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During the 2017 Ozone Water Land Environmental Transition Study (OWLETS), the Langley mobile ozone lidar system utilized a new small diameter receiver to improve the retrieval of near-surface signals from 0.1 to 1 km in altitude. This new receiver utilizes a single 90 ∘ fiber-coupled, off-axis parabolic mirror resulting in a compact form that is easy to align. The single reflective surface offers the opportunity to easily expand its use to multiple wavelengths for additional measurement channels such as visible wavelength aerosol measurements. Detailed results compare the performance of the receiver to both ozonesonde and in situ measurements from a UAV platform, validating the performance of the near-surface ozone retrievals. Absolute O3 differences averaged 7 % between lidar and ozonesonde data from 0.1 to 1.0 km and yielded a 2.3 % high bias in the lidar data, well within the uncertainty of the sonde measurements. Conversely, lidar O3 measurements from 0.1 to 0.2 km averaged 10.5 % lower than coincident UAV O3. A more detailed study under more stable atmospheric conditions would be necessary to resolve the residual instrument differences reported in this work. Nevertheless, this unique added capability is a significant improvement allowing for near-surface observation of ozone.

Although air quality in the United States improved remarkably in the past decades, ground-level ozone (O3) rises often in exceedance of the national ambient air quality standard in nonattainment areas, including the Long Island Sound (LIS) and its surrounding areas. Accurate prediction of high ozone episodes is needed to assist government agencies and the public in mitigating harmful effects of air pollution. In this study, we have developed a suite of potential forecast improvements, including dynamic boundary conditions, rapid emission refresh and chemical data assimilation, in a 3 km resolution Community Multi-scale Air Quality (CMAQ) modeling system. The purpose is to evaluate and assess the effectiveness of these forecasting techniques, individually or in combination, in improving forecast guidance for two major air pollutants: surface O3 and nitrogen dioxide (NO2). Experiments were conducted for a high O3 episode (August 28–29, 2018) during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, which provides abundant observations for evaluating model performance. The results show that these forecast system updates are useful in enhancing the capability of the forecasting model with varying effectiveness for different pollutants. For O3 prediction, the most significant improvement comes from the dynamic boundary conditions derived from NOAA National Air Quality Forecast Capability (NAQFC), which increases the correlation coefficient (R) from 0.81 to 0.93 and reduces the Root Mean Square Error (RMSE) from 14.97 ppbv to 8.22 ppbv, compared to that with the static boundary conditions. The NO2 from all high-resolution simulations outperforms that from the operational 12 km NAQFC simulation, highlighting the importance of spatially resolved emission and meteorology inputs for the prediction of short-lived pollutants. The effectiveness of improved initial concentrations through optimal interpolation (OI) is shown to be high in urban areas with high emission density. The influence of OI adjustment, however, is maintained for a longer period in rural areas where emissions and chemical transformation make a smaller contribution to the O3 budget than that in high emission areas. Following the assessment of individual forecast system updates, the forecasting system is configured with dynamic boundary conditions, optimal interpolation of initial concentrations, and emission adjustment, to simulate the high ozone episode over the Long Island Sound region. The newly developed forecasting system significantly reduces the bias of surface NO2 concentration. When compared with the NASA Langley GeoCAPE Airborne Simulator (GCAS) vertical column density (VCD), the new system is able to reproduce the NO2 VCD with a higher correlation (0.74), lower normalized mean bias (40 %) and normalized mean error (61 %) than NAQFC (0.57, 45 % and 76 %, respectively). The new system captures magnitude and timing of surface O3 peaks and valleys better. In comparison with LIDAR O3 profile variability of the vertical O3 is captured better by the new system (correlation coefficient of 0.71) than by NAQFC (correlation coefficient of 0.54). Although the experiments are limited to one pollution episode over the Long Island Sound, this study demonstrates feasible approaches to improve the predictability of high O3 episodes in contemporary urban environments.

The conventional two-wavelength differential absorption lidar (DIAL) has measured air pollutants such as nitrogen dioxide (NO2). However, high concentrations of aerosol within the planetary boundary layer (PBL) can cause significant retrieval errors using only a two-wavelength DIAL technique to measure NO2. We proposed a new technique to obtain more accurate measurements of NO2 using a three-wavelength DIAL technique based on an optical parametric oscillator (OPO) laser. This study derives the three-wavelength DIAL retrieval equations necessary to retrieve vertical profiles of NO2 in the troposphere. Additionally, two rules to obtain the optimum choice of the three wavelengths applied in the retrieval are designed to help increase the differences in the NO2 absorption cross-sections and reduce aerosol interference. NO2 retrieval relative uncertainties caused by aerosol extinction, molecular extinction, absorption of gases other than the gas of interest and backscattering are calculated using two-wavelength DIAL (438 and 439.5 nm) and three-wavelength DIAL (438, 439.5 and 441 nm) techniques. The retrieval uncertainties in aerosol extinction using the three-wavelength DIAL technique are reduced to less than 2 % of those when using the two-wavelength DIAL technique. Moreover, the retrieval uncertainty analysis indicates that the three-wavelength DIAL technique can reduce more fluctuation caused by aerosol backscattering than the two-wavelength DIAL technique. This study presents NO2 concentration profiles which were obtained using the HU (Hampton University) three-wavelength OPO DIAL. As a first step to assess the accuracy of the HU lidar NO2 profiles, we compared the NO2 profiles to simulated data from the Weather Research and Forecasting Chemistry (WRF-Chem) model. This comparison suggests that the NO2 profiles retrieved with the three-wavelength DIAL technique have similar vertical structure and magnitudes typically within ±0.1 ppb compared to modeled profiles.

Aerosol retrieval using ozone lidars in the ultraviolet (UV) band is challenging but necessary for correcting aerosol interference in ozone retrieval and for studying the ozone-aerosol correlations. This study describes the aerosol retrieval algorithm for a tropospheric ozone lidar, quantifies the retrieval error budget, and intercompares the aerosol retrieval products at 299 nm with those at 532 nm from a high spectral resolution lidar (HSRL). After the cloud-contaminated data is filtered out, the aerosol backscatter or extinction coefficients at a 30-m and 10-min resolution retrieved by the ozone lidar are highly correlated with the HSRL products, with a coefficient of 0.95 suggesting that the ozone lidar can reliably measure aerosol structures with high spatio-temporal resolution when the signal-to-noise ratio is sufficient. The actual uncertainties of the aerosol retrieval from the ozone lidar generally agree with our theoretical analysis. The backscatter color ratio (backscatter-related exponent of wavelength dependence) linking the coincident data measured by the two instruments at 299 and 532 nm is 1.34 ± 0.11 while the Ångström (extinction-related) exponent is 1.49 ± 0.16 for a mixture of urban and fire smoke aerosols within the troposphere above Huntsville, AL, USA.

The North-America-based Tropospheric Ozone Lidar Network (TOLNet) was recently established to provide high spatio-temporal vertical profiles of ozone, to better understand physical processes driving tropospheric ozone variability, and to validate the tropospheric ozone measurements of upcoming space-borne missions such as Tropospheric Emissions: Monitoring Pollution (TEMPO). The network currently comprises six tropospheric ozone lidars, four of which are mobile instruments deploying to the field a few times per year, based on campaign and science needs. In August 2016, all four mobile TOLNet lidars were brought to the fixed TOLNet site of JPL-Table Mountain Facility for the one-week-long Southern California Ozone Observation Project (SCOOP). This inter-comparison campaign, which included 400 hours of lidar measurements and 18 ozonesondes launches, allowed for the unprecedented simultaneous validation of five of the six TOLNet lidars. For measurements between 3 and 10 km above sea level, a mean difference of 0.7 ppbv (1.7 %), with a root-mean-square deviation of 1.6 ppbv or 2.4 % was found between the lidars and ozonesondes, which is well within the combined uncertainties of the two measurement techniques. The few minor differences identified were typically associated with the known limitations of the lidars at the profiles altitude extremes (i.e., first 1 km above ground and at the instruments highest retrievable altitude). As part of a large homogenization and quality control effort within the network, many aspects of the TOLNet in-house data processing algorithms were also standardized and validated. This thorough validation of both the measurements and retrievals builds confidence in the high quality and reliability of the TOLNet ozone lidar profiles for many years to come, making TOLNet a valuable ground-based reference network for tropospheric ozone profiling.