scholarly journals The Impact of GEM and MM5 Modeled Meteorological Conditions on CMAQ Air Quality Modeling Results in Eastern Canada and the Northeastern United States

2006 ◽  
Vol 45 (11) ◽  
pp. 1525-1541 ◽  
Author(s):  
Steven C. Smyth ◽  
Dazhong Yin ◽  
Helmut Roth ◽  
Weimin Jiang ◽  
Michael D. Moran ◽  
...  
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Relative Humidity ◽  
Mesoscale Model ◽  
Measurement Data ◽  
Northeastern United States ◽  
Eastern Canada ◽  
Meteorological Model ◽  
The Impact

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) is currently the meteorological model most widely used as input into the Community Multiscale Air Quality (CMAQ) modeling system. In this study, meteorological fields produced by the Global Environmental Multiscale (GEM) meteorological model were compared with those from MM5, and the impact of using the two different modeled datasets as inputs to CMAQ was investigated. Two CMAQ model runs, differing only in meteorological inputs and meteorologically influenced emissions, were conducted for a domain covering eastern Canada and the northeastern United States for a 9-day period in July 1999. Comparison of the two modeled meteorological datasets with surface measurements revealed that GEM and MM5 gave comparable results. For a direct comparison of the two meteorological datasets the differences were small for pressure and temperature but larger for wind speed and relative humidity (RH). The variations in meteorological fields affect emissions and air quality results in differing ways and to differing degrees. The most influential meteorological field on emissions was temperature, which had a minor impact on on-road mobile emissions and a larger impact on biogenic emissions. Performance statistics for O3 and for particulate matter less than 10 μm and less than 2.5 μm (PM10, and PM2.5, respectively) show that GEM-based and MM5-based CMAQ results compare similarly to hourly measurement data, with minor statistical differences. A direct comparison of O3, PM10, PM2.5, and speciated PM2.5 showed that the results correlate to varying degrees and that the differences in RH affect total particulate matter (PM) mass and aerosol species concentrations significantly. Relative humidity affects total particle mass and particle diameters, which in turn affect PM2.5 and PM10 concentrations.

scholarly journals Satellite-based estimation of the impacts of summertime wildfires on PM<sub>2.5</sub> concentration in the United States

2021 ◽  
Vol 21 (14) ◽  
pp. 11243-11256
Author(s):  
Zhixin Xue ◽  
Pawan Gupta ◽  
Sundar Christopher
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Atmospheric Correction ◽  
Health Assessment ◽  
The United States ◽  
Ancillary Data ◽  
Leave One Out ◽  
The Impact

Abstract. Frequent and widespread wildfires in the northwestern United States and Canada have become the “new normal” during the Northern Hemisphere summer months, which significantly degrades particulate matter air quality in the United States. Using the mid-visible Multi Angle Implementation of Atmospheric Correction (MAIAC) satellite-derived aerosol optical depth (AOD) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) and other ancillary data, we quantify the impact of these fires on fine particulate matter concentration (PM2.5) air quality in the United States. We use a geographically weighted regression (GWR) method to estimate surface PM2.5 in the United States between low (2011) and high (2018) fire activity years. Our results indicate an overall leave-one-out cross-validation (LOOCV) R2 value of 0.797 with root mean square error (RMSE) between 3 and 5 µg m−3. Our results indicate that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire-active year and that 15 of these states have PM2.5 concentrations more than 2 times that of the inactive year. Furthermore, these fires increased the daily mean surface PM2.5 concentrations in Washington and Oregon by 38 to 259 µg m−3, posing significant health risks especially to vulnerable populations. Our results also show that the GWR model can be successfully applied to PM2.5 estimations from wildfires, thereby providing useful information for various applications such as public health assessment.

scholarly journals Satellite-based Estimation of the Impacts of Summertime Wildfires on Particulate Matter Air Quality in United States

2020 ◽  
Author(s):  
Zhixin Xue ◽  
Pawan Gupta ◽  
Sundar Christopher
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Atmospheric Correction ◽  
Health Assessment ◽  
The United States ◽  
Ancillary Data ◽  
Weather Forecasts ◽  
The Impact

