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As a consequence of long-range transported pollution, air–sea exchange can become a major source of persistent organic pollutants in remote marine environments. The vertical gradients in the air were quantified for 14 species, i.e. four parent polycyclic aromatic hydrocarbons (PAHs), three polychlorinated biphenyls (PCBs), three organochlorine pesticides (OCPs) and two polybrominated diphenylethers (PBDEs) in the gas-phase at a remote coastal site in the southern Aegean Sea in summer. Most vertical gradients were positive (Δ<i>c</i>∕Δ<i>z</i> > 0), indicating downward (net depositional) flux. Significant upward (net volatilisational) fluxes were found for three PAHs, mostly during daytime, and for two OCPs, mostly during night-time, as well as for one PCB and one PBDE during part of the measurements. While phenanthrene was deposited, fluoranthene (FLT) and pyrene (PYR) seem to undergo flux oscillation, hereby not following a day–night cycle. Box modelling confirms that volatilisation from the sea surface has significantly contributed to the night-time maxima of OCPs. Fluxes were quantified based on eddy covariance. Deposition fluxes ranged from −28.5 to +1.8 µg m<sup>−2</sup> day<sup>−1</sup> for PAHs and −3.4 to +0.9 µg m<sup>−2</sup> day<sup>−1</sup> for halogenated compounds. Dry particle deposition of FLT and PYR did not contribute significantly to the vertical flux.
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This study investigates a cross-variable ozone data assimilation (DA) method based on an ensemble Kalman filter (EnKF) that has been used in the companion study to improve ozone forecasts over Beijing and surrounding areas. The main purpose is to delve into the impacts of the cross-variable adjustment of nitrogen oxide (NO<sub><i>x</i></sub>) emissions on the nitrogen dioxide (NO<sub>2</sub>) forecasts over this region during the 2008 Beijing Olympic Games. A mixed effect on the NO<sub>2</sub> forecasts was observed through application of the cross-variable assimilation approach in the real-data assimilation (RDA) experiments. The method improved the NO<sub>2</sub> forecasts over almost half of the urban sites with reductions of the root mean square errors (RMSEs) by 15–36 % in contrast to big increases of the RMSEs over other urban stations by 56–239 %. Over the urban stations with negative DA impacts, improvement of the NO<sub>2</sub> forecasts (with 7 % reduction of the RMSEs) was noticed at night and in the morning versus significant deterioration during daytime (with 190 % increase of the RMSEs), suggesting that the negative data assimilation impacts mainly occurred during daytime. Ideal-data assimilation (IDA) experiments with a box model and the same cross-variable assimilation method confirmed the mixed effects found in the RDA experiments. In the same way, NO<sub><i>x</i></sub> emission estimation was improved at night and in the morning even under large biases in the prior emission, while it deteriorated during daytime (except for the case of minor errors in the prior emission). The mixed effects observed in the cross-variable data assimilation, i.e., positive data assimilation impacts on NO<sub>2</sub> forecasts over some urban sites, negative data assimilation impacts over the other urban sites, and weak data assimilation impacts over suburban sites, highlighted the limitations of the EnKF under strong nonlinear relationships between chemical variables. Under strong nonlinearity between daytime ozone concentrations and NO<sub><i>x</i></sub> emissions uncertainties (with large biases in the a priori emission), the EnKF may come up with inefficient or wrong adjustments to NO<sub><i>x</i></sub> emissions. The present findings reveal that bias correction is essential for the application of the EnKF in dealing with the data assimilation problem over strong nonlinear system.
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Vertical profiles of dicarboxylic acids, related organic compounds and secondary organic aerosol (SOA) tracer compounds in particle phase have not yet been simultaneously explored in East Asia, although there is growing evidence that aqueous-phase oxidation of volatile organic compounds may be responsible for the elevated organic aerosols (OA) in the troposphere. Here, we found consistently good correlation of oxalic acid, the most abundant individual organic compounds in aerosols globally, with its precursors as well as biogenic-derived SOA compounds in Chinese tropospheric aerosols by aircraft measurements. Anthropogenically derived dicarboxylic acids (i.e., C<sub>5</sub> and C<sub>6</sub> diacids) at high altitudes were 4–20 times higher than those from surface measurements and even occasionally dominant over oxalic acid at altitudes higher than 2 km, which is in contrast to the predominance of oxalic acid previously reported globally including the tropospheric and surface aerosols. This indicates an enhancement of tropospheric SOA formation from anthropogenic precursors. Furthermore, oxalic acid-to-sulfate ratio maximized at altitudes of ∼ 2 km, explaining aqueous-phase SOA production that was supported by good correlations with predicted liquid water content, organic carbon and biogenic SOA tracers. These results demonstrate that elevated oxalic acid and related SOA compounds from both the anthropogenic and biogenic sources may substantially contribute to tropospheric OA burden over polluted regions of China, implying aerosol-associated climate effects and intercontinental transport.
