Satellite UV-Vis spectroscopy: implications for air quality trends and their driving forces in China during 2005-2017

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.

Applications of remote sensing vis-à-vis machine learning in air quality monitoring and modelling: a review

Environmental contamination especially air pollution is an exponentially growing menace requiring immediate attention, as it lingers on with the associated risks of health, economic and ecological crisis. The special focus of this study is on the advances in Air Quality (AQ) monitoring using modern sensors, integrated monitoring systems, remote sensing and the usage of Machine Learning (ML), Deep Learning (DL) algorithms, artificial neural networks, recent computational techniques, hybridizing techniques and different platforms available for AQ modelling. The modern world is data-driven, where critical decisions are taken based on the available and accessible data. Today's data analytics is a consequence of the information explosion we have reached. The current research also tends to re-evaluate its scope with data analytics. The emergence of artificial intelligence and machine learning in the research scenario has radically changed the methodologies and approaches of modern research. The aim of this review is to assess the impact of data analytics such as ML/DL frameworks, data integration techniques, advanced statistical modelling, cloud computing platforms and constantly improving optimization algorithms on AQ research. The usage of remote sensing in AQ monitoring along with providing enormous datasets is constantly filling the spatial gaps of ground stations, as the long-term air pollutant dynamics is best captured by the panoramic view of satellites. Remote sensing coupled with the techniques of ML/DL has the most impact in shaping the modern trends in AQ research. Current standing of research in this field, emerging trends and future scope are also discussed.

Assessing the impact of urban form and urbanization process on tropospheric nitrogen dioxide pollution in the Yangtze River Delta, China

Optimizing urban form through urban planning and management policies can improve air quality and transition to demand-side control. Nitrogen dioxide (NO2) in the urban atmosphere, mainly emitted by anthropogenic sources such as industry and vehicles, is a key precursor of fine particles and ozone pollution. Both NO2 and its secondary pollutants pose health risks for humans. Here we assess the interactions between urban forms and airborne NO2 pollution in different cities with various stages of urbanization in the Yangtze River Delta (YRD) in China, by using the machine learning and geographical regression model. The results reveal a strong correlation between urban fragmentation and tropospheric NO2 vertical column density (TVCD) in YRD cities in 2020, particularly those with lower or higher levels of urbanization. The correlation coefficients (R2) between NO2 TVCD and the largest patch index (a metric of urban fragmentation) in different cities are greater than 0.8. For cities at other urbanization stages, population and road density are strongly correlated with NO2 TVCD, with an R2 larger than 0.61. This study highlights the interdependence among urbanization, urban forms, and air pollution, emphasizing the importance of customized urban landscape management strategies for mitigating urban air pollution.

Eliminating the interference of water for direct sensing of submerged plastics using hyperspectral near-infrared imager

Interference from water in the reflectance spectra of plastics is a major obstacle to optical sensing of plastics in aquatic environments. Here we present evidence of the feasibility of sensing plastics in water using hyperspectral near-infrared to shortwave-infrared imaging techniques. We captured hyperspectral images of nine polymers submerged to four depths (2.5-15 mm) in water using a hyperspectral imaging system that utilizes near-infrared to shortwave-infrared light sources. We also developed algorithms to predict the reflectance spectra of each polymer in water using the spectra of the dry plastics and water as independent variables in a multiple linear regression model after a logarithmic transformation. A narrow 1100-1300 nm wavelength range was advantageous for detection of polyethylene, polystyrene, and polyvinyl chloride in water down to the 160-320 µm size range, while a wider 970-1670 nm wavelength range was beneficial for polypropylene reflectance spectrum prediction in water. Furthermore, we found that the spectra of the other five polymers, comprising polycarbonate, acrylonitrile butadiene styrene, phenol formaldehyde, polyacetal, and polymethyl methacrylate, could also be predicted within their respective optimized wavelength ranges. Our findings provide fundamental information for direct sensing of plastics in water on both benchtop and airborne platforms.

Satellite spectroscopy reveals the atmospheric consequences of the 2022 Russia-Ukraine war

With increasing geopolitical conflicts and climate change, the effects of war on the atmosphere remain unclear, especially the recent large-scale war between Russia and Ukraine. Here, we assess how war affects human emission activities by observing atmospheric nitrogen dioxide (NO₂) using high-resolution satellite spectroscopy. Spatial and temporal responses of atmospheric composition to armed conflict are characterized. Significant decreases in NO₂ concentrations of 10.7-27.3 % occurred in most Ukrainian cities at the beginning of the war, in contrast to dramatic increases in NO₂ concentrations in Russian cities outside the northern border. Anomalous changes in NO₂ were also found in transportation hubs. By excluding the effect of meteorology, the machine learning model indicates that war-induced changes in anthropogenic emissions may account for ∼40 % of the reduction in NO₂ pollution for major cities such as Kyiv. Our study demonstrates that satellites can provide a unique perspective on the atmospheric consequences of humanitarian disasters.

Quantification and evaluation of atmospheric emissions from crop residue burning constrained by satellite observations in China during 2016-2020

In rural regions of China, crop residue burning (CRB) is the major biomass burning activity, which can result in massive emissions of atmospheric particulate, greenhouse gas, and trace gas pollutants. Based on Himawari-8 satellite fire radiative power and agricultural statistics data, we implemented a daily inventory of agricultural fire emissions in 2016-2020 with a 2-km spatial resolution, including atmospheric pollutants such as CO₂, CH₄, CO, N₂O, NO_X, NH₃, SO₂, PM₁₀, PM_2.5, Hg, OC, EC, and NMVOCs. Our inventory constrained by geostationary satellite monitoring is more consistent with the actual CRB emissions in China, as many flaring events occur surreptitiously in the early morning and late evening to avoid regulation, which may be overlooked by polar-orbiting satellites. The spatiotemporal characterizations of various CRB emissions are found to be consistent with multiple satellite trace gas retrievals. We also assessed the effectiveness of field burning bans in China. Combined with other relevant datasets, it was found that although China has been advocating for a long time not to burn straw in the open field, CRB emissions was not successfully controlled nationwide until 2016. We estimated that the cumulative reduction of CO₂ CRB emissions alone amounts to 809 ± 651 (2σ) teragram (Tg) during the 13th Five-Year Plan period (2016-2020), with an average value equivalent to 1.2 times the total annual territorial CO₂ emissions by fossil fuels from Germany in 2021 (675 Tg, ranked 1st in EU27 and 7th in the world). Our inventory also suggests that continuous, long-term controls are necessary. Otherwise, CRB emissions may only be delayed on a seasonal scale, rather than reduced.

Identification of volatile organic compound emissions from anthropogenic and biogenic sources based on satellite observation of formaldehyde and glyoxal

Anthropogenic volatile organic compounds (VOCs) are serious pollutants in the atmosphere because of their toxicity and as precursors of secondary organic aerosols and ozone pollution. Although in-situ measurements provide accurate information on VOCs, their spatial coverage is limited and insufficient. In this study, we provide a global perspective for identifying anthropogenic VOC emission sources through the ratio of glyoxal to formaldehyde (RGF) based on satellite observations. We assessed typical cities and polluted areas in the mid latitudes and found that some Asian cities had higher anthropogenic VOC emissions than cities in Europe and America. For heavily polluted areas, such as the Yangtze River Delta (YRD), the areas dominated by anthropogenic VOCs accounted for 23 % of the total study areas. During the COVID-19 pandemic, a significant decline in RGF values was observed in the YRD and western United States, corresponding to a reduction in anthropogenic VOC emissions. Furthermore, developing countries appeared to have higher anthropogenic VOC emissions than developed countries. These observations could contribute to optimising industrial structures and setting stricter pollution standards to reduce anthropogenic VOCs in developing countries.

