International audience

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.

Nitrous acid (HONO), an essential precursor of hydroxyl radicals (OH) in the troposphere, plays an integral role in atmospheric photochemistry. However, potential HONO sources remain unclear, particularly in rural areas, where long-term (including seasonal) measurements are scarce. HONO and related parameters were measured at a rural site in the North China Plain (NCP) during the winter of 2017 and summer and autumn of 2020. The mean HONO level was higher in winter (1.79 ± 1.44 ppbv) than in summer (0.67 ± 0.50 ppbv) and autumn (0.83 ± 0.62 ppbv). Source analysis revealed that the heterogeneous conversion (including photo-enhanced conversion) of NO₂ on the ground surface dominated the daytime HONO production in the three seasons (43.1% in winter, 54.3% in summer, and 62.0% in autumn), and the homogeneous reaction of NO and OH contributed 37.8, 12.2, and 28.4% of the daytime HONO production during winter, summer, and autumn, respectively. In addition, the total contributions of other sources (direct vehicle emissions, particulate nitrate photolysis, NO₂ uptake and its photo-enhanced reaction on the aerosol surface) to daytime HONO production were less than 5% in summer and autumn and 12.0% in winter. Unlike winter and autumn, an additional HONO source was found in summer (0.45 ± 0.21 ppbv h⁻¹, 31.4% to the daytime HONO formation), which might be attributed to the HONO emission from the fertilized field. Among the primary radical sources (photolysis of HONO, O₃, and formaldehyde), HONO photolysis was dominant, with contributions of 82.6, 49.3, and 63.2% in winter, summer, and autumn, respectively. Our findings may aid in understanding HONO formation in different seasons in rural areas and may highlight the impact of HONO on atmospheric oxidation capacity.

This study aims to investigate the effect of transportation infrastructure on the decrease of NO₂ air pollution during three COVID-19-induced lockdowns in a vast region of France. For this purpose, using Sentinel-5P satellite data, the relative change in tropospheric NO₂ air pollution during the three lockdowns was calculated. The estimation of regional infrastructure intensity was performed using Kernel Density Estimation, being the predictor variable. By performing hotspot–coldspot analysis on the relative change in NO₂ air pollution, significant spatial clusters of decreased air pollution during the three lockdowns were identified. Based on the clusters, a novel spatial index, the Clustering Index (CI) was developed using its Coldspot Clustering Index (CCI) variant as a predicted variable in the regression model between infrastructure intensity and NO₂ air pollution decline. The analysis revealed that during the three lockdowns there was a strong and statistically significant relationship between the transportation infrastructure and the decline index, CCI (r = 0.899, R² = 0.808). The results showed that the largest decrease in NO₂ air pollution was recorded during the first lockdown, and in this case, there was the strongest inverse correlation with transportation infrastructure (r = −0.904, R² = 0.818). Economic and population predictors also explained with good fit the decrease in NO₂ air pollution during the first lockdown: GDP (R² = 0.511), employees (R² = 0.513), population density (R² = 0.837). It is concluded that not only economic-population variables determined the reduction of near-surface air pollution but also the transportation infrastructure. Further studies are recommended to investigate other pollutant gases as predicted variables.

In spring, ozone (O₃) pollution frequently occurrs in eastern China, but key drivers remain uncertain. In this study, interannual variations in springtime ozone in Shanghai, China, from 2013 to 2021, were investigated to assess the health impacts and the effectiveness of recent air pollution control measures. A combination of ground-level measurements of regulated air pollutants, lidar observations, and backward trajectories of air masses was used to identify the key drivers for enhancing springtime O₃. The results show that external imports of O₃ driven by atmospheric circulation are notable sources of springtime surface O₃. For example, the downward transport from the free troposphere could contribute to over 50% of surface O₃ in the morning. The surface O₃ mixing ratios in spring exhibited an upward trend of 0.93 ppb yr⁻¹ (p < 0.05) from 2013 to 2021. The change in meteorological variables, particularly the increase in air temperature, could explain nearly 87% of the springtime O₃ upward trend. The change in anthropogenic emissions of precursors only contributed to a small fraction (<13%) of the increase in springtime O₃. The cumulative exposure of urban residents to O₃ in spring also exhibited a significant upward trend (111 ppb yr⁻¹, p < 0.05). With the rapid increase in surface O₃, premature respiratory mortality attributable to O₃ exposure has fluctuated at approximately 2933 deaths per year since 2016, even though the total deaths from respiratory diseases have significantly declined. Long-term exposure to high O₃ concentrations is a significant contributor to premature respiratory mortality.

