The underappreciated role of agricultural soil nitrogen oxide emissions in ozone pollution regulation in North China

Rising frequency of ozone-favorable synoptic weather patterns contributes to 2015-2022 ozone increase in Guangzhou

Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns (SWPs), however, the consistency of different classification methods is rarely examined. In this study, we apply two widely-used objective methods, the self-organizing map (SOM) and K-means clustering analysis, to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022. We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities. In the case of classifying six SWPs, the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods, and the difference in the mean frequency of each SWP is less than 7%. The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature, lower cloud cover, relative humidity, and wind speed, and stronger subsidence compared to climatology mean. We find that during 2015-2022, the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 day/year, faster than the increases in the ozone exceedance days (3.0 day/year). The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6. In particular, the significant increase in ozone-favorable SWPs in 2022, especially the Subtropical High type which typically occurs in September, is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022. Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.

Global net climate effects of anthropogenic reactive nitrogen

Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times1,2, contributing to widespread eutrophication and air pollution3-6. Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of -0.34 [-0.20, -0.50] W m-2 in the year 2019 relative to the year 1850. This net cooling effect is the result of increased aerosol loading, reduced methane lifetime and increased terrestrial carbon sequestration associated with increases in anthropogenic Nr, which are not offset by the warming effects of enhanced atmospheric nitrous oxide and ozone. Future predictions using three representative scenarios show that this cooling effect may be weakened primarily as a result of reduced aerosol loading and increased lifetime of methane, whereas in particular N2O-induced warming will probably continue to increase under all scenarios. Our results indicate that future reductions in anthropogenic Nr to achieve environmental protection goals need to be accompanied by enhanced efforts to reduce anthropogenic greenhouse gas emissions to achieve climate change mitigation in line with the Paris Agreement.

The reward and penalty for ozone pollution control caused by natural sources and regional transport: A case study in Guangdong province

Ground-level O3 pollution in the Pearl River Delta region (PRD) is closely related to anthropogenic, natural emissions and regional transport. However, the interactions among different sources and natural intervention in modulating anthropogenic management have not been comprehensively assessed. Here, the WRF-CMAQ-MEGAN modeling system was utilized to simulate an O3 episode over PRD. The integrated source apportionment method (ISAM) and brute-force top-down combined with factor separation approach (BF-TD-FSA) were applied to quantify source contributions, impacts of individual or multiple sources on O3, and decouple interactions among various emissions; additionally, based on ISAM, O3 isopleths visualized MDA8 O3 response of different source types to anthropogenic perturbations. ISAM concluded considerable MDA8 O3 contributions of regional transport in PRD/NPRD (non-PRD areas in Guangdong province) (38.8 %/35.7 %), followed by anthropogenic (32.7 %/24.8 %), BVOC (biogenic volatile organic compounds, 23.8 %/20.3 %) and SNO (soil NO, ∼4 %) emissions. Compared to concentrated anthropogenic contributions, widespread natural contributions were observed across their source areas and along the transport pathways. The BF-TD also revealed that regional transport had the largest impact (>90 μg m-3) on MDA8 O3 while anthropogenic and BVOC emissions greatly affected downwind PRD (64.5 and 7.7 μg m-3). Negative synergy between anthropogenic and natural emissions (especially BVOC emission) suggested potential natural-induced intensification of anthropogenic impact during O3 management. The MDA8 O3 isopleths further demonstrated significant BVOC-induced reward and regional transport-induced penalty for anthropogenic NOx (ANOx) emission control benefits, leading to additional maximum MDA8 O3 decrease and increase by -27.5 and 13.8 μg m-3 in polluted high-emission grids. The natural-induced reward effect could impose loose requirements on anthropogenic reduction (decreased by 13.3 %-17.7 %) if there were no regional transport-induced control penalty. It is advisable to prioritize ANOx control and seek collaboration on air quality management with neighboring provinces to maximize the natural-induced control reward and achieve desired targets with minimal human efforts.

Unveiling 3-D evolution and mechanisms of ozone pollution in Changzhou, China: Insights from lidar observations and modelling

Ground ozone (O3) pollution has emerged as a prominent environmental concern in eastern cities of China, particularly during the summer and autumn seasons. However, a comprehensive investigation into the three-dimensional (3-D) evolution characteristics of O3 within complicated urban environments, especially in lake-land environment, is notably scarce. To enhance our understanding of the mechanisms underlying elevated O3 concentrations within a 3-D scale, this study employed an ozone lidar to delineate vertical ozone profiles in Changzhou, a typical city in China with complicated anthropogenic and biogenic emissions and complex land cover. The process analysis tool integrated into the Weather Research and Forecasting with Chemistry (WRF-Chem) model was further utilized to analyze the formation processes of O3. The results unveil a persistent O3 pollution episode lasting over 15 days in Changzhou during the study period, with multiple peaks exceeding 200 μg m⁻³. Notably, O3 predominantly accumulated within the boundary layer, confined below 1.2 km. Both ground and vertical contributions to this pollution were mainly due to local chemical reactions, with a maximum near-surface contribution reaching 19 ppb h-1 and a vertical contribution of 10 ppb h-1 at the height of 900 ± 200 m. Furthermore, episodes of the enhanced O3 concentrations on August 9 and August 26, 2021, were influenced by external advection process. Our study also found that local circulation plays an important role in the accumulation of surface O3 during certain periods. There was a temperature difference between the surface of Lake Tai and the adjacent land, resulting in the formation of lake-land breezes that facilitate the transport of O3 from the lake surface to the terrestrial environment during pollution events. Our study emphasizes the necessity of reducing local pollutant emissions and implementing joint emission controls as the primary strategies for mitigating O3 pollution in Changzhou and the surrounding region.

Efficient Ozone Elimination Over MnO2 via Double Moisture-Resistance Protection of Active Carbon and CeO2

The widespread ozone (O3) pollution is extremely hazardous to human health and ecosystems. Catalytic decomposition into O2 is the most promising method to eliminate ambient O3, while the fast deactivation of catalysts under humid conditions remains the primary challenge for their application. Herein, we elaborately developed a splendidly active and stable Mn-based catalyst with double hydrophobic protection of active carbon (AC) and CeO2 (CeMn@AC), which possessed abundant interfacial oxygen vacancies and excellent desorption of peroxide intermediates (O22-). Under extremely humid (RH = 90%) conditions and a high space velocity of 1200 L h-1 g-1, the optimized CeMn@AC achieved nearly 100% O3 conversion (140 h) at 5 ppm, showing unprecedented catalytic activity and moisture resistance toward O3 decomposition. In situ DRIFTS and theory calculations confirmed that the exceptional moisture resistance of CeMn@AC was ascribed to the double protection effect of AC and CeO2, which cooperatively prevented the competitive adsorption of H2O molecules and their accumulation on the active sites of MnO2. AC provided a hydrophobic reaction environment, and CeO2 further alleviated moisture deterioration of the MnO2 particles exposed on the catalyst surface via the moisture-resistant oxygen vacancies of MnO2-CeO2 crystal boundaries. This work offers a simple and efficient strategy for designing moisture-resistant materials and facilitates the practical application of the O3 decomposition catalysts in various environments.

Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities

Short-term exposure to particles with aerodynamic diameters less than 2.5 μm (PM2.5) and ozone (O3) are important risk factors for human health. Despite the awareness of reducing attributable health burden, region-specific and source-specific strategies remain less explored due to the gap between precursor emissions and health effects. In this study, we isolate the health burden of individual sector sources of PM2.5 and O3 precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), across the globe. Specifically, we estimate mortalities attributable to short-term exposure using machine-learning-based daily exposure estimates and quantify sectoral impacts using chemical transport model simulations. Globally, short-term exposure to PM2.5 and O3 result in 713.5 (95% Confidence Interval: 598.8-843.3) thousand and 496.3 (371.3-646.1) thousand mortalities in 2019, respectively, of which 12.5% are contributed by fuel-related NOx emissions from transportation, energy, and industry. Sectoral impacts from anthropogenic NOx and VOC emissions on health burden vary significantly among seasons and regions, requiring a target shift from transportation in winter to industry in summer for East Asia, for instance. Emission control and health management are additionally complicated by unregulated natural influences during climatic events. Fire-sourced NOx and VOC emissions, respectively, contribute to 8.5 (95% CI: 6.2-11.7) thousand and 4.8 (3.6-5.9) thousand PM2.5 and O3 mortalities, particularly for tropics with high vulnerability to climate change. Additionally, biogenic VOC emissions during heatwaves contribute to 1.8 (95% CI: 1.5-2.2) thousand O3-introduced mortalities, posing challenges in urban planning for high-income regions, where biogenic contributions to health burden during heatwaves are 13% of anthropogenic contributions annually. Our study provides important implications for temporally dynamic and sector-targeted emission control and health management strategies, which are of urgency under the projection of continuously increasing energy consumption and changing climate.

Highly Accurate and Explainable Predictions of Small-Molecule Antioxidants for Eight In Vitro Assays Simultaneously through an Alternating Multitask Learning Strategy

Small molecule antioxidants can inhibit or retard oxidation reactions and protect against free radical damage to cells, thus playing a key role in food, cosmetics, pharmaceuticals, the environment, as well as materials. Experimentally driven antioxidant discovery is a major paradigm, and computationally assisted antioxidants are rarely reported. In this study, a functional-group-based alternating multitask self-supervised molecular representation learning method is proposed to simultaneously predict the antioxidant activities of small molecules for eight commonly used in vitro antioxidant assays. Extensive evaluation results reveal that compared with the baseline models, the multitask FG-BERT model achieves the best overall predictive performance, with the highest average F1, BA, ROC-AUC, and PRC-AUC values of 0.860, 0.880, 0.954, and 0.937 for the test sets, respectively. The Y-scrambling testing results further demonstrate that such a deep learning model was not constructed by accident and that it has reliable predictive capabilities. Additionally, the excellent interpretability of the multitask FG-BERT model makes it easy to identify key structural fragments/groups that contribute significantly to the antioxidant effect of a given molecule. Finally, an online antioxidant activity prediction platform called AOP (freely available at https://aop.idruglab.cn/) and its local version were developed based on the high-quality multitask FG-BERT model for experts and nonexperts in the field. We anticipate that it will contribute to the discovery of novel small-molecule antioxidants.

Impact of soil-atmosphere HONO exchange on concentrations of HONO and O3 in the North China Plain

Nitrous acid (HONO) is an important precursor of the hydroxyl radical (OH) and plays a vital role in atmospheric photochemistry and nitrogen cycling. Soil emissions have been considered as a potential source of HONO. Lately, the HONO emission via soil-atmosphere exchange (ESA-exchange) from soil nitrite has been validated and quantified through chamber experiments, but has not been assessed in the real atmosphere. We coupled ESA-exchange and the other seven potential sources of HONO (i.e., traffic, indoor and soil bacterial emissions, heterogeneous reactions on ground and aerosol surfaces, nitrate photolysis, and acid displacement) into the Weather Research and Forecasting model with Chemistry (WRF-Chem), and found that diurnal variations of the soil emission flux at the Wangdu site were well simulated. During the non-fertilization period, ESA-exchange contributed ∼28 % and ∼35 % of nighttime and daytime HONO, respectively, and enhanced the net ozone (O3) production rate by ∼8 % across the North China Plain (NCP). During the preintensive/intensive fertilization period, the maximum ESA-Exchange contributions attained ∼70 %/83 % of simulated HONO in the afternoon across the NCP, definitely asserting its dominance in HONO production. ESA-Exchange enhanced the OH production rate via HONO photolysis by ∼3.5/7.0 times, and exhibited an increase rate of ∼13 %/20 % in the net O3 production rate across the NCP. The total enhanced O3 due to the eight potential HONO sources ranged from ∼2 to 20 ppb, and ESA-exchange produced O3 enhancements of ∼1 to 6 ppb over the three periods. Remarkably, the average contribution of ESA-exchange to the total O3 enhancements remained ∼30 %. This study suggests that ESA-exchange should be included in three-dimensional chemical transport models and more field measurements of soil HONO emission fluxes and soil nitrite levels are urgently required.

Spatiotemporal evolution and key driver analysis of ozone pollution from the perspectives of spatial spillover and path-dependence effects in China

In recent years, ozone (O3) has emerged as the primary air pollutant in China, superseding PM2.5. Previous studies have concentrated on the spatiotemporal variation of ozone pollution, the analysis of its sources and drivers, as well as its environmental impacts and health benefits. Since ozone pollution can be dynamically transferred through industrial activities and meteorological factors, it is crucial to scientifically identify the spatial spillover and path-dependent effects of ozone pollution in China. However, existing studies have not yet addressed this issue. Therefore, we investigate the spatiotemporal evolution and the spatial spillover of ozone pollution by means of the exploratory spatial data analysis (ESDA) using panel data of 30 Chinese provinces from 2013 to 2020 in this study. The dynamic spatial Durbin model (SDM) was employed to reveal the key drivers of ozone pollution from the perspectives of spatial spillover and path-dependence effects. The direct and spillover effects of each driver on ozone pollution are systematically analyzed. The results show that from 2013 to 2020 ozone concentrations followed a fluctuating upward trend at national and provincial scales. Ozone pollution presented significant spatial spillover and path dependence effects. The direct effects indicated that economic growth, technological level, industrial structure, energy structure, ventilation coefficient, relative humidity and precipitation were the key drivers of local ozone pollution. The spillover effects indicated that population density, technology level, industrial structure, environmental regulations, ventilation coefficient, sunshine hours and relative humidity had significant spatial spillover effects on ozone pollution of surrounding regions. These findings will contribute to the understanding of the spatial spillover and path-dependent effects of O3 pollution, and provide scientific guidance for regional synergy and long-term ozone control policies in China.

A new ChatGPT-empowered, easy-to-use machine learning paradigm for environmental science

The quantity and complexity of environmental data show exponential growth in recent years. High-quality big data analysis is critical for performing a sophisticated characterization of the complex network of environmental pollution. Machine learning (ML) has been employed as a powerful tool for decoupling the complexities of environmental big data based on its remarkable fitting ability. Yet, due to the knowledge gap across different subjects, ML concepts and algorithms have not been well-popularized among researchers in environmental sustainability. In this context, we introduce a new research paradigm-"ChatGPT + ML + Environment", providing an unprecedented chance for environmental researchers to reduce the difficulty of using ML models. For instance, each step involved in applying ML models to environmental sustainability, including data preparation, model selection and construction, model training and evaluation, and hyper-parameter optimization, can be easily performed with guidance from ChatGPT. We also discuss the challenges and limitations of using this research paradigm in the field of environmental sustainability. Furthermore, we highlight the importance of "secondary training" for future application of "ChatGPT + ML + Environment".

Reducing Soil-Emitted Nitrous Acid as a Feasible Strategy for Tackling Ozone Pollution

Severe ozone (O3) pollution has been a major air quality issue and affects environmental sustainability in China. Conventional mitigation strategies focusing on reducing volatile organic compounds and nitrogen oxides (NOx) remain complex and challenging. Here, through field flux measurements and laboratory simulations, we observe substantial nitrous acid (HONO) emissions (FHONO) enhanced by nitrogen fertilizer application at an agricultural site. The observed FHONO significantly improves model performance in predicting atmospheric HONO and leads to regional O3 increases by 37%. We also demonstrate the significant potential of nitrification inhibitors in reducing emissions of reactive nitrogen, including HONO and NOx, by as much as 90%, as well as greenhouse gases like nitrous oxide by up to 60%. Our findings introduce a feasible concept for mitigating O3 pollution: reducing soil HONO emissions. Hence, this study has important implications for policy decisions related to the control of O3 pollution and climate change.

