We analyzed satellite observations of nitrogen dioxide (NO2) columns by the Ozone Monitoring Instrument (OMI) over China from 2005 to 2010 in order to estimate the top-down anthropogenic nitrogen oxides (NOx) emission trends. Since NOx emissions were affected by the economic slowdown in 2009, we removed one year of abnormal data in the analysis. The estimated average emission trend is 4.01 ± 1.39% yr(-1), which is slower than the trend of 5.8-10.8% yr(-1) reported for previous years. We find large regional, seasonal, and urban-rural variations in emission trends. The average NOx emission trend of 3.47 ± 1.07% yr(-1) in warm season (June-September) is less than the trend of 5.03 ± 1.92% yr(-1) in cool season (October-May). The regional annual emission trends decrease from 4.76 ± 1.61% yr(-1) in North China Plain to 3.11 ± 0.98% yr(-1) in Yangtze River Delta and further down to -4.39 ± 1.81% yr(-1) in Pearl River Delta. The annual emission trends of the four largest megacities, Shanghai, Beijing, Guangzhou, and Shenzhen are -0.76 ± 0.29%, 0.69 ± 0.27%, -4.46 ± 1.22%, and -7.18 ± 2.88% yr(-1), considerably lower than the regional averages or surrounding rural regions. These results appear to suggest that a number of factors, including emission control measures of thermal power plants, increased hydro-power usage, vehicle emission regulations, and closure or migration of high-emission industries, have significantly reduced or even reversed the increasing trend of NOx emissions in more economically developed megacities and southern coastal regions, but their effects are not as significant in other major cities or less economically developed regions.

Inverse modeling using satellite observations of nitrogen dioxide (NO 2 ) columns has been extensively used to estimate nitrogen oxides (NO x ) emissions in China. Recently, the Global Ozone Monitoring Experiment-2 (GOME-2) and Ozone Monitoring Instrument (OMI) provide independent global NO 2 column measurements on a nearly daily basis at around 9:30 and 13:30 local time across the equator, respectively. Anthropogenic NO x emission estimates by applying previously developed monthly inversion (MI) or daily inversion (DI) methods to these two sets of measurements show substantial differences. We improve the DI method by conducting model simulation, satellite retrieval, and inverse modeling sequentially on a daily basis. After each inversion, we update anthropogenic NO x emissions in the model simulation with the newly obtained a posteriori results. Consequently, the inversion-optimized emissions are used to compute the a priori NO 2 profiles for satellite retrievals. As such, the a priori profiles used in satellite retrievals are now coupled to inverse modeling results. The improved procedure was applied to GOME-2 and OMI NO 2 measurements in 2011. The new daily retrieval-inversion (DRI) method estimates an average NO x emission of 6.9 Tg N/yr over China, and the difference between using GOME-2 and OMI measurements is 0.4 Tg N/yr, which is significantly smaller than the difference of 1.3 Tg N/yr using the previous DI method. Using the more consistent DRI inversion results, we find that anthropogenic NO x emissions tend to be higher in winter and summer than spring (and possibly fall) and the weekday-to-weekend emission ratio tends to increase with NO x emission in China.

Abstract. Long-range transport followed by deposition of black carbon on glaciers of Tibet is one of the key issues of climate research as it induces changes on radiative forcing and subsequently impacting the melting of glaciers. The transport mechanism, however, is not well understood. In this study, we use short-lived reactive aromatics as proxies to diagnose transport of pollutants to Tibet. In situ observations of short-lived reactive aromatics across the Tibetan Plateau are analyzed using a regional chemistry and transport model. The model performance using the current emission inventories over the region is poor due to problems in the inventories and model transport. Top-down emissions constrained by satellite observations of glyoxal are a factor of 2–6 higher than the a priori emissions over the industrialized Indo-Gangetic Plain. Using the top-down emissions, agreement between model simulations and surface observations of aromatics improves. We find enhancements of reactive aromatics over Tibet by a factor of 6 on average due to rapid transport from India and nearby regions during the presence of a high-altitude cut-off low system. Our results suggest that the cut-off low system is a major pathway for long-range transport of pollutants such as black carbon. The modeling analysis reveals that even the state-of-the-science high-resolution reanalysis cannot simulate this cut-off low system accurately, which probably explains in part the underestimation of black carbon deposition over Tibet in previous modeling studies. Another model deficiency of underestimating pollution transport from the south is due to the complexity of terrain, leading to enhanced transport. It is therefore challenging for coarse-resolution global climate models to properly represent the effects of long-range transport of pollutants on the Tibetan environment and the subsequent consequence for regional climate forcing.

An often used assumption in air pollution studies is a well‐mixed boundary layer (BL), where pollutants are evenly distributed. Because of the difficulty in obtaining vertically resolved measurements, the validity of the assumption has not been thoroughly evaluated. In this study, we use more than 200 vertical profiles observed in the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER‐AQ) aircraft campaign in July 2011 to examine the vertical distributions of pollutants over the Washington‐Baltimore area. While many long‐lived species are well mixed in daytime, the observed average vertical profile of NOx shows a large negative gradient with increasing altitude in the BL. Our analysis suggests that the magnitude of the NOx gradient is highly sensitive to atmospheric stability. We investigate how parameterizations of the BL and land‐surface processes impact vertical profiles in a 1‐D chemical transport model, using three BL schemes (Asymmetric Convective Model version 2 (ACM2), Yonsei University (YSU), and Mellor‐Yamada‐Janjic (MYJ)) and two land‐surface schemes (Noah and Rapid Update Cycle (RUC)). The model reasonably reproduces the median vertical profiles of NOx under different BL stability conditions within 30% of observations, classified based on potential temperature gradient and BL height. Comparisons with NOx observations for individual vertical profiles reveal that while YSU performs better in the turbulent and deep BL case, in general, ACM2 (RMSE = 2.0 ppbv) outperforms YSU (RMSE = 2.5 ppbv) and MYJ (RMSE = 2.2 ppbv). Results also indicate that the land‐surface schemes in the Weather Research and Forecasting (WRF) model have a small impact on the NOx gradient. Using model simulations, we analyze the impact of BL NOx gradient on the calculation of the ozone production rate and satellite NO2 retrieval. We show that using surface measurements and the well‐mixed BL assumption causes a ~45% high bias in the estimated BL ozone production rate and that the variability of NO2 vertical profiles is responsible for 5–10% variability in the retrieved NO2 tropospheric vertical columns.