Atmospheric environment monitoring technology and equipment in China: A review and outlook

Accurate monitoring of the atmospheric environment and its evolution are important for understanding the sources, chemical mechanisms, and transport processes of air pollution and carbon emissions in China, and for regulatory and control purposes. This study gives an overview of atmospheric environment monitoring technology and equipment in China and summarizes the major achievements obtained in recent years. China has made great progress in the development of atmospheric environment monitoring technology and equipment with decades of effort. The manufacturing level of atmospheric environment monitoring equipment and the quality of products have steadily improved, and a technical & production system that can meet the requirements of routine monitoring activities has been initiated. It is expected that domestic atmospheric environment monitoring technology and equipment will be able to meet future demands for routine monitoring activities in China and provide scientific assistance for addressing air pollution problems.

Advances in coastal ocean boundary layer detection technology and equipment in China

Accurate and comprehensive knowledge of the atmospheric environment and its evolution within the coastal ocean boundary layer are necessary for understanding the sources, chemical mechanisms, and transport processes of air pollution in land, sea, and atmosphere. We present an overview of coastal ocean boundary layer detection technology and equipment in China and summarize the progress and main achievements in recent years. China has developed a series of coastal ocean boundary layer detection technologies, including Light Detection and Ranging (LIDAR), turbulent exchange analyzer, air-sea flux analyzer, stereoscopic remote sensing of air pollutants, and oceanic aerosol detection equipment to address the technical bottleneck caused by harsh environmental conditions in coastal ocean regions. Advances in these technologies and equipment have provided scientific assistance for addressing air pollution issues and understanding land-sea-atmosphere interactions over coastal ocean regions in China. In the future, routine atmospheric observations should cover the coastal ocean boundary layer of China.

Inferring global surface HCHO concentrations from multisource hyperspectral satellites and their application to HCHO-related global cancer burden estimation

Formaldehyde (HCHO) is a toxic and hazardous air pollutant that widely exists in atmosphere. Insufficient spatial and temporal coverage of surface HCHO measurements is limiting studies on surface HCHO-related air quality management and health risk assessment. This study develops a method to derive global ground-level HCHO concentrations from satellite-based tropospheric HCHO columns using TM5-simulated surface-to-column conversion factor with coarse spatial resolution. The method improves the factor more representative in finer grids by constraining TM5-simulated vertical profile shapes with satellite HCHO columns. The surface HCHO concentrations derived by the Ozone Mapping and Profiler Suite (OMPS) show good correlation with in situ HCHO measurements (R = 0.59) from the U.S. Environmental Protection Agency surface network. We investigated how surface HCHO relates to urbanization and population aggregation over seven regions with high HCHO pollution. The results show urban HCHO increases as a power function with population size in China, India, and West Asia. HCHO concentrations in rural aeras also present strong log-log relationship with population aggregation in China, India, the United States, and Europe. Moreover, OMPS-derived ground-level HCHO concentrations were used to estimate global cancer burden caused by long-term outdoor HCHO exposure. The results show that up to 418188 more people worldwide will develop this cancer during the human life cycle. The global cancer burden is mainly from the South-East Asia region (33.11 %) and the Western Pacific region (22.95 %). This cancer occurrence in India and China is ranked 1st and 2nd in the world due to the large population size and serious HCHO pollution. Besides, global surface HCHO concentrations and cancer burden derived from the Environmental Trace Gases Monitoring Instrument which is China's first hyperspectral space-based spectrometer are found similar patterns with that from OMPS. Our results provide new insight into the impact of population urbanization on HCHO pollution and global outdoor HCHO-caused health risks.

Vertical profiles of the transport fluxes of aerosol and its precursors between Beijing and its southwest cities

The influence of regional transport on aerosol pollution has been explored in previous studies based on numerical simulation or surface observation. Nevertheless, owing to inhomogeneous vertical distribution of air pollutants, vertical observations should be conducted for a comprehensive understanding of regional transport. Here we obtained the vertical profiles of aerosol and its precursors using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) at the Nancheng site in suburban Beijing on the southwest transport pathway of the Beijing-Tianjin-Hebei (BTH) region, China, and then estimated the vertical profiles of transport fluxes in the southwest-northeast direction. The maximum net transport fluxes per unit cross-sectional area, calculated as pollutant concentration multiply by wind speed, of aerosol extinction coefficient (AEC), NO₂, SO₂ and HCHO were 0.98 km^-1 m s^-1, 24, 14 and 8.0 μg m^-2 s^-1 from southwest to northeast, which occurred in the 200-300 m, 100-200 m, 500-600 m and 500-600 m layers, respectively, due to much higher pollutant concentrations during southwest transport than during northeast transport in these layers. The average net column transport fluxes were 1200 km^-1 m² s^-1, 38, 26 and 15 mg m^-1 s^-1 from southwest to northeast for AEC, NO₂, SO₂ and HCHO, respectively, in which the fluxes in the surface layer (0-100 m) accounted for only 2.3%-4.2%. Evaluation only based on surface observation would underestimate the influence of the transport from southwest cities to Beijing. Northeast or weak southwest transports dominated in clean conditions with PM_2.5 <75 μg m^-3 and intense southwest transport dominated in polluted conditions with PM_2.5 >75 μg m^-3. Southwest transport through the middle boundary layer was a trigger factor for aerosol pollution events in urban Beijing, because it not only directly bringing air pollutants, but also induced an inverse structure of aerosols, which resulted in stronger atmospheric stability and aggravated air pollution in urban Beijing.

Vertical distributions and potential sources of wintertime atmospheric pollutants and the corresponding ozone production on the coast of Bohai Sea

This study investigated the wintertime vertical distributions and source areas of aerosols, NO₂, and HCHO in a coastal city of Dongying from December 2020 to March 2021, using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) and a potential source contribution function (PSCF) model, respectively. Moreover, the chemical production sensitivity of O₃ at different height layers was analyzed using HCHO/NO₂ ratios. The results revealed that the wintertime averaged highest concentrations of aerosol (1.25 km^-1), NO₂ (14.81 ppb), and HCHO (2.32 ppb) were mainly distributed at the surface layer, 100-200 m layer, and 200-300 m layer, respectively. Regarding the diurnal cycles, high concentrations of aerosol (>1.4 km^-1) and NO₂ (>16.0 ppb) usually appeared in the early morning and late afternoon, while high concentrations of HCHO (>2.5 ppb) usually occurred during 12:00-15:00. The PSCF model revealed that the wintertime aerosol mainly originated from Shandong, northern Jiangsu, Korea, and the northwestern Mongolian Plateau. Below 200 m, NO₂ was mainly from western Shandong, whereas above 600 m, it was mainly from northern Shandong and the Beijing-Tianjin-Hebei (BTH) region. The corresponding sources for HCHO were central and southern Shandong (below 200 m) and northern Shandong, northern Jiangsu, and southeastern BTH (above 600 m). In addition, the chemical production sensitivity of O₃ below 100 m was observed only in the VOC-limited regime. The percentages of O₃ production under the NO_x-limited, NO_x-VOC-limited, and VOC-limited regimes were 10.75% (31.18%), 4.30% (19.35%), and 84.95% (49.47%) at the 500-600 m (900-1000 m) layer. This study has guiding significance for the coordinated control of PM_2.5 and O₃, and can assist in the implementation of regional joint prevention and control strategies for air pollutants.

