Surface Ozone Concentrations Research Articles

Performance evaluation of UKESM1 for surface ozone across the pan-tropics

Abstract. Surface ozone monitoring sites in the tropics are limited, despite the risk that surface ozone poses to human health, tropical forest and crop productivity. Atmospheric chemistry models allow us to assess ozone exposure in unmonitored locations and evaluate the potential influence of changing policies and climate on air quality, human health and ecosystem integrity. Here, we utilise in situ ozone measurements from ground-based stations in the pan-tropics to evaluate ozone from the UK Earth system model, UKESM1, with a focus on remote sites. The study includes ozone data from areas with limited previous data, notably tropical South America, central Africa and tropical northern Australia. Evaluating UKESM1 against observations beginning in 1987 onwards, we show that UKESM1 is able to capture changes in surface ozone concentration at different temporal resolutions, albeit with a systematic high bias of 18.1 nmol mol−1 on average. We use the diurnal ozone range (DOR) as a metric for evaluation and find that UKESM1 captures the observed DOR (mean bias of 2.7 nmol mol−1 and RMSE of 7.1 nmol mol−1) and the trend in DOR with location and season. Results from this study reveal that hourly ozone concentrations from UKESM1 require bias correction before use for impact assessments based on human and ecosystem health. Indeed, hourly surface ozone data have been crucial to this study, and we encourage other modelling groups to include hourly surface ozone output as a default.

Diurnal hourly near-surface ozone concentration derived from geostationary satellite in China

Near-surface O3 is a harmful atmospheric pollutant and a key component of urban photochemical pollution. The availability of satellite ozone concentration products is predominantly restricted to daytime, resulting in a lack of understanding of nighttime ozone pollution (e.g. nocturnal ozone enhancement events). This research leverages 5-km bright temperatures derived from Advanced Himawari Images (AHI) on the Himawari-8 satellite, in conjunction with auxiliary data, to estimate 24-h near-surface O3 concentrations in China at a resolution of 5 km for 2020. The model achieves an average 5-fold cross-validation R2 of 0.92. Comparative analysis with on-site observations reveals that the model has low relative errors between 8:00 and 21:00 LT. The estimated O3 maps depict a consistent 24-h variation pattern, characterized by high and most fluctuating concentrations during the daytime, reaching a peak around 16:00 LT, which is primarily due to the increased photochemical reactions and the O3 accumulation in the mid-afternoon. In the daytime of summer, high surface ozone concentrations are mainly contributed by June. The elevated levels of O3 are predominantly found in central China, particularly in the Beijing-Tianjin-Hebei region and Inner Mongolia. It can also be seen that although the highest average daytime surface O3 concentration occurs in summer, the highest nighttime concentration is observed in spring, which may be attributed to the frequent occurrence of horizontal transport and vertical mixing of O3. This study holds promise in providing comprehensive round-the-clock surface O3 data across China, thereby enhancing our understanding of diurnal ground-level O3 variations.

Impacts of tropical cyclone–heat wave compound events on surface ozone in eastern China: comparison between the Yangtze River and Pearl River deltas

Abstract. China has implemented some air pollution management measures in recent years, yet severe ozone pollution remains a significant issue. The southeastern coast of China (SECC) is often influenced by hot extremes and tropical cyclones (TCs), and the two can occur simultaneously (TC–HDs). The compound TC–HDs show a rising trend in the summers of 2014–2019, potentially affecting ozone pollution. Here, we found that surface ozone concentrations over the SECC are more elevated during extremely hot days than the summer climatology. However, compared to extremely hot days alone (AHDs), the maximum 8 h average ozone (MDA8 O3) concentration increases by an average of 6.8 µg m−3 in the Pearl River Delta (PRD) and decreases by 13.2 µg m−3 in the Yangtze River Delta (YRD) during the compound TC–HDs. The meteorological conditions during AHDs favor the chemical production of ozone over the SECC, exhibiting increased temperature and solar radiation and decreased relative humidity. Relative to AHDs, strong northeasterly winds prevail in the SECC during TC–HDs, suggesting the potential of ozone cross-regional transport between YRD and PRD. The process analysis in the chemical transport model (GEOS-Chem) suggests that relative to AHDs, the chemical production of ozone is enhanced in YRD during TC–HDs, while horizontal transport alleviates ozone pollution in YRD but worsens it in PRD through cross-regional transport. The results highlight the significant effects of cross-regional transport in modulating ozone pollution in the two megacity clusters during hot extremes accompanied by TC activities, giving insight into future ozone control measures over the SECC under global warming.

Development of a city-level surface ozone forecasting system using deep learning techniques and air quality model: Application in eastern China

Utilizing regional air quality models to accurately forecast surface ozone (O3) concentrations, particularly high concentrations, is essential for protecting public health. However, forecasts of air quality model often deviate from site observations due to the limitation of grid resolution and uncertainties from emission sources, meteorological conditions, and chemical reaction mechanisms. Especially, the underestimation is significant under condition of high O3 concentrations. Moreover, such deviations tend to accumulate as forecast lead time increases, compounding the challenges associated with reliable air quality forecast. In this study, we employed AlexNet architecture, a classical convolutional neural network, combined with multiple variables related to meteorology, chemistry, emission and geography to establish a non-linear relationship between grid-scale input variables and site-scale hourly O3 forecast biases in Eastern China, aiming to realize accurate city-level ozone forecast based on a regional air quality prediction model (i.e., Nested Air Quality Prediction Model System, NAQPMS). By assigning weights to high-bias samples and high-concentration samples within the loss function, the proposed Weighted AlexNet model (W_AlexNet) effectively reduced forecast biases and enhanced its capability to predict O3 pollution levels. Compared to NAQPMS, W_AlexNet model demonstrated a 25.71% improvement in RMSE and a 7.17% increase in IOA averagely for hourly O3 (O3-1h) forecasts across four different lead times (24-h, 48-h, 72-h, and 96-h). Notably, W_AlexNet model alleviated the tendency of NAQPMS to underestimate high concentrations and showed a superior performance in improving O3-1h pollution level forecasts, particularly for the 72-h and 96-h lead times. W_AlexNet model can effectively mitigate the bias accumulation effect over increasing lead times, thereby enhancing the reliability of longer-term forecasts. Thus, the W_AlexNet model serves as a post-processing model that can calibrate forecast biases in air quality prediction models, significantly improving the accuracy of O3 high concentration forecasts and providing more precise early warnings of O3 pollution. This underscores its utility in air quality management.

National and transboundary contributions to surface ozone concentration across European countries

Tropospheric ozone impacts health, climate, and ecosystems. Effective ozone mitigation policies are challenged by limited quantitative understanding of national versus transboundary contributions to surface ozone. This study uses a chemical transport model with a source apportionment algorithm to analyze ozone contributions across Europe from 2015 to 2017 during peak ozone season. We quantify country-level ozone production and imported ozone, distinguishing contributions from 35 European countries, neighboring countries, seas, and hemispheric influences. Results show substantial contributions from outside the 35 European countries, with hemispheric contributions playing a significant role. European contributions are crucial during high ozone episodes, especially from Germany, France, Italy, the UK, Poland, and Spain. Spain, northern Italy, and northwest France are identified as areas where national precursor reductions would be more effective in improving national air quality. Furthermore, 25 of the 35 European countries studied are net importers of cumulative ozone mass, with the Netherlands, Belgium, and the UK acting as major exporters. These findings highlight the need for comprehensive air quality policies and cross-border cooperation.

Near-surface ozone concentration variability analysis in the Karadag Nature Reserve

The article presents the results of a study of a near-surface ozone concentration variability in the Crimea at the background environmental monitoring station in the Karadag Nature Reserve for 2012–2021 years with a more detailed analysis of the last six years from 2016 to 2021. A significantly high level air pollution of а near-surface ozone was revealed in the observation region, despite the absence of nearby sources of industrial emissions. The relationship of near-surface ozone concentration and meteorological parameters was investigated. Wind directions leading to increased levels of near-surface ozone pollution are established. Intra-annual variations of near-surface ozone concentration are analyzed, the factors causing the local summer minimum of surface ozone concentration in some years are established. By using the NOAA HYSPLIT model and ERA5 reanalysis, a spatial analysis of the atmospheric circulation pattern in the region was carried out. The recurrence of episodes of exceeding the ozone concentration 100 micrograms/m3 during 8 or more hours (WHO recommendation) was estimated. Possible causes of these episodes were determined. The mechanisms of long-range transport and its contribution to the near-surface ozone regime in the area of the station have been established. Annual trends of near-surface ozone concentration in the period 2012–2021 years are estimated as statistically insignificant.

