<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gu, Baojing.</style></author><author><style face="normal" font="default" size="100%">Zhang, Lin.</style></author><author><style face="normal" font="default" size="100%">Van Dingenen, Rita.</style></author><author><style face="normal" font="default" size="100%">Vieno, Massimo.</style></author><author><style face="normal" font="default" size="100%">Van Grinsven, Hans. J.M.</style></author><author><style face="normal" font="default" size="100%">Zhang, Xiuming.</style></author><author><style face="normal" font="default" size="100%">Zhang, Shaohui.</style></author><author><style face="normal" font="default" size="100%">Chen, Youfan.</style></author><author><style face="normal" font="default" size="100%">Wang, Sitong.</style></author><author><style face="normal" font="default" size="100%">Ren, Chenchen.</style></author><author><style face="normal" font="default" size="100%">Rao, Shilpa.</style></author><author><style face="normal" font="default" size="100%">Holland, Mike.</style></author><author><style face="normal" font="default" size="100%">Winiwarter, Wilfried.</style></author><author><style face="normal" font="default" size="100%">Chen, Deli.</style></author><author><style face="normal" font="default" size="100%">Xu, Jianming.</style></author><author><style face="normal" font="default" size="100%">Sutton, Mark. A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Abating ammonia is more cost-effective than nitrogen oxides for mitigating PM2.5 air pollution</style></title><secondary-title><style face="normal" font="default" size="100%">Science</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><volume><style face="normal" font="default" size="100%">374</style></volume><pages><style face="normal" font="default" size="100%">758-762</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Fine particulate matter (PM2.5, particles with a mass median aerodynamic diameter of less than 2.5 micrometers) in the atmosphere is associated with severe negative impacts on human health, and the gases sulfur dioxide, nitrogen oxides, and ammonia are the main PM2.5 precursors. However, their contribution to global health impacts has not yet been analyzed. Here, we show that nitrogen accounted for 39% of global PM2.5 exposure in 2013, increasing from 30% in 1990 with rising reactive nitrogen emissions and successful controls on sulfur dioxide. Nitrogen emissions to air caused an estimated 23.3 million years of life lost in 2013, corresponding to an annual welfare loss of 420 billion United States dollars for premature death. The marginal abatement cost of ammonia emission is only 10% that of nitrogen oxides emission globally, highlighting the priority for ammonia reduction.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">6568</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ge, Y.</style></author><author><style face="normal" font="default" size="100%">Heal, M. R.</style></author><author><style face="normal" font="default" size="100%">Stevenson, D. S.</style></author><author><style face="normal" font="default" size="100%">Wind, P.</style></author><author><style face="normal" font="default" size="100%">Vieno, M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evaluation of global EMEP MSC-W (rv4.34) WRF (v3.9.1.1) model surface concentrations and wet deposition of reactive N and S with measurements</style></title><secondary-title><style face="normal" font="default" size="100%">Geosci. Model Dev.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">7021–7046</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><issue><style face="normal" font="default" size="100%">11</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sharps, Katrina</style></author><author><style face="normal" font="default" size="100%">Vieno, Massimo</style></author><author><style face="normal" font="default" size="100%">Beck, Rachel</style></author><author><style face="normal" font="default" size="100%">Hayes, Felicity</style></author><author><style face="normal" font="default" size="100%">Harmens, Harry</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quantifying the impact of ozone on crops in sub-Saharan Africa demonstrates regional and local hotspots of production loss</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Science and Pollution Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Africa</style></keyword><keyword><style  face="normal" font="default" size="100%">beans</style></keyword><keyword><style  face="normal" font="default" size="100%">crop production</style></keyword><keyword><style  face="normal" font="default" size="100%">Ozone</style></keyword><keyword><style  face="normal" font="default" size="100%">wheat</style></keyword><keyword><style  face="normal" font="default" size="100%">yield loss</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><volume><style face="normal" font="default" size="100%">28</style></volume><pages><style face="normal" font="default" size="100%">62338-62352</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Tropospheric ozone can have a detrimental effect on vegetation, including reducing the quantity of crop yield. This study uses modelled ozone flux values (POD3IAM; phytotoxic ozone dose