Ground-based surveys of three coal fires and airborne surveys of two of the fires were conducted near Sheridan, Wyoming. The fires occur in natural outcrops and in abandoned mines, all containing Paleocene-age subbituminous coals. Diffuse (carbon dioxide (CO(2)) only) and vent (CO(2), carbon monoxide (CO), methane, hydrogen sulfide (H(2)S), and elemental mercury) emission estimates were made for each of the fires. Additionally, gas samples were collected for volatile organic compound (VOC) analysis and showed a large range in variation between vents. The fires produce locally dangerous levels of CO, CO(2), H(2)S, and benzene, among other gases. At one fire in an abandoned coal mine, trends in gas and tar composition followed a change in topography. Total CO(2) fluxes for the fires from airborne, ground-based, and rate of fire advancement estimates ranged from 0.9 to 780mg/s/m(2) and are comparable to other coal fires worldwide. Samples of tar and coal-fire minerals collected from the mouth of vents provided insight into the behavior and formation of the coal fires.

Abstract. With the improved spatial resolution of the Ozone Monitoring Instrument (OMI) over earlier instruments and more than 10 years of service, tropospheric NO 2 retrievals from OMI have led to many influential studies on the relationships between socioeconomic activities and NO x emissions. Previous studies have shown that the OMI NO 2 data show different relative trends compared to in situ measurements. However, the sources of the discrepancies need further investigations. This study focuses on how to appropriately compare relative trends derived from OMI and in situ measurements. We retrieve OMI tropospheric NO 2 vertical column densities (VCDs) and obtain the NO 2 seasonal trends over the United States, which are compared with coincident in situ surface NO 2 measurements from the Air Quality System (AQS) network. The Mann-Kendall method with Sen's slope estimator is applied to derive the NO 2 seasonal and annual trends for four regions at coincident sites during 2005-2014. The OMI-based NO 2 seasonal relative decreasing trends are generally biased low compared to the in situ trends by up to 3.7 % yr −1 , except for the underestimation in the US Midwest and Northeast during December, January, and February (DJF). We improve the OMI retrievals for trend analysis by removing the ocean trend, using the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo data in air mass factor (AMF) calculation. We apply a lightning flash filter to exclude lightning-affected data to make proper comparisons. These data processing procedures result in close agreement (within 0.3 % yr −1 ) between in situ and OMI-based NO 2 regional annual relative trends. The remaining discrepancies may result from inherent difference between trends of NO 2 tropospheric VCDs and surface concentrations, different spatial sampling of the measurements, chemical nonlinearity, and tropospheric NO 2 profile changes. We recommend that future studies apply these procedures (ocean trend removal and MODIS albedo update) to ensure the quality of satellite-based NO 2 trend analysis and apply the lightning filter in studying surface NO x emission changes using satellite observations and in comparison with the trends derived from in situ NO 2 measurements. With these data processing procedures, we derive OMI-based NO 2 regional annual relative trends using all available data for the US West (−2.0 % ± 0.3 yr −1 ), Midwest (−1.8 % ± 0.4 yr −1 ), Northeast (−3.1 % ± 0.5 yr −1 ), and South (−0.9 % ± 0.3 yr −1 ). The OMI-based annual mean trend over the contiguous United States is −1.5 % ± 0.2 yr −1 . It is a factor of 2 lower than that of the AQS in situ data (−3.9 % ± 0.4 yr −1 ); the difference is mainly due to the fact that the locations of AQS sites are concentrated in urban and suburban regions.

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Abstract. Satellite observations of nitrogen dioxide (NO 2 ) have often been used to derive nitrogen oxides (NO x = NO + NO 2 ) emissions. A widely used inversion method was developed by Martin et al. (2003). Refinements of this method were subsequently developed. In the context of this inversion method, we show that the local derivative (of a first-order Taylor expansion) is more appropriate than the "bulk ratio" (ratio of emission to column) used in the original formulation for polluted regions. Using the bulk ratio can lead to biases in regions of high NO x emissions such as eastern China due to chemical non-linearity. Inverse modelling using the local derivative method is applied to both GOME-2 and OMI satellite measurements to estimate anthropogenic NO x emissions over eastern China. Compared with the traditional method using bulk ratio, the local derivative method produces more consistent NO x emission estimates between the inversion results using GOME-2 and OMI measurements. The results also show significant changes in the spatial distribution of NO x emissions, especially over high emission regions of eastern China. We further discuss a potential pitfall of using the difference of two satellite measurements to derive NO x emissions. Our analysis suggests that chemical non-linearity needs to be accounted for and that a careful bias analysis is required in order to use the satellite differential method in inverse modelling of NO x emissions.