Global, High-Resolution, Reduced-Complexity Air Quality Modeling Using InMAP (Intervention Model for Air Pollution)

Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce these deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many policy scenarios at high spatial resolution. However, air quality modeling typically has high requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with 4 km horizontal grid cell widths in cities. We evaluate Global InMAP performance both against measurements and a state-of-the-science chemical transport model, GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%, which is sufficient for initial policy assessment and scoping. Global InMAP can be run on a desktop computer; simulations here took 2.6–4.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate air pollution policy assessment worldwide, providing a screening tool for reducing the deaths where they occur most.

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Global, High-Resolution, Reduced-Complexity Air Quality Modeling Using InMAP(Intervention Model for Air Pollution)

10.26434/chemrxiv.14330375.v1 ◽

2021 ◽

Author(s):

Sumil Thakrar ◽

Christopher Tessum ◽

Joshua Apte ◽

Srinidhi Balasubramanian ◽

Dylan B Millet ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Transport Model ◽

The United States ◽

Air Quality Modeling ◽

Air Quality Model ◽

Quality Model ◽

Desktop Computer ◽

Quality Modeling ◽

Reduced Complexity

Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many policy scenarios at high spatial resolution. However, air quality modeling typically has high requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with 4 km horizontal grid cell widths in cities. We evaluate Global InMAP performance both against measurements and a state-of-the-science chemical transport model, GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%. Global InMAP can be run on a desktop computer; simulations here took 2.6–4.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate air pollution policy assessment worldwide, providing a tool for reducing the deaths where they occur most.

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Global, High-Resolution, Reduced-Complexity Air Quality Modeling Using InMAP(Intervention Model for Air Pollution)

10.26434/chemrxiv.14330375 ◽

2021 ◽

Author(s):

Sumil Thakrar ◽

Christopher Tessum ◽

Joshua Apte ◽

Srinidhi Balasubramanian ◽

Dylan B Millet ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Transport Model ◽

The United States ◽

Air Quality Modeling ◽

Air Quality Model ◽

Quality Model ◽

Desktop Computer ◽

Quality Modeling ◽

Reduced Complexity

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Emission Inventories and Particulate Matter Air Quality Modeling over the Pearl River Delta Region

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18084155 ◽

2021 ◽

Vol 18 (8) ◽

pp. 4155

Author(s):

Diogo Lopes ◽

Joana Ferreira ◽

Ka In Hoi ◽

Ka-Veng Yuen ◽

Kai Meng Mok ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Pearl River Delta ◽

Air Quality Modeling ◽

Pearl River ◽

Emission Inventories ◽

Atmospheric Emission ◽

The Pearl River Delta ◽

Quality Modeling ◽

The Pearl River

The Pearl River Delta (PRD) region is located on the southeast coast of mainland China and it is an important economic hub. The high levels of particulate matter (PM) in the atmosphere, however, and poor visibility have become a complex environmental problem for the region. Air quality modeling systems are useful to understand the temporal and spatial distribution of air pollution, making use of atmospheric emission data as inputs. Over the years, several atmospheric emission inventories have been developed for the Asia region. The main purpose of this work is to evaluate the performance of the air quality modeling system for simulating PM concentrations over the PRD using three atmospheric emission inventories (i.e., EDGAR, REAS and MIX) during a winter and a summer period. In general, there is a tendency to underestimate PM levels, but results based on the EDGAR emission inventory show slightly better accuracy. However, improvements in the spatial and temporal disaggregation of emissions are still needed to properly represent PRD air quality. This study’s comparison of the three emission inventories’ data, as well as their PM simulating outcomes, generates recommendations for future improvements to atmospheric emission inventories and our understanding of air pollution problems in the PRD region.

