Understanding the surface O3 response over a “receptor” region to emission changes over a foreign “source” region is key to evaluating the potential gains from an international approach to abate ...ozone (O3) pollution. We apply an ensemble of 21 global and hemispheric chemical transport models to estimate the spatial average surface O3 response over east Asia (EA), Europe (EU), North America (NA), and south Asia (SA) to 20% decreases in anthropogenic emissions of the O3 precursors, NOx, NMVOC, and CO (individually and combined), from each of these regions. We find that the ensemble mean surface O3 concentrations in the base case (year 2001) simulation matches available observations throughout the year over EU but overestimates them by >10 ppb during summer and early fall over the eastern United States and Japan. The sum of the O3 responses to NOx, CO, and NMVOC decreases separately is approximately equal to that from a simultaneous reduction of all precursors. We define a continental‐scale “import sensitivity” as the ratio of the O3 response to the 20% reductions in foreign versus “domestic” (i.e., over the source region itself) emissions. For example, the combined reduction of emissions from the three foreign regions produces an ensemble spatial mean decrease of 0.6 ppb over EU (0.4 ppb from NA), less than the 0.8 ppb from the reduction of EU emissions, leading to an import sensitivity ratio of 0.7. The ensemble mean surface O3 response to foreign emissions is largest in spring and late fall (0.7–0.9 ppb decrease in all regions from the combined precursor reductions in the three foreign regions), with import sensitivities ranging from 0.5 to 1.1 (responses to domestic emission reductions are 0.8–1.6 ppb). High O3 values are much more sensitive to domestic emissions than to foreign emissions, as indicated by lower import sensitivities of 0.2 to 0.3 during July in EA, EU, and NA when O3 levels are typically highest and by the weaker relative response of annual incidences of daily maximum 8‐h average O3 above 60 ppb to emission reductions in a foreign region (<10–20% of that to domestic) as compared to the annual mean response (up to 50% of that to domestic). Applying the ensemble annual mean results to changes in anthropogenic emissions from 1996 to 2002, we estimate a Northern Hemispheric increase in background surface O3 of about 0.1 ppb a−1, at the low end of the 0.1–0.5 ppb a−1 derived from observations. From an additional simulation in which global atmospheric methane was reduced, we infer that 20% reductions in anthropogenic methane emissions from a foreign source region would yield an O3 response in a receptor region that roughly equals that produced by combined 20% reductions of anthropogenic NOx, NMVOC, and CO emissions from the foreign source region.
Tropospheric trace gas and aerosol pollutants have adverse effects on health, environment and climate. In order to quantify and mitigate such effects, a wide range of processes leading to the ...formation and transport of pollutants must be considered, understood and represented in numerical models. Regional scale pollution episodes result from the combination of several factors: high emissions (from anthropogenic or natural sources), stagnant meteorological conditions, kinetics and efficiency of the chemistry and the deposition. All these processes are highly variable in time and space, and their relative contribution to the pollutants budgets can be quantified with chemistry-transport models. The CHIMERE chemistry-transport model is dedicated to regional atmospheric pollution event studies. Since it has now reached a certain level a maturity, the new stable version, CHIMERE 2013, is described to provide a reference model paper. The successive developments of the model are reviewed on the basis of published investigations that are referenced in order to discuss the scientific choices and to provide an overview of the main results.
Urban air pollution is one of the most important environmental problems for human health and several strategies have been developed for its mitigation. The objective of this study is to assess the ...impact of single and combined mitigation measures on concentrations of air pollutants emitted by traffic at pedestrian level in the same urban environment. The effectiveness of different scenarios of green infrastructure (GI), the implementation of photocatalytic materials and traffic low emission zones (LEZ) are investigated, as well as several combinations of LEZ and GI. A wide set of scenarios is simulated through Computational Fluid Dynamics (CFD) modelling for two different wind directions (perpendicular (0°) and 45° wind directions). Wind flow for the BASE scenario without any measure implemented was previously evaluated using wind-tunnel measurements. Air pollutant concentrations for this scenario are compared with the results obtained from the different mitigation scenarios. Reduction of traffic emissions through LEZ is found to be the most effective single measure to improve local air quality. However, GI enhances the effects of LEZ, which makes the combination of LEZ + GI a very effective measure. The effectiveness of this combination depends on the GI layout, the intensity of emission reduction in the LEZ and the traffic diversion in streets surrounding the LEZ. These findings, in line with previous literature, suggest that the implementation of GI may increase air pollutant concentrations at pedestrian level for some cases. However, this study highlights that this negative effect on air quality can turn into positive when used in combination with reductions of local traffic emissions.
