High Concentrations Of NO Research Articles

First evaluation of the GEMS glyoxal products against TROPOMI and ground-based measurements

Abstract. The Geostationary Environment Monitoring Spectrometer (GEMS) on board the GEO-KOMPSAT-2B satellite is the first geostationary satellite launched to monitor the environment. GEMS conducts hourly measurements during the day over eastern and southeastern Asia. This work presents glyoxal (CHOCHO) vertical column densities (VCDs) retrieved from GEMS, with optimal settings for glyoxal retrieval based on sensitivity tests involving reference spectrum sampling and fitting window selection. We evaluated GEMS glyoxal VCDs by comparing them to the TROPOspheric Monitoring Instrument (TROPOMI) and multi-axis differential optical absorption spectroscopy (MAX-DOAS) ground-based observations. On average, GEMS and TROPOMI VCDs show a spatial correlation coefficient of 0.63, increasing to 0.87 for northeastern Asia. While GEMS and TROPOMI demonstrate similar monthly variations in the Indochinese Peninsula regions (R > 0.67), variations differ in other areas. Specifically, GEMS VCDs are higher in the winter and either lower or comparable to TROPOMI and MAX-DOAS VCDs in the summer across northeastern Asia. We attributed the discrepancies in the monthly variation to a polluted reference spectrum and high NO2 concentrations. When we correct GEMS glyoxal VCDs as a function of NO2 SCDs, the monthly correlation coefficients substantially increase from 0.16–0.40 to 0.45–0.72 in high NO2 regions. When averaged hourly, GEMS and MAX-DOAS VCDs exhibit similar diurnal variations, especially at stations in Japan (Chiba, Kasuga, and Fukue).

Evaluating the Spatio-Temporal Distribution of Nitrogen Dioxide, Land Surface Temperature and NDVI in Nairobi City County

Abstract. Cities are becoming larger and it is estimated that by the year 2050, more than 6 billion people will be living in cities. As cities expand and grow, the quality of life and conditions will also transform. An integral part of environmental studies has been statistical analysis in modelling the spatial dynamics of land use changes. The research involved the use of satellite imagery to determine yearly averaged values of LST and NDVI from Landsat 8 OLI/TIR and monthly mean values of Nitrogen Dioxide (NO2) from Sentinel 5-Precursor (Sentinel-5P) across Nairobi City County. The datasets covered the period 2019, 2020, 2021, 2022 and 2023 and were analysed in Google Earth Engine. Results indicated that the yearly mean values in NO2 and LST in 2020 reduced by 2% and 12% respectively from 2019, while the mean NDVI value significantly increased by 28% in 2020 from 2019. NO2 has a negative correlation with LST in all years and a positive correlation with NDVI. Pearson correlation with population densities in constituencies in Nairobi in 2019 and 2023 indicate a negative correlation with NDVI and a positive correlation with NO2 and LST. Constituencies that have higher population densities tend to have lower vegetation densities and higher NO2 concentrations and temperature. Vegetation therefore plays a crucial role in air quality and that climatic factors such as precipitation and temperature influence the concentration of pollutants.

Assessment of exurban expansion on water quality in Rock Creek of the Yellowstone River in southcentral Montana, USA

Exurban expansion can degrade significantly stream water quality. This study was conducted on Rock Creek of the Clark’s Fork of the Yellowstone River in southcentral Montana, USA. The impact from recent exurban expansion was evaluated by a baseline study measuring total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and nitrites (NO2) and nitrates (NO3) together. This was part of a larger study by Montana Department of Environmental Quality to assess water quality, identify sources of pollution and develop total maximum daily loads (TMDL). Water samples were measured for these analytes at nine (2022) and 11 (2023) locations with different land-uses over seven periods (both years). Seasonal spikes, corresponding to runoff (2022, late May), occurred in TSS, TP and TN. Data from 2023 showed similar but reduced levels occurring in June for TSS and TP. Total suspended solids, TP, NO2 and NO3 concentrations increased by location year over year, 2022 to 2023. The high relative concentrations of NO2 and NO3 in Rock Creek are primarily associated with exurban expansion, a significant threat to stream quality and wildlife habitat in Montana. The results will assist county planners in land use decisions.

IPCC Emission Factor Overestimates N2O Emissions from Agricultural Ditches.