Coping with the concurrent heatwaves and ozone extremes in China under a warming climate

Intensive human activity has brought about unprecedented climate and environmental crises, in which concurrent heatwaves and ozone extremes pose the most serious threats. However, a limited understanding of the comprehensive mechanism hinders our ability to mitigate such compound events, especially in densely populated regions like China. Here, based on field observations and climate-chemistry coupled modelling, we elucidate the linkage between human activities and the climate system in heat-related ozone pollution. In China, we have observed that both the frequency and intensity of heatwaves have almost tripled since the beginning of this century. Moreover, these heatwaves are becoming more common in urban clusters with serious ozone pollution. Persistent heatwaves during the extremely hot and dry summers of 2013 and 2022 accelerated photochemical ozone production by boosting anthropogenic and biogenic emissions, and aggravated ozone accumulation by suppressing dry deposition due to water-stressed vegetation, leading to a more than 30% increase in ozone pollution in China's urban areas. The sensitivity of ozone to heat is demonstrated to be substantially modulated by anthropogenic emissions, and China's clean air policy may have altered the relationship between ozone and temperature. Climate model projections further highlight that the high-emission climate-socioeconomic scenario tends to intensify the concurrent heat and ozone extremes in the next century. Our results underscore that the implementation of a strict emission strategy will significantly reduce the co-occurrence of heatwaves and ozone extremes, achieving climate and environmental co-benefits.

Unveiling the importance of VOCs from pesticides applicated in main crops for elevating ozone concentrations in China

Volatile organic compounds (VOCs) are considered as important precursors of ozone in the air, while the contribution of VOCs from pesticide application (PVOCs) to ozone production is unknown. Utilizing data from the Ministry of Agriculture and Rural Affairs of the People's Republic of China and ChinaCropPhen1km, this paper developed PVOC emission inventories with a resolution of 1 km for the main crops (rice, maize, and wheat) from 2012 to 2019 in China. The results revealed that pesticide application is an important VOC emission source in China. Specially, the PVOC emissions from the major grain-producing regions in June accounted for approximately 30% of the annual total PVOC emissions in the local regions. The simulation with the Weather Research and Forecasting Community Multiscale Air Quality model (WRF-CMAQ) indicated that the PVOC emissions increased the mean maximum daily 8-hour average (MDA8) ozone concentration across China by 2.5 ppb in June 2019. During the same period, PVOCs in the parts of North China Plain contributed 10% of the ozone formation. Under the comprehensive emission reduction scenario, it is anticipated that by 2025, the joint implementation of measures including reducing pesticide application, improving pesticide utilization efficiency and promoting solvent substitution will decrease PVOC emissions by 60% compared with 2019, thereby mitigating ozone pollution.

Spatial and temporal variations of surface background ozone in China analyzed with the grid-stretching capability of GEOS-Chem High Performance

Surface background ozone, defined as the ozone in the absence of domestic anthropogenic emissions, is important for developing emission reduction strategies. Here we apply the recently developed GEOS-Chem High Performance (GCHP) global atmospheric chemistry model with ∼0.5° stretched resolution over China to understand the sources of Chinese background ozone (CNB) in the metric of daily maximum 8 h average (MDA8) and to identify the drivers of its interannual variability (IAV) from 2015 to 2019. The GCHP ozone simulations over China are evaluated with an ensemble of surface and aircraft measurements. The five-year national-mean CNB ozone is estimated as 37.9 ppbv, with a spatially west-to-southeast downward gradient (55 to 25 ppbv) and a summer peak (42.5 ppbv). High background levels in western China are due to abundant transport from the free troposphere and adjacent foreign regions, while in eastern China, domestic formation from surface natural precursors is also important. We find greater importance of soil nitric oxides (NOx) than biogenic volatile organic compound emissions to CNB ozone in summer (6.4 vs. 3.9 ppbv), as ozone formation becomes increasingly NOx-sensitive when suppressing anthropogenic emissions. The percentage of daily CNB ozone to total surface ozone generally decreases with increasing daily total ozone, indicating an increased contribution of domestic anthropogenic emissions on polluted days. CNB ozone shows the largest IAV in summer, with standard deviations (seasonal means) of ∼5 ppbv over Qinghai-Tibet Plateau (QTP) and >3.5 ppbv in eastern China. CNB values in QTP are strongly correlated with horizontal circulation anomalies in the middle troposphere, while soil NOx emissions largely drive the IAV in the east. El Nino can inhibit CNB ozone formation in Southeast China by increased precipitation and lower temperature locally in spring, but enhance CNB in Southwest China through increased biomass burning emissions in Southeast Asia.

Manure application maintained the CO2 fixation activity of soil autotrophic bacteria but changed its ecological characteristics in an entisol of China

The response of soil autotrophs to anthropogenic activities has attracted increasing attention against the background of global change. Here, three entisol plots under different fertilizing regimes, including no fertilization (CK), manure (M), and a combined application of chemical fertilizer and manure (NPKM) were selected, and then the soil RubisCO (ribulose-1,5-bisphosphate carboxylase/oxygenase) activity and cbbl (gene encoding the large subunit of RubisCO) composition were measured to indicate the activity and community of autotrophic bacteria, respectively. The results revealed that the RubisCO activity of CK showed no difference from that of M but was significantly higher than that of NPKM. The CK and M had the lowest and highest soil cbbl abundance, respectively. The α-diversity of soil cbbl-carrying bacteria showed no significant difference among these treatments, whereas they showed significantly different community structures of cbbl-carrying bacteria. Meanwhile, compared with CK, M had significantly lower abundances of bacterial species with the functions of nitrogen fixation (Azoarcus sp.KH32C) or detoxification (Methylibium petroleiphilum), indicating that manure application might have an inhibiting potential to some beneficial autotrophic bacterial species in this entisol.

Life cycle assessment of coal mines of diverse scales over time in China

Coal mining has important detrimental effects on the environment and human health. By the end of 2022, China mined more than 4 billion tons of raw coal, and coal mining contributed to adverse environmental impacts. The objective of this work is to evaluate the environmental impacts emanated from coal mines in different periods (construction period, production period and closing period) and to find the relationship between coal mine scale and ecological impacts. This study uses coal mines that produce 0.45 Mt/a (considered a medium sized mine), 3 Mt/a and 8 Mt/a (both classified as large mines in this study) and a 12 Mt/a extra-large coal mine. Based on the time dimension, the mine life cycle was classified into construction, production and closing period, and the life cycle assessment method was used to conduct environmental assessment. The main influencing substances and key processes were tracked. The results indicated that mining engineering and gangue are the main factors affecting the construction and production periods of coal mines. Freshwater ecotoxicity, marine ecotoxicity, and human toxicity are the main environmental effects of coal produce, and they are mostly brought up by the release of hazardous elements like copper, chromium, zinc, nickel, and copper. Furan, formaldehyde, and chromium emissions during mine closure can be effectively reduced through environmental compensation, however coal mines' environmental compensation during mine closure is minimal. The environmental impact of coal mines producing 3 Mt and 8 Mt annually is minimal. The environmental impact of 0.45 Mt/a and 3 Mt/a coal mines is more prominent in the construction period. The pollutant discharge throughout the production phase, particularly the metal leaching discharge from gangue, needs to receive more attention from the 8 Mt/a and 12 Mt/a coal mines. Additionally, the larger the scale of coal mine production, the greater the proportion of the total environmental impact in the production stage.

