scholarly journals Impacts of different characterizations of large-scale background on simulated regional-scale ozone over the continental United States

2018 ◽  
Vol 18 (5) ◽  
pp. 3839-3864 ◽  
Author(s):  
Christian Hogrefe ◽  
Peng Liu ◽  
George Pouliot ◽  
Rohit Mathur ◽  
Shawn Roselle ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Large Scale ◽  
Surface Ozone ◽  
Regional Scale ◽  
Model Performance ◽  
Lower Troposphere ◽  
Substantial Impact ◽  
Mixing Ratios ◽  
Scale Models

Abstract. This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global-scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental US for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ process analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couples fluctuations in free-tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry – Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), the Goddard Earth Observing System model coupled to chemistry (GEOS-Chem), and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the middle and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8 h average ozone on individual days. In contrast, the differences between the C-IFS-, GEOS-Chem-, and H-CMAQ-driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

scholarly journals Impacts of Different Characterizations of Large-Scale Background on Simulated Regional-Scale Ozone Over the Continental United States

2017 ◽  
Author(s):  
Christian Hogrefe ◽  
Peng Liu ◽  
George Pouliot ◽  
Rohit Mathur ◽  
Shawn Roselle ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Large Scale ◽  
Surface Ozone ◽  
Regional Scale ◽  
Model Performance ◽  
Lower Troposphere ◽  
Substantial Impact ◽  
Mixing Ratios ◽  
Scale Models

Abstract. This study analyzes simulated regional-scale ozone burdens both near the surface and aloft, estimates process contributions to these burdens, and calculates the sensitivity of the simulated regional-scale ozone burden to several key model inputs with a particular emphasis on boundary conditions derived from hemispheric or global scale models. The Community Multiscale Air Quality (CMAQ) model simulations supporting this analysis were performed over the continental U.S. for the year 2010 within the context of the Air Quality Model Evaluation International Initiative (AQMEII) and Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) activities. CMAQ Process Analysis (PA) results highlight the dominant role of horizontal and vertical advection on the ozone burden in the mid-to-upper troposphere and lower stratosphere. Vertical mixing, including mixing by convective clouds, couple fluctuations in free tropospheric ozone to ozone in lower layers. Hypothetical bounding scenarios were performed to quantify the effects of emissions, boundary conditions, and ozone dry deposition on the simulated ozone burden. Analysis of these simulations confirms that the characterization of ozone outside the regional-scale modeling domain can have a profound impact on simulated regional-scale ozone. This was further investigated by using data from four hemispheric or global modeling systems (Chemistry – Integrated Forecasting Model (C-IFS), CMAQ extended for hemispheric applications (H-CMAQ), GEOS-Chem, and AM3) to derive alternate boundary conditions for the regional-scale CMAQ simulations. The regional-scale CMAQ simulations using these four different boundary conditions showed that the largest ozone abundance in the upper layers was simulated when using boundary conditions from GEOS-Chem, followed by the simulations using C-IFS, AM3, and H-CMAQ boundary conditions, consistent with the analysis of the ozone fields from the global models along the CMAQ boundaries. Using boundary conditions from AM3 yielded higher springtime ozone columns burdens in the mid- and lower troposphere compared to boundary conditions from the other models. For surface ozone, the differences between the AM3-driven CMAQ simulations and the CMAQ simulations driven by other large-scale models are especially pronounced during spring and winter where they can reach more than 10 ppb for seasonal mean ozone mixing ratios and as much as 15 ppb for domain-averaged daily maximum 8-hr average ozone on individual days. In contrast, the differences between the C-IFS, GEOS-Chem, and H-CMAQ driven regional-scale CMAQ simulations are typically smaller. Comparing simulated surface ozone mixing ratios to observations and computing seasonal and regional model performance statistics revealed that boundary conditions can have a substantial impact on model performance. Further analysis showed that boundary conditions can affect model performance across the entire range of the observed distribution, although the impacts tend to be lower during summer and for the very highest observed percentiles. The results are discussed in the context of future model development and analysis opportunities.

scholarly journals Evaluating the capability of regional-scale air quality models to capture the vertical distribution of pollutants

2013 ◽  
Vol 6 (3) ◽  
pp. 791-818 ◽  
Author(s):  
E. Solazzo ◽  
R. Bianconi ◽  
G. Pirovano ◽  
M. D. Moran ◽  
R. Vautard ◽  
...  
Keyword(s):  
Air Quality ◽  
Correlation Coefficient ◽  
Regional Scale ◽  
Model Performance ◽  
Correlation Coefficients ◽  
Surface Processes ◽  
Free Troposphere ◽  
Commercial Aircraft ◽  
Mixing Ratios ◽  
The North

Abstract. This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias ≤ 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km−1). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next.

scholarly journals Low modeled ozone production suggests underestimation of precursor emissions (especially NO<sub><i>x</i></sub>) in Europe

2018 ◽  
Vol 18 (3) ◽  
pp. 2175-2198 ◽  
Author(s):  
Emmanouil Oikonomakis ◽  
Sebnem Aksoyoglu ◽  
Giancarlo Ciarelli ◽  
Urs Baltensperger ◽  
André Stephan Henry Prévôt
Keyword(s):  
Air Quality ◽  
Surface Ozone ◽  
Model Performance ◽  
Ozone Production ◽  
Nox Emissions ◽  
Air Quality Model ◽  
Quality Model ◽  
Voc Emissions ◽  
Mixing Ratios ◽  
The Impact

Abstract. High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modeling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone–temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, the Comprehensive Air Quality Model with Extensions (CAMx). The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (≥ 60 ppb) by 10–20 ppb and overestimates the lower ones (< 40 ppb) by 5–15 ppb, resulting in a misleading good agreement with the observations for average ozone. The model also underestimates the ozone–temperature regression slope by about a factor of 2 for most of the measurement stations. To investigate the impact of emissions, four scenarios were tested: (i) increased volatile organic compound (VOC) emissions by a factor of 1.5 and 2 for the anthropogenic and biogenic VOC emissions, respectively, (ii) increased nitrogen oxide (NOx) emissions by a factor of 2, (iii) a combination of the first two scenarios and (iv) increased traffic-only NOx emissions by a factor of 4. For southern, eastern, and central (except the Benelux area) Europe, doubling NOx emissions seems to be the most efficient scenario to reduce the underestimation of the observed high ozone mixing ratios without significant degradation of the model performance for the lower ozone mixing ratios. The model performance for ozone–temperature correlation is also better when NOx emissions are doubled. In the Benelux area, however, the third scenario (where both NOx and VOC emissions are increased) leads to a better model performance. Although increasing only the traffic NOx emissions by a factor of 4 gave very similar results to the doubling of all NOx emissions, the first scenario is more consistent with the uncertainties reported by other studies than the latter, suggesting that high uncertainties in NOx emissions might originate mainly from the road-transport sector rather than from other sectors. The impact of meteorology was examined with three sensitivity tests: (i) increased surface temperature by 4 ∘C, (ii) reduced wind speed by 50 % and (iii) doubled wind speed. The first two scenarios led to a consistent increase in all surface ozone mixing ratios, thus improving the model performance for the high ozone values but significantly degrading it for the low ozone values, while the third scenario had exactly the opposite effects. Overall, the modeled ozone is predicted to be more sensitive to its precursor emissions (especially traffic NOx) and therefore their uncertainties, which seem to be responsible for the model underestimation of the observed high ozone mixing ratios and ozone production.

scholarly journals Two-scale multi-model ensemble: is a hybrid ensemble of opportunity telling us more?

