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Tropospheric NO 2 and SO 2 concentrations are of great importance with regard to air quality, atmospheric chemistry, and climate change. Due to lack of surface monitoring stations, this study analyzes long term trend of NO 2 and SO 2 levels (2005–2014), retrieved from Ozone Monitoring Instrument (OMI) board on the NASA's Aura satellite, in an important region of China – Henan Province. Henan Province, located in North China Plain, has encountered serious air pollution problems including extremely high PM 2.5 concentrations and as one of the most polluted region in China. The satellite spatial images clearly show that high levels of both NO 2 and SO 2 are concentrated in north and northeastern regions with much lower levels observed in other parts of Henan. Both pollutants exhibit the highest levels in winter with the least in summer/spring. The temporal trend analysis based on moving average of deseasonalized and decyclic data indicates that for NO 2 , there is a continuous increasing pattern from 2005 to 2011 at 6.4% per year, thereafter, it shows a decreasing trend (10.6% per year). As for SO 2 , the increasing trend is about 16% per year from 2005 to 2007 with decreasing rate 7% per year from 2007 to 2014. The economic development with incredible annual 11% GDP growth in Henan is responsible for increasing levels of NO 2 and SO 2 . The observed decreasing SO 2 level starting in 2007 is due to reduced SO 2 emission, utilization of flue gas desulfurization (FGD) devices and to some extent, in preparation of Beijing 2008 Olympic Games. On the other hand, increasing vehicle numbers (155% from 2006 to 2012) and coal consumption (37% during the same span), along with the lack of denitration process for removing flue/exhaust gas NO x are responsible for increasing NO 2 trend until 2011. The ratio of SO 2 /NO 2 started decreasing in 2007 and dropped significantly from 2011 to 2013 indicating good performance of FGD and ever increasing NO x contribution from mobile sources. Unlike those observed in developed countries (US, EU and Japan) where a decreasing trend for both SO 2 and NO 2 has been observed since 1990s, the observed upward and downward trend found in Henan is similar to those found in North China Plain and other parts of China. The spatial and temporal trend analyses of SO 2 and NO 2 in four other regions in Henan further indicate a similar trend to those observed in Henan Province, albeit with different increasing and decreasing rate. The results provide regulatory agency to develop action plans to combat air pollution problem in general and SO 2 and NO 2 problems in particular in Henan. The implications of our findings and recommendations for decision makers are discussed in the paper. [ABSTRACT FROM AUTHOR]

Abstract: Land use regression (LUR) models are widely employed in health studies to characterize chronic exposure to air pollution. The LUR is essentially an interpolation technique that employs the pollutant of interest as the dependent variable with proximate land use, traffic, and physical environmental variables used as independent predictors. Two major limitations with this method have not been addressed: (1) variable selection in the model building process, and (2) dealing with unbalanced repeated measures. In this paper, we address these issues with a modeling framework that implements the deletion/substitution/addition (DSA) machine learning algorithm that uses a generalized linear model to average over unbalanced temporal observations. Models were derived for fine particulate matter with aerodynamic diameter of 2.5 microns or less (PM2.5) and nitrogen dioxide (NO2) using monthly observations. We used 4119 observations at 108 sites and 15,301 observations at 138 sites for PM2.5 and NO2, respectively. We derived models with good predictive capacity (cross-validated-R 2 values were 0.65 and 0.71 for PM2.5 and NO2, respectively). By addressing these two shortcomings in current approaches to LUR modeling, we have developed a framework that minimizes arbitrary decisions during the model selection process. We have also demonstrated how to integrate temporally unbalanced data in a theoretically sound manner. These developments could have widespread applicability for future LUR modeling efforts. [Copyright &y& Elsevier]

This paper represents, for the first time, scientific data as a part of monitoring air quality in the city of Split. The city has a problem with the air pollution mostly caused by anthropogenic activities and partly by natural origin activities. This study presents results of monthly and seasonal variations of NO2, SO2 and black-smoke as well as the influence of meteorological parameters on observed concentration levels. Average seasonal values for SO2 ranged from 22.54 to 54.81 gg m-3, for NO2 from 48.24 to 56.38 gg m-3 and for black-smoke from 4.15 to 5.64/µg m-3. The results obtained for SO2 and black-smoke were below, while for NO2 were above the limit value of pollutants in the air recommended by Croatian Government (Air Protection Act (OG 178/04); Regulation on limit values of pollutants in air (OG 133/05)). As the result of stable meteorological conditions (high temperatures and drought), the increase in SO2 concentration was significant in summer period, while the concentrations of NO2 and black-smoke were not significantly changed during year and did not depend on other parameters. [ABSTRACT FROM AUTHOR]

