NO2 Trends Research Articles

Soil Emissions of Reactive Oxidized Nitrogen Reduce the Effectiveness of Anthropogenic Source Control in China.

Nitrogen dioxide (NO2) has decreased by ∼33% across over 1200 monitoring sites in China during 2015-2023, following a series of clean air policies. However, most of these sites are located in or near cities, leading to uncertainties in NO2 trends beyond urban regions due to limited observations. Here, we used satellite measurements to examine the differences in NO2 trends between urban and rural China. In urban areas, NO2 columns decreased by 4.0% per annum (a-1) during summer 2011-2023, consistent with bottom-up anthropogenic emission inventory and in situ measurements. In contrast, rural NO2 columns showed a slower than expected reduction (-2.6 to -0.0% a-1) during the same period. Model simulations with updates in the soil reactive oxidized nitrogen (Nr) scheme indicated that increasing soil Nr emissions can be an important factor contributing to the observed slow NO2 decrease in rural areas. This unregulated source increased summertime pollutant levels, partially offsetting the national efforts to mitigate NO2, ozone (O3), and particulate nitrate (NO3-) levels by 20.9%, 15.4%, and 4.7%, respectively, from 2011 to 2020. In the agriculture-intensive North China Plain, the increase in soil Nr emissions offset 46.6% of the NO2 reductions achieved by clean air policies. Our results highlight the increasing significance of soil emissions and the need to control them in future air-quality policies.

Long-term spatiotemporal changes in nitrate contamination of municipal groundwater resources after sewerage network construction in the Hungarian Great Plain.

Over the last decades, as a consequence of wastewater discharges and other anthropogenic sources, severe nitrate (NO3-) pollution has developed in municipal environment causing global concern. Thus, eliminating the potential sources of pollution is one of the major challenges of the twenty-first century, whereby sanitation services are essential for ensuring public health and environmental protection. In the present study, long-term monitoring (2011-2022) of shallow groundwater NO3- contamination in municipal environment was carried following the construction of the sewerage network (2014) in the light of the pre-sewerage situation. Our primary aim was to assess the long-term effects of sewerage on nitrate NO3- levels in the shallow groundwater and evaluate the efficiency of these sanitation measures over time. Based on the results, significant pollution of the shallow groundwater in the municipality was identified. During the pre-sewer period, NO3- concentrations exceeded the 50mg/L limit in the majority of monitoring wells significantly, upper quartile values ranged between 341 and 623mg/L respectively. Using Nitrate Pollution Index (NPI) and interpolated NO3- pollution maps, marked spatial north-south differences were detected. In order to verify the presence of wastewater discharges in the monitoring wells, the isotopic ratio shifts (δ) for 18O and D(2H) were determined, confirming municipal wastewater effluent. Variations in NO3-/Cl- molar ratios suggest also contamination from anthropogenic sources, including septic tank effluent from households and the extensive use of manure. Data series of 7years (2015-2022) after the investment indicate marked positive changes by the appearance of decreasing trends in NO3- values confirmed by Wilcoxon signed rank test and ANOVA. By comparing the pre- and post-sewerage conditions, the mean NO3- value decreased from 289.7 to 175.6mg/L, with an increasing number of monitoring wells with concentrations below the limit. Our results emphasise the critical role of sanitation investments, while also indicating that the decontamination processes occur at a notably slow pace. Detailed, long-term monitoring is therefore essential to ensure accurate follow-up of the ongoing changes. The results can provide information for local citizens and authorities to improve groundwater management tools in the region.

Mapping air quality trends across 336 cities in India: Insights from three decades of monitoring (1987–2019)