2018 ◽  
Vol 18 (12) ◽  
pp. 8727-8744 ◽  
Author(s):  
Stefano Galmarini ◽  
Ioannis Kioutsioukis ◽  
Efisio Solazzo ◽  
Ummugulsum Alyuz ◽  
Alessandra Balzarini ◽  
...  
Keyword(s):  
Time Series ◽  
Air Quality ◽  
Surface Ozone ◽  
Regional Scale ◽  
Probability Of Detection ◽  
Daily Maximum ◽  
Regional Models ◽  
Global Models ◽  
Ensemble Performance ◽  
Scale Models

Abstract. In this study we introduce a hybrid ensemble consisting of air quality models operating at both the global and regional scale. The work is motivated by the fact that these different types of models treat specific portions of the atmospheric spectrum with different levels of detail, and it is hypothesized that their combination can generate an ensemble that performs better than mono-scale ensembles. A detailed analysis of the hybrid ensemble is carried out in the attempt to investigate this hypothesis and determine the real benefit it produces compared to ensembles constructed from only global-scale or only regional-scale models. The study utilizes 13 regional and 7 global models participating in the Hemispheric Transport of Air Pollutants phase 2 (HTAP2)–Air Quality Model Evaluation International Initiative phase 3 (AQMEII3) activity and focuses on surface ozone concentrations over Europe for the year 2010. Observations from 405 monitoring rural stations are used for the evaluation of the ensemble performance. The analysis first compares the modelled and measured power spectra of all models and then assesses the properties of the mono-scale ensembles, particularly their level of redundancy, in order to inform the process of constructing the hybrid ensemble. This study has been conducted in the attempt to identify that the improvements obtained by the hybrid ensemble relative to the mono-scale ensembles can be attributed to its hybrid nature. The improvements are visible in a slight increase of the diversity (4 % for the hourly time series, 10 % for the daily maximum time series) and a smaller improvement of the accuracy compared to diversity. Root mean square error (RMSE) improved by 13–16 % compared to G and by 2–3 % compared to R. Probability of detection (POD) and false-alarm rate (FAR) show a remarkable improvement, with a steep increase in the largest POD values and smallest values of FAR across the concentration ranges. The results show that the optimal set is constructed from an equal number of global and regional models at only 15 % of the stations. This implies that for the majority of the cases the regional-scale set of models governs the ensemble. However given the high degree of redundancy that characterizes the regional-scale models, no further improvement could be expected in the ensemble performance by adding yet more regional models to it. Therefore the improvement obtained with the hybrid set can confidently be attributed to the different nature of the global models. The study strongly reaffirms the importance of an in-depth inspection of any ensemble of opportunity in order to extract the maximum amount of information and to have full control over the data used in the construction of the ensemble.

scholarly journals Impacts of near-future cultivation of biofuel feedstocks on atmospheric composition and local air quality

2012 ◽  
Vol 12 (2) ◽  
pp. 919-939 ◽  
Author(s):  
K. Ashworth ◽  
G. Folberth ◽  
C. N. Hewitt ◽  
O. Wild
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Oil Palm ◽  
Large Scale ◽  
Global Climate ◽  
Surface Ozone ◽  
Regional Scale ◽  
Atmospheric Composition ◽  
Scale Production ◽  
Reactive Trace Gases

Abstract. Large-scale production of feedstock crops for biofuels will lead to land use changes. We quantify the effects of realistic land use change scenarios for biofuel feedstock production on isoprene emissions and hence atmospheric composition and chemistry using the HadGEM2 model. Two feedstocks are considered: oil palm for biodiesel in the tropics and short rotation coppice (SRC) in the mid-latitudes. In total, 69 Mha of oil palm and 9 Mha of SRC are planted, each sufficient to replace just over 1% of projected global fossil fuel demand in 2020. Both planting scenarios result in increases in total global annual isoprene emissions of about 1%. In each case, changes in surface concentrations of ozone and biogenic secondary organic aerosol (bSOA) are substantial at the regional scale, with implications for air quality standards. However, the changes in tropospheric burden of ozone and the OH radical, and hence effects on global climate, are negligible. Over SE Asia, one region of oil palm planting, increases in annual mean surface ozone and bSOA concentrations reach over 3 ppbv (+11%) and 0.4 μg m−3 (+10%) respectively for parts of Borneo, with monthly mean increases of up to 6.5 ppbv (+25%) and 0.5 μg m−3 (+12%). Under the SRC scenario, Europe experiences monthly mean changes of over 0.6 ppbv (+1%) and 0.1 μg m−3 (+5%) in June and July, with peak increases of over 2 ppbv (+3%) and 0.5 μg m−3 (+8 %). That appreciable regional atmospheric impacts result from low level planting scenarios demonstrates the need to include changes in emissions of reactive trace gases such as isoprene in life cycle assessments performed on potential biofuel feedstocks.