Application of machine learning in atmospheric pollution research: A state-of-art review

Machine learning (ML) is an artificial intelligence technology that has been used in atmospheric pollution research due to their powerful fitting ability. In this review, 105 articles related to ML and the atmospheric pollution research are critically reviewed. Applications of ML in the prediction of atmospheric pollution (mainly particulate matters) are systematically described, including the principle of prediction, influencing factors and improvement measures. Researchers can improve the accuracy of the prediction model through three main aspects, namely considering the geographical features of the study area into the model, introducing the physical characteristics of pollutants, matching and optimizing ML models. And by using interpretable ML tools, researchers are able to understand the mechanism of the model and gain in-depth information. Then, the state-of-art applications of ML in the source apportionment of atmospheric particulate matter and the effect of atmospheric pollutants on human health are also described. In addition, the advantages and disadvantages of the current applications of ML in atmospheric pollution research are summarized, and the application perspective of ML in this field is elucidated. Given the scarcity of source apportionment applications and human health research, standardized research methods and specialized ML methods are required in atmospheric pollution research to connect these two disciplines.

Organizational support, market access, and farmers' adoption of agricultural green production technology: evidence from the main kiwifruit production areas in Shaanxi Province

Industrial organizations play a crucial role in transforming the production and management practices of smallholder farmers, encouraging the adoption of environmentally friendly production methods. However, limited studies have conducted comprehensive research examining how these industrial organizations effectively encourage farmers to adopt green production technologies. To address this research gap, this study examines the influence of organizational support on the adoption of agricultural green production technologies among 645 kiwifruit farmers in Shaanxi Province, northwestern China, using cross-sectional survey data from 2022. In addition, this research explores the mechanisms and heterogeneity in this impact. In our analysis, we estimated Probit models and mediation effect models, which show a positive influence of organizational support on farmers' adoption of these technologies. Notably, both institutional support and tool support have a more pronounced positive effect on this adoption. The mechanism analysis shows that organizational support facilitates farmers' adoption of these agricultural green production technologies by expanding their access to high-value markets. Furthermore, when considering heterogeneity among farmers, the study finds that organizational support has the most significant impact on the adoption of these technologies among farmers operating at a moderate scale. Moreover, our research highlights a technology linkage effect in the adoption process. Specifically, organizational support has a positive and significant effect on the adoption of technologies like bagging, physical control, and soil testing formulas, while also having a positive but statistically insignificant impact on technologies such as pollution-free pesticides and organic fertilizer substitution. In conclusion, the study proposes to increase assistance to industrial organizations, to play an influential role in guiding and driving farmers.

Elevated tropospheric ozone and crop production: potential negative effects and plant defense mechanisms

Ozone (O3) levels on Earth are increasing because of anthropogenic activities and natural processes. Ozone enters plants through the leaves, leading to the overgeneration of reactive oxygen species (ROS) in the mesophyll and guard cell walls. ROS can damage chloroplast ultrastructure and block photosynthetic electron transport. Ozone can lead to stomatal closure and alter stomatal conductance, thereby hindering carbon dioxide (CO2) fixation. Ozone-induced leaf chlorosis is common. All of these factors lead to a reduction in photosynthesis under O3 stress. Long-term exposure to high concentrations of O3 disrupts plant physiological processes, including water and nutrient uptake, respiration, and translocation of assimilates and metabolites. As a result, plant growth and reproductive performance are negatively affected. Thus, reduction in crop yield and deterioration of crop quality are the greatest effects of O3 stress on plants. Increased rates of hydrogen peroxide accumulation, lipid peroxidation, and ion leakage are the common indicators of oxidative damage in plants exposed to O3 stress. Ozone disrupts the antioxidant defense system of plants by disturbing enzymatic activity and non-enzymatic antioxidant content. Improving photosynthetic pathways, various physiological processes, antioxidant defense, and phytohormone regulation, which can be achieved through various approaches, have been reported as vital strategies for improving O3 stress tolerance in plants. In plants, O3 stress can be mitigated in several ways. However, improvements in crop management practices, CO2 fertilization, using chemical elicitors, nutrient management, and the selection of tolerant crop varieties have been documented to mitigate O3 stress in different plant species. In this review, the responses of O3-exposed plants are summarized, and different mitigation strategies to decrease O3 stress-induced damage and crop losses are discussed. Further research should be conducted to determine methods to mitigate crop loss, enhance plant antioxidant defenses, modify physiological characteristics, and apply protectants.

Meteorological and anthropogenic drivers of surface ozone change in the North China Plain in 2015-2021

Surface ozone (O3) concentrations in China have increased largely in the past decade. An accurate understanding of O3 pollution evolution is critical for making effective regulatory policies. Here we integrate data- and process-based models to explore the drivers of the observed summertime surface O3 change in the North China Plain (NCP) over 2015-2021. The data-based model by the deep learning (DL) suggests the reverse of meteorological contributions to the observed O3 change, i.e., 0.14 ppb/y in 2015-2019 and -1.74 ppb/y in 2019-2021. This is mainly resulted from the reversed changes in meteorological variables in surface air temperature and relative humidity. The simulations from a global chemical transport model, GEOS-Chem, also support those results, i.e., the meteorological contribution to O3 changes are 0.26 ppb/y in 2015-2019 and -0.74 ppb/y in 2019-2021. Furthermore, our analysis exhibits possible weakened anthropogenic contributions to surface O3 rise, for example, 1.53 and 0.54 ppb/y by DL in 2015-2019 and 2019-2021, respectively. Similarly, GEOS-Chem simulations suggest an accelerated decrease in surface O3 concentrations driven by the decline in nitrogen dioxide (NO2) concentrations, i.e., approximately 0.4 and 1.2 ppb in 2015-2019 and 2019-2021, respectively. The combined effects of meteorological and anthropogenic contributions led to a significant decrease in surface O3 concentrations by -1.20 ppb/y in 2019-2021. The findings in this work offer valuable insights to mitigate O3 pollution in China.

Summertime tropospheric ozone source apportionment study in the Madrid region (Spain)

The design of emission abatement measures to effectively reduce high ground-level ozone (O3) concentrations in urban areas is very complex. In addition to the strongly non-linear chemistry of this secondary pollutant, precursors can be released by a variety of sources in different regions, and locally produced O3 is mixed with that transported from the regional or continental scales. All of these processes depend also on the specific meteorological conditions and topography of the study area. Consequently, high-resolution comprehensive modeling tools are needed to understand the drivers of photochemical pollution and to assess the potential of local strategies to reduce adverse impacts from high tropospheric O3 levels. In this study, we apply the Integrated Source Apportionment Method (ISAM) implemented in the Community Multiscale Air Quality (CMAQ v5.3.2) model to investigate the origin of summertime O3 in the Madrid region (Spain). Consistent with previous studies, our results confirm that O3 levels are dominated by non-local contributions, representing around 70 % of mean values across the region. Nonetheless, precursors emitted by local sources, mainly road traffic, play a more important role during O3 peaks, with contributions as high as 25 ppb. The potential impact of local measures is higher under unfavorable meteorological conditions associated with regional accumulation patterns. These findings suggest that this modeling system may be used in the future to simulate the potential outcomes of specific emission abatement measures to prevent high-O3 episodes in the Madrid metropolitan area.

Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain

Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.

NOx degradation ability of S-g-C3N4/MgAl-CLDH nanocomposite and its potential application in cement-based materials

In this study a new photocatalytic nanocomposite, S-g-C₃N₄/MgAl-CLDH, was synthesized and implemented into cement mortar by internal mixing or coating. The photocatalytic NO_x degradation efficiency of the S-g-C₃N₄/MgAl-CLDH and photocatalytic mortar was investigated. The NO_x degradation efficiency and photoluminescence spectra of S-g-C₃N₄/MgAl-CLDH after being immersed in the simulated concrete pore solution were evaluated to assess its chemical stability. The results show that compared with S-g-C₃N₄, the S-g-C₃N₄/MgAl-CLDH exhibits a narrower bandgap (2.45 eV), a lower photogenerated electron-hole pair recombination rate and a higher specific surface area (36.86 m² g^-1). After 21 min of visible light irradiation, the NO_x degradation rate of S-g-C₃N₄/MgAl-CLDH achieves 100% as compared to merely 81.5% of S-g-C₃N₄. After being submerged in simulated concrete pore solution, the S-g-C₃N₄/MgAl-CLDH exhibits only a slight decrease of 5% in degradation rate after 12 min of irradiation, confirming a good compatibility and stability in cement-based materials. The NO_x degradation ability of the internally mixed mortar is enhanced with an increase in the dosage of S-g-C₃N₄/MgAl-CLDH. For coated mortar, in contrast, a decline in NO_x degradation rate is observed after 5 layers of coating owing to the lower porosity of mortar after excessive coating.