Abstract. Frequent and widespread wildfires in North Western United States and Canada has become the new normal during the northern hemisphere summer months, which degrades particulate matter air quality in the United States significantly. Using the mid-visible Multi Angle Implementation of Atmospheric Correction (MAIAC) satellite-derived Aerosol Optical Depth (AOD) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) and other ancillary data, we quantify the impact of these fires on fine particulate matter air quality (PM2.5) in the United States. We use a Geographically Weighted Regression method to estimate surface PM2.5 in the United States between low (2011) and high (2018) fire activity years. Our results indicate that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire active year and 15 of these states have PM2.5 concentrations more than 2 times than that of the inactive year. Furthermore, these fires increased daily mean surface PM2.5 concentrations in Washington and Oregon by 38 to 259 µgm−3 posing significant health risks especially to vulnerable populations. Our results also show that the GWR model can be successfully applied to PM2.5 estimations from wildfires thereby providing useful information for various applications including public health assessment.

scholarly journals The effects of global change upon United States air quality

2015 ◽  
Vol 15 (21) ◽  
pp. 12645-12665 ◽  
Author(s):  
R. Gonzalez-Abraham ◽  
S. H. Chung ◽  
J. Avise ◽  
B. Lamb ◽  
E. P. Salathé ◽  
...  
Keyword(s):  
United States ◽  
Land Use ◽  
Particulate Matter ◽  
Air Quality ◽  
The United States ◽  
Biogenic Emissions ◽  
Anthropogenic Emissions ◽  
The Us ◽  
The Impact ◽  
Global Emissions

Abstract. To understand more fully the effects of global changes on ambient concentrations of ozone and particulate matter with aerodynamic diameter smaller than 2.5 μm (PM2.5) in the United States (US), we conducted a comprehensive modeling effort to evaluate explicitly the effects of changes in climate, biogenic emissions, land use and global/regional anthropogenic emissions on ozone and PM2.5 concentrations and composition. Results from the ECHAM5 global climate model driven with the A1B emission scenario from the Intergovernmental Panel on Climate Change (IPCC) were downscaled using the Weather Research and Forecasting (WRF) model to provide regional meteorological fields. We developed air quality simulations using the Community Multiscale Air Quality Model (CMAQ) chemical transport model for two nested domains with 220 and 36 km horizontal grid cell resolution for a semi-hemispheric domain and a continental United States (US) domain, respectively. The semi-hemispheric domain was used to evaluate the impact of projected global emissions changes on US air quality. WRF meteorological fields were used to calculate current (2000s) and future (2050s) biogenic emissions using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). For the semi-hemispheric domain CMAQ simulations, present-day global emissions inventories were used and projected to the 2050s based on the IPCC A1B scenario. Regional anthropogenic emissions were obtained from the US Environmental Protection Agency National Emission Inventory 2002 (EPA NEI2002) and projected to the future using the MARKet ALlocation (MARKAL) energy system model assuming a business as usual scenario that extends current decade emission regulations through 2050. Our results suggest that daily maximum 8 h average ozone (DM8O) concentrations will increase in a range between 2 to 12 parts per billion (ppb) across most of the continental US. The highest increase occurs in the South, Central and Midwest regions of the US due to increases in temperature, enhanced biogenic emissions and changes in land use. The model predicts an average increase of 1–6 ppb in DM8O due to projected increase in global emissions of ozone precursors. The effects of these factors are only partially offset by reductions in DM8O associated with decreasing US anthropogenic emissions. Increases in PM2.5 levels between 4 and 10 μg m−3 in the Northeast, Southeast, Midwest and South regions are mostly a result of increase in primary anthropogenic particulate matter (PM), enhanced biogenic emissions and land use changes. Changes in boundary conditions shift the composition but do not alter overall simulated PM2.5 mass concentrations.

