scholarly journals Reduced-complexity air quality intervention modeling over China: the development of InMAPv1.6.1-China and a comparison with CMAQv5.2

2021 ◽  
Vol 14 (12) ◽  
pp. 7621-7638
Author(s):  
Ruili Wu ◽  
Christopher W. Tessum ◽  
Yang Zhang ◽  
Chaopeng Hong ◽  
Yixuan Zheng ◽  
...  
Keyword(s):  
Air Quality ◽  
Control Policy ◽  
Premature Mortality ◽  
Health Impact ◽  
Assessment Model ◽  
Health Impacts ◽  
Emission Sources ◽  
Air Quality Model ◽  
Quality Model ◽  
Reduced Complexity

Abstract. This paper presents the first development and evaluation of a reduced-complexity air quality model for China. In this study, the reduced-complexity Intervention Model for Air Pollution over China (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 modeling system is applied over mainland China for 2017 under various emission scenarios. A comprehensive model evaluation is conducted by comparison against conventional Community Multiscale Air Quality (CMAQ) modeling system 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 m−3, −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 USA. 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 to those based on the CMAQ model, with variation mainly caused by the different 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 250 000 deaths lower than estimated based on CMAQ simulations as a result of the underestimation of PM2.5 concentrations. This work presents a version of the reduced-complexity air quality model over China that 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.

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

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.

scholarly journals New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations

2015 ◽  
Vol 112 (35) ◽  
pp. 10884-10889 ◽  
Author(s):  
Paul Y. Kerl ◽  
Wenxian Zhang ◽  
Juan B. Moreno-Cruz ◽  
Athanasios Nenes ◽  
Matthew J. Realff ◽  
...  
Keyword(s):  
Air Quality ◽  
Power Plant ◽  
Power Plants ◽  
Air Pollutant ◽  
Health Impacts ◽  
Reduced Form ◽  
Air Quality Model ◽  
Quality Model ◽  
Electricity Planning

Integrating accurate air quality modeling with decision making is hampered by complex atmospheric physics and chemistry and its coupling with atmospheric transport. Existing approaches to model the physics and chemistry accurately lead to significant computational burdens in computing the response of atmospheric concentrations to changes in emissions profiles. By integrating a reduced form of a fully coupled atmospheric model within a unit commitment optimization model, we allow, for the first time to our knowledge, a fully dynamical approach toward electricity planning that accurately and rapidly minimizes both cost and health impacts. The reduced-form model captures the response of spatially resolved air pollutant concentrations to changes in electricity-generating plant emissions on an hourly basis with accuracy comparable to a comprehensive air quality model. The integrated model allows for the inclusion of human health impacts into cost-based decisions for power plant operation. We use the new capability in a case study of the state of Georgia over the years of 2004–2011, and show that a shift in utilization among existing power plants during selected hourly periods could have provided a health cost savings of $175.9 million dollars for an additional electricity generation cost of $83.6 million in 2007 US dollars (USD2007). The case study illustrates how air pollutant health impacts can be cost-effectively minimized by intelligently modulating power plant operations over multihour periods, without implementing additional emissions control technologies.

Pollution Exposure to Humans and Its Assessment

2018 ◽  
pp. 93-121
Author(s):  
Rajmal Jat ◽  
Veerendra Sahu ◽  
Bhola Ram Gurjar
Keyword(s):  
Air Quality ◽  
Dispersion Model ◽  
Direct Method ◽  
Health Impact ◽  
Pollution Level ◽  
Air Quality Model ◽  
Quality Model ◽  
Exposure Analysis ◽  
Cfd Models ◽  
Pollution Exposure

Exposure analysis is the receptor-oriented approach of the pollution-level measurement. In this chapter, a detailed discussion is provided of the fundamentals of exposure analysis, methods of measurement, basics of models used for the prediction of pollution concentration indoors and outdoors, and a brief discussion about the health impact of selected pollutants. A detail of fundamental of indoor air quality (IAQ) models like mass balance and CFD models is discussed. Also, basic structures of community multiscale air quality model (CMAQ) and AIRMOD ambient air dispersion models are described. It is observed that measurement of pollution exposure by direct method requires more time and effort as compared with the integrated exposure and stationary measurement. AIRMODE is steady state model and based upon the Gaussian dispersion model. CMAQ is capable of simulating the pollution level for the range of geographic scale for multiple pollutants.

scholarly journals The quest for improved air quality may push China to continue its CO2reduction beyond the Paris Commitment

2020 ◽  
Vol 117 (47) ◽  
pp. 29535-29542
Author(s):  
Jia Xing ◽  
Xi Lu ◽  
Shuxiao Wang ◽  
Tong Wang ◽  
Dian Ding ◽  
...  
Keyword(s):  
Air Quality ◽  
Health Benefit ◽  
Cost Effective ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Chinese Government ◽  
Low Carbon ◽  
Air Quality Model ◽  
Quality Model ◽  
Low Carbon Energy