scholarly journals Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown

2017 ◽  
Vol 17 (4) ◽  
pp. 3001-3054 ◽  
Author(s):  
Efisio Solazzo ◽  
Roberto Bianconi ◽  
Christian Hogrefe ◽  
Gabriele Curci ◽  
Paolo Tuccella ◽  
...  
Keyword(s):  
Air Quality ◽  
Boundary Conditions ◽  
Regional Scale ◽  
Model Performance ◽  
Transport Modeling ◽  
Strong Impact ◽  
Air Quality Model ◽  
Quality Model ◽  
Modeling Systems ◽  
The Impact

Abstract. 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, SO2, NO, NO2, PM10, PM2. 5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense 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 evaluation 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.

Cyclic Breathing Simulations in Large Scale Models of the Lung Airway From the Oronasal Opening to the Terminal Bronchioles

2012 ◽  
Author(s):  
D. Keith Walters ◽  
Greg W. Burgreen ◽  
Robert L. Hester ◽  
David S. Thompson ◽  
David M. Lavallee ◽  
...  
Keyword(s):  
Steady State ◽  
Boundary Conditions ◽  
Large Scale ◽  
Whole Body ◽  
Patient Specific ◽  
Cfd Simulations ◽  
Reduced Order ◽  
Scale Models ◽  
Steady State Simulation ◽  
Conducting Zone

Computational fluid dynamics (CFD) simulations were performed for unsteady periodic breathing conditions, using large-scale models of the human lung airway. The computational domain included fully coupled representations of the orotracheal region and large conducting zone up to generation four (G4) obtained from patient-specific CT data, and the small conducting zone (to G16) obtained from a stochastically generated airway tree with statistically realistic geometrical characteristics. A reduced-order geometry was used, in which several airway branches in each generation were truncated, and only select flow paths were retained to G16. The inlet and outlet flow boundaries corresponded to the oronasal opening (superior), the inlet/outlet planes in terminal bronchioles (distal), and the unresolved airway boundaries arising from the truncation procedure (intermediate). The cyclic flow was specified according to the predicted ventilation patterns for a healthy adult male at three different activity levels, supplied by the whole-body modeling software HumMod. The CFD simulations were performed using Ansys FLUENT. The mass flow distribution at the distal boundaries was prescribed using a previously documented methodology, in which the percentage of the total flow for each boundary was first determined from a steady-state simulation with an applied flow rate equal to the average during the inhalation phase of the breathing cycle. The distal pressure boundary conditions for the steady-state simulation were set using a stochastic coupling procedure to ensure physiologically realistic flow conditions. The results show that: 1) physiologically realistic flow is obtained in the model, in terms of cyclic mass conservation and approximately uniform pressure distribution in the distal airways; 2) the predicted alveolar pressure is in good agreement with previously documented values; and 3) the use of reduced-order geometry modeling allows accurate and efficient simulation of large-scale breathing lung flow, provided care is taken to use a physiologically realistic geometry and to properly address the unsteady boundary conditions.

scholarly journals Application of global models and satellite data for smaller-scale groundwater recharge studies

2016 ◽  
Author(s):  
Rogier Westerhoff ◽  
Paul White ◽  
Zara Rawlinson
Keyword(s):  
New Zealand ◽  
Satellite Data ◽  
Input Data ◽  
Large Scale ◽  
Regional Scale ◽  
Global Scale ◽  
Global Models ◽  
Scale Models ◽  
Boundary Issues ◽  
Rainfall Recharge

