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An estimation of the 18O / 16O ratio of UT/LMS ozone based on artefact CO in air sampled during CARIBIC flights

An issue of O3-driven artefact production of O3 in the upper troposphere/lowermost stratosphere (UT/LMS) air analysed in the CARIBIC-1 project is being discussed. By confronting the CO mixing and isotope ratios obtained from different analytical instrumentation, we (i) reject natural/artificial sampling and mixing effects as possible culprits of the problem, (ii) ascertain the chemical nature and quantify the strength of the contamination, and (iii) demonstrate successful application of the isotope mass-balance calculations for inferring the isotope composition of the contamination source. The δ18O values of the latter indicate that the oxygen is very likely being inherited from O3. The δ13C values hint at reactions of trace amounts of organics with stratospheric O3 that could have yielded the artificial CO. While the exact contamination mechanism is not known, it is clear that the issue pertains only to the earlier (first) phase of the CARIBIC (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container) project. Finally, estimated UT/LMS ozone δ18O values are lower than those observed in the stratosphere within the same temperature range, suggesting that higher pressures (240–270 hPa) imply lower isotope fractionation controlling the local δ18O(O3) value.
Sources of humic-like substances in the Pearl River Delta, China: positive matrix factorization analysis of PM2.5 major components and source markers

Humic-like substances (HULIS), the hydrophobic part of water-soluble organic carbon (WSOC), account for a significant fraction of PM2.5 mass. Their source studies are so far largely qualitative. In this study, HULIS and WSOC were determined in 100 PM2.5 samples collected in 2009 at an urban site (Guangzhou) and a suburban site (Nansha) in the Pearl River Delta in South China. The annual average concentration of HULIS was 4.83 and 4.71 μg m−3, constituting 8.5 and 10.2% of the PM2.5 mass, while HULIS-C (the carbon component of HULIS) contributed 48 and 57% of WSOC at the two sites, respectively. HULIS were found to correlate with biomass burning (BB) tracers (i.e., levoglucosan and K) and secondary species (e.g., SO42− and NH4+), suggesting its association with BB emissions and secondary formation processes. Sources of HULIS were investigated using positive matrix factorization analysis of PM2.5 chemical composition data, including major components and source markers. In addition to secondary formation process and BB emissions, residual oil combustion related to shipping was identified for the first time as a significant source of HULIS. Secondary formation process contributed the most, accounting for 49–82% of ambient HULIS at the two sites in different seasons. BB emissions contributed a seasonal average of 8–28%, with more contributions observed in the winter months (November–February) due to crop residue burning during harvest season. Residual oil combustion was revealed to be an important source at the suburban site in summer (44% of HULIS-C) due to its proximity to one of the ports and the shipping lane in the region. Vehicle emissions were found to contribute little to HULIS, but had contributions to the hydrophilic WSOC fraction. The contrast in contributions from different combustion sources to HULIS and hydrophilic WSOC suggests that primary sources of HULIS are linked to inefficient combustion. This source analysis suggests further study of HULIS be focused on secondary formation process and source characteristics of HULIS from BB and residual oil combustion.
Investigation of secondary formation of formic acid: urban environment vs. oil and gas producing region