above 3 nmol m−2 s−1, parameterised for integrated assessment modelling) for 2015, together with species-specific flux-effect relationships, spatial data on production and growing season dates to quantify the impact of ozone on the production of common wheat (Triticum aestivum) and common beans (Phaseolus vulgaris) across Sub-Saharan Africa (SSA). A case study for South Africa was also done using detailed data per province. Results suggest that ozone pollution could decrease wheat yield by between 2 and 13%, with a total annual loss of 453,000 t across SSA. The impact on bean production depended on the season; however, estimated yield losses were up to 21% in some areas of SSA, with an annual loss of ~300,000 t for each of the two main growing seasons. Production losses tended to be greater in countries with the highest production, for example, Ethiopia (wheat) and Tanzania (beans). This study provides an indication of the location of areas at high risk of crop losses due to ozone. Results emphasise that efforts to reduce ozone precursors could contribute to reducing the yield gap in SSA. More stringent air pollution abatement policies are required to reduce crop losses to ozone in the future.</style></abstract><issue><style face="normal" font="default" size="100%">44</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Graham, Ailish. M.</style></author><author><style face="normal" font="default" size="100%">Pringle, Kirsty. J.</style></author><author><style face="normal" font="default" size="100%">Arnold, Stephen. R.</style></author><author><style face="normal" font="default" size="100%">Pope, Richard. J.</style></author><author><style face="normal" font="default" size="100%">Vieno, Massimo</style></author><author><style face="normal" font="default" size="100%">Butt, Edward. W.</style></author><author><style face="normal" font="default" size="100%">Conibear, Luke</style></author><author><style face="normal" font="default" size="100%">Stirling, Ellen. L.</style></author><author><style face="normal" font="default" size="100%">McQuaid, James. B.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Impact of weather types on UK ambient particulate matter concentrations</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Environment: X</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">air quality</style></keyword><keyword><style  face="normal" font="default" size="100%">AURN</style></keyword><keyword><style  face="normal" font="default" size="100%">emissions</style></keyword><keyword><style  face="normal" font="default" size="100%">long-range transport</style></keyword><keyword><style  face="normal" font="default" size="100%">LWT</style></keyword><keyword><style  face="normal" font="default" size="100%">PM2.5</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.aeaoa.2019.100061</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">5</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Each year more than 29,000 premature deaths in the UK are linked to long term-exposure to ambient particulate matter (PM) with a diameter less than 2.5 μm (PM2.5). Many studies have focused on the long-term impacts of exposure to PM, but short-term increases in pollution can also exacerbate health effects, leading to deaths brought forward within exposed populations. This study investigates the impact of different atmospheric circulation patterns on UK PM2.5 concentrations and the relative contribution of local and transboundary pollutants to variations in PM2.5 concentrations. Daily mean PM2.5 observations from 42 UK background sites indicate that easterly, south-easterly and southerly wind directions and anticyclonic circulation patterns enhance background concentrations of PM2.5 at all UK sites by up to 12 μg m-3. Results from back trajectory analysis and the European Monitoring and Evaluation Programme for UK model (EMEP4UK) show this is due to the transboundary transport of pollutants from continental Europe. While back trajectories indicate under easterly, south-easterly and southerly flow 25–50% of the total accumulated primary PM2.5 emissions originate outside of the UK, with a very polluted footprint (0.25–0.35 μg m-2). Anticyclonic conditions, which occur frequently (21%), also lead to increases in PM2.5 concentrations (UK multi-annual mean 14.7 μg m-3). EMEP4UK results indicate this is likely due the build-up of local emissions due to slack winds. Under westerly and north-westerly flow 15–30% of the total accumulated primary PM2.5 emissions originate outside of the UK, and are much less polluted (0.1 μg m-2) with model results indicating transport of clean maritime air masses from the Atlantic. Results indicate that both wind-direction and stability under anticyclonic conditions are important in controlling ambient PM2.5 concentrations across the UK. There is also a strong dependence of high PM2.5 Daily Air Quality Index (DAQI) values on easterly, south-easterly and southerly wind-directions, with &amp;gt;70% of occurrences of observed 48–71+ μg m-3 concentrations occurring under these wind directions. While north-westerly and cyclonic conditions reduce PM2.5 concentrations at all sites by up to 8 μg m-3. PM2.5 DAQI values are also lowest under these conditions, with &amp;gt;80% of 0–11 μg m-3 concentrations and &amp;gt;50% of 12–23 μg m-3 concentrations observed during westerly, north-westerly and northerly wind directions. Indicating that these conditions are likely to be associated with a reduction in the potential health effects from exposure to ambient levels of PM2.5.