scholarly journals Heterogeneous sulfate aerosol formation mechanisms during wintertime Chinese haze events: air quality model assessment using observations of sulfate oxygen isotopes in Beijing

2019 ◽  
Vol 19 (9) ◽  
pp. 6107-6123 ◽  
Author(s):  
Jingyuan Shao ◽  
Qianjie Chen ◽  
Yuxuan Wang ◽  
Xiao Lu ◽  
Pengzhen He ◽  
...  
Keyword(s):  
Air Quality ◽  
Oxygen Isotopes ◽  
Metal Ion ◽  
Transport Model ◽  
Formation Mechanisms ◽  
Model Assessment ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Sulfate Production ◽  
Sulfate Formation

Abstract. Air quality models have not been able to reproduce the magnitude of the observed concentrations of fine particulate matter (PM2.5) during wintertime Chinese haze events. The discrepancy has been at least partly attributed to low biases in modeled sulfate production rates, due to the lack of heterogeneous sulfate production on aerosols in the models. In this study, we explicitly implement four heterogeneous sulfate formation mechanisms into a regional chemical transport model, in addition to gas-phase and in-cloud sulfate production. We compare the model results with observations of sulfate concentrations and oxygen isotopes, Δ17O(SO42-), in the winter of 2014–2015, the latter of which is highly sensitive to the relative importance of different sulfate production mechanisms. Model results suggest that heterogeneous sulfate production on aerosols accounts for about 20 % of sulfate production in clean and polluted conditions, partially reducing the modeled low bias in sulfate concentrations. Model sensitivity studies in comparison with the Δ17O(SO42-) observations suggest that heterogeneous sulfate formation is dominated by transition metal ion-catalyzed oxidation of SO2.

scholarly journals Heterogeneous sulfate aerosol formation mechanisms during wintertime Chinese haze events: Air quality model assessment using observations of sulfate oxygen isotopes in Beijing

2019 ◽  
Author(s):  
Jingyuan Shao ◽  
Qianjie Chen ◽  
Yuxuan Wang ◽  
Xiao Lu ◽  
Pengzhen He ◽  
...  
Keyword(s):  
Air Quality ◽  
Oxygen Isotopes ◽  
Metal Ion ◽  
Transport Model ◽  
Formation Mechanisms ◽  
Model Assessment ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Sulfate Production ◽  
Sulfate Formation

Abstract. Air quality models have not been able to reproduce the magnitude of the observed concentrations of fine particulate matter (PM2.5) during wintertime Chinese haze events. The discrepancy has been at least partly attributed to low biases in modeled sulfate production rates due to the lack of heterogeneous sulfate production on aerosols in the models. In this study, we explicitly implement four heterogeneous sulfate formation mechanisms into a regional chemical transport model, in addition to gas-phase and in-cloud sulfate production. We compare the model results with observations of sulfate concentrations and oxygen isotopes (Δ17O(SO42−)) in the winter of 2014–2015, the latter of which is highly sensitive to the relative importance of different sulfate production mechanisms. Model results suggest that heterogeneous sulfate production on aerosols accounts for about 20 % of sulfate production in clean and polluted conditions, partially reducing the modeled low bias in sulfate concentrations. Model sensitivity studies in comparison with the Δ17O(SO42−) observations suggest that heterogeneous sulfate formation is dominated by transition metal ion catalyzed oxidation of SO2.

Regional source apportionment of ozone and PM2.5 during the EXPLORE-YRD campaign in the Yangtze River Delta region of China

2020 ◽  
Author(s):  
Jianlin Hu ◽  
Lin Li ◽  
Jingyi Li ◽  
Xueying Wang ◽  
Kangjia Gong
Keyword(s):  
Air Quality ◽  
Yangtze River Delta ◽  
River Delta ◽  
Formation Mechanisms ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model ◽  
Haze Pollution ◽  
Source Category ◽  
The Yrd