Over a span of 34 years (1987–2019), an in-depth analysis of PM10, SO2, and NO2 trends across India was conducted using data from the National Ambient Air Quality Monitoring Programme’s manual monitoring stations in 336 cities. The study encompassed six geographical regions over three time blocks, revealing a correlation between the expansion of monitoring networks and the nation’s economic growth. Regions like the densely populated Indo-Gangetic Plains (IGP) and Central India consistently hosted more monitoring stations, while the Himalayan and Northeast regions saw substantial increases from initial scarcity. SO2 concentrations showed a declining trend, while NO2 levels remained relatively stable with intermittent fluctuations. Conversely, national average PM10 concentrations exhibited an upward trajectory, notably spiking by 128 % between 2006 and 2009 due to economic activities, construction, network expansion, the 2009 drought, and heightened coal consumption. Spatially, pollutant concentrations across three blocks demonstrated improved SO2 levels, several cities exceeding NO2 standards, and persistently high PM10 levels in the IGP. PM10 levels in block 3 were lower than in block 2, reflecting effective policy interventions. State rankings, however, did not consistently reflect pollutant trends across blocks. Regionally, the IGP consistently had the highest PM10 concentrations, while the Northeast recorded the lowest. Population-weighted exposure levels indicated an overall increase in public exposure to PM10. Analysis of major city per region aligned with national trends, as evidenced by Delhi (IGP), Guwahati (Northeast), Vadodara (Northwest), and Bhopal (Central) showing increased PM10 concentrations since 2006, followed by intermittent declines. In contrast, Shimla (Himalayan) and Chennai (Southern) exhibited distinct patterns. Major industrial cities such as Parwanoo, Bongaigaon, Angul and Talcher, and Visakhapatnam mirrored national trends, with PM10 levels rising since 2009, highlighting the significant impact of industrial activities on air quality. This research underscores the need for targeted, effective mitigation strategies based on spatial and temporal pollutant trends.

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.

Two decades of fire activity over the PEEX domain: a look from space, with contribution from models and ground-based measurements

ABSTRACT It has been suggested that forest fires will become more frequent/intense with changing climate, which would increase aerosol/gas emissions into the atmosphere. A better understanding of the relations between meteorological conditions, fires, and fire emissions will help estimate the climate response via forest fires. In this study, we use ERA5 meteorological products, including temperature, precipitation, and soil moisture, to explain the frequency of forest fires and the amount of radiant energy released per time unit by burning vegetation (fire radiative power, FRP). We explore the relationships between satellite-retrieved fire products and aerosol properties (aerosol optical depth, AOD), carbon monoxide (CO), formaldehyde (HCHO), and nitrogen dioxide (NO2) concentrations over the PEEX domain, which covers different vegetation zones (e.g. croplands/grasslands, forest, arctic tundra) of Pan-Eurasia and China. We analyse the concentrations of black carbon and absorbing organic carbon using ground-based AErosol RObotic NETwork. The analysis covers the months of May to August from 2002 to 2022. We show positive temperature trends in the Northern zone (>65°N) in June and August (1.56°C and 0.64°C, respectively); all statistically significant trends for precipitation and soil moisture are negative. This can explain increased fire activity in Siberia over the recent years (2019–2022). Over the whole PEEX domain, FC and FRP trends remain insignificant or negative; a decrease in AOD may address those negative trends. We show that intra-summer variations exist for cropland/grassland fires, which occur most often in May and August, while Siberian forest fires occur more often in July and August. We show that CO concentration has been gradually decreasing in the last two decades in May and June. CO trends are negative in May, June, and over summer for all regions, in July in Europe, China, the Southern zone (<55°N), and the PEEX domain. HCHO trends are not significant in all regions. NO2 trends are positive in May and negative in June in all zones. We calculated total column enhancement ratios for satellite observations influenced by wildfires. A common feature has been recognized with measurements and ratios utilized in SILAM (System for Integrated Modelling of Atmospheric Composition): AOD(or PM):CO and AOD(or PM):HCHO ratios for grass are clearly lower than for shrubs, opposite for AOD:NO2. We showed that emission ratios are increasing towards South and are 2–3 times higher for high (>0.5) AOD. Using a 21-year satellite record of the AOD and CO, an 18-year record of NO2, and a 16-year record of HCHO, we created background products of those variables over the PEEX domain. In the regions with low anthropogenic activity and conditions where long-range transport is not happening, anomalies in AOD, CO, and HCHO over biomass-burning areas may be assigned directly to the wildfire emissions.