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•Local air pollution mitigation measures are evaluated by CFD modelling.•Not all Green Infrastructure (GI) are effective due to reduction of street ventilation•Low Emission Zones (LEZ) is the most effective single measure studied.•For some scenarios, the combination GI + LEZ is more effective than an individual LEZ•Negative effects of GI can turn into positive if traffic emissions are reduced.
Health impacts of atmospheric pollution is an important issue in urban environments. Its magnitude depends on population exposure which have been frequently estimated by considering different ...approaches relating pollutant concentration and population exposed to it. However, the uncertainties due to the spatial resolution of the model used to estimate the pollutant concentration or due to the lack of representativeness of urban air quality monitoring station (AQMS) have not been evaluated in detail. In this context, NO2 annual average concentration at pedestrian level in the whole city of Pamplona (Spain) modelled at high spatial resolution (~1 m) by Computational Fluid Dynamic (CFD) simulations is used to estimate the total population exposure and health-related externalities by using different approaches. Air pollutant concentration and population are aggregated at different spatial resolutions ranging from a horizontal grid cell size of 100 m × 100 m to a coarser resolution where the whole city is covered by only one cell (6 km × 5 km). In addition, concentrations at AQMS locations are also extracted to assess the representativeness of those AQMS. The case with a spatial resolution of 100 m × 100 m for both pollutant-concentration distribution and population data is used as a reference (Base case) and compared with those obtained with the other approaches. This study indicates that the spatial resolution of concentration and population distribution in the city should be 1 km × 1 km or finer to obtain appropriate estimates of total population exposure (underestimations <13%) and health-related externalities (underestimations <37%). For the cases with coarser resolutions, a strong underestimation of total population exposure (>31%) and health-related externalities (>76%) was found. On the other hand, the use of AQMS concentrations can induce important errors due to the limited spatial representativeness, in particular in terms of population exposure.
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•High-resolution NO2 concentrations was computed by CFD modelling for an entire city.•Population exposure and health externalities are estimated using these NO2 maps.•Resolution equals or finer than 1 km × 1 km are needed to obtain good estimates.•The use of AQMS concentrations can induce important errors on the estimates.•Different criteria are used to assess AQMS spatial representativeness.
As part of the Hemispheric Transport of Air Pollution (HTAP; http:// www.htap.org) project, we analyze results from 15 global and 1 hemispheric chemical transport models and compare these to Clean ...Air Status and Trends Network (CASTNet) observations in the United States (US) for 2001. Using the policy-relevant maximum daily 8-h average ozone (MDA8 O3) statistic, the multi-model ensemble represents the observations well (mean r2=0.57, ensemble bias = +4.1 ppbv for all US regions and all seasons) despite a wide range in the individual model results. Correlations are strongest in the northeastern US during spring and fall (r2=0.68); and weakest in the midwestern US in summer (r2=0.46). However, large positive mean biases exist during summer for all eastern US regions, ranging from 10–20 ppbv, and a smaller negative bias is present in the western US during spring (~3 ppbv). In nearly all other regions and seasons, the biases of the model ensemble simulations are ≤5 ppbv. Sensitivity simulations in which anthropogenic O3-precursor emissions (NOx + NMVOC + CO + aerosols) were decreased by 20% in four source regions: East Asia (EA), South Asia (SA), Europe (EU) and North America (NA) show that the greatest response of MDA8 O3 to the summed foreign emissions reductions occurs during spring in the West (0.9 ppbv reduction due to 20% emissions reductions from EA + SA + EU). East Asia is the largest contributor to MDA8 O3 at all ranges of the O3 distribution for most regions (typically ~0.45 ppbv) followed closely by Europe. The exception is in the northeastern US where emissions reductions in EU had a slightly greater influence than EA emissions, particularly in the middle of the MDA8 O3 distribution (response of ~0.35 ppbv between 35–55 ppbv). EA and EU influences are both far greater (about 4x) than that from SA in all regions and seasons. In all regions and seasons O3-precursor emissions reductions of 20% in the NA source region decrease MDA8 O3 the most – by a factor of 2 to nearly 10 relative to foreign emissions reductions. The O3 response to anthropogenic NA emissions is greatest in the eastern US during summer at the high end of the O3 distribution (5–6 ppbv for 20% reductions). While the impact of foreign emissions on surface O3 in the US is not negligible – and is of increasing concern given the recent growth in Asian emissions – domestic emissions reductions remain a far more effective means of decreasing MDA8 O3 values, particularly those above 75 ppb (the current US standard).
