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Air Pollution Modelling: Local-, Regional-, and Global-Scale Application

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A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: closed (20 December 2019) | Viewed by 36384

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Special Issue Editor

Dr. Syuichi Itahashi

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Guest Editor

Sustainable System Research Laboratory (SSRL), Central Research Institute of Electric Power Industry (CRIEPI), Abiko 2701194, Japan
Interests: numerical modeling simulation; air pollution; deposition
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Air pollution problem is inevitably accompanied to our human activities. Severe air pollution situations have been reported especially in emerging countries, and satisfying the air quality standards fully have been still underlying issues. Today, modeling researches is one of the valuable approaches to promote our understanding on the behavior of air pollutants and to be used as regulatory, policy, and environmental decision makings. Such a modeling application range with regard to horizontal grid resolution varied from a few km (local) to hundreds of km (regional) to thousands of km (global).

To foster our current scientific knowledge on modeling potentialities and limitations, we would like to call scientific papers related to air pollution modeling applied for urban-, regional-, and global-scale on this special issue in the journal of Atmosphere. By collecting devoted papers, this theme seeks the future strategies for modeling researches across multi-scales. Modeling is not limited on the Eulerian and Lagrangian models, and other modeling techniques (e.g., box model, receptor model) are welcome. The online-coupled chemical transport model integrated with meteorological model will also contribute to this special issue. This topic would represent a notable contribution to this important scientific field.

Dr. Syuichi Itahashi
Guest Editor

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Keywords

Eulerian model
Lagrangian model
box model
receptor model
local air pollution
long-range transport

Published Papers (10 papers)

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Editorial

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3 pages, 161 KiB

Open AccessEditorial

Air Pollution Modeling: Local, Regional, and Global-Scale Applications

by Syuichi Itahashi

Atmosphere 2021, 12(2), 178; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12020178 - 29 Jan 2021

Cited by 3 | Viewed by 1731

Abstract

The Atmosphere Special Issue entitled “Air Pollution Modeling: Local, Regional, and Global-Scale Applications” comprises nine original papers [...] Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

Research

Jump to: Editorial

18 pages, 5483 KiB

Open AccessArticle

WRF-Chem Simulation of Winter Visibility in Jiangsu, China, and the Application of a Neural Network Algorithm

by Peishu Zong, Yali Zhu, Huijun Wang and Duanyang Liu

Atmosphere 2020, 11(5), 520; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11050520 - 18 May 2020

Cited by 7 | Viewed by 4360

Abstract

In this paper, the winter visibility in Jiangsu Province is simulated by WRF-Chem (Weather Research and Forecasting (WRF) model coupled with Chemistry) with high spatiotemporal resolutions. Simulation results show that WRF-Chem has good capability to simulate the visibility and related local meteorological elements and air pollutants in Jiangsu in the winters of 2013–2017. For visibility inversion, this study adopts the neural network algorithm. Meteorological elements, including wind speed, humidity and temperature, are introduced to improve the performance of WRF-Chem relative to the visibility inversion scheme, which is based on the Interagency Monitoring of Protected Visual Environments (IMPROVE) extinction coefficient algorithm. The neural network offers a noticeable improvement relative to the inversion scheme of the IMPROVE visibility extinction coefficient, substantially improving the underestimation of winter visibility in Jiangsu Province. For instance, the correlation coefficient increased from 0.17 to 0.42, and root mean square error decreased from 2.62 to 1.76. The visibility inversion results under different humidity and wind speed levels show that the underestimation of the visibility using the IMPROVE scheme is especially remarkable. However, the underestimation issue is essentially solved using the neural network algorithm. This study serves as a basis for further predicting winter haze events in Jiangsu Province using WRF-Chem and deep-learning methods. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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25 pages, 6628 KiB

Open AccessEditor’s ChoiceArticle

Model Inter-Comparison for PM_2.5 Components over urban Areas in Japan in the J-STREAM Framework

by Kazuyo Yamaji, Satoru Chatani, Syuichi Itahashi, Masahiko Saito, Masayuki Takigawa, Tazuko Morikawa, Isao Kanda, Yukako Miya, Hiroaki Komatsu, Tatsuya Sakurai, Yu Morino, Kyo Kitayama, Tatsuya Nagashima, Hikari Shimadera, Katsushige Uranishi, Yuzuru Fujiwara, Tomoaki Hashimoto, Kengo Sudo, Takeshi Misaki and Hiroshi Hayami

