Multi-axis Differential Optical Absorption Spectroscopy Research Articles

The global daily High Spatial–Temporal Coverage Merged tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2

Abstract. Remote sensing based on satellites can provide long-term, consistent, and global coverage of NO2 (an important atmospheric air pollutant) as well as other trace gases. However, satellites often miss data due to factors including but not limited to clouds, surface features, and aerosols. Moreover, as one of the longest continuous observational platforms of NO2, the Ozone Monitoring Instrument (OMI) has suffered from missing data over certain rows since 2007, significantly reducing its spatial coverage. This work uses the OMI-based tropospheric NO2 (OMNO2) product as well as a NO2 product from the Global Ozone Monitoring Experiment-2 (GOME-2) in combination with machine learning (eXtreme Gradient Boosting – XGBoost) and spatial interpolation (data-interpolating empirical orthogonal function – DINEOF) methods to produce the 16-year global daily High Spatial–Temporal Coverage Merged tropospheric NO2 dataset (HSTCM-NO2; https://doi.org/10.5281/zenodo.10968462; Qin et al., 2024), which increases the average global spatial coverage of NO2 from 39.5 % to 99.1 %. The HSTCM-NO2 dataset is validated using upward-looking observations of NO2 (multi-axis differential optical absorption spectroscopy – MAX-DOAS), other satellites (the Tropospheric Monitoring Instrument – TROPOMI), and reanalysis products. The comparisons show that HSTCM-NO2 maintains a good correlation with the magnitudes of other observational datasets, except for under heavily polluted conditions (> 6 × 1015 molec.cm-2). This work also introduces a new validation technique to validate coherent spatial and temporal signals (empirical orthogonal function – EOF) and confirms that HSTCM-NO2 is not only consistent with the original OMNO2 data but in some parts of the world also effectively fills in missing gaps and yields a superior result when analyzing long-range atmospheric transport of NO2. The few differences are also reported to be related to areas in which the original OMNO2 signal was very low, which has been shown elsewhere but not from this perspective, further confirming that applying a minimum cutoff to retrieved NO2 data is essential. The reconstructed data product can effectively extend the utilization value of the original OMNO2 data, and the data quality of HSTCM-NO2 can meet the needs of scientific research.

NitroNet – a machine learning model for the prediction of tropospheric NO2 profiles from TROPOMI observations

Abstract. We introduce NitroNet, a deep learning model for the prediction of tropospheric NO2 profiles from satellite column measurements. NitroNet is a neural network trained on synthetic NO2 profiles from the regional chemistry and transport model WRF-Chem, which was operated on a European domain for the month of May 2019. This WRF-Chem simulation was constrained by in situ and satellite measurements, which were used to optimize important simulation parameters (e.g. the boundary layer scheme). The NitroNet model receives NO2 vertical column densities (VCDs) from the TROPOspheric Monitoring Instrument (TROPOMI) and ancillary variables (meteorology, emissions, etc.) as input, from which it reproduces NO2 concentration profiles. Training of the neural network is conducted on a filtered dataset, meaning that NO2 profiles showing strong disagreement (>20 %) with colocated TROPOMI column measurements are discarded. We present a first evaluation of NitroNet over a variety of geographical and temporal domains (Europe, the US West Coast, India, and China) and different seasons. For this purpose, we validate the NO2 profiles predicted by NitroNet against satellite, in situ, and MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) measurements. The training data were previously validated against the same datasets. During summertime, NitroNet shows small biases and strong correlations with all three datasets: a bias of +6.7 % and R=0.95 for TROPOMI NO2 VCDs, a bias of −10.5 % and R=0.75 for AirBase surface concentrations, and a bias of −34.3 % to +99.6 % with R=0.83–0.99 for MAX-DOAS measurements. In comparison to TROPOMI satellite data, NitroNet even shows significantly lower errors and stronger correlation than a direct comparison with WRF-Chem numerical results. During wintertime considerable low biases arise because the summertime/late-spring training data are not fully representative of all atmospheric wintertime characteristics (e.g. longer NO2 lifetimes). Nonetheless, the wintertime performance of NitroNet is surprisingly good and comparable to that of classic regional chemistry and transport models. NitroNet can demonstrably be used outside the geographic and temporal domain of the training data with only slight performance reductions. What makes NitroNet unique when compared to similar existing deep learning models is the inclusion of synthetic model data, which offers important benefits: due to the lack of NO2 profile measurements, models trained on empirical datasets are limited to the prediction of surface concentrations learned from in situ measurements. NitroNet, however, can predict full tropospheric NO2 profiles. Furthermore, in situ measurements of NO2 are known to suffer from biases, often larger than +20 %, due to cross-sensitivities to photooxidants, which other models trained on empirical data inevitably reproduce.