Impacts of TROPOMI-Derived NO X Emissions on NO2 and O3 Simulations in the NCP during COVID-19

NO₂ and O₃ simulations have great uncertainties during the COVID-19 epidemic, but their biases and spatial distributions can be improved with NO₂ assimilations. This study adopted two top-down NO _X inversions and estimated their impacts on NO₂ and O₃ simulation for three periods: the normal operation period (P1), the epidemic lockdown period following the Spring Festival (P2), and back to work period (P3) in the North China Plain (NCP). Two TROPOspheric Monitoring Instrument (TROPOMI) NO₂ retrievals came from the Royal Netherlands Meteorological Institute (KNMI) and the University of Science and Technology of China (USTC), respectively. Compared to the prior NO _X emissions, the two TROPOMI posteriors greatly reduced the biases between simulations with in situ measurements (NO₂ MREs: prior 85%, KNMI -27%, USTC -15%; O₃ MREs: Prior -39%, KNMI 18%, USTC 11%). The NO _X budgets from the USTC posterior were 17-31% higher than those from the KNMI one. Consequently, surface NO₂ levels constrained by USTC-TROPOMI were 9-20% higher than those by the KNMI one, and O₃ is 6-12% lower. Moreover, USTC posterior simulations showed more significant changes in adjacent periods (surface NO₂: P2 vs P1, -46%, P3 vs P2, +25%; surface O₃: P2 vs P1, +75%, P3 vs P2, +18%) than the KNMI one. For the transport flux in Beijing (BJ), the O₃ flux differed by 5-6% between the two posteriori simulations, but the difference of NO₂ flux between P2 and P3 was significant, where the USTC posterior NO₂ flux was 1.5-2 times higher than the KNMI one. Overall, our results highlight the discrepancies in NO₂ and O₃ simulations constrained by two TROPOMI products and demonstrate that the USTC posterior has lower bias in the NCP during COVD-19.

Spatiotemporal neural network for estimating surface NO2 concentrations over north China and their human health impact

Atmospheric nitrogen dioxide (NO₂) is an important reactive gas pollutant harmful to human health. The spatiotemporal coverage provided by traditional NO₂ monitoring methods is insufficient, especially in the suburban and rural areas of north China, which have a high population density and experience severe air pollution. In this study, we implemented a spatiotemporal neural network (STNN) model to estimate surface NO₂ from multiple sources of information, which included satellite and in situ measurements as well as meteorological and geographical data. The STNN predicted NO₂ with high accuracy, with a coefficient of determination (R²) of 0.89 and a root mean squared error of 5.8 μg/m³ for sample-based 10-fold cross-validation. Based on the surface NO₂ concentration determined by the STNN, we analyzed the spatial distribution and temporal trends of NO₂ pollution in north China. We found substantial drops in surface NO₂ concentrations ranging between 9.1% and 33.2% for large cities during the 2020 COVID-19 lockdown when compared to those in 2019. Moreover, we estimated the all-cause deaths attributed to NO₂ exposure at a high spatial resolution of about 1 km, with totals of 6082, 4200, and 18,210 for Beijing, Tianjin, and Hebei Provinces in 2020, respectively. We observed remarkable regional differences in the health impacts due to NO₂ among urban, suburban, and rural areas. Generally, the STNN model could incorporate spatiotemporal neighboring information and infer surface NO₂ concentration with full coverage and high accuracy. Compared with machine learning regression techniques, STNN can effectively avoid model overfitting and simultaneously consider both spatial and temporal correlations of input variables using deep convolutional networks with residual blocks. The use of the proposed STNN model, as well as the surface NO₂ dataset, can benefit air quality monitoring, forecasting, and health burden assessments.

Source analysis of the tropospheric NO2 based on MAX-DOAS measurements in northeastern China

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (Max-DOAS) measurements of nitrogen dioxide (NO₂) were continuously obtained from January to November 2019 in northeastern China (NEC). Seasonal variations in the mean NO₂ vertical column densities (VCDs) were apparent, with a maximum of 2.9 × 10¹⁶ molecules cm^-2 in the winter due to enhanced NO₂ emissions from coal-fired winter heating, a longer photochemical lifetime and atmospheric transport. Daily maximum and minimum NO₂ VCDs were observed, independent of the season, at around 11:00 and 13:00 local time, respectively, and the most obvious increases and decreases occurred in the winter and autumn, respectively. The mean diurnal NO₂ VCDs at 11:00 increased to at 08:00 by 1.6, 5.8, and 6.7 × 10¹⁵ molecules cm^-2 in the summer, autumn and winter, respectively, due to increased NO₂ emissions, and then decreased by 2.8, 4.2, and 5.1 × 10¹⁵ molecules cm^-2 at 13:00 in the spring, summer, and autumn, respectively. This was due to strong solar radiation and increased planetary boundary layer height. There was no obvious weekend effect, and the NO₂ VCDs only decreased by about 10% on the weekends. We evaluated the contributions of emissions and transport in the different seasons to the NO₂ VCDs using a generalized additive model, where the contributions of local emissions to the total in the spring, summer, autumn, and winter were 89 ± 12%, 92 ± 11%, 86 ± 12%, and 72 ± 16%, respectively. The contribution of regional transport reached 26% in the winter, and this high contribution value was mainly correlated with the northeast wind, which was due to the transport channel of air pollutants along the Changbai Mountains in NEC. The NO₂/SO₂ ratio was used to identify NO₂ from industrial sources and vehicle exhaust. The contribution of industrial NO₂ VCD sources was >66.3 ± 16% in Shenyang due to the large amount of coal combustion from heavy industrial activity, which emitted large amounts of NO₂. Our results suggest that air quality management in Shenyang should consider reductions in local NO₂ emissions from industrial sources along with regional cooperative control.

Long-term declining in carbon monoxide (CO) at a rural site of Beijing during 2006-2018 implies the improved combustion efficiency and effective emission control

Carbon monoxide (CO) is primarily the result of incomplete combustion, which has important impacts on the atmospheric chemical cycle and climate. Improved quantitative characterization of long-term CO trends is important for both atmospheric modeling and the design and implementation of policies to efficiently control multiple pollutants. Due to the limitations of high time-resolution and high-quality long-term observational data, studies on long-term trends in the CO concentration in China are quite limited. In this study, the observational data of the concentration of CO in a rural site of Beijing during 2006-2018 was used to analyze the long-term trend in CO concentration in Beijing. The Theil-Sen method and the generalized additive model (GAM)-based method, were used to conduct the trend estimation analysis. We found that the concentration of CO at the Shangdianzi site showed a significant downward trend during 2006-2018, with a decline rate of 22.8 ± 5.1 ppbV per year. The declining trend in CO also showed phasic characteristics, with a fast decreasing rate during the period of 2006-2008, stable variations during the period of 2009-2013 and a continuous downward trend after 2013. The declining trend in the CO concentration in the south to west (S-W) sectors where the polluted air masses come from is more rapid than that in the sectors where the clean air masses come from. The declining trend in the CO concentration implies the improved combustion efficiency and the successful air pollution control policies in Beijing and the surrounding area.

Analysis of the Effect of Economic Development on Air Quality in Jiangsu Province Using Satellite Remote Sensing and Statistical Modeling

In recent decades, the economy of China has developed rapidly, but this has brought widespread damage to the environment, which forces us to explore a sustainable, green, economic development model. Therefore, it is particularly necessary to clarify the relationship between economic development and environmental pollution. In this paper, we used satellite remote sensing tropospheric NO2 vertical column density (VCD) as an air quality indicator; the total exports, total imports, and industrial electricity consumption as the economic indicators; and the wind speed, temperature, and planetary boundary layer height as the meteorological factors to perform a Generalized Additive Modeling (GAM) analysis. By deducing the influence of meteorological factors, the relationship between economic indicators and the air quality indicator can be determined. When total exports increased by one billion USD (United States Dollar), the tropospheric NO2 VCDs of Nanjing and Suzhou increased by about 15% and 6%, respectively. The tropospheric NO2 VCDs of Suzhou increased by about 5% when the total imports increased by one billion USD. In addition, when the industrial electricity consumption increased by one billion kWh, the tropospheric NO2 VCDs of Nanjing, Suzhou and Xuzhou increased by about 25%, 12%, and 59%, respectively. This study provides a method to quantify the contribution of economic growth to air pollution, which is helpful for better understanding of the relationship between economic development and air quality.

