NO2 Concentrations Research Articles

Big data analyses for determining the spatio-temporal trends of air pollution due to wildfires in California using Google Earth Engine

California has a long history of wildfires that release substantial amounts of smoke, contributing to regional air pollution. This study employs advancements in Earth observation satellites, cloud computing, and the Google Earth Engine to analyze MODIS MCD19A2 Version 6 level 2, Sentinel-5P NRTI AER AI, and Sentinel-5P NRTI NO2, evaluating the impact of wildfires from 2010 to 2022 on air quality in California. Historical fire events are cross-validated using the MODIS 1-km MYD14A1 V6 dataset, and the MODIS MAIAC-derived Aerosol Optical Depth (AOD) values are validated against AERONET AOD measurements from ground-based sun photometers. To assess the analysis's uncertainty, metrics such as Mean Absolute Error, Relative Mean Bias, and Root Mean Square Error are applied. Additionally, linear regression is used to verify the correlation between satellite and ground measurements. Results show that the average monthly MODIS MAIAC AOD at 470 nm and 550 nm tends to overestimate AOD by 24% and 6%, respectively, compared to AERONET AOD values. The correlation coefficient and adjusted R-squared value range from 0.78 to 0.80 and from 0.61 to 0.65, respectively, for AOD values at 470 nm and 550 nm. During the fire season, correlations exhibit closer associations, with a coefficient above 0.78 and an adjusted R-squared value above 0.63 are observed for both wavelengths. Sentinel-5P data reveal a significant increase in NO2 concentration in the surrounding areas during the 2020 and 2021 wildfires. This study identifies historical spatiotemporal trends of air pollution attributable to wildfires in California from 2010 to 2022, informing decision-making in the development of effective prevention and mitigation programs.

The observation of atmospheric HONO by wet-rotating-denuder ion chromatograph in a coastal city: Performance and influencing factors

Due to the significance of atmospheric HONO as a reservoir for radicals and the presence of substantial unknown sources of HONO, there is a pressing need for accurate and consistent measurement of its concentration. In this study, we compared the measurements obtained from the monitor for aerosols and gases in ambient air (MARGA) based on wet chemical method with those from the incoherent broadband cavity-enhanced absorption spectroscopy (IBBCEAS) based on optical method to assess the suitability of the MARGA instrument for accurate HONO detection. The diurnal patterns obtained by the two instruments are similar, with peaks at 8 a.m. and lows at 5 p.m. Over the course of the observation period, it was often observed that HONO concentrations recorded by the MARGA instrument consistently exceeded those obtained through the IBBCEAS technique, accounting for approximately 91.33% of the total observation time. Throughout the entire observation period, the R2 value between the two instruments was 0.49, indicating relatively good correlation. However, with a slope of only 0.27, it suggests poor agreement between the two instruments. Furthermore, the R2 and slopes between the two instruments vary with the seasons and day-night. The larger the quartile values of NO2, NH3, and BC, the greater the slopes of both MARGA and IBBCEAS instruments, and the higher the concentrations of NO2, NH3, and BC (indicator of semivolatile oxidizable hydrocarbons), the greater the differences between the two instruments, all indicating that NH3 may promote the reaction of NO2 with semivolatile oxidizable hydrocarbons to produce HONO. The O3 with its strong oxidizing properties may cause underestimation in the MARGA instrument by oxidizing NO2− to NO3− in the absorbing solution. It is challenging to derive a universal correction formula due to the interference of various chemical substances. Hence, MARGA should not be used for HONO research in the future.

Combustion Efficiency of Various Forms of Solid Biofuels in Terms of Changes in the Method of Fuel Feeding into the Combustion Chamber

