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Measurements of trace gaseous pollutants were taken at the Shangdianzi site, a WMO Global Atmosphere Watch (GAW) background station in Northern China. The results are presented for the period from September 2003 to December 2006. Seasonal and diurnal variations of the O<sub>3</sub>, NO<sub>x</sub>, SO<sub>2</sub>, and CO concentration are characterized and possible causes for them are discussed. The observed levels of the trace gases are comparable to those at some other background sites in polluted regions inside and outside of China. It was shown that the seasonal variation of O<sub>3</sub> can change slightly from year to year due to the year-to-year alternation in the meteorological conditions. Higher CO concentrations were observed in some warmer months, particularly in June and July, 2006. Intensive biomass burning in the North China Plain region, in combination with the transport of regional pollution by more frequent southwesterly winds, is believed to be responsible for the elevated CO concentrations. The diurnal variation of O<sub>3</sub>, with delayed peaking times, suggests that the transport of photochemical aged plume is an important source for O<sub>3</sub> at Shangdianzi. The diurnal variations of SO<sub>2</sub> in all seasons show higher values during daytime, contradicting the common view. An explanation for this unusual phenomenon is hypothesized. To gain an insight into the impact of transport on the trace gases levels at Shangdianzi, air mass backward trajectories were calculated and analyzed in combination with corresponding pollutant concentrations. The results indicate that the transport of air masses from the North China Plain region and from the major coal mining regions west of Shangdianzi is responsible for the high concentrations of the gaseous pollutants.
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The local and regional influence of elevated point sources on summertime aerosol forcing and cloud-aerosol interactions in northeastern North America was investigated using the WRF-Chem community model. The direct effects of aerosols on incoming solar radiation were simulated using existing modules to relate aerosol sizes and chemical composition to aerosol optical properties. Indirect effects were simulated by adding a prognostic treatment of cloud droplet number and adding modules that activate aerosol particles to form cloud droplets, simulate aqueous-phase chemistry, and tie a two-moment treatment of cloud water (cloud water mass and cloud droplet number) to precipitation and an existing radiation scheme. Fully interactive feedbacks thus were created within the modified model, with aerosols affecting cloud droplet number and cloud radiative properties, and clouds altering aerosol size and composition via aqueous processes, wet scavenging, and gas-phase-related photolytic processes. Comparisons of a baseline simulation with observations show that the model captured the general temporal cycle of aerosol optical depths (AODs) and produced clouds of comparable thickness to observations at approximately the proper times and places. The model overpredicted SO<sub>2</sub> mixing ratios and PM<sub>2.5</sub> mass, but reproduced the range of observed SO<sub>2</sub> to sulfate aerosol ratios, suggesting that atmospheric oxidation processes leading to aerosol sulfate formation are captured in the model. The baseline simulation was compared to a sensitivity simulation in which all emissions at model levels above the surface layer were set to zero, thus removing stack emissions. Instantaneous, site-specific differences for aerosol and cloud related properties between the two simulations could be quite large, as removing above-surface emission sources influenced when and where clouds formed within the modeling domain. When summed spatially over the finest resolution model domain (the extent of which corresponds to the typical size of a single global climate model grid cell) and temporally over a three day analysis period, total rainfall in the sensitivity simulation increased by 31% over that in the baseline simulation. Fewer optically thin clouds, arbitrarily defined as a cloud exhibiting an optical depth less than 1, formed in the sensitivity simulation. Domain-averaged AODs dropped from 0.46 in the baseline simulation to 0.38 in the sensitivity simulation. The overall net effect of additional aerosols attributable to primary particulates and aerosol precursors from point source emissions above the surface was a domain-averaged reduction of 5 W m<sup>−2</sup> in mean daytime downwelling shortwave radiation.
