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The stratospheric mean-meridional circulation (MMC) and eddy mixing are compared among six meteorological reanalysis data sets: NCEP-NCAR, NCEP-CFSR, ERA-40, ERA-Interim, JRA-25, and JRA-55 for the period 1979–2012. The reanalysis data sets produced using advanced systems (i.e., NCEP-CFSR, ERA-Interim, and JRA-55) generally reveal a weaker MMC in the Northern Hemisphere (NH) compared with those produced using older systems (i.e., NCEP/NCAR, ERA-40, and JRA-25). The mean mixing strength differs largely among the data products. In the NH lower stratosphere, the contribution of planetary-scale mixing is larger in the new data sets than in the old data sets, whereas that of small-scale mixing is weaker in the new data sets. Conventional data assimilation techniques introduce analysis increments without maintaining physical balance, which may have caused an overly strong MMC and spurious small-scale eddies in the old data sets. At the NH mid-latitudes, only ERA-Interim reveals a weakening MMC trend in the deep branch of the Brewer–Dobson circulation (BDC). The relative importance of the eddy mixing compared with the mean-meridional transport in the subtropical lower stratosphere shows increasing trends in ERA-Interim and JRA-55; this together with the weakened MMC in the deep branch may imply an increasing age-of-air (AoA) in the NH middle stratosphere in ERA-Interim. Overall, discrepancies between the different variables and trends therein as derived from the different reanalyses are still relatively large, suggesting that more investments in these products are needed in order to obtain a consolidated picture of observed changes in the BDC and the mechanisms that drive them.
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Western China has experienced rapid industrialization and urbanization since the implementation of the National Western Development Strategies (the "Go West" movement) in 1999. This transition has affected the spatial and temporal characteristics of nitrogen dioxide (NO<sub>2</sub>) pollution. In this study, we analyze the trends and variability of tropospheric NO<sub>2</sub> vertical column densities (VCDs) from 2005 to 2013 over Western China, based on a wavelet analysis on monthly mean NO<sub>2</sub> data derived from the Ozone Monitoring Instrument (OMI) measurements. We focus on the anthropogenic NO<sub>2</sub> by subtracting region-specific "background" values dominated by natural sources. After removing the background influences, we find significant anthropogenic NO<sub>2</sub> growth over Western China between 2005 and 2013 (8.6 ± 0.9 % yr<sup>−1</sup> on average, relative to 2005), with the largest increments (15 % yr<sup>−1</sup> or more) over parts of several city clusters. The NO<sub>2</sub> pollution in most provincial-level regions rose rapidly from 2005 to 2011 but stabilized or declined afterwards. The NO<sub>2</sub> trends were driven mainly by changes in anthropogenic emissions, as confirmed by a nested GEOS-Chem model simulation and a comparison with Chinese official emission statistics. The rate of NO<sub>2</sub> growth during 2005–2013 reaches 11.3 ± 1.0 % yr<sup>−1</sup> over Northwestern China, exceeding the rates over Southwestern China (5.9 ± 0.6 % yr<sup>−1</sup>) and the three well-known polluted regions in the east (5.3 ± 0.8 % yr<sup>−1</sup> over Beijing-Tianjin-Hebei, 4.0 ± 0.6 % yr<sup>−1</sup> over the Yangtze River Delta, and −3.3 ± 0.3 % yr<sup>−1</sup> over the Pearl River Delta). Subsequent socioeconomic analyses suggest that the rapid NO<sub>2</sub> growth over Northwestern China is likely related to the fast developing resource- and pollution-intensive industries along with the "Go West" movement as well as relatively weak emission controls. Further efforts should be made to alleviate NO<sub><i>x</i></sub> pollution to achieve sustainable development in Western China.