This study analyzes the combustion of pellets and briquettes made of plant biomass in low-power heating devices powered periodically with fuel being placed on the grate, as well as after modification using an automatic fuel feeding system in the gutter burner. The use of herbaceous biomass in the form of pellets in low-power heating devices with automatic fuel feeding and combustion in a gutter burner is not widely promoted and popular. Therefore, this study used four types of herbaceous waste biomass (wheat straw, rye straw, oat straw and hay) and one type of woody waste biomass (birch sawdust) for testing. The basic chemical characteristics were determined for the raw materials. After appropriate preparation, the selected starting materials were subjected to briquetting and pelleting processes. Selected physical properties were also determined for the obtained biofuels. Biofuels made from birch sawdust had the lowest heat value (16.34 MJ·kg−1), although biofuels made from wheat, rye and hay straw had a slightly lower calorific value, respectively: 16.29; 16.28 and 16.26 MJ·kg−1. However, the calorific value of oat straw biofuels was only 15.47 MJ kg−1. Moreover, the ash content for herbaceous biomass was 2–4 times higher than for woody biomass. Similar differences between herbaceous and woody biomass were also observed for the nitrogen and sulfur content. To burn the prepared biofuels, a domestic grate-fired biomass boiler was used, periodically fed with portions of fuel in the form of pellets or briquettes (type A tests), which was then modified with a gutter burner enabling the automatic feeding of fuel in the form of pellets (type B tests). During the combustion tests with simultaneous timing, the concentration of CO2, CO, NO and SO2 in the exhaust gases was examined and the temperature of the supplied air and exhaust gases was measured. The stack loss (qA), combustion efficiency index (CEI) and toxicity index (TI) were also calculated. The research shows that the use of automatic fuel feeding stabilizes the combustion process. The combustion process is balanced between herbaceous and woody biomass biofuels. Disparities in CO2, CO and Tgas emissions are decreasing. However, during type B tests, an increase in NO emissions is observed. At the same time, the research conducted indicates that the combustion of herbaceous biomass pellets with their automatic feeding into the combustion chamber is characterized by an increase in combustion efficiency, indicating that when the combustion process is automated, they are a good replacement for wood biofuels—both pellets and briquettes.

The Relationship Between Air Pollution Components and Hospitalizations Due to Acute Pulmonary Embolism

Objectives: This study was conducted to examine the relationship between air pollution and pulmonary embolism in patients hospitalized in Urmia city. This cross-sectional study was conducted in West Azerbaijan province, Iran. According to the daily report from the meteorology center of West Azarbaijan province, the data on the concentrations of air pollutants, including PM10, NO2, O3, CO, and PM2.5 were extracted. Moreover, the files of patients without underlying risk factors hospitalized due to pulmonary embolism were extracted. Finally, admissions from 2 days before until 2 days after the polluted days were compared to hospitalizations on clean air days of the same month. Design: A cross-sectional study. Setting(s): Urmia, the capital city of the West Azerbaijan province in northwestern Iran. Participants: A total of 1275 patients without underlying risk factors hospitalized due to pulmonary embolism were included. Outcome measures: Admissions from 2 days before until 2 days after the polluted days were compared to hospitalizations on clean air days of the same month. Results: Out of 1779 patients admitted due to pulmonary embolism, 1275 patients met our inclusion and exclusion criteria. Based on the results, 403 patients (31.6%) were hospitalized in clean and healthy air (air quality index [AQI] of 0-50 and 50-100), 816 patients (64.1%) were hospitalized in unhealthy air (AQI: 150-101), and 56 patients (4.4%) were hospitalized in days with polluted air (AQI:151-200). According to Pearson’s correlation coefficient, there was a significant relationship between carbon monoxide (r=0.09, P=0.0001), sulfur dioxide (r=0.11, P=0.001), PM10 (r=0.28, P=0.001), and PM2.5 (r=0.45, P=0.0001) concentrations and the frequency of hospitalizations due to pulmonary embolism. Conclusions: There is a positive and significant relationship between air pollutants and the number of hospitalizations due to pulmonary embolism. Hence, preventive measures should be taken into account regarding the air pollution at the provincial and national levels.

Air pollution, greenspace exposure and risk of Parkinson's disease: a prospective study of 441,462 participants.