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A significant fraction of the organic material in aerosols is made of highly soluble compounds such as sugars (mono- and polysaccharides) and polyols such as the 2-methyltetrols, methylerythritol and methyltreitol. Because of their high solubility these compounds are considered as potentially efficient CCN material. For the 2-methyltetrols, this would have important implications for cloud formation at global scale because they are thought to be produced by the atmospheric oxidation of isoprene. To investigate this question, the complete Köhler curves for C3-C6 polyols and the 2-methyltetrols have been determined experimentally from osmolality and surface tension measurements. Contrary to what was expected, none of these compounds displayed a higher CCN efficiency than organic acids. Their Raoult terms show that this limited CCN efficiency is due to their absence of dissociation in water, this in spite of slight surface-tension effects for the 2-methyltetrols. Thus, compounds such as saccharides and polyols would not contribute more to cloud formation than other organic compounds studied so far. In particular, the presence of 2-methyltetrols in aerosols would not particularly enhance cloud formation in the atmosphere, in contrary to recently suggested.
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We present the hypothesis of homogeneous nucleation of ice nano-particles in the polar summer mesosphere. The nucleation of condensed phase is traced back to the first step on the formation pathway, which is assumed to be the transition of water vapor to amorphous cluster. Amorphous clusters then freeze into water ice, likely metastable cubic ice, when they reach the critical size. The estimates based on the equilibrium thermodynamics give the critical size (radius) of amorphous water clusters as about 1.0 nm. The same estimates for the final transition step, that is the transformation of cubic to hexagonal ice, give the critical size of about 15 nm at typical upper mesospheric conditions during the polar summer (temperature <i>T</i>=150 K, water vapor density <i>ρ</i><sub>vapor</sub>=10<sup>9</sup> cm<sup>−3</sup>).
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The concept of disjunct eddy sampling (DES) for use in measuring ecosystem-level micrometeorological fluxes is re-examined. The governing equations are discussed as well as other practical considerations and guidelines concerning this sampling method as it is applied to either the disjunct eddy covariance (DEC) or disjunct eddy accumulation (DEA) techniques. A disjunct eddy sampling system was constructed that could either be combined with relatively slow sensors (response time of 2 to 40 s) to measure fluxes using DEC, or could also be used to accumulate samples in stable reservoirs for later laboratory analysis (DEA technique). Both the DEC and DEA modes of this sampler were tested against conventional eddy covariance (EC) for fluxes of either CO<sub>2</sub> (DEC) or isoprene (DEA). Good agreement in both modes was observed relative to the EC systems. However, the uncertainty in a single DEA flux measurement was considerable (~40%) due to both the reduced statistical sampling and the analytical precision of the concentration difference measurements. We have also re-investigated the effects of nonzero mean vertical wind velocity on accumulation techniques as it relates to our DEA measurements. Despite the higher uncertainty, disjunct eddy sampling can provide an alternative technique to eddy covariance for determining ecosystem-level fluxes for species where fast sensors do not currently exist.
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In this study, NO<sub>2</sub> columns from the US EPA Models-3/CMAQ model simulations carried out using the 2001 ACE-ASIA (Asia Pacific Regional Aerosol Characterization Experiment) emission inventory over East Asia were compared with the GOME-derived NO<sub>2</sub> columns. There were large discrepancies between the CMAQ-predicted and GOME-derived NO<sub>2</sub> columns in the fall and winter seasons. In particular, while the CMAQ-predicted NO<sub>2</sub> columns produced larger values than the GOME-derived NO<sub>2</sub> columns over South Korea for all four seasons, the CMAQ-predicted NO<sub>2</sub> columns produced smaller values than the GOME-derived NO<sub>2</sub> columns over North China for all seasons with the exception of summer (summer anomaly). It is believed that there might be some