<p>Although the air quality in China has been improved by collaborative efforts dedicating to mitigate the haze pollution, PM2.5 concentrations still remain high levels and the issue of increasing O<sub>3</sub> concentration has attracted more attention of the public. The YRD region has been suffering from both the PM2.5 and O3 pollution problems. To investigate the formation mechanisms and sources of PM2.5 and O3 in this region, a comprehensive EXPLORE-YRD campaign (EXPeriment on the eLucidation of theatmospheric Oxidation capacity and aerosol foRmation, and their Effects inYangtze River Delta) was carried out in May - June 2018. In this study, we investigate the contributions of different source categories to PM2.5 and O<sub>3</sub>. A source-oriented 3-D air quality model (CMAQ) was applied to analyze contributions of different emission sources to PM2.5 and O<sub>3 </sub>in the YRD region. Emissions were divided into eight source categories: industry, power, transportation, residential, agriculture, biogenic, wildfire, and other countries. Contribution from individual source category was quantified. The importance of anthropogenic and natural sources to PM2.5 and O<sub>3</sub> was discussed.</p>

scholarly journals The sensitivity of the oxygen isotopes of ice core sulfate to changing oxidant concentrations since the preindustrial

2010 ◽  
Vol 10 (8) ◽  
pp. 20607-20623 ◽  
Author(s):  
E. D. Sofen ◽  
B. Alexander ◽  
S. A. Kunasek
Keyword(s):  
Oxygen Isotopes ◽  
Radiative Forcing ◽  
Transport Model ◽  
Ice Core ◽  
Ice Cores ◽  
The Arctic ◽  
Aerosol Formation ◽  
Chemical Transport Model ◽  
Sensitivity Studies ◽  
Sulfate Formation

Abstract. Changes in tropospheric oxidant concentrations since preindustrial times have implications for the ozone radiative forcing, lifetimes of reduced trace gases, aerosol formation, and human health but are highly uncertain. Measurements of the triple oxygen isotopes of sulfate in ice cores (described by Δ17OSO4 = δ17O − 0.52 × δ18O) provide one of the few constraints on paleo-oxidants. We use the GEOS-Chem global atmospheric chemical transport model to simulate changes in oxidant concentrations and the Δ17OSO4 between 1850 and 1990 to assess the sensitivity of Δ17OSO4 measurements in Greenland and Antarctic ice cores to changing tropospheric oxidant concentrations. The model indicates a 42% increase in the concentration of global mean tropospheric O3, a 10% decrease in OH, and a 58% increase in H2O2 between the preindustrial and present. Modeled Δ17OSO4 is consistent with measurements from ice core and aerosol samples. Model results indicate that the observed decrease in the Arctic Δ17OSO4 in spite of increasing O3 is due to the combined effects of increased sulfate formation by O2 catalyzed by anthropogenic transition metals and increased cloud water acidity. In Antarctica, the Δ17OSO4 is sensitive to relative changes of oxidant concentrations, but in a nonlinear fashion. Sensitivity studies explore the uncertainties in preindustrial emissions of oxidant precursors.

scholarly journals Development of the city-scale chemistry transport model CityChem-EPISODE and its application to the city of Hamburg

2018 ◽  
Author(s):  
Matthias Karl
Keyword(s):  
Air Quality ◽  
Urban Area ◽  
Transport Model ◽  
Dispersion Model ◽  
Temporal Correlation ◽  
Urban Atmosphere ◽  
Aerosol Formation ◽  
Urban Background ◽  
New Model ◽  
The City

Abstract. This paper describes the City-scale Chemistry (CityChem) extension of the urban dispersion model EPISODE with the aim to enable chemistry/transport simulations of multiple reactive pollutants on urban scales. The new model is called CityChem-EPISODE. The primary focus is on the simulation of urban ozone concentrations. Ozone is produced in photochemical reaction cycles involving nitrogen oxides (NOx) and volatile organic compounds (VOC) emitted by various anthropogenic activities in the urban area. The performance of the new model was evaluated with a series of synthetic tests and with a first application to the air quality situation in the city of Hamburg, Germany. The model performs fairly well for ozone in terms of temporal correlation and bias at the air quality monitoring stations in Hamburg. In summer afternoons, when photochemical activity is highest, modelled median ozone at an inner-city urban background station was about 30 % lower than the observed median ozone. Inaccuracy of the computed photolysis frequency of nitrogen dioxide (NO2) is the most probable explanation for this. CityChem-EPISODE reproduces the spatial variation of annual mean NO2 concentrations between urban background, traffic and industrial stations. However, the temporal correlation between modelled and observed hourly NO2 concentrations is weak for some of the stations. For daily mean PM10, the performance of CityChem-EPISODE is moderate due to low temporal correlation. The low correlation is linked to uncertainties in the seasonal cycle of the anthropogenic particulate matter (PM) emissions within the urban area. Missing emissions from domestic heating might be an explanation for the too low modelled PM10 in winter months. Four areas of need for improvement have been identified: (1) dry and wet deposition fluxes; (2) treatment of photochemistry in the urban atmosphere; (3) formation of secondary inorganic aerosol (SIA); and (4) formation of biogenic and anthropogenic secondary organic aerosol (SOA). The inclusion of secondary aerosol formation will allow for a better sectorial attribution of observed PM levels. Envisaged applications of the CityChem-EPISODE model are urban air quality studies, environmental impact assessment, sensitivity analysis of sector-specific emission and the assessment of local and regional emission abatement policy options.