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Aleksankina, K.</style></author><author><style face="normal" font="default" size="100%">Reis, S.</style></author><author><style face="normal" font="default" size="100%">Vieno, M.</style></author><author><style face="normal" font="default" size="100%">Heal, M. R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Advanced methods for uncertainty assessment and global sensitivity analysis of an Eulerian atmospheric chemistry transport model</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Chemistry and Physics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year></dates><volume><style face="normal" font="default" size="100%">19</style></volume><pages><style face="normal" font="default" size="100%">2881-2898</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Atmospheric chemistry transport models (ACTMs) are extensively used to provide scientific support for the development of policies to mitigate the detrimental effects of air pollution on human health and ecosystems. Therefore, it is essential to quantitatively assess the level of model uncertainty and to identify the model input parameters that contribute the most to the uncertainty. For complex process-based models, such as ACTMs, uncertainty and global sensitivity analyses are still challenging and are often limited by computational constraints due to the requirement of a large number of model runs. In this work, we demonstrate an emulator-based approach to uncertainty quantification and variance-based sensitivity analysis for the EMEP4UK model (regional application of the European Monitoring and Evaluation Programme Meteorological Synthesizing Centre-West). A separate Gaussian process emulator was used to estimate model predictions at unsampled points in the space of the uncertain model inputs for every modelled grid cell. The training points for the emulator were chosen using an optimised Latin hypercube sampling design. The uncertainties in surface concentrations of O3, NO2, and PM2.5 were propagated from the uncertainties in the anthropogenic emissions of NOx, SO2, NH3, VOC, and primary PM2.5 reported by the UK National Atmospheric Emissions Inventory. The results of the EMEP4UK uncertainty analysis for the annually averaged model predictions indicate that modelled surface concentrations of O3, NO2, and PM2.5 have the highest level of uncertainty in the grid cells comprising urban areas (up to ±7 %, ±9 %, and ±9 %, respectively). The uncertainty in the surface concentrations of O3 and NO2 were dominated by uncertainties in NOx emissions combined from non-dominant sectors (i.e. all sectors excluding energy production and road transport) and shipping emissions. Additionally, uncertainty in O3 was driven by uncertainty in VOC emissions combined from sectors excluding solvent use. Uncertainties in the modelled PM2.5 concentrations were mainly driven by uncertainties in primary PM2.5 emissions and NH3 emissions from the agricultural sector. Uncertainty and sensitivity analyses were also performed for five selected grid cells for monthly averaged model predictions to illustrate the seasonal change in the magnitude of uncertainty and change in the contribution of different model inputs to the overall uncertainty. Our study demonstrates the viability of a Gaussian process emulator-based approach for uncertainty and global sensitivity analyses, which can be applied to other ACTMs. Conducting these analyses helps to increase the confidence in model predictions. Additionally, the emulators created for these analyses can be used to predict the ACTM response for any other combination of perturbed input emissions within the ranges set for the original Latin hypercube sampling design without the need to rerun the ACTM, thus allowing for fast exploratory assessments at significantly reduced computational costs.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">5</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hood, C.</style></author><author><style face="normal" font="default" size="100%">MacKenzie, I.</style></author><author><style face="normal" font="default" size="100%">Stocker, J.</style></author><author><style face="normal" font="default" size="100%">Johnson, K.</style></author><author><style face="normal" font="default" size="100%">Carruthers, D.</style></author><author><style face="normal" font="default" size="100%">Vieno, M.</style></author><author><style face="normal" font="default" size="100%">Doherty, R.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Air quality simulations for London using a coupled regional-to-local modelling system</style></title><secondary-title><style face="normal" font="default" size="100%">Atmos. Chem. Phys.