Objective The environmental trace gases monitoring instrument (EMI) is one of the key payloads aboard the GF-5 satellite, designed to monitor the spatiotemporal distribution of polluting gases-such as O-3 and NO2-and aerosols on a global scale. Among these, aerosols constitute a major atmospheric component that significantly influences regional climate change, air quality, and human health. The absorbing aerosol index (AAI), a critical satellite-derived indicator for tracking absorbing aerosols, is widely used to assess their impacts on Earth's radiation budget and climate system. However, EMI AAI retrievals are subject to substantial uncertainties due to the instrument's relatively low spectral signal-to-noise ratio and limitations in on-orbit radiometric calibration. This study successfully retrieves AAI from measurements acquired by the EMI/GF5A and EMI/DQ01 payloads, demonstrating the potential of domestic instruments for monitoring global absorbing aerosol pollution events. Furthermore, a background statistical correction method based on oceanic clear-sky conditions is proposed to mitigate striping noise and radiometric calibration errors in the initial AAI results, thereby significantly enhancing the accuracy of AAI products and inter-satellite consistency. Methods AAI retrieval in this study is based on radiance data from the EMI/GF5A and EMI/DQ01 payloads. First, the SCIATRAN radiative transfer model is employed to simulate top of atmosphere (TOA) reflectance under varying solar zenith angle, viewing zenith angle, relative azimuth angle, surface altitude, and cloud altitude, generating a multi-dimensional TOA reflectance lookup table. The AAI is then derived using the ultraviolet spectral contrast method. To establish a clear-sky background, aerosol-and cloud-affected pixels over the Pacific Ocean are filtered out within a one-month window by applying strict thresholds to TROPOMI AAI and cloud product data. Pixels with a sun glint angle below 18 degrees are subsequently excluded to minimize high-AAI artifacts caused by surface specular reflection. Cubic spline interpolation is applied to address NaN values, followed by a Gaussian filter to suppress random noise, yielding statistically robust TOA reflectance as a function of latitude and viewing geometry. Finally, a two-dimensional correction factor for TOA reflectance is constructed from the relative deviation between observed and simulated reflectance. These correction factors are applied to the initial EMI/GF5A and EMI/DQ01 AAI results, and the corrected products are validated against high-resolution TROPOMI AAI data. Results and Discussions The TOA reflectance correction factors for EMI/GF5A and EMI/DQ01 were derived using a statistical approach based on marine clear-sky conditions. After correction, the correlation with TROPOMI reflectance at 340 nm improved for both payloads, with correlation coefficients increasing from 0.83 and 0.77 to 0.89 and 0.80, respectively. The two-dimensional correction factors were then applied to the initial EMI/GF5A and EMI/DQ01 AAI results for April 2024. Comparison with TROPOMI AAI products reveals strong spatial consistency across all three datasets, clearly depicting the global distribution and transport patterns of absorbing aerosols. Further correlation analysis over key regions-including the Sahara Desert, Taklimakan Desert, Arabian Peninsula, and North America-shows that the average correlation coefficients between the two EMI payloads and TROPOMI reached 0.86 and 0.85, respectively. These results confirm the capability of EMI/GF5A and EMI/DQ01 to monitor global absorbing aerosol dynamics and validate the effectiveness of the TOA reflectance correction in mitigating band noise and calibration errors in initial AAI retrievals. Moreover, merging EMI/GF5A and EMI/DQ01 data effectively compensates for observational gaps, successfully capturing a major Saharan sandstorm event and clearly delineating the transport of dust aerosols under the influence of atmospheric circulation. Conclusions In this study, latitude-and viewing geometry-dependent TOA reflectance correction factors were developed for the domestic EMI/GF5A and EMI/DQ01 payloads using a statistical method. At 340 nm, the corrected reflectance exhibited a marked reduction in average relative error: decreases of similar to 14.73% (0 degrees N-40 degrees N) and similar to 27.28% (40 degrees N-60 degrees N) for EMI/GF5A, and similar to 10.22% and similar to 23.78% for EMI/DQ01, respectively. This indicates that reflectance deviation is more pronounced at higher latitudes and systematically greater for EMI/GF5A than for EMI/DQ01. The global daily average AAI derived from corrected TOA reflectance followed the order TROPOMI>EMI/DQ01>EMI/GF5A. The spatial distributions of both EMI/GF5A and EMI/DQ01 AAI closely aligned with TROPOMI, as evidenced by average correlation coefficients of 0.86 and 0.85 over key absorbing aerosol-prone regions. The combined EMI AAI dataset successfully captured a major dust event in the Sahara Desert, demonstrating the consistent capability of the EMI payload series for monitoring significant absorbing aerosol events. In the future, multi-source satellite collaborative observations aim to deliver continuous and consistent AAI datasets for long-term monitoring of global atmospheric aerosols and climate research.