The current understandings of the relationship between air pollution (AP), greenspace exposure and Parkinson's Disease (PD) remain inconclusive. We engaged 441,462 participants from the UK Biobank who were not diagnosed with PD. Utilizing Cox proportional hazard regression model, relationships between AP [nitrogen dioxide (NO2), and nitrogen oxides (NOX), particulate matter < 2.5μm in aerodynamic diameter(PM2.5), coarse particulate matter between 2.5μm and 10μm in aerodynamic diameter(PM2.5-10), particulate matter < 10μm in aerodynamic diameter(PM10)], greenspace exposure, and PD risk were determined independently. Our analyses comprised three models, adjusted for covariates, and affirmed through six sensitivity analyses to bolster the robustness of our findings. Moreover, mediation analysis was deployed to discern the mediating effect of AP between greenspaces and PD. During a median follow-up of 12.23years (5,574,293 person-years), there were 3,293 PD events. Each interquartile (IQR) increment in NO2 and PM10 concentrations were associated with 10% and 8% increase in PD onset risk, while the increases in NOX, PM2.5 and PM2.5-10 were not associated with PD risk. Additionally, greenspace may safeguard by reducing NO2 and PM10 levels, with the effect mediated by NO2 and PM10 in greenspace-PD relationship. Our findings indicate that an IQR increase in ambient NO2 and PM10 concentrations was associated with risk of PD development, while other pollutants (NOX, PM2.5 and PM2.5-10) were not associated with PD risk. Firstly, we find that augmented exposure to greenspace was associated with the lower PD risk by reducing NO2 and PM10 levels.

M-MnCeOX derived from MOF for low temperature selective catalytic reduction of NOX by NH3: Experiments and mechanisms

A series of M-MnCeOX catalysts using MOF (Metal-organic Framework) were prepared to apply for NH3-SCR (Selective Catalytic Reduction) of NOX. The effects of Mn/Ce molar ratio, calcination temperature and its activity including catalytic activity, H2O/SO2 resistance and stability were systematically investigated. The results showed that under the Mn/Ce molar ratio of 1 and calcination temperature of 400 ℃, the catalyst exhibited excellent catalytic activity, H2O/SO2 resistance, and stability. When the concentration of NO was 500 ppm, the gas spatiotemporal velocity (GHSV) was 36,000 h−1, and the reaction temperature was 100 ℃, the NO conversion efficiency of M-MnCeOX exceeded 90.0 %. Added 200 ppm SO2 and 3 vol% H2O simultaneously, the NO conversion efficiency was close to 80.0 %. By analyzing the physicochemical properties of the catalyst, M-MnCeOX had a large specific surface area, numerous acidic sites, and excellent redox properties. According to density functional theory (DFT), the NH3/NO adsorption energy of M-MnCeOX were −2.35 and −2.40 eV, exhibiting lower than a single MOF-derivative, promoting the adsorption of NH3 or NO. The reaction mechanism on the M-MnCeOX catalyst followed the E-R and L-H mechanisms by In situ DRIFTS.

Acute effects of air pollution on cardiovascular hospital admissions in the port district of Klang, Malaysia: A time-series analysis

Cardiovascular diseases are recognised as a significant burden on healthcare systems globally. In this study, the acute impacts of air pollution, especially from shipping emissions, on cardiovascular hospital admissions in Klang, Malaysia, a notable port district, are explored. Time-series analysis and Quasi-Poisson regressions, combined with distributed lag non-linear models, were employed to examine the relationships between daily levels of pollutants and hospital admissions for cardiovascular issues. Focus was placed on the pollutants NO2 (nitrogen dioxide), SO2 (sulphur dioxide), O3 (ozone), particulate matters with diameters ≤10 μm (PM10), particulate matters with diameters ≤2.5 μm (PM2.5), and CO (carbon monoxide), with consideration of lag effects up to 7 days. An increment of 10 μg/m3 in NO2 concentrations was associated with a 7.32% increase in cardiovascular admissions on the exposure day, with statistically significant elevations in relative risks at lag 0 were observed for admissions among patients with ischaemic heart disease, those aged less than 65 years, and male patients. At lag 4, an association was identified between O3 levels and an increase in relative risk of 1.0513 for hypertensive diseases. Two-pollutant models further highlighted significant interactions between NO2 and PM10, which influenced overall cardiovascular admissions, admissions due to ischaemic heart disease, and particularly affected patients below 65 years old and males, especially at earlier lags. Additionally, interactions involving NO2 and O3 were noted, impacting overall cardiovascular admissions, as well as admissions among patients aged less than 65 years and male patients. The findings underscore the severe health risks posed by air pollution in port areas, highlighting the urgent need for targeted interventions to mitigate these effects. Stricter air quality regulations in port cities are supported by the results to protect public health.