First evaluation of the GEMS glyoxal products against TROPOMI and ground-based measurements

Abstract. The Geostationary Environment Monitoring Spectrometer (GEMS) on board the GEO-KOMPSAT-2B satellite is the first geostationary satellite launched to monitor the environment. GEMS conducts hourly measurements during the day over eastern and southeastern Asia. This work presents glyoxal (CHOCHO) vertical column densities (VCDs) retrieved from GEMS, with optimal settings for glyoxal retrieval based on sensitivity tests involving reference spectrum sampling and fitting window selection. We evaluated GEMS glyoxal VCDs by comparing them to the TROPOspheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) ground-based observations. On average, GEMS and TROPOMI VCDs show a spatial correlation coefficient of 0.63, increasing to 0.87 for northeastern Asia. While GEMS and TROPOMI demonstrate similar monthly variations in the Indochinese Peninsula regions (R > 0.67), variations differ in other areas. Specifically, GEMS VCDs are higher in the winter and either lower or comparable to TROPOMI and MAX-DOAS VCDs in the summer across northeastern Asia. We attributed the discrepancies in the monthly variation to a polluted reference spectrum and high NO2 concentrations. When we correct GEMS glyoxal VCDs as a function of NO2 SCDs, the monthly correlation coefficients substantially increase from 0.16–0.40 to 0.45–0.72 in high NO2 regions. When averaged hourly, GEMS and MAX-DOAS VCDs exhibit similar diurnal variations, especially at stations in Japan (Chiba, Kasuga, and Fukue).

Ground-Based MAX-DOAS Observations for Spatiotemporal Distribution and Transport of Atmospheric Water Vapor in Beijing

Understanding the spatiotemporal distribution and transport of atmospheric water vapor in urban areas is crucial for improving mesoscale models and weather and climate predictions. This study employs Multi-Axis Differential Optical Absorption Spectroscopy to monitor the dynamic distribution and transport flux of water vapor in Beijing within the tropospheric layer (0–4 km) from June 2021 to May 2022. The seasonal peaks in precipitable water occur in August, reaching 39.13 mm, with noticeable declines in winter. Water vapor was primarily distributed below 2.0 km and generally decreases with increasing altitude. The largest water vapor transport flux occurs in the southeast–northwest direction, whereas the smallest occurs in the southwest–northeast direction. The maximum flux, observed at about 1.2 km in the southeast–northwest direction during summer, reaches 31.77 g/m2/s (transported towards the southeast). Before continuous rainfall events, water vapor transport, originating primarily from the southeast, concentrates below 1 km. Backward trajectory analysis indicates that during the rainy months, there was a higher proportion of southeasterly winds, especially at lower altitudes, with air masses from the southeast at 500 m accounting for 69.11%. This study shows the capabilities of MAX-DOAS for remote sensing water vapor and offers data support for enhancing weather forecasting and understanding urban climatic dynamics.

Troposphere–stratosphere-integrated bromine monoxide (BrO) profile retrieval over the central Pacific Ocean

Abstract. Bromine monoxide (BrO) is relevant to atmospheric oxidative capacity, affecting the lifetime of greenhouse gases (i.e., methane, dimethylsulfide) and mercury oxidation. However, measurements of BrO radical vertical profiles are rare, and BrO is highly variable. As a result, the few available aircraft observations in different regions of the atmosphere are not easily reconciled. Autonomous multi-axis differential optical absorption spectroscopy (MAX-DOAS) instruments placed at remote mountaintop observatories (MT-DOAS) present a cost-effective alternative to aircraft, with the potential to probe the climate-relevant yet understudied free troposphere more routinely. Here, we describe an innovative full-atmosphere BrO and formaldehyde (HCHO) profile retrieval algorithm using MT-DOAS measurements at Mauna Loa Observatory (MLO – 19.536° N, 155.577° W; 3401 m a.s.l.). The retrieval is based on time-dependent optimal estimation and simultaneously inverts 190+ individual BrO (and formaldehyde, HCHO) SCDs (slant column densities; SCD = dSCD + SCDRef) from solar stray light spectra measured in the zenith and off-axis geometries at high and low solar zenith angles (92° > SZA > 30°) to derive BrO concentration profiles from 1.9 to 35 km with 7.5 degrees of freedom (DoFs). Two case study days are characterized by the absence (26 April 2017, base case) and presence of a Rossby-wave-breaking double tropopause (29 April 2017, RW-DT case). Stratospheric-BrO vertical columns are nearly identical on both days (VCD = (1.5 ± 0.2) × 1013 molec. cm−2), and the stratospheric-BrO profile peaks at a lower altitude during the RW-DT (1.6–2.0 DoFs). Tropospheric-BrO VCDs increase from (0.70 ± 0.14) × 1013 molec. cm−2 (base case) to (1.00 ± 0.14) × 1013 molec. cm−2 (RW-DT) owing to a 3-fold increase in BrO in the upper troposphere (1.7–1.9 DoFs). BrO at MLO increases from (0.23 ± 0.03) pptv (base case) to (0.46 ± 0.03) pptv (RW-DT) and is characterized by an added time resolution (∼ 3.8 DoFs). Up to (0.9 ± 0.1) pptv BrO is observed above MLO in the lower free troposphere in the absence of the double tropopause. We validate the retrieval using aircraft BrO profiles and in situ HCHO measurements aboard the NSF/NCAR GV aircraft above MLO (11 January 2014) that establish BrO peaks around 2.4 pptv above 13 km in the upper troposphere–lower stratosphere (UTLS) during a similar RW-DT event (0.83 × 1013 molec. cm2 tropospheric-BrO VCD above 2 km). The tropospheric-BrO profile measured using MT-DOAS (RW-DT case) and using the aircraft agree well (after averaging-kernel smoothing). Furthermore, these tropospheric-BrO profiles over the central Pacific Ocean are found to closely resemble those over the eastern Pacific Ocean (2–14 km) and are in contrast to those over the western Pacific Ocean, where a C-shaped tropospheric-BrO profile shape has been observed.