Development of an integrated machine-learning and data assimilation framework for NOx emission inversion

As major air pollutants, nitrogen oxides (NO_x, mainly comprising NO and NO₂) not only have adverse effects on human health but also contribute to the formation of secondary pollutants, such as ozone and particulate nitrate. To acquire reasonable NO_x simulation results for further analysis, a reasonable emission inventory is needed for three-dimensional chemical transport models (3D-CTMs). In this study, a comprehensive emission adjustment framework for NO_x emission, which integrates the simulation results of the 3D-CTM, surface NO₂ measurements, the three-dimensional variational data assimilation method, and an ensemble back propagation neural network, was proposed and applied to correct NO_x emissions over China for the summers of 2015 and 2020. Compared with the simulation using prior NO_x emissions, the root-mean-square error, normalized mean error, and normalized mean bias decreased by approximately 40 %, 40 %, and 60 % in NO₂ simulation using posterior NO_x emissions corrected by the framework proposed in this work. Compared with the emissions for 2015, the NO_x emission generally decreased by an average of 5 % in the simulation domain for 2020, especially in Henan and Anhui provinces, where the percentage reductions reached 24 % and 19 %, respectively. The proposed framework is sufficiently flexible to correct emissions in other periods and regions. The framework can provide reliable and up-to-date emission information and can thus contribute to both scientific research and policy development relating to NO_x pollution.

Divergent summertime surface O3 pollution formation mechanisms in two typical Chinese cities in the Beijing-Tianjin-Hebei region and Fenwei Plain

Recently, severe summertime ozone (O₃) pollution has swept across most areas of China, especially the Beijing-Tianjin-Hebei (BTH) region and Fenwei Plain. By focusing on Beijing and Yuncheng, which are two typical cities in the BTH region and the Fenwei Plain, we intended to reveal the neglected fact that they had disparate emission features and atmospheric movements but suffered from similar high-O₃ pollution levels. Field observations indicated that Yuncheng had lower volatile organic compound (VOC) and NO_x concentrations but higher background O₃ levels. The model simulation verified that both photochemical reactions and net O₃ generation were stronger in Beijing. Ultimately, faster net O₃ generation rates (8.4 ppbv/h) plus lower background O₃ values in Beijing and lower net O₃ generation rates (6.2 ppbv/h) plus higher background O₃ values in Yuncheng caused both regions to reach similar O₃ peak values in July 2020. However, different O₃ control measures were appropriate for the two cities according to the different simulated O₃-VOCs-NO_x responses. Additionally, as surface O₃ levels are greatly affected by the ongoing O₃ production/depletion process that occurs in three dimensions, exploring the effects of spatially distributed O₃ on surface O₃ should be high on the agenda in the future.

Large Contribution of Nitrous Acid to Soil-Emitted Reactive Oxidized Nitrogen and Its Effect on Air Quality

Soil emissions have long been recognized as an important source of nitric oxide (NO), which regulates atmospheric oxidative capacity and the production of air pollutants. Recent research has also indicated that nitrous acid (HONO) can be emitted in significant quantities from soil microbial activities. However, only a few studies have quantified emissions of HONO along with NO from a wide range of soil types. In this study, we measured emissions of HONO and NO from soil samples collected from 48 sites across China and found much higher emissions of HONO than of NO, especially for samples from northern China. We performed a meta-analysis of 52 field studies in China, which revealed that long-term fertilization increased the abundance of nitrite-producing genes much more than the abundance of NO-producing genes. This promotion effect was greater in northern China than in southern China. In simulations using a chemistry transport model with laboratory-derived parametrization, we found that HONO emissions had a greater effect than NO emissions on air quality. Moreover, we determined that with projected continuous reductions in anthropogenic emissions, the contribution from soils to maximum 1 h concentrations of hydroxyl radicals and ozone and daily average concentrations of particulate nitrate in the Northeast Plain will increase to 17%, 4.6%, and 14%, respectively. Our findings highlight the need to consider HONO in the assessment of the loss of reactive oxidized nitrogen from soils to the atmosphere and its effect on air quality.

First long-term surface ozone variations at an agricultural site in the North China Plain: Evolution under changing meteorology and emissions

Significant upward trends in surface ozone (O₃) have been widely reported in China during recent years, especially during warm seasons in the North China Plain (NCP), exerting adverse environmental effects on human health and agriculture. Quantifying long-term O₃ variations and their attributions helps to understand the causes of regional O₃ pollution and to formulate according control strategy. In this study, we present long-term trends of O₃ in the warm seasons (April-September) during 2006-2019 at an agricultural site in the NCP and investigate the relative contributions of meteorological and anthropogenic factors. Overall, the maximum daily 8-h average (MDA8) O₃ exhibited a weak decreasing trend with large interannual variability. < 6 % of the observed trend could be explained by changes in meteorological conditions, while the remaining 94 % was attributed to anthropogenic impacts. However, the interannual variability of warm season MDA8 O₃ was driven by both meteorology (36 ± 28 %) and anthropogenic factors (64 ± 27 %). Daily maximum temperature was the most essential factor affecting O₃ variations, followed by ultraviolet radiation b (UVB) and boundary layer height (BLH), with rising temperature trends inducing O₃ inclines throughout April to August, while UVB mainly influenced O₃ during summer months. Under changes in emissions and air quality, warm season O₃ production regime gradually shifted from dominantly VOCs-limited during 2006-2015 to NO_x-limited afterwards. Relatively steady HCHO and remarkably rising NO_x levels resulted in the fast decreasing MDA8 O₃ (-2.87 ppb yr^-1) during 2006-2012. Rapidly decreasing NO_x, flat or slightly increasing HCHO promoted O₃ increases during 2012-2015 (9.76 ppb yr^-1). While afterwards, slow increases in HCHO and downwards fluctuating NO_x led to decreases in MDA8 O₃ (-4.97 ppb yr^-1). Additionally, continuous warming trends might promote natural emissions of O₃ precursors and magnify their impacts on agricultural O₃ by inducing high variability, which would require even more anthropogenic reduction to compensate for.

Increased diurnal difference of NO2 concentrations and its impact on recent ozone pollution in eastern China in summer

Nitrogen dioxide (NO₂) is a key tropospheric O₃ precursor. Since 2013, efforts to decrease air pollution in China have driven substantial declines in annual NO₂ concentrations, whereas ozone (O₃) concentrations have increased. Based on nationwide NO₂ observations and a regional air quality model (WRF-CMAQ), we analyzed trends in the diurnal difference (DD, the difference between nighttime and daytime concentrations) of NO₂ concentrations across eastern China and in five national urban agglomerations (UAs) from 2014 to 2021, and explored the factors underlying such changes and the potential impacts on O₃ pollution. We found that the observed DD of NO₂ has increased in most cities and UAs, and that this trend can be primarily attributed to changes in anthropogenic emissions, based on comparison with DDs simulated with fixed anthropogenic emissions, which generally showed much weaker trends and little interannual variation. A sensitivity analysis using the WRF-CMAQ model was conducted to investigate the impact of a modified diurnal cycle of nitrogen oxides (NO_x) emissions on O₃ concentrations. The result revealed that enhancing the DD of NO₂ would increase O₃ concentrations in the morning and the daily maximum 8-h O₃ concentrations in the cities with high NO_x concentrations, as well as downwind areas of cities, indicating that greater DDs in NO₂ is one of the reasons that have led to the enhanced China's O₃ pollution in recent years.