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We examine the impact of assumed cloud droplet concentration on the simulated diurnal cycle of rainfall over New Guinea and surrounding seas using convection-permitting numerical simulations with the Weather Research and Forecasting (WRF) model. The simulations mimic effects of cloud condensation nuclei on cloud and precipitation processes. They follow simulations reported in Hassim et al (ACP 2016) that focused on dynamical aspects, namely the topographic forcing and the off-shore propagation of convective systems that contribute to the observed early-morning rainfall maximum north-east of New Guinea. Simulations reported in this current study apply the bulk cloud microphysics of Thompson et al. with contrasting cloud droplet concentrations of 100 and 1,000 per cc, referred to as pristine and polluted conditions, respectively. Overall, the assumed cloud droplet concentration has a small impact on the simulated convection. This emphasizes the predominant control from the diurnal cycle and the large-scale conditions. Pristine convection results in a 15–20 % larger surface accumulated rainfall over both land and ocean, and a noticeable shift of the cloud top height distribution, a reduction of the contribution of shallow cloudiness (cloud tops below 3 km) and an increase of the population of deep clouds (cloud tops above 9 km). The simulated impact on precipitation and cloud fields is in stark contrast to previous modelling studies that document small enhancement of surface precipitation and significant increase of the cloud top height in polluted conditions. Analysis of microphysical fields suggests that the simulated small enhancement of precipitation in pristine conditions comes from more efficient rain processes below the freezing level and enhanced graupel initiation and growth aloft. The increase of the cloud top height is arguably due to precipitation off-loading increasing cloud buoyancy aloft that has been shown to operate in shallow warm convection. However, the relatively low horizontal resolution and application of the bulk cloud microphysics warrants follow-up studies to assess validity of the impacts documented in the current study.
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Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1 Hz data recorded by as many as 99 pyranometers during the HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE), we analyze field variability of clear-sky index <i>k</i>* (i.e., irradiance normalized to clear-sky conditions) and sub-minute <i>k</i>* increments (i.e., changes over specified intervals of time) for distances between tens of meters and about 10 km. By means of a simple classification scheme based on <i>k</i>* statistics, we identify overcast, clear, and mixed sky conditions, and demonstrate that the last of these is the most potentially problematic in terms of short-term PV power fluctuations. Under mixed conditions, the probability of relatively strong <i>k</i>* increments of ±0.5 is approximately twice as high compared to increment statistics computed without conditioning by sky type. Additionally, spatial autocorrelation structures of <i>k</i>* increment fields differ considerably between sky types. While the profiles for overcast and clear skies mostly resemble the predictions of a simple model published by Hoff and Perez (2012), this is not the case for mixed conditions. As a proxy for the smoothing effects of distributed PV, we finally show that spatial averaging mitigates variability in <i>k</i>* less effectively than variability in <i>k</i>* increments, for a spatial sensor density of 2 km<sup>−2</sup>.