Enhanced ammonia combustion by partial pre-cracking strategy in a gas turbine model combustor: Flame macrostructures, lean blowout characteristics and exhaust emissions

Cofiring with hydrogen presents a reasonable approach to achieve enhanced ammonia (NH3) combustion without introducing an extra carbon footprint. A promising strategy for NH3/H2 cofiring in gas turbines involves on-site partial pre-cracking of NH3 and burns of NH3/H2/N2 mixtures, eliminating additional hydrogen transportation and storage. This work investigates the effects of the pre-cracking ratio (γ) on flame macrostructures, lean blowout characteristics and exhaust emissions of the partially pre-cracked NH3 flames in a single-swirl gas turbine model combustor. Flow and flame macrostructures were captured using particle image velocimetry (PIV) and OH planar laser-induced fluorescence (OH-PLIF) measurements. Lean blowout limits (ϕLBO) were assessed under varying γ, and emissions at the burner outlet were measured using a Fourier transform infrared spectroscopic (FTIR) gas analyzer. Results show that as γ increases, the flame exhibits a shortened height, strengthened OH fluorescence, amplified core jet velocities and significantly reduced ϕLBO, indicating an effective enhancement of NH3 combustion by partial pre-cracking strategy. Nevertheless, NO and NO2 emissions exhibit a substantial increase with larger γ. Opposite trends of NO and NH3 emissions versus equivalence ratio (ϕ) suggest a trade-off between NO and NH3 emissions, with relatively low NO/NH3 window appearing under slightly-rich (ϕ = 1.0–1.1) conditions. Low NO emissions are also noted under ultra-lean conditions (ϕ = 0.4–0.5) with the penalty of high NH3 and N2O emissions, making it an unacceptable trade-off. Furthermore, the effect of N2 separation from the partially pre-cracked NH3 mixtures was evaluated at γ = 0.4. The results show deteriorating effects on NOx emissions, resulting in 13 % and 21 % increases in peak NO and NO2 emissions, respectively, which implies more feasibility to burn the partially pre-cracked NH3 in a direct manner rather than N2 separation.

Air pollution and economic growth in Dubai a fast-growing Middle Eastern city

This paper discusses the impact of rapid economic development on air quality in the Emirate of Dubai, United Arab Emirates (UAE). Dubai is one of the fastest-growing cities in the world, with a population increase of approximately 80× over the last 60 years. The concentrations of five criteria air pollutants (CAPs) including carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter with diameter less than 10 μm (PM10), ozone (O3) and sulphur dioxide (SO2) were studied from 2013 to 2021 at 14 regulatory monitoring stations. Results show that the biggest improvements in air pollution are for the primary air pollutants NO2 and SO2, with reductions of 54% and 93% respectively over the period studied. Gross domestic product (GDP), population growth and energy consumption are significantly and negatively correlated with NO2 and SO2 and strongly and positively correlated with PM10. CO is positively correlated with the number of buildings completed, while the results for O3 are inconclusive. Trends in NO2 and SO2 indicate that these two pollutants are decoupled from economic development, supporting, with caution, the Environmental Kuznets Curve hypothesis on the relationship between economic growth and environmental degradation. The improvement in the city's air quality is due to the effective implementation of local environmental policies, unaffected by large-scale development and urbanization. The monthly assessments of Dubai's air pollution for 2019 and 2020 show a 3–16% COVID-related improvement in the levels of the studied air pollutants, except for ozone, which increased by an average of 8%.

Synergistic effect and volatile emission characteristics during co-combustion of biomass and low-rank coal

Mass loss behaviours, volatile emissions (NO, HCN, NH3, CO, and CO2), and the O2 consumption characteristics during co-combustion of Naomaohu coal (NMH coal) and pine sawdust (PS) are studied using a TG-FTIR and a specially designed fixed-bed reactor. The results reveal that the trends of CO and CO2 in the TG-FTIR and fixed bed reactor results were similar, while the NO trends showed opposite behavior. In an inert atmosphere, there was no significant interaction during co-combustion of NMH coal and PS. However, a synergistic effect was observed under air atmosphere, leading to enhanced oxidation reactions and a notable reduction in ignition time. Specifically, the ignition time of NMH coal reduced from 5 s to 0.5 s when PS was added in the proportion of 75 %. Furthermore, the replacement of 25 % NMH coal with PS resulted in an 8.9 % reduction in NO emissions. This research provides a valuable framework for the thermal conversion of blends consisting of lignocellulosic biomass and low-rank coal.

