Comprehensive evaluations of diurnal NO2 measurements during DISCOVER-AQ 2011: effects of resolution-dependent representation of NO x emissions

Nitrogen oxides (NO _x =NO+NO₂) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO₂ are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO₂ concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment - 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO₂ observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO₂ (O₃) surface concentrations during night-time, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO₂ TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NO _x emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO₂ vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NO _x emissions in the National Emissions Inventory (NEI) 2011.

Regional characteristics of NO2 column densities from Pandora observations during the MAPS-Seoul campaign

Vertical column density (VCD) of nitrogen dioxide (NO2) was measured using Pandora spectrometers at six sites on the Korean Peninsula during the Megacity Air Pollution Studies-Seoul (MAPS-Seoul) campaign from May to June 2015. To estimate the tropospheric NO₂ VCD, the stratospheric NO₂ VCD from the Ozone Monitoring Instrument (OMI) was subtracted from the total NO₂ VCD from Pandora. European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis wind data was used to analyze variations in tropospheric NO₂ VCD caused by wind patterns at each site. The Yonsei/SEO site was found to have the largest tropospheric NO₂ VCD (1.49 DU on average) from a statistical analysis of hourly tropospheric NO₂ VCD measurements. At rural sites, remarkably low NO₂ VCDs were observed. However, a wind field analysis showed that trans-boundary transport and emissions from domestic sources lead to an increase in tropospheric NO₂ VCD at NIER/BYI and KMA/AMY, respectively. At urban sites, high NO₂ VCD values were observed under conditions of low wind speed, which were influenced by local urban emissions. Tropospheric NO₂ VCD at HUFS/Yongin increases under conditions of significant transport from urban area of Seoul according to a correlation analysis that considers the transport time lag. Significant diurnal variations were found at urban sites during the MAPS-Seoul campaign, but not at rural sites, indicating that it is associated with diurnal patterns of NO₂ emissions from dense traffic.

Climate-driven ground-level ozone extreme in the fall over the Southeast United States

Ground-level ozone is adverse to human and vegetation health. High ground-level ozone concentrations usually occur over the United States in the summer, often referred to as the ozone season. However, observed monthly mean ozone concentrations in the southeastern United States were higher in October than July in 2010. The October ozone average in 2010 reached that of July in the past three decades (1980-2010). Our analysis shows that this extreme October ozone in 2010 over the Southeast is due in part to a dry and warm weather condition, which enhances photochemical production, air stagnation, and fire emissions. Observational evidence and modeling analysis also indicate that another significant contributor is enhanced emissions of biogenic isoprene, a major ozone precursor, from water-stressed plants under a dry and warm condition. The latter finding is corroborated by recent laboratory and field studies. This climate-induced biogenic control also explains the puzzling fact that the two extremes of high October ozone both occurred in the 2000s when anthropogenic emissions were lower than the 1980s and 1990s, in contrast to the observed decreasing trend of July ozone in the region. The occurrences of a drying and warming fall, projected by climate models, will likely lead to more active photochemistry, enhanced biogenic isoprene and fire emissions, an extension of the ozone season from summer to fall, and an increase of secondary organic aerosols in the Southeast, posing challenges to regional air quality management.

Satellite-based PM concentrations and their application to COPD in Cleveland, OH

A hybrid approach is proposed to estimate exposure to fine particulate matter (PM(2.5)) at a given location and time. This approach builds on satellite-based aerosol optical depth (AOD), air pollution data from sparsely distributed Environmental Protection Agency (EPA) sites and local time-space Kriging, an optimal interpolation technique. Given the daily global coverage of AOD data, we can develop daily estimate of air quality at any given location and time. This can assure unprecedented spatial coverage, needed for air quality surveillance and management and epidemiological studies. In this paper, we developed an empirical relationship between the 2 km AOD and PM(2.5) data from EPA sites. Extrapolating this relationship to the study domain resulted in 2.3 million predictions of PM(2.5) between 2000 and 2009 in Cleveland Metropolitan Statistical Area (MSA). We have developed local time-space Kriging to compute exposure at a given location and time using the predicted PM(2.5). Daily estimates of PM(2.5) were developed for Cleveland MSA between 2000 and 2009 at 2.5 km spatial resolution; 1.7 million (∼79.8%) of 2.13 million predictions required for multiyear and geographic domain were robust. In the epidemiological application of the hybrid approach, admissions for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) was examined with respect to time-space lagged PM(2.5) exposure. Our analysis suggests that the risk of AECOPD increases 2.3% with a unit increase in PM(2.5) exposure within 9 days and 0.05° (∼5 km) distance lags. In the aggregated analysis, the exposed groups (who experienced exposure to PM(2.5) >15.4 μg/m(3)) were 54% more likely to be admitted for AECOPD than the reference group. The hybrid approach offers greater spatiotemporal coverage and reliable characterization of ambient concentration than conventional in situ monitoring-based approaches. Thus, this approach can potentially reduce exposure misclassification errors in the conventional air pollution epidemiology studies.