Agricultural ditches emit disproportionate amounts of nitrous oxide (N2O), but their contributions to regional or global N2O emissions remain unclear due to limited data. The Intergovernmental Panel on Climate Change (IPCC) recommends using emission factors (EFs) to estimate indirect N2O emission, but the EF for ditches (EF5g) is categorized as groundwater, which potentially introduces a significant bias. This study conducted a regional-scale campaign in the North China Plain, one of the world's most intensive agricultural regions, and calculated the EF5g values from agricultural ditches by the concentration method (N2O-N/NO3--N). The results found that the regional-scale mean EF5g value (0.0028) was less than half of the IPCC default value (0.006), illustrating that the current IPCC methodology significantly overestimates N2O emissions from agricultural ditches. Despite the relatively small EF5g values, agricultural ditches exhibited a high mean N2O concentration (3.36 μg L-1) and a large regional emission (1.14 ± 0.86 Gg N2O-N yr-1), which is equal to 3.8 ± 2.9% of direct N2O emission from the croplands in the North China Plain. Since ditches are ubiquitous in agricultural regions and are likely to expand under climate change, refining EF5g is crucial to accurately assess their contribution to global N2O budgets.

Hybrid system for nitric oxide and hydrogen production

The device for nitric oxide inhalation therapy TIANOX has been put into use in clinical practice. It produces NO in nonequilibrium plasma of a diffusive spark discharge in the air at atmospheric pressure. There is a tendency to use a therapeutic gas mixture with high NO concentration for inhalation in the developing medical treatment methods. Nitric oxide transition into active compounds such as nitric dioxide, peroxynitrite, and nitrotyrosine can lead to oxidative stress. The use of hydrogen as an antioxidant that decreases the levels of hydroxyl radicals and peroxynitrite can protect cells from oxidative damage. Positive effect of the nitric oxide mixture and hydrogen is shown in the experiments with animals.The aim of the article is to describe development and performance the first hybrid system producing nitric oxide and hydrogen that was created in Federal State Unitary Enterprise “Russian Federal Nuclear Center – All-Russian Research Institute of Experimental Physics”. The system is based on the plasmochemical generator Tianox and the hydrogen generator, which is based on the electrolyzer with a solid polymeric electrolyte. It is fitted with H2, NO, and NO2 monitor and provides a continuous monitoring of concentrations of these gases and helps ensure safety of medical procedures by disconnecting NO and H2 generators at the moment when the gas concentrations exceed maximum levels (H2max, NOmax, NO2max).Conclusion. This hybrid system for nitrogen and hydrogen production passed the first study in human successfully. The preclinical studies also demonstrated its efficacy and safety.

Daily NO2 Simulation Research Based on Automatic Machine Learning Ensemble Models

To understand the spatial distribution of NO2 near the surface, we utilized measured data from NO2 monitoring stations and combined it with column concentration data from the Tropospheric Monitoring Instrument （TROPOMI）, taking the Yangtze River Delta region as the study area. We considered the impact of factors such as population, elevation, and meteorological conditions on NO2 levels. We used automated machine learning to select five machine-learning algorithms with high simulation accuracy, namely ET, RF, XGBoost, LightGBM, and Catboost, and then integrated these five algorithms using the Stacking model to simulate the daily NO2 concentration in the Yangtze River Delta region from March 2020 to February 2021. The results indicated that the RMAE and MAE values of the Stacking ensemble model were 7.078 and 5.270, respectively, which outperformed the single algorithms of ET, RF, XGBoost, LightGBM, and Catboost. The spatial distribution of high NO2 concentrations in the Yangtze River Delta region, consisting of three provinces and one municipality, exhibited a U-shaped pattern with the convergence point located at the intersection of the three provinces, extending towards the southwest. Notably, urban pollution was particularly significant in the urban agglomerations centered around Shanghai, Hangzhou, Nanjing, and Hefei. There were 27 cities that exceeded the national standard daily limit. Changzhou was the city with the most serious NO2 pollution, with the NO2 concentration exceeding the standard for 14 d, followed by Shanghai, with 13 d. In terms of seasonal variation, the order of severity was as follows： winter, autumn, spring, and summer, with the least NO2 pollution occurring on July 9th during the summer, and the most severe NO2 pollution was observed on December 23rd during the winter.

