Assessing chemistry schemes and constraints in air quality models used to predict ozone in London against the detailed Master Chemical Mechanism

Air pollution is the environmental factor with the greatest impact on human health in Europe. Understanding the key processes driving air quality across the relevant spatial scales, especially during pollution exceedances and episodes, is essential to provide effective predictions for both policymakers and the public. It is particularly important for policy regulators to understand the drivers of local air quality that can be regulated by national policies versus the contribution from regional pollution transported from mainland Europe or elsewhere. One of the main objectives of the Coupled Urban and Regional processes: Effects on AIR quality (CUREAIR) project is to determine local and regional contributions to ozone events. A detailed zero-dimensional (0-D) box model run with the Master Chemical Mechanism (MCMv3.2) is used as the benchmark model against which the less explicit chemistry mechanisms of the Generic Reaction Set (GRS) and the Common Representative Intermediates (CRIv2-R5) schemes are evaluated. GRS and CRI are used by the Atmospheric Dispersion Modelling System (ADMS-Urban) and the regional chemistry transport model EMEP4UK, respectively. The MCM model uses a near-explicit chemical scheme for the oxidation of volatile organic compounds (VOCs) and is constrained to observations of VOCs, NOx, CO, HONO (nitrous acid), photolysis frequencies and meteorological parameters measured during the ClearfLo (Clean Air for London) campaign. The sensitivity of the less explicit chemistry schemes to different model inputs has been investigated: Constraining GRS to the total VOC observed during ClearfLo as opposed to VOC derived from ADMS-Urban dispersion calculations, including emissions and background concentrations, led to a significant increase (674% during winter) in modelled ozone. The inclusion of HONO chemistry in this mechanism, particularly during wintertime when other radical sources are limited, led to substantial increases in the ozone levels predicted (223%). When the GRS and CRIv2-R5 schemes are run with the equivalent model constraints to the MCM, they are able to reproduce the level of ozone predicted by the near-explicit MCM to within 40% and 20% respectively for the majority of the time. An exception to this trend was observed during pollution episodes experienced in the summer, when anticyclonic conditions favoured increased temperatures and elevated O3. The in situ O3 predicted by the MCM was heavily influenced by biogenic VOCs during these conditions and the low GRS [O3] : MCM [O3] ratio (and low CRIv2-R5 [O3] : MCM [O3] ratio) demonstrates that these less explicit schemes under-represent the full O3 creation potential of these VOCs. To fully assess the influence of the in situ O3 generated from local emissions versus O3 generated upwind of London and advected in, the time since emission (and, hence, how far the real atmosphere is from steady state) must be determined. From estimates of the mean transport time determined from the NOx : NOy ratio observed at North Kensington during the summer and comparison of the O3 predicted by the MCM model after this time, ∼60% of the median observed [O3] could be generated from local emissions. During the warmer conditions experienced during the easterly flows, however, the observed [O3] may be even more heavily influenced by London's emissions

Structure of ice crystallized from supercooled water

The freezing of water to ice is fundamentally important to fields as diverse as cloud formation to cryopreservation. At ambient conditions, ice is considered to exist in two crystalline forms: stable hexagonal ice and metastable cubic ice. Using X-ray diffraction data and Monte Carlo simulations, we show that ice that crystallizes homogeneously from supercooled water is neither of these phases. The resulting ice is disordered in one dimension and therefore possesses neither cubic nor hexagonal symmetry and is instead composed of randomly stacked layers of cubic and hexagonal sequences. We refer to this ice as stacking-disordered ice I. Stacking disorder and stacking faults have been reported earlier for metastable ice I, but only for ice crystallizing in mesopores and in samples recrystallized from high-pressure ice phases rather than in water droplets. Review of the literature reveals that almost all ice that has been identified as cubic ice in previous diffraction studies and generated in a variety of ways was most likely stacking-disordered ice I with varying degrees of stacking disorder. These findings highlight the need to reevaluate the physical and thermodynamic properties of this metastable ice as a function of the nature and extent of stacking disorder using well-characterized samples

CCDC 836762: Experimental Crystal Structure Determination

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures

CCDC 836763: Experimental Crystal Structure Determination

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures

CCDC 836792: Experimental Crystal Structure Determination

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures

CCDC 836761: Experimental Crystal Structure Determination

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures

Synthesis of 2,6-Di(pyrazol-1-yl)pyrazine derivatives and the spin-state behavior of their iron(II) complexes

Chlorination of 2,6-bis(pyrazol-1-yl)pyrazine (bppz) with NaClO in acetic acid afforded 2,6-bis(4-chloropyrazol-1-yl)pyrazine (L2Cl). 2,6-Bis(4-bromopyrazol-1-yl)pyrazine (L2Br), 2,6-bis(4-iodopyrazol-1-yl)pyrazine (L2I), 2,6-bis(4-methylpyrazol-1-yl)pyrazine (L2Me), and 2,6-bis(4-nitropyrazol-1-yl)pyrazine (L2NO2) were also prepared by reactions of the preformed 4-substituted pyrazoles with 2,6-dichloropyrazine. The reduction of L2NO2 with iron powder gave 2,6-bis(4-aminopyrazol-1-yl)pyrazine (L2NH2) and L2I was converted into 2,6-bis[4-(phenylethynyl)pyrazol-1-yl]pyrazine (L2CCPh) by a Sonogashira coupling reaction. The salts [Fe(L2Me)2]X2 (X- = BF4- and ClO4-) underwent thermal spin-crossover abruptly at around 200 K in one and two steps, respectively. The [Fe(L2Me)2]X2 salts exhibited different light-induced excited spin-state trapping (LIESST) behavior; the BF4- salt behaves classically [T(LIESST) = 93 K], but the ClO4- salt undergoes a multistep LIESST relaxation. In contrast, solid [Fe(L2Cl)2][BF4]2 adopts a fixed 2:1 high/low-spin-state population that does not change with temperature below 300 K, whereas [Fe(L2Br)2][BF4]2 and [Fe(L2I)2][BF4]2 form low-spin solvated crystals that are transformed into high-spin powders on drying. The pyrazinyl group in the L2R ligands slightly stabilizes the low-spin state of the complexes, as determined by solution-phase magnetic measurements. The crystal structure of [Fe(L2CCPh)(OH2)z][BF4]2 contains a disordered mixture of six- (z = 3) and seven-coordinate (z = 4) iron centers

CCDC 899458: Experimental Crystal Structure Determination

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures

CCDC 899459: Experimental Crystal Structure Determination

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures