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The Chinese government recently proposed ammonia (NH3) emission reductions (but without a specific national target) as a strategic option to mitigate fine particulate matter (PM2.5) pollution. We combined a meta-analysis of nationwide measurements and air quality modeling to identify efficiency gains by striking a balance between controlling NH3 and acid gas (SO2 and NOx) emissions. We found that PM2.5 concentrations decreased from 2000 to 2019, but annual mean PM2.5 concentrations still exceeded 35 µg m−3 at 74 % of 1498 monitoring sites during 2015–2019. The concentration of PM2.5 and its components were significantly higher (16 %–195 %) on hazy days than on non-hazy days. Compared with mean values of other components, this difference was more significant for the secondary inorganic ions SO42-, NO3-, and NH4+ (average increase 98 %). While sulfate concentrations significantly decreased over this period, no significant change was observed for nitrate and ammonium concentrations. Model simulations indicate that the effectiveness of a 50 % NH3 emission reduction for controlling secondary inorganic aerosol (SIA) concentrations decreased from 2010 to 2017 in four megacity clusters of eastern China, simulated for the month of January under fixed meteorological conditions (2010). Although the effectiveness further declined in 2020 for simulations including the natural experiment of substantial reductions in acid gas emissions during the COVID-19 pandemic, the resulting reductions in SIA concentrations were on average 20.8 % lower than those in 2017. In addition, the reduction in SIA concentrations in 2017 was greater for 50 % acid gas reductions than for the 50 % NH3 emission reductions. Our findings indicate that persistent secondary inorganic aerosol pollution in China is limited by emissions of acid gases, while an additional control of NH3 emissions would become more important as reductions of SO2 and NOx emissions progress.

This article was prepared, after a previous work on the field of several companies of the industrial graphic sector, with the primary objective of evaluating the degree of satisfaction or accommodation to justice / injustice wage of a convenience sample with both genders and their future perspectives of salary justice. We decide to study the company that revealed greater gender homogeneity, thus ensuring balance both numerically: 37 subjects interviewed, including 18 women and 19 men, as well as relevant characteristics such as age, professional categories and academic qualifications. In conclusion, women still receive lower wages compared to men, in the performance of the same functions and with a similar degree of productivity, corroborating previous studies.

The Human being by his mutable, evolutive (or involutive) human condition, obligatorily, not only learn to face the constraints and challenges of life, as to avoid it or to defend from it. Innate and learned mechanisms and strategies aren’t just represented by continuos or isolated points, but mostly represented by a function of diverse equations with diverse variables, resulting on convergent planes, as well divergent planes, meaning the same human being sometimes copes with other defends from. The relevance of this paper comes from the necessity of questioning the learning models, drawing a Therapeutical Alternative ilustrated by the essential distinction of the primary processes to learning : cope with and defend from, as Bruner (66) explains that although exists always some defense level, excepted the depleted psychotic, exists always some hability to cope with a problem, as even the most severe schizophrenic can generaly cope with a substantial emergency.

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.

Evidence is accumulating that emissions of primary particulate matter (PM) from residential wood and coal combustion in the UK may be underestimated and/or spatially misclassified. In this study, different assumptions for the spatial distribution and total emission of PM from solid fuel (wood and coal) burning in the UK were tested using an atmospheric chemical transport model. Modelled concentrations of the PM components were compared with measurements from aerosol mass spectrometers at four sites in central and Greater London (ClearfLo campaign, 2012), as well as with measurements from the UK black carbon network.The two main alternative emission scenarios modelled were Base4x and combRedist. For Base4x, officially reported PM2.5 from the residential and other non-industrial combustion source sector were increased by a factor of four. For the combRedist experiment, half of the baseline emissions from this same source were redistributed by residential population density to simulate the effect of allocating some emissions to the smoke control areas (that are assumed in the national inventory to have no emissions from this source). The Base4x scenario yielded better daily and hourly correlations with measurements than the combRedist scenario for year-long comparisons of the solid fuel organic aerosol (SFOA) component at the two London sites. However, the latter scenario better captured mean measured concentrations across all four sites. A third experiment, Redist – all emissions redistributed linearly to population density, is also presented as an indicator of the maximum concentrations an assumption like this could yield.The modelled elemental carbon (EC) concentrations derived from the combRedist experiments also compared well with seasonal average concentrations of black carbon observed across the network of UK sites. Together, the two model scenario simulations of SFOA and EC suggest both that residential solid fuel emissions may be higher than inventory estimates and that the spatial distribution of residential solid fuel burning emissions, particularly in smoke control areas, needs re-evaluation. The model results also suggest the assumed temporal profiles for residential emissions may require review to place greater emphasis on evening (including discretionary) solid fuel burning.

Atmospheric chemistry transport models (ACTMs) are widely used to underpin policy decisions associated with the impact of potential changes in emissions on future pollutant concentrations and deposition. It is therefore essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input pollutant emissions. ACTMs incorporate complex and non-linear descriptions of chemical and physical processes which means that interactions and non-linearities in input–output relationships may not be revealed through the local one-at-a-time sensitivity analysis typically used. The aim of this work is to demonstrate a global sensitivity and uncertainty analysis approach for an ACTM, using as an example the FRAME model, which is extensively employed in the UK to generate source–receptor matrices for the UK Integrated Assessment Model and to estimate critical load exceedances. An optimised Latin hypercube sampling design was used to construct model runs within ±40 % variation range for the UK emissions of SO2, NOx, and NH3, from which regression coefficients for each input–output combination and each model grid ( > 10 000 across the UK) were calculated. Surface concentrations of SO2, NOx, and NH3 (and of deposition of S and N) were found to be predominantly sensitive to the emissions of the respective pollutant, while sensitivities of secondary species such as HNO3 and particulate SO42−, NO3−, and NH4+ to pollutant emissions were more complex and geographically variable. The uncertainties in model output variables were propagated from the uncertainty ranges reported by the UK National Atmospheric Emissions Inventory for the emissions of SO2, NOx, and NH3 (±4, ±10, and ±20 % respectively). The uncertainties in the surface concentrations of NH3 and NOx and the depositions of NHx and NOy were dominated by the uncertainties in emissions of NH3, and NOx respectively, whilst concentrations of SO2 and deposition of SOy were affected by the uncertainties in both SO2 and NH3 emissions. Likewise, the relative uncertainties in the modelled surface concentrations of each of the secondary pollutant variables (NH4+, NO3−, SO42−, and HNO3) were due to uncertainties in at least two input variables. In all cases the spatial distribution of relative uncertainty was found to be geographically heterogeneous. The global methods used here can be applied to conduct sensitivity and uncertainty analyses of other ACTMs.

Cooking organic aerosol (COA) is currently not included in European emission inventories. However, recent positive matrix factorization (PMF) analyses of aerosol mass spectrometer (AMS) measurements have suggested important contributions of COA in several European cities. In this study, emissions of COA were estimated for the UK, based on hourly AMS measurements of COA made at two sites in London (a kerbside site in central London and an urban background site in a residential area close to central London) for the full calendar year of 2012 during the Clean Air for London (ClearfLo) campaign. Iteration of COA emissions estimates and subsequent evaluation and sensitivity experiments were conducted with the EMEP4UK atmospheric chemistry transport modelling system with a horizontal resolution of 5 km × 5 km. The spatial distribution of these emissions was based on workday population density derived from the 2011 census data. The estimated UK annual COA emission was 7.4 Gg per year, which is an almost 10 % addition to the officially reported UK national total anthropogenic emissions of PM2.5 (82 Gg in 2012), corresponding to 320 mg person−1 day−1 on average. Weekday and weekend diurnal variation in COA emissions were also based on the AMS measurements. Modelled concentrations of COA were then independently evaluated against AMS-derived COA measurements from another city and time period (Manchester, January–February 2007), as well as with COA estimated by a chemical mass balance model of measurements for a 2-week period at the Harwell rural site (∼ 80 km west of central London). The modelled annual average contribution of COA to ambient particulate matter (PM) in central London was between 1 and 2 µg m−3 (∼ 20 % of total measured OA1) and between 0.5 and 0.7 µg m−3 in other major cities in England (Manchester, Birmingham, Leeds). It was also shown that cities smaller than London can have a central hotspot of population density of smaller area than the computational grid cell, in which case higher localized COA concentrations than modelled here may be expected. Modelled COA concentrations dropped rapidly outside of major urban areas (annual average of 0.12 µg m−3 for the Harwell location), indicating that although COA can be a notable component in urban air, it does not have a significant effect on PM concentrations on rural areas. The possibility that the AMS-PMF apportionment measurements overestimate COA concentrations by up to a factor of 2 is discussed. Since COA is a primary emission, any downward adjustments in COA emissions would lead to a proportional linear downward scaling in the absolute magnitudes of COA concentrations simulated in the model.

