Advances on urban air quality modeling: bias correction approach for estimated annual NO2 levels and macroscopic traffic simulators for scenario planning

2021 ◽  
Author(s):  
Jan Mateu Armengol ◽  
Daniel Rodriguez-Rey ◽  
Jaime Benavides ◽  
Oriol Jorba ◽  
Marc Guevara ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Traffic Flow ◽  
Bias Correction ◽  
Scenario Planning ◽  
Urban Air Quality ◽  
Pollutant Emission ◽  
Urban Air ◽  
Air Quality Forecast ◽  
Modelling System

<p>Awareness of air pollution impacts on public health is quickly increasing, especially in urban areas where legal air quality (AQ) limits are often exceeded. This awareness has driven policymakers to minimize citizens' exposure not only by direct legislative control in emissions (i.e., the application of a Low Emission Zone), but also by applying mobility restrictions to modify traffic patterns, and by the use of forecasted warnings to alert citizens of air pollution episodes. The European AQ directives encourage the use of numerical models to support the design and evaluation of such strategies.</p><p>In this framework, we present a versatile AQ model, CALIOPE-Urban (Benavides et al., 2019), able to address the threefold objectives to (i) compute urban air quality forecast at the street-scale resolution; (ii) to perform reanalysis studies of historical periods using a bias correction methodology that preserves the model spatial variability; and (iii) to simulate the traffic flow response to the application of different traffic restrictions and their effect on urban AQ.</p><p>In this contribution, we discuss two specific applications. On the one hand, CALIOPE-Urban is used to estimate the NO2 levels in the city of Barcelona (Spain) during the entire year of 2019. To do so, we report accurate maps of NO2 levels during the whole year by consistently integrating the AQ model data with publicly available observations from the official monitoring network in Catalonia (XVPCA) available in Barcelona by means of a bias correction method. On the other hand, the macroscopic traffic simulator BCN-VML (Rodriguez-Rey et al. 2021) coupled with CALIOPE-Urban is used to assess the AQ impact of the traffic flow-induced changes after the application of a traffic restriction policy. </p><p><strong>References</strong></p><p>Benavides, J., Snyder, M., Guevara, M., Soret, A., Pérez García-Pando, C., Amato, F., Querol, X., and Jorba, O.: CALIOPE-Urban v1.0: coupling R-LINE with a mesoscale air quality modelling system for urban air quality forecasts over Barcelona city (Spain), Geosci. Model Dev., 12, 2811–2835, https://doi.org/10.5194/gmd-12-2811-2019, 2019.</p><p>Rodriguez-Rey, D., Guevara, M., Linares, MP., Casanovas, J., Salmerón, J., Soret, A., Jorba, O., Tena, C., Pérez García-Pando, C.: A coupled macroscopic traffic and pollutant emission modelling system for Barcelona, Transportation Research Part D, accepted for publication.</p>

Assessing the impact of the New Athens airport to urban air quality with contemporary air pollution models

1997 ◽  
Vol 31 (10) ◽  
pp. 1497-1511 ◽  
Author(s):  
N. Moussiopoulos ◽  
P. Sahm ◽  
K. Karatzas ◽  
S. Papalexiou ◽  
A. Karagiannidis
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Air Quality ◽  
Urban Air ◽  
The Impact ◽  
Air Pollution Models

Residents’ preferred measures and willingness-to-pay for improving urban air quality: A case study of Hanoi city, Vietnam

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Thanh Cong Nguyen ◽  
Hang Dieu Nguyen ◽  
Hoa Thu Le ◽  
Shinji Kaneko
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Willingness To Pay ◽  
Public Transportation ◽  
Online Survey ◽  
Urban Air Quality ◽  
Multivariate Probit ◽  
Urban Air ◽  
Content Type ◽  
Public Opinions