Atmosphere 2020, 11(3), 222; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11030222 - 25 Feb 2020

Cited by 14 | Viewed by 4104

Abstract

A model inter-comparison of secondary pollutant simulations over urban areas in Japan, the first phase of Japan’s study for reference air quality modeling (J-STREAM Phase I), was conducted using 32 model settings. Simulated hourly concentrations of nitric oxide (NO) and nitrogen dioxide (NO₂), which are primary pollutant precursors of particulate matter with a diameter of 2.5 µm or less (PM_2.5), showed good agreement with the observed concentrations, but most of the simulated hourly sulfur oxide (SO₂) concentrations were much higher than the observations. Simulated concentrations of PM_2.5 and its components were compared to daily observed concentrations by using the filter pack method at selected ambient air pollution monitoring stations (AAPMSs) for each season. In general, most models showed good agreement with the observed total PM_2.5 mass concentration levels in each season and provided goal or criteria levels of model ensemble statistics in warmer seasons. The good performances of these models were associated with the simulated reproducibility of some dominant components, sulfates (SO₄²⁻) and ammonium (NH₄⁺). The other simulated PM_2.5 components, i.e., nitrates (NO₃⁻), elemental carbon (EC), and organic carbon (OC), often show clear deviations from the observations. The considerable underestimations (approximately 30 µg/m³ for total PM_2.5) of all participant models found on heavily polluted days with approximately 40–50 µg/m³ for total PM_2.5 indicated some problems in the simulated local meteorology such as the atmospheric stability. This model inter-comparison suggests that these deviations may be owing to a need for further improvements both in the emission inventories and additional formation pathways in chemical transport models, and meteorological conditions also require improvement to simulate elevated atmospheric pollutants. Additional accumulated observations are likely needed to further evaluate the simulated concentrations and improve the model performance. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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13 pages, 5928 KiB

Open AccessArticle

Impacts of Biomass Burning Emission Inventories and Atmospheric Reanalyses on Simulated PM₁₀ over Indochina

by Kyohei Takami, Hikari Shimadera, Katsushige Uranishi and Akira Kondo

Atmosphere 2020, 11(2), 160; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11020160 - 04 Feb 2020

Cited by 18 | Viewed by 3158

Abstract

Biomass burning (BB) is a major source of atmospheric particles over Indochina during the dry season. Moreover, Indochina has convoluted meteorological scales, and regional meteorological conditions dominate the transport patterns of pollutants. This study focused on the impacts of BB emission inventories and atmospheric reanalyses on simulated PM₁₀ over Indochina in 2014 using the Community Multiscale Air Quality (CMAQ) model. Meteorological fields to input to CMAQ were produced by using the Weather Research and Forecasting (WRF) model simulation with the United States National Centers for Environmental Prediction Final (NCEP FNL) Operational Global Analysis or European Centre for Medium Range Weather Forecasts Interim Reanalysis (ERA-interim). The Fire INventory from NCAR (FINN) v1.5 or the Global Fire Emissions Database including small fires (GFED v4.1s) was selected for BB emissions for the air quality simulation. The simulation case with NCEP FNL and FINN v1.5 (FNL + FINN) performed best throughout 2014, including the season when BB activities were intensified. The normalized percentage difference for maximum daily mean PM₁₀ concentrations at Chiang Mai for FNL + FINN and the two simulation cases applying GFED v4.1s for BB emissions (−53% to −27%) was much larger than that between the FNL + FINN and ERA + FINN cases (10%). BB emission inventories more strongly impacted PM₁₀ simulation than atmospheric reanalyses in highly polluted areas by BB over Indochina in 2014. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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23 pages, 27805 KiB

Open AccessArticle

RePLaT-Chaos: A Simple Educational Application to Discover the Chaotic Nature of Atmospheric Advection

by Tímea Haszpra

Atmosphere 2020, 11(1), 29; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11010029 - 27 Dec 2019

