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 Seasonal Simulation of Tropospheric Ozone over the Midwestern and Northeastern United States: An Application of a Coupled Regional Climate and Air Quality Modeling System

2007 ◽  
Vol 46 (7) ◽  
pp. 945-960 ◽  
Author(s):  
Ho-Chun Huang ◽  
Xin-Zhong Liang ◽  
Kenneth E. Kunkel ◽  
Michael Caughey ◽  
Allen Williams
Keyword(s):  
United States ◽  
Air Quality ◽  
Tropospheric Ozone ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Future Climate ◽  
Climate Projections ◽  
Northeastern United States ◽  
Ozone Episodes

Abstract The impacts of air pollution on the environment and human health could increase as a result of potential climate change. To assess such possible changes, model simulations of pollutant concentrations need to be performed at climatic (seasonal) rather than episodic (days) time scales, using future climate projections from a general circulation model. Such a modeling system was employed here, consisting of a regional climate model (RCM), an emissions model, and an air quality model. To assess overall model performance with one-way coupling, this system was used to simulate tropospheric ozone concentrations in the midwestern and northeastern United States for summer seasons between 1995 and 2000. The RCM meteorological conditions were driven by the National Centers for Environmental Prediction/Department of Energy global reanalysis (R-2) using the same procedure that integrates future climate model projections. Based on analyses for several urban and rural areas and regional domains, fairly good agreement with observations was found for the diurnal cycle and for several multiday periods of high ozone episodes. Even better agreement occurred between monthly and seasonal mean quantities of observed and model-simulated values. This is consistent with an RCM designed primarily to produce good simulations of monthly and seasonal mean statistics of weather systems.

scholarly journals Air Quality Impacts of Distributed Energy Resources Implemented in the Northeastern United States

2008 ◽  
Vol 58 (7) ◽  
pp. 902-912 ◽  
Author(s):  
Marc Carreras-Sospedra ◽  
Donald Dabdub ◽  
Jacob Brouwer ◽  
Eladio Knipping ◽  
Naresh Kumar ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy ◽  
Northeastern United States

Towards Disentangling Lockdown-Driven Air Quality Changes in the Northeastern U.S.

2021 ◽  
pp. 2150017
Author(s):  
Christian Braneon ◽  
Robert Field ◽  
Edmund Seto ◽  
Kai Chen ◽  
Kathryn McConnell ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Severe Acute Respiratory Syndrome ◽  
Economic Activity ◽  
System Response ◽  
Quality Changes ◽  
Earth System ◽  
Northeastern United States ◽  
Response Measures ◽  
Pandemic Response

In the absence of preventive therapies or effective treatment for most cases of coronavirus disease 2019 (COVID-19), governments worldwide have sought to minimize person-to-person severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission through a variety of lock-down measures and social distancing policies. Extreme events like the COVID-19 pandemic present a tremendous opportunity to make quantitative connections between changes in anthropogenic forcing, social and economic activity, and the related Earth system response. In this paper, we examine the air quality impacts associated with the pandemic response measures in the Northeastern United States.

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.

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.

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