Investigation of the spatiotemporal patterns of air quality over the metropolitan area of Tehran, using TROPOMI and OMI data

AbstractAir quality has been one of the main concerns among Tehran residents for at least two decades. In this study, we investigated air quality in the metropolitan area of Tehran utilizing TROPOMI and OMI data based on the Google Earth Engine platform. Long-term analysis indicated slight negative trends in NO2, SO2, and HCHO over the last two decades, which are due to the development of urban transportation systems. Air quality parameters were classified based on spatiotemporal similarities. Urban pollutants include CO1, NO2, and HCHO, which were concentrated over the eastern part of Tehran and decreased radially towards the city border. Among the pollutants, CO1 showed a dependency with altitude. SO2 was controlled by both urban vehicles and nonurban industrial activities. SO2 was thus classified as an urban-industrial pollutant. The exterior parameters almost entirely controlled by external factors include O3, aerosols, and clouds. The spatial variations of the pollutants highly differed from a fraction to several times. All pollutants exhibited seasonality associated with fuel consumption and air conditions. However, the seasonality in the exterior parameters was associated with regional air masses. The Iranian New Year holiday significantly impacts air pollution. NO2, CO1, and SO2 experienced their annual minimum levels during this holiday period. COVID-19–related closures also led to negative trends in NO2, CO1, and SO2 after March 2020. However, the exterior parameters were not affected by these events. The results agreed with in situ measurements. As the final objective, we aimed to support urban management to reduce atmospheric pollution in Tehran.

Comprehensive Evaluation of Spatial Distribution and Temporal Trend of NO2, SO2 and AOD Using Satellite Observations over South and East Asia from 2011 to 2021

The past decade has witnessed remarkable economic development, marked by rapid industrialization and urbanization across Asian regions. This surge in economic activity has led to significant emissions, resulting in alarming levels of air pollution. Our study comprehensively assessed the spatial and temporal trends of key pollutants, namely nitrogen dioxide (NO2), sulfur dioxide (SO2), and aerosol (using aerosol optical depth (AOD) at 550 nm as an indicator), from 2011 to 2021. The data sources utilized include OMI onboard the Aura satellite for NO2 and SO2, as well as MODIS onboard Terra and Aqua satellites for AOD. The results from spatial and temporal trend analyses of the three parameters show that there is a clear declining trend over China and Republic of Korea (e.g., NO2 is declining with an overall rate of −7.8 × 1012 molecules/cm2/year over China) due to the strict implementation of air pollution control policies. However, it is essential to note that both countries still grapple with substantial pollution levels, with proportions exceeding 0.5, indicating that air quality is improving but has not yet reached a safe threshold. In contrast, South Asian regions, including Bangladesh, Pakistan, and India, are experiencing an increasing trend (e.g., NO2 is increasing with an overall rate of 1.2 × 1012 molecules/cm2/year in Bangladesh), primarily due to the lack of rigorous air pollution control policies. The average emissions of NO2 and SO2 were remarkably higher in winter than in summer. Notably, the identified hotspots are statistically significant and predominantly coincide with densely populated areas, such as the North China Plain (NCP). Furthermore, this study underscores the pivotal role of sector-wise emissions in air quality monitoring and improvement. Different cities are primarily influenced by emissions from specific sectors, emphasizing the need for targeted pollution control measures. The findings presented in this research contribute valuable insights to the air quality monitoring and improvement efforts in East and South Asian regions.

Trends in Ambient Air Quality (NO2 and SO2) in Tenggarong City, Kutai Kartanegara District. East Kalimantan

This research aims to determine the concentration of ambient air quality NO2 and SO2, determine the trend in ambient air quality NO2 and SO2, and determine the Air Quality Value index for Tenggarong City, Kutai Kartanegara Regency, East Kalimantan. The data collection method was using the 18-SPEKTRO-33/MU/SMM-AAS (Passive Sampler Spectrophotometry) method, then analyzed using environmental quality standards, government regulation number 22 of 2021. The research results show that the quality concentration of NO2 gas in Jam Bentong is between (5.23-19.85) µg/m3 and SO2 is between (3.75-38.55) µg/m3, in the Industrial Area NO2 is between (5.54-10.20) µg/m3 and SO2 is between (4.28 -10.41) µg/m3, while in residential locations NO2 is between (2.49-7.98) µg/m3 and SO2 is between (&lt;2.57-10.60) µg/m3. The tendency for ambient air quality NO2 and SO2 at the Jam Bentong location to fluctuate is inconsistent, while the Industrial Location is almost the same as the Residential Location, namely with uniform quality, but all quality concentrations are still below environmental quality standards. The Environmental Quality Index value at the Jam Bentong location is 79,618, this value is included in good environmental conditions. Meanwhile, in industrial locations it is 90,043, this value is included in superior environmental conditions. Meanwhile, in residential locations, the Environmental Quality Index value is 93,429, this value also falls into superior environmental conditions.