Visualizing Convergent Pressures on Arctic Development

A rapidly changing Arctic has impacted biophysical and human systems while creating new economic opportunities. Spatially identifying locations with development potential in this changing environment requires characterizing convergences in critical enabling/constraining factors occurring in a particular place. However, mapping techniques based on simple overlays of spatially heterogeneous data may result in visual clutter, compromising legibility, and increasing the likelihood of interpretation errors. To overcome these limitations, we introduce Pythia, a tool that combines geographic statistical analysis with a subtractive color model to enable bi- or tri-variate data analysis. Three case studies showcase this visualization tool. Case study 1 identifies locations where temperature and population are projected to increase by 2040. Case study 2 reveals locations with a significant presence of major roads and high NO2 concentrations but few hospitals and clinics. In case study 3, a combination of transportation infrastructure, protected areas, and travel and tourism infrastructure signals challenges for the future Alaskan tourism industry. Comparing these results allows for further geographic characterization of locations, aiding policymakers in identifying areas lacking resources and infrastructure, exploring possible futures, and supporting long-term strategic planning.

Exposure to tropospheric ozone and NO2 in the ambient air of Tehran metropolis: Spatiotemporal distribution and inhalation health risk assessment

BackgroundAir pollution has emerged as a critical challenge in the 21st century, necessitating alert monitoring of key pollutants such as ozone and nitrogen dioxide (NO2)F. These pollutants are exacerbated by urbanization and industrialization, posing significant health risks, particularly in densely populated metropolitan areas. ObjectiveThe aim of this study was inhalation health risk assessment of NO2 and ozone in various scenarios and spatiotemporal Distribution Interpolation. MethodsData were collected from the Tehran Air Quality Control Center, encompassing 18 monitoring stations from March 2019 to February 2022. Health risk assessments (HRA) were performed for adult age groups across three different exposure scenarios (3, 8, and 12 h) And a sensitivity analysis was also conducted to determine the relative importance of each parameter in assessing the risks of each scenario. ResultsThe hazard index (HI) values for NO2 and ozone in all three scenarios were found to range from 0.24 to 1.56 and 0.04 to 0.49, respectively and body weight is a risk-lowering factor in sensitivity analyses. The interpolation results of ozone, NOx, and NO2 using the IDW approach from March 2019 to February 2022 showed that overall, the north and northeast of Tehran had the highest concentrations of NO2 and NOx, and the north and west had the highest concentrations of ozone. SignificanceThis study underscores the HRA with exposure to NO2 and ozone, particularly for individuals spending more than 8 h outdoors. Given Tehran's high population density and persistent air pollution, it is imperative to implement effective control policies to safeguard public health. The findings advocate for limiting outdoor activity to less than 8 h per day, especially for vulnerable occupational groups. Additionally, the study highlights the importance of considering body weight in health risk assessments.

-temporal variability in fire events due to crop residue burning and their impact on atmospheric variables using ground and remote sensingdata in Punjab

We attempted monitoring and mapping of the active fire events in Punjab, during the wheat and rice harvesting period of 2017-2021 from the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375 m aboard. The analysis showed that the highest fire counts were observed in the central region, followed by the south-west and thelowest in the north-east region of Punjab during all the years. Moreover, during the wheat season, highest fire counts were observed in 2019, being 2535, 11062 and 6212 in north-east, central and south-west regions, respectively. However, during rice, highest fire counts were observed in 2020 in the north-east being 2857 and in 2021 the central and south-west regions being 40960 and 30351 respectively. In line with the number of fire counts, the highest concentration of gases and particulate matter obtained from the Central Pollution Control Board (CPCB) was also observed in the central zone. During the wheat harvesting season, central zone experienced the highest concentration of PM2.5 and PM10 in May 2018 and that of SO2 and O3 in May 2019. Similarly, during the rice harvesting season, central zone also experienced the highest concentration of PM2.5 and PM10 during November 2017 and that of SO2 in 2018. However, the highest concentration of NO2 was observed in October 2018 and that of O3 in October 2020 in the central region. Analysis of the concentration of NO2 and SO2 obtained from the Soumi-NPP satellite also had similar results to CPCB. Such a high concentration of gases and particulate matter might be attributed to crop residue burning a significant positive correlation was observed between fire counts and concentration of particulate matter (PM2.5 and PM10). In view of the alarming deterioration of air quality, there is a dire need to check this practice in the region by providing incentives and viable alternatives to the farmers.

Air pollution is associated with persistent peanut allergy in the first 10 years.