The Impact of Stratosphere-to-Troposphere Transport Associated with the Northeast China Cold Vortex on Surface Ozone Concentrations in Eastern China

Abstract As the surface ozone (O3) concentration is increasing despite emission control measures, it is urgent to clarify the impact of dynamic transport, such as quantifying the impact of stratosphere-to-troposphere transport (STT) on the surface O3 budget. Based on observations and numerical models, this study explores the relationship between the surface O3 concentration in eastern China (30°–38°N, 112°–122°E) and the location and intensity of the Northeast China cold vortex (NCCV), a predictable weather system. The results show that when the NCCV occurs in the southeastern region (35°–47.5°N, 125°–140°E), there is a corresponding increase in the surface O3 concentration in eastern China. The stronger the intensity of the NCCV is, the greater the increase in surface O3. The strongest 10% of the NCCV may cause an increase in the surface O3 concentration of 12–18 ppbv (30%–45% of the summer average surface O3 concentration). NCCV events and enhanced O3 are related to the STT. Anomalies in the 200-hPa wind field induce downward motion in the NCCV region and its west side. The cold O3-rich stratospheric air is transported southeastward and downward during the NCCV period, leading to an increase in the surface O3 concentration. The correlation and predictability between 500-hPa meteorological fields and surface O3 concentrations are also highlighted in this work. Significance Statement Despite the emission control measures taken in the past, the surface O3 concentration continues to increase in most regions of the world. It is urgent to quantify all the factors that impact the surface O3 concentration. This study focuses on a predictable weather system, the Northeast China cold vortex (NCCV), and its connection with stratosphere-to-troposphere transport (STT) that induces enhanced surface O3 concentrations. Our findings provide a fresh perspective for studying the sources and forecasting of O3 concentrations by linking upper-level weather systems and meteorological fields with changes in surface O3 concentrations.

Responses of surface ozone under the tropical cyclone circulations: Case studies from Fujian Province, China

The circulation of tropical cyclones (TCs) exerts a multifaceted influence on the spatial and temporal distribution of surface pollutants. This study investigates the response of surface ozone (O3) concentration to the TCs in Fujian Province from June to December 2022 by analyzing the contributions of atmospheric pollutants, meteorological conditions, and dynamical transports. Empirical orthogonal function (EOF) decomposition methods are used to analyze the spatio-temporal distribution patterns of affected O3, and a Gradient Boosting Regression Trees (GBRT) machine learning model is employed to estimate surface O3 concentration, quantifying the influence of each factor. The results indicate an anomaly increase in O3 concentration during this period, with photochemistry-related meteorological conditions being the primary influencer, accounting for 66.9% of O3 variations, elucidating the interpretability of the GBRT model for attributing changes in O3 concentration. Low relative humidity and high temperature conditions have been identified as pivotal factors influencing the rise in O3 concentrations. The presence of TC undermines this predominant influence, amplifying the role of transport factors and other atmospheric pollutants. In the case studies of TC (Muifa and Nanmadol, 2022), the slow or stagnant TCs triggered persistent downdrafts in its periphery and brought favorable meteorological conditions such as clear sky and warm temperature for photochemistry. TCs also enhances the impact of horizontal and vertical dynamic transport on O3 concentrations. This work provides vital insights into the complex interplay between TCs and surface O3 concentrations, highlighting the need for targeted environmental and air quality management strategies in regions frequently impacted by TCs.

Aggravated surface O3 pollution primarily driven by meteorological variations in China during the 2020 COVID-19 pandemic lockdown period

Abstract. Due to the lockdown during the COVID-19 pandemic in China from late January to early April in 2020, a significant reduction in primary air pollutants, as compared to the same time period in 2019, has been identified by satellite and ground observations. However, this reduction is in contrast with the increase of surface ozone (O3) concentration in many parts of China during the same period from 2019 to 2020. The reasons for this contrast are studied here from two perspectives: emission changes and inter-annual meteorological variations. Based on top-down constraints of nitrogen oxide (NOx) emissions from TROPOMI measurements and GEOS-Chem model simulations, our analysis reveals that NOx and volatile organic compound (VOC) emission reductions as well as meteorological variations lead to 8 %, −3 % and 1 % changes in O3 over North China, respectively. In South China, however, we find that meteorological variations cause ∼ 30 % increases in O3, which is much larger than −1 % and 2 % changes due to VOC and NOx emission reductions, respectively, and the overall O3 increase in the simulations is consistent with the surface observations. The higher temperature associated with the increase in solar radiation and the decreased relative humidity are the main reasons that led to the surface O3 increase in South China. Collectively, inter-annual meteorological variations had a larger impact than emission reductions on the aggravated surface O3 pollution in China during the lockdown period of the COVID-19 pandemic.