Long-term spatiotemporal variations in surface NO2 for Beijing reconstructed from surface data and satellite retrievals

Remote sensing data from the Ozone Monitoring Instrument (OMI) and the TROPOspheric Monitoring Instrument (TROPOMI) play important roles in estimating surface nitrogen dioxide (NO2), but few studies have compared their differences for application in surface NO2 reconstruction. This study aims to explore the effectiveness of incorporating the tropospheric NO2 vertical column density (VCD) from OMI and TROPOMI (hereafter referred to as OMI and TROPOMI, respectively, for conciseness) for deriving surface NO2 and to apply the resulting data to revisit the spatiotemporal variations in surface NO2 for Beijing over the 2005–2020 period during which there were significant reductions in nitrogen oxide emissions. In the OMI versus TROPOMI performance comparison, the cross-validation R2 values were 0.73 and 0.72, respectively, at 1 km resolution and 0.69 for both at 100 m resolution. The comparisons between satellite data sources indicate that even though TROPOMI has a finer resolution it does not improve upon OMI for deriving surface NO2 at 1 km resolution, especially for analyzing long-term trends. In light of the comparison results, we used a hybrid approach based on machine learning to derive the spatiotemporal distribution of surface NO2 during 2005–2020 based on OMI. We had novel, independent passive sampling data collected weekly from July to September of 2008 for hindcasting validation and found a spatiotemporal R2 of 0.46 (RMSE = 7.0 ppb). Regarding the long-term trend of surface NO2, the level in 2008 was obviously lower than that in 2007 and 2009, as expected, which was attributed to pollution restrictions during the Olympic Games. The NO2 level started to steadily decline from 2015 and fell below 2008's level after 2017. Based on OMI, a long-term and fine-resolution surface NO2 dataset was developed for Beijing to support future environmental management questions and epidemiological research.

Satellite NO2 trends reveal pervasive impacts of wildfire and soil emissions across California landscapes

Nitrogen dioxide (NO2) plays a pivotal role in the production of secondary pollutants, most importantly ozone (O3) and particulate matter. Regulatory controls have greatly reduced NO2 in cities, where most of the surface monitoring occurs, but the change in rural environments is less certain. Here, we present summertime (June–September) spatio-temporal patterns of NO2 concentrations using satellite and ground observations across California from 2009–2020, quantifying the differences in NO2 trends for five distinct land cover classes: urban, forests, croplands, scrublands (shrublands, savannas, and grasslands), and barren (minimally vegetated) lands. Over urban environments, NO2 columns exhibited continued but weakening downward trends (−3.7 ± 0.3%a−1), which agree fairly well with contemporaneous trends estimated from the surface air quality network (−4.5 ± 0.5%a−1). In rural (i.e., non-urban) parts of the state, however, secular trends are insignificant (0.0–0.4 ± 0.4%a−1) or in the case of remote forests are rapidly on the rise (+4.2 ± 1.2%a−1). Sorting the NO2 columns by air temperature and soil moisture reveals relationships that are commensurate with extant parameterizations but do indicate a stronger temperature dependence. We further find that rapidly rising temperatures and, to a lesser extent, decreasing precipitation in response to climate change are acting to increase soil NO x emissions, explaining about one-third of the observed NO2 rise in non-urban regions across California. Finally, we show that these trends, or their absence, can be attributed predominantly to the dramatic rise in wildfire frequency, especially since the turn of the 21st century.

Assessing the Impacts of COVID-19 on SO2, NO2, and CO Trends in Durban Using TROPOMI, AIRS, OMI, and MERRA-2 Data

This research report investigated the impacts of the COVID-19 lockdown restrictions on CO, SO2, and NO2 trends in Durban from 2019 to 2021. The COVID-19 lockdown restrictions proved to decrease greenhouse gas (GHG) emissions globally; however, the decrease in GHG emissions was for a short period only. Space-borne technology has been used by researchers to understand the spatial and temporal trends of GHGs. This study used Sentinel-5P to map the spatial distribution of CO, SO2, and NO2. Use was also made of the Atmospheric Infrared Sounder (AIRS), Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), and the Ozone Monitoring Instrument (OMI) to understand the temporal trends of CO, SO2, and NO2, respectively. To validate the results of this study, we used the Sequential Mann–Kendall (SQMK) test. This study indicated that there were no significant changes in all the investigated gases. Therefore, this study failed to reject the null hypothesis of the SQMK test that there was no significant trend for all investigated gasses. Increasing trends were observed for CO, SO2, and NO2 trends during winter months throughout the study period, whereas a decreasing trend was observed in all investigated gases during the spring months. This shows that meteorological factors play a significant role in the accumulation of air pollutants in the atmosphere. Most importantly, this study has noted that there was an inverse relationship between the trends of all investigated gases and the COVID-19 lockdown restrictions.