In the framework of the UNECE Task Force on Measurement and Modelling (TFMM) under the Convention on Long-range Transboundary Air Pollution (LRTAP), the EURODELTAIII project is evaluating how well ...air quality models are able to reproduce observed pollutant air concentrations and deposition fluxes in Europe. In this paper the sulphur and nitrogen deposition estimates of six state-of-the-art regional models (CAMx, CHIMERE, EMEP MSC-W, LOTOS-EUROS, MINNI and CMAQ) are evaluated and compared for four intensive EMEP measurement periods (25 Feb–26 Mar 2009; 17 Sep–15 Oct 2008; 8 Jan–4 Feb 2007 and 1–30 Jun 2006).
For sulphur, this study shows the importance of including sea salt sulphate emissions for obtaining better model results; CMAQ, the only model considering these emissions in its formulation, was the only model able to reproduce the high measured values of wet deposition of sulphur at coastal sites. MINNI and LOTOS-EUROS underestimate sulphate wet deposition for all periods and have low wet deposition efficiency for sulphur.
For reduced nitrogen, all the models underestimate both wet deposition and total air concentrations (ammonia plus ammonium) in the summer campaign, highlighting a potential lack of emissions (or incoming fluxes) in this period. In the rest of campaigns there is a general underestimation of wet deposition by all models (MINNI and CMAQ with the highest negative bias), with the exception of EMEP, which underestimates the least and even overestimates deposition in two campaigns. This model has higher scavenging deposition efficiency for the aerosol component, which seems to partly explain the different behaviour of the models.
For oxidized nitrogen, CMAQ, CAMx and MINNI predict the lowest wet deposition and the highest total air concentrations (nitric acid plus nitrates). Comparison with observations indicates a general underestimation of wet oxidized nitrogen deposition by these models, as well as an overestimation of total air concentration for all the campaigns, except for the 2006 campaign. This points to a low efficiency in the wet deposition of oxidized nitrogen for these models, especially with regards to the scavenging of nitric acid, which is the main driver of oxidized N deposition for all the models. CHIMERE, LOTOS-EUROS and EMEP agree better with the observations for both wet deposition and air concentration of oxidized nitrogen, although CHIMERE seems to overestimate wet deposition in the summer period. This requires further investigation, as the gas-particle equilibrium seems to be biased towards the gas phase (nitric acid) for this model.
In the case of MINNI, the frequent underestimation of wet deposition combined with an overestimation of atmospheric concentrations for the three pollutants indicates a low efficiency of the wet deposition processes. This can be due to several reasons, such as an underestimation of scavenging ratios, large vertical concentration gradients (resulting in small concentrations at cloud height) or a poor parameterization of clouds.
Large differences between models were also found for the estimates of dry deposition. However, the lack of suitable measurements makes it impossible to assess model performance for this process. These uncertainties should be addressed in future research, since dry deposition contributes significantly to the total deposition for the three deposited species, with values in the same range as wet deposition for most of the models, and with even higher values for some of them, especially for reduced nitrogen.
•The estimates of N and S deposition by six regional models are evaluated.•The inclusion of sea salt sulfate emissions was found to be important.•Formation of NH3+NH4+ is generally underestimated in summer.•There is a general underestimation of wet deposition of reduced N by most models.•Different performance was found for the different models and pollutants.