Ground-based MAX-DOAS observations of tropospheric formaldehyde and nitrogen dioxide: Insights into ozone formation sensitivity

Tropospheric profiles of HCHO, NO2, and O3 are important for analyzing ozone formation mechanism. In this study, ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS), light detection and ranging (LIDAR), and in-situ measurements were simultaneously performed to diagnose ozone formation sensitivity at the Heshan Observatory in the Pearl River Delta (PRD) region from September to end October 2019. The profiles of tropospheric HCHO and NO2 were retrieved from MAX-DOAS measurements using an optimal estimation method. The retrieved surface HCHO and NO2 results were validated with 2,4-dinitrophenylhydrazine (DNPH) and Thermo 42i measurements, and the correlation coefficients (R) were 0.78 and 0.81, respectively. The retrieved tropospheric vertical column densities (VCDs) of HCHO and NO2 were compared with TROPOMI measurements, and the correlation coefficients (R) were 0.68 and 0.87, respectively. In addition, MAX-DOAS and LIDAR measurements were combined to diagnose a typical planetary boundary layer (PBL) ozone pollution episode from September 28 to October 10, 2019; this episode was analyzed using HCHO/NO2 ratio as an indicator and was found to be dominated by the VOC-sensitive regime. Moreover, the regime transition of ozone formation sensitivity was calculated using the surface HCHO/NO2 ratio and increased O3 from the MAX-DOAS and Thermo 49i measurements, with transition thresholds of 1.43 and 1.78, respectively. Based on this definition, the ozone formation sensitivity at Heshan Observatory varied from VOC-sensitive (< 0.2 km and > 0.8 km) to NOx-sensitive (0.3–0.7 km) to VOC-NOx-sensitive (0.2–0.3 km and 0.7–0.8 km). The results improve our understanding of ozone formation sensitivity in the PRD region.

A convolutional neural networks method for tropospheric ozone vertical distribution retrieval from Multi-AXis Differential Optical Absorption Spectroscopy measurements

The vertical distribution of tropospheric ozone (O3) is crucial for understanding atmospheric physicochemical processes. A Convolutional Neural Networks (CNN) method for the retrieval of tropospheric O3 vertical distribution from ground-based Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements to tackle the issue of stratospheric O3 absorption interference faced by MAX-DOAS in obtaining tropospheric O3 profiles. Firstly, a hybrid model, named PCA-F_Regression-SVR, is developed to screen features sensitive to O3 inversion based on the MAX-DOAS spectra and EAC4 reanalysis O3 profiles, which incorporates Principal Component Analysis (PCA), F_Regression function, and Support Vector Regression (SVR) algorithm. Thus, these screened features for ancillary inversion include the profiles of temperature, specific humidity, fraction of cloud coverage, eastward and northward wind, the profiles of SO2, NO2, and HCHO, as well as season and time features to serve as sensitive factors. Secondly, the preprocessed MAX-DOAS spectra dataset and the sensitive factor dataset are utilized as input, while the O3 profiles of the EAC4 reanalysis dataset incorporating the surface O3 concentrations are employed as output for constructing the CNN model. The Mean Absolute Percentage Error (MAPE) decreases from 26 % to approximately 19 %. Finally, the CNN model is applied for inversion and comparison of tropospheric O3 profiles using independent input data. The CNN model effectively reproduces the O3 profiles of the EAC4 dataset, showing a Gaussian-like spatial distribution with peaks primarily around 950 hPa (550 m). Since the reanalysis data used for model training has been smoothed, the CNN model is insensitive to extreme values. This behavior can be attributed to the MAPE loss function, which evaluates Absolute Percentage Errors (APEs) of O₃ concentration at all altitudes, resulting in varying retrieval accuracy across different altitudes while maintaining overall MAPE control. Temporally, the CNN model tends to overestimate surface O3 in summer by around 20 μg/m3, primarily due to the influence of the temperature feature in the sensitivity factor dataset. In conclusion, leveraging MAX-DOAS spectra enables the retrieval of tropospheric O3 vertical distribution through the established CNN model.

Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations

Abstract. Formaldehyde (HCHO), a precursor to tropospheric ozone, is an important tracer of volatile organic compounds (VOCs) in the atmosphere. Two years (2019–2020) of HCHO simulations obtained from the global chemistry transport model CHASER at a horizontal resolution of 2.8° × 2.8° have been evaluated using the Tropospheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations. In situ measurements from the Atmospheric Tomography Mission (ATom) in 2018 were used to evaluate the HCHO simulations for 2018. CHASER reproduced the TROPOMI-observed global HCHO spatial distribution with a spatial correlation (r) of 0.93 and a negative bias of 7 %. The model showed a good capability to reproduce the observed magnitude of the HCHO seasonality in different regions, including the background conditions. The discrepancies between the model and satellite in the Asian regions were related mainly to the underestimated and missing anthropogenic emission inventories. The maximum difference between two HCHO simulations based on two different nitrogen oxide (NOx) emission inventories was 20 %. TROPOMI's finer spatial resolution than that of the Ozone Monitoring Instrument (OMI) sensor reduced the global model–satellite root-mean-square error (RMSE) by 20 %. The OMI- and TROPOMI-observed seasonal variations in HCHO abundances were consistent. The simulated seasonality showed better agreement with TROPOMI in most regions. The simulated HCHO and isoprene profiles correlated strongly (R=0.81) with the ATom observations. However, CHASER overestimated HCHO mixing ratios over dense vegetation areas in South America and the remote Pacific region (background condition), mainly within the planetary boundary layer (&lt; 2 km). The simulated seasonal variations in the HCHO columns showed good agreement (R&gt;0.70) with the MAX-DOAS observations and agreed within the 1σ standard deviation of the observed values. However, the temporal correlation (R∼0.40) was moderate on a daily scale. CHASER underestimated the HCHO levels at all sites, and the peak occurrences in the observed and simulated HCHO seasonality differed. The coarseness of the model's resolution could potentially lead to such discrepancies. Sensitivity studies showed that anthropogenic emissions were the highest contributor (up to ∼ 35 %) to the wintertime regional HCHO levels.

Measurement report: Combined use of MAX-DOAS and AERONET ground-based measurements in Montevideo, Uruguay, for the detection of distant biomass burning

Abstract. Biomass burning releases large amounts of aerosols and chemical species into the atmosphere, representing a major source of air pollutants. Emissions and by-products can be transported over long distances, presenting challenges in quantification. This is mainly done using satellites, which offer global coverage and data acquisition for places that are difficult to access. In this study, ground-based observations are used to assess the abundance of trace gases and aerosols. On 24 November 2020, a significant increase in formaldehyde was observed with a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument located in Montevideo (Uruguay), and its vertical column densities reached values of 2.4×1016 molec. cm−2, more than twice the values observed during the previous days. This was accompanied by an increase in the aerosol levels measured by an AErosol RObotic NETwork (AERONET) photometer located at the same site. The aerosol optical depth (AOD) at 440 nm reached values close to 1, an order of magnitude larger than typical values in Montevideo. Our findings indicate that the increase was associated with the passage of a plume originating from distant biomass burning. This conclusion is supported by TROPOspheric Monitoring Instrument (TROPOMI) satellite observations as well as HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) simulations. The profiles of the gases and aerosols retrieved from the MAX-DOAS observations are consistent with the HYSPLIT analysis, showing the passage of a plume over Montevideo on 24 November located at a height of ∼ 1.5 km. This corroborates the finding that biomass burning events occurring about 800 km north of Montevideo can affect the local atmosphere through long-distance emissions transport. This study underscores the potential of ground-based atmospheric monitoring as a tool for detection of such events. Furthermore, it demonstrates greater sensitivity compared to satellite when it comes to detection of relatively small amounts of carbonyls like glyoxal and formaldehyde.

The investigation of retrieval method for aerosol and water vapor profiles based on MAX-DOAS technology