Atmospheric pollutants response to the emission reduction and meteorology during the COVID-19 lockdown in the north of Africa (Morocco)

Climate and air quality change due to COVID-19 lockdown (LCD) are extremely concerned subjects of several research recently. The contribution of meteorological factors and emission reduction to air pollution change over the north of Morocco has been investigated in this study using the framework generalized additive models, that have been proved to be a robust technique for the environmental data sets, focusing on main atmospheric pollutants in the region including ozone (O₃), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter (PM_2.5 and PM₁₀), secondary inorganic aerosols (SIA), nom-methane volatile organic compounds and carbon monoxide (CO) from the regional air pollution dataset of the Copernicus Atmosphere Monitoring Service. Our results, indicate that secondary air pollutants (PM_2.5, PM₁₀ and O₃) are more influenced by metrological factors and the other air pollutants reported by this study (NO₂ and SO₂₎. We show a negative effect for PBHL, total precipitation and NW10M on PM (PM_2.5 and PM₁₀ ), this meteorological parameters contribute to decrease in PM_2.5 by 9, 2 and 9% respectively, before LCD and 8, 1 and 5% respectively during LCD. However, a positive marginal effect was found for SAT, Irradiance and RH that contribute to increase PM_2.5 by 9, 12 and 18% respectively, before LCD and 17, 54 and 34% respectively during LCD. We found also that meteorological factors contribute to O₃, PM_2.5, PM₁₀ and SIA average mass concentration by 22, 5, 3 and 34% before LCD and by 28, 19, 5 and 42% during LCD respectively. The increase in meteorological factors marginal effect during LCD shows the contribution of photochemical oxidation to air pollution due to increase in atmospheric oxidant (O₃ and OH radical) during LCD, which can explain the response of PM to emission reduction. This study indicates that PM (PM_2.5, PM₁₀) has more controlled by SO₂ due to the formation of sulfate particles especially under high oxidants level. The positive correlation between westward wind at 10 m (WW10M), Northward Wind at 10 m (NW10M) and PM indicates the implication of sea salt particles transported from Mediterranean Sea and Atlantic Ocean. The Ozone mass concentration shows a positive trend with Irradiance, Total and SAT during LCD; because temperature and irradiance enhance tropospheric ozone formation via photochemical reaction.This study shows the contribution of atmospheric oxidation capacity to air pollution change.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00477-022-02224-z.

Identification of ozone sensitivity for NO2 and secondary HCHO based on MAX-DOAS measurements in northeast China

In this study, tropospheric formaldehyde (HCHO) vertical column densities (VCDs) were measured using multi-axis differential optical absorption spectroscopy (MAX-DOAS) from January to November 2019 in Shenyang, Northeast China. The maximum HCHO VCD value appeared in the summer (1.74 × 10¹⁶ molec/cm²), due to increased photo-oxidation of volatile organic compounds (VOCs). HCHO concentrations increased from 08:00 and peaked near 13:00, which was mainly attributed to the increased release of isoprene from plants and enhanced photolysis at noon. The HCHO VCDs observed by MAX-DOAS and OMI have a good correlation coefficient (R) of 0.78, and the contributions from primary and secondary HCHO sources were distinguished by the multi-linear regression model. The anthropogenic emissions showed unobvious seasonal variations, and the primary HCHO was relatively stable in Shenyang. Secondary HCHO contributed 82.62%, 83.90%, 78.90%, and 41.53% to the total measured ambient HCHO during the winter, spring, summer, and autumn, respectively. We also found a good correlation (R = 0.78) between enhanced vegetation index (EVI) and HCHO VCDs, indicating that the oxidation of biogenic volatile organic compounds (BVOCs) was the main source of HCHO. The ratio of secondary HCHO to nitrogen dioxide (NO₂) was used as the tracer to analyze O₃-NO_x-VOC sensitivities. We found that the VOC-limited, VOC-NO_x-limited, and NO_x-limited regimes made up 93.67%, 6.23%, 0.11% of the overall measurements, respectively. In addition, summertime ozone (O₃) sensitivity changed from VOC-limited in the morning to VOC-NO_x-limited in the afternoon. Therefore, this study offers information on HCHO sources and corresponding O₃ production sensitivities to support strategic management decisions.

Variations of Urban NO2 Pollution during the COVID-19 Outbreak and Post-Epidemic Era in China: A Synthesis of Remote Sensing and In Situ Measurements

Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production.

Exploring the impact of new particle formation events on PM2.5 pollution during winter in the Yangtze River Delta, China

New particle formation (NPF) events are an increasingly interesting topic in air quality and climate science. In this study, the particle number size distributions, and the frequency of NPF events over Hefei were investigated from November 2018 to February 2019. The proportions of the nucleation mode, Aitken mode, and accumulation mode were 24.59%, 53.10%, and 22.30%, respectively, which indicates the presence of abundant ultrafine particles in Hefei. Forty-six NPF events occurred during the observation days, accounting for 41.82% of the entire observation period. Moreover, the favorable meteorological conditions, potential precursor gases, and PM_2.5 range of the NPF events were analyzed. Compared to non-NPF days, the NPF events preferentially occurred on days with lower relative humidity, higher wind speeds, and higher temperatures. When the PM_2.5 was 15-20, 70-80, and 105-115 μg/m³, the frequency of the NPF events was higher. Nucleation mode particles were positively related to atmospheric oxidation indicated by ozone when PM_2.5 ranged from 15 to 20 μg/m³, and related to gaseous precursors like SO₂ and NO₂ when PM_2.5 was located at 70-80 and 105-115 μg/m³. On pollution days, NPF events did not directly contribute to the increase in the PM_2.5 in the daytime, however, NPF events would occur during the night and the growth of particulate matter contributes to the nighttime PM_2.5 contents. This could lead to pollution that lasted into the next day. These findings are significant to the improvement of our understanding of the effects of aerosols on air quality.

Opposite impact of emission reduction during the COVID-19 lockdown period on the surface concentrations of PM2.5 and O3 in Wuhan, China

To prevent the spread of the COVID-19 epidemic, the Chinese megacity Wuhan has taken emergent lockdown measures starting on January 23, 2020. This provided a natural experiment to investigate the response of air quality to such emission reductions. Here, we decoupled the influence of meteorological and non-meteorological factors on main air pollutants using generalized additive models (GAMs), driven by data from the China National Environmental Monitoring Center (CNEMC) network. During the lockdown period (Jan. 23 - Apr. 8, 2020), PM_2.5, PM₁₀, NO₂, SO₂, and CO concentrations decreased significantly by 45 %, 49 %, 56 %, 39 %, and 18 % compared with the corresponding period in 2015-2019, with contributions by S(meteos) of 15 %, 17 %, 13 %, 10 %, and 6 %. This indicates an emission reduction of NO_x at least 43 %. However, O₃ increased by 43 % with a contribution by S(meteos) of 6 %. In spite of the reduced volatile organic compound (VOC) emissions by 30 % during the strict lockdown period (Jan. 23 - Feb. 14, 2020), which likely reduced the production of O₃, O₃ concentrations increased due to a weakening of the titration effect of NO. Our results suggest that conventional emission reduction (NO_x reduction only) measures may not be sufficient to reduce (or even lead to an increase of) surface O₃ concentrations, even if reaching the limit, and VOC-specific measures should also be taken.

Aggravated ozone pollution in the strong free convection boundary layer

Clarifying the relationship between meteorological factors and ozone can provide scientific support for ozone pollution prediction, but the effects of boundary layer meteorology, especially boundary layer height and turbulence, on ozone pollution are rarely studied. Here, ozone and its related meteorological factors were observed in summer in Shijiazhuang, a city with the most serious ozone pollution on the North China Plain. The forced and free convection boundary layers were classified using ground remote observations. After eliminating the forced convection condition, strong free convection conditions, exhibiting a high boundary layer height, high wind speed, strong turbulence and large-scale free convection velocity, were found to be beneficial for the aggravation of ozone pollution. Combined with the ozone profile detected by a tethered balloon, the ozone chemical budget was calculated using the differences in the column ozone concentrations between the morning and afternoon, and the results confirmed the impact of free convection intensity on ozone pollution. The change in ozone sensitivity from VOCs sensitivity to NOx sensitivity driven by strong free convection was the main reason for the deterioration of ozone pollution. This study clarified the impact of boundary layer meteorology on ozone and its sensitivity and has important practical significance for ozone pollution prevention and early warning.

