Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model

A new version of the Global Model of Aerosol Processes (GLOMAP) is described, which uses a two-moment pseudo-modal aerosol dynamics approach rather than the original two-moment bin scheme. GLOMAP-mode simulates the multi-component global aerosol, resolving sulfate, sea-salt, dust, black carbon (BC) and particulate organic matter (POM), the latter including primary and biogenic secondary POM. Aerosol processes are simulated in a size-resolved manner including primary emissions, secondary particle formation by binary homogeneous nucleation of sulfuric acid and water, particle growth by coagulation, condensation and cloud-processing and removal by dry deposition, in-cloud and below-cloud scavenging. A series of benchmark observational datasets are assembled against which the skill of the model is assessed in terms of normalised mean bias (<i>b</i>) and correlation coefficient (<i>R</i>). Overall, the model performs well against the datasets in simulating concentrations of aerosol precursor gases, chemically speciated particle mass, condensation nuclei (CN) and cloud condensation nuclei (CCN). Surface sulfate, sea-salt and dust mass concentrations are all captured well, while BC and POM are biased low (but correlate well). Surface CN concentrations compare reasonably well in free troposphere and marine sites, but are underestimated at continental and coastal sites related to underestimation of either primary particle emissions or new particle formation. The model compares well against a compilation of CCN observations covering a range of environments and against vertical profiles of size-resolved particle concentrations over Europe. The simulated global burden, lifetime and wet removal of each of the simulated aerosol components is also examined and each lies close to multi-model medians from the AEROCOM model intercomparison exercise

Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model

In the most advanced aerosol-climate models it is common to represent the aerosol particle size distribution in terms of several log-normal modes. This approach, motivated by computational efficiency, makes assumptions about the shape of the particle distribution that may not always capture the properties of global aerosol. Here, a global modal aerosol microphysics module (GLOMAP-mode) is evaluated and improved by comparing against a sectional version (GLOMAP-bin) and observations in the same 3-D global offline chemistry transport model. With both schemes, the model captures the main features of the global particle size distribution, with sub-micron aerosol approximately unimodal in continental regions and bi-modal in marine regions. Initial bin-mode comparisons showed that the current values for two size distribution parameter settings in the modal scheme (mode widths and inter-modal separation sizes) resulted in clear biases compared to the sectional scheme. By adjusting these parameters in the modal scheme, much better agreement is achieved against the bin scheme and observations. Annual mean surface-level mass of sulphate, sea-salt, black carbon (BC) and organic carbon (OC) are within 25% in the two schemes in nearly all regions. Surface level concentrations of condensation nuclei (CN), cloud condensation nuclei (CCN), surface area density and condensation sink also compare within 25% in most regions. However, marine CCN concentrations between 30° N and 30° S are systematically 25–60% higher in the modal model, which we attribute to differences in size-resolved particle growth or cloud-processing. Larger differences also exist in regions or seasons dominated by biomass burning and in free-troposphere and high-latitude regions. Indeed, in the free-troposphere, GLOMAP-mode BC is a factor 2–4 higher than GLOMAP-bin, likely due to differences in size-resolved scavenging. Nevertheless, in most parts of the atmosphere, we conclude that bin-mode differences are much less than model-observation differences, although some processes are missing in these runs which may pose a bigger challenge to modal schemes (e.g., boundary layer nucleation and ultra-fine sea-spray). The findings here underline the need for a spectrum of complexity in global models, with size-resolved aerosol properties predicted by modal schemes needing to be continually benchmarked and improved against freely evolving sectional schemes and observations

Explaining Evidence Denial as Motivated Pragmatically Rational Epistemic Irrationality

This paper introduces a model for evidence denial that explains this behavior as a manifestation of rationality and it is based on the contention that social values (measurable as utilities) often underwrite these sorts of responses. Moreover, it is contended that the value associated with group membership in particular can override epistemic reason when the expected utility of a belief or belief system is great. However, it is also true that it appears to be the case that it is still possible for such unreasonable believers to reverse this sort of dogmatism and to change their beliefs in a way that is epistemically rational. The conjecture made here is that we should expect this to happen only when the expected utility of the beliefs in question dips below a threshold where the utility value of continued dogmatism and the associated group membership is no longer sufficient to motivate defusing the counter-evidence that tells against such epistemically irrational beliefs

