Characterization of errors in satellite-based HCHO ∕ NO 2 tropospheric column ratios with respect to chemistry, column-to-PBL translation, spatial representation, and retrieval uncertainties

[摘要] The availability of formaldehyde (HCHO) (a proxy for volatile organiccompound reactivity) and nitrogen dioxide (NO 2 ) (a proxy for nitrogenoxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into thenear-surface ozone sensitivity. Strong emphasis has been placed on thechallenges that come with transforming what is being observed in thetropospheric column to what is actually in the planetary boundary layer(PBL) and near the surface; however, little attention has been paid to othersources of error such as chemistry, spatial representation, and retrievaluncertainties. Here we leverage a wide spectrum of tools and data toquantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrainedby more than 500 h of aircraft data from NASA's air quality campaigns isused to simulate the ratio of the chemical loss of HO 2   +  RO 2 ( LRO x ) to the chemical loss of NO x ( LNO x ). Subsequently, we challengethe predictive power of HCHO / NO 2 ratios (FNRs), which are commonlyapplied in current research, in detecting the underlying ozone regimes by comparing them to LRO x / LNO x .FNRs show a strongly linear ( R 2 =0 .94)relationship with LRO x / LNO x , but only on the logarithmic scale. Following the baseline (i.e., ln( LRO x / LNO x )  =   − 1.0  ±  0.2) with the model andmechanism (CB06, r2) used for segregating NO x -sensitive from VOC-sensitiveregimes, we observe a broad range of FNR thresholds ranging from 1 to 4. Thetransitioning ratios strictly follow a Gaussian distribution with a mean andstandard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error ( 1 σ ) resulting from not accuratelydescribing the RO x – HO x cycle. We calculate high ozone production rates (PO 3 ) dominated by large HCHO  ×  NO 2 concentration levels,a new proxy for the abundance of ozone precursors. The relationship betweenPO 3 and HCHO  ×  NO 2 becomes more pronounced when movingtowards NO x -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO  ×  NO 2 metric that has not been utilized in ozone studies. The vast amount ofvertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using asecond-order rational function permitting an analytical solution for analtitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representationerror based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatialinformation at its native resolution with respect to a high-resolutionsensor like the TROPOspheric Monitoring Instrument (TROPOMI) ( >  5.5  ×  3.5 km 2 ). A pixel with a grid size of 216 km 2 fails at capturing ∼  65 % of the spatial information in FNRs at a50 km length scale comparable to the size of a large urban center (e.g., LosAngeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMIand OMI tropospheric NO 2 and HCHO columns. At a 68 % confidenceinterval ( 1 σ ), errors pertaining to daily TROPOMI observations, eitherHCHO or tropospheric NO 2 columns, should be above 1.2–1.5  ×  10 16  molec. cm −2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the totalerror (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the totalrelative error (  50 %) tends to be mild, whereas areas with lowvegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain ( >  100 %). Our study suggests that continuingdevelopment in the retrieval algorithm and sensor design and calibration isessential to be able to advance the application of FNRs beyond a qualitativemetric.

[学科分类] 医学（综合）