Seasonal variability and trends in global type-segregated aerosol optical depth as revealed by MISR satellite observations

This study utilized a long-term (2001-2018) aerosol optical component dataset retrieved from the Multiangle Imaging Spectroradiometer (MISR), Version 23, to perform comprehensive analyses of the global climatology of seasonal AODs, partitioned by aerosol types (including small-size, medium-size, large-size, spherical, and non-spherical). By dividing eight different AOD bins and performing trend analysis, the seasonal variability and trends in these type-segregated AODs, as well as in the frequency occurrences (FOs) for different AOD bins, globally and over 12 regions of interest, were also investigated. In terms of particle size, small-size aerosol particles (diameter < 0.7 μm) contribute the largest to global extinction in all three seasons except winter. A similar globally dominant role is exhibited by spherical aerosols, which contribute 68.5%, 73.3%, 71.6% and 70.2% to the global total AOD (TAOD) in spring, summer, autumn and winter, respectively, on a global average scale. FOs with different aerosol loading levels suggested that the seasonal FOs tend to decrease progressively with increasing aerosol loading, except for Level 1 (TAOD< 0.05). Examination of the seasonal distribution of FOs revealed that the FO at Level 1 (Level 2, 0.05 < TAOD< 0.15) is much larger in summer/winter (winter/autumn) than in spring/autumn (spring/summer) over most areas of the world. However, the FOs for Level 3 (0.15 < TAOD< 0.25) to Level 8 (TAOD> 1.0) generally exhibit greater intensity in spring/summer than in autumn/winter. Temporal trend analyses showed that the seasonal TAOD experiences a significant decline during 2001-2018 in most regions globally, except in South Asia, the Middle East, and North Africa. Opposite seasonal trends in the above regions are closely related to the increase in FOs in the range of 0.4 < TAOD< 1.0. The global average TAOD shows the most pronounced decline in spring, falling by -10.4% (P < 0.05). Examination of the trends in type-segregated AODs further revealed that the decreases in size-segregated (shape-segregated) AODs all contribute to the decrease in seasonal TAOD, with small-size AOD (spherical AOD) contributing most significantly.

Improved Anthropogenic SO2 Retrieval from High-Spatial-Resolution Satellite and its Application during the COVID-19 Pandemic

Sulfur dioxide (SO₂) measured by satellites is widely used to estimate anthropogenic emissions. The Sentinel-5 Precursor (S-5P) operational SO₂ product is overestimated compared to the ground-based multiaxis differential optical absorption spectroscopy (MAX-DOAS) measurements in China and shows an opposite variation to the surface measurements, which limits the application of TROPOspheric monitoring instrument (TROPOMI) products in emissions research. Radiometric calibration, a priori profiles, and fitting windows might cause the overestimation of S-5P operational SO₂ product. Here, we improve the optimal-estimation-based algorithm through several calibration methods. The improved retrieval agrees reasonably well with the ground-based measurements (R > 0.70, bias <13.7%) and has smaller biases (-28.9%) with surface measurements over China and India. It revealed that the SO₂ column in March 2020 decreased by 51.6% compared to March 2019 due to the lockdown for curbing the spread of the COVID-19 pandemic, and there was a decrease of 50% during the lockdown than those after the lockdown, similar to the surface measurement trend, while S-5P operational SO₂ product showed an unrealistic increase of 19%. In India, the improved retrieval identified obvious "hot spots" and observed a 30% decrease of SO₂ columns during the lockdown.

Observations by Ground-Based MAX-DOAS of the Vertical Characters of Winter Pollution and the Influencing Factors of HONO Generation in Shanghai, China

Analyzing vertical distribution characters of air pollutants is conducive to study the mechanisms under polluted atmospheric conditions. Nitrous acid (HONO) is a kind of crucial species in photochemical cycles. Exploring the influence and sources of HONO in air pollution at different altitudes offers some insights into the research of tropospheric oxidation chemistry processes. Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements were conducted in Shanghai, China, from December 2017 to March 2018 to investigate vertical distributions and diurnal variations of trace gases (NO2, HONO, HCHO, SO2, and water vapor) and aerosol extinction coefficient in the boundary layer. Aerosol and NO2 showed decreasing profile exponentially, SO2 and HCHO concentrations were observed relatively high values in the middle layer. SO2 was caused by industrial emissions, while HCHO was from secondary sources. As for HONO, below 0.82 km, the heterogeneous reactions of NO2 impacted on forming HONO, while in the upper layers, vertical diffusion might be the dominant source. The contribution of OH production from HONO photolysis at different altitudes was mainly controlled by the concentration of HONO. MAX-DOAS measurements characterize the vertical structure of air pollutants in Shanghai and provide further understanding for HONO formation, which can help deploy advanced measurement platforms of regional air pollution over eastern China.

Profiling of Dust and Urban Haze Mass Concentrations during the 2019 National Day Parade in Beijing by Polarization Raman Lidar

The polarization–Raman Lidar combined sun photometer is a powerful method for separating dust and urban haze backscatter, extinction, and mass concentrations. The observation was performed in Beijing during the 2019 National Day parade, the particle depolarization ratio at 532 nm and Lidar ratio at 355 nm are 0.13 ± 0.05 and 52 ± 9 sr, respectively. It is the typical value of a mixture of dust and urban haze. Here we quantify the contributions of cross-regional transported natural dust and urban haze mass concentrations to Beijing’s air quality. There is a significant correlation between urban haze mass concentrations and surface PM2.5 (R = 0.74, p < 0.01). The contributions of local emissions to air pollution during the 2019 National Day parade were insignificant, mainly affected by regional transport, including urban haze in North China plain and Guanzhong Plain (Hebei, Tianjin, Shandong, and Shanxi), and dust aerosol in Mongolia regions and Xinjiang. Moreover, the trans-regional transmission of natural dust dominated the air pollution during the 2019 National Day parade, with a relative contribution to particulate matter mass concentrations exceeding 74% below 4 km. Our results highlight that controlling anthropogenic emissions over regional scales and focusing on the effects of natural dust is crucial and effective to improve Beijing’s air quality.

Investigation on the Relationship between Satellite Air Quality Measurements and Industrial Production by Generalized Additive Modeling

The development of the green economy is universally recognized as a solution to natural resource shortages and environmental pollution. When exploring and developing a green economy, it is important to study the relationships between the environment and economic development. As opposed to descriptive and qualitative research without modeling or based on environmental Kuznets curves, quantitative relationships between environmental protection and economic development must be identified for exploration and practice. In this paper, we used the generalized additive model (GAM) regression method to identify relationships between atmospheric pollutants (e.g., NO2, SO2 and CO) from remote sensing and in situ measurements and their driving effectors, including meteorology and economic indicators. Three representative cities in the Anhui province, such as Hefei (technology-based industry), Tongling (resource-based industry) and Huangshan (tourism-based industry), were studied from 2016 to 2020. After eliminating the influence of meteorological factors, the relationship between air quality indexes and industrial production in the target cities was clearly observed. Taking Hefei, for example, when the normalized output of chemical products increases by one unit, the effect on atmospheric NO2 content increases by about 20%. When the normalized output of chemical product increases by one unit, the effect on atmospheric SO2 content increases by about 10%. When chemical and steel product outputs increase by one unit, the effect on atmospheric CO content increases by 25% and 20%, respectively. These results can help different cities predict local economic development trends varying by the changes in air quality and adjust local industrial structure.