Formic acid (HCOOH) is one of the most abundant carboxylic acids in the atmosphere. However, current photochemical models cannot fully explain observed concentrations and in particular secondary formation of formic acid across various environments. In this work, formic acid measurements made at an urban receptor site (Pasadena) in June–July 2010 during CalNex (California Research at the Nexus of Air Quality and Climate Change) and a site in an oil and gas producing region (Uintah Basin) in January–February 2013 during UBWOS 2013 (Uintah Basin Winter Ozone Studies) will be discussed. Although the VOC (volatile organic compounds) compositions differed dramatically at the two sites, measured formic acid concentrations were comparable: 2.3 ± 1.3 in UBWOS 2013 and 2.0 ± 1.0 ppb in CalNex. We determine that concentrations of formic acid at both sites were dominated by secondary formation (> 99%). A constrained box model using the Master Chemical Mechanism (MCM v3.2) underestimates the measured formic acid concentrations drastically at both sites (by a factor of > 10). Compared to the original MCM model that includes only ozonolysis of unsaturated organic compounds and OH oxidation of acetylene, when we updated yields of ozonolysis of alkenes and included OH oxidation of isoprene, vinyl alcohol chemistry, reaction of formaldehyde with HO2, oxidation of aromatics, and reaction of CH3O2 with OH, the model predictions for formic acid were improved by a factor of 6.4 in UBWOS 2013 and 4.5 in CalNex, respectively. A comparison of measured and modeled HCOOH/acetone ratios is used to evaluate the model performance for formic acid. We conclude that the modified chemical mechanism can explain 19 and 45% of secondary formation of formic acid in UBWOS 2013 and CalNex, respectively. The contributions from aqueous reactions in aerosol and heterogeneous reactions on aerosol surface to formic acid are estimated to be 0–6 and 0–5% in UBWOS 2013 and CalNex, respectively. We observe that air–snow exchange processes and morning fog events may also contribute to ambient formic acid concentrations during UBWOS 2013 (~ 20% in total). In total, 53–59 in UBWOS 2013 and 50–55% in CalNex of secondary formation of formic acid remains unexplained. More work on formic acid formation pathways is needed to reduce the uncertainties in the sources and budget of formic acid and to narrow the gaps between measurements and model results.
Effect of biomass burning over the western North Pacific Rim: wintertime maxima of anhydrosugars in ambient aerosols from Okinawa

Biomass burning (BB) largely modifies the chemical composition of atmospheric aerosols on the globe. We collected aerosol samples (TSP) at Cape Hedo, on subtropical Okinawa Island, from October 2009 to February 2012 to study anhydrosugars as BB tracers. Levoglucosan was detected as the dominant anhydrosugar followed by its isomers, mannosan and galactosan. We found a clear seasonal trend of levoglucosan and mannosan with winter maxima and summer minima. Positive correlation was found between levoglucosan and nss-K+ (r = 0.38, p < 0.001); the latter is another BB tracer. The analyses of air mass trajectories and fire spots demonstrated that the seasonal variations of anhydrosugars are caused by long-range transport of BB emissions from the Asian continent. We found winter maxima of anhydrosugars, which may be associated with open burning and domestic heating and cooking in northern and northeastern China, Mongolia and Russia and with the enhanced westerly winds. The monthly averaged levoglucosan / mannosan ratios were lower (2.1–4.8) in May–June and higher (13.3–13.9) in November–December. The lower values may be associated with softwood burning in northern China, Korea and southwestern Japan whereas the higher values are probably caused by agricultural waste burning of maize straw in the North China Plain. Anhydrosugars comprised 0.22% of water-soluble organic carbon (WSOC) and 0.13% of organic carbon (OC). The highest values to WSOC (0.37%) and OC (0.25%) were found in winter, again indicating an important BB contribution to Okinawa aerosols in winter. This study provides useful information to better understand the effect of East Asian biomass burning on the air quality in the western North Pacific Rim.
A comparison study between CMAQ-simulated and OMI-retrieved NO2 columns over East Asia for evaluation of NOx emission fluxes of INTEX-B, CAPSS, and REAS inventories