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Progress toward a general analytical method for predicting indoor air pollution in buildings- indoor air quality modeling phase III report

10.6028/nbs.ir.88-3814 ◽

1988 ◽

Cited By ~ 4

Author(s):

James Axley

Keyword(s):

Air Pollution ◽

Air Quality ◽

Indoor Air Quality ◽

Indoor Air ◽

Analytical Method ◽

Indoor Air Pollution ◽

Air Quality Modeling ◽

Phase Iii ◽

Quality Modeling

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Air Quality Modeling and Metamodeling Approach

Advances in Environmental Engineering and Green Technologies - Environmental Modeling for Sustainable Regional Development ◽

10.4018/978-1-60960-156-0.ch007 ◽

2011 ◽

pp. 144-161 ◽

Cited By ~ 1

Author(s):

Miloslava Kašparová ◽

Jirí Krupka

Keyword(s):

Air Pollution ◽

Air Quality ◽

Classification Problem ◽

Air Quality Modeling ◽

Point Of View ◽

Interaction Detection ◽

Power Stations ◽

Quality Modeling ◽

Chi Squared ◽

Problematic Area

This chapter deals with modeling and metamodeling of air quality in the Pardubice region of the Czech Republic. From a regional point of view, the Pardubice district is the most problematic area in regards to air pollution. Concentrations of traffic, industry and power stations (Opatovice and Chvaletice) activities are the cause of this situation, although emissions of all pollutants have markedly decreased within the last ten years. A decrease in air pollution was achieved particularly by restriction and restructuring of industrial production, use of emission standards, changes in legislation in the area of air protection, etc. The mentioned air quality modeling belongs to classification tasks. It means the authors deal with the classification problem, with the creation of classification models (classifiers) and they focus on metamodeling (combining classifiers). Through the application of modeling and metamodeling the authors use selected algorithms of decision trees (C5.0, chi-squared automatic interaction detection and classification and regression trees) that belong to useful explanatory techniques.

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Poor Air Quality and Its Association with Mortality in Ho Chi Minh City: Case Study

Atmosphere ◽

10.3390/atmos11070750 ◽

2020 ◽

Vol 11 (7) ◽

pp. 750

Author(s):

Hoang Ngoc Khue Vu ◽

Quang Phuc Ha ◽

Duc Hiep Nguyen ◽

Thi Thu Thuy Nguyen ◽

Thoai Tam Nguyen ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Ambient Air ◽

Air Quality Modeling ◽

World Health ◽

Ho Chi Minh City ◽

Annual Average ◽

Quality Modeling ◽

Concentration Of Air Pollutants

Along with its rapid urban development, Ho Chi Minh City (HCMC) in recent years has suffered a high concentration of air pollutants, especially fine particulate matters or PM2.5. A comprehensive study is required to evaluate the air quality conditions and their health impact in this city. Given the lack of adequate air quality monitoring data over a large area of the size of HCMC, an air quality modeling methodology is adopted to address the requirement. Here, by utilizing a corresponding emission inventory in combination with The Air Pollution Model-Chemical Transport Model (TAPM-CTM), the predicted concentration of air pollutants is first obtained for PM2.5, NOx, and SO2. Then by associating the pollutants exposed with the mortality rate from three causes, namely Ischemic Heart Disease (IHD), cardiopulmonary, and lung cancer, the impact of air pollution on human health is obtained for this purpose. Spatial distribution has shown a high amount of pollutants concentrated in the central city with a high density of combustion vehicles (motorcycles and automobiles). In addition, a significant amount of emissions can be observed from stevedoring and harbor activities, including ferries and cargo handling equipment located along the river. Other sources such as household activities also contribute to an even distribution of emission across the city. The results of air quality modeling showed that the annual average concentrations of NO2 were higher than the standard of Vietnam National Technical Regulation on Ambient Air Quality (QCVN 05: 2013 40 µg/m3) and World Health Organization (WHO) (40 µg/m3). The annual average concentrations of PM2.5 were 23 µg/m3 and were also much higher than the WHO (10 µg/m3) standard by about 2.3 times. In terms of public health impacts, PM2.5 was found to be responsible for about 1136 deaths, while the number of mortalities from exposure to NO2 and SO2 was 172 and 89 deaths, respectively. These figures demand some stringent measures from the authorities to potentially remedy the alarming situation of air pollution in HCM City.