Evaluating the effects of columnar NO2on the accuracy of aerosol optical properties retrievals

Abstract. We aim to evaluate the NO2 absorption effect in aerosol columnar properties, namely the aerosol optical depth (AOD), Ångström exponent (AE), and single scattering albedo (SSA), derived from sun–sky radiometers in addition to the possible retrieval algorithm improvements by using more accurate characterization of NO2 optical depth from co-located or satellite-based real-time measurements. For this purpose, we employ multiannual (2017–2022) records of AOD, AE, and SSA collected by sun photometers at an urban and a suburban site in the Rome area (Italy) in the framework of both the Aerosol Robotic Network (AERONET) and SKYNET networks. The uncertainties introduced in the aerosol retrievals by the NO2 absorption are investigated using high-frequency observations of total NO2 derived from co-located Pandora spectroradiometer systems in addition to spaceborne NO2 products from the Tropospheric Monitoring Instrument (TROPOMI). For both AERONET and SKYNET, the standard network products were found to systematically overestimate AOD and AE. The average AOD bias found for Rome is relatively low for AERONET (∼ 0.002 at 440 nm and ∼ 0.003 at 380 nm) compared to the retrieval uncertainties but quite a bit higher for SKYNET (∼ 0.007). On average, an AE bias of ∼ 0.02 and ∼ 0.05 was estimated for AERONET and SKYNET, respectively. In general, the correction seems to be low for areas with low columnar NO2 concentrations, but it is still useful for low AODs (&lt; 0.3), where the majority of observations are found, especially under high NO2 pollution events. For the cases of relatively high NO2 levels (&gt; 0.7 DU), the mean AOD bias was found within the range 0.009–0.012 for AERONET, depending on wavelength and location, and about 0.018 for SKYNET. The analysis does not reveal any significant impact of the NO2 correction on the derived aerosol temporal trends for the very limited data sets used in this study. However, the effect is expected to become more evident for trends derived from larger data sets and in the case of an important NO2 trend. In addition, the comparisons of the NO2-modified ground-based AOD data with satellite retrievals from the Deep Blue (DB) algorithm of the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) resulted in a slight improvement in the agreement of about 0.003 and 0.006 for AERONET and SKYNET, respectively. Finally, the uncertainty in assumptions on NO2 seems to have a non-negligible impact on the retrieved values of SSA at 440 nm leading to an average positive bias of about 0.02 (2 %) in both locations for high NO2 loadings (&gt; 0.7 DU).

Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires

Abstract. Tropospheric nitrogen dioxide (NO2) measured from satellites has been widely used to track anthropogenic NOx emissions, but its retrieval and interpretation can be complicated by the free tropospheric NO2 background to which satellite measurements are particularly sensitive. Tropospheric NO2 vertical column densities (VCDs) from the spaceborne Ozone Monitoring Instrument (OMI) averaged over the contiguous US (CONUS) show no trend after 2009, despite sustained decreases in anthropogenic NOx emissions, implying an important and rising contribution from the free tropospheric background. Here, we use the GEOS-Chem chemical transport model applied to the simulation of OMI NO2 to better understand the sources and trends of background NO2 over CONUS. The previous model underestimate of the background is largely corrected by the consideration of aerosol nitrate photolysis, which increases the model NO2 VCDs by 13 % on an annual basis (25 % in spring) and also increases the air mass factor (AMF) to convert the tropospheric slant column densities (SCDs) inferred from the OMI spectra into VCDs by 7 % on an annual basis (11 % in spring). The increase in the AMF decreases the retrieved NO2 VCDs in the satellite observations, contributing to the improved agreement with the model. Accounting for the 2009–2017 increase in aircraft NOx emissions drives only a 1.4 % mean increase in NO2 VCDs over CONUS and a 2 % increase in the AMF, but the combination of decreasing surface NOx emissions and increasing aircraft emissions is expected to drive a 14 % increase in the AMF over the next decade that will be necessary to account for in the interpretation of satellite NO2 trends. Fire smoke identification with the National Oceanic and Atmospheric Administration (NOAA) Hazard Mapping System (HMS) indicates that wildfires contribute 1 %–8 % of OMI NO2 VCDs over the western US in June–September and that this contribution has been increasing since 2009, contributing to the flattening of OMI NO2 trends. Future analyses of NO2 trends from satellite data to infer trends in surface NOx emissions must critically consider the effects of a rising free tropospheric background due to increasing emissions from aircraft, fires, and possibly lightning.