Sun-induced chlorophyll fluorescence (SIF) is an effective proxy for vegetation photosynthesis, but tower-based retrieval suffers from atmospheric path interference under humid and variable conditions. We present a DOAS-based SIF retrieval algorithm that operates in Fraunhofer lines (680–686 nm, 745–758 nm) and water vapour-sensitive bands (717–727 nm). It constructs an adaptive reference spectrum from SCOPE simulations and PCA and incorporates H2O absorption cross-sections into the fitting process for active atmospheric correction. The algorithm is implemented in a dedicated tower-based system integrating a 1° scanning gimbal with a high-resolution spectrometer. Validation with simulated and field data demonstrates the following: (1) the algorithm retrieves SIF with high fidelity (correlation coefficients >0.9 across all windows); (2) it exhibits lower water-vapour sensitivity and greater cloudy-sky stability than FLD, 3FLD, and SFM, achieving the lowest coefficient of variation (CV = 0.356); (3) over a complete wheat–rice rotation, the retrieved SIF tracks crop growth and phenological stages. This work provides a reliable solution for automated, high-precision tower-based SIF observation under complex atmospheric conditions.

This paper evaluates the accuracy and quality of International GNSS Service (IGS) combined Global Ionospheric Maps (GIMs), with a specific focus on the real-time product (IRTG) compared to the rapid (IGRG) and final (IGSG) combined solutions. The analysis employs independent validation datasets, including Jason-3 altimetry-derived vertical total electron content (VTEC) and DORIS-based differential slant TEC (dSTEC). Additionally, the evaluation in the positioning domain was performed using Single-Frequency Precise Point Positioning (SF-PPP). The results reveal that IGSG and IGRG provide the highest accuracy and temporal stability, whereas IRTG offers promising performance under dynamic ionospheric conditions, including geomagnetic disturbances. Although IRTG exhibits larger variability relative to post-processed GIM solutions, it achieves comparable positioning performance, confirming its potential for operational use in real-time applications. The analysis also highlights the importance of expanding observational coverage in equatorial regions and refining ionospheric modeling techniques to improve the accuracy and reliability of real-time GIMs across diverse GNSS operations.

Nitrous acid (HONO) is a key precursor of hydroxyl radicals (OH·), exerting an important influence on regional atmospheric oxidation capacity and the formation of ozone (O₃) and secondary aerosols. However, its multiple sources and complex formation pathways lead to substantial uncertainties in source apportionment and process constraints. In agricultural regions in particular, the contributions of soil microbial emissions and heterogeneous conversion on soil/aerosol surfaces remain poorly constrained by long-term observations, resulting in systematic underestimation in models.To this end, leveraging our self-developed 2D MAX-DOAS remote-sensing observation network spanning typical regions across China, we conducted a two-year continuous campaign (2022–2023) at an agricultural site in Shouxian County, Anhui Province (32.44 °N,116.79 °E). Vertical profiles of HONO, NO₂, and aerosols were retrieved with the PriAM algorithm. Data consistency and instrumental stability were evaluated via dual-instrument intercomparison, enabling an investigation of HONO spatiotemporal variability, formation mechanisms, and estimated emission fluxes in agricultural environments.The two systems showed excellent agreement for HONO, NO₂, and aerosols, with R² up to 0.90, demonstrating robust long-term stability. HONO exhibited pronounced near-surface accumulation, being mainly confined below 0.5 km and decreasing exponentially with altitude. Diurnal variations displayed a clear morning–evening bimodal pattern in spring, autumn, and winter, typically peaking at 09:00 and 16:00 Beijing time (BJT). In summer, this bimodality weakened due to enhanced photolysis and dilution associated with a deeper boundary layer, leading to a much smaller diurnal amplitude.Seasonally, HONO emission fluxes showed a pronounced winter maximum and summer minimum. Winter accumulation was promoted by low temperature, high humidity, a shallow boundary layer, and sustained NO₂ supply. Autumn was mainly influenced by residual nitrogen inputs during harvest and straw burning, whereas spring enhancements were closely linked to increased soil emissions following fertilization during wheat regreening. In summer, stronger photolysis and more efficient vertical mixing inhibited accumulation. High-HONO events predominantly occurred under RH>70 % and T