The role of air pollution in eczema and food allergy development remains understudied. We aimed to assess whether exposure to air pollution is associated with eczema and food allergies in the first 10 years of life. HealthNuts recruited a population-based sample of 1-year-old infants who were followed up at ages 4, 6, and 10 years. Annual average fine particulate matter (particulate matter with diameter of 2.5 μm or less, or PM2.5) and nitrogen dioxide (NO2) exposures were assigned to geocoded residential addresses. Eczema was defined by parent report. Oral food challenges to peanut, egg, and sesame were used to measure food allergy. Multilevel logistic regression models were fitted, and estimates were reported as adjusted odds ratios. Those exposed to high concentration of NO2 (<10 ppb) at age 1 year had higher peanut allergy prevalence at ages 1 (adjusted odds ratio [95% confidence interval], 2.21 [1.40-3.48]) and 4 (2.29 [1.28-4.11]) years. High exposure to NO2 at 6 years old were associated with higher peanut allergy prevalence at age 6 (1.34 [1.00-1.82] per 2.7 ppb NO2 increase) years. Similarly, increased PM2.5 at age 1 year was associated with peanut allergy at ages 4, 6, and 10 years (respectively, 1.27 [1.01-1.60], 1.27 [1.01-1.56], and 1.46 [1.05-2.04] per 1.2 μg/m PM2.5 increase) years. We found that increased concentrations of NO2 or PM2.5 at age 1 year were associated with persistent peanut allergy at later ages. Little evidence of associations was observed with eczema or with egg allergy. Early-life exposure to PM2.5 and NO2 was associated with peanut allergy prevalence and persistence. Policies aiming at reducing air pollution could potentially reduce presence and persistence of peanut allergy.

Numerical study on the effect of injection strategy on combustion and NO emission from different sources in a diesel/ammonia RCCI engine

Diesel/ammonia operation is one of the ways to efficiently utilize ammonia and reduce carbon emissions, however, the increase in fuel NO introduces serious emission problems. To explore the generation mechanisms of fuel NO and oxidant source NO, a multi-component diesel/ammonia chemical reaction mechanism was constructed in this study, and based on 3D CFD simulation and N-element tracking method, the combustion and different source NO emission characteristics of diesel/ammonia reactivity controlled compression ignition (RCCI) engine at low loads were investigated by pilot injection timing (SOI1) and pilot injection ratio (PIR). In addition, the effect of different first injection spray angle (SA1) and double injection spray angle (SAtotal) on the engine operation was investigated. The results showed that high PIR and delayed SOI1 enhanced the engine IMEP but led to high PRRmax. At a PIR of 15 %, total NO emissions increased as SOI1 advanced, and the trend was reversed when the PIR was higher than 15 %. Fuel NO was produced earlier than the oxidant source N∗O. In terms of 1 spatial distribution, high concentrations of both NO and N∗O were distributed in and around the secondary diesel fuel ignition location, and fuel NO began to be reduced where the oxidant source N∗O was rapidly formed. The reduction mechanism of NO in the cylinder was a multi-path reduction mechanism incorporating Thermal DeNOx, NO Reburning, and inverse reaction pathways for NO formation from the oxidant source. Appropriate reduction of the SAtotal can significantly reduce the total NO emission while maintaining no significant reduction in IMEP. When SAtotal was 82°, the total NO emission was only 16.3 % of the original spray angle and PRRmax was further reduced. After optimization, when a narrow SAtotal of 82°, SOI1 of −15° CA, and PIR of 35 % were used, the IMEP of the engine increased by 5.9 %, and the total NO emission was reduced by 86 %, while PRRmax did not exceed the PRR upper limit.

PM2.5 estimation and its relationship with NO2 and SO2 in China from 2016 to 2020

ABSTRACT The distribution of surface particulate matter (PM2.5) exhibits significant spatiotemporal patterns, especially with a spatial clustering effect. Therefore, resolving spatial characteristics is essential in the modeling process. This study proposes a space–time varying coefficients (STVC-LG) model by considering spatial effects from the perspective of eigenvector spatial filtering and incorporating spatial effects and temporal features into the LightGBM model to estimate ground PM2.5. A site-based cross-validation result of the estimated daily 1 km PM2.5 concentration in China from 2016 to 2020 shows that the proposed model offers high accuracy, an R2 of 0.88, and an RMSE of 12.21 μg/m3 (17% and 32% enhanced compared to the original LightGBM model). It uses a series of spatial eigenvectors to describe different spatial patterns. It then constructs spatial interaction terms by combining the eigenvectors and influencing variables, allowing the values of the variable to vary spatially with the eigenvectors. The obtained PM2.5, with a decreasing trend, had a clear distributional consistency with NO2 and SO2 according to the co-occurrence distribution maps, particularly in winter. In areas where high concentrations co-occur, both NO2 and SO2 concentrations are Granger-causing PM2.5 concentrations from a statistical perspective.

