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.

scholarly journals Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0

2013 ◽  
Vol 6 (4) ◽  
pp. 883-899 ◽  
Author(s):  
K. W. Appel ◽  
G. A. Pouliot ◽  
H. Simon ◽  
G. Sarwar ◽  
H. O. T. Pye ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Trace Metals ◽  
Urban Areas ◽  
Temporal Distribution ◽  
Air Pollutant ◽  
Eastern United States ◽  
Air Quality Model ◽  
Quality Model ◽  
Model Version

Abstract. The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transformation, transport, and fate of the many different air pollutant species that comprise particulate matter (PM), including dust (or soil). The CMAQ model version 5.0 (CMAQv5.0) has several enhancements over the previous version of the model for estimating the emission and transport of dust, including the ability to track the specific elemental constituents of dust and have the model-derived concentrations of those elements participate in chemistry. The latest version of the model also includes a parameterization to estimate emissions of dust due to wind action. The CMAQv5.0 modeling system was used to simulate the entire year 2006 for the continental United States, and the model estimates were evaluated against daily surface-based measurements from several air quality networks. The CMAQ modeling system overall did well replicating the observed soil concentrations in the western United States (mean bias generally around ±0.5 μg m−3); however, the model consistently overestimated the observed soil concentrations in the eastern United States (mean bias generally between 0.5–1.5 μg m−3), regardless of season. The performance of the individual trace metals was highly dependent on the network, species, and season, with relatively small biases for Fe, Al, Si, and Ti throughout the year at the Interagency Monitoring of Protected Visual Environments (IMPROVE) sites, while Ca, K, and Mn were overestimated and Mg underestimated. For the urban Chemical Speciation Network (CSN) sites, Fe, Mg, and Mn, while overestimated, had comparatively better performance throughout the year than the other trace metals, which were consistently overestimated, including very large overestimations of Al (380%), Ti (370%) and Si (470%) in the fall. An underestimation of nighttime mixing in the urban areas appears to contribute to the overestimation of trace metals. Removing the anthropogenic fugitive dust (AFD) emissions and the effects of wind-blown dust (WBD) lowered the model soil concentrations. However, even with both AFD emissions and WBD effects removed, soil concentrations were still often overestimated, suggesting that there are other sources of errors in the modeling system that contribute to the overestimation of soil components. Efforts are underway to improve both the nighttime mixing in urban areas and the spatial and temporal distribution of dust-related emission sources in the emissions inventory.

Study on the Countermeasures of NOx Emission Reduction in Chengdu Economic Circle

2013 ◽  
Vol 726-731 ◽  
pp. 2324-2332
Author(s):  
Wen Yong Wang ◽  
Xiao Juan Ma
Keyword(s):  
Air Quality ◽  
Power Plant ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Ambient Air ◽  
Control Measures ◽  
Cement Plant ◽  
Air Quality Model ◽  
Quality Model ◽  
Mean Concentration

Based on the detailed survey on the source and volume of NOx emission over Chengdu Economic Circle, the third-generation air quality model CMAQ is adopted for simulating the density of NOx in the air over Chengdu Economic Circle. The result shows that the hourly concentration, daily mean concentration and annual mean concentration of NOx in air exceed the standard data, and the affected areas respectively account for 0.2%, 0.18% and 0.12% of the total area of the economic circle. Meanwhile, in accordance with the simulation calculation, The NOX emission of the vehicle exhaust, the thermal power plant and the cement plant are the major NOX concentration contribution sources in air, contribution rate is amounting to 39.13%, 21.41% and 15.34% respectively. Thus, three main measures to reduce the emission of NOx of Chengdu Economic Circle are proposed as follows: firstly, strengthen the management of vehicle and reduce the emission of NOx by the vehicle; secondly, manage the NOx of the industrial enterprise; flue gas denitrification equipment must be constructed in the thermal power plant and cement manufacturing enterprise, and the comprehensive denitration efficiency of the thermal power plant should be not less than 70% and the comprehensive denitration efficiency of the cement plant should not be less than 60%; thirdly, joint prevention and control measures should be implemented between the cities, so as to reduce the transport of NOx. With the application of the above measures, the emission reductions of NOx can be reduced to 55% of the existing volume, and the concentration of NOx in the air can meet with the Class II of national ambient air quality Standard.

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 Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0

2013 ◽  
Vol 6 (1) ◽  
pp. 1859-1899 ◽  
Author(s):  
K. W. Appel ◽  
G. A. Pouliot ◽  
H. Simon ◽  
G. Sarwar ◽  
H. O. T. Pye ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Trace Metals ◽  
Urban Areas ◽  
Temporal Distribution ◽  
Air Pollutant ◽  
Eastern United States ◽  
Air Quality Model ◽  
Quality Model ◽  
Model Version

Abstract. The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transformation, transport and fate of the many different air pollutant species that comprise particulate matter (PM), including dust (or soil). The CMAQ model version 5.0 (CMAQv5.0) has several enhancements over the previous version of the model for estimating the emission and transport of dust, including the ability to track the specific elemental constituents of dust and have the model-derived concentrations of those elements participate in chemistry. The latest version of the model also includes a parameterization to estimate emissions of dust due to wind action. The CMAQv5.0 modeling system was used to simulate the entire year 2006 for the continental United States, and the model estimates were evaluated against daily surface based measurements from several air quality networks. The CMAQ modeling system generally did well replicating the observed soil concentrations in the western United States; however the model consistently overestimated the observed soil concentrations in the eastern United States, regardless of season. The performance of the individual trace metals was generally good at the rural network sites, with relatively small biases for Fe, Al, Si and Ti throughout the year, while Ca, K and Mn were overestimated and Mg underestimated. For the urban sites, Fe, Mg and Mn, while overestimated, had comparatively better performance throughout the year than the other trace metals, which were consistently overestimated, including very large overestimations of Al, Ti and Si in the fall. An underestimation of nighttime mixing in the urban areas appears to contribute to the overestimation of trace metals. Removing the anthropogenic fugitive dust (AFD) emissions and the effects of wind-blown dust (WBD) lowered the model soil concentrations. However, even with both AFD emissions and WBD effects removed, soil concentrations were still often overestimated, suggesting that there are other sources of errors in the modeling system that contribute to the overestimation of soil components. Efforts are underway to improve both the nighttime mixing in urban areas and the spatial and temporal distribution of dust related emissions sources in the emissions inventory.