Temporal variations in NO, N2O, and NO2 generation in filament-induced atmospheric plasmas

Ultra-short pulse lasers generate filaments in air, inducing changes in molecular concentration and the formation of new molecules. However, our understanding of the specific chemical reactions triggered by these filaments remains limited. This study aimed to investigate the NxOy species produced by femtosecond laser filaments in a sealed chamber. We employed mid-infrared laser spectroscopy to analyze the resulting products over the reaction time. The research revealed that filament plasma generates NO, N2O, and NO2. Notably, N2O was detected for the first time in filament plasmas generated in the air. The production of NxOy species depends on the initial pressure and is influenced by factors such as plasma properties and molecular collisions. We measured the equilibrium concentrations of NO, N2O, and NO2 under atmospheric conditions, finding them to be 67, 38, and 518 ppm, respectively. Furthermore, comparative experiments conducted in zero air illustrated significantly higher concentrations of NO and NO2 under identical pressure conditions, indicating a significant negative impact of other air molecules on the generation of these species. These findings provide valuable insight into the understanding of filament-induced atmospheric chemical reactions and the generation of NxOy species.

Contribution of emissions from the oil sands activities in Alberta, Canada to atmospheric concentration and deposition of nitrogen and sulfur species at a downwind site

Oil sands activities in the Athabasca Oil Sands Region in Alberta, Canada, are large sources of atmospheric NOx and SO2. This study investigated the impact of oil sands emissions on the atmospheric deposition of nitrogen and sulfur species at a downwind site, about 350 km from the oil sands facilities. Measurement data are from the Canadian Air and Precipitation Monitoring Network (CAPMoN) from 2015 to 2019, including ambient concentrations of HNO3, pNO3-, NO2, pNH4+, NH3, SO2, pSO42− and base cations, as well as concentrations of NO3−, SO42−, NH4+, and base cations in precipitation. Sector analysis of air mass back trajectories was conducted to distinguish measurements with different air mass origins. Median atmospheric concentrations and dry deposition fluxes of HNO3, pNO3-, NO2, pNH4+, pSO42−, and SO2 on days when the air masses came from the oil sands sector were significantly greater than those with the “Clean” sector by 34–67%, whereas the difference in NH3 concentration was not significant. Contributions of the oil sands emissions to dry deposition fluxes of these species ranged from 3.8 to 13.1%. The precipitation-weighted mean concentrations of NO3−, SO42−, and NH4+ in samples with the oil sands sector were 76 %, 65 % and 81 % greater than those with the “Clean” sector, respectively. Contributions of the oil sands emissions to wet deposition of NO3−, SO42−, and NH4+ were 12.5 ± 8.9 %, 8.7 ± 4.4 %, and 6.0 ± 3.3 %, respectively. The annual total deposition of nitrogen and sulfur were 1.9 kg-N ha−1 and 0.74 kg-S ha−1, respectively, of which 8.0 ± 3.5 % and 8.7 ± 3.6 % were from oil sands emissions. The total deposition of sulfur and nitrogen did not exceed the critical loads (CL) of acidity, but nitrogen deposition exceeded the CLs of nutrient nitrogen in the region.

An Assessment of the Contribution of Vehicular Traffic to Ambient Air Quality - A Case Study of Nairobi Expressway Corridor

Abstract In this study, the vehicular air pollution from the Nairobi Expressway corridor was estimated by simulation using AERMOD dispersion model. The Vehicle Kilometer Travelled (VKT), emission factors, and traffic data were used to estimate the pollutants from vehicular traffic.. The highest modelled 24-hour and annual concentrations of PM2.5 were 0.274 µg/m3 and 0.152 µg/m3, whereas the highest 24-hour and annual concentrations of PM10 were 0.405 µg/m3 and 0.225 µg/m3, respectively. The maximum 24-hour and annual concentrations of Total Volatile Organic Compounds (TVOCs) were 20.8 µg/m3 and 11.5 µg/m3, respectively, whereas the maximum 8-hour and annual concentrations of carbon monoxide (CO) were 319 µg/m3 and 177 µg/m3, respectively. The highest modeled 24-hour and annual concentrations of NO2 were 28.2 µg/m3 and 15.7 µg/m3, respectively. The 24-hour average measured TVOCs values showed that Nairobi expressway traffic contributed 3.5 percent to the measured TVOCs concentration value, but CO accounted for 55 percent of the measured value. According to the simulated PM2.5 and PM10 concentration values, Nairobi expressway traffic contributed 1.1 and 1.6 percent, respectively, to the 24-hour average measured concentration levels.