Nitrate, Nitrite, and Iodine Concentrations in Commercial Edible Algae: An Observational Study.

Edible algae are a natural source of nutrients, including iodine, and can also contain nitrogen in the form of nitrate (NO3-) and nitrite (NO2-) as they can fix nitrogen from seawater. This study aimed to analyse the NO3-, NO2-, and iodine concentrations in eighteen macroalgae and five microalgae species commercially available in the United Kingdom. NO3- and NO2- concentrations were measured using high-performance liquid chromatography (HPLC), and iodine was determined using inductively coupled plasma mass spectrometry (ICP-MS). NO3- and iodine concentrations in macroalgae (NO3-: 4050.13 ± 1925.01 mg/kg; iodine: 1925.01 ± 1455.80 mg/kg) were significantly higher than in microalgae species (NO3-: 55.73 ± 93.69 mg/kg; iodine: 17.61 ± 34.87 mg/kg; p < 0.001 for both). In the macroalgae group, nori had the highest NO3- (17,191.33 ± 980.89 mg/kg) and NO2- (3.64 ± 2.38 mg/kg) content, as well as the highest iodine content. Among microalgae, Dunaliella salina had the highest concentration of NO3- (223.00 ± 21.93 mg/kg) and iodine (79.97 ± 0.76 mg/kg), while Spirulina had the highest concentration of NO2- (7.02 ± 0.13 mg/kg). These results indicate that commercially available edible algae, particularly macroalgae species, could be a relevant dietary source of NO3- and iodine.

A Comparison of Regression Methods for Inferring Near‐Surface NO2 With Satellite Data

AbstractNitrogen dioxide (NO2) is an atmospheric pollutant emitted from anthropogenic and natural sources. Human exposure to high NO2 concentrations causes cardiovascular and respiratory illnesses. The Environmental Protection Agency operates ground monitors across the U.S. which take hourly measurements of NO2 concentrations, providing precise measurements for assessing human pollution exposure but with sparse spatial distribution. Satellite‐based instruments capture NO2 amounts through the atmospheric column with global coverage at regular spatial resolution, but do not directly measure surface NO2. This study compares regression methods using satellite NO2 data from the TROPospheric Ozone Monitoring Instrument (TROPOMI) to estimate annual surface NO2 concentrations in varying geographic and land use settings across the continental U.S. We then apply the best‐performing regression models to estimate surface NO2 at 0.01° by 0.01° resolution, and we term this estimate as quasi‐NO2 (qNO2). qNO2 agrees best with measurements at suburban sites (cross‐validation (CV) R2 = 0.72) and away from major roads (CV R2 = 0.75). Among U.S. regions, qNO2 agrees best with measurements in the Midwest (CV R2 = 0.89) and agrees least in the Southwest (CV R2 = 0.65). To account for the non‐Gaussian distribution of TROPOMI NO2, we apply data transforms, with the Anscombe transform yielding highest agreement across the continental U.S. (CV R2 = 0.77). The interpretability, minimal computational cost, and health relevance of qNO2 facilitates use of satellite data in a wide range of air quality applications.

Sensitivity analysis of NO2 differential slant column density according to spatial resolution using GCAS data from the SIJAQ 2022 campaign

The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) instrument made observations over the South Korea during Satellite Integrated Joint Monitoring for Air Quality (SIJAQ) 2022 (July–August 2022) campaign aimed at collecting high-resolution remote sensing data. To investigate the impact of spatial resolution on nitrogen dioxide (NO2) retrieval from remote sensing data, the NO2 differential slant column density (dSCD) was examined using high-resolution GCAS data, which are suitable for upscaling, to identify differences related to spatial resolution. Through the GCAS NO2 dSCD, the structure at the original resolution (100 m × 200 m) was maintained even following a shift to a coarser resolution; however, it was difficult to distinguish boundary areas with large concentration differences at resolutions coarser than 1.5 km × 3 km. In the comparison of coadded NO2 dSCD and merged NO2 dSCD, the standard deviations from the merged data increased when NO2 dSCD was >3 × 1016 molecules/cm2, such as in the high NO2 concentration cases. The slope of the scatter plot obtained using the top 25% of the data determined from the regression line tended to increase as the resolution became coarser. In addition, the average standard deviation within merged pixels at a resolution of 3 km × 6 km was twice that obtained at 400 m × 800 m resolution. Accordingly, the standard deviation of the information contained in the pixels increased when the spatial resolution became coarser.