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2018</style></year></dates><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">11221–11245</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A coupled regional-to-local modelling system comprising a regional chemistry–climate model with 5 km horizontal resolution (EMEP4UK) and an urban dispersion and chemistry model with explicit road source emissions (ADMS-Urban) has been used to simulate air quality in 2012 across London. The study makes use of emission factors for NO&lt;em&gt;x&lt;/em&gt;&amp;nbsp;and NO2&amp;nbsp;and non-exhaust emission rates of PM10&amp;nbsp;and PM2.5&amp;nbsp;which have been adjusted compared to standard factors to reflect real-world emissions, with increases in total emissions of around 30 % for these species. The performance of the coupled model and each of the two component models is assessed against measurements from background and near-road sites in London using a range of metrics concerning annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good performance compared to measurements for background sites for these metrics, but under-predicts concentrations of all pollutants except O3&amp;nbsp;at near-road sites due to the low resolution of input emissions and calculations. The coupled model shows good performance at both background and near-road sites, which is broadly comparable with that of the urban model that uses measured concentrations as regional background, except for PM2.5&amp;nbsp;where the under-prediction of the regional model causes the coupled model to also under-predict concentrations. Using the coupled model, it is estimated that 13 % of the area of London exceeded the EU limit value of 40 µg m−3&amp;nbsp;for annual average NO2&amp;nbsp;in 2012, whilst areas of exceedances of the annual average limit values of 40 and 25 µg m−3&amp;nbsp;for PM10&amp;nbsp;and PM2.5&amp;nbsp;respectively were negligible.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">15</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vieno, M.</style></author><author><style face="normal" font="default" size="100%">Heal, M. R.</style></author><author><style face="normal" font="default" size="100%">Williams, M. L.</style></author><author><style face="normal" font="default" size="100%">Carnell, E. J.</style></author><author><style face="normal" font="default" size="100%">Nemitz, E.</style></author><author><style face="normal" font="default" size="100%">Stedman, J. R.</style></author><author><style face="normal" font="default" size="100%">Reis, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The sensitivities of emissions reductions for the mitigation of UK PM2.5</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Chemistry and Physics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">01/2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.atmos-chem-phys.net/16/265/2016/acp-16-265-2016.html</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">16</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The reduction of ambient concentrations of fine particulate matter (PM2.5) is a key objective for air pollution control policies in the UK and elsewhere. Long-term exposure to PM2.5&amp;nbsp;has been identified as a major contributor to adverse human health effects in epidemiological studies and underpins ambient PM2.5&amp;nbsp;legislation. As a range of emission sources and atmospheric chemistry transport processes contribute to PM2.5&amp;nbsp;concentrations, atmospheric chemistry transport models are an essential tool to assess emissions control effectiveness. The EMEP4UK atmospheric chemistry transport model was used to investigate the impact of reductions in UK anthropogenic emissions of primary PM2.5, NH3, NO&lt;em&gt;x&lt;/em&gt;, SO&lt;em&gt;x&lt;/em&gt;&amp;nbsp;or non-methane VOC on surface concentrations of PM2.5&amp;nbsp;in the UK for a recent year (2010) and for a future current legislation emission (CLE) scenario (2030). In general, the sensitivity to UK mitigation is rather small. A 30 % reduction in UK emissions of any one of the above components yields (for the 2010 simulation) a maximum reduction in PM2.5&amp;nbsp;in any given location of  ∼  0.6 µg m−3&amp;nbsp;(equivalent to  ∼  6 % of the modelled PM2.5). On average across the UK, the sensitivity of PM2.5&amp;nbsp;concentrations to a 30 % reduction in UK emissions of individual contributing components, for both the 2010 and 2030 CLE baselines, increases in the order NMVOC, NO&lt;em&gt;x&lt;/em&gt;, SO&lt;em&gt;x&lt;/em&gt;, NH3&amp;nbsp;and primary PM2.5; however there are strong spatial differences in the PM2.5&amp;nbsp;sensitivities across the UK. Consequently, the sensitivity of PM2.5&amp;nbsp;to individual component emissions reductions varies between area and population weighting. Reductions in NH3&amp;nbsp;have the greatest effect on area-weighted PM2.5. A full UK population weighting places greater emphasis on reductions of primary PM2.5&amp;nbsp;emissions, which is simulated to be the most effective single-component control on PM2.5&amp;nbsp;for the 2030 scenario. An important conclusion is that weighting corresponding to the average exposure indicator metric (using data from the 45 model grids containing a monitor whose measurements are used to calculate the UK AEI) further increases the emphasis on the effectiveness of primary PM2.5&amp;nbsp;emissions reductions (and of NO&lt;em&gt;x&lt;/em&gt;&amp;nbsp;emissions reductions) relative to the effectiveness of NH3emissions reductions. Reductions in primary PM2.5&amp;nbsp;have the largest impact on the AEI in both 2010 and the 2030 CLE scenario. The summation of the modelled reductions to the UK PM2.5&amp;nbsp;AEI from 30 % reductions in UK emissions of primary PM2.5, NH3, SO&lt;em&gt;x&lt;/em&gt;, NO&lt;em&gt;x&lt;/em&gt;&amp;nbsp;and VOC totals 1.17 and 0.82 µg m−3&amp;nbsp;for the 2010 and 2030 CLE simulations, respectively (not accounting for non-linearity).