Comparison between the CMAQ (Community Multi-scale Air Quality Model)-calculated and OMI (Ozone Monitoring Instrument)-retrieved tropospheric NO2 columns was carried out for 2006 over East Asia (100–150° E; 20–50° N) to evaluate the bottom-up NOx emission fluxes of INTEX-B, CAPSS, and REAS v1.11 inventories. The three emission inventories were applied to the CMAQ model simulations for the countries of China, South Korea, and Japan, respectively. For the direct comparison between the two NO2 columns, the averaging kernels (AKs) obtained from the Royal Netherlands Meteorological Institute (KNMI)/DOMINO v2.0 daily product were applied to the CMAQ-simulated data. The analysis showed that the two tropospheric NO2 columns from the CMAQ model simulations and OMI observations (ΩCMAQ,AK and ΩOMI) had good spatial and seasonal correlation, with correlation coefficients ranging from 0.71 to 0.96. In addition, the normalized mean errors (NMEs) between the ΩCMAQ,AK and ΩOMI were found to range from ~ 40 to ~ 63%. The ΩCMAQ,AK were, on annual average, ~ 28% smaller (in terms of the NMEs) than the ΩOMI, indicating that the NOx emissions used were possibly underestimated in East Asia. Large absolute differences between the ΩCMAQ,AK and ΩOMI were found, particularly over central eastern China (CEC) during winter (annual averaged mean error of ~ 4.51 × 1015 molecules cm−2). Although such differences between the ΩCMAQ,AK and ΩOMI are likely caused by the errors and biases in the NOx emissions used in the CMAQ model simulations, it can be rather difficult to quantitatively relate the differences to the accuracy of the NOx emissions, because there are also several uncertain factors in the CMAQ model, satellite-retrieved NO2 columns and AK products, and NOx and other trace gas emissions. In this context, three uncertain factors were selected and analyzed with sensitivity runs (monthly variations in NOx emissions; influences of different NOx emission fluxes; and reaction probability of N2O5 radicals). Other uncertain or possible influential factors were also discussed to suggest future direction of the study.
Time-dependent freezing rate parcel model

The time-dependent freezing rate (TDFR) model here described represents the formation of ice particles by immersion freezing within an air parcel. The air parcel trajectory follows an adiabatic ascent and includes a period in time when the parcel remains stationary at the top of its ascent. The description of the ice nucleating particles (INPs) in the air parcel is taken from laboratory experiments with cloud and precipitation samples and is assumed to represent the INP content of the cloud droplets in the parcel. Time dependence is included to account for variations in updraft velocity and for the continued formation of ice particles under isothermal conditions. The magnitudes of these factors are assessed on the basis of laboratory measurements. Results show that both factors give rise to three-fold variations in ice concentration for a realistic range of the input parameters. Refinements of the parameters specifying time dependence and INP concentrations are needed to make the results more specific to different atmospheric aerosol types. The simple model framework described in this paper can be adapted to more elaborate cloud models. The results here presented can help guide decisions on whether to include a time-dependent ice nucleation scheme or a simpler singular description in models.
Greenhouse gas network design using backward Lagrangian particle dispersion modelling – Part 2: Sensitivity analyses and South African test case

This is the second part of a two-part paper considering a measurement network design based on a stochastic Lagrangian particle dispersion model (LPDM) developed by Marek Uliasz, in this case for South Africa. A sensitivity analysis was performed for different specifications of the network design parameters which were applied to this South African test case. The LPDM, which can be used to derive the sensitivity matrix used in an atmospheric inversion, was run for each candidate station for the months of July (representative of the Southern Hemisphere winter) and January (summer). The network optimisation procedure was carried out under a standard set of conditions, similar to those applied to the Australian test case in Part 1, for both months and for the combined 2 months, using the incremental optimisation (IO) routine. The optimal network design setup was subtly changed, one parameter at a time, and the optimisation routine was re-run under each set of modified conditions and compared to the original optimal network design. The assessment of the similarity between network solutions showed that changing the height of the surface grid cells, including an uncertainty estimate for the ocean fluxes, or increasing the night-time observation error uncertainty did not result in any significant changes in the positioning of the stations relative to the standard design. However, changing the prior flux error covariance matrix, or increasing the spatial resolution, did. Large aggregation errors were calculated for a number of candidate measurement sites using the resolution of the standard network design. Spatial resolution of the prior fluxes should be kept as close to the resolution of the transport model as the computing system can manage, to mitigate the exclusion of sites which could potentially be beneficial to the network. Including a generic correlation structure in the prior flux error covariance matrix led to pronounced changes in the network solution. The genetic algorithm (GA) was able to find a marginally better solution than the IO procedure, increasing uncertainty reduction by 0.3 %, but still included the most influential stations from the standard network design. In addition, the computational cost of the GA compared to IO was much higher. Overall the results suggest that a good improvement in knowledge of South African fluxes is available from a feasible atmospheric network, and that the general features of this network are invariable under several reasonable choices in a network design study.
Heterogeneous chemistry: a mechanism missing in current models to explain secondary inorganic aerosol formation during the January 2013 haze episode in North China

