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Archived Ozone Design Values (ODVs) provide smoothed temporal records of maximum ozone concentrations impacting monitoring sites throughout the US. Utilizing time series of ODVs recorded at sites along the US West Coast, we separately estimate ODV contributions from US background ozone and from production driven by US anthropogenic precursor emissions. Sondes launched from Trinidad Head in northern California measure the vertical distribution of baseline ozone transported ashore from the Pacific; this profile is reflected in the increase of the US background ODV contribution with monitoring site elevation in both rural and urban areas. The ODVs that would result from US background ozone alone are small at coastal, sea level locations (average ~45 ppb), but increase with altitude; above 1 km US background ODVs can exceed 60 ppb. US background ozone contributions now constitute the majority of the maximum ODVs throughout the US west coast region, including the Los Angeles urban area, which records the country's highest ODVs. US anthropogenic emissions presently cause enhancements of 35 to 55 ppb to the maximum ODVs in the Los Angeles area; thus, local emission controls can further reduce ozone even though the background contribution is larger. In other US west coast urban areas ODV enhancements from US anthropogenic emissions are much smaller than the US background ODV contribution. The past decrease in US anthropogenic ODV enhancements from emission controls is larger than generally realized – a factor of more than 6 from 1980 to 2020, while US background ODV contributions varied to only a small extent over those four decades. Wildfire impacts on ODVs are significant in urban areas of the Pacific Northwest, but not over the vast northern US rural region. There is an indication that agricultural emissions of nitrogen oxides in California's Salinas Valley increase downwind maximum ODVs by 5–10 ppb. Implications: In 2020 the ozone design values (ODVs) resulting from transported background ozone alone are now larger than the ODV enhancements from US anthropogenic precursor emissions, even in the Los Angeles urban area, where the nation's highest ODVs are recorded. The US anthropogenic ODV enhancements have been reduced by more than a factor of 6 from 1980 to 2020. The maximum US background ODV contributions have varied somewhat, but in each of the US west coast urban areas it was 60 ppb or larger in 2000. These contributions are so large that reducing maximum urban ODVs to the 70 ppb required by the 2015 ozone NAAQS is very difficult. There remains relatively little room for further reducing ODVs through domestic emission controls alone. From this perspective, degraded US ozone air quality in the western US is primarily due to the US background ozone contribution, with the US anthropogenic enhancement making a significant, but smaller contribution. Notably, the US background ODV has slowly decreased (~1 ppb decade−1; Parrish, Derwent, and Faloona 2021) since the mid-2000s; cooperative, international emission control efforts aimed at continuing or even accelerating this background ozone decrease may be an effective approach to further ODV reductions, since the US background ODV is largely due to a hemisphere-wide, transported reservoir of ozone with contributions from all northern midlatitude continents. Given the major contribution of background ozone to observed ODVs, future reviews of the ozone NAAQS will be better informed if observational-based estimates of background ODV contributions are considered, in addition to model-derived estimates upon which past reviews have solely relied. [ABSTRACT FROM AUTHOR]

US ambient ozone concentrations have two components: US background ozone and enhancements produced from the country's anthropogenic precursor emissions. Only the enhancements effectively respond to national emission controls. We investigate the temporal evolution and spatial variability in the largest ozone concentrations, i.e., those that define the ozone design value (ODV) upon which the National Ambient Air Quality Standard (NAAQS) is based, within the northern tier of US states. We focus on two regions: rural western states, with only small anthropogenic precursor emissions, and the urbanized northeastern states, which include the New York City urban area, the nation's most populated. The US background ODV (i.e., the ODV remaining if US anthropogenic precursor emissions were reduced to zero) is estimated to vary from 54 to 63 ppb in the rural western states and to be smaller and nearly constant (45.8±3.0 ppb) throughout the northeastern states. These US background ODVs correspond to 65 % to 90 % of the 2015 NAAQS of 70 ppb. Over the past 2 to 3 decades US emission control efforts have decreased the US anthropogenic ODV enhancements at an approximately exponential rate, with an e -folding time constant of ∼22 years. These ODV enhancements are relatively large in the northeastern US, with state maximum ODV enhancements of ∼35 –64 ppb in 2000, but are not discernible in the rural western states. The US background ODV contribution is significantly larger than the present-day ODV enhancements due to photochemical production from US anthropogenic precursor emissions in the urban as well as the rural regions investigated. Forward projections of past trends suggest that average maximum ODVs in northeastern US will drop below the NAAQS of 70 ppb by about 2021, assuming that the exponential decrease in the ODV enhancements can be maintained and the US background ODV remains constant. This estimate is much more optimistic than in the Los Angeles urban area, where a similar approach estimates the maximum ODV to reach 70 ppb in ∼2050 (Parrish et al., 2017a). The primary reason for this large difference is the significantly higher US ODV background (62.0±2.0 ppb) estimated for the Los Angeles urban area. The approach used in this work has some unquantified uncertainties that are discussed. Models can also estimate US background ODVs; some of those results are shown to correlate with the observationally based estimates derived here (r2 values for different models are ∼0.31 to 0.90), but they are on average systematically lower by 4 to 13 ppb. Further model improvement is required until their output can accurately reproduce the time series and spatial variability in observed ODVs. Ideally, the uncertainties in the model and observationally based approaches can then be reduced through additional comparisons. [ABSTRACT FROM AUTHOR]

Abstract: Methane (CH4) and carbon monoxide (CO) mixing ratios were measured at an air quality monitoring station near the Mt. Wilson (MW) Observatory in southern California starting in the spring of 2007. Diurnal variation and mixing ratio correlation (R 2 = 0.81) were observed. The correlation results observed agree with previous aircraft measurements collected over the greater Los Angeles (LA) metropolitan area. The consistent agreement between CH4 and CO indicates these gases are well-mixed before reaching the sampling site and the emission source contributions of both compounds are reasonably constant. Since CH4 and CO are considered non-reactive on the time scale of dispersion within the LA urban area and their emission sources are likely to be similarly distributed (e.g., associated with human activities) they are subject to similar scales of atmospheric transport and dilution. This behavior allows the relationship of CH4 and CO to be applied for estimation of CH4 emissions using well-documented CO emissions. Applying this relationship a “top–down” CH4 inventory was calculated for LA County based on the measurements observed at MW and compared with the California Air Resources Board (CARB) “bottom–up” CH4 emissions inventory based on the Intergovernmental Panel on Climate Change recommended methodologies. The “top–down” CH4 emissions inventory is approximately one-third greater than CARB''s “bottom–up” inventory for LA County. Considering the uncertainties in both methodologies, the different CH4 emissions inventory approaches are in good agreement, although some under and/or uninventoried CH4 sources may exist. [Copyright &y& Elsevier]