Air pollution has become a major issue in China, especially for traffic-related pollutants such as nitrogen dioxide (NO₂). Current studies in China at the national scale were less focused on NO₂ exposure and consequent health effects than fine particulate exposure, mainly due to a lack of high-quality exposure models for accurate NO₂ predictions over a long period. We developed an advanced modeling framework that incorporated multisource, high-quality predictor data (e.g., satellite observations [Ozone Monitoring Instrument NO₂, TROPOspheric Monitoring Instrument NO₂, and Multi-Angle Implementation of Atmospheric Correction aerosol optical depth], chemical transport model simulations, high-resolution geographical variables) and three independent machine learning algorithms into an ensemble model. The model contains three stages: (1) filling missing satellite data; (2) building an ensemble model and predicting daily NO₂ concentrations from 2013 to 2019 across China at 1×1 km² resolution; (3) downscaling the predictions to finer resolution (100 m) at the urban scale. Our model achieves a high performance in terms of cross-validation to assess the agreement of the overall (R² = 0.72) and the spatial (R² = 0.85) variations of the NO₂ predictions over the observations. The model performance remains moderately good when the predictions are extrapolated to the previous years without any monitoring data (CV R² > 0.68) or regions far away from monitors (CV R² > 0.63). We identified a clear decreasing trend of NO₂ exposure from 2013 to 2019 across the country with the largest reduction in suburban and rural areas. Our downscaled model further improved the prediction ability by 4%–14% in some megacities and captured substantial NO₂ variations within 1-km grids in the urban areas, especially near major roads. Our model provides flexibility at both temporal and spatial scales and can be applied to exposure assessment and epidemiological studies with various study domains (e.g., national or citywide) and settings (e.g., long-term and short-term).

The co-occurrence of enhancement in aerosol concentration, temperatures, and ozone mixing ratio was observed between June 29 and July 4, 2018 (enhanced period, EP) on Long Island (LI) and the greater NYC metropolitan area during part of the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS). Two aerosol formation pathways were identified during the EP, the first being the condensation of semi- and intermediate volatility oxidation products of anthropogenic volatile organic compounds (AVOCs) under stagnant synoptic flow conditions, high temperatures and afternoon sea-breeze circulation. While this first pathway was prevalent, the most abundant organic aerosol factor was less oxidized oxygenated organic aerosol or LO-OOA. The second formation pathway occurred during a period of more persistent (synoptic) on-shore flow transporting more aged aerosol which consisted of an internal mixture of more oxidized oxygenated organic aerosol (MO-OOA), methanesulfonic acid (MSA) and sulfate. It was estimated that 35% of the sulfate observed during the mature period (an average of about 1.2 μg m⁻³) originated from oceanic dimethyl sulfide (DMS) emissions. These two formation pathways helped elucidate the sources of fine particle pollution, highlighted the interaction between human emissions and natural DMS emission, and will help our understanding of pollution affecting other urban areas adjacent to large bodies of water during hot and stagnant periods.