&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">265</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vieno, M</style></author><author><style face="normal" font="default" size="100%">Heal, M</style></author><author><style face="normal" font="default" size="100%">Twigg, M</style></author><author><style face="normal" font="default" size="100%">MacKenzie, I</style></author><author><style face="normal" font="default" size="100%">Braban, C</style></author><author><style face="normal" font="default" size="100%">Lingard, J</style></author><author><style face="normal" font="default" size="100%">Ritchie, S</style></author><author><style face="normal" font="default" size="100%">Beck, R</style></author><author><style face="normal" font="default" size="100%">Móring, A</style></author><author><style face="normal" font="default" size="100%">Ots, R</style></author><author><style face="normal" font="default" size="100%">Di Marco, C</style></author><author><style face="normal" font="default" size="100%">Nemitz, E</style></author><author><style face="normal" font="default" size="100%">Sutton, M. A.</style></author><author><style face="normal" font="default" size="100%">Reis, S</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The UK particulate matter air pollution episode of March-April 2014: more than Saharan dust</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Research Letters</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1088/1748-9326/11/4/044004</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;A period of elevated surface concentrations of airborne particulate matter (PM) in the UK in spring 2014 was widely associated in the UK media with a Saharan dust plume. This might have led to over-emphasis on a natural phenomenon and consequently to a missed opportunity to inform the public and provide robust evidence for policy-makers about the observed characteristics and causes of this pollution event. In this work, the EMEP4UK regional atmospheric chemistry transport model (ACTM) was used in conjunction with speciated PM measurements to investigate the sources and long-range transport (including vertical) processes contributing to the chemical components of the elevated surface PM. It is shown that the elevated PM during this period was mainly driven by ammonium nitrate, much of which was derived from emissions outside the UK. In the early part of the episode, Saharan dust remained aloft above the UK; we show that a significant contribution of Saharan dust at surface level was restricted only to the latter part of the elevated PM period and to a relatively small geographic area in the southern part of the UK. The analyses presented in this paper illustrate the capability of advanced ACTMs, corroborated with chemically-speciated measurements, to identify the underlying causes of complex PM air pollution episodes. Specifically, the analyses highlight the substantial contribution of secondary inorganic ammonium nitrate PM, with agricultural ammonia emissions in continental Europe presenting a major driver. The findings suggest that more emphasis on reducing emissions in Europe would have marked benefits in reducing episodic PM2.5 concentrations in the UK.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">4</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Reis, S</style></author><author><style face="normal" font="default" size="100%">Seto, E</style></author><author><style face="normal" font="default" size="100%">Northcross, A</style></author><author><style face="normal" font="default" size="100%">Quinn, N. W.</style></author><author><style face="normal" font="default" size="100%">Convertino, M</style></author><author><style face="normal" font="default" size="100%">Jones, R. L.</style></author><author><style face="normal" font="default" size="100%">Maier, H. R.</style></author><author><style face="normal" font="default" size="100%">Schlink, U</style></author><author><style face="normal" font="default" size="100%">Steinle, S</style></author><author><style face="normal" font="default" size="100%">Vieno, M</style></author><author><style face="normal" font="default" size="100%">Wimberly, M. C.