Associations of long-term exposure to air pollution and greenness with incidence of chronic obstructive pulmonary disease in Northern Europe: The Life-GAP project

BackgroundProlonged exposure to air pollution has been linked to adverse respiratory health, yet the evidence concerning its association with chronic obstructive pulmonary disease (COPD) is inconsistent. The evidence of a greenness effect on chronic respiratory diseases is limited. ObjectiveThis study aimed to investigate the association between long-term exposure to particulate matter (PM2.5 and PM10), black carbon (BC), nitrogen dioxide (NO2), ozone (O3) and greenness (as measured by the normalized difference vegetation index - NDVI) and incidence of self-reported chronic bronchitis or COPD (CB/COPD). MethodsWe analyzed data from 5355 adults from 7 centers participating in the Respiratory Health in Northern Europe (RHINE) study. Mean exposures to air pollution and greenness were assessed at available residential addresses in 1990, 2000 and 2010 using air dispersion models and satellite data, respectively. Poisson regression with log person-time as an offset was employed to analyze the association between air pollution, greenness, and CB/COPD incidence, adjusting for confounders. ResultsOverall, there were 328 incident cases of CB/COPD during 2010–2023. Despite wide statistical uncertainty, we found a trend for a positive association between NO2 exposure and CB/COPD incidence, with incidence rate ratios (IRRs) per 10 μg/m³ difference ranging between 1.13 (95% CI: 0.90–1.41) in 1990 and 1.18 (95% CI: 0.96–1.45) in 2000. O3 showed a tendency for inverse association with CB/COPD incidence (IRR from 0.84 (95% CI: 0.66–1.07) in 2000 to 0.88 (95% CI: 0.69–1.14) in 2010. No consistent association was found between PM, BC and greenness with CB/COPD incidence across different exposure time windows. ConclusionConsistent with prior research, our study suggests that individuals exposed to higher concentrations of NO2 may face an elevated risk of developing COPD, although evidence remains inconclusive. Greenness was not associated with CB/COPD incidence, while O3 showed a tendency for an inverse association with the outcome.

Characteristics of Aqueous Chemical Species Generation in Plasma-Facing Liquid Systems Using Helium Jet Plasma.

Plasma-facing liquids (PFLs) facilitate the storage of reactive O and N species (RONS), including H2O2 and NO2 -, which remain in the PFL after plasma treatment, and they can continuously influence the target immersed in the liquid. However, their behaviors and levels of generation and extinction depend strongly on the plasma characteristics and liquid condition. Therefore, understanding the effects of the liquid type on the plasma discharge characteristics and the RONS generated via plasma discharge is necessary. We compared the RONS generation and storage trends of deionized H2O and a high-conductivity PFL, RPMI 1640, which is a well-known cell culture medium commonly used to culture mammalian cells. RPMI 1640 acted as an electrode and enhanced the plasma discharge power by supplying abundant radicals and RONS. The production of gaseous hydroxyl radicals and NO markedly increased, which facilitated H2O2 and NO2 - production in the PFL for the first 200 s, and then the increase in the RONS concentration stagnated. With respect to storage, as the components within RMPI 1640 exhibited high reaction constants for their reactions with H2O2, H2O2 elimination was completed in <30 min. Unlike H2O2, the concentration of NO2 - in the PFL was unchanged.