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About 70 % of the anthropogenic carbon dioxide (CO<sub>2</sub>) is emitted from the megacities and urban areas of the world. In order to draw effective emission mitigation policies for combating future climate change as well as independently validating the emission inventories for constraining their large range of uncertainties, especially over major metropolitan areas of developing countries, there is an urgent need for greenhouse gas measurements over representative urban regions. India is a fast developing country, where fossil fuel emissions have increased dramatically in the last three decades and are predicted to continue to grow further by at least 6 % per year through to 2025. The CO<sub>2</sub> measurements over urban regions in India are lacking. To overcome this limitation, simultaneous measurements of CO<sub>2</sub> and carbon monoxide (CO) have been made at Ahmedabad, a major urban site in western India, using a state-of-the-art laser-based cavity ring down spectroscopy technique from November 2013 to May 2015. These measurements enable us to understand the diurnal and seasonal variations in atmospheric CO<sub>2</sub> with respect to its sources (both anthropogenic and biospheric) and biospheric sinks. The observed annual average concentrations of CO<sub>2</sub> and CO are 413.0 ± 13.7 and 0.50 ± 0.37 ppm respectively. Both CO<sub>2</sub> and CO show strong seasonality with lower concentrations (400.3 ± 6.8 and 0.19 ± 0.13 ppm) during the south-west monsoon and higher concentrations (419.6 ± 22.8 and 0.72 ± 0.68 ppm) during the autumn (SON) season. Strong diurnal variations are also observed for both the species. The common factors for the diurnal cycles of CO<sub>2</sub> and CO are vertical mixing and rush hour traffic, while the influence of biospheric fluxes is also seen in the CO<sub>2</sub> diurnal cycle. Using CO and CO<sub>2</sub> covariation, we differentiate the anthropogenic and biospheric components of CO<sub>2</sub> and found significant contributions of biospheric respiration and anthropogenic emissions in the late night (00:00–05:00 h, IST) and evening rush hours (18:00–22:00 h) respectively. We compute total yearly emissions of CO to be 69.2 ± 0.07 Gg for the study region using the observed CO : CO<sub>2</sub> correlation slope and bottom-up CO<sub>2</sub> emission inventory. This calculated emission of CO is 52 % larger than the estimated emission of CO by the emissions database for global atmospheric research (EDGAR) inventory. The observations of CO<sub>2</sub> have been compared with an atmospheric chemistry-transport model (ACTM), which incorporates various components of CO<sub>2</sub> fluxes. ACTM is able to capture the basic variabilities, but both diurnal and seasonal amplitudes are largely underestimated compared to the observations. We attribute this underestimation by the model to uncertainties in terrestrial biosphere fluxes and coarse model resolution. The fossil fuel signal from the model shows fairly good correlation with observed CO<sub>2</sub> variations, which supports the overall dominance of fossil fuel emissions over the biospheric fluxes in this urban region.</p>
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The representation of vertical velocity in chemistry climate models is a key element for the representation of the large-scale Brewer–Dobson circulation in the stratosphere. Here, we diagnose and compare the kinematic and diabatic vertical velocities in the ECHAM/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model. The calculation of kinematic vertical velocity is based on the continuity equation, whereas diabatic vertical velocity is computed using diabatic heating rates. Annual and monthly zonal mean climatologies of vertical velocity from a 10-year simulation are provided for both kinematic and diabatic vertical velocity representations. In general, both vertical velocity patterns show the main features of the stratospheric circulation, namely, upwelling at low latitudes and downwelling at high latitudes. The main difference in the vertical velocity pattern is a more uniform structure for diabatic and a noisier structure for kinematic vertical velocity. Diabatic vertical velocities show higher absolute values both in the upwelling branch in the inner tropics and in the downwelling regions in the polar vortices. Further, there is a latitudinal shift of the tropical upwelling branch in boreal summer between the two vertical velocity representations with the tropical upwelling region in the diabatic representation shifted southward compared to the kinematic case. Furthermore, we present mean age of air climatologies from two transport schemes in EMAC using these different vertical velocities and analyze the impact of residual circulation and mixing processes on the age of air. The age of air distributions show a hemispheric difference pattern in the stratosphere with younger air in the Southern Hemisphere and older air in the Northern Hemisphere using the transport scheme with diabatic vertical velocities. Further, the age of air climatology from the transport scheme using diabatic vertical velocities shows a younger mean age of air in the inner tropical upwelling branch and an older mean age in the extratropical tropopause region.