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Air pollution emission inventory and air quality modeling for Can Tho City, Mekong Delta, Vietnam

Air Quality Atmosphere & Health ◽

10.1007/s11869-017-0512-x ◽

2017 ◽

Vol 11 (1) ◽

pp. 35-47 ◽

Cited By ~ 7

Author(s):

Ho Quoc Bang ◽

Vu Hoang Ngoc Khue ◽

Nguyen Thoai Tam ◽

Kristofer Lasko

Keyword(s):

Air Pollution ◽

Air Quality ◽

Emission Inventory ◽

Mekong Delta ◽

Air Quality Modeling ◽

Pollution Emission ◽

Quality Modeling ◽

Can Tho City

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Reduced-complexity air quality intervention modelling over China: development of the InMAPv1.6.1-China and comparison with the CMAQv5.2 model

10.5194/gmd-2021-87 ◽

2021 ◽

Author(s):

Ruili Wu ◽

Christopher W. Tessum ◽

Yang Zhang ◽

Chaopeng Hong ◽

Yixuan Zheng ◽

...

Keyword(s):

Air Quality ◽

Control Policy ◽

Premature Mortality ◽

The United States ◽

Assessment Model ◽

Health Impacts ◽

Emission Sources ◽

Air Quality Model ◽

Quality Model ◽

Reduced Complexity

Abstract. This paper presents the first development and evaluation of the reduced-complexity air quality model for China. In this study, a reduced-complexity air quality intervention model over China (InMAPv1.6.1-China, hereafter, InMAP-China) is developed by linking a regional air quality model, a reduced-complexity air quality model, an emission inventory database for China, and a health impact assessment model to rapidly estimate the air quality and health impacts of emission sources in China. The modelling system is applied over mainland China for 2017 under various emission scenarios. A comprehensive model evaluation is conducted by comparison against conventional CMAQ simulations and ground-based observations. We found that InMAP-China satisfactorily predicted total PM2.5 concentrations in terms of statistical performance. Compared with the observed PM2.5 concentrations, the mean bias (MB), normalized mean bias (NMB), and correlations of the total PM2.5 concentrations are −8.1 μg/m3, −18 %, and 0.6, respectively. The statistical performance is considered to be satisfactory for a reduced-complexity air quality model and remains consistent with that evaluated in the United States. The underestimation of total PM2.5 concentrations was mainly caused by its composition, primary PM2.5. In terms of the ability to quantify source contributions of PM2.5 concentrations, InMAP-China presents similar results in comparison with those based on the CMAQ model, the difference is mainly caused by the different mechanism and the treatment of secondary inorganic aerosols in the two models. Focusing on the health impacts, the annual PM2.5-related premature mortality estimated using InMAP-China in 2017 was 1.92 million, which was 25 ten thousand deaths lower than that estimated based on CMAQ simulations as a result of underestimation of PM2.5 concentrations. This work presents a version of the reduced-complexity air quality model over China, provides a powerful tool to rapidly assess the air quality and health impacts associated with control policy, and to quantify the source contribution attributable to many emission sources.

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Overview of Model Inter-Comparison in Japan’s Study for Reference Air Quality Modeling (J-STREAM)

Atmosphere ◽

10.3390/atmos9010019 ◽

2018 ◽

Vol 9 (1) ◽

pp. 19 ◽

Cited By ~ 18

Author(s):

Satoru Chatani ◽

Kazuyo Yamaji ◽

Tatsuya Sakurai ◽

Syuichi Itahashi ◽

Hikari Shimadera ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Three Dimensional ◽

Model Performance ◽

Air Quality Modeling ◽

Second Phase ◽

Common Input ◽

Quality Modeling ◽

Photochemical Ozone ◽

Secondary Air

The inter-comparison of regional air quality models is an effective way to understand uncertainty in ambient pollutant concentrations simulated using various model configurations, as well as to find ways to improve model performance. Based on the outcomes and experiences of Japanese projects thus far, a new model inter-comparison project called Japan’s study for reference air quality modeling (J-STREAM) has begun. The objective of J-STREAM is to establish reference air quality modeling for source apportionment and effective strategy making to suppress secondary air pollutants including PM2.5 and photochemical ozone in Japan through model inter-comparison. The first phase focuses on understanding the ranges and limitations in ambient PM2.5 and ozone concentrations simulated by participants using common input datasets. The second phase focuses on issues revealed in previous studies in simulating secondary inorganic aerosols, as well as on the three-dimensional characteristics of photochemical ozone as a new target. The third phase focuses on comparing source apportionments and sensitivities under heavy air pollution episodes simulated by participating models. Detailed understanding of model performance, uncertainty, and possible improvements to urban-scale air pollution involving secondary pollutants, as well as detailed sector-wise source apportionments over megacities in Japan are expected.

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