A multi-resolution ensemble model of three decision-tree-based algorithms to predict daily NO2 concentration in France 2005–2022

Understanding and managing the health effects of Nitrogen Dioxide (NO2) requires high resolution spatiotemporal exposure maps. Here, we developed a multi-stage multi-resolution ensemble model that predicts daily NO2 concentration across continental France from 2005 to 2022. Innovations of this work include the computation of daily predictions at a 200 m resolution in large urban areas and the use of a spatio-temporal blocking procedure to avoid data leakage and ensure fair performance estimation. Predictions were obtained after three cascading stages of modeling: (1) predicting NO2 total column density from Ozone Monitoring Instrument satellite; (2) predicting daily NO2 concentrations at a 1 km spatial resolution using a large set of potential predictors such as predictions obtained from stage 1, land-cover and road traffic data; and (3) predicting residuals from stage 2 models at a 200 m resolution in large urban areas. The latter two stages used a generalized additive model to ensemble predictions of three decision-tree algorithms (random forest, extreme gradient boosting and categorical boosting). Cross-validated performances of our ensemble models were overall very good, with a ten-fold cross-validated R2 for the 1 km model of 0.83, and of 0.69 for the 200 m model. All three basis learners participated in the ensemble predictions to various degrees depending on time and space. In sum, our multi-stage approach was able to predict daily NO2 concentrations with a relatively low error. Ensembling the predictions maximizes the chance of obtaining accurate values if one basis learner fails in a specific area or at a particular time, by relying on the other learners. To the best of our knowledge, this is the first study aiming to predict NO2 concentrations in France with such a high spatiotemporal resolution, large spatial extent, and long temporal coverage. Exposure estimates are available to investigate NO2 health effects in epidemiological studies.

High-performance NO2 gas sensor enabled by Fe, N co-doped GQDs modification and pulse-driven temperature modulation

Nitrogen dioxide (NO2) is a typical reactive nitrogen species harmful to health and the environment. However, NO2 sensors still suffer from low sensitivity and poor response/recovery rates. Herein, 3D In2O3 assembled by stacked nanosheets were prepared and modified with N element-doped GQDs (N-GQDs) and Fe, N co-doped GQDs (Fe,N-GQDs), respectively. The results of NO2-sensing performance indicated that the optimal sample (0.3 wt% Fe,N-GQDs/In2O3) showed a high response of 414.5 to 1 ppm NO2 and could detect as low as 10 ppb at 50℃, which was 1.3 and 4.0 times higher than that of 0.3 wt% N-GQDs/In2O3 and In2O3, respectively. The gas-sensing kinetics were analyzed by establishing gas adsorption/desorption isotherms. The enhanced NO2 sensing properties of 0.3 wt% Fe,N-GQDs/In2O3 were mainly due to the enhanced active site accessibility of stacked nanosheets with open layer spaces, the heterointerface between Fe,N-GQDs and In2O3, and electrical modulation of Fe,N-GQDs. Additionally, A pulse-driving circuit was designed for a pulse temperature modulation (PTM) strategy to further boost NO2 detection. The sensor response is further enhanced by 1.7 times, and the response/recovery time is reduced by 42.5 %/60.1 %. The NO2 concentration in vehicle exhaust was determined using PTM mode with good spike recoveries. It validated the reliability of the sensor for the quantitative detection of NO2 in the real environment. This work provides insights into sensor design and has the potential to contribute to the development of novel sensing platforms for other gas pollutants.

Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling

Abstract. Ground-level ozone (O3) pollution is a persistent environmental concern, even in regions that have made efforts to reduce emissions. This study focuses on the state of Arizona, which has experienced elevated O3 concentrations over past decades and contains two non-attainment areas as designated by the U.S. Environmental Protection Agency. Using the Weather Research and Forecasting with Chemistry (WRF-Chem) model, we examine O3 levels in the semi-arid and arid regions of Arizona. Our analysis focuses on the month of June between 2017 and 2021, a period characterized by high O3 levels before the onset of the North American Monsoon (NAM). Our evaluation of the WRF-Chem model against surface Air Quality System (AQS) observations reveals that the model adeptly captures the diurnal variation of hourly O3 levels and the episodes of O3 exceedance through the maximum daily 8 h average (MDA8) O3 concentrations. However, the model tends to overestimate surface NO2 concentrations, particularly during nighttime hours. Among the three cities studied, Phoenix (PHX) and Tucson (TUS) exhibit a negative bias in both hourly and MDA8 O3 levels, while Yuma demonstrates a relatively large positive bias. The simulated mean hourly and MDA8 O3 concentrations in Phoenix are 44.6 and 64.7 parts per billion (ppb), respectively, compared to observed values of 47.5 and 65.7 ppb, resulting in mean negative biases of −2.9 and −1.0 ppb, respectively. Furthermore, the analysis of the simulated ratio of formaldehyde (HCHO) to NO2 (HCHO/NO2; FNR), reveals interesting insights of the sensitivity of O3 to its precursors. In Phoenix, the FNR varies from a VOC (volatile organic compound)-limited regime in the most populated areas to a transition between VOC-limited and NOx-limited regimes throughout the metro area, with an average FNR of 1.15. In conclusion, this study sheds light on the persistent challenge of ground-level O3 pollution in semi-arid and arid regions, using the state of Arizona as a case study.