China is challenged with the simultaneous goals of improving air quality and mitigating climate change. The “Beautiful China” strategy, launched by the Chinese government in 2020, requires that all cities in China attain 35 μg/m3or below for annual mean concentration of PM2.5(particulate matter with aerodynamic diameter less than 2.5 μm) by 2035. Meanwhile, China adopts a portfolio of low-carbon policies to meet its Nationally Determined Contribution (NDC) pledged in the Paris Agreement. Previous studies demonstrated the cobenefits to air pollution reduction from implementing low-carbon energy policies. Pathways for China to achieve dual targets of both air quality and CO2mitigation, however, have not been comprehensively explored. Here, we couple an integrated assessment model and an air quality model to evaluate air quality in China through 2035 under the NDC scenario and an alternative scenario (Co-Benefit Energy [CBE]) with enhanced low-carbon policies. Results indicate that some Chinese cities cannot meet the PM2.5target under the NDC scenario by 2035, even with the strictest end-of-pipe controls. Achieving the air quality target would require further reduction in emissions of multiple air pollutants by 6 to 32%, driving additional 22% reduction in CO2emissions relative to the NDC scenario. Results show that the incremental health benefit from improved air quality of CBE exceeds 8 times the additional costs of CO2mitigation, attributed particularly to the cost-effective reduction in household PM2.5exposure. The additional low-carbon energy polices required for China’s air quality targets would lay an important foundation for its deep decarbonization aligned with the 2 °C global temperature target.

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

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

<p>Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM<sub>2.5</sub>). Designing policies to reduce deaths relies on air quality modeling for estimating changes in PM<sub>2.5</sub> 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 PM<sub>2.5</sub>-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 PM<sub>2.5</sub> 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.</p>

scholarly journals Improvementof the computer model of air pollution estimation due to emissions of stationary sources of airports and compressor stations

2021 ◽  
Vol 3 (10(111)) ◽  
pp. 54-64
Author(s):  
Oleksandr Zaporozhets ◽  
Kateryna Synylo ◽  
Sergii Karpenko ◽  
Andriy Krupko
Keyword(s):  
Air Quality ◽  
Transportation Systems ◽  
Emission Sources ◽  
Air Quality Model ◽  
Quality Model ◽  
Test Scenario ◽  
Gas Pumping ◽  
Pumping Units ◽  
Coordination Meeting ◽  
Stationary Sources

Emission sources at airports and compressor stations have the potential to emit pollutants, the effects of which can degrade local air quality. In most cases, the basis of gas pumping units includes either aircraft engines that have exhausted their flight life, or their targeted modifications to fulfill the tasks of gas pumping units and compressor stations in various gas transportation systems. The methodology for calculating the concentration of pollutants contained in the emissions of enterprises does not take into account all possible features of emission sources, in terms of passive stationary sources and cold emissions, the algorithm of the methodology requires clarification and the justifications given in the article indicate possible ways of clarification. According to the decision of the CAEP SG-2020 Coordination Meeting "detailed documentation for the Ukrainian POLEMICA air quality model provided in CAEP / 12-FESG-MDG / 2-WP / 09 should be considered as the final documentation for verifying this model for compliance with ICAO document 9889 requirements" ... The results of calculating the maximum concentration for the test scenario using Gaussian models, verified in CAEP, differ by almost 2 times. A similar result according to the PolEmiCa model ~ 1.5 μg/m3 is almost two times less, which is due to the inclusion of the effects of the initial rise in the emission of the mixture from a stationary source into the algorithms of the OND-86 method

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

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

<p>Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM<sub>2.5</sub>). Designing policies to reduce deaths relies on air quality modeling for estimating changes in PM<sub>2.5</sub> 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 PM<sub>2.5</sub>-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 PM<sub>2.5</sub> 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.</p>

scholarly journals Indian annual ambient air quality standard is achievable by completely mitigating emissions from household sources

2019 ◽  
Vol 116 (22) ◽  
pp. 10711-10716 ◽  
Author(s):  
Sourangsu Chowdhury ◽  
Sagnik Dey ◽  
Sarath Guttikunda ◽  
Ajay Pillarisetti ◽  
Kirk R. Smith ◽  
...  
Keyword(s):  
Air Quality ◽  
Dispersion Model ◽  
Fine Particulate Matter ◽  
Weighted Average ◽  
Premature Mortality ◽  
Ambient Air ◽  
Quality Standard ◽  
Population Exposure ◽  
Air Quality Model ◽  
Quality Model

Exposures to ambient and household fine-particulate matter (PM2.5) together are among the largest single causes of premature mortality in India according to the Global Burden of Disease Studies (GBD). Several recent investigations have estimated that household emissions are the largest contributor to ambient PM2.5 exposure in the country. Using satellite-derived district-level PM2.5 exposure and an Eulerian photochemical dispersion model CAMx (Comprehensive Air Quality Model with Extensions), we estimate the benefit in terms of population exposure of mitigating household sources––biomass for cooking, space- and water-heating, and kerosene for lighting. Complete mitigation of emissions from only these household sources would reduce India-wide, population-weighted average annual ambient PM2.5 exposure by 17.5, 11.9, and 1.3%, respectively. Using GBD methods, this translates into reductions in Indian premature mortality of 6.6, 5.5, and 0.6%. If PM2.5 emissions from all household sources are completely mitigated, 103 (of 597) additional districts (187 million people) would meet the Indian annual air-quality standard (40 μg m−3) compared with baseline (2015) when 246 districts (398 million people) met the standard. At 38 μg m−3, after complete mitigation of household sources, compared with 55.1 μg m−3 at baseline, the mean annual national population-based concentration would meet the standard, although highly polluted areas, such as Delhi, would remain out of attainment. Our results support expansion of programs designed to promote clean household fuels and rural electrification to achieve improved air quality at regional scales, which also has substantial additional health benefits from directly reducing household air pollution exposures.

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