Impact of Domain Size on Modeled Ozone Forecast for the Northeastern United States

2008 ◽  
Vol 47 (2) ◽  
pp. 443-461 ◽  
Author(s):  
Pius Lee ◽  
Daiwen Kang ◽  
Jeff McQueen ◽  
Marina Tsidulko ◽  
Mary Hart ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
The United States ◽  
Skill Score ◽  
Northeastern United States ◽  
Forecast System ◽  
Air Quality Forecast ◽  
Model Domain ◽  
The Impact ◽  
The U.S

Abstract This study investigates the impact of model domain extent and the specification of lateral boundary conditions on the forecast quality of air pollution constituents in a specific region of interest. A developmental version of the national Air Quality Forecast System (AQFS) has been used in this study. The AQFS is based on the NWS/NCEP Eta Model (recently renamed the North American Mesoscale Model) coupled with the U.S. Environmental Protection Agency Community Multiscale Air Quality (CMAQ) model. This coupled Eta–CMAQ modeling system provided experimental air quality forecasts for the northeastern region of the United States during the summers of 2003 and 2004. The initial forecast over the northeastern United States was approved for operational deployment in September 2004. The AQFS will provide forecast coverage for the entire United States in the near future. In a continuing program of phased development to extend the geographical coverage of the forecast, the developmental version of AQFS has undergone two domain expansions. Hereinafter, this “developmental” domain-expanded forecast system AQFS will be dubbed AQFS-β. The current study evaluates the performance of AQFS-β for the northeastern United States using three domain sizes. Quantitative comparisons of forecast results with compiled observation data from the U.S. Aerometric Information Retrieval Now (AIRNOW) network were performed for each model domain, and interdomain comparisons were made for the regions of overlap. Several forecast skill score measures have been employed. Based on the categorical statistical metric of the critical success index, the largest domain achieved the highest skill score. This conclusion should catapult the implementation of the largest domain to attain the best forecast performance whenever the operational resource and criteria permit.

Monitoring air quality in class I wilderness areas of the northeastern United States using lichens and bryophytes

2016 ◽  
Author(s):  
Alison C. Dibble ◽  
James W. Hinds ◽  
Ralph Perron ◽  
Natalie Cleavitt ◽  
Richard L. Poirot ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Class I ◽  
Northeastern United States ◽  
Wilderness Areas

scholarly journals The impact of measures to reduce ambient air PM<sub>10</sub> concentrations originating from road dust, evaluated for a street canyon in Helsinki

2019 ◽  
Vol 19 (17) ◽  
pp. 11199-11212 ◽  
Author(s):  
Ana Stojiljkovic ◽  
Mari Kauhaniemi ◽  
Jaakko Kukkonen ◽  
Kaarle Kupiainen ◽  
Ari Karppinen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Street Canyon ◽  
Dust Emission ◽  
Road Dust ◽  
Ambient Air ◽  
Air Quality Measurements ◽  
Emission Models ◽  
The Impact ◽  
Quality Measurements

Abstract. We have numerically evaluated how effective selected potential measures would be for reducing the impact of road dust on ambient air particulate matter (PM10). The selected measures included a reduction of the use of studded tyres on light-duty vehicles and a reduction of the use of salt or sand for traction control. We have evaluated these measures for a street canyon located in central Helsinki for four years (2007–2009 and 2014). Air quality measurements were conducted in the street canyon for two years, 2009 and 2014. Two road dust emission models, NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and FORE (Forecasting Of Road dust Emissions), were applied in combination with the Operational Street Pollution Model (OSPM), a street canyon dispersion model, to compute the street increments of PM10 (i.e. the fraction of PM10 concentration originating from traffic emissions at the street level) within the street canyon. The predicted concentrations were compared with the air quality measurements. Both road dust emission models reproduced the seasonal variability of the PM10 concentrations fairly well but under-predicted the annual mean values. It was found that the largest reductions of concentrations could potentially be achieved by reducing the fraction of vehicles that use studded tyres. For instance, a 30 % decrease in the number of vehicles using studded tyres would result in an average decrease in the non-exhaust street increment of PM10 from 10 % to 22 %, depending on the model used and the year considered. Modelled contributions of traction sand and salt to the annual mean non-exhaust street increment of PM10 ranged from 4 % to 20 % for the traction sand and from 0.1 % to 4 % for the traction salt. The results presented here can be used to support the development of optimal strategies for reducing high springtime particulate matter concentrations originating from road dust.

scholarly journals Association of temporary Environmental Protection Agency regulation suspension with industrial economic viability and local air quality in California, United States