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrating modelling and smart sensors for environmental and human health</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Modelling &amp; Software</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">12/2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">74</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate and scale. However, models that assess impacts of human activities on environmental and human health, have typically been developed in contexts where data scarcity is the norm. Models are essential tools to understand processes, identify relationships, associations and causality, formalize stakeholder mental models, and to quantify the effects of prevention and interventions. They can help to explain data, as well as inform the deployment and location of sensors by identifying hotspots and areas of interest where data collection may achieve the best results. We identify a paradigm shift in how the integration of models and sensors can contribute to harnessing ‘Big Data’ and, more importantly, make the vital step from ‘Big Data’ to ‘Big Information’. In this paper, we illustrate current developments and identify key research needs using human and environmental health challenges as an example.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">238</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vieno, M.</style></author><author><style face="normal" font="default" size="100%">Heal, M. R.</style></author><author><style face="normal" font="default" size="100%">Hallsworth, S.</style></author><author><style face="normal" font="default" size="100%">Famulari, D.</style></author><author><style face="normal" font="default" size="100%">Doherty, R. M.</style></author><author><style face="normal" font="default" size="100%">Dore, A. J.</style></author><author><style face="normal" font="default" size="100%">Tang, Y. S.</style></author><author><style face="normal" font="default" size="100%">Braban, C. F.</style></author><author><style face="normal" font="default" size="100%">Leaver, D.</style></author><author><style face="normal" font="default" size="100%">Sutton, M. A.</style></author><author><style face="normal" font="default" size="100%">Reis, S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The role of long-range transport and domestic emissions in determining atmospheric secondary inorganic particle concentrations across the UK</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Chemistry and Physics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.atmos-chem-phys.net/14/8435/2014/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">14</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Surface concentrations of secondary inorganic particle components over the UK have been analysed for 2001–2010 using the EMEP4UK regional atmospheric chemistry transport model and evaluated against measurements. Gas/particle partitioning in the EMEP4UK model simulations used a bulk approach, which may lead to uncertainties in simulated secondary inorganic aerosol. However, model simulations were able to accurately represent both the long-term decadal surface concentrations of particle sulfate and nitrate and an episode in early 2003 of substantially elevated nitrate measured across the UK by the AGANet network. The latter was identified as consisting of three separate episodes, each of less than 1 month duration, in February, March and April. The primary cause of the elevated nitrate levels across the UK was meteorological: a persistent high-pressure system, whose varying location impacted the relative importance of transboundary versus domestic emissions. Whilst long-range transport dominated the elevated nitrate in February, in contrast it was domestic emissions that mainly contributed to the March episode, and for the April episode both domestic emissions and long-range transport contributed. A prolonged episode such as the one in early 2003 can have substantial impact on annual average concentrations. The episode led to annual concentration differences at the regional scale of similar magnitude to those driven by long-term changes in precursor emissions over the full decade investigated here. The results demonstrate that a substantial part of the UK, particularly the south and southeast, may be close to or exceeding annual mean limit values because of import of inorganic aerosol components from continental Europe under specific conditions. The results reinforce the importance of employing multiple year simulations in the assessment of emissions reduction scenarios on particulate matter concentrations and the need for international agreements to address the transboundary component of air pollution.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">8435</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Simpson, D.</style></author><author><style face="normal" font="default" size="100%">Benedictow, A.</style></author><author><style face="normal" font="default" size="100%">Berge, H.</style></author><author><style face="normal" font="default" size="100%">Bergström, R.</style></author><author><style face="normal" font="default" size="100%">Emberson, L. D.</style></author><author><style face="normal" font="default" size="100%">Fagerli, H.</style></author><author><style face="normal" font="default" size="100%">Flechard, C. R.</style></author><author><style face="normal" font="default" size="100%">Hayman, G. D.</style></author><author><style face="normal" font="default" size="100%">Gauss, M.</style></author><author><style face="normal" font="default" size="100%">Jonson, J. E.</style></author><author><style face="normal" font="default" size="100%">Jenkin, M. E.</style></author><author><style face="normal" font="default" size="100%">Nyíri, A.