Quantify the Contribution of Dust and Anthropogenic Sources to Aerosols in North China by Lidar and Validated with CALIPSO

Persistent heavy haze episodes have repeatedly shrouded North China in recent years. Besides anthropogenic emissions, natural dust also contributes to the aerosols in this region. Through continuous observation by a dual-wavelength Raman lidar, the primary aerosol types and their contributions to air pollution in North China were determined. The following three aerosol types can be classified: natural dust, anthropogenic aerosols, and the mixture of anthropogenic aerosols and dust (polluted dust). The classification results are basically consistent with the classification results from the cloud–aerosol lidar and infrared pathfinder satellite observations (CALIPSO) satellite measurements. The relative bias of the lidar ratio between the Raman lidar and CALIPSO is less than 25% over 90% of the cases, indicating that the CALIPSO lidar ratio selection algorithm is reasonable. The classification results show that approximately 45% of aerosols below 1.8 km are contributed by polluted dust during our one year observations. The contribution of dust increased with height, from 6% at 500 m to 28% at 1,800 m, while the contribution of anthropogenic aerosols decreased from 49% to 25%. In addition, polluted dust is the major aerosol subtype below 1.0 km in spring (over 60%) and autumn (over 70%). Anthropogenic aerosols contribute more than 75% of air pollution in summer. In winter, anthropogenic aerosols prevailed (over 80%) in the lower layer, while polluted dust (around 60%) dominated the upper layer. Our results identified the primarily aerosol types to assess the contributions of anthropogenic and natural sources to air pollution in North China, and highlight that natural dust plays a crucial role in lower-layer air pollution in spring and autumn, while controlling anthropogenic aerosols will significantly improve air quality in winter.

Quantifying Contributions of Local Emissions and Regional Transport to NOX in Beijing Using TROPOMI Constrained WRF-Chem Simulation

Air quality is strongly influenced by both local emissions and regional transport. Atmospheric chemical transport models can distinguish between emissions and regional transport sources in air pollutant concentrations. However, quantifying model inventories is challenging due to emission changes caused by the recent strict control measures taken by the Chinese government. In this study, we use NO2 column observations from the Tropospheric Monitoring Instrument to retrieve top-down nitrogen oxide (NOX) emissions and quantify the contributions of local emissions and regional transport to NOx in Beijing (BJ), from 1 November 2018 to 28 February 2019 (W_2018) and 1 November 2019 to 29 February 2020 (W_2019). In W_2018 and W_2019, the BJ bottom-up NOX emissions from the multi-resolution emission inventory for China in 2017 were overestimated by 11.8% and 40.5%, respectively, and the input of NOX from other cities to BJ was overestimated by 10.9% and 51.6%, respectively. The simulation using our adjusted inventory exhibited a much higher spatial agreement (slope = 1.0, R2 = 0.79) and reduced a mean relative error by 45% compared to those of bottom-up NOX emissions. The top-down inventory indicated that (1) city boundary transport contributes approximately 40% of the NOX concentration in BJ; (2) in W_2019, NOX emissions and transport in BJ decreased by 20.4% and 17.2%, respectively, compared to those of W_2018; (3) in W_2019, NOX influx substantially decreased (−699 g/s) in BJ compared to that of W_2018 despite negative meteorological conditions that should have increased NOx influx by +503 g/s. Overall, the contribution of intercity input to NOx in BJ has declined with decreasing emissions in the surrounding cities due to regional cooperative control measures, and the role of local emissions in BJ NOx levels was more prominent. Our findings indicate that local emissions may play vital roles in regional center city air quality.

Vertical distributions of tropospheric SO2 based on MAX-DOAS observations: Investigating the impacts of regional transport at different heights in the boundary layer

Information on the vertical distribution of air pollutants is essential for understanding their spatiotemporal evolution underlying urban atmospheric environment. This paper presents the SO₂ profiles based on ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) measurements from March 2018 to February 2019 in Hefei, East China. SO₂ decrease rapidly with increasing heights in the warm season, while lifted layers were observed in the cold season, indicating accumulation or long-range transport of SO₂ in different seasons might occur at different heights. The diurnal variations of SO₂ were roughly consistent for all four seasons, exhibiting the minimum at noon and higher values in the morning and late afternoon. Lifted layers of SO₂ were observed in the morning for fall and winter, implying the accumulation or transport of SO₂ in the morning mainly occurred at the top of the boundary layer. The bivariate polar plots showed that weighted SO₂ concentrations in the lower altitude were weakly dependent on wind, but in the middle and upper altitudes, higher weighted SO₂ concentrations were observed under conditions of middle-high wind speed. Concentration weighted trajectory (CWT) analysis suggested that potential sources of SO₂ in spring and summer were local and transported mainly occurred in the lower altitude from southern and eastern areas; while in fall and winter, SO₂ concentrations were deeply affected by long-range transport from northwestern and northern polluted regions in the middle and upper altitudes. Our findings provide new insight into the impacts of regional transport at different heights in the boundary layer on SO₂ pollution.

Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO₃) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO₂ and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO₂ TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NO_x emission weakened the titration of ozone, causing an increase of ozone.

Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO₃) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO₂ and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO₂ TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NO_x emission weakened the titration of ozone, causing an increase of ozone.

Source apportionment of PM2.5 and visibility in Jinan, China

Atmospheric extinction is impacted by the chemical composition of particles. To better understand the chemical composition of PM_2.5 (particles with diameters of less than 2.5 μm) and its relationship with extinction, one-month sampling campaigns were carried out in four different seasons from 2013 to 2014 in Jinan, China. The seasonal average concentrations of PM_2.5 were 120.9 (autumn), 156.6 (winter), 102.5 (spring), and 111.8 μg/m³ (summer). The reconstructed PM_2.5 chemical composition showed that sulfate, nitrate, chlorine salt, organic matter (OM), mineral dust, elemental carbon (EC) and others accounted for 25%, 14%, 2%, 24%, 22%, 3% and 10%, respectively. The relationship between the chemical composition of PM_2.5 and visibility was reconstructed by the IMPROVE method, and ammonium sulfate, ammonium nitrate, OM and EC dominated the visibility. Seven main sources were resolved for PM_2.5, including secondary particles, coal combustion, biomass burning, industry, motor vehicle exhaust, soil dust and cooking, which accounted for 37%, 21%, 13%, 13%, 12%, 3% and 1%, respectively. The contributions of different sources to visibility were similar to those to PM_2.5. With increasing severity of air pollution, the contributions of secondary particles and coal combustion increased, while the contribution of motor vehicle exhaust decreased. The results showed that coal combustion and biomass burning were still the main sources of air pollution in Jinan.

Revealing the modulation of boundary conditions and governing processes on ozone formation over northern China in June 2017

In this study, ozonesonde data were used to evaluate the impact of different boundary conditions on the vertical distribution of ozone over urban Beijing. The comparison shows that the clean and static boundary conditions, referred to as PROFILE, apparently underestimate the ozone concentration over the upper troposphere and stratosphere, whereas the global chemical transport model (CTM) provides much more reasonable performance. Further investigation reveals that the boundary conditions exert larger impacts over areas with high altitudes and close distances to boundaries, such as the Tibetan Plateau, while they yield weak impacts on regions relatively far from the boundary, such as the North China Plain (NCP). Process analysis was conducted to investigate the modulation of physical and chemical processes on ozone formation in June 2017, illustrating that during the daytime of the high-O₃ period, the photochemical reactions within the planetary boundary layer (PBL) almost become the only source favorable to ozone accumulation. Motivated by this phenomenon, we constructed a linear regression and found that the maximum daily 8-hr ozone (MDA8) ozone concentration was highly correlated with the surface ozone change rate and chemical reactions in the PBL during the pollution period, with MDA8 ozone exceeding 70 ppbv over NCP. Based on this relationship as well as the design of numerical experiments, we propose a strategy of dynamic emission control. Firstly, the emission reduction during the peak ozone formation period may weaken the fast chemical reactions in the PBL and subsequent surface ozone concentration. Secondly, emission reduction one or two days prior to an episode might achieve larger ozone reduction through the accumulation effect. Lastly, emission control outside of the NCP may surpass the local impact under favorable meteorological conditions. Therefore, the efficacy of dynamic emission control was striking when both the accumulation and transport effect were taken into consideration.