Driven by human activities, air pollution and soil degradation are threatening food production systems. Rising ozone in the troposphere can affect several physiological processes in plants and their interaction with symbiotic microorganisms. Plant responses to ozone may depend on both soil fertility and the ontogenetic stage in which they are exposed. In this work, we studied the effects of ozone episodes and soil fertility on soybean plants. We analysed soybean plant responses in the production of aboveground and belowground biomass, structural and functional attributes of rhizobia, and seed production and quality. The experiment was performed with plants grown in two substrates with different fertility (commercial soil, and soil diluted (50%, v/v) with sand). Plants were exposed to acute episodes of ozone during vegetative and reproductive stages. We observed that ozone significantly reduced belowground biomass (≈25%), nodule biomass (≈30%), and biological nitrogen fixation (≈21%). Plants exposed to ozone during reproductive stage growing in soil with reduced fertility had lower seed production (≈10% lower) and seed protein (≈12% lower). These responses on yield and quality can be explained by the observed changes in belowground biomass and nitrogen fixation. The negative impact of ozone on the symbiotic interaction with rhizobia, seed production and quality in soybean plants were greater in soils with reduced fertility. Our results indicate that food security could be at risk in the future if trends in ozone concentration and soil degradation processes continue to increase.

Increased tropospheric ozone (O₃) concentrations in boreal forests affect the emission of biogenic volatile organic compounds (BVOCs), which play crucial roles in biosphere-atmosphere feedbacks. Although it has been well documented that BVOC emissions are altered in response to elevated O₃, consequent effects on the carbon budget have been largely unexplored. Here, we studied the effects of elevated O₃ (80 nmol mol⁻¹) on diurnal variation of BVOC emissions and gas exchange of CO₂ from above- and belowground parts of Norway spruce (Picea abies) and Scots pine (Pinus sylvestris) and further investigated effects on the carbon budget. In spring, elevated O₃ decreased BVOC emissions and net photosynthesis rate (Pn) from above-ground parts of both species. As BVOC emissions have a causal relationship with dormancy recovery, O₃-induced decreases in BVOC emissions indicated the inhibition of dormancy recovery. Contrary to the spring results, in summer BVOC emissions from aboveground parts were increased in response to elevated O₃ in both species. Decreases in Pn indicated O₃ stress. O₃-induced monoterpene emissions from aboveground were the main volatile defense response. Elevated O₃ had little effect on BVOC emissions from belowground parts of either species in spring or summer. In spring, elevated O₃ decreased the proportion of carbon emitted as BVOCs relative to that assimilated by photosynthesis (the proportion of BVOC-C loss) at the soil-plant system levels in both species. In summer, elevated O₃ resulted in a net CO₂–C loss at the soil-plant system level of Scots pine. During this process, O₃-induced BVOC-C loss can represent a significant fraction of carbon exchange between the atmosphere and Scots pine. In Norway spruce, the effects of O₃ were less pronounced. The current results highlight the need for prediction of BVOC emissions and their contributions to the carbon budget in boreal forests under O₃ stress.

Tropospheric (ground-level) ozone is a harmful phytotoxic pollutant, and can have a negative impact on crop yield and quality in sensitive species. Ozone can also induce visible symptoms on leaves, appearing as tiny spots (stipples) between the veins on the upper leaf surface. There is little measured data on ozone concentrations in Africa and it can be labour-intensive and expensive to determine the direct impact of ozone on crop yield in the field. The identification of visible ozone symptoms is an easier, low cost method of determining if a crop species is being negatively affected by ozone pollution, potentially resulting in yield loss. In this study, thirteen staple African food crops (including wheat (Triticum aestivum), common bean (Phaseolus vulgaris), sorghum (Sorghum bicolor), pearl millet (Pennisetum glaucum) and finger millet (Eleusine coracana)) were exposed to an episodic ozone regime in a solardome system to monitor visible ozone symptoms. A more detailed examination of the progression of ozone symptoms with time was carried out for cultivars of P. vulgaris and T. aestivum, which showed early leaf loss (P. vulgaris) and an increased rate of senescence (T. aestivum) in response to ozone exposure. All of the crops tested showed visible ozone symptoms on their leaves in at least one cultivar, and ozone sensitivity varied between cultivars of the same crop. A guide to assist with identification of visible ozone symptoms (including photographs and a description of symptoms for each species) is presented.