Abstract. Nitrous acid (HONO) photolysis is an important source of hydroxyl radicals (OH) in the atmospheric boundary layer, but long-term observations of HONO vertical distributions and their responses to agricultural activities remain limited. We conducted nearly 2 years (2022–2023) of two-dimensional multi-axis differential optical absorption spectroscopy (2D MAX-DOAS) observations in a rice–wheat rotation region in Shouxian, China. Retrieval reliability and stability were assessed through an intercomparison between two synchronized systems, spectral fit quality, degrees of freedom for signal (DOFS), and averaging-kernel analysis. Meteorological data, farming records, backward trajectories, potential source contribution function (PSCF) analysis, and Tropospheric Ultraviolet and Visible (TUV) calculations were integrated to investigate HONO variability, fertilization effects, and potential OH production. HONO was concentrated below 0.5 km, with morning and late-afternoon peaks and a noon minimum. Seasonal means followed the order winter > autumn > spring > summer. In spring and summer, near-surface HONO decreased toward midday, whereas HONO increased aloft, suggesting possible radiation-associated replenishment in elevated layers. During the 10 d following fertilization on 15 March 2023, HONO concentrations at 0.05, 0.20, and 0.50 km increased by factors of 5.3, 3.7, and 2.5, respectively, relative to the preceding 10 d. Near-site PSCF values suggested local and short-range agricultural influences. At 0.05 km, potential OH production from HONO photolysis increased after fertilization by 710 % under clear-sky conditions and by 86 % under cloudy conditions. These findings demonstrate the importance of resolving HONO vertical structure and agricultural-event responses when evaluating its photochemical relevance in agricultural regions.

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.

This study employed dual-azimuth scanning MAX-DOAS to monitor vertical column densities of NO2 and HCHO in Shanghai during the summer and winter of 2023, and compared the results with Sentinel-5P TROPOMI data. Dual-azimuth scanning revealed a generally consistent trend in gas concentrations (r > 0.95), but concentrations at 90° were higher than those at 0°, especially near the surface. This suggests that averaging multiple azimuth angles is necessary to better represent regional pollution levels. During the observation period, diurnal patterns revealed that NO2 exhibited a “double peak” in the morning and evening, which was more pronounced in the summer, while HCHO peaked between 13:00 and 15:00. Comparisons with the TROPOMI data demonstrated overall good agreement. However, the probability of TROPOMI’s NO2 and HCHO measurements being lower than those of MAX-DOAS was 80% and 62.5%, respectively. Furthermore, TROPOMI tended to overestimate at high concentrations, with overestimation reaching 41.14% for NO2 when exceeding 9.54 × 1015 molecules/cm2 and 25.93% for HCHO when exceeding 1.26 × 1016 molecules/cm2. Sensitivity analysis of the sampling distance (0–40 km) between TROPOMI samples and the ground-based site, and the sampling time (±5 to ±60 min) relative to the TROPOMI overpass, revealed that using a sampling distance of 15–25 km for NO2 and 10–20 km for HCHO, along with appropriately shortening sampling times in the winter and extending them in the summer, can effectively enhance the consistency between satellite and ground-based observations. These findings not only reveal the spatiotemporal distribution characteristics of regional pollutants but optimize the sampling time and distance parameters for satellite–ground observation validation, providing data support for improving and enhancing the accuracy of satellite retrieval algorithms.

Multi-axis differential absorption spectroscopy (MAX-DOAS) has become an important tool for detecting trace gases in optical remote sensing. At present, the temporal resolution of the system using the traditional motor-rotated elevation telescope is extremely low. We focus on studying the atmospheric radiation transmission of fast synchronous MAX-DOAS (FS MAX-DOAS), which has greatly improved the temporal resolution on the ground and on mobile platforms and the influence of related parameters on the atmospheric mass factor (AMF), which is used to guide the design and experiments of the new system. The optimal elevation angle combination, the spectral resolution, and the specific effects of relevant parameters on the AMF during profile inversion by the new system were analyzed, and the feasibility of the new system for mobile MAX-DOAS was evaluated. The inversion results of the measured spectra collected by the system show that FS MAX-DOAS can meet the requirements of both ground and mobile platform observation scenarios. The results of our sensitivity study are of great significance for guiding experiments.