PurposeThis purpose of this paper is to understand residents’ choice of preferred measures and their willingness-to-pay (WTP) for the measures to improve the air quality of Hanoi city.Design/methodology/approachQuestionnaire surveys were conducted to collect the opinions of 212 household representatives living in Hanoi City. The survey tools were tested and adjusted through an online survey with 191 responses. Multivariate probit and linear regression models were used to identify determinants of respondents’ choices of measures and their WTP.FindingsRespondents expressed their strong preferences for three measures for air quality improvements, including: (1) increase of green spaces; (2) use of less polluting fuels; (3) expansion of public transportation. The mean WTP for the implementation of those measures was estimated at about 148,000–282,000 Vietnamese dong, equivalent to 0.09–0.16% of household income. The respondents’ choices appear to be consistent with their characteristics and needs, such as financial affordability, time on roads and their perceived impacts of air pollution. The WTP estimates increase with perception of air pollution impacts, time on roads, education and income; but are lower for older people.Originality/valueTo gain a better understanding of public opinions, we applied multivariate probit models to check whether respondents’ choices were consistent with their characteristics and perceptions. This appears to be the first attempt to test the validity of public opinions on choices of measures for improving urban air quality in Vietnam. Our WTP estimates also contribute to the database on the values of improved air quality in the developing world.

scholarly journals Assessment of urban air quality in China using air pollution indices (APIs)

2012 ◽  
Vol 63 (2) ◽  
pp. 170-178 ◽  
Author(s):  
Litao Wang ◽  
Pu Zhang ◽  
Shaobo Tan ◽  
Xiujuan Zhao ◽  
Dandan Cheng ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Air Quality ◽  
Pollution Indices ◽  
Urban Air

scholarly journals Determining the PM10 and PM2.5 Concentrations in Prayagraj City due to Solid Waste Burning using AERMOD

2021 ◽  
Vol 9 (8) ◽  
pp. 2840-2845
Author(s):  
Abhijeet Singh
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Municipal Solid Waste ◽  
Solid Waste ◽  
Uttar Pradesh ◽  
Urban Air Quality ◽  
Air Pollutant ◽  
Urban Air ◽  
Pollutant Concentrations ◽  
Waste Burning

Abstract: Open burning of municipal solid waste (MSW) is a poorly-characterized and frequently-underestimated source of air pollution in developing countries. This paper estimates the air pollution happening from MSW burning in municipality areas of the Prayagraj, Uttar Pradesh, India. Air quality models (AQMs) are critical components for urban air quality management because they can predict and forecast air pollutant concentrations. Advanced AQM, such as AERMOD, has a well-established application in the developed world provided sufficient input data is available. However, in poor countries, it is limited due to a lack of adequate and trustworthy data. The present study is focused to assess the urban air quality due to municipal solid waste burning around a Sangam city Prayagraj in India using dispersion modelling. Keywords: PM10, PM2.5, Air Quality Modelling, AERMOD

scholarly journals High-resolution mapping of urban air quality with heterogeneous observations: a new methodology and its application to Amsterdam

2019 ◽  
Author(s):  
Bas Mijling
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Low Cost ◽  
Urban Air Pollution ◽  
Heterogeneous Data ◽  
Urban Air Quality ◽  
Quality Data ◽  
Urban Air ◽  
Reference Measurements ◽  
Concentration Patterns

Abstract. In many cities around the world people are exposed to elevated levels of air pollution. Often local air quality is not well known due to the sparseness of official monitoring networks, or unrealistic assumptions being made in urban air quality models. Low-cost sensor technology, which has become available in recent years, has the potential to provide complementary information. Unfortunately, an integrated interpretation of urban air pollution based on different sources is not straightforward because of the localized nature of air pollution, and the large uncertainties associated with measurements of low-cost sensors. In this study, we present a practical approach to producing high spatio-temporal resolution maps of urban air pollution capable of assimilating air quality data from heterogeneous data streams. It offers a two-step solution: (1) building a versatile air quality model, driven by an open source atmospheric dispersion model and emission proxies from open data sources, and (2) a practical spatial interpolation scheme, capable of assimilating observations with different accuracies. The methodology, called Retina, has been applied and evaluated for nitrogen dioxide (NO2) in Amsterdam, the Netherlands, during the summer of 2016. The assimilation of reference measurements results in hourly maps with a typical accuracy of 39 % within 2 km of an observation location, and 53 % at larger distances. When low-cost measurements of the Urban AirQ campaign are included, the maps reveal more detailed concentration patterns in areas which are undersampled by the official network. During the summer holiday period, NO2 concentrations drop about 10 % due to reduced urban activity. The reduction is less in the historic city center, while strongest reductions are found around the access ways to the tunnel connecting the northern and the southern part of the city, which was closed for maintenance. The changing concentration patterns indicate how traffic flow is redirected to other main roads. Overall, we show that Retina can be applied for an enhanced understanding of reference measurements, and as a framework to integrate low-cost measurements next to reference measurements in order to get better localized information in urban areas.