Spatio-temporal patterns and trends of the air pollution integrating MERRA-2 and in situ air quality data over Egypt (2013–2021)

For best-informed decision-making to improve climate change adaptation and reduce present and future air pollution health hazards, it is essential to identify major trends in spatiotemporal air quality patterns of common air contaminants. This study examined the patterns and trends of SO2, NO2, CO, O3, and particulate matter (PM) air pollutants over 91 monitoring stations in Egypt during 93 months in the August (2013)–April (2021) period. In situ data with their monthly, seasonal, and yearly spatial trends are defined and used to validate the counterpart satellite reanalysis MERRA-2 data. The Mann–Kendall test characterized the seasonal monotonic trends and their Sen’s slope, and annual change rate for both data series. Regression analysis of MERRA-2 against in situ concentrations of SO2 and PM10 revealed underestimation with RMSE values of 13.38 g m−3 and 69.46 g m−3, respectively. Local plumes with variable magnitudes characterized distinct industrial places clarified by patterns of in situ pollutants. As a result of the COVID-19 lockdown, the in situ air pollutants showed a considerable regional decline in the yearly average in 2020 compared to the years before. The in situ air pollutants showed annual trends far more significant than those seen in the MERRA-2 data. The shortcomings of the few and spatiotemporal discontinuities of the in situ contaminants are addressed by MERRA-2 air quality products. The in situ data made trends and magnitudes clear that were hidden in their MERRA-2 counterparts. The results clarified air pollution patterns, trends, and spatial variability over Egypt that are essential for climate risk management and for reducing environmental/health concerns.

Tracking NO2 Pollution Changes Over Texas: Synthesis of In Situ and Satellite Observations

AbstractNitrogen oxides (NOx) are major air pollutants that play a crucial role in atmospheric chemistry. We compare Ozone Measuring Instrument's (OMI) NO2 records with the in situ surface measurements from the Air Quality System of the US Environmental Protection Agency and the Texas Commission on Environmental Quality network in the state of Texas with the goal of understanding the correspondence of satellite and in situ surface observations and identifying the potential synergies between the two observing systems. Our analysis of over 40 in situ daily surface site observations, mostly from urban areas, and OMI daily observed data suggests a correlation (r) ranging between 0.2 and 0.8. The correlation improves considerably (r &gt; 0.5) for monthly average data. Weekly variation of surface NO2 with a Sunday minimum is well captured by OMI tropospheric NO2 column observations with similar weekend reductions. NO2 trend in Texas during 2005–2019 is characterized by significant reductions of 20%–36% in highly populated cities and urban centers. However, a significant (up to 80%) increase was observed in oil and gas producing regions of the Permian and Eagle Ford Basins over the same period. In March–April of 2020, like the other US and global cities, Texas experienced up to 60% reduction in NO2 levels in major cities due to travel restrictions imposed at local and national levels to contain the spread of COVID‐19. Though such reduction is temporary, these reductions were significantly larger than those achieved in the past 16 years of OMI record suggesting that technological advancement can curtail NOx emissions.

Climatology and landscape determinants of AOD, SO2 and NO2 over Indo-Gangetic Plain