Location, location, location–A study of factors affecting air quality in Swedish preschool yards

Air pollution exposure is a major health concern globally. Children are especially vulnerable as their lungs and organs are still maturing and it is important to minimize children's exposure to air pollution. In this study we analyse one year of measurements of monthly average Nitrogen dioxide (NO₂) concentrations, in 17 sites around 11 preschools, to assess the influence of the preschool yard location on air quality. The urban background levels greatly affected concentrations at the preschool yards, with up to 50 % higher NO₂ concentrations in exposed central neighbourhoods compared to suburban. However, the specific placement of the preschool yard within the neighbourhood could also markedly reduce the pollution concentrations. A more exposed preschool suffered between 11 and 24 % higher concentrations compared to a nearby, more protected, preschool in the same neighbourhood. Differences of the same magnitude were also connected to the presence of barriers blocking the flow of polluted air from the source to the yard. The health implications of exposure differences were estimated to be small for each child but not negligible on a population level. Careful placement of preschool yards, especially in high-risk neighbourhoods, can improve air quality and provide a healthier environment for our children.

Global estimates of ambient NO2 concentrations and long-term health effects during 2000–2019

High concentrations of ambient NO2 causes serious air pollution and could also pose great threats to human health. However, the long-term trends (20-year) and potential health effects of ambient NO2 exposure globally still shows high uncertainties. In this work, the field measurements, satellite dataset, GEOS-Chem output, and multiple geographical covariates were incorporated into the multi-stage model to investigate the global evolutions of ambient NO2 during 2000–2019. The results indicated that the cross-validation (CV) R2 values of ambient NO2 based on multi-stage model displayed satisfied performance (R2 = 0.78), which was superior to the individual model. Besides, the out-of-bag R2 was 0.75, which suggested the multi-stage model showed the better transferability. At the spatial scale, the NO2 concentrations followed the order of China (16.9 ± 9.0 μg/m3) > India (15.5 ± 5.6 μg/m3) > United States (10.7 ± 5.6 μg/m3) > Europe (7.7 ± 4.5 μg/m3), which was in consistent with the anthropogenic NOx emission. At the temporal scale, the ambient NO2 levels in China experienced persistent increases (0.29 μg/m3/year) during 2000–2013, whereas they showed slight decreases (−0.23 μg/m3/year) during 2013–2019. The ambient NO2 levels in the United States experienced continuous decreases during 2000–2019 (−0.20 μg/m3/year), while both of India and Europe remained relatively stable. Long-term NO2 exposure inevitably increased premature mortalities. The global premature all-cause mortalities associated with the excessive NO2 exposure increased from 288,169 (95% CI: 43,650, 527,971) to 461,301 (95% CI: 69,973, 843,996) in the past 20 years. This study would provide sufficient policy support for future ambient NO2 mitigation.

Comparative analysis of meteorological parameters and their relationship with NO2, PM10, PM2.5 and O3 concentrations at selected urban air quality monitoring stations in Krakow, Paris, and Milan

Meteorological parameters play a major role in air pollutant concentrations as they create conditions that either hinder or facilitate the reaction and dispersion of pollutants in our environments. This is particularly evident in Europe, where frequent alternation of meteorological parameters has the potential to significantly impact pollutant concentrations. This study applied the R openair package to comparatively analyse the relationship between key meteorological parameters and NO2, O3, PM2.5, and PM10 concentrations measured at selected air quality monitoring stations in Krakow, Milan, and Paris in the year 2021. The study made use of meteorological data acquired from National Aeronautics and Space Administration (NASA) Power data repository, and air pollutants data measured at air quality monitoring stations in each of the three cities. The air pollutants data were retrieved from European Environmental Agency’s Airbase. Concentration and correlation analyses were conducted using the relevant functions of the R openair package. Findings in the study revealed a positive relationship between temperature and O3, wind speed and O3; and a negative relationship between temperature and NO2/PM2.5/PM10. The study further revealed a negative relationship between wind speed and NO2/PM2.5/PM10, as well as a negative relationship between precipitation and NO2/PM2.5/PM10. NO2, PM2.5, and PM10 concentrations were higher in winter periods, weekdays, nights, and evenings, but lower in summer periods, weekends, and midday. Whereas O3 concentration was higher in summer periods, weekends, midday, and lower in winter periods, weekdays, nights, and evenings. NO2, PM10, and PM2.5 concentrations were higher during the periods without precipitation than periods with precipitation. In addition, temperature inversions were found to be linked with higher concentrations of NO2, PM2.5, and PM10, but lower concentrations of O3 in Krakow, Paris and Milan. Accordingly, the study recommends effective monitoring, increased awareness, the use of pollutant removing devices, and further research to enhance adaptation and advance knowledge.