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The optical properties and chemical composition of PM<sub>1.0</sub> particles in a suburban environment (Huairou) near the megacity of Beijing were measured during the HOPE-J<sup>3</sup>A (Haze Observation Project Especially for Jing–Jin–Ji Area) field campaign. The campaign covered the period November 2014 to January 2015 during the winter coal heating season. The average values and standard deviations of the extinction, scattering, absorption coefficients, and the aerosol single scattering albedo (SSA) at <i>λ</i> = 470 nm during the measurement period were 201 ± 240, 164 ± 202, 37 ± 43 Mm<sup>−1</sup>, and 0.80 ± 0.08, respectively. The average values for the real and imaginary components of the effective complex refractive index (CRI) over the campaign were 1.40 ± 0.06 and 0.03 ± 0.02, while the average mass scattering and absorption efficiencies (MSEs and MAEs) of PM<sub>1.0</sub> were 3.6 and 0.7 m<sup>2</sup> g<sup>−1</sup>, respectively. Highly time-resolved air pollution episodes clearly show the dramatic evolution of the PM<sub>1.0</sub> size distribution, extensive optical properties (extinction, scattering, and absorption coefficients), and intensive optical properties (SSA and CRI) during haze formation, development, and decline. Time periods were classified into three different pollution levels (clear, slightly polluted, and polluted) for further analysis. It was found that (1) the relative contributions of organic and inorganic species to observed aerosol composition changed significantly from clear to polluted days: the organic mass fraction decreased from 50 to 43 % while the proportion of sulfates, nitrates, and ammonium increased strongly from 34 to 44 %. (2) Chemical apportionment of extinction, calculated using the IMPROVE algorithm, tended to underestimate the extinction compared to measurements. Agreement with measurements was improved by modifying the parameters to account for enhanced absorption by elemental carbon (EC). Organic mass was the largest contributor (52 %) to the total extinction of PM<sub>1.0</sub>, while EC, despite its low mass concentration of ∼ 4 %, contributed about 17 % to extinction. When the air quality deteriorated, the contribution of nitrate aerosol increased significantly (from 15 % on clear days to 22 % on polluted days). (3) Under polluted conditions, the average MAEs of EC were up to 4 times as large as the reference MAE value for freshly generated black carbon (BC). The temporal pattern of MAE values was similar to that of the OC / EC ratio, suggesting that non-BC absorption from secondary organic aerosol also contributes to particle absorption.
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Isoprene (Is) emissions by plants represent a loss of carbon and energy resources leading to the initial hypothesis that fast growing pioneer species in secondary tropical forests allocate carbon primarily to growth at the expense of isoprenoid defenses. In this study, we quantified leaf isoprene and methanol emissions from the abundant pantropical pioneer tree species <i>Vismia guianensis</i> and ambient isoprene concentrations above a diverse secondary forest in the central Amazon. As photosynthetically active radiation (PAR) was varied (0 to 3000 µmol m<sup>−2</sup> s<sup>−1</sup>) under standard leaf temperature (30 °C), isoprene emissions from <i>V. guianensis</i> increased without saturation up to 80 nmol m<sup>−2</sup> s<sup>−1</sup>. A nonlinear increase in isoprene emissions with respect to net photosynthesis (Pn) resulted in the fraction of Pn dedicated to isoprene emissions increasing with light intensity (up to 2 % of Pn). Emission responses to temperature under standard light conditions (PAR of 1000 µmol m<sup>−2</sup> s<sup>−1</sup>) resulted in the classic uncoupling of isoprene emissions (<i>T</i><sub>opt, iso</sub> > 40 °C) from net photosynthesis (<i>T</i><sub>opt, Pn</sub> = 30.0–32.5 °C) with up to 7 % of Pn emitted as isoprene at 40 °C. Under standard environmental conditions of PAR and leaf temperature, young <i>V. guianensis</i> leaves showed high methanol emissions, low Pn, and low isoprene emissions. In contrast, mature leaves showed high Pn, high isoprene emissions, and low methanol emissions, highlighting the differential control of leaf phenology over methanol and isoprene emissions. High daytime ambient isoprene concentrations (11 ppbv) were observed above a secondary Amazon rainforest, suggesting that isoprene emissions are common among neotropical pioneer species. The results are not consistent with the initial hypothesis and support a functional role of methanol during leaf expansion and the establishment of photosynthetic machinery and a protective role of isoprene for photosynthesis during high temperature extremes regularly experienced in secondary rainforest ecosystems.
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A major continental-scale biomass burning smoke event from 28–30 June 2015, spanning central Canada through the eastern seaboard of the United States, resulted in unforecasted drops in daytime high surface temperatures on the order of 2–5 °C in the upper Midwest. This event, with strong smoke gradients and largely cloud-free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP) forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near-surface air temperatures between Bismarck (clear) and Grand Forks (overcast smoke), to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm) smoke aerosol optical thickness (AOT, <i>τ</i>) reached values above 5. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, <i>τ</i><sub>550</sub>) was found. A further analysis of European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), United Kingdom Meteorological Office (UKMO) near-surface air temperature forecasts for up to 54 h as a function of Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 to −1.0 °C per unit <i>τ</i><sub>550</sub>. In addition, using observations from the surface stations, uncertainties in near-surface air temperatures from ECMWF, NCEP, and UKMO model runs are estimated. This study further suggests that significant daily changes in <i>τ</i><sub>550</sub> above 1, at which the smoke-aerosol-induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events on a global scale. Thus, incorporating a more realistic smoke aerosol field into numerical models is currently less likely to significantly improve the accuracy of near-surface air temperature forecasts. However, regions such as eastern China, eastern Russia, India, and portions of the Saharan and Taklamakan deserts, where significant daily changes in AOTs are more frequent, are likely to benefit from including an accurate aerosol analysis into numerical weather forecasts.