scholarly journals Urban Vegetation in Air Quality Management: A Review and Policy Framework

2020 ◽  
Vol 12 (3) ◽  
pp. 1258 ◽  
Author(s):  
Joanna Badach ◽  
Małgorzata Dymnicka ◽  
Andrzej Baranowski
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Management ◽  
Urban Planning ◽  
Design Guidelines ◽  
Urban Air Quality ◽  
Policy Framework ◽  
Urban Air ◽  
Air Quality Management ◽  
Urban Greenery

Recent episodes of high air pollution concentration levels in many Polish cities indicate the urgent need for policy change and for the integration of various aspects of urban development into a common platform for local air quality management. In this article, the focus was placed on the prospects of improving urban air quality through proper design and protection of vegetation systems within local spatial planning strategies. Recent studies regarding the mitigation of air pollution by urban greenery due to deposition and aerodynamic effects were reviewed, with special attention given to the design guidelines resulting from these studies and their applicability in the process of urban planning. The conclusions drawn from the review were used to conduct three case studies: in Gdańsk, Warsaw, and Poznań, Poland. The existing local urban planning regulations for the management of urban greenery were critically evaluated in relation to the findings of the review. The results indicate that the current knowledge regarding the improvement of urban air quality by vegetation is not applied in the process of urban planning to a sufficient degree. Some recommendations for alternative provisions were discussed.

Analysis of urban air quality in 6 European cities by lower cost sensors, Lagrangian urban dispersion modelling and traffic flow modelling: the TRAFAIR project

2020 ◽  
Author(s):  
Ohad Zivan ◽  
Alessandro Bigi ◽  
Giorgio Veratti ◽  
José Antonio Souto González ◽  
Lorena Marrodán ◽  
...  
Keyword(s):  
Air Quality ◽  
Traffic Flow ◽  
Urban Area ◽  
Lower Cost ◽  
Dispersion Model ◽  
Urban Air Quality ◽  
Urban Air ◽  
Electrochemical Cells ◽  
Dispersion Modelling ◽  
Traffic Data

<p>Most of worldwide population lives in urban areas, demanding for air quality information with a high spatio-temporal resolution. The most promising approaches for estimating urban air quality within the complex urban topography are small sensor networks and simulation models.</p><p>The TRAFAIR project focuses on understanding the role of traffic emissions on urban air quality by the combination of dispersion modelling, space- and time-resolved gas monitoring by lower cost sensors and realistic traffic flow rates by dynamic traffic model based on real time traffic data. Test cities of TRAFAIR are Modena, Florence, Pisa, Livorno, Zaragoza and Santiago de Compostela.</p><p>Depending on the size of the urban area, from 6 to 13 sensors units are deployed across each city since August 2019, providing estimates of NO, NO<sub>2</sub>, CO and O<sub>3</sub>, along with RH and temperature. Metal oxide sensors are deployed in Tuscany (Florence, Pisa, Livorno) and electrochemical cells are used elsewhere. The units are calibrated on a regular basis by co-location at the air quality regulatory stations and subsequently deployed across the town to monitor several representative locations (e.g. Low Emission Zones, hospital surroundings). For each sensor the raw readings (e.g. mV for electrochemical cells) are collected and a regression model (e.g. Random Forest) is applied to derive a calibration function, exploiting the data from the regulatory stations during co-location periods; for instance in Modena, the first short-term calibration provided a model with a Mean Absolute Error between 5 – 6 ppb and 2 – 4 ppb for NO and NO<sub>2</sub> respectively.</p><p>The sensors are used for both real-time urban air quality mapping and to test and validate the 24hr forecast service of NOx by the microscale lagrangian dispersion model GRAL. The simulation domains, covering the urban area of each TRAFAIR city, have a horizontal resolution of 4 m and allow to account for the presence of buildings. The dispersion model mainly focuses on NOx by traffic emissions, although domestic heating will be also included in the analysis. Vehicular emissions are based either upon historical traffic data (e.g. induction loops), or upon previously available traffic flow simulation, or upon traffic pattern reconstruction using a traffic flow model followed by a cluster analysis to group streets with similar pattern.</p><p>The final goal of the project is the development of a tool to support local policymakers and to inform citizenship about the quality of air and the impact of urban emission sources, particularly traffic. A secondary goal of the project is the development of a valuable QA/QC protocol for small sensor units and the optimization of the modelling chain for the forecast of traffic and domestic heating impact on local air quality at the urban scale.</p>

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