As a significant city in the Yangtze River Delta regions, Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion. However, there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants. To address this, this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022. The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data. Temporally, there were pronounced seasonal variations in air pollutants. Spatially, high concentration of HCHO and NO2 were closely associated with traffic congestion on roadways, while heightened SO2 levels were attributed to winter heating and industrial emissions. The study also revealed that with the implementation of road policies, the average vehicle speed increased by 95.4%, while the NO concentration decreased by 54.4%. In the estimation of urban NOx emission flux, it was observed that in temporal terms, compared with inventory data, the emissions calculated via mobile measurements exhibited more distinct seasonal patterns, with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer. In spatial terms, the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city's primary NOx emission sources in the area between these two rings. This study offers data support for formulating the next phase of air pollution control measures in urban areas.

Sun-induced chlorophyll fluorescence (SIF) is an important indicator of vegetation photosynthesis. While remote sensing enables large-scale monitoring of SIF, existing products face the challenge of trade-offs between temporal and spatial resolutions, limiting their applications. To select the optimal model for SIF data downscaling, we used a consistent dataset combined with vegetation physiological and meteorological parameters to evaluate four different regression methods in this study. The XGBoost model demonstrated the best performance during cross-validation (R2 = 0.84, RMSE = 0.137 mW/m2/nm/sr) and was, therefore, selected to downscale GOME-2 SIF data. The resulting high-resolution SIF product (HRSIF) has a temporal resolution of 8 days and a spatial resolution of 0.05° × 0.05°. The downscaled product shows high fidelity to the original coarse SIF data when aggregated (correlation = 0.76). The reliability of the product was ensured through cross-validation with ground-based and satellite observations. Moreover, the finer spatial resolution of HRSIF better matches the footprint of eddy covariance flux towers, leading to a significant improvement in the correlation with tower-based gross primary productivity (GPP). Specifically, in the mixed forest vegetation type with the best performance, the R2 increased from 0.66 to 0.85, representing an increase of 28%. This higher-precision product will support more effective ecosystem monitoring and research.

This study investigates a multi-elevation fast synchronous multi-axis differential optical absorption spectroscopy (FS MAX-DOAS) observation system that can rapidly acquire trace gas profiles. It modifies the conventional MAX-DOAS method by sequentially scanning at elevation angles using motors. The new system incorporates a two-dimensional area array charge-coupled device (CCD) grating spectrometer, telescopes with a small field of view (< 1°), a high-speed shutter switching module, and a multi-mode multi-core fiber to enable multi-channel spectroscopy and significantly enhance the time resolution of the collected spectra (one elevation cycle within 2 min). When selecting the spectrometer grating, the impact of the spectral resolution on the detection of nitrogen dioxide (NO2) and formaldehyde (HCHO) by FS MAX-DOAS was simulated and analyzed. The optimal resolution range was determined to be 0.3–0.6 nm. The selection of the number of binning rows in the acquisition settings considers the signal-to-noise ratio of the pixels in each row to enhance the quality of the spectral data. Two-step acquisition is used for low elevation angles within one cycle to overcome the influence of variations in light intensity. A comparative test was conducted on outfield NO2 and HCHO measurements using differential optical absorption spectroscopy. Compared with the differential slant column densities (dSCDs) at each elevation angle measured by the MAX-DOAS system, the Pearson correlation coefficient of NO2 reached 0.9, while for HCHO it ranged mostly between 0.76 and 0.85. The results of the slant column concentration inversion indicate that the root mean square (rms) of the FS MAX-DOAS spectrum inversion can consistently be lower than that of MAX-DOAS over an extended period. The profile results show that the diurnal variation trend of the two systems was consistent, and because of the enhanced time resolution, the gas profile obtained by the former system can provide more detailed information. Compared with the near-ground NO2 concentration measured by the long-path DOAS (LP-DOAS) system, the daily variation trend shows a characteristic of being high in the morning and starting to decrease at noon, and the correlation coefficient between FS MAX-DOAS and LP-DOAS is higher (R = 0.901). The FS MAX-DOAS system can quickly and simultaneously obtain the vertical distribution profiles of NO2 and HCHO with high accuracy, providing a basis for mobile MAX-DOAS to achieve gas profile inversion.