scholarly journals Exploring the nature of air quality over southwestern Ontario: main findings from the Border Air Quality and Meteorology Study

2013 ◽  
Vol 13 (20) ◽  
pp. 10461-10482 ◽  
Author(s):  
J. R. Brook ◽  
P. A. Makar ◽  
D. M. L. Sills ◽  
K. L. Hayden ◽  
R. McLaren
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Great Lakes ◽  
The United States ◽  
Urban Heat Islands ◽  
Anthropogenic Emissions ◽  
Lake Breeze ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Quality Model

Abstract. This paper serves as an overview and discusses the main findings from the Border Air Quality and Meteorology Study (BAQS-Met) in southwestern Ontario in 2007. This region is dominated by the Great Lakes, shares borders with the United States and consistently experiences the highest ozone (O3) and fine particulate matter concentrations in Canada. The purpose of BAQS-Met was to improve our understanding of how lake-driven meteorology impacts air quality in the region, and to improve models used for forecasting and policy scenarios. Results show that lake breeze occurrence frequencies and inland penetration distances were significantly greater than realized in the past. Due to their effect on local meteorology, the lakes were found to enhance secondary O3 and aerosol formation such that local anthropogenic emissions have their impact closer to the populated source areas than would otherwise occur in the absence of the lakes. Substantial spatial heterogeneity in O3 was observed with local peaks typically 30 ppb above the regional values. Sulfate and secondary organic aerosol (SOA) enhancements were also linked to local emissions being transported in the lake breeze circulations. This study included the first detailed evaluation of regional applications of a high-resolution (2.5 km grid) air quality model in the Great Lakes region. The model showed that maxima in secondary pollutants occur in areas of convergence, in localized updrafts and in distinct pockets over the lake surfaces. These effects are caused by lake circulations interacting with the synoptic flow, with each other or with circulations induced by urban heat islands. Biogenic and anthropogenic emissions were both shown to play a role in the formation of SOA in the region. Detailed particle measurements and multivariate receptor models reveal that while individual particles are internally mixed, they often exist within more complex external mixtures. This makes it difficult to predict aerosol optical properties and further highlights the challenges facing aerosol modelling. The BAQS-Met study has led to a better understanding of the value of high-resolution (2.5 km) modelling for air quality and meteorological predictions and has led to several model improvements.

scholarly journals Comparisons of ground-based tropospheric NO<sub>2</sub> MAX-DOAS measurements to satellite observations with the aid of an air quality model over the Thessaloniki area, Greece

2017 ◽  
Vol 17 (9) ◽  
pp. 5829-5849 ◽  
Author(s):  
Theano Drosoglou ◽  
Alkiviadis F. Bais ◽  
Irene Zyrichidou ◽  
Natalia Kouremeti ◽  
Anastasia Poupkou ◽  
...  
Keyword(s):  
Air Quality ◽  
Transport Model ◽  
Optical Absorption Spectroscopy ◽  
Monitoring Site ◽  
Air Quality Model ◽  
Ozone Monitoring Instrument ◽  
Quality Model ◽  
Meteorological Model ◽  
Tropospheric No2 ◽  
Ozone Monitoring