Assessment of ozone pollution on rice yield reduction and economic losses in Sichuan province during 2015–2020

In recent years, there has been a significant increase in surface ozone (O3) concentrations in the troposphere. Ozone pollution has significant adverse effects on ecosystems, human health, and climate change, particularly on crop growth and yield. This study utilized the observational hourly O3 data, cumulative O3 concentration over 40 ppb per h (AOT40), and the mean daytime 7-h O3 concentration (M7) to analyze the spatiotemporal distributions of relative yield losses (RYLs) and evaluate the yield reduction and economic losses of rice in Sichuan province from 2015 to 2020. The results indicated that the average O3 concentration during the growing rice season ranged from 55.4 to 69.3 μg/m3, with the highest O3 concentration observed in 2017, and the AOT40 ranged from 4.5 to 8.7 ppm h from 2015 to 2020. At the county level, the O3 concentration, AOT40, and the relative yield loss (RYL) of rice based on AOT40 exhibited clear spatiotemporal differences in Sichuan. The RYLs of AOT40 were 4.9–9.2% from 2015 to 2020. According to AOT40 and M7 metrics, the yield loss and economic losses attributed to O3 pollution amounted to 78.75–150.36 (9.74–21.54) ten thousand tons, and 2079.08–4149.89 (257.25–594.45) million Yuan, respectively. Rice yield and economic losses were relatively large in the Chengdu Plain, southern Sichuan, and northeast Sichuan. These findings will contribute to a deeper understanding of the detrimental effects of elevated surface O3 concentrations on rice crops. It is imperative to implement more stringent O3 reduction measures aimed at lowering O3 concentrations, enhancing rice quality, and safeguarding food security in Sichuan.

Machine-learning-based corrections of CMIP6 historical surface ozone in China during 1950–2014

Due to a lack of long-term observations in China, reports on historical ozone concentration are severely limited. In this study, by combining observation, reanalysis and model simulation data, XGBoost machine learning algorithm is used to correct the surface ozone concentration from CMIP6 climate model, and the long-term and large-scale surface ozone concentration of China during 1950–2014 is obtained. The long-term evolutions and trends of ozone and meteorological effects on interannual ozone variations are further analyzed. The results reveal that CMIP6 historical simulations have a large underestimation in ozone concentrations and their trends. The XGB-derived ozone are closer to observations, with R2 value of 0.66 and 0.74 for daily and monthly retrievals, respectively. Both the concentrations and exceedances of ozone in most parts of China have shown increasing trends from 1950 to 2014. The daily mean ozone concentration without climate change effects is estimated to be 117 ppb in the year 1950 averaged over China. It indicates that the increase in anthropogenic emissions of China has a significant contribution to ozone enhancement between 1950 and 2014. The higher ozone growth rates of XGB retrievals than those from the model indicate a regional surface ozone penalty due to the warming climate. The relatively significant increment in ozone are estimated in the Central and Western China. Seasonally, the ozone enhancement is largest in spring, indicating a shift in seasonal variation of ozone. Given the uncertainty in simulating historical ozone by climate model, we show that machine learning approaches can provide improved assessment of evolution in surface ozone, along with valuable information to guide future model development and formulate future ozone pollution prevention and control policies.

Observational analysis of surface ozone variability in China from 2015 to 2020: Insights from consecutive ENSO episodes

Utilizing daily surface ozone (O3) concentration data (MDA8-O3) from nearly 1500 monitoring stations across mainland China, complemented by gridded atmospheric reanalysis data, this study conducts a comprehensive analysis of O3 concentration, anomalies, and oscillations. Employing regression and composite analyses, we investigate the potential linkage between O3 variations and the phase and strength of El Niño-Southern Oscillation (ENSO) across diverse regions and seasons in China. Noteworthy findings include the identification of regions exhibiting peak O3 concentrations in autumn or spring, deviating from the typical seasonal cycle, as well as regions exhibiting varying strengths of seasonal and semi-annual O3 oscillations. Moreover, the study unveils the spatiotemporal patterns of synoptic and intra-seasonal O3 oscillations. The analyses reveal a prevailing inverse association between O3 anomalies and ENSO in most Chinese regions except for the southern and southeastern coastal areas. The potential impacts of ENSO on O3 are elucidated by anomalous atmospheric conditions linked to ENSO, the nature of which strongly depends on the region and season. In northern China, anomalous temperature and solar radiation related to ENSO exert a more pronounced influence on O3 anomalies. On the other hand, in southern China, anomalies in wind speed/direction and precipitation associated with anomalous atmospheric circulations play a more predominant role. These findings contribute valuable insights to the nuanced understanding of O3 variability, paving the way for the development of sophisticated O3 forecasting approaches tailored to different regions and seasons across China.