Abstract. Large-scale models and satellite data are increasingly used to characterise groundwater and its recharge at the global scale. Although these models have the potential to fill in data gaps and solve trans-boundary issues, they are often neglected in smaller-scale studies, since data are often coarse or uncertain. Large-scale models and satellite data could play a more important role in smaller-scale (i.e., national or regional) studies, if they could be adjusted to fit that scale. In New Zealand, large-scale models and satellite data are not used for groundwater recharge estimation at the national scale, since regional councils (i.e., the water managers) have varying water policy and models are calibrated at the local scale. Also, some regions have many localised ground observations (but poor record coverage), whereas others are data-sparse. Therefore, estimation of recharge is inconsistent at the national scale. This paper presents an approach to apply large-scale, global, models and satellite data to estimate rainfall recharge at the national to regional scale across New Zealand. We present a model, NGRM, that is largely inspired by the global-scale WaterGAP recharge model, but is improved and adjusted using national data. The NGRM model uses MODIS-derived ET and vegetation satellite data, and the available nation-wide datasets on rainfall, elevation, soil and geology. A valuable addition to the recharge estimation is the model uncertainty estimate, based on variance, covariance and sensitivity of all input data components in the model environment. This research shows that, with minor model adjustments and use of improved input data, large-scale models and satellite data can be used to derive rainfall recharge estimates, including their uncertainty, at the smaller scale, i.e., national and regional scale of New Zealand. The estimated New Zealand recharge of the NGRM model compare well to most local and regional lysimeter data and recharge models. The NGRM is therefore assumed to be capable to fill in gaps in data-sparse areas and to create more consistency between datasets from different regions, i.e., to solve trans-boundary issues. This research also shows that smaller-scale recharge studies in New Zealand should include larger boundaries than only a (sub-)aquifer, and preferably the whole catchment. This research points out the need for improved collaboration on the international to national to regional levels to further merge large-scale (global) models to smaller (i.e., national or regional) scales. Future research topics should, collaboratively, focus on: improvement of rainfall-runoff and snowmelt methods; inclusion of river recharge; further improvement of input data (rainfall, evapotranspiration, soil and geology); and the impact of recharge uncertainty in mountainous and irrigated areas.

scholarly journals Potential impact of a US climate policy and air quality regulations on future air quality and climate change

2015 ◽  
Vol 15 (21) ◽  
pp. 31385-31432
Author(s):  
Y. H. Lee ◽  
D. T. Shindell ◽  
G. Faluvegi ◽  
R. W. Pinder
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Air Quality ◽  
Climate Policy ◽  
Radiative Forcing ◽  
Surface Ozone ◽  
Regional Scale ◽  
Climate Mitigation ◽  
The Us ◽  
Indirect Forcing

Abstract. We have investigated how future air quality and climate change are influenced by the US air quality regulations that existed or were proposed in 2013 and a hypothetical climate mitigation policy that reduces 2050 CO2 emissions to be 50 % below 2005 emissions. Using NASA GISS ModelE2, we look at the impacts in year 2030 and 2055. The US energy-sector emissions are from the GLIMPSE project (GEOS-Chem LIDORT Integrated with MARKAL for the Purpose of Scenario Exploration), and other US emissions and the rest of the world emissions are based on the RCP4.5 scenario. The US air quality regulations are projected to have a strong beneficial impact on US air quality and public health in the future but result in positive radiative forcing. Surface PM2.5 is reduced by ~ 2 μg m−3 on average over the US, and surface ozone by ~ 8 ppbv. The improved air quality prevents about 91 400 premature deaths in the US, mainly due to the PM2.5 reduction (~ 74 200 lives saved). The air quality regulations reduces the light-reflecting aerosols (i.e., sulfate and organic matter) more than the light-absorbing species (i.e., black carbon and ozone), leading a strong positive radiative forcing (RF) by both aerosols direct and indirect forcing: total RF is ~ 0.04 W m−2 over the globe; ~ 0.8 W m−2 over the US. Under the hypothetical climate policy, future US energy relies less on coal and thus SO2 emissions are noticeably reduced. This provides air quality co-benefits, but it leads to climate dis-benefits over the US. In 2055, the US mean total RF is +0.22 W m−2 due to positive aerosol direct and indirect forcing, while the global mean total RF is −0.06 W m−2 due to the dominant negative CO2 RF (instantaneous RF). To achieve a regional-scale climate benefit via a climate policy, it is critical (1) to have multi-national efforts to reduce GHGs emissions and (2) to target emission reduction of light-absorbing species (e.g., BC and O3) on top of long-lived species. The latter is very desirable as the resulting climate benefit occurs faster and provides co-benefits to air quality and public health.