Urgency of controlling agricultural nitrogen sources to alleviate summertime air pollution in the North China Plain

Agricultural nitrogen sources (ANS) have played an increasingly important role in the air quality since ANS emission controls are much weaker than those for fossil fuel combustion sources due to the increasing food demand. However, ANS emissions are highly uncertain due to stochastic agricultural management activities and limited field measurements, and impacts of ANS on the air quality remain elusive. In the study, the WRF-Chem model has been used to investigate ANS shares in near surface air pollutant concentrations during a growing season in the North China Plain (NCP), with ANS emissions constrained by satellite retrievals. Soil NOX and agricultural NH3 emissions are about 36% and 92% of their total emissions during the growing season. Sensitivity studies demonstrate that ANS count 16.9 μg m-3 (9.9%) of the mean maximum daily average 8-h ozone concentrations (MDA8 [O3]) and 8.9 μg m-3 (31.7%) of fine particulate matter concentrations ([PM2.5]) on average in the NCP. Additionally, the contributions of ANS to MDA8 [O3] and [PM2.5] increase with the deterioration of air pollution in cities. A 50% emission reduction in ANS decreases MDA8 [O3] ([PM2.5]) from 4.2% to 8.4% (from 19.7% to 31.9%) when the air quality changes from being lightly to heavily polluted in terms of MDA8 [O3] (hourly [PM2.5]). Without fossil fuel combustion emissions, the simulated average MDA8 [O3] and [PM2.5] are 111.7 and 8.2 μg m-3 in cities of the NCP, respectively, exceeding the new standards from the World Health Organization. Our study highlights important contributions of ANS to air quality and the urgency of ANS emission abatement for air pollution alleviation during summertime in the NCP.

Nutrient status regulates MED19a phase separation for ORESARA1-dependent senescence

The mediator complex is highly conserved in eukgaryotes and is integral for transcriptional responses. Mediator subunits associate with signal-responsive transcription factors (TF) to activate expression of specific signal-responsive genes. As the key TF of Arabidopsis thaliana senescence, ORESARA1 (ORE1) is required for nitrogen deficiency (-N) induced senescence; however, the mediator subunit that associates with ORE1 remains unknown. Here, we show that Arabidopsis MED19a associates with ORE1 to activate -N senescence-responsive genes. Disordered MED19a forms inducible nuclear condensates under -N that is regulated by decreasing MED19a lysine acetylation. MED19a carboxyl terminus (cMED19a) harbors a mixed-charged intrinsically disordered region (MC-IDR) required for ORE1 interaction and liquid-liquid phase separation (LLPS). Plant and human cMED19 are sufficient to form heterotypic condensates with ORE1. Human cMED19 MC-IDR, but not yeast cMED19 IDR, partially complements med19a suggesting functional conservation in evolutionarily distant eukaryotes. Phylogenetic analysis of eukaryotic cMED19 revealed that the MC-IDR could arise through convergent evolution. Our result of MED19 MC-IDR suggests that plant MED19 is regulated by phase separation during stress responses.

The relationship between the intensified heat waves and deteriorated summertime ozone pollution in the Beijing-Tianjin-Hebei region, China, during 2013-2017

Summertime ozone (O₃) pollution has frequently occurred in the Beijing-Tianjin-Hebei (BTH) region, China, since 2013, resulting in detrimental impacts on human health and ecosystems. The contribution of weather shifts to O₃ concentration variability owing to climate change remains elusive. By combining regional air chemistry model simulations with near-surface observations, we found that anthropogenic emission changes contributed to approximately 23% of the increase in maximum daily 8-h average O₃ concentrations in the BTH region in June-July-August (JJA) 2017 (compared with that in 2013). With respect to the weather shift influence, the frequencies, durations, and magnitudes of O₃ exceedance were consistent with those of the heat wave events in the BTH region during JJA in 2013-2017. Intensified heat waves are a significant driver for worsening O₃ pollution. In particular, the prolonged duration of heat waves creates consecutive adverse weather conditions that cause O₃ accumulation and severe O₃ pollution. Our results suggest that the variability in extreme summer heat is closely related to the occurrence of high O₃ concentrations, which is a significant driver of deteriorating O₃ pollution.

Elucidating Contributions of Anthropogenic Volatile Organic Compounds and Particulate Matter to Ozone Trends over China

In China, emissions of ozone (O₃)-producing pollutants have been targeted for mitigation to reduce O₃ pollution. However, the observed O₃ decrease is slower than/opposite to expectations affecting the health of millions of people. For a better understanding of this failure and its connection with anthropogenic emissions, we quantify the summer O₃ trends that would have occurred had the weather stayed constant by applying a numerical tool that "de-weathers" observations across 31 urban regions (123 cities and 392 sites) over 8 years. O₃ trends are significant (p < 0.05) over 234 sites after de-weathering, contrary to the directly observed trends (only 39 significant due to high meteorology-induced variability). The de-weathered data allow categorizing cities in China into four different groups regarding O₃ mitigation, with group 1 exhibiting steady O₃ reductions, while group 4 showing significant (p < 0.05) O₃ increases. Analysis of the relationships between de-weathered odd oxygen and nitrogen oxides illustrates how the changes in NO_x, in anthropogenic volatile organic compounds (VOCs), and reductions in fine particulate matter (PM_2.5) affect the O₃ trends differently in these groups. While this analysis suggests that VOC reductions are the main driver of O₃ decreases in group 1, groups 3 and 4 are primarily affected by decreasing PM_2.5, which results in enhanced O₃ formation. Our analysis demonstrates both the importance of and possibility for isolating emission-driven changes from climate and weather for interpreting short-term air quality observations.

Assessment of background ozone concentrations in China and implications for using region-specific volatile organic compounds emission abatement to mitigate air pollution

Mitigation of ambient ozone (O₃) pollution is a great challenge because it depends heavily on the background O₃ which has been poorly evaluated in many regions, including in China. By establishing the relationship between O₃ and air temperature near the surface, the mean background O₃ mixing ratios in the clean and polluted seasons were determined to be 35-40 and 50-55 ppbv in China during 2013-2019, respectively. Simulations using the chemical transport model (i.e., the Weather Research and Forecasting coupled with Chemistry model, WRF/Chem) suggested that biogenic volatile organic compounds (VOC) emissions were the primary contributor to the increase in the background O₃ in the polluted season (BOP) compared to the background O₃ in the clean season (BOC), ranging from 8 ppbv to 16 ppbv. More importantly, the BOP continuously increased at a rate of 0.6-8.0 ppbv yr^-1 during 2013-2019, while the non-BOP stopped increasing after 2017. Consequently, an additional 2%-16% reduction in anthropogenic VOC emissions is required to reverse the current O₃ back to that measured in the period from 2013 to 2017. The results of this study emphasize the importance of the relative contribution of the background O₃ to the observed total O₃ concentration in the design of anthropogenic precursor emission control strategies for the attainment of O₃ standards.

