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

2020 ◽  
Vol 13 (8) ◽  
pp. 4601-4617
Author(s):  
Bas Mijling
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Low Cost ◽  
Urban Air Pollution ◽  
Urban Air Quality ◽  
Quality Data ◽  
City Centre ◽  
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. This study presents a practical approach to producing high-spatiotemporal-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 (defined as the ratio between the root mean square error and the mean of the observations) 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. It is shown that during the summer holiday period, NO2 concentrations drop about 10 %. The reduction is less in the historic city centre, 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, it is shown 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 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 A very high-resolution assessment and modelling of urban air quality

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.

scholarly journals Integrated systems for forecasting urban meteorology, air pollution and population exposure

2007 ◽  
Vol 7 (3) ◽  
pp. 855-874 ◽  
Author(s):  
A. Baklanov ◽  
O. Hänninen ◽  
L. H. Slørdal ◽  
J. Kukkonen ◽  
N. Bjergene ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Health Effects ◽  
Weather Prediction ◽  
Urban Air Pollution ◽  
Urban Air Quality ◽  
Population Exposure ◽  
Quality Information ◽  
Urban Air ◽  
Initial Development

Abstract. Urban air pollution is associated with significant adverse health effects. Model-based abatement strategies are required and developed for the growing urban populations. In the initial development stage, these are focussed on exceedances of air quality standards caused by high short-term pollutant concentrations. Prediction of health effects and implementation of urban air quality information and abatement systems require accurate forecasting of air pollution episodes and population exposure, including modelling of emissions, meteorology, atmospheric dispersion and chemical reaction of pollutants, population mobility, and indoor-outdoor relationship of the pollutants. In the past, these different areas have been treated separately by different models and even institutions. Progress in computer resources and ensuing improvements in numerical weather prediction, air chemistry, and exposure modelling recently allow a unification and integration of the disjunctive models and approaches. The current work presents a novel approach that integrates the latest developments in meteorological, air quality, and population exposure modelling into Urban Air Quality Information and Forecasting Systems (UAQIFS) in the context of the European Union FUMAPEX project. The suggested integrated strategy is demonstrated for examples of the systems in three Nordic cities: Helsinki and Oslo for assessment and forecasting of urban air pollution and Copenhagen for urban emergency preparedness.

scholarly journals Integrated systems for forecasting urban meteorology, air pollution and population exposure

2006 ◽  
Vol 6 (2) ◽  
pp. 1867-1913 ◽  
Author(s):  
A. Baklanov ◽  
O. Hänninen ◽  
L. H. Slørdal ◽  
J. Kukkonen ◽  
N. Bjergene ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Health Effects ◽  
Weather Prediction ◽  
Urban Air Pollution ◽  
Urban Air Quality ◽  
Population Exposure ◽  
Quality Information ◽  
Urban Air ◽  
Initial Development

Abstract. Urban air pollution is associated with significant adverse health effects. Model-based abatement strategies are required and developed for the growing urban populations. In the initial development stage, these are focussed on exceedances of air quality standards caused by high short-term pollutant concentrations. Prediction of health effects and implementation of urban air quality information and abatement systems require accurate forecasting of air pollution episodes and population exposure, including modelling of emissions, meteorology, atmospheric dispersion and chemical reaction of pollutants, population mobility, and indoor-outdoor relationship of the pollutants. In the past, these different areas have been treated separately by different models and even institutions. Progress in computer resources and ensuing improvements in numerical weather prediction, air chemistry, and exposure modelling recently allow a unification and integration of the disjunctive models and approaches. The current work presents a novel approach that integrates the latest developments in meteorological, air quality, and population exposure modelling into Urban Air Quality Information and Forecasting Systems (UAQIFS) in the context of the European Union FUMAPEX project. The suggested integrated strategy is demonstrated for examples of the systems in three Nordic cities: Helsinki and Oslo for assessment and forecasting of urban air pollution and Copenhagen for urban emergency preparedness.

scholarly journals An Assessment of the Relationship between Urban Air Quality and Environmental Urban Factors in Urban Regeneration Areas

2016 ◽  
Vol 1 (2) ◽  
pp. 171
Author(s):  
Yakup Egercioglu ◽  
Nur Sinem Ozcan
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Environmental Factors ◽  
Urban Air Pollution ◽  
Urban Regeneration ◽  
Urban Air Quality ◽  
Traffic Density ◽  
Urban Air ◽  
Rapid Urbanization ◽  
Planning Decisions

Urban air pollution has been increasing due to ever increasing population, rapid urbanization, industrialization, energy usage, traffic density. The purpose of the study is to examine the relation between urban air quality and urban environmental factors in urban regeneration areas. Two common air polluters (SO2 and PM10) are considered in the study. The data are collected for Cigli district, including the level of air pollutants, the local natural gas service lines and planning decisions for the years between 2007 and 2011. According to the examinations, urban environmental factors and planning decisions affect the urban air quality in urban regeneration areas.© 2016. The Authors. Published for AMER ABRA by e-International Publishing House, Ltd., UK. Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia.Keywords: Urban air pollution; urban regeneration; quality of lif; environmental factors Introduction