Global air quality and climate

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.

Evidence of reactive aromatics as a major source of peroxy acetyl nitrate over China

We analyze the observations of near-surface peroxy acetyl nitrate (PAN) and its precursors in Beijing, China in August of 2007. The levels of PAN are remarkably high (up to 14 ppbv), surpassing those measured over other urban regions in recent years. Analyses employing a 1-D version of a chemical transport model (Regional chEmical and trAnsport Model, REAM) indicate that aromatic non-methane hydrocarbons (NMHCs) are the dominant (55-75%) PAN source. The major oxidation product of aromatics that produces acetyl peroxy radicals is methylglyoxal (MGLY). PAN and O(3) in the observations are correlated at daytime; aromatic NMHCs appear to play an important role in O(3) photochemistry. Previous NMHC measurements indicate the presence of reactive aromatics at high levels over broad polluted regions of China. Aromatics are often ignored in global and (to a lesser degree) regional 3D photochemical transport models; their emissions over China as well as photochemistry are quite uncertain. Our findings suggest that critical assessments of aromatics emissions and chemistry (such as the yields of MGLY) are necessary to understand and assess ozone photochemistry and regional pollution export in China.

East China plains: a "basin" of ozone pollution

Economic growth and associated pollution emissions in China are concentrated over three connected plains to the east In this work, we analyze an episode of highly elevated ozone over East China on June 9-14, 2004, using a 3-D chemical transport model. During this episode, the East China plains were under a high-pressure system, which suppressed the ventilation of pollutants from the boundary layer. Simulated ozone concentrations over a major fraction of East China reached high levels, all the way down to the Pearl River Delta region in the southern border. The convergence of pollutant emissions and population over the vast stretch of the geographically flat plains of East China makes the region susceptible to high-ozone exposure. During this episode, the high-03 region extended over an area >1 million km2, which hosts a population of >800 million people. Model results indicate that controlling anthropogenic NOx emissions effectively reduces the area with high-ozone exposure.

Quantifying the spatial and temporal variation of ground-level ozone in the rural Annapolis Valley, Nova Scotia, Canada using nitrite-impregnated passive samplers

The spatiotemporal variability of ground-level ozone (GLO) in the rural Annapolis Valley, Nova Scotia was investigated between August 29, 2006, and September 28, 2007, using Ogawa nitrite-impregnated passive diffusion samplers (PS). A total of 353 PS measurements were made at 17 ambient and 1 indoor locations over 18 sampling periods ranging from 2 to 4 weeks. The calculated PS detection limit was 0.8 +/- 0.02 parts per billion by volume (ppbv), for a 14-day sampling period. Duplicate samplers were routinely deployed at three sites and these showed excellent agreement (R2 values of 0.88 [n = 11], 0.95 [n = 17], and 0.96 [n = 17]), giving an overall PS imprecision value of 5.4%. Comparisons between PS and automated continuous ozone analyzers at three sites also demonstrated excellent agreement with R2 values of 0.82, 0.95, and 0.95, and gradients not significantly different from unity. The minimum, maximum, and mean (+/- 1 sigma) ambient annual GLO concentrations observed were 7.7, 72.1, and 34.3 +/- 10.1 ppbv, respectively. The three highest sampling sites had significantly greater (P = 0.032) GLO concentrations than three Valley floor sites, and there was a strong correlation between concentration and elevation (R2 = 0.82). Multivariate models were used to parameterize the observed GLO concentrations in terms of prevailing meteorology at an elevated site found at Kejimkujik National Park and also at a site on the Valley floor. Validation of the multivariate models using 30 months of historical meteorological data at these sites yielded R2 values of 0.70 (elevated site) and 0.61 (Valley floor). The mean indoor ozone concentration was 5.4 +/- 3.3 ppbv and related to ambient GLO concentration by the equation: indoor = 0.34 x ambient - 5.07. This study has demonstrated the suitability of PS for long-term studies of GLO over a wide geographic area and the effect of topographical and meteorological influences on GLO in this region.