Modelling aerosol–cloud–meteorology interaction: A case study with a fully coupled air quality model (GEM-MACH)

2015 ◽  
Vol 115 ◽  
pp. 695-715 ◽  
Author(s):  
W. Gong ◽  
P.A. Makar ◽  
J. Zhang ◽  
J. Milbrandt ◽  
S. Gravel ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Quality Model ◽  
Quality Model ◽  
Aerosol Cloud ◽  
Fully Coupled

scholarly journals Updated emission inventories of power plants in simulating air quality during haze periods over East China

2018 ◽  
Vol 18 (3) ◽  
pp. 2065-2079 ◽  
Author(s):  
Lei Zhang ◽  
Tianliang Zhao ◽  
Sunling Gong ◽  
Shaofei Kong ◽  
Lili Tang ◽  
...  
Keyword(s):  
Air Quality ◽  
Power Plant ◽  
Power Plants ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Atmospheric Environment ◽  
East China ◽  
Emission Inventories ◽  
Power Plant Emissions ◽  
Plant Emissions

Abstract. Air pollutant emissions play a determinant role in deteriorating air quality. However, an uncertainty in emission inventories is still the key problem for modeling air pollution. In this study, an updated emission inventory of coal-fired power plants (UEIPP) based on online monitoring data in Jiangsu Province of East China for the year of 2012 was implemented in the widely used Multi-resolution Emission Inventory for China (MEIC). By employing the Weather Research and Forecasting model with Chemistry (WRF-Chem), two simulation experiments were executed to assess the atmospheric environment change by using the original MEIC emission inventory and the MEIC inventory with the UEIPP. A synthetic analysis shows that power plant emissions of PM2.5, PM10, SO2, and NOx were lower, and CO, black carbon (BC), organic carbon (OC) and NMVOCs (non-methane volatile organic compounds) were higher in UEIPP relative to those in MEIC, reflecting a large discrepancy in the power plant emissions over East China. In accordance with the changes in UEIPP, the modeled concentrations were reduced for SO2 and NO2, and increased for most areas of primary OC, BC, and CO. Interestingly, when the UEIPP was used, the atmospheric oxidizing capacity significantly reinforced. This was reflected by increased oxidizing agents, e.g., O3 and OH, thus directly strengthening the chemical production from SO2 and NOx to sulfate and nitrate, respectively, which offset the reduction of primary PM2.5 emissions especially on haze days. This study indicates the importance of updating air pollutant emission inventories in simulating the complex atmospheric environment changes with implications on air quality and environmental changes.

Simulation of Air Quality and Pollution Control Countermeasures of Chengdu Urban Agglomeration

2012 ◽  
Vol 610-613 ◽  
pp. 1387-1397 ◽  
Author(s):  
Wen Yong Wang ◽  
Nan Chen ◽  
Xiao Juan Ma
Keyword(s):  
Air Quality ◽  
Sulfur Dioxide ◽  
Pollution Sources ◽  
Air Pollutant ◽  
Urban Agglomeration ◽  
Pollutant Concentration ◽  
Pollutant Emission ◽  
Air Quality Model ◽  
Quality Model ◽  
Allowable Limit

The CMAQ model (Community Multiscale Air Quality model) was used to stimulate the atmospheric environmental quality of Chengdu urban agglomeration. The result shows that air pollutant concentration in some zones of the urban agglomeration is higher than the allowable limit of the national grade II standard. Fortunately, such zones only cover a small area. Zones where the average daily and annual PM10 concentration is higher than the allowable limit only account for 4% of the total area of Chengdu urban agglomeration. Less than 1% of the total area has the concentration of other pollutants higher than the limit. Zones with pollutant concentration higher than the limit are mainly distributed in Chengdu City, Mianyang City, and Meishan City. Pollutants emitted from the cities of Chengdu urban agglomeration shift on to and interact with each other. Therefore, the air pollutant concentration of one city is partially attributable to pollutants emitted from its own pollution sources and a part of or even most of it results from pollutants from other cities. For example, regarding PM10 in air of Deyang City, only 12% comes from its own pollution sources, and 55% comes from pollution sources of Chengdu, and the rest 29% comes from pollution sources of Mianyang. Regarding Sulfur dioxide in air of Chengdu, 59% comes from local pollution sources of Chengdu and 23% comes from pollution sources of Deyang. Other pollutants are also subject to such a rule. As in the urban agglomeration, there are zones where pollutant concentration is higher than the allowable limit, the existing pollution sources must be further controlled by setting reduction target according to the total capacity. The pollutant emission should be reduced by means of eliminating backward productivity, adjusting structure and layout of industries, and controlling pollution sources in depth to effectively improve the regional environmental air quality. At the same time, as pollutants emitted from the cities interact with each other, the 5 cities must sign a joint prevention and control agreement to collaborate in control of sulfur dioxide, nitrogen oxides, smoke and dust, and organic pollutants.

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