error in the NO<sub>x</sub> emission estimates as well as uncertainty in the NO<sub>x</sub> chemical loss rates over North China and South Korea. Regarding the latter, this study further focused on the biogenic VOC (BVOC) emissions that were strongly coupled with NO<sub>x</sub> chemistry during summer in East Asia. This study also investigated whether the CMAQ-modeled NO<sub>2</sub>/NO<sub>x</sub> ratios with the possibly overestimated isoprene emissions were higher than those with reduced isoprene emissions. Although changes in both the NO<sub>x</sub> chemical loss rates and NO<sub>2</sub>/NO<sub>x</sub> ratios from CMAQ-modeling with the different isoprene emissions affected the CMAQ-modeled NO<sub>2</sub> levels, the effects were found to be limited, mainly due to the low absolute levels of NO<sub>2</sub> in summer. Seasonal variations of the NO<sub>x</sub> emission fluxes over East Asia were further investigated by a set of sensitivity runs of the CMAQ model. Although the results still exhibited the summer anomaly possibly due to the uncertainties in both NO<sub>x</sub>-related chemistry in the CMAQ model and the GOME measurements, it is believed that consideration of both the seasonal variations in NO<sub>x</sub> emissions and the correct BVOC emissions in East Asia are critical. Overall, it is estimated that the NO<sub>x</sub> emissions are underestimated by ~57.3% in North China and overestimated by ~46.1% in South Korea over an entire year. In order to confirm the uncertainty in NO<sub>x</sub> emissions, the NO<sub>x</sub> emissions over South Korea and China were further investigated using the ACE-ASIA, REAS (Regional Emission inventory in ASia), and CAPSS (Clean Air Policy Support System) emission inventories. The comparison between the CMAQ-calculated and GOME-derived NO<sub>2</sub> columns indicated that both the ACE-ASIA and REAS inventories have some uncertainty in NO<sub>x</sub> emissions over North China and South Korea, which can also lead to some errors in modeling the formation of ozone and secondary aerosols in South Korea and North China.
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A new one-decade (1997–2006) dataset of formaldehyde (HCHO) columns retrieved from GOME and SCIAMACHY is compared with HCHO columns simulated by an updated version of the IMAGES global chemical transport model. This model version includes an optimized chemical scheme with respect to HCHO production, where the short-term and final HCHO yields from pyrogenically emitted non-methane volatile organic compounds (NMVOCs) are estimated from the Master Chemical Mechanism (MCM) and an explicit speciation profile of pyrogenic emissions. The model is driven by the Global Fire Emissions Database (GFED) version 1 or 2 for biomass burning, whereas biogenic emissions are provided either by the Global Emissions Inventory Activity (GEIA), or by a newly developed inventory based on the Model of Emissions of Gases and Aerosols from Nature (MEGAN) algorithms driven by meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF). The comparisons focus on tropical ecosystems, North America and China, which experience strong biogenic and biomass burning NMVOC emissions reflected in the enhanced measured HCHO columns. These comparisons aim at testing the ability of the model to reproduce the observed features of the HCHO distribution on the global scale and at providing a first assessment of the performance of the current emission inventories. The high correlation coefficients (<i>r</i>>0.7) between the observed and simulated columns over most regions indicate a good consistency between the model, the implemented inventories and the HCHO dataset. The use of the MEGAN-ECMWF inventory improves the model/data agreement in almost all regions, but biases persist over parts of Africa and Australia. Although neither GFED version is consistent with the data over all regions, a better agreement is achieved over Indonesia and Southern Africa when GFEDv2 is used, but GFEDv1 succeeds better in getting the correct seasonal patterns and intensities of the fire episodes over the Amazon basin, as reflected in the significantly higher correlations calculated in this region. Although the uncertainties in the HCHO retrievals, especially over fire scenes, can be quite large, this study provides a first assessment about whether the improved methodologies and input data implemented in GFEDv2 and MEGAN-ECMWF lead to better results in the comparisons of modelled with observed HCHO column measurements.