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−3, 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.

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 has been identified as a major contributor to adverse human health effects in epidemiological studies and underpins ambient PM2.5 legislation. As a range of emission sources and atmospheric chemistry transport processes contribute to PM2.5 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, NOx, SOx or non-methane VOC on surface concentrations of PM2.5 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 in any given location of ∼ 0.6 µg m−3 (equivalent to ∼ 6 % of the modelled PM2.5). On average across the UK, the sensitivity of PM2.5 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, NOx, SOx, NH3 and primary PM2.5; however there are strong spatial differences in the PM2.5 sensitivities across the UK. Consequently, the sensitivity of PM2.5 to individual component emissions reductions varies between area and population weighting. Reductions in NH3 have the greatest effect on area-weighted PM2.5. A full UK population weighting places greater emphasis on reductions of primary PM2.5 emissions, which is simulated to be the most effective single-component control on PM2.5 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 emissions reductions (and of NOx emissions reductions) relative to the effectiveness of NH3 emissions reductions. Reductions in primary PM2.5 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 AEI from 30 % reductions in UK emissions of primary PM2.5, NH3, SOx, NOx and VOC totals 1.17 and 0.82 µg m−3 for the 2010 and 2030 CLE simulations, respectively (not accounting for non-linearity).

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.

Silicon (Si) is indispensable for many cellular processes including bone tissue metabolism. In this work, the effects of Si on human osteogenesis and osteoclastogenesis were characterized. Human mesenchymal stem cells (hMSC) and CD14+ stem cells, as osteoblast and osteoclast precursors, were treated with a wide range of Si concentrations, covering the physiological plasma levels. Si promoted a dose-dependent increase in hMSC proliferation, differentiation, and function, at levels similar to the normal basal plasma levels. Additionally, a decrease in the expression of the osteoclastogenic activators M-CSF and RANKL was observed. Also, Si elicited a decrease in osteoclastogenesis, which became significant at higher concentrations, as those observed after meals. Among the intracellular mechanisms studied, an upregulation of MEK and PKC signalling pathways was observed in both cell types. In conclusion, Si appears to have a direct positive effect on human osteogenesis, at basal plasma levels. On the other hand, it also seemed to be an inhibitor of osteoclastogenesis, but at higher concentrations, though yet in the physiological range. Further, an indirect effect of Si on osteoclastogenesis may also occur, through a downregulation of M-CSF and RANKL expression by osteoblasts. Thus, Si may be an important player in bone anabolic regenerative approaches.