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Impervious surfaces are ubiquitous in urban environments and constitute a substrate onto which atmospheric constituents can deposit and undergo photochemical and oxidative processing, giving rise to “urban grime” films. HNO<sub>3</sub> and N<sub>2</sub>O<sub>5</sub> are important sinks for NO<sub><i>x</i></sub> in the lower atmosphere and may be deposited onto these films, forming nitrate through surface hydrolysis. Although such deposition has been considered as a net loss of NO<sub><i>x</i></sub> from the atmosphere, there is increasing evidence that surface-associated nitrate undergoes further reaction. Here, we examine the gas phase products of the photochemistry of real, field-collected urban grime using incoherent broadband cavity-enhanced absorption spectroscopy (IBBCEAS). Gas phase nitrogen oxides are emitted upon illumination of grime samples and their production increases with ambient relative humidity (RH) up to 35 % after which the production becomes independent of RH. These results are discussed in the context of water uptake onto and evaporation from grime films.
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In this study, methods are proposed to diagnose the causes of errors in air quality (AQ) modelling systems. We investigate the deviation between modelled and observed time series of surface ozone through a revised formulation for breaking down the mean square error (MSE) into bias, variance and the minimum achievable MSE (mMSE). The bias measures the accuracy and implies the existence of systematic errors and poor representation of data complexity, the variance measures the precision and provides an estimate of the variability of the modelling results in relation to the observed data, and the mMSE reflects unsystematic errors and provides a measure of the associativity between the modelled and the observed fields through the correlation coefficient. Each of the error components is analysed independently and apportioned to resolved processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) and as a function of model complexity.<br><br>The apportionment of the error is applied to the AQMEII (Air Quality Model Evaluation International Initiative) group of models, which embrace the majority of regional AQ modelling systems currently used in Europe and North America.<br><br>The proposed technique has proven to be a compact estimator of the operational metrics commonly used for model evaluation (bias, variance, and correlation coefficient), and has the further benefit of apportioning the error to the originating timescale, thus allowing for a clearer diagnosis of the processes that caused the error.
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Shipping emissions have significant influence on atmospheric environment as well as human health, especially in coastal areas and the harbour districts. However, the contribution of shipping emissions on the environment in China still need to be clarified especially based on measurement data, with the large number ownership of vessels and the rapid developments of ports, international trade and shipbuilding industry. Pollutants in the gaseous phase (carbon monoxide, sulfur dioxide, nitrogen oxides, total volatile organic compounds) and particle phase (particulate matter, organic carbon, elemental carbon, sulfates, nitrate, ammonia, metals) in the exhaust from three different diesel-engine-powered offshore vessels in China (350, 600 and 1600 kW) were measured in this study. Concentrations, fuel-based and power-based emission factors for various operating modes as well as the impact of engine speed on emissions were determined. Observed concentrations and emission factors for carbon monoxide, nitrogen oxides, total volatile organic compounds, and particulate matter were higher for the low-engine-power vessel (HH) than for the two higher-engine-power vessels (XYH and DFH); for instance, HH had NO<sub><i>x</i></sub> EF (emission factor) of 25.8 g kWh<sup>−1</sup> compared to 7.14 and 6.97 g kWh<sup>−1</sup> of DFH, and XYH, and PM EF of 2.09 g kWh<sup>−1</sup> compared to 0.14 and 0.04 g kWh<sup>−1</sup> of DFH, and XYH. Average emission factors for all pollutants except sulfur dioxide in the low-engine-power engineering vessel (HH) were significantly higher than that of the previous studies (such as 30.2 g kg<sup>−1</sup> fuel of CO EF compared to 2.17 to 19.5 g kg<sup>−1</sup> fuel in previous studies, 115 g kg<sup>−1</sup> fuel of NO<sub><i>x</i></sub> EF compared to 22.3 to 87 g kg<sup>−1</sup> fuel in previous studies and 9.40 g kg<sup>−1</sup> fuel of PM EF compared to 1.2 to 7.6 g kg<sup>−1</sup> fuel in previous studies), while for the two higher-engine-power vessels (DFH and XYH), most of the average emission factors for pollutants were comparable to the results of the previous studies, engine type was one of the most important influence factors for the differences. Emission factors for all three vessels were significantly different during different operating modes. Organic carbon and elemental carbon were the main components of particulate matter, while water-soluble ions and elements were present in trace amounts. The test inland ships and some test offshore vessels in China always had higher EFs for CO, NO<sub><i>x</i></sub>, and PM than previous studies. Besides, due to the significant influence of engine type on shipping emissions and that no accurate local EFs could be used in inventory calculation, much more measurement data for different vessels in China are still in urgent need. Best-fit engine speeds during actual operation should be based on both emission factors and economic costs.