Parsimonious estimation of hourly surface ozone concentration across China during 2015–2020

Surface ozone is an important air pollutant detrimental to human health and vegetation productivity, particularly in China. However, high resolution surface ozone concentration data is still lacking, largely hindering accurate assessment of associated environmental impacts. Here, we collected hourly ground ozone observations (over 6 million records), remote sensing products, meteorological data, and social-economic information, and applied recurrent neural networks to map hourly surface ozone data (HrSOD) at a 0.1° × 0.1° resolution across China during 2015–2020. The coefficient of determination (R2) values in sample-based, site-based, and by-year cross-validations were 0.72, 0.65 and 0.71, respectively, with the root mean square error (RMSE) values being 11.71 ppb (mean = 30.89 ppb), 12.81 ppb (mean = 30.96 ppb) and 11.14 ppb (mean = 31.26 ppb). Moreover, it exhibits high spatiotemporal consistency with ground-level observations at different time scales (diurnal, seasonal, annual), and at various spatial levels (individual sites and regional scales). Meanwhile, the HrSOD provides critical information for fine-resolution assessment of surface ozone impacts on environmental and human benefits.

Deciphering multi-temporal scale dynamics in the concentration, sources and processes of near surface ozone over different climatic regions of India.

This study aims to investigate the factors influencing seasonal and long-term (2003-2021) changes in the near surface ozone (850 hpa) concentrations over different climatic sub-regions of India. Detailed comparison of daily (2019-2021) near surface ozone values of ERA-5 and CAAQMS (Continuous Ambient Air Quality Monitoring Stations) ground-based measurements revealed that ERA-5 is temporally in phase with CAAQMS measurements falling indifferent climatic sub-regions of India. ERA-5 near surface ozone shows statistically significant long-term (2003-2021) positive trends [2-4 percent per decade (ppd)] over most of the climatic sub-regions, over Indo-Gangetic Planes (IGPs), Southern and Central India trends are particularly strong. Trends were also estimated for each season separately, which were largely positive (2-6 ppd) over Central and Southern India in the Autumn and Winter seasons. Extensive climatological analysis reveals that the reversal of winds in the Indian monsoonal system plays a vital role in such trend patterns across the Indian subcontinent. South-westerly winds from June through September presumably bring ozone deficit air of marine origin, thus causing a dilution effect while the North-easterly winds during late Autumn and early Winters plausibly bring ozone-rich air from the stratospheric-tropospheric efflux dominated Himalayan region. It allows near surface ozone enhancement over Central and Southern India. Seasonal Principal component analysis (PCA) revealed that precursor gases (CH4 and NO2) and climatic variables especially specific humidity (SH) are the primary drivers of near surface ozone variability in the Winter season, while in Spring, climatic variables like boundary layer height (BLH), temperature (T) and SH have a significant role. Principal component regression (PCR) reveals a long-term increase in near surface ozone levels mostly dominated by precursor concentration over IGPs and Southern sub-regions. Whereas, BLH, T and SH significantly explain near surface ozone trends over North-eastern and Coastal India.

Radiative and Chemical Effects of Non‐Homogeneous Methane on Terrestrial Carbon Fluxes in Asia