Hourly Seamless Surface O3 Estimates by Integrating the Chemical Transport and Machine Learning Models in the Beijing-Tianjin-Hebei Region

Surface ozone (O3) is an important atmospheric trace gas, posing an enormous threat to ecological security and human health. Currently, the core objective of air pollution control in China is to realize the joint treatment of fine particulate matter (PM2.5) and O3. However, high-accuracy near-surface O3 maps remain lacking. Therefore, we established a new model to determine the full-coverage hourly O3 concentration with the WRF-Chem and random forest (RF) models combined with anthropogenic emission data and meteorological datasets. Based on this method, choosing the Beijing-Tianjin-Hebei (BTH) region in 2018 as an example, full-coverage hourly O3 maps were generated at a horizontal resolution of 9 km. The performance evaluation results indicated that the new model is reliable with a sample (station)-based 10-fold cross-validation (10-CV) R2 value of 0.94 (0.90) and root mean square error (RMSE) of 14.58 (19.18) µg m−3. In addition, the estimated O3 concentration is accurately determined at varying temporal scales with sample-based 10-CV R2 values of 0.96, 0.98 and 0.98 at the daily, monthly, and seasonal scales, respectively, which is highly superior to traditional derivation algorithms and other techniques in previous studies. An initial increase and subsequent decrease, which constitute the diurnal variation in the O3 concentration associated with temperature and solar radiation variations, were captured. The highest concentration reached approximately 112.73 ± 9.65 μg m−3 at 15:00 local time (1500 LT) in the BTH region. Summertime O3 posed a high pollution risk across the whole BTH region, especially in southern cities, and the pollution duration accounted for more than 50% of the summer season. Additionally, 43 and two days exhibited light and moderate O3 pollution, respectively, across the BTH region in 2018. Overall, the new method can be beneficial for near-surface O3 estimation with a high spatiotemporal resolution, which can be valuable for research in related fields.

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO_x), ammonia (NH₃), and nitrous oxide (N₂O). The propensity of NO_x and NH₃ to generate ozone and fine particulate matter and associated impacts on health are highly variable, whereas the climate impacts of long-lived N₂O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially resolved monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the Nr emissions from fertilized soils across the contiguous United States. We then apply a reduced-form air pollution health effect model to assess air quality impacts from NO_x and NH₃ and a social cost of N₂O to assess the climate impacts. Assuming an $8.2 million value of a statistical life and a $13,100/ton social cost of N₂O, the air quality impacts are a factor of ∼7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

Synergistic effects of biogenic volatile organic compounds and soil nitric oxide emissions on summertime ozone formation in China

Natural emissions play a key role in modulating the formation of ground-level ozone (O₃), especially emissions of biogenic volatile organic compounds (BVOCs) and soil nitric oxide (SNO), and their individual effects on O₃ formation have been previously quantified and evaluated. However, their synergistic effects remain unclear and have not yet been well assessed. By applying the Weather Research and Forecasting (WRF) model coupled with the Chemistry-Model of Emissions of Gases and Aerosols from Nature (WRF/Chem-MEGAN) model, this study reveals that in the presence of sufficient BVOC emissions, which act as a fuel, SNO emissions act as a fuel additive and promote the chemical reactions of BVOCs and the subsequent production of O₃. Consequently, the synergistic effects of BVOC and SNO emissions on summertime O₃ production surpassed the sum of their individual effects by as much as 10-20 μg m^-3 in eastern China in 2014. In order to reduce O₃ concentration to a level corresponding to no natural emissions of BVOC or SNO (i.e., the BASE scenario), the anthropogenic volatile organic compound (AVOC) emissions in the scenario considers BVOC and SNO emissions must be reduced by 1.76 times that of the BASE scenario. This study demonstrates that the synergistic effects of BVOC and SNO emissions can impede ground-level O₃ regulation and can subsequently impose stricter requirements on anthropogenic precursor emission control in China. The results of this study can also inform efforts in other regions that are still combating ground-level O₃ pollution.

A landscape review of controlled release urea products: Patent objective, formulation and technology

Fertiliser has been a vital part of agriculture due to it boosting crop productivity and preventing starvation throughout the world. Despite this huge contribution, the application of nitrogen (N) fertilisers results in N leaching and the formation of greenhouse gases, which threaten the environment and human health. To minimise the impacts, slow/controlled release fertilisers (S/CRFs) have been being developed since the beginning of the 20th century. Despite the efforts made over a century, the basic terminological and classification information of these fertilisers remains vague. The scientific knowledge published in S/CRF patents has also been overlooked since the beginning. This review focused on the information gaps, clarified the definitions, differentiation and classification methods that have been randomly used in previous literature. The objectives, formulations and technologies of 109 controlled release urea patents involving sulphur coated urea, polymer coated urea and urea matrix fertilisers published in the years since these products emerged were also reviewed to 1) highlight the overlooked scientific knowledge in the patents; 2) understand the evolutionary processes and current research states of the products; 3) clarify research preferences and challenges to date; 4) identify remaining gaps for the future direction. It is expected that the organised basic information and the patent knowledge highlighted in this paper can be new resources and foster the development of S/CRFs in the future.

A New Framework of Green Transition of Cultivated Land-Use for the Coordination among the Water-Land-Food-Carbon Nexus in China

As a fundamental solution to the ecological problems of resources and environment, the Green Transition of Cultivated Land-use (GTCL) has become an inherent requirement for promoting ecological progress and implementing the food security strategy in the new era. This paper proposed a theoretical framework of GTCL and constructed a GTCL development index system based on four aspects: water, land, food and carbon; then, by applying a comprehensive evaluation model, a coupling coordination model and exploratory spatial data analysis, the development level of GTCL in China’s 31 provinces, municipalities and autonomous regions in 2000, 2005, 2010, 2015 and 2020 was evaluated and the spatial and temporal rates of change of “water, land, food and carbon” (WLFC) and their coupling coordination were finally analyzed to reveal the “water, land, food and carbon” effect of GTCL. Results showed that the systemic changes of WLFC and its coupling coordination degree of GTCL presented a spatial and temporal coincidence with a high degree of consistency; from 2000 to 2020, the overall GTCL rate in all Chinese provinces, municipalities and autonomous regions showed a “W”-shaped fluctuation uptrend. In the past five years, the development level of GTCL was higher in Northeast China, followed by Central China and North China, while South China was at a low level. In addition, WLFC showed a more obvious “W”-shaped fluctuation, with higher coupling coordination in Northeast China in good coordination and lower coordination in East China and Southwest China. Therefore, according to the results of the study, areas were divided into: benefit leading area, quality improvement area, connotation tapping potential area, ductile development area and ecological reserve area for the regulation of GTCL in all Chinese provinces, municipalities and autonomous regions.

New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China

Ozone (O3), whose concentrations have been increasing in eastern China recently, plays a key role in human health, biodiversity, and climate change. Accurate information about the spatiotemporal distribution of O3 is crucial for human exposure studies. We developed a deep learning model based on a long short-term memory (LSTM) network to estimate the daily maximum 8 h average (MDA8) O3 across eastern China in 2020. The proposed model combines LSTM with an attentional mechanism and residual connection structure. The model employed total O3 column product from the Tropospheric Monitoring Instrument, meteorological data, and other covariates as inputs. Then, the estimates from our model were compared with real observations of the China air quality monitoring network. The results indicated that our model performed better than other traditional models, such as the random forest model and deep neural network. The sample-based cross-validation R2 and RMSE of our model were 0.94 and 10.64 μg m−3, respectively. Based on the O3 distribution over eastern China derived from the model, we found that people in this region suffered from excessive O3 exposure. Approximately 81% of the population in eastern China was exposed to MDA8 O3 > 100 μg m−3 for more than 150 days in 2020.

Atmospheric Pollution of Agriculture-Dominated Cities

With rapid development of modern agriculture, a multitude and a large amount of air pollutants were generated by agricultural activities, which are becoming more and more serious issues with regards to air pollution [...]