From Urban Air Quality Forecasting and Information Systems to Integrated Urban Hydrometeorology, Climate and Environment Systems and Services for Smart Cities

2020 ◽  
Author(s):  
Alexander Baklanov ◽  
Keyword(s):  
Climate Change ◽  
Air Pollution ◽  
Air Quality ◽  
Urban Areas ◽  
Urban Air Pollution ◽  
Urban Air Quality ◽  
Urban Air ◽  
Climate Services ◽  
Urban Weather ◽  
Air Quality Forecasting

<p>This presentation is analysing a modern evolution in research and development from specific urban air quality systems to multi-hazard and integrated urban weather, environment and climate systems and services and provides an overview of joint results of large EU FP FUMAPEX, MEGAPOLI, EuMetChem and MarcoPolo projects and international WMO GURME and IUS teams. </p><p>Urban air pollution is still one of the key environmental issues for many cities around the world. A number of recent and previous international studies have been initiated to explore these issues. In particular relevant experience from several European projects will be demonstrated. MEGAPOLI studies aimed to assess the impacts of megacities and large air-pollution hotspots on local, regional and global air quality; to quantify feedback mechanisms linking megacity air quality, local and regional climates, and global climate change; and to develop improved tools for predicting air pollution levels in megacities (doi:10.5194/asr-4-115-2010). FUMAPEX developed for the first time an integrated system encompassing emissions, urban meteorology and population exposure for urban air pollution episode forecasting, the assessment of urban air quality and health effects, and for emergency preparedness issues for urban areas (UAQIFS: Urban Air Quality Forecasting and Information System; doi.org/10.5194/acp-6-2005-2006; doi.org/10.5194/acp-7-855-2007).</p><p>While important advances have been made, new interdisciplinary research studies are needed to increase our understanding of the interactions between emissions, air quality, and regional and global climates. Studies need to address both basic and applied research and bridge the spatial and temporal scales connecting local emissions, air quality and weather with climate and global atmospheric chemistry. WMO has established the Global Atmosphere Watch (GAW) Urban Research Meteorology and Environment (GURME) project which provides an important research contribution to the integrated urban services.</p><p>Most of the disasters affecting urban areas are of a hydro-meteorological nature and these have increased due to climate change. Cities are also responsible not only for air pollution emissions, but also for generating up to 70% of GHG emissions that drive large scale climate change. Thus, there is a strong feedback between contributions of cities to environmental health, climate change and the impacts of climate change on cities and these phases of the problem should not be considered separately. There is a critical need to consider the problem in a complex manner with interactions of climate change and disaster risk reduction for urban areas (doi:10.1016/j.atmosenv.2015.11.059, doi.org/10.1016/j.uclim.2017.05.004).</p><p>WMO is promoting safe, healthy and resilient cities through the development of Integrated Urban Weather, Environment and Climate Services (IUS). The aim is to build urban services that meet the special needs of cities through a combination of dense observation networks, high-resolution forecasts, multi-hazard early warning systems, disaster management plans and climate services. This approach gives cities the tools they need to reduce emissions, build thriving and resilient communities and implement the UN Sustainable Development Goals. The Guidance on IUS, developed by a WMO inter-programme working group, documents and shares the good practices that will allow countries and cities to improve the resilience of urban areas to a great variety of natural and other hazards (https://library.wmo.int/doc_num.php?explnum_id=9903).</p>

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

2020 ◽  
Vol 20 (2) ◽  
pp. 625-647 ◽  
Author(s):  
Tobias Wolf ◽  
Lasse H. Pettersson ◽  
Igor Esau
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
High Resolution ◽  
Road Traffic ◽  
Urban Air Quality ◽  
City Centre ◽  
Urban Air ◽  
Wood Burning ◽  
The City ◽  
Very High

Abstract. Urban air quality is one of the most prominent environmental concerns for modern city residents and authorities. 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 monitoring stations. A more advanced integrated approach is needed. This study presents a very high-resolution air quality assessment with the Parallelized Large-Eddy Simulation Model (PALM), capitalising on local measurements. This fully three-dimensional primitive-equation hydrodynamical model resolves both structural details of the complex urban surface and turbulent eddies larger than 10 m in size. We ran a set of 27 meteorological weather 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 weather 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 weather and emission scenario. Overall, the largest contribution to air pollution over inhabited areas in Bergen was caused by road traffic emissions for NO2 and wood-burning fireplaces for PM2.5 pollution. The effect of emission from ships in the port was mostly restricted to the areas close to the harbour and moderate in comparison. However, the results have contributed to implementation of measures to reduce emissions from ships in Bergen harbour, including provision of shore power.