Simultaneously obtaining the vertical distribution and profile of aerosol and water vapor is crucial for in-depth understanding of the Earth's radiation balance, regional water cycle, and the causes of frequent haze weather in China. This study developed a system and inversion method based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) to simultaneously retrieve tropospheric aerosol and water vapor profiles. The absorption of dioxy (O4) was obtained by multi-elevation measurement using the developed ground-based MAX-DOAS system. By minimizing a cost function combining an atmospheric radiative transfer model, aerosol extinction profiles were first inverted, followed by water vapor profiles. Optimized parameter selection in the look-up table method reduced reliance on prior profile information, enhancing pollutant distribution retrieval accuracy. In the monitoring period in Huaibei region, aerosols were mainly below 1.5 km, while water vapor concentrations decreased with altitude. Comparisons of water vapor vertical column densities (VCDs) retrieved through the look-up table method with the European Centre for Medium-Range Weather Forecasts(ECMWF) ERA5 model and geometric approximation showed good agreement, with correlation coefficients of 0.93 and 0.98, respectively. To comprehend water vapor sources at various vertical layers, a 24-h backward trajectory clustering analysis was conducted using the HYSPLIT model based on observed wind fields. Findings revealed that at 500 m altitude, water vapor primarily emanated from the southeast, whereas at 1 km and 2 km altitudes, it predominantly originated from the southwest. The study advances simultaneous tropospheric aerosol and water vapor profile retrieval, providing reliable technical support for the investigation of regional pollution.

MAX-DOAS observations of pollutant distribution and transboundary transport in typical regions of China

Studying the spatiotemporal distribution and transboundary transport of aerosols, NO2, SO2, and HCHO in typical regions is crucial for understanding regional pollution causes. In a 2-year study using multi-axis differential optical absorption spectroscopy in Qingdao, Shanghai, Xi'an, and Kunming, we investigated pollutant distribution and transport across Eastern China-Ocean, Tibetan Plateau-Central and Eastern China, and China-Southeast Asia interfaces. First, pollutant distribution was analyzed. Kunming, frequently clouded and misty, exhibited consistently high aerosol optical depth throughout the year. In Qingdao and Shanghai, NO2 and SO2, as well as SO2 in Xi'an, increased in winter. Elevated HCHO in summer in Shanghai and Xi'an, especially Xi'an, suggests potential ozone pollution issues. Subsequently, pollutant transportation across interfaces was studied. At the Eastern China-Ocean interface, the gas transport flux was the largest among other interfaces, with the outflux exceeding the influx, especially in winter and spring. The input of pollutants from the Tibetan Plateau to central-eastern China was larger than the output in winter and spring, with SO2 having the highest transport flux in winter. The pollution input from Southeast Asia to China significantly exceeded the output, with spring and winter inputs being 3.22 and 3.03 times the output, respectively. Lastly, the transportation characteristics of a pollution event at Kunming were studied. During this period, pollutants were transported from west to east, with the maximum SO2 transport flux at an altitude of 2.87 km equaling 27.74 µg/(m2·s). It is speculated that this pollution was caused by the transport from Southeast Asian countries to Kunming.

Vertical distribution characteristics and potential sources of atmospheric pollutants in the North China Plain basing on the MAX-DOAS measurement

The mechanism for the generation of atmospheric pollution sources can be further investigated through the examination of atmospheric evolution and diffusion characteristics. The authors of this study conducted a 3-month MAX-DOAS (multi-axis differential optical absorption spectroscopy) vertical observation in Shijiazhuang City, North China Plain, in the summer of 2020 in response to the long-standing air pollution issues in the region. The vertical distribution profiles of aerosol, NO2, HCHO, and CHOCHO were generated, and the inversion findings showed good agreement with the TROPOMI (tropospheric monitoring instrument) satellite remote sensing validation, demonstrating the validity and accuracy of the observations. The near-surface boundary layer is home to the majority of the NO2, HCHO, and CHOCHO species. The species’ daytime evolution trends varied, with the highest NO2 peaks occurring in the morning and evening commute, the highest HCHO peaks occurring in the morning at 10:00 a.m., and CHOCHO's concentration during the day declined. Two minor aerosol pollution processes took place in Shijiazhuang City during the summer observation period. The elevated concentrations of NO2, CO, and the PM2.5/PM10 ratio during the pollution processes suggest that anthropogenic emissions, particularly biomass burning, were responsible for the large number of fine particles generated during the pollution events. Based on the examination of pollutant concentration profiles and meteorological data, it was determined that local emissions and north wind transport were the primary causes of Shijiazhuang's high NO2 values. Meanwhile, the southern region of Shijiazhuang was primarily responsible for the majority of the potential sources of atmospheric HCHO, and local emissions were also a major factor affecting the high CHOCHO values. Shijiazhuang's local near-surface volatile organic compounds (VOCs) are mostly caused by human emissions, although biomass burning and its regional transportation have a greater influence on the middle and upper boundary layers. This study systematically sorted the evolution characteristics and potential sources of pollutants in Shijiazhuang City during the summer based on the joint observations of various pollutants, including NO2, HCHO, and CHOCHO. These results can be used to support the development of appropriate policies for the prevention and control of pollutants in the Shijiazhuang local area of the North China Plain.