Extreme ozone pollution events (EOPEs) are associated with synoptic weather patterns (SWPs) and pose severe health and ecological risks. However, a systematic investigation of the meteorological causes, transport pathways, and source contributions to historical EOPEs is still lacking. In this paper, the K-means clustering method is applied to identify six dominant SWPs during the warm season in the Yangtze River Delta (YRD) region from 2016 to 2022. It provides an integrated analysis of the meteorological factors affecting ozone pollution in Hefei under different SWPs. Using the WRF-FLEXPART model, the transport pathways (TPPs) and geographical sources of the near-surface air masses in Hefei during EOPEs are investigated. The results reveal that Hefei experienced the highest ozone concentration (134.77 +/- 42.82 mu g/m3), exceedance frequency (46 days (23.23 %)), and proportion of EOPEs (21 instances, 47.7 %) under the control of peripheral subsidence of typhoon (Type 5). Regional southeast winds correlated with the ozone pollution in Hefei. During EOPEs, a high boundary layer height, solar radiation, and temperature; low humidity and cloud cover; and pronounced subsidence airflow occurred over Hefei and the broader YRD region. The East-South (E_S) patterns exhibited the highest frequency (28 instances, 65.11 %). Regarding the TPPs and geographical sources of the near-surface air masses during historical EOPEs. The YRD was the main source for land-originating air masses under E_S patterns (50.28 %), with Hefei, southern Anhui, southern Jiangsu, and northern Zhejiang being key contributors. These findings can help improve ozone pollution early warning and control mechanisms at urban and regional scales. (c) 2025 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

Following the success of the environmental trace gases monitoring instrument (EMI) on board the GaoFen5 satellite, algorithms have been applied to the EMI onboard the atmospheric environment monitoring satellite (DQ-1) to provide global absorbing aerosol index (AAI) products. Despite improvements to the accuracy of satellite-derived AAI products, the presence of viewing geometries and radiometric calibration problems substantially degrade EMI AAI product quality. To overcome these constraints, we propose a reflectance correction method based on a large-scale statistical method. Appropriate correction coefficients were determined for each ground pixel in the EMI reflectances for the ultraviolet visible through a comparison with reflectances calculated using the radiative transfer model, and correction coefficients were applied to AAI results to remove the structural features induced by viewing geometries and radiometric calibration problems. Reflectance calibration was performed using extensive real-time data from global regions collected between June 2022 and January 2023. The corrected reflectances were then used to derive the AAI and analyze seasonal variations. Based on a comprehensive validation of the TROPOMI products, the proposed method significantly improved the capability of EMI in identifying aerosol plumes and provided a more homogeneous AAI distribution. The correction method is satisfying for eliminating the asymmetry in AAI values. The comparison of the EMI with TROPOMI shows a high correlation of 0.91 and a root mean square of 0.296.

Bromine oxides (BrO) play a critical role in ozone depletion and boundary layer chemistry. During the spring-summer period of 2024 (May 1 to June 15), Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements were conducted in Hangzhou Bay Area, China, to observe the presence of BrO, aerosols, and other trace gases (NO₂, HCHO, etc.). The average BrO volume mixing ratio (VMR) during the observation period was 2.14 ppt, increasing to 4.24 ppt during pollution episodes. High concentrations of BrO were primarily observed in the boundary layer at altitudes of 1.5–2.5 km, while other trace gases are mainly concentrated between 0-1 km near the surface. BrO concentrations tended to peak during the morning hours (7:00 am–10:00 am local time), showing a clear correlation with aerosol variations, indicating significant photochemical activation. A anti-correlation was observed between BrO and ozone (O₃), revealing a bromine-mediated O₃ depletion mechanism.Furthermore, the overall pollutant concentration in June was higher than in May, and this change is closely related to seasonal meteorological factors, particularly variations in wind direction and temperature, which are considered the main factors influencing BrO levels.Validation conducted during the CINDI-3 campaign demonstrated the high reliability of MAX-DOAS measurements, confirming the robustness of the MAX-DOAS technique for monitoring coastal air quality. These findings enhance our understanding of BrO dynamics in coastal regions and their impact on atmospheric chemistry.