We present an assessment of the impacts on atmospheric composition and radiative forcing of short‐lived pollutants following a worldwide decrease in anthropogenic activity and emissions comparable to what has occurred in response to the COVID‐19 pandemic, using the global composition‐climate model United Kingdom Chemistry and Aerosols Model (UKCA). Emission changes reduce tropospheric hydroxyl radical and ozone burdens, increasing methane lifetime. Reduced SO2 emissions and oxidizing capacity lead to a decrease in sulfate aerosol and increase in aerosol size, with accompanying reductions to cloud droplet concentration. However, large reductions in black carbon emissions increase aerosol albedo. Overall, the changes in ozone and aerosol direct effects (neglecting aerosol‐cloud interactions which were statistically insignificant but whose response warrants future investigation) yield a radiative forcing of −33 to −78 mWm−2. Upon cessation of emission reductions, the short‐lived climate forcers rapidly return to pre‐COVID levels; meaning, these changes are unlikely to have lasting impacts on climate assuming emissions return to pre‐intervention levels. Plain Language Summary: As a result of the global COVID‐19 pandemic, unprecedented lockdown measures have been imposed worldwide to reduce the spread of the disease, causing huge reductions in economic activity and corresponding reductions in transport, industrial, and aircraft emissions. As well as lowering emissions of greenhouse gases, such as carbon dioxide, this has resulted in a dramatic reduction in the emissions of pollutants that also affect climate. In this study, we have used state‐of‐the‐art computer simulations to quantify how changes in these components are likely to impact the chemical make‐up of the atmosphere and the likely short‐term impacts on climate. Despite large decreases in nitrogen dioxide and atmospheric particles, we find these changes result in a very small impact on the energy balance of the atmosphere but one that would act to cool the planet, without considering the knock‐on impacts on clouds (which we cannot be confident about). However, these effects are all likely to be short‐lived if emissions return to pre‐lockdown levels. Key Points: Emission reductions are likely to have led to a global reduction in short‐lived climate forcers and tropospheric oxidizing capacityReductions in O3 and aerosol from both lower emissions and decreased sulfate oxidation resulted in a net negative radiative forcingThe radiative impacts are small and short‐lived. Longer term climate impacts must come through future sustained emission reductions [ABSTRACT FROM AUTHOR]

Global observations of tropospheric nitrogen dioxide (NO2) columns have been shown to be feasible from space, but consistent multi-sensor records do not yet exist, nor are they covered by planned activities at the international level. Harmonised, multi-decadal records of NO2 columns and their associated uncertainties can provide crucial information on how the emissions and concentrations of nitrogen oxides evolve over time. Here we describe the development of a new, community best-practice NO2 retrieval algorithm based on a synthesis of existing approaches. Detailed comparisons of these approaches led us to implement an enhanced spectral fitting method for NO2 , a 1 ∘ × 1 ∘ TM5-MP data assimilation scheme to estimate the stratospheric background and improve air mass factor calculations. Guided by the needs expressed by data users, producers, and WMO GCOS guidelines, we incorporated detailed per-pixel uncertainty information in the data product, along with easily traceable information on the relevant quality aspects of the retrieval. We applied the improved QA4ECV NO2 algorithm to the most current level-1 data sets to produce a complete 22-year data record that includes GOME (1995–2003), SCIAMACHY (2002–2012), GOME-2(A) (2007 onwards) and OMI (2004 onwards). The QA4ECV NO2 spectral fitting recommendations and TM5-MP stratospheric column and air mass factor approach are currently also applied to S5P-TROPOMI. The uncertainties in the QA4ECV tropospheric NO2 columns amount to typically 40 % over polluted scenes. The first validation results of the QA4ECV OMI NO2 columns and their uncertainties over Tai'an, China, in June 2006 suggest a small bias (- 2 %) and better precision than suggested by uncertainty propagation. We conclude that our improved QA4ECV NO2 long-term data record is providing valuable information to quantitatively constrain emissions, deposition, and trends in nitrogen oxides on a global scale. [ABSTRACT FROM AUTHOR]

Anthropogenic emissions of sulfur dioxide (SO), nitrogen dioxide (NO), and carbon monoxide (CO) exert significant influence on local and regional atmospheric chemistry. Temporal and spatial variability of these gases are investigated using surface measurements by the Central Pollution Control Board (India) during 2005-2009 over six urban locations in and around the Indo-Gangetic Plain (IGP) and supported using the satellite measurements of these gases. The stations chosen are Jodhpur (west of IGP), Delhi (central IGP), Kolkata and Durgapur (eastern IGP), Guwahati (east of IGP), and Nagpur (south of IGP). Among the stations studied, SO concentrations are found to be the highest over Kolkata megacity. Elevated levels of NO occur over the IGP stations of Durgapur, Kolkata, and Delhi. Columnar NO values are also found to be elevated over these regions during winter due to high surface concentrations while columnar SO values show a monsoon maximum. Elevated columnar CO over Guwahati during pre-monsoon are attributed to biomass burning. Statistically significant correlations between columnar NO and surface NO obtained for Delhi, Kolkata, and Durgapur along with very low SO to NO ratios (≤0.2) indicate fossil fuel combustion from mobile sources as major contributors to the ambient air over these regions. [ABSTRACT FROM AUTHOR]

The article offers information on the study based on the presence of Nitrogen Dioxide in atmosphere of North Caucasus. It mentions that the Kislovodsk high mountain scientific station of the Institute of Atmospheric Physics, Russian Academy of Sciences, Russia, was used for the research. It includes that total content of NO2 was measured on the basis of direct solar irradiance over slope pathways. It also adds that the study analyzed the several characteristic of the NO2 TC time variations related to variations in the atmospheric state, volcanic eruptions, quasi-biannual oscillations of the tropical circulation (QBO) and the ElNiño effect.