O3 sensitivity and vertical distribution of summertime HCHO, NO2, and SO2 in Shihezi, China

Shihezi City has experienced severe ozone pollution. The vertical observation of ozone precursors (NO2 and HCHO) and SO2 in this area was conducted by multi-axis differential optical absorption spectroscopy in summer, 2023. During this experiment, ozone was measured at an average concentration of 94.89 ± 37.46 μg/m3, and it mainly increased when the northerly wind dominated, accompanied by the increasing of its precursors. In addition, SO2 had a relatively high concentration and elevated with the rising ozone concentration, remarkably different from other cities in China. The average vertical distribution of HCHO in the ozone pollution period was a Gaussian type, with the peak value at about 0.2 km. In contrast, the vertical distribution of NO2 and SO2 decreased exponentially with the rise of vertical height, and their concentrations dropped rapidly within 0–1 km. The RFN range of the transitional regime in Shihezi City was [1.26, 2.80]. Given that ozone pollution mostly occurred when RFN was 1–2, the chemical production of near-surface ozone in Shihezi City was controlled by a transition regime. The RFN vertical pattern was Gaussian type and reached a maximal value at 400–600 m. RFN increased at the middle altitude (0.4–1.2 km), and the ozone formation was controlled by the transitional regime. RFN decreased above 1.2 km, and the photochemical ozone formation was mainly controlled by a VOCs-limited regime. This study provides an improved understanding of O3 precursors vertical distribution and O3 formation sensitivity in Shihezi City.

Vertical Characteristics of HCHO and NO2 in Suburban Shanghai: Understanding of Ozone formation sensitivity via Secondary HCHO

Abstract Since ozone (O3) pollution in China is on the rise, vertical distribution of nitrogen dioxide (NO2) and formaldehyde (HCHO) and their role towards O3 formation are critical towards designing O3 control strategies. Seasonal characteristics of aerosols, HCHO and NO2 were investigated over suburban Shanghai using Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) from June 2020 to May 2021. For HCHO, the highest average vertical mixing ratios (VMRs) were observed for summer (0.775 ppb), followed by autumn (0.719 ppb), spring (0.718 ppb) and winter (0.672 ppb) at ground level. Seasonal trends in NO2 VMRs were observed to be opposite to that of HCHO with peak values occurring during winter (2.212 ppb) at the ground level followed by autumn (1.881 ppb), spring (1.415 ppb) and summer (1.124 ppb). In vertical, aerosols depicted a Gaussian shape with a higher values between 0.2 - 0.5 km. An exponential decay in NO2 VMRs is observed from 0.0 km to 3.0 km while the integral component of HCHO was found to be concentrated up to 2.0 km particularly during summer months. The vertical distribution of NO2 in different seasons mainly appeared below 0.5 km, while that of HCHO appeared within the range of 0.2-1.0 km. Both aerosols and NO2 tend to be higher during haze days compared to non-haze days while HCHO was found to be higher during clear days owing to high photochemical activity on a clear day. Based on the ratio of HCHO to NO2 (RFN), this study attempted to quantify the vertical characteristics of O3 sensitivity for different seasons. The results indicated that the O3 sensitivity was VOC-limited both at lower (generally, 0.0 - 0.6 km) and higher heights (1.8 - 3.0 km) while some transition limited scenarios were found at middle height (0.7 – 1.7 km) particularly during daytime. The results depicted that secondary HCHO is a crucial factor controlling on O3 sensitivity over Shanghai where enhanced ratio of VOC limited regime was observed with secondary HCHO for all the seasons.

Vertical Evolution of Ozone Formation Sensitivity Based on Synchronous Vertical Observations of Ozone and Proxies for Its Precursors: Implications for Ozone Pollution Prevention Strategies.

Photochemical ozone (O3) formation in the atmospheric boundary layer occurs at both the surface and elevated altitudes. Therefore, the O3 formation sensitivity is needed to be evaluated at different altitudes before formulating an effective O3 pollution prevention and control strategy. Herein, we explore the vertical evolution of O3 formation sensitivity via synchronous observations of the vertical profiles of O3 and proxies for its precursors, formaldehyde (HCHO) and nitrogen dioxide (NO2), using multi-axis differential optical absorption spectroscopy (MAX-DOAS) in urban areas of the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions in China. The sensitivity thresholds indicated by the HCHO/NO2 ratio (FNR) varied with altitude. The VOC-limited regime dominated at the ground level, whereas the contribution of the NOx-limited regime increased with altitude, particularly on heavily polluted days. The NOx-limited and transition regimes played more important roles throughout the entire boundary layer than at the surface. The feasibility of extreme NOx reduction to mitigate the extent of the O3 pollution was evaluated using the FNR-O3 curve. Based on the surface sensitivity, the critical NOx reduction percentage for the transition from a VOC-limited to a NOx-limited regime is 45-72%, which will decrease to 27-61% when vertical evolution is considered. With the combined effects of clean air action and carbon neutrality, O3 pollution in the YRD and PRD regions will transition to the NOx-limited regime before 2030 and be mitigated with further NOx reduction.