Indo-Gangetic Plains (IGP) experiences high loading of particulate and gaseous pollutants all year around and is considered to be the most polluted regions of India. Understanding the effect of landscape determinants on air pollution in IGP regions is crucial to make its environment sustainable. We examined satellite retrievals of OMI NO2 and SO2, and MODIS AOD to analyse the long-term trend, spatio-seasonal pattern and dynamics of aerosols, NO2 and SO2 over three IGP regions, namely Upper Indo-Gangetic plain (UIGP), Middle Indo-Gangetic plain (MIGP) and Lower Indo-Gangetic plain (LIGP) over the period 2005–2019. IGP experienced an overall increment in AOD (R2 = 0.63) and SO2 (R2 = 0.67) values, with LIGP (AOD, R2 = 0.8 & SO2, R2 = 0.8) experiencing the largest rate of enhancement. The levels of NO2 (R2 = 0.2) experienced a decrement after 2012 (owing to implementation of vehicle emission policy) except in MIGP, with UIGP (R2 = 0.23) exhibiting the largest rate of decrement. Seasonal heterogeneity in the nature of sources was observed over IGP regions. AOD (0.61 ± 0.1) and NO2 value (3.82 ± 0.98 × 1015 molecules/cm2) were found highest during post-monsoon in UIGP owing to crop residue burning activity. The value of NO2 (3.8 ± 1.4 × 1015 molecules/cm2) in MIGP was found highest during pre-monsoon due to high consumption of coal in power plants for summer cooling demand. The highest SO2 level (0.09 ± 0.06 DU) was observed during post-monsoon in UIGP, as a large number of brick kilns are fired during this period. Correlations among landscape determinants and pollutants revealed that topography is the dominant variable that affect the spatial pattern of AOD compared to vegetation and land use. Lower elevation tends to have high AOD values compared to higher elevation. Vegetation-AOD relationship showed an inverse association in IGP regions and is influenced by factors such as seasonal meteorology and size of the airborne particles. Vegetation possesses positive relationship with SO2 and NO2, implying no pollution abatement effect on SO2 and NO2 pollutants. Built-up change has deteriorating effect as well as quenching effect on pollutants. Increase in built terrain have deteriorated the air quality in UIGP whereas it favored in suppressing the aerosol level in LIGP.

Decoupling impacts of weather conditions on interannual variations in concentrations of criteria air pollutants in South China – constraining analysis uncertainties by using multiple analysis tools

Abstract. In this study, three methods, i.e., the random forest (RF) algorithm, boosted regression trees (BRTs) and the improved complete ensemble empirical-mode decomposition with adaptive noise (ICEEMDAN), were adopted for investigating emission-driven interannual variations in concentrations of air pollutants including PM2.5, PM10, O3, NO2, CO, SO2 and NO2 + O3 monitored in six cities in South China from May 2014 to April 2021. The first two methods were used to calculate the deweathered hourly concentrations, and the third one was used to calculate decomposed hourly residuals. To constrain the uncertainties in the calculated deweathered or decomposed hourly values, a self-developed method was applied to calculate the range of the deweathered percentage changes (DePCs) of air pollutant concentrations on an annual scale (each year covers May to the next April). These four methods were combined together to generate emission-driven trends and percentage changes (PCs) during the 7-year period. Consistent trends between the RF-deweathered and BRT-deweathered concentrations and the ICEEMDAN-decomposed residuals of an air pollutant in a city were obtained in approximately 70 % of a total of 42 cases (for seven pollutants in six cities), but consistent PCs calculated from the three methods, defined as the standard deviation being smaller than 10 % of the corresponding mean absolute value, were obtained in only approximately 30 % of all the cases. The remaining cases with inconsistent trends and/or PCs indicated large uncertainties produced by one or more of the three methods. The calculated PCs from the deweathered concentrations and decomposed residuals were thus combined with the corresponding range of DePCs calculated from the self-developed method to gain the robust range of DePCs where applicable. Based on the robust range of DePCs, we identified significant decreasing trends in PM2.5 concentration from 2014 to 2020 in Guangzhou and Shenzhen, which were mainly caused by the reduced air pollutant emissions and to a much lesser extent by weather perturbations. A decreasing or probably decreasing emission-driven trend was identified in Haikou and Sanya with inconsistent PCs, and a stable or no trend was identified in Zhanjiang with positive PCs. For O3, a significant increasing trend from 2014 to 2020 was identified in Zhanjiang, Shenzhen, Guangzhou and Haikou. An increasing trend in NO2 + O3 was also identified in Zhanjiang and Guangzhou and an increasing or probably increasing trend in Haikou, suggesting the contributions from enhanced formation of O3. The calculated PCs from using different methods implied that the emission changes in O3 precursors and the associated atmospheric chemistry likely played a dominant role than did the perturbations from varying weather conditions. Results from this study also demonstrated the necessity of combining multiple decoupling methods in generating emission-driven trends in atmospheric pollutants.