scholarly journals The influence of meteorology and air quality on parkrun athletic performance

2020 ◽  
Author(s):  
James Robert Hodgson ◽  
Stephanie Elliott ◽  
Lee Chapman ◽  
Chris Hudson ◽  
Francis D Pope
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Relative Humidity ◽  
Athletic Performance ◽  
General Public ◽  
Urban Air Pollution ◽  
Quality Data ◽  
Urban Air ◽  
Wind Speeds ◽  
Healthy Activity

Abstract Background Despite increased awareness of climate change and urban air pollution, little research has been performed to examine the influence of meteorology and air quality on athletic performance of the general public and recreational exercisers. Anecdotal evidence of increased temperatures and wind speeds as well as higher relative humidity conditions resulting in reduced athletic performance has been presented in the past, whilst urban air pollution can have negative short- and long-term impacts on health. Furthermore, pollutants such as Ozone, Nitrogen Dioxide and Particulate Matter can cause respiratory and cardiovascular distress, which can be heightened during physical activity. Previous research has examined these impacts on marathon runners, or have been performed in laboratory settings. Instead, this paper focuses on the potential impacts on the general public. With the rise of parkrun events (timed 5 km runs) across the UK and worldwide concerns regarding public health in relation to both air quality and activity levels, the potential influence of air quality and meteorology on what is viewed as a ‘healthy’ activity has been investigated. A weekly dataset of parkrun participants at fifteen events, located in London UK, from 2011–2016 alongside local meteorological and air quality data has been analysed. Results The biggest influencer on athletic performance is meteorology, particularly temperature and wind speed. Regression results between parkrun finishing times and temperature predominantly show positive relationships, supporting previous laboratory tests. Increased relative humidity also causes slower finishing times but in several cases is not statistically significant. Higher wind speeds also result in slower times and in contrast to temperature and relative humidity, male participants are more influenced than female by this variable. Although air quality does influence athletic performance to an extent, the heterogeneity of pollutants within London and between parkrun events and monitoring sites makes this difficult to prove decisively. Conclusions It has been determined that temperature and relative humidity can have the largest detrimental impact on parkrun performance, with Ozone also having an impact. The influence of other variables cannot be discounted however and it is recommended that modelling is performed to further determine the extent to which ‘at event’ meteorology and air quality has on performance. In the future, there results can be used to determine safe operating and exercise conditions for parkrun and other public athletics events.

scholarly journals Meta-modeling of a simulation chain for urban air quality

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
J. K. Hammond ◽  
R. Chen ◽  
V. Mallet
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Road Traffic ◽  
Low Cost ◽  
Urban Air Quality ◽  
Multiple Models ◽  
Urban Air ◽  
Dynamic Traffic ◽  
Reduced Basis ◽  
Meta Modeling

Abstract Urban air quality simulation is an important tool to understand the impacts of air pollution. However, the simulations are often computationally expensive, and require extensive data on pollutant sources. Data on road traffic pollution, often the predominant source, can be obtained through sparse measurements, or through simulation of traffic and emissions. Modeling chains combine the simulations of multiple models to provide the most accurate representation possible, however the need to solve multiple models for each simulation increases computational costs even more. In this paper we construct a meta-modeling chain for urban atmospheric pollution, from dynamic traffic modeling to air pollution modeling. Reduced basis methods (RBM) aim to compute a cheap and accurate approximation of a physical state using approximation spaces made of a suitable sample of solutions to the model. One of the keys of these techniques is the decomposition of the computational work into an expensive one-time offline stage and a low-cost parameter-dependent online stage. Traditional RBMs require modifying the assembly routines of the computational code, an intrusive procedure which may be impossible in cases of operational model codes. We propose a non-intrusive reduced order scheme, and study its application to a full chain of operational models. Reduced basis are constructed using principal component analysis (PCA), and the concentration fields are approximated as projections onto this reduced space. We use statistical emulation to approximate projection coefficients in a non-intrusive manner. We apply a multi-level meta-modeling technique to a chain using the dynamic traffic assignment model LADTA, the emissions database COPERT IV, and the urban dispersion-reaction air quality model SIRANE to a case study on the city of Clermont-Ferrand with over 45, 000 daily traffic observations, a 47, 000-link road network, a simulation domain covering $$180\,\text {km}^2$$ 180 km 2 . We assess the results using hourly NO$$_2$$ 2 concentration observations measured at stations in the agglomeration. Computational times are reduced from nearly 3 h per simulation to under 0.1 s, while maintaining accuracy comparable to the original models. The low cost of the meta-model chain and its non-intrusive character demonstrate the versatility of the method, and the utility for long-term or many-query air quality studies such as epidemiological inquiry or uncertainty quantification.

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