Abstract. One of the main issues arising from the comparison of ground-based and satellite measurements is the difference in spatial representativeness, which for locations with inhomogeneous spatial distribution of pollutants may lead to significant differences between the two data sets. In order to investigate the spatial variability of tropospheric NO2 within a sub-satellite pixel, a campaign which lasted for about 6 months was held in the greater area of Thessaloniki, Greece. Three multi-axial differential optical absorption spectroscopy (MAX-DOAS) systems performed measurements of tropospheric NO2 columns at different sites representative of urban, suburban and rural conditions. The direct comparison of these ground-based measurements with corresponding products from the Ozone Monitoring Instrument onboard NASA's Aura satellite (OMI/Aura) showed good agreement over the rural and suburban areas, while the comparison with the Global Ozone Monitoring Experiment-2 (GOME-2) onboard EUMETSAT's Meteorological Operational satellites' (MetOp-A and MetOp-B) observations is good only over the rural area. GOME-2A and GOME-2B sensors show an average underestimation of tropospheric NO2 over the urban area of about 10.51 ± 8.32  ×  1015 and 10.21 ± 8.87  × 1015 molecules cm−2, respectively. The mean difference between ground-based and OMI observations is significantly lower (6.60 ± 5.71  ×  1015 molecules cm−2). The differences found in the comparisons of MAX-DOAS data with the different satellite sensors can be attributed to the higher spatial resolution of OMI, as well as the different overpass times and NO2 retrieval algorithms of the satellites. OMI data were adjusted using factors calculated by an air quality modeling tool, consisting of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the Comprehensive Air Quality Model with Extensions (CAMx) multiscale photochemical transport model. This approach resulted in significant improvement of the comparisons over the urban monitoring site. The average difference of OMI observations from MAX-DOAS measurements was reduced to −1.68 ± 5.01  ×  1015 molecules cm−2.

scholarly journals Secondary Organic Aerosol Formation via Multiphase Reaction of Hydrocarbons in Urban Atmospheres Using the CAMx Model Integrated with the UNIPAR model

2022 ◽  
Author(s):  
Zechen Yu ◽  
Myoseon Jang ◽  
Soontae Kim ◽  
Kyuwon Son ◽  
Sanghee Han ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Secondary Organic Aerosol ◽  
Model Simulation ◽  
Organic Aerosol ◽  
Phase Reaction ◽  
Aerosol Formation ◽  
Air Quality Model ◽  
Aqueous Reactions ◽  
Urban Atmospheres

Abstract. The prediction of Secondary Organic Aerosol (SOA) in regional scales is traditionally performed by using gas-particle partitioning models. In the presence of inorganic salted wet aerosols, aqueous reactions of semivolatile organic compounds can also significantly contribute to SOA formation. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model utilizes explicit gas chemistry to better predict SOA mass from multiphase reactions. In this work, the UNIPAR model was incorporated with the Comprehensive Air Quality Model with Extensions (CAMx) to predict the ambient concentration of organic matter (OM) in urban atmospheres during the Korean-United States Air Quality (2016 KORUS-AQ) campaign. The SOA mass predicted with the CAMx-UNIPAR model changed with varying levels of humidity and emissions and in turn, has the potential to improve the accuracy of OM simulations. The CAMx-UNIPAR model significantly improved the simulation of SOA formation under the wet condition, which often occurred during the KORUS-AQ campaign, through the consideration of aqueous reactions of reactive organic species and gas-aqueous partitioning. The contribution of aromatic SOA to total OM was significant during the low-level transport/haze period (24–31 May 2016) because aromatic oxygenated products are hydrophilic and reactive in aqueous aerosols. The OM mass predicted with the CAMx-UNIPAR model was compared with that predicted with the CAMx model integrated with the conventional two product model (SOAP). Based on estimated statistical parameters to predict OM mass, the performance of CAMx-UNIPAR was noticeably better than the conventional CAMx model although both SOA models underestimated OM compared to observed values, possibly due to missing precursor hydrocarbons such as sesquiterpenes, alkanes, and intermediate VOCs. The CAMx-UNIPAR model simulation suggested that in the urban areas of South Korea, terpene and anthropogenic emissions significantly contribute to SOA formation while isoprene SOA minimally impacts SOA formation.

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 ◽  
Desktop Computer ◽  
Policy Assessment ◽  
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 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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