The impact of shipping on the air quality in European port cities with a detailed analysis for Rotterdam

Air quality in cities with large maritime ports is considerably impacted by emissions from shipping activity which is of a growing relevance due to an increasing relative contribution. To explore the extent of shipping emissions to ambient air quality, simulations with the chemical transport model LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog model) were performed for the year 2018 at an approximate 1 × 1 km resolution for six European cities with large ports, i.e., Rotterdam, Antwerp, Hamburg, Amsterdam, Le Havre, and London. It was found that depending on the investigated city, 6.5%–62% of the nitrogen dioxide (NO2) concentration in the city centres is attributable to shipping activities. This corresponds to contributions of 1.8–11.5 μg/m3 to the ambient air NO2 concentrations. The average NO2 contribution of shipping in these six cities was 28% (7.1 μg/m3). The largest relative contribution was found for Le Havre where 62% (10.8 μg/m3) of the annual average NO2 concentration was caused by shipping emissions. The largest absolute contribution is found for the city centre of Hamburg with 11.5 μg/m3 (41%). The lowest absolute and relative contribution (respectively 1.8 μg/m3 and 6.5%) are found for London, also having the smallest port in terms of tonnage throughput, which is one of the influential factors that determine emission totals, investigated in this study. For the other investigated pollutants, i.e., PM2.5, PM10 and SO2, contributions from shipping were less pronounced with average contribution for all cities of 10% (1.2 μg/m3) 7% (1.5 μg/m3) and 4% (0.16 μg/m3) respectively. To assess the effect of model choices on these results, this study also looked into the choice of simulation resolution and relations between meteorological parameters and NO2 concentrations. Following simulations with varying chemical transport model resolutions (1 × 1 km to 24 × 24 km), it is found that a decrease in ambient air pollutant concentrations away from localized emission sources is more pronounced at higher (1 × 1 km) model resolutions and source contributions are influenced more significantly than total concentrations. Considering meteorology, generally low wind speeds (1–2 m/s) lead to high NO2 concentration in city centres. For the cities where the port is much closer to the city centre (e.g., London, Le Havre, Hamburg and Antwerp) the absolute NO2 concentrations as well as the contributions from shipping emissions become highest for windless conditions. The high concentrations (>60 μg/m3 NO2) only occur when wind speeds fall below 6 m/s.

Atmospheric H2O2 during haze episodes in a Chinese megacity: Concentration, source, and implication on sulfate production

Atmospheric hydrogen peroxide (H2O2), as an important oxidant, plays a key role in atmospheric chemistry. To reveal its characteristics in polluted areas, comprehensive observations were conducted in Zhengzhou, China from February 22 to March 4, 2019, including heavy pollution days (HP) and light pollution days (LP). High NO concentrations (18 ± 26 ppbv) were recorded in HP, preventing the recombination reaction of two HO2• radicals. Surprisingly, higher concentrations of H2O2 were observed in HP (1.5 ± 0.6 ppbv) than those in LP (1.2 ± 0.6 ppbv). In addition to low wind speed and relative humidity, the elevated H2O2 in HP could be mainly attributed to intensified particle-phase photoreactions and biomass burning. In terms of sulfate formation, transition-metal ions (TMI)-catalyzed oxidation emerged as the predominant oxidant pathway in both HP and LP. Note that the average H2O2 oxidation rate increased from 3.6 × 10−2 in LP to 1.1 × 10−1 μg m−3 h−1 in HP. Moreover, the oxidation by H2O2 might exceed that of TMI catalysis under specific conditions, emerging as the primary driver of sulfate formation.