Improved Estimation of Trends in U.S. Ozone Concentrations Adjusted for Interannual Variability in Meteorological Conditions.

Daily maximum 8-hour average (MDA8) ozone (O3) concentrations are well-known to be influenced by local meteorological conditions, which vary across both daily and seasonal temporal scales. Previous studies have adjusted long-term trends in O3 concentrations for meteorological effects using various statistical and mathematical methods in order to get a better estimate of the long-term changes in O3 concentrations due to changes in precursor emissions such as nitrogen oxides (NOX) and volatile organic compounds (VOCs). In this work, the authors present improvements to the current method used by the United States Environmental Protection Agency (US EPA) to adjust O3 trends for meteorological influences by making refinements to the input data sources and by allowing the underlying statistical model to vary locally using a variable selection procedure. The current method is also expanded by using a quantile regression model to adjust trends in the 90th and 98th percentiles of the distribution of MDA8 O3 concentrations, allowing for a better understanding of the effects of local meteorology on peak O3 levels in addition to seasonal average concentrations. The revised method is used to adjust trends in the May to September mean, 90th percentile, and 98th percentile MDA8 O3 concentrations at over 700 monitoring sites in the U.S. for years 2000 to 2016. The utilization of variable selection and quantile regression allow for a more in-depth understanding of how weather conditions affect O3 levels in the U.S. This represents a fundamental advancement in our ability to understand how interannual variability in weather conditions in the U.S. may impact attainment of the O3 National Ambient Air Quality Standards (NAAQS).

A Functional Data Analysis of Spatiotemporal Trends and Variation in Fine Particulate Matter.

In this paper we illustrate the application of modern functional data analysis methods to study the spatiotemporal variability of particulate matter components across the United States. The approach models the pollutant annual profiles in a way that describes the dynamic behavior over time and space. This new technique allows us to predict yearly profiles for locations and years at which data are not available and also offers dimension reduction for easier visualization of the data. Additionally it allows us to study changes of pollutant levels annually or for a particular season. We apply our method to daily concentrations of two particular components of PM2.5 measured by two networks of monitoring sites across the United States from 2003 to 2015. Our analysis confirms existing findings and additionally reveals new trends in the change of the pollutants across seasons and years that may not be as easily determined from other common approaches such as Kriging.

Attribution of the United States "warming hole": aerosol indirect effect and precipitable water vapor.

Aerosols can influence the climate indirectly by acting as cloud condensation nuclei and/or ice nuclei, thereby modifying cloud optical properties. In contrast to the widespread global warming, the central and south central United States display a noteworthy overall cooling trend during the 20(th) century, with an especially striking cooling trend in summertime daily maximum temperature (Tmax) (termed the U.S. "warming hole"). Here we used observations of temperature, shortwave cloud forcing (SWCF), longwave cloud forcing (LWCF), aerosol optical depth and precipitable water vapor as well as global coupled climate models to explore the attribution of the "warming hole". We find that the observed cooling trend in summer Tmax can be attributed mainly to SWCF due to aerosols with offset from the greenhouse effect of precipitable water vapor. A global coupled climate model reveals that the observed "warming hole" can be produced only when the aerosol fields are simulated with a reasonable degree of accuracy as this is necessary for accurate simulation of SWCF over the region. These results provide compelling evidence of the role of the aerosol indirect effect in cooling regional climate on the Earth. Our results reaffirm that LWCF can warm both winter Tmax and Tmin.

Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study.

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.

The New England Air Quality Forecasting Pilot Program: development of an evaluation protocol and performance benchmark.

The National Oceanic and Atmospheric Administration recently sponsored the New England Forecasting Pilot Program to serve as a "test bed" for chemical forecasting by providing all of the elements of a National Air Quality Forecasting System, including the development and implementation of an evaluation protocol. This Pilot Program enlisted three regional-scale air quality models, serving as prototypes, to forecast ozone (O3) concentrations across the northeastern United States during the summer of 2002. A suite of statistical metrics was identified as part of the protocol that facilitated evaluation of both discrete forecasts (observed versus modeled concentrations) and categorical forecasts (observed versus modeled exceedances/nonexceedances) for both the maximum 1-hr (125 ppb) and 8-hr (85 ppb) forecasts produced by each of the models. Implementation of the evaluation protocol took place during a 25-day period (August 5-29), utilizing hourly O3 concentration data obtained from over 450 monitors from the U.S. Environment Protection Agency's Air Quality System network.