As the most economically, industrially, and transport-developed region in China, Eastern China suffers from severe pollution due to anthropogenic emissions. To better understand the distribution and transport of pollutants in this region, a regional-scale long-distance mobile observation experiment was conducted from August to September 2020 in the North China Plain (NCP), the Yangtze River Delta (YRD), and the southeastern coastal (SEC) areas, obtaining the distribution characteristics of NO2 column concentrations in different areas. The NO2 pollution in the Beijing-Tianjin-Hebei region of the NCP, especially along the southwest measurement line on the eastern side of the Taihang Mountains, is the most severe. The NO2 values in the SEC only show an increase around several large cities. The highest NO2 values were recorded on the Hefei to Shanghai segment in the YRD. The study further discusses the NO2 transport process along the typical transport section from Hefei to Shanghai. By combining WRF-Chem model simulations, the NO2 transport flux across the section was quantitatively analyzed. The results showed that under a southerly wind field, the measured and modeled NO2 transport fluxes were 10.588 kg/s and 13.254 kg/s, respectively; under a northerly wind field, the measured and modeled fluxes were 28.881 kg/s and 32.207 kg/s, respectively. The measured values differed by 2.73 times, and the modeled values differed by 2.43 times, indicating a significant difference in transport flux between the north and south directions. Combining emission inventory data, it was found that the NOx emission rate in the northern part of the YRD is 2.03 times that of the southern part, indicating high NOx emissions. This study reveals the differences in pollution transport flux in the north-south direction of the region, providing data support for exploring new pathways for regional linkage, coordinated management, and win-win cooperation in total pollutant control.

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.

This study addresses significant knowledge gaps in understanding the complex interplay between atmospheric chemistry and synoptic conditions. Using emerging machine learning techniques - Boosted Regression Trees (BRTs) and Random Forest (RF) models - we investigate the influence of synoptic conditions on pollutant levels. Several BRTs and RF models are developed to estimate surface concentrations of ozone (O 3 ), nitrogen dioxide (NO 2 ), and formaldehyde (HCHO). By considering a range of algorithmic structures and explanatory variables for each pollutant, the research aims to identify the most skillful predictive approaches and influential factors governing pollutant levels. The design seeks to highlight key determinants of concentration patterns without constraining the investigation to pre -defined model structures or explanatory variable sets. Introducing a novel methodology, Correlation Coefficient Differential Evaluation (C 2 DE), we quantitatively assess the influence of explanatory variables. C 2 DE reveals significant contributions from spatial variables (i.e., trajectory clusters at varying altitudes), formaldehyde to nitrogen dioxide ratio (FNR), and meteorological parameters. Specifically, spatial variables contribute approximately 28 % to O 3 concentrations, while the FNR accounts for around 5.2 - 9.8 % of the overall influence. For NO 2 and HCHO, spatial variables contribute around 26.5 % and 32.1 %, respectively. Moreover, when considering the combined influence of meteorological parameters, these collectively explain about 45.34 %, 35.31 %, and 45.41 % of the variations in O 3 , NO 2 , and HCHO concentrations, respectively. Thus, C 2 DE provides valuable insights into the relative contributions of these factors, aiding in the comprehensive evaluation of air quality dynamics. This underscores the need for a multifaceted approach to comprehending and effectively addressing air pollution before devising its control strategies.

Shihezi City has experienced severe ozone pollution. The vertical observation of ozone precursors (NO 2 and HCHO) and SO 2 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 mu g/m 3 , and it mainly increased when the northerly wind dominated, accompanied by the increasing of its precursors. In addition, SO 2 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 NO 2 and SO 2 decreased exponentially with the rise of vertical height, and their concentrations dropped rapidly within 0 - 1 km. The R FN range of the transitional regime in Shihezi City was [1.26, 2.80]. Given that ozone pollution mostly occurred when R FN was 1 - 2, the chemical production of near-surface ozone in Shihezi City was controlled by a transition regime. The R FN vertical pattern was Gaussian type and reached a maximal value at 400 - 600 m. R FN increased at the middle altitude (0.4 - 1.2 km), and the ozone formation was controlled by the transitional regime. R FN 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 O 3 precursors vertical distribution and O 3 formation sensitivity in Shihezi City.

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.