Trace gases and organic aerosol at a rural site in Vietnam during large scale biomass burning

2021 ◽  
Author(s):  
Simone M. Pieber ◽  
Dac-Loc Nguyen ◽  
Hendryk Czech ◽  
Stephan Henne ◽  
Nicolas Bukowiecki ◽  
...  
Keyword(s):  
Air Quality ◽  
Chemical Composition ◽  
Biomass Burning ◽  
Large Scale ◽  
Trace Gases ◽  
Organic Aerosol ◽  
Trace Gas ◽  
Rural Site ◽  
Air Masses ◽  
Mixing Ratios

&lt;p&gt;Open biomass burning (BB) is a globally widespread phenomenon. The fires release pollutants, which are harmful for human and ecosystem health and alter the Earth's radiative balance. Yet, the impact of various types of BB on the global radiative forcing remains poorly constrained concerning greenhouse gas emissions, BB organic aerosol (OA) chemical composition and related light absorbing properties. Fire emissions composition is influenced by multiple factors (e.g., fuel and thereby vegetation-type, fuel moisture, fire temperature, available oxygen). Due to regional variations in these parameters, studies in different world regions are needed. Here we investigate the influence of seasonally recurring BB on trace gas concentration and air quality at the regional Global Atmosphere Watch (GAW) station Pha Din (PDI) in rural Northwestern Vietnam. PDI is located in a sparsely populated area on the top of a hill (1466 m a.s.l.) and is well suited to study the large-scale fires on the Indochinese Peninsula, whose pollution plumes are frequently transported towards the site [1]. We present continuous trace gas observations of CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, CO, and O&lt;sub&gt;3&lt;/sub&gt; conducted at PDI since 2014 and interpret the data with atmospheric transport simulations. Annually recurrent large scale BB leads to hourly time-scale peaks CO mixing ratios at PDI of 1000 to 1500 ppb around every April since the start of data collection in 2014. We complement this analysis with carbonaceous PM&lt;sub&gt;2.5 &lt;/sub&gt;chemical composition analyzed during an intensive campaign in March-April 2015. This includes measurements of elemental and organic carbon (EC/OC) and more than 50 organic markers, such as sugars, PAHs, fatty acids and nitro-aromatics [2]. For the intensive campaign, we linked CO, CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt; and O&lt;sub&gt;3&lt;/sub&gt; mixing ratios to a statistical classification of BB events, which is based on OA composition. We found increased CO and O&lt;sub&gt;3&lt;/sub&gt; levels during medium and high BB influence during the intensive campaign. A backward trajectory analysis confirmed different source regions for the identified periods based on the OA cluster. Typically, cleaner air masses arrived from northeast, i.e., mainland China and Yellow sea during the intensive campaign. The more polluted periods were characterized by trajectories from southwest, with more continental recirculation of the medium cluster, and more westerly advection for the high cluster. These findings highlight that BB activities in Northern Southeast Asia significantly enhances the regional OA loading, chemical PM&lt;sub&gt;2.5 &lt;/sub&gt;composition and the trace gases in northwestern Vietnam. The presented analysis adds valuable data on air quality in a region of scarce data availability.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;REFERENCES&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;[1] Bukowiecki, N. et al. Effect of Large-scale Biomass Burning on Aerosol Optical Properties at the GAW Regional Station Pha Din, Vietnam. AAQR. 19, 1172&amp;#8211;1187 (2019).&lt;/p&gt;&lt;p&gt;[2] Nguyen, D. L, et al. Carbonaceous aerosol composition in air masses influenced by large-scale biomass burning: a case-study in Northwestern Vietnam. ACPD., https://doi.org/10.5194/acp-2020-1027, in review, 2020.&lt;/p&gt;

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