Physicochemical analysis of rotavirus segment 11 supports a 'modified panhandle' structure and not the predicted alternative tRNA-like structure (TRLS)

.Rotaviruses are a major cause of acute gastroenteritis, which is often fatal in infants. The viral genome consists of 11 double-stranded RNA segments, but little is known about their cis-acting sequences and structural elements. Covariation studies and phylogenetic analysis exploring the potential structure of RNA11 of rotaviruses suggested that, besides the previously predicted "modified panhandle" structure, the 5' and 3' termini of one of the isoforms of the bovine rotavirus UKtc strain may interact to form a tRNA-like structure (TRLS). Such TRLSs have been identified in RNAs of plant viruses, where they are important for enhancing replication and packaging. However, using tRNA mimicry assays (in vitro aminoacylation and 3'- adenylation), we found no biochemical evidence for tRNA-like functions of RNA11. Capping, synthetic 3' adenylation and manipulation of divalent cation concentrations did not change this finding. NMR studies on a 5'- and 3'-deletion construct of RNA11 containing the putative intra-strand complementary sequences supported a predominant panhandle structure and did not conform to a cloverleaf fold despite the strong evidence for a predicted structure in this conserved region of the viral RNA. Additional viral or cellular factors may be needed to stabilise it into a form with tRNA-like properties

Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning

In this paper, it is argued that single function dual process theory is a more credible psychological account of non-monotonicity in human conditional reasoning than recent attempts to apply logic programming (LP) approaches in artificial intelligence to these data. LP is introduced and among other critiques, it is argued that it is psychologically unrealistic in a similar way to hash coding in the classicism vs. connectionism debate. Second, it is argued that causal Bayes nets provide a framework for modelling probabilistic conditional inference in System 2 that can deal with patterns of inference LP cannot. Third, we offer some speculations on how the cognitive system may avoid problems for System 1 identified by Fodor in 1983. We conclude that while many problems remain, the probabilistic single function dual processing theory is to be preferred over LP as an account of the non-monotonicity of human reasoning

Atmospheric processing outside clouds increases soluble iron in mineral dust

Iron (Fe) is a key micronutrient regulating primary productivity in many parts of the global ocean. Dust deposition is an important source of Fe to the surface ocean, but most of this Fe is biologically unavailable. Atmospheric processing and reworking of Fe in dust aerosol can increase the bioavailable Fe inputs to the ocean, yet the processes are not well understood. Here, we experimentally simulate and model the cycling of Fe-bearing dust between wet aerosol and cloud droplets. Our results show that insoluble Fe in dust particles readily dissolves under acidic conditions relevant to wet aerosols. By contrast, under the higher pH conditions generally relevant to clouds, Fe dissolution tends to stop, and dissolved Fe precipitates as poorly crystalline nanoparticles. If the dust-bearing cloud droplets evaporated again (returning to the wet aerosol stage with low pH), those neo-formed Fe nanoparticles quickly redissolve, while the refractory Fe-bearing phases continue to dissolve gradually. Overall, the duration of the acidic, wet aerosol stage ultimately increases the amount of potentially bioavailable Fe delivered to oceans, while conditions in clouds favor the formation of Fe-rich nanoparticles in the atmosphere

Pathways to mental healthcare in south-eastern Nigeria

In sub-Saharan Africa, traditional and faith healers provide competing services alongside biomedical professionals. This may be associated with delays in reaching specialised mental health services, and hence with longer duration of untreated illness. As first line care constitutes a crucial stage in accessing of psychiatric care, investigating pathways to mental healthcare can highlight help-seeking choices. This study explored the pathways to care for mental illness preferred by a non-clinical sample of the population in south-eastern Nigeria. Multistage sampling was used to select participants (N = 706) who completed questionnaires on help-seeking. Results showed a significant preference for biomedical (90.8%) compared to spiritual (57.8%) and traditional (33.2%) pathways. Higher education predicted preference for the biomedical model, while low education was associated with traditional and spiritual pathways. Protestants preferred the spiritual pathway more than did Catholics. The use of biomedical care is potentially undermined by poor mental health infrastructure, a lack of fit between the culture of biomedical care and the deep-seated cultural/religious worldviews of the people, stigma surrounding mental illness, and the likelihood of a social desirability bias in responses. A complementary model of care is proposed