AbstractMethane (CH4) plays a crucial role in shaping terrestrial ecosystems due to its radiative effect and atmospheric photochemical reactions. In this study, we employed an enhanced regional climate‐chemistry‐ecosystem model (RegCM‐Chem‐YIBs) to comprehensively evaluate the impacts of both radiative and chemical effects of CH4 on terrestrial carbon fluxes across the East, South, and Southeast Asia (EA, SA, SEA) during the year 2010. Our findings showed that the radiative effects of CH4 yielded a positive influence on carbon fluxes. Specifically, the EA region experienced a significant increase in the gross primary production (GPP), reaching up to 0.515 Pg C Yr−1. In comparison, the SEA region exhibited a decrease in the net ecosystem exchange (NEE) of approximately −0.066 Pg C Yr−1. Further analysis revealed that alterations in radiation and vapor pressure deficit (VPD) were dominant drivers. Conversely, the chemical effects of CH4 lead to heightened regional surface ozone (O3) concentrations (2.704–3.115 ppb) and generate a negative response in carbon fluxes. Within the SEA region, GPP observed a decrease of up to −0.144 Pg C Yr−1, while NEE displayed a significant increase of 0.022 Pg C Yr−1. Taken together, the combined radiative and chemical effects of CH4 indicated a positive impact on regional carbon fluxes, with GPP increasing by 0.632 Pg C Yr−1 and NEE decreasing by −0.09 Pg C Yr−1. This holistic perspective is crucial for comprehending the intricate interactions linking climate change, atmospheric pollution, and the global carbon cycle.

Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0

Abstract. Elevated surface ozone (O3) concentrations can negatively impact growth and development of crop production by reducing photosynthesis and accelerating leaf senescence. Under unabated climate change, future global O3 concentrations are expected to increase in many regions, adding additional challenges to global agricultural production. Presently, few global process-based crop models consider the effects of O3 stress on crop growth. Here, we incorporated the effects of O3 stress on photosynthesis and leaf senescence into the Decision Support System for Agrotechnology Transfer (DSSAT) crop models for maize, rice, soybean, and wheat. The advanced models reproduced the reported yield declines from observed O3-dose field experiments and O3 exposure responses reported in the literature (O3 relative yield loss RMSE <10 % across all calibrated models). Simulated crop yields decreased as daily O3 concentrations increased above 25 ppb, with average yield losses of 0.16 % to 0.82 % (maize), 0.05 % to 0.63 % (rice), 0.36 % to 0.96 % (soybean), and 0.26 % to 1.23 % (wheat) per ppb O3 increase, depending on the cultivar O3 sensitivity. Increased water deficit stress and elevated CO2 lessen the negative impact of elevated O3 on crop yield, but potential yield gains from CO2 concentration increases may be counteracted by higher O3 concentrations in the future, a potentially important constraint to global change projections for the latest process-based crop models. The improved DSSAT models with O3 representation simulate the effects of O3 stress on crop growth and yield in interaction with other growth factors and can be run in the parallel DSSAT global gridded modeling framework for future studies on O3 impacts under climate change and air pollution scenarios across agroecosystems globally.

Influence of Transboundary Pollution on the Variability of Surface Ozone Concentrations in the Desert Southwest of the U.S.: Case Study for Arizona

Arizona, a rapidly growing state in the southwestern U.S., faces ozone pollution challenges, including nonattainment areas in Yuma and Maricopa counties influenced by neighboring state pollution transport. In this study, we use five-year (2017–2021) hourly back-trajectories and O3 concentration data for concentration-weighted trajectory (CWT) analysis to identify transport pathways and potential source regions of O3 at six monitoring sites in Arizona. We divide the data into five seasons (winter, spring, dry summer, monsoon summer, and fall) to examine variations in O3 concentration and transport across sites and seasons. The highest mean O3 concentrations occur during spring (37–49 ppb), dry summer (39–51 ppb), and monsoon summer (34–49 ppb), while winter (19–41 ppb) exhibits the lowest seasonal mean. The CWT results reveal that high O3 concentrations (≥40 ppb) in Arizona, with the exception of Phoenix and Tucson sites, are influenced significantly by regional and international transport, especially in spring (14.9–35.4%) and dry summer (12.7–26.9%). The major potential source areas (excluding the Phoenix and Tucson sites) are predominantly located outside Arizona. This study highlights the critical role of pollution transport in influencing O3 variability within Arizona and will be valuable in shaping pollution control strategies in the future.

Interactions between aerosols and surface ozone in arid and semi-arid regions of China.