Identification of O3 Sensitivity to Secondary HCHO and NO2 Measured by MAX-DOAS in Four Cities in China

This study analyzed the differences in ozone (O3) sensitivity in four different urban areas in China from February 2019 to January 2020 based on data on various near-surface pollutants from passive multi-axis differential optical absorption spectroscopy (MAX-DOAS) sites and nearby China National Environmental Monitoring Center (CNEMC) sites. Across the four cities, the nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations varied seasonally. Xianghe consistently displayed the lowest NO2 levels, suggesting reduced emissions compared to other cities. Guangzhou, a city with a robust economy and a high level of vehicle ownership, exhibited higher concentrations in spring. Summer brought elevated HCHO levels in Guangzhou, Xianghe, and Shenyang due to intensified photochemical processes. Autumn and winter showed higher HCHO concentrations in Guangzhou and Xianghe compared to Lanzhou and Shenyang. Overall, Guangzhou recorded the highest annual averages, due to its developed economy, while Xianghe’s lower NO2 levels were offset by the elevated HCHO due to higher O3 values. The analysis delved into primary and secondary HCHO sources across seasons and used carbon monoxide (CO) and O3 data. Xianghe showcased the dominance of secondary sources in summer and autumn, while Lanzhou was characterized by primary dominance throughout the year. Shenyang mirrored Xianghe’s evolution due to industrial emissions. In Guangzhou, due to the high levels of vehicular traffic and sunlight conditions, secondary sources predominantly influenced HCHO concentrations. These findings highlight the interplay between primary and secondary emissions in diverse urban settings. This study explored O3 sensitivity variations across seasons. Xianghe exhibited a balanced distribution among volatile organic compound (VOC)-limited conditions, nitrogen oxide (NOx)-limited conditions, and transitional influences. Lanzhou was mainly affected by VOC-limited conditions in winter and NOx-limited conditions in other seasons. Shenyang’s sensitivity varied with the seasons and was primarily influenced by transitions between VOCs and NOx in autumn and NOx-limited conditions otherwise. Guangzhou experienced varied influences. During periods of high O3 pollution, all regions were affected by NOx-limited conditions, indicating the necessity of NOx monitoring in these areas, especially during summer in all regions and during autumn in Xianghe and Guangzhou.

Remote Sensing Measurements at a Rural Site in China: Implications for Satellite NO2 and HCHO Measurement Uncertainty and Emissions From Fires

AbstractNitrogen dioxide (NO2) and formaldehyde (HCHO) play vital roles in atmospheric photochemical processes. Their tropospheric vertical column density (TVCD) distributions have been monitored by satellite instruments. Evaluation of these observations is essential for applying these observations to study photochemistry. Assessing satellite products using observations at rural sites, where local emissions are minimal, is particularly useful due in part to the spatial homogeneity of trace gases. In this study, we evaluate OMI and TROPOMI NO2 and HCHO TVCDs using multi‐axis differential optical absorption spectroscopy (MAX‐DOAS) measurements at a rural site in the east coast of the Shandong province, China in spring 2018 during the Ozone Photochemistry and Export from China Experiment (OPECE) measurement campaign. On days not affected by local burning, we found generally good agreement of NO2 data after using consistent a priori profiles in satellite and MAX‐DOAS retrievals and accounting for low biases in scattering weights in one of the OMI products. In comparison, satellite HCHO products exhibited weaker correlations with MAX‐DOAS data, in contrast to satellite NO2 products. However, TROPOMI HCHO products showed significantly better agreement with MAX‐DOAS measurements compared to OMI data. Furthermore, case studies of the vertical profiles measured by MAX‐DOAS on burning days revealed large enhancements of nitrous acid (HONO), NO2, and HCHO in the upper boundary layer, accompanied with considerable variability, particularly in HONO enhancements.

Absolute radiance calibration in the UV and visible spectral range using atmospheric observations during twilight

Abstract. We present an improved radiance calibration method for UV–Vis spectroscopic instruments with a narrow field of view (up to a few degrees) based on the calibration method by Wagner et al. (2015). The updated method uses only measurements during the twilight period instead of several hours as for the original method. The calibration is based on the comparison of measurements and simulations of the radiance of zenith-scattered sunlight. The main advantage of our method compared to radiance calibration methods in the laboratory is that the calibration can be directly applied in the field. This allows routine radiance calibrations whenever the sky is clear during twilight. The calibration can also be performed retrospectively and will thus be applicable for the large number of existing data sets. Also, potential changes in the instrument properties during transport from the laboratory to the field are avoided. The new version of the calibration method presented here has two main advantages. First, the required measurement period can be rather short (only a few minutes during twilight for cloud-free conditions). Second, even without knowledge of the aerosol optical depth (AOD), the errors in the calibration method are rather small, especially in the UV spectral range where they range from about 4 % at 340 nm to 8 % at 420 nm. If the AOD is known, the uncertainties are even smaller (about 3 % at 340 nm to 4 % at 420 nm). For visible wavelengths, good accuracy is only obtained if the AOD is approximately known with uncertainties from about 4 % at 420 nm to 10 % between about 550 and 700 nm (generally the AOD is nevertheless smaller in the visible than in the UV spectral range). One shortcoming of the method is that it is not possible to determine the AOD exactly at the time of the (twilight) measurements because AOD observations from sun photometer measurements or the MAX-DOAS (Multi-AXis Differential Optical Absorption Spectroscopy) measurements are usually not meaningful for such high solar zenith angle (SZA). But the related uncertainty can be minimised by repeating the radiance calibrations during the twilight periods of several days.

On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO2 in WRF-Chem – comparisons to in situ, satellite, and MAX-DOAS observations

Abstract. We present WRF-Chem simulations over central Europe with a spatial resolution of 3 km × 3 km and focus on nitrogen dioxide (NO2). A regional emission inventory issued by the German Environmental Agency, with a spatial resolution of 1 km × 1 km, is used as input. We demonstrate by comparison of five different model setups that significant improvements in model accuracy can be achieved by choosing the appropriate boundary layer scheme, increasing vertical mixing strength, and/or tuning the temporal modulation of the emission data (“temporal profiles”) driving the model. The model setup with improved vertical mixing is shown to produce the best results. Simulated NO2 surface concentrations are compared to measurements from a total of 275 in situ measurement stations in Germany, where the model was able to reproduce average noontime NO2 concentrations with a bias of ca. −3 % and R=0.74. The best agreement is achieved when correcting for the presumed NOy cross sensitivity of the molybdenum-based in situ measurements by computing an NOy correction factor from modelled peroxyacetyl nitrate (PAN) and nitric acid (HNO3) mixing ratios. A comparison between modelled NO2 vertical column densities (VCDs) and satellite observations from TROPOMI (TROPOspheric Monitoring Instrument) is conducted with averaging kernels taken into account. Simulations and satellite observations are shown to agree with a bias of +5.5 % and R=0.87 for monthly means. Lastly, simulated NO2 concentration profiles are compared to noontime NO2 profiles obtained from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at five locations in Europe. For stations within Germany, average biases of −25.3 % to +12.0 % were obtained. Outside of Germany, where lower-resolution emission data were used, biases of up to +50.7 % were observed. Overall, the study demonstrates the high sensitivity of modelled NO2 to the mixing processes in the boundary layer and the diurnal distribution of emissions.

Tropospheric bromine monoxide vertical profiles retrieved across the Alaskan Arctic in springtime

Abstract. Reactive halogen chemistry in the springtime Arctic causes ozone depletion events and alters the rate of pollution processing. There are still many uncertainties regarding this chemistry, including the multiphase recycling of halogens and how sea ice impacts the source strength of reactive bromine. Adding to these uncertainties are the impacts of a rapidly warming Arctic. We present observations from the CHACHA (CHemistry in the Arctic: Clouds, Halogens, and Aerosols) field campaign based out of Utqiaġvik, Alaska, from mid-February to mid-April of 2022 to provide information on the vertical distribution of bromine monoxide (BrO), which is a tracer for reactive bromine chemistry. Data were gathered using the Heidelberg Airborne Imaging DOAS (differential optical absorption spectroscopy) Instrument (HAIDI) on the Purdue University Airborne Laboratory for Atmospheric Research (ALAR) and employing a unique sampling technique of vertically profiling the lower atmosphere with the aircraft via “porpoising” maneuvers. Observations from HAIDI were coupled to radiative transfer model calculations to retrieve mixing ratio profiles throughout the lower atmosphere (below 1000 m), with unprecedented vertical resolution (50 m) and total information gathered (average of 17.5 degrees of freedom) for this region. A cluster analysis was used to categorize 245 retrieved BrO mixing ratio vertical profiles into four common profile shapes. We often found the highest BrO mixing ratios at the Earth's surface with a mean of nearly 30 pmol mol−1 in the lowest 50 m, indicating an important role for multiphase chemistry on the snowpack in reactive bromine production. Most lofted-BrO profiles corresponded with an aerosol profile that peaked at the same altitude (225 m above the ground), suggesting that BrO was maintained due to heterogeneous reactions on particle surfaces aloft during these profiles. A majority (11 of 15) of the identified lofted-BrO profiles occurred on a single day, 19 March 2022, over an area covering more than 24 000 km2, indicating that this was a large-scale lofted-BrO event. The clustered BrO mixing ratio profiles should be particularly useful for some MAX-DOAS (multi-axis DOAS) studies, where a priori BrO profiles and their uncertainties, used in optimal estimation inversion algorithms, are not often based on previous observations. Future MAX-DOAS studies (and past reanalyses) could rely on the profiles provided in this work to improve BrO retrievals.