</style></author><author><style face="normal" font="default" size="100%">Richter, C.</style></author><author><style face="normal" font="default" size="100%">Semeena, V. S.</style></author><author><style face="normal" font="default" size="100%">Tsyro, S.</style></author><author><style face="normal" font="default" size="100%">Tuovinen, J.-P.</style></author><author><style face="normal" font="default" size="100%">Valdebenito, Á.</style></author><author><style face="normal" font="default" size="100%">Wind, P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The EMEP MSC-W chemical transport model - technical description</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Chemistry and Physics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.atmos-chem-phys.net/12/7825/2012/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">12</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The Meteorological Synthesizing Centre-West (MSC-W) of the European Monitoring and Evaluation Programme (EMEP) has been performing model calculations in support of the Convention on Long Range Transboundary Air Pollution (CLRTAP) for more than 30 years. The EMEP MSC-W chemical transport model is still one of the key tools within European air pollution policy assessments. Traditionally, the model has covered all of Europe with a resolution of about 50 km × 50 km, and extending vertically from ground level to the tropopause (100 hPa). The model has changed extensively over the last ten years, however, with flexible processing of chemical schemes, meteorological inputs, and with nesting capability: the code is now applied on scales ranging from local (ca. 5 km grid size) to global (with 1 degree resolution). The model is used to simulate photo-oxidants and both inorganic and organic aerosols. In 2008 the EMEP model was released for the first time as public domain code, along with all required input data for model runs for one year. The second release of the EMEP MSC-W model became available in mid 2011, and a new release is targeted for summer 2012. This publication is intended to document this third release of the EMEP MSC-W model. The model formulations are given, along with details of input data-sets which are used, and a brief background on some of the choices made in the formulation is presented. The model code itself is available at www.emep.int, along with the data required to run for a full year over Europe.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">7825</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Werner, M.</style></author><author><style face="normal" font="default" size="100%">Kryza, M.</style></author><author><style face="normal" font="default" size="100%">Dore, A. J.</style></author><author><style face="normal" font="default" size="100%">Blaś, M.</style></author><author><style face="normal" font="default" size="100%">Hallsworth, S.</style></author><author><style face="normal" font="default" size="100%">Vieno, M.</style></author><author><style face="normal" font="default" size="100%">Tang, Y. S.</style></author><author><style face="normal" font="default" size="100%">Smith, R. I.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelling of marine base cation emissions, concentrations and deposition in the UK</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Chemistry and Physics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">02/2011</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.atmos-chem-phys.net/11/1023/2011/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Base cations exert a large impact on various geochemical and geophysical processes both in the atmosphere and at the Earth surface. One of the essential roles of these compounds is impact on surface pH causing an increase in alkalinity and neutralizing the effects of acidity generated by sulphur and nitrogen deposition. During recent years anthropogenic emissions of base cations in the UK have decreased substantially, by about 70%, 78%, 75% and 48% for Na+, Mg2+, Ca2+ and K+, respectively, over the period 1990–2006. For the island regions, such as the UK, the main source of base cation particles is the aerosol produced from the sea surface. Here, the sea salt aerosol (SSA) emissions are calculated with parameterisations proposed by Mårtensson et al. (2003) for ultra fine particles, Monahan et al. (1986) for fine particles and Smith and Harisson (1998) for coarse particles continuously with a 0.1 μm size step using WRF-modelled wind speed data at a 5 km × 5 km grid square resolution with a 3 h time step for two selected years 2003 and 2006. SSA production has been converted into base cation emissions, with the assumption that the chemical composition of the particle emitted from the sea surface is equal to the chemical composition of sea water, and used as input data in the Fine Resolution Atmospheric Multi-pollutant Exchange Model (FRAME). FRAME model annual mean concentrations and total wet deposition at a 5 km × 5 km grid resolution, are compared with concentrations in air and wet deposition from the National Monitoring Network and measurements based estimates of UK deposition budget. The correlation coefficient for wet deposition achieves high values (R = 0.8) for Na+ and Mg2+, whereas for Ca2+ the correlation is poor (R &amp;lt; 0.3). Base cation concentrations are also represented well, with some overestimations on the west coast and underestimations in the centre of the land.