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Urban land–atmosphere interactions can be captured by numerical modeling framework with coupled land surface and atmospheric processes, while the model performance depends largely on accurate input parameters. In this study, we use an advanced stochastic approach to quantify parameter uncertainty and model sensitivity of a coupled numerical framework for urban land–atmosphere interactions. It is found that the development of urban boundary layer is highly sensitive to surface characteristics of built terrains. Changes of both urban land use and geometry impose significant impact on the overlying urban boundary layer dynamics through modification on bottom boundary conditions, i.e., by altering surface energy partitioning and surface aerodynamic resistance, respectively. Hydrothermal properties of conventional and green roofs have different impacts on atmospheric dynamics due to different surface energy partitioning mechanisms. Urban geometry (represented by the canyon aspect ratio), however, has a significant nonlinear impact on boundary layer structure and temperature. Besides, managing rooftop roughness provides an alternative option to change the boundary layer thermal state through modification of the vertical turbulent transport. The sensitivity analysis deepens our insight into the fundamental physics of urban land–atmosphere interactions and provides useful guidance for urban planning under challenges of changing climate and continuous global urbanization.
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State-of-the-art techniques allow for rapid measurements of total OH reactivity. Unknown sinks of OH and oxidation processes in the atmosphere have been attributed to what has been termed “missing” OH reactivity. Often overlooked are the differences in timescales over which the diverse measurement techniques operate. Volatile organic compounds (VOCs) acting as sinks of OH are often measured by gas chromatography (GC) methods which provide low-frequency measurements on a timescale of hours, while sampling times are generally only a few minutes. Here, the effect of the sampling time and thus the contribution of unmeasured VOC variability on OH reactivity is investigated. Measurements of VOC mixing ratios by proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) conducted during two field campaigns (ClearfLo and PARADE) in an urban and a semi-rural environment were used to calculate OH reactivity. VOCs were selected to represent variability for different compound classes. Data were averaged over different time intervals to simulate lower time resolutions and were then compared to the mean hourly OH reactivity. The results show deviations in the range of 1 to 25 %. The observed impact of VOC variability is found to be greater for the semi-rural site.<br><br>The selected compounds were scaled by the contribution of their compound class to the total OH reactivity from VOCs based on concurrent gas chromatography measurements conducted during the ClearfLo campaign. Prior to being scaled, the variable signal of aromatic compounds results in larger deviations in OH reactivity for short sampling intervals compared to oxygenated VOCs (OVOCs). However, once scaled with their lower share during the ClearfLo campaign, this effect was reduced. No seasonal effect on the OH reactivity distribution across different VOCs was observed at the urban site.
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The spatial resolution of global climate models with interactive aerosol and the observations used to evaluate them is very different. Current models use grid spacings of ∼ 200 km, while satellite observations of aerosol use so-called pixels of ∼ 10 km. Ground site or airborne observations relate to even smaller spatial scales. We study the errors incurred due to different resolutions by aggregating high-resolution simulations (10 km grid spacing) over either the large areas of global model grid boxes ("perfect" model data) or small areas corresponding to the pixels of satellite measurements or the field of view of ground sites ("perfect" observations). Our analysis suggests that instantaneous root-mean-square (RMS) differences of perfect observations from perfect global models can easily amount to 30–160 %, for a range of observables like AOT (aerosol optical thickness), extinction, black carbon mass concentrations, PM<sub>2.5</sub>, number densities and CCN (cloud condensation nuclei). These differences, due entirely to different spatial sampling of models and observations, are often larger than measurement errors in real observations. Temporal averaging over a month of data reduces these differences more strongly for some observables (e.g. a threefold reduction for AOT), than for others (e.g. a twofold reduction for surface black carbon concentrations), but significant RMS differences remain (10–75 %). Note that this study ignores the issue of temporal sampling of real observations, which is likely to affect our present monthly error estimates. We examine several other strategies (e.g. spatial aggregation of observations, interpolation of model data) for reducing these differences and show their effectiveness. Finally, we examine consequences for the use of flight campaign data in global model evaluation and show that significant biases may be introduced depending on the flight strategy used.