Cited by 5 | Viewed by 2751

Abstract

Large-scale atmospheric pollutant spreading via volcano eruptions and industrial accidents may have serious effects on our life. However, many students and non-experts are generally not aware of the fact that pollutant clouds do not disperse in the atmosphere like dye blobs on clothes. Rather, an initially compact pollutant cloud soon becomes strongly stretched with filamentary and folded structure. This is the result of the chaotic behaviour of advection of pollutants in 3-D flows, i.e., the advection dynamics of pollutants shows the typical characteristics such as sensitivity to the initial conditions, irregular motion, and complicated but well-organized (fractal) structures. This study presents possible applications of a software called RePLaT-Chaos by means of which the characteristics of the long-range atmospheric spreading of volcanic ash clouds and other pollutants can be investigated in an easy and interactive way. This application is also a suitable tool for studying the chaotic features of the advection and determines two quantities which describe the chaoticity of the advection processes: the stretching rate quantifies the strength of the exponential stretching of pollutant clouds; and the escape rate characterizes the rate of the rapidity by which the settling particles of a pollutant cloud leave the atmosphere. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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13 pages, 1461 KiB

Open AccessArticle

Capturing Plume Rise and Dispersion with a Coupled Large-Eddy Simulation: Case Study of a Prescribed Burn

by Nadya Moisseeva and Roland Stull

Atmosphere 2019, 10(10), 579; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos10100579 - 25 Sep 2019

Cited by 5 | Viewed by 2919

Abstract

Current understanding of the buoyant rise and subsequent dispersion of smoke due to wildfires has been limited by the complexity of interactions between fire behavior and atmospheric conditions, as well as the uncertainty in model evaluation data. To assess the feasibility of using numerical models to address this knowledge gap, we designed a large-eddy simulation of a real-life prescribed burn using a coupled semi-emperical fire–atmosphere model. We used observational data to evaluate the simulated smoke plume, as well as to identify sources of model biases. The results suggest that the rise and dispersion of fire emissions are reasonably captured by the model, subject to accurate surface thermal forcing and relatively steady atmospheric conditions. Overall, encouraging model performance and the high level of detail offered by simulated data may help inform future smoke plume modeling work, plume-rise parameterizations and field experiment designs. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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16 pages, 2756 KiB

Open AccessArticle

Differences in Model Performance and Source Sensitivities for Sulfate Aerosol Resulting from Updates of the Aqueous- and Gas-Phase Oxidation Pathways for a Winter Pollution Episode in Tokyo, Japan

by Syuichi Itahashi, Kazuyo Yamaji, Satoru Chatani and Hiroshi Hayami

Atmosphere 2019, 10(9), 544; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos10090544 - 12 Sep 2019

Cited by 8 | Viewed by 3217

Abstract

During the Japanese intercomparison study, Japan’s Study for Reference Air Quality Modeling (J-STREAM), it was found that wintertime SO₄^2– concentrations were underestimated over Japan with the Community Multiscale Air Quality (CMAQ) modeling system. Previously, following two development phases, model performance was improved by refining the Fe- and Mn-catalyzed oxidation pathways and by including an additional aqueous-phase pathway via NO₂ oxidation. In a third phase, we examined a winter haze period in December 2016, involving a gas-phase oxidation pathway whereby three stabilized Criegee intermediates (SCI) were incorporated into the model. We also included options for a kinetic mass transfer aqueous-phase calculation. According to statistical analysis, simulations compared well with hourly SO₄^2– observations in Tokyo. Source sensitivities for four domestic emission sources (transportation, stationary combustion, fugitive VOC, and agricultural NH₃) were investigated. During the haze period, contributions from other sources (overseas and volcanic emissions) dominated, while domestic sources, including transportation and fuel combustion, played a role in enhancing SO₄^2– concentrations around Tokyo Bay. Updating the aqueous phase metal catalyzed and NO₂ oxidation pathways lead to increase contribution from other sources, and the additional gas phase SCI chemistry provided a link between fugitive VOC emission and SO₄^2– concentration via changes in O₃ concentration. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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14 pages, 7035 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Pollutant Dispersion in a Realistic Urban Street Canyon Using Coupled CFD and Chemical Reaction Modeling

by Franchesca G. Gonzalez Olivardia, Qi Zhang, Tomohito Matsuo, Hikari Shimadera and Akira Kondo

Atmosphere 2019, 10(9), 479; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos10090479 - 21 Aug 2019