•We tested the factors related with foliar stoichiometry in Spanish forestall species.•Climate and N deposition are related with foliar stoichiometry in Spanish forests.•Phylogenetic distances are ...related to foliar stoichiometry differences among species.•Competitive neighborhood is also related to species-specific foliar stoichiometry.•The results supported the hypothesis that foliar stoichiometry is species-specific.
Concentrations of nutrient elements in organisms and in the abiotic environment are key factors influencing ecosystem structure and function. We studied how concentrations and stoichiometries of nitrogen (N), phosphorus (P) and potassium (K) in leaves of forest trees are related to phylogeny and to environmental factors (mean annual precipitation, mean annual temperature, forest type, and nitrogen deposition). Using data for 4691 forest plots from across Spain, we tested the following hypotheses: (i) that foliar stoichiometries of forest trees are strongly influenced by phylogeny, (ii) that climate, as an important driver of plant uptake and nutrient use efficiency, affects foliar stoichiometry, (iii) that long-term loads of N influence N, P and K concentrations and ratios in natural vegetation, and (iv) that sympatric species are differentiated according to their foliar stoichiometry, thereby reducing the intensity of resource competition.
Our analyses revealed that several factors contributed to interspecific variation in elemental composition and stoichiometry. These included phylogeny, forest type, climate, N deposition, and competitive neighborhood relationships (probably related to niche segregation effect).
These findings support the notion that foliar elemental composition reflects adaptation both to regional factors such as climate and to local factors such as competition with co-occurring species.
Through the comparison of several regional-scale chemistry transport modeling systems that simulate meteorology and air quality over the European and North American continents, this study aims at (i) ...apportioning error to the responsible processes using timescale analysis, (ii) helping to detect causes of model error, and (iii) identifying the processes and temporal scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of the models biases for several fields (ozone, CO, SO
, NO, NO
, PM
, PM
, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overallsense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance, and covariance) can help assess the nature and quality of the error. Each of the error components is analyzed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intraday) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact of model inputs (emission and boundary conditions) and poor representation of the stable boundary layer on model bias, results also highlighted the high interdependencies among meteorological and chemical variables, as well as among their errors. This indicates that the evaluation of air quality model performance for individual pollutants needs to be supported by complementary analysis of meteorological fields and chemical precursors to provide results that are more insightful from a model development perspective. This will require evaluaion methods that are able to frame the impact on error of processes, conditions, and fluxes at the surface. For example, error due to emission and boundary conditions is dominant for primary species (CO, particulate matter (PM)), while errors due to meteorology and chemistry are most relevant to secondary species, such as ozone. Some further aspects emerged whose interpretation requires additional consideration, such as the uniformity of the synoptic error being region- and model-independent, observed for several pollutants; the source of unexplained variance for the diurnal component; and the type of error caused by deposition and at which scale.
The realism of a specific configuration of the WRF Regional Climate Model (RCM) to represent the observed temperature evolution over the Iberian Peninsula (IP) in the 1971–2005 period has been ...analyzed. The E-OBS observational dataset was used for this purpose. Also, the
added value
of the WRF simulations with respect to the IPSL Earth System Model (ESM) used to drive the WRF RCM was evaluated. In general, WRF presents lower temperatures than in the observations (negative biases) over the IP. These biases are comparatively larger than those of the driving ESM. Once the biases are corrected, WRF provides an added value in terms of a higher spatial representation. WRF introduces more variability in some regions in comparison to gridded observation. Warming trends according to the observations are also well represented by the RCM. In the second part of this study, the projections of future climate performed with both the ESM and the RCM were evaluated for the RCP4.5 and RCP8.5 scenarios during the 21st century. Although both models simulate temperature increases, the RCM simulates a smaller warming than the ESM after the mid-21st century, except for winter. Using the WRF model, the maximum temperature increase reaches
6
∘
C
and
3
∘
C
for RCP8.5 and RCP4.5 in the south east of the Iberian Peninsula by the end of the 21st century, respectively.
The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990-2010, was designed to answer a ...series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM.sub.10 and PM.sub.2.5 for the period of 2000-2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty.
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