Characteristics of PM2.5 pollution in Beijing after the improvement of air quality

Following the implementation of the strictest clean air policies to date in Beijing, the physicochemical characteristics and sources of PM_2.5 have changed over the past few years. To improve pollution reduction policies and subsequent air quality further, it is necessary to explore the changes in PM_2.5 over time. In this study, over one year (2017-2018) field study based on filter sampling (TH-150C; Wuhan Tianhong, China) was conducted in Fengtai District, Beijing, revealed that the annual average PM_2.5 concentration (64.8 ± 43.1 μg/m³) was significantly lower than in previous years and the highest PM_2.5 concentration occurred in spring (84.4 ± 59.9 μg/m³). Secondary nitrate was the largest source and accounted for 25.7% of the measured PM_2.5. Vehicular emission, the second largest source (17.6%), deserves more attention when considering the increase in the number of motor vehicles and its contribution to gaseous pollutants. In addition, the contribution from coal combustion to PM_2.5 decreased significantly. During weekends, the contribution from EC and NO₃^- increased whereas the contributions from SO₄^2-, OM, and trace elements decreased, compared with weekdays. During the period of residential heating, PM_2.5 mass decreased by 23.1%, compared with non-heating period, while the contributions from coal combustion and vehicular emission, and related species increased. With the aggravation of pollution, the contribution of vehicular emission and secondary sulfate increased and then decreased, while the contribution of NO₃^- and secondary nitrate continued to increase, and accounted for 34.0% and 57.5% of the PM_2.5 during the heavily polluted days, respectively.

Hydrogel gratings with patterned analyte responsive dyes for spectroscopic sensing

This is an unprecedented report of hydrogel gratings with an analyte responsive dye immobilised in alternating strips where the patterned dye is its own dispersive element to perform spectroscopy. At each wavelength, the diffraction efficiency of hydrogel gratings is a function of dye absorbance, which in turn is dependent on the concentration of analytes in samples. Thus, changes in intensity of diffracted light of hydrogel gratings were measured for sensing of analytes. Equally, the ratio of diffracted intensities at two wavelengths was used for quantification of analytes to reduce errors caused by variations in intensity of light sources and photobleaching of dyes. 15.27 μm pitch gratings were fabricated by exposing 175 μm thick films of photofunctionalisable poly(acrylamide) hydrogel in a laser interferometric lithography setup, generating an array of alternating lines with and without free functional groups. The freed functional groups were reacted with pH sensitive fluorescein isothiocyanate to create gratings for measurement of pH. The ratio of intensity of diffracted light of hydrogel gratings at 430 and 475 nm was shown to be linear over 4 pH units, which compares favourably with ∼2 pH units for conventional absorption spectroscopy. This increased dynamic range was a result of cancellation of the opposite non-linearities in the pH response of the analyte responsive dye and the diffraction efficiency as a function of dye absorbance.

This is an unprecedented report of hydrogel gratings with an analyte responsive dye immobilised in alternating strips where the patterned dye is its own dispersive element to perform spectroscopic sensing.

Strategy and Future Prospects to Develop Room-Temperature-Recoverable NO2 Gas Sensor Based on Two-Dimensional Molybdenum Disulfide

Nitrogen dioxide (NO2), a hazardous gas with acidic nature, is continuously being liberated in the atmosphere due to human activity. The NO2 sensors based on traditional materials have limitations of high-temperature requirements, slow recovery, and performance degradation under harsh environmental conditions. These limitations of traditional materials are forcing the scientific community to discover future alternative NO2 sensitive materials. Molybdenum disulfide (MoS2) has emerged as a potential candidate for developing next-generation NO2 gas sensors. MoS2 has a large surface area for NO2 molecules adsorption with controllable morphologies, facile integration with other materials and compatibility with internet of things (IoT) devices. The aim of this review is to provide a detailed overview of the fabrication of MoS2 chemiresistance sensors in terms of devices (resistor and transistor), layer thickness, morphology control, defect tailoring, heterostructure, metal nanoparticle doping, and through light illumination. Moreover, the experimental and theoretical aspects used in designing MoS2-based NO2 sensors are also discussed extensively. Finally, the review concludes the challenges and future perspectives to further enhance the gas-sensing performance of MoS2. Understanding and addressing these issues are expected to yield the development of highly reliable and industry standard chemiresistance NO2 gas sensors for environmental monitoring.

Turbidity compensation method based on Mie scattering theory for water chemical oxygen demand determination by UV-Vis spectrometry

In view of the problem that chemical oxygen demand (COD) measurement in water using UV-Vis spectrometry was easily affected by turbidity, this paper proposed an analytical method for determining the complex refractive index of particles in water based on Lambert-Beer's law and K-K (Kramers-Kronig) relationship. The obtained complex refractive index was used to establish the turbidity compensation model in the COD characteristic spectral region, and the COD concentration inversion were achieved by using the PLS algorithm. The results show that the turbidity compensation method based on Mie scattering theory can improve the accuracy of COD measurement by UV-Vis spectroscopy. Compared with before turbidity compensation, R² (determination coefficient) between true values and predicted values of COD increased from 0.2274 to 0.9629, and RMSE (root mean square error) of predicted values decreased from 21.73 to 3.12 mg L^-1. Compared with 350 nm PC, derivative method, and improved MSC method, the turbidity compensation method for COD measurement based on Mie scattering theory is simple, fast, and highly accurate. And the calculated spectrum can represent the scattering characteristics of the measured spectrum. The average relative error between the fitted spectrum and the original normalized spectrum in the 55 mixed solutions was 0.52%, and the maximum relative error was 6.65%. This method can be useful for online COD measurement. Graphical abstract.

How aerosol transport from the North China plain contributes to air quality in northeast China

Northeast China (NEC) has unique climate characteristics and emission sources; continued urbanisation has aggravated regional pollution. The in situ observation data concerning PM_2.5, visibility, surface meteorological elements and synchronous aerosol vertical extinction profiles obtained from ground-based Lidar were investigated to better understand local and regional particulate pollution in NEC. The WRF (3.7.1)/CAMx (6.40) model was employed to quantitative investigate the contribution of regional transport to PM_2.5 in Shenyang. The results suggested that PM_2.5 increased significantly from 9 to 14 January over NEC and the Northern China (NC), with monthly PM_2.5 highest in Shijiazhuang and Baoding of NC about 145.2 ± 88.9 and 136.8 ± 83.1 μg m^-3, respectively. The distribution of SO₂ and NO₂ for PM_2.5 implied SO₂ was more influence on PM_2.5 in NEC, while NO₂ has larger impact on PM_2.5 in NC. The significant increasing of relative humidity (RH) and temperatures exhibited in the pollution indicate water vapor and warm air flow during the transport. The development of the southwest airflow was conducive to pollutant transport across the Beijing-Tianjin-Hebei (or Jing-Jin-Ji) megalopolis to NEC, and together with the local emissions in NEC to affect air quality. The modelling results pointed out that contribution of regional transport to PM_2.5 in Shenyang was about 80.12% at 00:00 LT in 10 January, of which the contribution of BTH was about 61.52%; the total regional contribution to PM_2.5 in Shenyang reaching 60.70% at 02:00 LT on 13 January including 34.56% contributed by BTH region. Aerosol vertical extinction indicated the particle layer appeared in the near-surface and in the upper atmospheric layer from 0.5 to 1.0 km following the development of transport event. The findings of this study can facilitate a comprehensive understanding of the local and regional air pollution in NEC and helpful for national environment pollution controls and improvement.