Reactive nitrogen (Nr) compounds have different fates in the atmosphere due to differences in the governing processes of physical transport, deposition and chemical transformation. Nr compounds addressed here include reduced nitrogen (NHx: ammonia (NH3) and its reaction product ammonium (NH4+)), oxidized nitrogen (NOy: nitrogen monoxide (NO) + nitrogen dioxide (NO2) and their reaction products) as well as organic nitrogen compounds (organic N). Pollution abatement strategies need to take into account the differences in the governing processes of these compounds when assessing their impact on ecosystem services, biodiversity, human health and climate. NOx (NO + NO2) emitted from traffic affects human health in urban areas where the presence of buildings increases the residence time in streets. In urban areas this leads to enhanced exposure of the population to NOx concentrations. NOx emissions generally have little impact on nearby ecosystems because of the small dry deposition rates of NOx. These compounds need to be converted into nitric acid (HNO3) before removal through deposition is efficient. HNO3 sticks quickly to any surface and is thereby either dry deposited or incorporated into aerosols as nitrate (NO3−). In contrast to NOx compounds, NH3 has potentially high impacts on ecosystems near the main agricultural sources of NH3 because of its large ground-level concentrations along with large dry deposition rates. Aerosol phase NH4+ and NO3− contribute significantly to background PM2.5 and PM10 (mass of aerosols with an aerodynamic diameter of less than 2.5 and 10 μm, respectively) with an impact on radiation balance as well as potentially on human health. Little is known quantitatively and qualitatively about organic N in the atmosphere, other than that it contributes a significant fraction of wet-deposited N, and is present in both gaseous and particulate forms. Further studies are needed to characterise the sources, air chemistry and removal rates of organic N emissions.

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.

Excess reactive Nitrogen (Nr) has become one of the most pressing environmental problems leading to air pollution, acidification and eutrophication of ecosystems, biodiversity impacts, leaching of nitrates into groundwater and global warming. This paper investigates how current inventories cover emissions of Nr to the atmosphere in Europe, the United States of America, and China. The focus is on anthropogenic sources, assessing the state-of-the-art of quantifying emissions of Ammonia (NH3), Nitrogen Oxides (NOx) and Nitrous Oxide (N2O), the different purposes for which inventories are compiled, and to which extent current inventories meet the needs of atmospheric dispersion modelling. The paper concludes with a discussion of uncertainties involved and a brief outlook on emerging trends in the three regions investigated is conducted. Key issues are substantial differences in the overall magnitude, but as well in the relative sectoral contribution of emissions in the inventories that have been assessed. While these can be explained by the use of different methodologies and underlying data (e.g. emission factors or activity rates), they may lead to quite different results when using the emission datasets to model ambient air quality or the deposition with atmospheric dispersion models. Hence, differences and uncertainties in emission inventories are not merely of academic interest, but can have direct policy implications when the development of policy actions is based on these model results. The level of uncertainty of emission estimates varies greatly between substances, regions and emission source sectors. This has implications for the direction of future research needs and indicates how existing gaps between modelled and measured concentration or deposition rates could be most efficiently addressed. The observed current trends in emissions display decreasing NOx emissions and only slight reductions for NH3 in both Europe and the US. However, in China projections indicate a steep increase of both.

European emission trends of nitrogen oxides since 1880 and up to present are presented here and are linked to the evolution of road transport emissions. Road transport has been the dominating source of NOx emissions since 1970, and contributes with 40% to the total emissions in 2005. Five trend regimes have been identified between 1880 and 2005. The first regime (1880–1950) is determined by a slow increase in fuel consumption all over Europe. The second regime (1950–1980) is characterized by a continued steep upward trend in liquid fuel use and by the introduction of the first regulations on road traffic emissions. Reduction in fuel consumption determines the emission trends in the third regime (1980–1990) that is also characterized by important differences between Eastern and Western Europe. Emissions from road traffic continue to grow in Western Europe in this period, and it is argued here that the reason for this continued NOx emission increase is related to early inefficient regulations for NOx in the transport sector. The fourth regime (1990–2000) involves a turning point for road traffic emissions, with a general decrease of emissions in Europe during that decade. It is in this period that we can identify the first emission reductions due to technological abatement in Western Europe. In the fifth regime (2000–2005), the economic recovery in Eastern Europe imposes increased emission from road traffic in this area. Western European emissions are on the other hand decoupled from the fuel consumption, and continue to decrease. The implementation of strict measures to control NOx emissions is demonstrated here to be a main reason for the continued Western European emission reductions. The results indicate that even though the effectiveness of European standards is hampered by a slow vehicle turnover, loopholes in the type-approval testing, and an increase in diesel consumption, the effect of such technical abatement measures is traceable in the evolution of European road traffic emissions over the last 15 years.