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Emily Chang ◽  
Kenneth Zhang ◽  
Margaret Paczkowski ◽  
Sara Kohler ◽  
Marco Ribeiro
Keyword(s):  
United States ◽  
Air Quality ◽  
Environmental Protection ◽  
Environmental Protection Agency ◽  
Manufacturing Industry ◽  
Economic Viability ◽  
Treatment Control ◽  
Oil Refineries ◽  
Pollution Levels ◽  
The Impact

Abstract Background This study seeks to answer two questions about the impacts of the 2020 Environmental Protection Agency’s enforcement regulation rollbacks: is this suspension bolstering the economic viability of industries as oil and manufacturing executives claim they will and are these regulations upholding the agency’s mission of protecting the environment? Results To answer the former question, we utilized 6 months of state employment level data from California, United States, as a method of gauging the economic health of agency-regulated industries. We implemented a machine learning model to predict weekly employment data and a t-test to indicate any significant changes in employment. We found that, following California's state-issued stay-at-home order and the agency’s regulation suspension, oil and certain manufacturing industries had statistically significant lower employment values. To answer the latter question, we used 10 years of PM2.5 levels in California, United States, as a metric for local air quality and treatment–control county pairs to isolate the impact of regulation rollbacks from the impacts of the state lockdown. Using the agency’s data, we performed a t-test to determine whether treatment–control county pairs experienced a significant change in PM2.5 levels. Even with the statewide lockdown—a measure we hypothesized would correlate with decreased mobility and pollution levels—in place, counties with oil refineries experienced the same air pollution levels when compared to historical data averaged from the years 2009 to 2019. Conclusions In contrast to the expectation that the suspension would improve the financial health of the oil and manufacturing industry, we can conclude that these industries are not witnessing economic growth with the suspension and state shutdown in place. Additionally, counties with oil refineries could be taking advantage of these rollbacks to continue emitting the same amount of PM2.5, in spite of state lockdowns. For these reasons, we ask international policymakers to reconsider the suspension of enforcement regulations as these actions do not fulfill their initial expectations. We recommend the creation and maintenance of pollution control and prevention programs that develop emission baselines, mandate the construction of pollution databases, and update records of pollution emissions.

scholarly journals Quantification of Non-Exhaust Particulate Matter Traffic Emissions and the Impact of COVID-19 Lockdown at London Marylebone Road

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 190
Author(s):  
William Hicks ◽  
Sean Beevers ◽  
Anja H. Tremper ◽  
Gregor Stewart ◽  
Max Priestman ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Measurement Data ◽  
Emission Factors ◽  
Meteorological Conditions ◽  
Traffic Emissions ◽  
Atmospheric Particulate Matter ◽  
Exhaust Emission ◽  
Brake Wear ◽  
The Impact ◽  
Exhaust Particulate

This research quantifies current sources of non-exhaust particulate matter traffic emissions in London using simultaneous, highly time-resolved, atmospheric particulate matter mass and chemical composition measurements. The measurement campaign ran at Marylebone Road (roadside) and Honor Oak Park (background) urban monitoring sites over a 12-month period between 1 September 2019 and 31 August 2020. The measurement data were used to determine the traffic increment (roadside–background) and covered a range of meteorological conditions, seasons, and driving styles, as well as the influence of the COVID-19 “lockdown” on non-exhaust concentrations. Non-exhaust particulate matter (PM)10 concentrations were calculated using chemical tracer scaling factors for brake wear (barium), tyre wear (zinc), and resuspension (silicon) and as average vehicle fleet non-exhaust emission factors, using a CO2 “dilution approach”. The effect of lockdown, which saw a 32% reduction in traffic volume and a 15% increase in average speed on Marylebone Road, resulted in lower PM10 and PM2.5 traffic increments and brake wear concentrations but similar tyre and resuspension concentrations, confirming that factors that determine non-exhaust emissions are complex. Brake wear was found to be the highest average non-exhaust emission source. In addition, results indicate that non-exhaust emission factors were dependent upon speed and road surface wetness conditions. Further statistical analysis incorporating a wider variability in vehicle mix, speeds, and meteorological conditions, as well as advanced source apportionment of the PM measurement data, were undertaken to enhance our understanding of these important vehicle sources.

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