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We present high-resolution (5 km × 5 km) atmospheric chemical transport model (ACTM) simulations of the impact of newly estimated traffic-related emissions on secondary organic aerosol (SOA) formation over the UK for 2012. Our simulations include additional diesel-related intermediate-volatility organic compound (IVOC) emissions derived directly from comprehensive field measurements at an urban background site in London during the 2012 Clean Air for London (ClearfLo) campaign. Our IVOC emissions are added proportionally to VOC emissions, as opposed to proportionally to primary organic aerosol (POA) as has been done by previous ACTM studies seeking to simulate the effects of these missing emissions. Modelled concentrations are evaluated against hourly and daily measurements of organic aerosol (OA) components derived from aerosol mass spectrometer (AMS) measurements also made during the ClearfLo campaign at three sites in the London area. According to the model simulations, diesel-related IVOCs can explain on average ∼ 30 % of the annual SOA in and around London. Furthermore, the 90th percentile of modelled daily SOA concentrations for the whole year is 3.8 µg m<sup>−3</sup>, constituting a notable addition to total particulate matter. More measurements of these precursors (currently not included in official emissions inventories) is recommended. During the period of concurrent measurements, SOA concentrations at the Detling rural background location east of London were greater than at the central London location. The model shows that this was caused by an intense pollution plume with a strong gradient of imported SOA passing over the rural location. This demonstrates the value of modelling for supporting the interpretation of measurements taken at different sites or for short durations.
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Measurements of the optical properties (absorption, scattering and extinction) of PM<sub>1</sub>, PM<sub>2.5</sub> and PM<sub>10</sub> made at two sites around Sacramento, CA, during the June 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES) are reported. These observations are used to establish relationships between various intensive optical properties and to derive information about the dependence of the optical properties on photochemical aging and sources. Supermicron particles contributed substantially to the total light scattering at both sites, about 50 % on average. A strong, linear relationship is observed between the scattering Ångström exponent for PM<sub>10</sub> and the fraction of the scattering that is contributed by submicron particles (<i>f</i><sub>sca, PM<msub level="4"><i/>1</msub></sub>) at both sites and with similar slopes and intercepts (for a given pair of wavelengths), suggesting that the derived relationship may be generally applicable for understanding variations in particle size distributions from remote sensing measurements. At the more urban T0 site, the <i>f</i><sub>sca, PM<msub level="4"><i/>1</msub></sub> increased with photochemical age, whereas at the downwind, more rural T1 site the <i>f</i><sub>sca, PM<msub level="4"><i/>1</msub></sub> decreased slightly with photochemical age. This difference in behavior reflects differences in transport, local production and local emission of supermicron particles between the sites. Light absorption is dominated by submicron particles, but there is some absorption by supermicron particles ( ∼ 15 % of the total). The supermicron absorption derives from a combination of black carbon that has penetrated into the supermicron mode and from dust, and there is a clear increase in the mass absorption coefficient of just the supermicron particles with increasing average particle size. The mass scattering coefficient (MSC) for the supermicron particles was directly observed to vary inversely with the average particle size, demonstrating that MSC cannot always be treated as a constant in estimating mass concentrations from scattering measurements, or vice versa. The total particle backscatter fraction exhibited some dependence upon the relative abundance of sub- versus supermicron particles; however this was modulated by variations in the median size of particles within a given size range; variations in the submicron size distribution had a particularly large influence on the observed backscatter efficiency and an approximate method to account for this variability is introduced. The relationship between the absorption and scattering Ångström exponents is examined and used to update a previously suggested particle classification scheme. Differences in composition led to differences in the sensitivity of PM<sub>2.5</sub> to heating in a thermodenuder to the average particle size, with more extensive evaporation (observed as a larger decrease in the PM<sub>2.5</sub> extinction coefficient) corresponding to smaller particles; i.e., submicron particles were generally more susceptible to heating than the supermicron particles. The influence of heating on the particle hygroscopicity varied with the effective particle size, with larger changes observed when the PM<sub>2.5</sub> distribution was dominated by smaller particles.