Development and Application of HECORA Cloud Retrieval Algorithm Based On the O2-O2 477 nm Absorption Band

In this paper, we present the Hefei EMI Cloud Retrieval Algorithm (HECORA), which uses information from the O2-O2 absorption band around 477 nm to retrieve effective cloud fraction and effective cloud pressure from satellite observations. The retrieved cloud information intends to improve the atmospheric trace gas products based on the Environment Monitoring Instrument (EMI) spectrometer. The HECORA method builds on OMCLDO2 and presents some evolutions. The Vector Linearized Discrete Ordinate Radiative Transfer (VLIDORT) model has been used to produce the Top of the Atmosphere (TOA) reflectance Look-up Tables (LUT) as a function of the cloud fraction and cloud pressure. Applying the Differential Optical Absorption Spectroscopy (DOAS) technique to the synthetic reflectance LUT, the reflectance spectra can be associated with O2-O2 geometrical vertical column densities (VCDgeo) and continuum reflectance. This is the core of the retrieval method, since there is a one-to-one relationship between O2-O2 VCDgeo and continuum reflectance, on the one hand, and effective cloud fraction and effective cloud pressure, on the other hand, for a given illumination and observing geometry and given surface height and surface albedo. We first used the VLIDORT synthetic spectra to verify the HECORA algorithm and obtained good results in both the Lambertian cloud model and the scattering cloud model. Secondly, HECORA is applied to OMI and TROPOMI and compared with OMCLDO2, FRESCO+, and OCRA/ROCINN cloud products. Later, the cloud pressure results from TROPOMI observations obtained using HECORA and FRESCO+ are compared with the CALIOP Cloud Layer product. HECORA is closer to the CALIOP results under low cloud conditions, while FRESCO+ is closer to high clouds due to the higher sensitivity of the O2 A-band to cloud vertical information. Finally, HECORA is applied to the TROPOMI NO2 retrieval. Validation of the tropospheric NO2 VCD with ground-based MAX-DOAS measurements shows that choosing HECORA cloud products to correct for photon path variations on the TROPOMI tropospheric NO2 VCD retrievals has better performance than using FRESCO+ under low cloud conditions. In conclusion, this paper shows that the HECORA cloud products are in good agreement with the well-established cloud products and that they are suitable for correcting the effect of cloud in trace gas retrievals. Therefore, HECORA has the potential to be applied to EMI.

Construction of a virtual PM2.5 observation network in China based on high-density surface meteorological observations using the Extreme Gradient Boosting model

With increasing public concerns on air pollution in China, there is a demand for long-term continuous PM_2.5 datasets. However, it was not until the end of 2012 that China established a national PM_2.5 observation network. Before that, satellite-retrieved aerosol optical depth (AOD) was frequently used as a primary predictor to estimate surface PM_2.5. Nevertheless, satellite-retrieved AOD often encounter incomplete daily coverage due to its sampling frequency and interferences from cloud, which greatly affect the representation of these AOD-based PM_2.5. Here, we constructed a virtual ground-based PM_2.5 observation network at 1180 meteorological sites across China using the Extreme Gradient Boosting (XGBoost) model with high-density meteorological observations as major predictors. Cross-validation of the XGBoost model showed strong robustness and high accuracy in its estimation of the daily (monthly) PM_2.5 across China in 2018, with R², root-mean-square error (RMSE) and mean absolute error values of 0.79 (0.92), 15.75 μg/m³ (6.75 μg/m³) and 9.89 μg/m³ (4.53 μg/m³), respectively. Meanwhile, we find that surface visibility plays the dominant role in terms of the relative importance of variables in the XGBoost model, accounting for 39.3% of the overall importance. We then use meteorological and PM_2.5 data in the year 2017 to assess the predictive capability of the model. Results showed that the XGBoost model is capable to accurately hindcast historical PM_2.5 at monthly (R² = 0.80, RMSE = 14.75 μg/m³), seasonal (R² = 0.86, RMSE = 12.28 μg/m³), and annual (R² = 0.81, RMSE = 10.10 μg/m³) mean levels. In general, the newly constructed virtual PM_2.5 observation network based on high-density surface meteorological observations using the Extreme Gradient Boosting model shows great potential in reconstructing historical PM_2.5 at ~1000 meteorological sites across China. It will be of benefit to filling gaps in AOD-based PM_2.5 data, as well as to other environmental studies including epidemiology.

Spatiotemporal distribution of ground-level ozone in China at a city level

In recent years, ozone (O3) pollution in China has shown a worsening trend. Due to the vast territory of China, O3 pollution is a widespread and complex problem. It is vital to understand the current spatiotemporal distribution of O3 pollution in China. In this study, we collected hourly data on O3 concentrations in 338 cities from January 1, 2016, to February 28, 2019, to analyze O3 pollution in China from a spatiotemporal perspective. The spatial analysis showed that the O3 concentrations exceeded the limit in seven geographical regions of China to some extent, with more serious pollution in North, East, and Central China. The O3 concentrations in the eastern areas were usually higher than those in the western areas. The temporal analysis showed seasonal variations in O3 concentration, with the highest O3 concentration in the summer and the lowest in the winter. The weekend effect, which occurs in other countries (such as the USA), was found only in some cities in China. We also found that the highest O3 concentration usually occurred in the afternoon and the lowest was in the early morning. The comprehensive analysis in this paper could improve our understanding of the severity of O3 pollution in China.

First observation of tropospheric nitrogen dioxide from the Environmental Trace Gases Monitoring Instrument onboard the GaoFen-5 satellite

The Environmental Trace Gases Monitoring Instrument (EMI) is the first Chinese satellite-borne UV-Vis spectrometer aiming to measure the distribution of atmospheric trace gases on a global scale. The EMI instrument onboard the GaoFen-5 satellite was launched on 9 May 2018. In this paper, we present the tropospheric nitrogen dioxide (NO2) vertical column density (VCD) retrieval algorithm dedicated to EMI measurement. We report the first successful retrieval of tropospheric NO2 VCD from the EMI instrument. Our retrieval improved the original EMI NO2 prototype algorithm by modifying the settings of the spectral fit and air mass factor calculations to account for the on-orbit instrumental performance changes. The retrieved EMI NO2 VCDs generally show good spatiotemporal agreement with the satellite-borne Ozone Monitoring Instrument and TROPOspheric Monitoring Instrument (correlation coefficient R of ~0.9, bias < 50%). A comparison with ground-based MAX-DOAS (Multi-Axis Differential Optical Absorption Spectroscopy) observations also shows good correlation with an R of 0.82. The results indicate that the EMI NO2 retrieval algorithm derives reliable and precise results, and this algorithm can feasibly produce stable operational products that can contribute to global air pollution monitoring.

Can MERRA-2 Reanalysis Data Reproduce the Three-Dimensional Evolution Characteristics of a Typical Dust Process in East Asia? A Case Study of the Dust Event in May 2017

This study used the MERRA-2 reanalysis dataset and ground-based and satellite observational data to comprehensively analyze a typical dust storm event in east Asia on 2–7 May 2017 which engulfed most of China as well as ocean and Japan, and explore the accuracy and comprehensiveness of the MERRA-2 dataset in the analysis of dust processes. The results of comparison show that the description of the spatiotemporal distribution and evolution of the dust aerosols in the dust event using the MERRA-2 data is consistent with the data of AERONET, National Urban Air Quality Real-time Publishing Platform and Hamawari-8. Gobi Deserts was the most influential source area of this dust event with the highest emissions reaching 1.9 × 106 μg/m3. The vertical motion of the atmosphere can lift dust from the source area above 500 hPa. There were low-pressure troughs at 500 and 850 hPa and the winds behind and in front of the trough led to the high-altitude, long-distance transport of dust. Dust gradually affected the northwest China, north China, northeast China, and even the ocean and Japan on 2–7 May. This study demonstrates that although there is some uncertainty about the source of dust emission in the MERRA-2 model, the data accurately simulated the evolution of the dust event and analyze it comprehensively, while the accuracy of simulating the long-term evolution of dust requires further evaluation.