrete mode choice models were developed (one for each season) to quantify and compare the impacts of different air pollution levels on mode choices. Trip and socioeconomic characteristics also were included in the model to identify changes in their impacts across seasons. Taiyuan, a Chinese city that operates a successful bikesharing scheme, was selected for a case study. The study results showed that air quality improvement had a significant, positive impact on nonmotorized transport use, which suggested that improvements in air quality and promotion of nonmotorized transport must be undertaken simultaneously because of their interdependence. The results of the study could act as a harbinger to policy makers and encourage them to design measures and policies that lead to sustainable travel behavior.

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Reduced Middle East Air Pollution Linked to Societal Disruption

Eos ◽

10.1029/2015eo034647 ◽

2015 ◽

Vol 96 ◽

Author(s):

JoAnna Wendel

Keyword(s):

Air Pollution ◽

Air Quality ◽

High Resolution ◽

Middle East ◽

Satellite Data ◽

Armed Conflict ◽

Economic Distress ◽

The Individual

Invasions, armed conflict, sanctions, and economic distress correlate with cleaner air in high-resolution satellite data that reveal air quality at the individual city level.

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Research on an Iot Based Air Pollution Monitoring System

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.i1116.0789s219 ◽

2019 ◽

Vol 8 (9S2) ◽

pp. 553-558

Keyword(s):

Air Pollution ◽

Air Quality ◽

Quality Index ◽

Life Forms ◽

Pollution Monitoring ◽

Wireless Sensor ◽

Pollution Level ◽

Air Pollution Monitoring ◽

Pollution Levels ◽

Different Sources

Humankind, moving to a period centered upon improvement has overlooked the significance of supportability and has been the real guilty party behind the rising Pollution levels in the world's air among all other living life forms. The Pollution levels at certain spots have come to such high degrees that they have begun hurting our very own It will being. An IoT based Air Pollution observing framework incorporates a MQ Series sensor interfaced to a Node MCU outfitted with an ESP8266 WLAN connector to send the sensor perusing to a Thing Speak cloud. Further extent of this work incorporates an appropriate AI model to foresee the air Pollution level and an anticipating model, which is fundamentally a subset of prescient displaying. As age of poisonous gases from ventures, vehicles and different sources is immensely expanding step by step, it winds up hard to control the dangerous gases from dirtying the unadulterated air. In this paper a practical air Pollution observing framework is proposed. This framework can be utilized for observing Pollutions in demeanor of specific territory and to discover the air peculiarity or property examination. The obligated framework will concentrate on the checking of air poisons concentrate with the assistance of mix of Internet of things with wireless sensor systems. The investigation of air quality should be possible by figuring air quality index (AQI)

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

10.21203/rs.3.rs-234681/v1 ◽

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.

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Visualization of uncertainty in air quality ensemble forecasts

10.5194/egusphere-egu21-15612 ◽

2021 ◽

Author(s):

Angelika Heil ◽

Augustin Colette

Keyword(s):

Air Pollution ◽

Time Series ◽

Air Quality ◽

Mobile Apps ◽

Predictive Performance ◽

User Preferences ◽

Ensemble Forecasts ◽

The Public ◽

Pollution Levels ◽

Wide Range

<p>Air quality forecasts help decision-makers to respond to air pollution episodes and to improve air quality management. In recent years, the public increasingly uses mobile apps to check forecasted air pollution levels and then adjusts outdoor activities accordingly. For Europe, state-of-the-art daily air quality forecasts are provided by the regional Copernicus Atmosphere Monitoring System (CAMS). The system integrates forecasts from 9 individual models. This ensemble approach not only achieves better predictive performance compared to a single model, but also allows a better quantification of forecast uncertainty. How to best communicate this uncertainty to a broad audience is by no means a trivial task, but yet essential to maintain trust in the forecasts.</p><p>We developed innovative visualizations to convey CAMS forecast uncertainties in time series and maps. The development is strongly user-driven and involves iterative consultation with a wide range of expert and non-expert users. We investigate the feasibility of different bivariate techniques to communicate the ensemble's best estimate and its uncertainty in a single map. We explore user preferences for a variety of time-series graphs, including boxplots, violinplots, and fancharts. Whilst preferences are largely driven by the data and visualization literacy of the users, we identify some generally valid best practices in terms of graph types, choices of colors and labels, and accompanying textual explanations. Finally, we present our candidate designs for the public display of air quality forecasts on the regional CAMS webpage.</p>

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A very high-resolution assessment and modelling of urban air quality

10.5194/acp-2019-294 ◽

2019 ◽

Author(s):

Tobias Wolf ◽

Lasse H. Pettersson ◽

Igor Esau

Keyword(s):

Air Pollution ◽

Air Quality ◽

High Resolution ◽

Landscape Heterogeneity ◽

Urban Air Quality ◽

City Centre ◽

Urban Air ◽

Large Eddy Simulation Model ◽

The City ◽

Very High

Abstract. Urban air quality is one of the most prominent environmental concerns for a modern city dweller. Accurate monitoring of air quality is difficult due to intrinsic urban landscape heterogeneity and superposition of multiple polluting sources. Existing approaches often do not provide the necessary spatial details and peak concentrations of pollutants, especially at larger distances from measuring stations. A more advanced approach is needed. This study presents a very high-resolution air quality assessment with the large-eddy simulation model PALM. This fully three-dimensional primitive-equation hydro-dynamical model resolves both structural details of the complex urban surface and turbulent eddies larger than 10 m in size. We ran a set of 9 meteorological scenarios in order to assess the dispersion of pollutants in Bergen, a middle-sized Norwegian city embedded in a coastal valley. This set of scenarios represents typically observed conditions with high air pollution from nitrogen dioxide (NO2) and particulate matter (PM2.5). The modelling methodology helped to identify pathways and patterns of air pollution caused by the three main local air pollution sources in the city. These are road vehicle traffic, domestic house heating with wood-burning fireplaces and ships docked in the harbour area next to the city centre. The study produced vulnerability maps, highlighting the most impacted districts for each scenario.

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Analysis of air pollution caused by mass transportation design changes

MATEC Web of Conferences ◽

10.1051/matecconf/201819504021 ◽

2018 ◽

Vol 195 ◽

pp. 04021

Author(s):

Budiman Napitupulu ◽

Ismiyati Ismiyati ◽

Mudjiastuti Handajani

Keyword(s):

Air Pollution ◽

Air Quality ◽

Public Transportation ◽

Simulation Method ◽

Degree Of Saturation ◽

Traffic Jam ◽

Pollution Levels ◽

Urban Quality Of Life ◽

Mass Public ◽

Design Changes

Traffic jams are a common phenomenon in Indonesia’s big cities due to the proliferation of private vehicles. The resulting air pollution directly threatens public health and urban quality of life. This research is to identify and analyze air pollution levels and forecast the potential to improve air quality by developing mass public transportation. This research employs the dust sampler method to measure the air pollution levels and calculate traffic volume, while the simulation method is used to analyze the data. The results show that the air pollution levels detected exceed the air quality thresholds established by regulations in the Decision by the Minister of Health and Environment. Traffic jam levels indicated by the Degree of Saturation (SD) were determined to be, on average, > 0.75. The simulation results show that by changing modes of transportation traffic jam levels decrease, ranging from 0.2201 to 0.291(DS), and air pollution decreases. Specifically, nitrogen oxides (NOx) are reduced by 48.19 %; sulfur dioxide (SO2) is reduced by 51.77 %; particulate matter (PM) is reduced by 29.86%; lead (Pb) is reduced by 52.22%; and carbon monoxide (CO) is reduced by 52.15%. This research suggests the mass public transportation planning should be implemented.

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