scholarly journals Description and Evaluation of the Fine Particulate Matter Forecasts in the NCAR Regional Air Quality Forecasting System

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 302
Author(s):  
Rajesh Kumar ◽  
Piyush Bhardwaj ◽  
Gabriele Pfister ◽  
Carl Drews ◽  
Shawn Honomichl ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Information Dissemination ◽  
Fine Particulate Matter ◽  
Model Errors ◽  
Air Quality Forecast ◽  
Fine Particulate ◽  
Regional Air Quality ◽  
Forecasting System ◽  
Air Quality Forecasting

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.

A quasi-operational air quality forecasting system for the contiguous United States (CONUS) 

2021 ◽  
Author(s):  
Rajesh Kumar ◽  
Gabriele Pfister ◽  
Piyush Bhardwaj
Keyword(s):  
United States ◽  
Air Quality ◽  
Information Dissemination ◽  
Surface Ozone ◽  
High Surface ◽  
Model Errors ◽  
Grid Spacing ◽  
Air Quality Forecast ◽  
Forecasting System ◽  
Air Quality Forecasting

&lt;p&gt;We present a research system for regional air quality forecasting over&amp;#160; the contiguous United States (CONUS). This system has been developed at the National Center for Atmospheric Research (NCAR) to support community model development, allow early identification of model errors and biases, and support the atmospheric science community in their research. At the same time, it assists field campaign planning and air quality decision-making. The forecasts aim to complement the operational air quality forecasts produced by the National Oceanic and Atmospheric Administration (NOAA) and 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. Our forecasting system has been producing a 48-h forecast every day at 12 km x 12 km grid spacing over the entire CONUS since June 2019 and at 4 km x 4 km grid spacing in Colorado since June 2020. Here, we will report on the performance of our air quality forecasting system in simulating meteorology, PM2.5, ozone, and NOx for the period of 1 June 2019 to 31 December 2020. Our system showed excellent skill in capturing hourly to daily variations in temperature, surface pressure, relative humidity, water vapor mixing ratios, and wind direction but showed, in parts, relatively larger errors in wind speed. The model captured the seasonal cycle of surface PM2.5 and ozone very well in different regions of CONUS and at different types of sites (urban, suburban, and rural) but generally overestimates summertime surface ozone and fails to capture very high surface PM2.5 events. These shortcomings are being addressed in current work. 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 https://www.acom.ucar.edu/firex-aq/forecast.shtml and we invite the community to use our forecasting products for their research, as input for urban scale (&lt; 4 km) air quality forecasts, or the co-development of customized products just to name a few applications.&lt;/p&gt;

Regional Air Quality:  Local and Interstate Impacts of NOxand SO2Emissions on Ozone and Fine Particulate Matter in the Eastern United States

2007 ◽  
Vol 41 (13) ◽  
pp. 4677-4689 ◽  
Author(s):  
Michelle S. Bergin ◽  
Jhih-Shyang Shih ◽  
Alan J. Krupnick ◽  
James W. Boylan ◽  
James G. Wilkinson ◽  
...  
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Eastern United States ◽  
Fine Particulate ◽  
Regional Air Quality

scholarly journals Meteorological controls on atmospheric particulate pollution during hazard reduction burns

2017 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Melissa Anne Hart ◽  
Ningbo Jiang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Meteorological Conditions ◽  
Atmospheric Conditions ◽  
Hazard Reduction ◽  
Particulate Pollution ◽  
Fine Particulate ◽  
Projected Changes ◽  
Sydney Australia

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

scholarly journals Impacts of historical climate and land cover changes on fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia over 1980–2010

2016 ◽  
Author(s):  
Yu Fu ◽  
Amos P. K. Tai ◽  
Hong Liao
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
East Asia ◽  
Fine Particulate Matter ◽  
Anthropogenic Emissions ◽  
Voc Emissions ◽  
Fine Particulate

Abstract. To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981–1985 and 2007–2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0–12.0 μg m−3 in northern China, but an increase in summertime PM2.5 by 6.0–8.0 μg m−3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2–0.8 μg m−3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (−2.1 to +1.3 μg m−3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (−0.4 to +1.2 μg m−3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by −12.0 to +12.0 μg m−3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.

scholarly journals A low-cost monitor for measurement of fine particulate matter and aerosol optical depth – Part 2: Citizen-science pilot campaign in northern Colorado

2019 ◽  
Vol 12 (12) ◽  
pp. 6385-6399 ◽  
Author(s):  
Bonne Ford ◽  
Jeffrey R. Pierce ◽  
Eric Wendt ◽  
Marilee Long ◽  
Shantanu Jathar ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Aerosol Optical Depth ◽  
Citizen Science ◽  
Optical Depth ◽  
Spatial Scales ◽  
Fine Particulate Matter ◽  
Optical Measurements ◽  
Fine Particulate ◽  
Northern Colorado

Abstract. A pilot field campaign was conducted in the fall and winter of 2017 in northern Colorado to test the deployment of the Aerosol Mass and Optical Depth (AMOD) instrument as part of the Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) network. Citizen scientists were recruited to set up the device to take filter and optical measurements of aerosols in their backyards. The goal of the network is to provide more surface particulate matter and aerosol optical depth (AOD) measurements to increase the spatial and temporal resolution of ratios of fine particulate matter (PM2.5) to AOD and to improve satellite-based estimates of air quality. Participants collected 65 filters and 160 multi-wavelength AOD measurements, from which 109 successful PM2.5 : AOD ratios were calculated. We show that PM2.5, AOD, and their ratio (PM2.5 : AOD) often vary substantially over relatively short spatial scales; this spatial variation is not typically resolved by satellite- and model-based PM2.5 exposure estimates. The success of the pilot campaign suggests that citizen-science networks are a viable means for providing new insight into surface air quality. We also discuss lessons learned and AMOD design modifications, which will be used in future wider deployments of the CEAMS network.

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