Atmospheric aerosols affect surface ozone concentrations by influencing radiation, but the mechanism and dominant factors are unclear. Therefore, this paper analyses the changes in aerosol-radiative-surface ozone in China's arid and semi-arid regions with the help of the Atmospheric Radiative Transfer (SBDART) model. The results suggest that Aerosol Optical Depth (AOD) and coarse Particulate Matter (PM10) have the same trend, with high values in spring and winter and low values in summer and autumn. Surface ozone is high in spring and summer and low in autumn and winter. Surface ozone is higher in spring and summer and lower in autumn and winter. In winter, mainly secondary pollutants are dominated by high pollution levels. In the rest of the seasons, a mixture of dust, motor vehicle exhaust, and soot is dominated by low pollution levels. Surface ozone is positively correlated with fine particles and negatively correlated with coarse particles. Temperature is positively correlated with surface ozone in all seasons and negatively correlated with PM10 in summer, autumn, and winter. Precipitation negatively correlates with PM10 each season and surface ozone in winter and spring. Analysis of surface ozone and PM10 sources in the more polluted city of Hohhot based on the back-line trajectory model showed that airflow trajectories mainly transported surface ozone and PM10 pollution from northwestern Inner Mongolia and western Mongolia. During dusty solid weather, the decrease in radiation reaching the Earth's surface and the cooling effect of aerosols lead to lower temperatures, which slows down the rate of chemical reactions of precursors of surface ozone, resulting in lower ozone concentrations at the surface. This study can provide a theoretical reference for aerosol and surface ozone control in arid and semi-arid areas of China.

Evaluating the multi-variable influence on O3, NO2, and HCHO using BRTs and RF model

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 (O3), nitrogen dioxide (NO2), 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 (C2DE), we quantitatively assess the influence of explanatory variables. C2DE 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 O3 concentrations, while the FNR accounts for around 5.2–9.8 % of the overall influence. For NO2 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 O3, NO2, and HCHO concentrations, respectively. Thus, C2DE 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.

Aerosol Vertical Structure and Optical Properties during Two Dust and Haze Episodes in a Typical Valley Basin City, Lanzhou of Northwest China

The vertical profiles of aerosol optical properties are vital to clarify their transboundary transport, climate forcing and environmental health influences. Based on synergistic measurements of multiple advanced detection techniques, this study investigated aerosol vertical structure and optical characteristics during two dust and haze events in Lanzhou of northwest China. Dust particles originated from remote deserts traveled eastward at different altitudes and reached Lanzhou on 10 April 2020. The trans-regional aloft (~4.0 km) dust particles were entrained into the ground, and significantly modified aerosol optical properties over Lanzhou. The maximum aerosol extinction coefficient (σ), volumetric depolarization ratio (VDR), optical depth at 500 nm (AOD500), and surface PM10 and PM2.5 concentrations were 0.4~1.5 km−1, 0.15~0.30, 0.5~3.0, 200~590 μg/m3 and 134 μg/m3, respectively, under the heavy dust event, which were 3 to 11 times greater than those at the background level. The corresponding Ångström exponent (AE440–870), fine-mode fraction (FMF) and PM2.5/PM10 values consistently persisted within the ranges of 0.10 to 0.50, 0.20 to 0.50, and 0.20 to 0.50, respectively. These findings implied a prevailing dominance of coarse-mode and irregular non-spherical particles. A severe haze episode stemming from local emissions appeared at Lanzhou from 30 December 2020 to 2 January 2021. The low-altitude transboundary transport aerosols seriously deteriorated the air quality level in Lanzhou, and aerosol loading, surface air pollutants and fine-mode particles strikingly increased during the gradual strengthening of haze process. The maximum AOD500, AE440–870nm, FMF, PM2.5 and PM10 concentrations, and PM2.5/PM10 were 0.65, 1.50, 0.85, 110 μg/m3, 180 μg/m3 and 0.68 on 2 January 2021, respectively, while the corresponding σ and VDR at 0.20–0.80 km height were maintained at 0.68 km−1 and 0.03~0.12, implying that fine-mode and spherical small particles were predominant. The profile of ozone concentration exhibited a prominent two-layer structure (0.60–1.40 km and 0.10–0.30 km), and both concentrations at two heights always remained at high levels (60~72 μg/m3) during the entire haze event. Conversely, surface ozone concentration showed a significant decrease during severe haze period, with the peak value of 20~30 μg/m3, which was much smaller than that before haze pollution (~80 μg/m3 on 30 December). Our results also highlighted that the vertical profile of aerosol extinction coefficient was a good proxy for evaluating mass concentrations of surface particulate matters under uniform mixing layers, which was of great scientific significance for retrieving surface air pollutants in remote desert or ocean regions. These statistics of the aerosol vertical profiles and optical properties under heavy dust and haze events in Lanzhou would contribute to investigate and validate the transboundary transport and radiative forcing of aloft aerosols in the application of climate models or satellite remote sensing.