scholarly journals Nucleation Events During the Pittsburgh Air Quality Study: Description and Relation to Key Meteorological, Gas Phase, and Aerosol Parameters Special Issue ofAerosol Science and Technologyon Findings from the Fine Particulate Matter Supersites Program

2004 ◽  
Vol 38 (sup1) ◽  
pp. 253-264 ◽  
Author(s):  
Charles O. Stanier ◽  
Andrey Y. Khlystov ◽  
Spyros N. Pandis
2008 ◽  
Vol 42 (29) ◽  
pp. 6897-6904 ◽  
Author(s):  
Kerry R. Bullock ◽  
Rachelle M. Duvall ◽  
Gary A. Norris ◽  
Stephen R. McDow ◽  
Michael D. Hays

2020 ◽  
Author(s):  
Chinmay Jena ◽  
Sachin D. Ghude ◽  
Rachana Kulkarni ◽  
Sreyashi Debnath ◽  
Rajesh Kumar ◽  
...  

Abstract. Elevated levels of fine particulate matter (PM2.5) during winter-time have become one of the most important environmental concerns over the Indo-Gangetic Plain (IGP) region of India, and particularly for Delhi. Accurate reconstruction of PM2.5, its optical properties, and dominant chemical components over this region is essential to evaluate the performance of the air quality models. In this study, we investigated the effect of three different aerosol mechanisms coupled with gas-phase chemical schemes on simulated PM2.5 mass concentration in Delhi using the Weather Research and Forecasting model with the Chemistry module (WRF-Chem). The model was employed to cover the entire northern region of India at 10 km horizontal spacing. Results were compared with comprehensive filed data set on dominant PM2.5 chemical compounds from the Winter Fog Experiment (WiFEX) at Delhi, and surface PM2.5 observations in Delhi (17 sites), Punjab (3 sites), Haryana (4 sites), Uttar Pradesh (7 sites) and Rajasthan (17 sites). The Model for Ozone and Related Chemical Tracers (MOZART-4) gas-phase chemical mechanism coupled with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) aerosol scheme (MOZART-GOCART) were selected in the first experiment as it is currently employed in the operational air quality forecasting system of Ministry of Earth Sciences (MoES), Government of India. Other two simulations were performed with the MOZART-4 gas-phase chemical mechanism coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOZART-MOSAIC), and Carbon Bond 5 (CB-05) gas-phase mechanism couple with the Modal Aerosol Dynamics Model for Europe/Secondary Organic Aerosol Model (CB05-MADE/SORGAM) aerosol mechanisms. The evaluation demonstrated that chemical mechanisms affect the evolution of gas-phase precursors and aerosol processes, which in turn affect the optical depth and overall performance of the model for PM2.5. All the three coupled schemes, MOZART-GOCART, MOZART-MOSAIC, and CB05-MADE/SORGAM, underestimate the observed concentrations of major aerosol composition (NO3−, SO42−, Cl−, BC, OC, and NH4+) and precursor gases (HNO3, NH3, SO2, NO2, and O3) over Delhi. Comparison with observations suggests that the simulations using MOZART-4 gas-phase chemical mechanism with MOSAIC aerosol performed better in simulating aerosols over Delhi and its optical depth over the IGP. The lowest NMB (−18.8 %, MB = −27.4 μg/m3) appeared for the simulations using MOZART-MOSAIC scheme, whereas the NMB was observed 32.5 % (MB = −47.5 μg/m3) for CB05-MADE/SORGAM and −53.3 % (MB = −78 μg/m3) for MOZART-GOCART scheme.


Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  

This paper describes a quasi-operational regional air quality forecasting system for the contiguous United States (CONUS) developed at the National Center for Atmospheric Research (NCAR) to support air quality decision-making, field campaign planning, early identification of model errors and biases, and support the atmospheric science community in their research. This system aims to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA), not to replace them. A publicly available information dissemination system has been established that displays various air quality products, including a near-real-time evaluation of the model forecasts. Here, we report the performance of our air quality forecasting system in simulating meteorology and fine particulate matter (PM2.5) for the first year after our system started, i.e., 1 June 2019 to 31 May 2020. Our system shows excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but shows relatively larger errors in wind speed. The model also captures the seasonal cycle of surface PM2.5 very well in different regions and for different types of sites (urban, suburban, and rural) in the CONUS with a mean bias smaller than 1 µg m−3. The skill of the air quality forecasts remains fairly stable between the first and second days of the forecasts. Our air quality forecast products are publicly available at a NCAR webpage. We invite the community to use our forecasting products for their research, as input for urban scale (<4 km), air quality forecasts, or the co-development of customized products, just to name a few applications.


2017 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Melissa Anne Hart ◽  
Ningbo Jiang

Abstract. Internationally, severe wildfires are an escalating problem likely to worsen given projected changes to climate. Hazard reduction burns (HRB) are used to suppress wildfire occurrences, but they generate considerable emissions of atmospheric fine particulate matter, which depending upon prevailing atmospheric conditions, can degrade air quality. Our objectives are to improve understanding of the relationships between meteorological conditions and air quality during HRBs in Sydney, Australia. We identify the primary meteorological covariates linked to high PM2.5 pollution (particulates


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