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Ultrafine particle (UFP) number concentrations vary significantly on small spatial and temporal scales due to their short atmospheric lifetimes and multiplicity of sources. To determine UFP exposure gradients within a community, simultaneous particle number concentration measurements at a network of sites are necessary. Concurrent particle number size distribution measurements aid in identifying UFP sources, while providing data to investigate local scale effects of both photochemical and physical processes on UFP. From April to December 2007, we monitored particle number size distributions at 13 sites within 350 m–11 km of each other in the vicinity of the Ports of Los Angeles and Long Beach using Scanning Mobility Particle Sizers (SMPS). Typically, three SMPS units were simultaneously deployed and rotated among sites at 1–2 week intervals. Total particle number concentration measurements were conducted continuously at all sites. Seasonal and diurnal number size distribution patterns are complex, highly dependent on local meteorology, nearby PM sources, and times of day, and cannot be generalized over the study area nor inferred from one or two sampling locations. Spatial variation in particle number size distributions was assessed by calculating the coefficient of divergence (COD) and correlation coefficients (<i>r</i>) between site pairs. Results show an overall inverse relationship between particle size and CODs, implying that number concentrations of smaller particles (<40 nm) differ from site to site, whereas larger particles tend to have similar concentrations at various sampling locations. In addition, variations in r values as a function of particle size are not necessarily consistent with corresponding COD values, indicating that using results from correlation analysis alone may not accurately assess spatial variability.
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We have estimated changes in surface solar ultraviolet (UV) radiation under cloud free conditions in the 21st century based on simulations of 11 coupled Chemistry-Climate Models (CCMs). The total ozone columns and vertical profiles of ozone and temperature projected from CCMs were used as input to a radiative transfer model in order to calculate the corresponding erythemal irradiance levels. Time series of monthly erythemal irradiance received at the surface during local noon are presented for the period 1960 to 2100. Starting from the first decade of the 21st century, the surface erythemal irradiance decreases globally as a result of the projected stratospheric ozone recovery at rates that are larger in the first half of the 21st century and smaller towards its end. This decreasing tendency varies with latitude, being more pronounced over areas where stratospheric ozone has been depleted the most after 1980. Between 2000 and 2100 surface erythemal irradiance is projected to decrease over midlatitudes by 5 to 15%, while at the southern high latitudes the decrease is twice as much. In this study we have not included effects from changes in cloudiness, surface reflectivity and tropospheric aerosol loading, which will likely be affected in the future due to climate change. Consequently, over some areas the actual changes in future UV radiation may be different depending on the evolution of these parameters.
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The impact that changes in future climate, anthropogenic US emissions, background tropospheric composition, and land-use have on summertime regional US ozone and PM<sub>2.5</sub> concentrations is examined through a matrix of downscaled regional air quality simulations, where each set of simulations was conducted for five months of July climatology, using the Community Multi-scale Air Quality (CMAQ) model. Projected regional scale changes in meteorology due to climate change under the Intergovernmental Panel on Climate Change (IPCC) A2 scenario are derived through the downscaling of Parallel Climate Model (PCM) output with the MM5 meteorological model. Future chemical boundary conditions are obtained through downscaling of MOZART-2 (Model for Ozone and Related Chemical Tracers, version 2.4) global chemical model simulations based on the IPCC Special Report on Emissions Scenarios (SRES) A2 emissions scenario. Projected changes in US anthropogenic emissions are estimated using the EPA Economic Growth Analysis System (EGAS), and changes in land-use are projected using data from the Community Land Model (CLM) and the Spatially Explicit Regional Growth Model (SERGOM). For July conditions, changes in chemical boundary conditions are found to have the largest impact (+5 ppbv) on average daily maximum 8-h (DM8H) ozone. Changes in US anthropogenic emissions are projected to increase average DM8H ozone by +3 ppbv. Land-use changes are projected to have a significant influence on regional air quality due to the impact these changes have on biogenic hydrocarbon emissions. When climate changes and land-use changes are considered simultaneously, the average DM8H ozone decreases due to a reduction in biogenic VOC emissions (−2.6 ppbv). Changes in average 24-h (A24-h) PM<sub>2.5</sub> concentrations are dominated by projected changes in anthropogenic emissions (+3 μg m<sup>−3</sup>), while changes in chemical boundary conditions have a negligible effect. On average, climate change reduces A24-h PM<sub>2.5</sub> concentrations by −0.9 μg m<sup>−3</sup>, but this reduction is more than tripled in the Southeastern US due to increased precipitation and wet deposition.