During the last twenty-five years European emission data have been compiled and reported under the Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP) as part of the work under the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP). This paper presents emission trends of SO2 reported to EMEP and validated within the programme for the period 1980–2004. These European anthropogenic sulphur emissions have been steadily decreasing over the last twenty-five years, amounting from about 55 Tg SO2 in 1980 to 15 Tg SO2 in 2004. The uncertainty in sulphur emission estimates for individual countries and years are documented to range between 3% and 25%. The relative contribution of European emissions to global anthropogenic sulphur emissions has been halved during this period. Based on annual emission reports from European countries, three emission reduction regimes have been identified. The period 1980–1989 is characterized by low annual emission reductions (below 5% reduction per year and 20% for the whole period) and is dominated by emission reductions in Western Europe. The period 1990–1999 is characterised by high annual emission reductions (up to 11% reduction per year and 54% for the whole period), most pronounced in Central and Eastern Europe. The annual emission reductions in the period 2000–2004 are medium to low (below 6% reduction per year and 17% for the whole period) and reflect the unified Europe, with equally large reductions in both East and West. The sulphur emission reduction has been largest in the sector Combustion in energy and transformation industries, but substantial decreases are also seen in the Non-industrial combustion plants together with the sectors Industrial combustion and Industrial production processes. The majority of European countries have reduced their emissions by more than 60% between 1990 and 2004, and one quarter have already achieved sulphur emission reductions higher than 80%. At European level, the total sulphur target for 2010 set in the Gothenburg Protocol (16 Tg) has apparently already been met by 2004. However, still half of the Parties to the Gothenburg Protocol have to reduce further their sulphur emissions in order to attain their individual country total emission targets for 2010. It is also noteworthy that, contrasting the Gothenburg Protocol requirements, a growing number of countries have recently been reporting increasing sulphur emissions, while others report only minor further decreases. The emission trends presented here are supported by different studies of air concentrations and depositions carried out within and outside the framework of the LRTAP Convention.

The aim of the present investigation was to describe and validate an electronic mechanical test for quantification of the intensity of inflammatory nociception in mice. The electronic pressure-meter test consists of inducing the animal hindpaw flexion reflex by poking the plantar region with a polypropylene pipette tip adapted to a hand-held force transducer. This method was compared to the classical von Frey filaments test in which pressure intensity is automatically recorded after the nociceptive hindpaw flexion reflex. The electronic pressure-meter and the von Frey filaments were used to detect time versus treatment interactions of carrageenin-induced hypernociception. In two separate experiments, the electronic pressure-meter was more sensitive than the von Frey filaments for the detection of the increase in nociception (hypernociception) induced by small doses of carrageenin (30 µg). The electronic pressure-meter detected the antinociceptive effect of non-steroidal drugs in a dose-dependent manner. Indomethacin administered intraperitoneally (1.8-15 mg/kg) or intraplantarly (30-300 µg/paw) prevented the hypersensitive effect of carrageenin (100 µg/paw). The electronic pressure-meter also detected the hypernociceptive effect of prostaglandin E2 (PGE2; 10-100 ng) in a dose-dependent manner. The hypernociceptive effect of PGE2 (100 ng) was blocked by dipyrone (160 and 320 µg/paw) but not by intraplantar administration of indomethacin (300 µg/paw). The present results validate the use of the electronic pressure-meter as more sensitive than the von Frey filaments in mice. Furthermore, it is an objective and quantitative nociceptive test for the evaluation of the peripheral antinociceptive effect of anti-inflammatory analgesic drugs, which inhibit prostaglandin synthesis (indomethacin) or directly block the ongoing hypernociception (dipyrone).