Severe regional haze pollution events occurred in eastern and central China in January 2013, which had adverse effects on the environment and public health. Extremely high levels of particulate matter with aerodynamic diameter of 2.5 μm or less (PM2.5) with dominant components of sulfate and nitrate are responsible for the haze pollution. Although heterogeneous chemistry is thought to play an important role in the production of sulfate and nitrate during haze episodes, few studies have comprehensively evaluated the effect of heterogeneous chemistry on haze formation in China by using the 3-D models due to of a lack of treatments for heterogeneous reactions in most climate and chemical transport models. In this work, the WRF-CMAQ model with newly added heterogeneous reactions is applied to East Asia to evaluate the impacts of heterogeneous chemistry and the meteorological anomaly during January 2013 on regional haze formation. As the parameterization of heterogeneous reactions on different types of particles is not well established yet, we arbitrarily selected the uptake coefficients from reactions on dust particles and then conducted several sensitivity runs to find the value that can best match observations. The revised CMAQ with heterogeneous chemistry not only captures the magnitude and temporal variation of sulfate and nitrate, but also reproduces the enhancement of relative contribution of sulfate and nitrate to PM2.5 mass from clean days to polluted haze days. These results indicate the significant role of heterogeneous chemistry in regional haze formation and improve the understanding of the haze formation mechanisms during the January 2013 episode.
Characterization of road freight transportation and its impact on the national emission inventory in China

Diesel trucks are major contributors of nitrogen oxides (NOx) and primary particulate matter smaller than 2.5 μm (PM2.5) in the transportation sector. However, there are more obstacles to existing estimations of diesel-truck emissions compared with those of cars. The obstacles include both inappropriate methodology and missing basic data in China. According to our research, a large number of trucks are conducting long-distance intercity or interprovincial transportation. Thus, the method used by most existing inventories, based on local registration number, is inappropriate. A road emission intensity-based (REIB) approach is introduced in this research instead of registration-population-based approach. To provide efficient data for the REIB approach, 1060 questionnaire responses and approximately 1.7 million valid seconds of onboard GPS monitoring data were collected in China. The estimated NOx and PM2.5 emissions from diesel freight trucks in China were 5.0 (4.8–7.2) million tonnes and 0.20 (0.17–0.22) million tonnes, respectively, in 2011. The province-based emission inventory is also established using the REIB approach. It was found that the driving conditions on different types of road have significant impacts on the emission levels of freight trucks. The largest differences among the emission factors (in g km−1) on different roads exceed 70 and 50% for NOx and PM2.5, respectively. A region with more intercity freeways or national roads tends to have more NOx emissions, while urban streets play a more important role in primary PM2.5 emissions from freight trucks. Compared with the inventory of the Ministry of Environment Protection, which allocates emissions according to local truck registration number and neglects interregional long-distance transport trips, the differences for NOx and PM2.5 are +28 and −57%, respectively. The REIB approach matches better with traffic statistical data on a provincial level. Furthermore, the different driving conditions on the different roads types are no longer overlooked with this approach.
Estimating surface fluxes using eddy covariance and numerical ogive optimization

Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm−2, |latent heat flux|> 20 Wm−2 and |CO2 flux|> 100 mmol m−2 d−1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5–20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23–98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.