Long-term variations and trends of tropospheric and ground-level NO2 over typical coastal areas

Tropospheric and ground-level levels of nitrogen dioxide (NO2) may have changed due to environmental policies and technological changes. Here, multiyear ground-based measurement (2014–2022) and satellite-derived retrieval (October 2004 to May 2023) datasets of NO2 concentrations are used to study the long-term ground-level and tropospheric NO2 patterns and trends at four time scales (interannual, quarterly, monthly, and hourly) over the three regions with the highest global NO2 concentrations. Several tropospheric NO2 hotspots are observed over industrialized and highly populated coastal zone areas. Over the past 18 years, these hotpots have generally decreased due to the implementation of strong and effective environmental protection policies. A significant trend reversal was observed in 2011 in East-central China. The maximum values of tropospheric NO2 occurred in winter over East-central China, Western Europe and East-central USA, with concentrations of 13.010, 4.243 and 4.149 × 1015 molecules cm−2, respectively. The Bohai Sea exhibited disproportionately high tropospheric NO2 levels, suggesting it as a significant contributor to regional nitrogen pollution. Ground-level NO2 shows similar temporal patterns to tropospheric concentrations, with over 82.8 % of sites in East-central China exceeding 30 μg m−3, compared to 12.8 % in Western Europe and 3.8 % in East-central USA. The analysis of diurnal variations in ground-level NO2 concentrations shows a significantly decrease during the daytime compared to nighttime, reflecting that the peak occurs at approximately 08:00 and 20:00 LT, while the lowest concentrations at around 12:00 LT. These insights clarify the impacts of environmental policies on NO2 levels and identify critical areas for targeted pollution control, enhancing our understanding of NO2 dynamics in high-pollution regions globally.

A Multi-Temporal Analysis on the Dynamics of the Impact of Land Use and Land Cover on NO2 and CO Emissions in Argentina for Sustainable Environmental Management

This study presents an analysis of NO2 and CO emissions in Argentina, utilizing remote sensing data. This research aims to determine the spatiotemporal distribution of NO2 and CO emissions from 2019 to 2021. It examines the influence of land use and cover on NO2 and CO emissions using various climatic, anthropic, and natural indicators. The year with the highest CO and NO2 concentration was 2020. NO2 exhibited the highest concentrations in built-up urban areas and croplands, notably impacting the capital city and the northern region of Buenos Aires province. Also, CO concentration was influenced by anthropic variable distances to national route, mining extraction, power plants, airports, and urban index (UI). They were also influenced by climatic and natural variables (Palmer drought index, vapor pressure, maximum environment temperature, wind speed, DEM, humidity, and normalized difference vegetation index (NDVI)) for the different uses and land covers. NO2 concentrations were influenced by anthropic (distance to airports, service stations, open dumpsites, power plants, and factories), climatic, and natural variables (Palmer drought index, vapor pressure, wind speed, and DEM) for the different uses and land cover. This research supports sustainable environmental management by guiding the development of effective emission mitigation strategies for improved community health and well-being.