Cited by 14 | Viewed by 5739

Abstract

Studies in actual urban settings that integrate chemical reaction modeling, radiation, and particular emissions are mandatory to evaluate the effects of traffic-related air pollution on street canyons. In this paper, airflow patterns and reactive pollutant behavior for over 24 h, in a realistic urban canyon in Osaka City, Japan, was conducted using a computational fluid dynamics (CFD) model coupled with a chemical reaction model (CBM-IV). The boundary conditions for the CFD model were obtained from mesoscale meteorological and air quality models. Inherent street canyon processes, such as ground and wall radiation, were evaluated using a surface energy budget model of the ground and a building envelope model, respectively. The CFD-coupled chemical reaction model surpassed the mesoscale models in describing the NO, NO₂, and O₃ transport process, representing pollutants concentrations more accurately within the street canyon since the latter cannot capture the local phenomena because of coarse grid resolution. This work showed that the concentration of pollutants in the urban canyon is heavily reliant on roadside emissions and airflow patterns, which, in turn, is strongly affected by the heterogeneity of the urban layout. The CFD-coupled chemical reaction model characterized better the complex three-dimensional site and hour-dependent dispersion of contaminants within an urban canyon. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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14 pages, 4273 KiB

Open AccessArticle

Determination of the Area Affected by Agricultural Burning

by Daniel F. Prato and Jose I. Huertas

Atmosphere 2019, 10(6), 312; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos10060312 - 05 Jun 2019

Cited by 7 | Viewed by 3575

Abstract

Agricultural burning is still a common practice around the world. It is associated with the high emission of air pollutants, including short-term climate change forcing pollutants such as black carbon and PM_2.5. The legal requirements to start any regulatory actions to control them is the identification of its area of influence. However, this task is challenging from the experimental and modeling point of view, since it is a short-term event with a moving area source of pollutants. In this work, we assessed this agricultural burning influence-area using the US Environmental authorities recommended air dispersion model (AERMOD). We considered different sizes and geometries of burning areas located on flat terrains, and several crops burning under the worst-case scenario of meteorological conditions. The influence area was determined as the largest area where the short-term concentrations of pollutants (1 h or one day) exceed the local air quality standards. We found that this area is a band around the burning area whose size increases with the burning rate but not with its size. Finally, we suggested alternatives of public policy to regulate this activity, which is based on limiting the burning-rate in the way that no existing households remain inside the resulting influence-area. However, this policy should be understood as a transition towards a policy that forbids agricultural burning. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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20 pages, 4970 KiB

Open AccessArticle

Sensitivity of Nitrate Aerosol Production to Vehicular Emissions in an Urban Street

by Minjoong J. Kim

Atmosphere 2019, 10(4), 212; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos10040212 - 22 Apr 2019

Cited by 12 | Viewed by 3765

Abstract

This study investigated the sensitivity of nitrate aerosols to vehicular emissions in urban streets using a coupled computational fluid dynamics (CFD)–chemistry model. Nitrate concentrations were highest at the street surface level following NH₃ emissions from vehicles, indicating that ammonium nitrate formation occurs under NH₃-limited conditions in street canyons. Sensitivity simulations revealed that the nitrate concentration has no clear relationship with the NO_x emission rate, showing nitrate changes of only 2% across among 16 time differences in NO_x emissions. NO_x emissions show a conflicting effect on nitrate production via decreasing O₃ and increasing NO₂ concentrations under a volatile organic compound (VOC)-limited regime for O₃ production. The sensitivity simulations also show that nitrate aerosol is proportional to vehicular VOC and NH₃ emissions in the street canyon. Changes of VOC emissions affect the nitrate aerosol and HNO₃ concentrations through changes in the O₃ concentration under a VOC-limited regime for O₃ production. Nitrate aerosol concentration is influenced by vehicular NH₃ emissions, which produce ammonium nitrate effectively under an NH₃-limited regime for nitrate production. This research suggests that, when vehicular emissions are dominant in winter, the control of vehicular VOC and NH₃ emissions might be a more effective way to degrade PM_2.5 problems than the control of NO_x. Full article

(This article belongs to the Special Issue Air Pollution Modelling: Local-, Regional-, and Global-Scale Application)

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