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">1023</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vieno, M.</style></author><author><style face="normal" font="default" size="100%">Dore, A. J.</style></author><author><style face="normal" font="default" size="100%">Stevenson, D. S.</style></author><author><style face="normal" font="default" size="100%">Doherty, R.</style></author><author><style face="normal" font="default" size="100%">Heal, M. R.</style></author><author><style face="normal" font="default" size="100%">Reis, S.</style></author><author><style face="normal" font="default" size="100%">Hallsworth, S.</style></author><author><style face="normal" font="default" size="100%">Tarrason, L.</style></author><author><style face="normal" font="default" size="100%">Wind, P.</style></author><author><style face="normal" font="default" size="100%">Fowler, D.</style></author><author><style face="normal" font="default" size="100%">Simpson, D.</style></author><author><style face="normal" font="default" size="100%">Sutton, M. A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modelling surface ozone during the 2003 heat-wave in the UK</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Chemistry and Physics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2010</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.atmos-chem-phys.net/10/7963/2010/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">10</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The EMEP4UK modelling system is a high resolution (5×5 km2) application of the EMEP chemistry-transport model, designed for scientific and policy studies in the UK. We demonstrate the use and performance of the EMEP4UK system through the study of ground-level ozone (O3) during the extreme August 2003 heat-wave. Meteorology is generated by the Weather Research and Forecast (WRF) model, nudged every six hours with reanalysis data. We focus on SE England, where hourly average O3 reached up to 140 ppb during the heat-wave. EMEP4UK accurately reproduces elevated O3 and much of its day-to-day variability during the heat-wave. Key O3 precursors, nitrogen dioxide and isoprene, are less well simulated, but show generally accurate diurnal cycles and concentrations to within a factor of ~2–3 of observations. The modelled surface O3 distribution has an intricate spatio-temporal structure, governed by a combination of meteorology, emissions and photochemistry. A series of sensitivity runs with the model are used to explore the factors that influenced O3 levels during the heat-wave. Various factors appear to be important on different days and at different sites. Ozone imported from outside the model domain, especially the south, is very important on several days during the heat-wave, contributing up to 85 ppb. The effect of dry deposition is also important on several days. Modelled isoprene concentrations are generally best simulated if isoprene emissions are changed from the base emissions: typically doubled, but elevated by up to a factor of five on one hot day. We found that accurate modelling of the exact positions of nitrogen oxide and volatile organic compound plumes is crucial for the successful simulation of O3 at a particular time and location. Variations in temperature of ±5 K were found to have impacts on O3 of typically less than ±10 ppb.&lt;/p&gt;</style></abstract><section><style face="normal" font="default" size="100%">7963</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vieno, M.</style></author><author><style face="normal" font="default" size="100%">Dore, A. J.</style></author><author><style face="normal" font="default" size="100%">Wind, P.</style></author><author><style face="normal" font="default" size="100%">Di Marco, C.</style></author><author><style face="normal" font="default" size="100%">Nemitz, E.</style></author><author><style face="normal" font="default" size="100%">Phillips, G.</style></author><author><style face="normal" font="default" size="100%">Tarrason, L.</style></author><author><style face="normal" font="default" size="100%">Sutton, M. A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Application of the EMEP Unified Model to the UK with a Horizontal Resolution of 5 x 5 km2</style></title><secondary-title><style face="normal" font="default" size="100%">Atmospheric Ammonia</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">atmospheric transport model</style></keyword><keyword><style  face="normal" font="default" size="100%">emissions</style></keyword><keyword><style  face="normal" font="default" size="100%">reduced nitrogen</style></keyword><keyword><style  face="normal" font="default" size="100%">united-kingdom</style></keyword><keyword><style  face="normal" font="default" size="100%">wet deposition</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><pages><style face="normal" font="default" size="100%">367-372</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><accession-num><style face="normal" font="default" size="100%">ISI:000266236200021</style></accession-num></record></records></xml>