Air pollution in Białowieża forest: Analysis of short-term trends from 2014 to 2021

Air pollution caused by sulphur dioxide (SO2) and nitrogen oxides (NOx) has negative impacts on forest health and can initiate forest dieback. Long-term monitoring and analysis of these pollution are carried out in Białowieża Forest in NE Poland due to the threats from abiotic, biotic and anthropogenic factors. The main objective of our study was to monitor the levels and trends of air pollutant deposition in Białowieża Forest. During a short-term monitoring period over six years (2014–2021), the concentration of SO2 in the air decreased significantly (from 2.03 μg m−3 in December 2015 to 0.20 μg m−3 in July 2016), while the concentration of NO2 in the air showed a non-significant decrease (from 8.24 μg m−3 in December 2015 to 1.61 μg m−3 May 2016). There was no significant linear trend in the wet deposition of S–SO4 anions. Mean monthly S–SO4 deposition varies between 4.54 and 94.14 mg m−2month−1. Wet nitrogen deposition, including oxidized nitrogen (N–NO3) and reduced nitrogen (N–NH4), showed a non-significant increase. Mean monthly precipitation of N–NO3 and N–N H4 ranged from 1.91 to 451.73 mg m−2month−1. Neither did total sulphur deposition nor total nitrogen deposition exceed the mean deposition values for forests in Europe (below 6 ha−1yr−1 and 3–15 ha−1yr−1, respectively). Our results indicate that air pollutants originate from local sources (households), especially from the village of Białowieża, as demonstrated by the level and spatial distribution of air pollutant deposition. This indicates that air pollutants from the village of Białowieża could spread to other parts of Białowieża Forest in the future and may have a negative impact on forest health and can initiate forest dieback. It is therefore important to continue monitoring air pollution to assess the threats to this valuable forest ecosystem.

Synergistic tailoring of adsorption and vacancy enrichment in lamellar stacked layers of α-MoO3 nanorods by Mg2+ for NO2 gas sensor

Extremely toxic nitrogen dioxide (NO2) was detected using lamellar layered α-MoO3. The stable orthorhombic phase of MoO3 (α-MoO3) with preferential growth along (02k0) and the nano-rectangular rods (NRs) like morphology were observed. The incorporation of Mg2+ in α-MoO3 influenced the morphology and the oxygen vacancies (VO), which were analyzed through Raman, photoluminescence, and X-ray photoelectron spectroscopy. The core level spectra provided direct evidence for VO enrichment in 3 %Mg-α-MoO3 via emergence of peak at 531.02 eV with an area of 45.15 %. NO2 response was analyzed at 150–200 °C with various NO2 concentrations. 3 %Mg-α-MoO3 NRs provided maximum response of 133.9 % for 50 ppm with low limit of detection (LOD) of 250 ppb with good response (193 s) and recovery (260 s) transient behaviors. The fabricated sensor shows high selectivity to NO2 among H2S, SO2, N2O, and NH3, also good repeatability suggesting potential suitability for NO2 detection.

A new quantitative method via on-line mass spectrometer: Application in biomass char/NO reaction

A novel quantitative analysis method via on-line mass spectrometer (OMS) was developed to calculate the mass flows of the reactants and products for the reaction between NO and biomass char in micro-fluidized bed. The experimental results showed that the quantitative method could accurately calculate the mass flow rate of each gas even though there were ion currents overlapping at mass-to-charge ratio (m/z) = 12,16, and 28 when CO, CO2 and N2 were simultaneously present in OMS. Furthermore, the method facilitated the quantitative analysis of gaseous reactants and products, thereby enabling the assessment of mass conversions of carbon (C) and nitrogen (N) in the NO reduction reaction. It was observed that CO was the predominant carbon-containing product in the reaction involving biomass char and NO at 900 °C, with over 96 % of nitrogen in NO participating in the reduction reaction being converted to N2. This study also revealed that increasing the fluidization number, NO concentration, and temperature in the micro-fluidized bed could significantly accelerate the conversion processes of C and N in the reduction of NO by biomass char. The peak mass flow rates of CO, CO2, and N2 were found to increase correspondingly with higher NO concentrations and temperature levels. The NO reduction process over sawdust char was compared to that of corncob char, showing a higher maximum NO reduction efficiency. The reaction order with respect to NO concentration was determined to be 0.82 for corncob char and 0.68 for sawdust char. Additionally, the apparent activation energies were determined to be 92.35 kJ/mol for corncob char and 125.60 kJ/mol for sawdust char, respectively.