Characterizing the distinct modulation of future emissions on summer ozone concentrations between urban and rural areas over China

Previous studies on ozone pollution primarily focus on the characterization of ozone on a large regional scale, yet much less attention has been paid towards the contrast between urban and surrounding suburban-rural areas. As anthropogenic emissions are projected to decrease in the coming decades, the evolutions of ozone concentrations over urban and suburban-rural areas are compared using the Community Multiscale Air Quality (CMAQ) model coupled with the Weather Research and Forecasting (WRF). The top 25 city clusters are firstly identified across China based on the amount of NO_x emissions and population size. At present, the averages of maximum daily 8-h (MDA8) ozone concentrations over the suburban-rural areas (65.74 ppbv) among these city clusters are higher than the corresponding urban areas (62.00 ppbv). The projections in 2050s depend on the scenarios. Under the Shared Socioeconomic Pathways (SSPs) scenarios such as SSP1-2.6, SSP2-4.5 and SSP5-8.5 indicative of primary decreases in anthropogenic emissions, the mean MDA8 ozone concentrations in suburban-rural areas decrease more than urban areas. In contrast, the gap of higher MDA8 ozone concentrations in suburban-rural than urban areas increases under SSP3-7.0 concomitant with increase in anthropogenic emissions. The strongest response to emission changes is found in SSP1-2.6, in which anthropogenic emission reduction leads to lower MDA8 ozone concentrations in the suburban-rural than urban areas, reversing the present state of higher ozone concentrations in the suburban-rural areas. The feature abovementioned regarding changes of mean MDA8 ozone concentrations is largely reproduced in the response of ozone exceedance. The finding highlights different efficacies of anthropogenic emissions in urban from suburban-rural areas. In a region like China where the population density is much higher in urban than suburban-rural regions, the benefit of ozone reduction due to large emission reductions (e.g., SSP1-2.6) is diminished to some extent because the effect is larger in suburban-rural areas.

Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges

Microbial communities are ubiquitous and carry an exceptionally broad metabolic capability. Upon environmental perturbation, microbes are also amongst the first natural responsive elements with perturbation-specific cues and markers. These communities are thereby uniquely positioned to inform on the status of environmental conditions. The advent of microbial omics has led to an unprecedented volume of complex microbiological data sets. Importantly, these data sets are rich in biological information with potential for predictive environmental classification and forecasting. However, the patterns in this information are often hidden amongst the inherent complexity of the data. There has been a continued rise in the development and adoption of machine learning (ML) and deep learning architectures for solving research challenges of this sort. Indeed, the interface between molecular microbial ecology and artificial intelligence (AI) appears to show considerable potential for significantly advancing environmental monitoring and management practices through their application. Here, we provide a primer for ML, highlight the notion of retaining biological sample information for supervised ML, discuss workflow considerations, and review the state of the art of the exciting, yet nascent, interdisciplinary field of ML-driven microbial ecology. Current limitations in this sphere of research are also addressed to frame a forward-looking perspective toward the realization of what we anticipate will become a pivotal toolkit for addressing environmental monitoring and management challenges in the years ahead.

Temporal variations of soil NO and NO2 fluxes in two typical subtropical forests receiving contrasting rates of N deposition

Soils have been widely acknowledged as important natural sources of nitric oxide (NO) and meanwhile sinks of nitric dioxide (NO₂). High nitrogen deposition across South China could potentially result in large NO emissions from subtropical forests soils there. In this study, the dynamic chamber method was applied to monitor NO and NO₂ fluxes at two subtropical forest sites in South China, namely "Qianyanzhou" (QYZ) and "Tieshanping" (TSP). Chronically higher N deposition occurred at TSP than that at QYZ. Besides soil water filled pore spaces (WFPS) and temperature, ambient NO concentration could also possibly be important in regulating temporal NO emissions, especially in the winter. For both sites, the optimum soil temperature was above 25 °C, while the optimum WFPS for NO release at QYZ was higher (65-70%) than that at TSP (<23%). Moreover, heavy rainfall could trigger NO emission pulses from moist soils at QYZ, while rainfall-induced NO pulses were only observed after a long drying period at TSP. Distinctly different contents of mineral nitrogen and soil moisture conditions between the two sites might induce the divergent preference of WFPS and responses to rainfall. The cumulative soil emission of NO reached 0.41 ± 0.01 and 0.76 ± 0.01 kg N ha^-1 yr^-1 at QYZ and TSP, contributing to 2.5% and 1.4% of the annual throughfall N input, respectively. At both sites, NO₂ were mainly deposited to soils, accounting for 2% and 21% of soil-emitted NO at QYZ and TSP, respectively. The observed annual NO emissions at these two sites were larger than the median values observed for tropical and temperate forests and unfertilized croplands. Higher N deposition could induce larger NO emission potential, while soil temperature and pH might also be important in regulating regional soil NO emissions as N-loss from subtropical forests.

Cropland nitrogen dioxide emissions and effects on the ozone pollution in the North China plain

Soil nitrogen dioxide (NO_X = NO₂ + NO) emissions have been measured and estimated to be the second most significant contributor to the NO_X burden following the fossil fuel combustion source globally. NO_X emissions from croplands are subject to being underestimated or overlooked in air pollution simulations of regional atmospheric chemistry models. With constraints of ground and space observations of NO₂, the WRF-Chem model is used to investigate the cropland NO_X emission and its contribution to the near-surface ozone (O₃) pollution in North China Plain (NCP) during a growing season as a case study. Model simulations have revealed that the cropland NO_X emissions are underestimated by around 80% without constraints of satellite measured NO₂ column densities. The biogenic NO_X source is estimated to account for half of the anthropogenic NO_X emissions in the NCP during the growing season. Additionally, the cropland NO_X source contributes around 5.0% of the maximum daily average 8h O₃ concentration and 27.7% of NO₂ concentration in the NCP. Our results suggest the agriculture NO_X emission exerts non-negligible impacts on the summertime air quality and needs to be considered when designing emission abatement strategies.

Optimization of a NOx and VOC Cooperative Control Strategy Based on Clean Air Benefits

Serious ambient PM_2.5 and O₃ pollution is one of the most important environmental challenges of China, necessitating an urgent cost-effective cocontrol strategy. Herein, we introduced a novel integrated assessment system to optimize a NO_x and volatile organic compound (VOC) control strategy for the synergistic reduction of ambient PM_2.5 and O₃ pollution. Focusing on the Beijing-Tianjin-Hebei cities and their surrounding regions, which are experiencing the most serious PM_2.5 and O₃ pollution in China, we found that NO_x emission reduction (64-81%) is essential to attain the air quality standard no matter how much VOC emission is reduced. However, the synergistic VOC control is strongly recommended considering its substantially human health and crop production benefits, which are estimated up to 163 (PM_2.5-related) and 101 (O₃-related) billion CHY during the reduction of considerable emissions. Notably, such benefits will be greatly reduced if the synergistic VOC reduction is delayed. This study also highlights the necessity of simultaneous VOC and NO_x emission control in winter while enhancing the NO_x control in the summer, which is contrary to the current control strategy adopted in China. These findings point out the right pathways for future policy making on comitigating PM_2.5 and O₃ pollution in China and other countries.

Trends and Variability of Ozone Pollution over the Mountain-Basin Areas in Sichuan Province during 2013–2020: Synoptic Impacts and Formation Regimes

Sichuan Province, the most industrialized and populated region in southwestern China, has been experiencing severe ozone pollution in the boreal warm season (April–September). With a surface ozone monitoring network and reanalysis dataset, we find that nearly all cities in Sichuan Province showed positive increasing trends in the warm-season ozone levels. The warm-season daily maximum 8-h average (MDA8) ozone levels increased by 2.0 ppb (4.8%) year−1 as a whole, with slightly larger trends in some sites such as a site in Zigong (5.2 ppb year−1). Seasonally, the monthly ozone level in Sichuan peaks from May to August (varies with year). The predominant warm-season synoptic patterns were objectively identified based on concurrent hourly meteorological fields from ERA5. High-pressure systems promote ozone production and result in high ozone concentrations, due to strong solar radiation as well as hot and dry atmospheric conditions. The increased occurrence of high-pressure patterns probably drives the ozone increase in Sichuan. When ozone pollution is relatively weak (with MDA8 ozone around 170 μg m−3), the air quality standard could be achieved in the short term by a 25% reduction of NOx and VOCs emissions. Strengthened emission control is needed when ozone pollution is more severe. Our study provides implications for effective emission control of ozone pollution in Sichuan.