scholarly journals Emission factors for open and domestic biomass burning for use in atmospheric models

2011 ◽  
Vol 11 (9) ◽  
pp. 4039-4072 ◽  
Author(s):  
S. K. Akagi ◽  
R. J. Yokelson ◽  
C. Wiedinmyer ◽  
M. J. Alvarado ◽  
J. S. Reid ◽  
...  
Keyword(s):  
Gas Phase ◽  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
Emission Factor ◽  
Standard Form ◽  
Model Performance ◽  
Future Research ◽  
Atmospheric Models ◽  
Carbonaceous Particles ◽  
Global Estimate

Abstract. Biomass burning (BB) is the second largest source of trace gases and the largest source of primary fine carbonaceous particles in the global troposphere. Many recent BB studies have provided new emission factor (EF) measurements. This is especially true for non-methane organic compounds (NMOC), which influence secondary organic aerosol (SOA) and ozone formation. New EF should improve regional to global BB emissions estimates and therefore, the input for atmospheric models. In this work we present an up-to-date, comprehensive tabulation of EF for known pyrogenic species based on measurements made in smoke that has cooled to ambient temperature, but not yet undergone significant photochemical processing. All EFs are converted to one standard form (g compound emitted per kg dry biomass burned) using the carbon mass balance method and they are categorized into 14 fuel or vegetation types. Biomass burning terminology is defined to promote consistency. We compile a large number of measurements of biomass consumption per unit area for important fire types and summarize several recent estimates of global biomass consumption by the major types of biomass burning. Post emission processes are discussed to provide a context for the emission factor concept within overall atmospheric chemistry and also highlight the potential for rapid changes relative to the scale of some models or remote sensing products. Recent work shows that individual biomass fires emit significantly more gas-phase NMOC than previously thought and that including additional NMOC can improve photochemical model performance. A detailed global estimate suggests that BB emits at least 400 Tg yr−1 of gas-phase NMOC, which is almost 3 times larger than most previous estimates. Selected recent results (e.g. measurements of HONO and the BB tracers HCN and CH3CN) are highlighted and key areas requiring future research are briefly discussed.

scholarly journals Emission factors for open and domestic biomass burning for use in atmospheric models

2010 ◽  
Vol 10 (11) ◽  
pp. 27523-27602 ◽  
Author(s):  
S. K. Akagi ◽  
R. J. Yokelson ◽  
C. Wiedinmyer ◽  
M. J. Alvarado ◽  
J. S. Reid ◽  
...  
Keyword(s):  
Gas Phase ◽  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
Emission Factor ◽  
Standard Form ◽  
Emission Factors ◽  
Future Research ◽  
Atmospheric Models ◽  
Carbonaceous Particles ◽  
Global Estimate

Abstract. Biomass burning (BB) is the second largest source of trace gases and the largest source of primary fine carbonaceous particles in the global troposphere. Many recent BB studies have provided new emission factor (EF) measurements. This is especially true for non methane organic compounds (NMOC), which influence secondary organic aerosol (SOA) and ozone formation. New EF should improve regional to global BB emissions estimates and therefore, the input for atmospheric models. In this work we present an up-to-date, comprehensive tabulation of EF for known pyrogenic species based on measurements made in smoke that has cooled to ambient temperature, but not yet undergone significant photochemical processing. All the emission factors are converted to one standard form (g compound emitted per kg dry biomass burned) using the carbon mass balance method and they are categorized into 14 fuel or vegetation types. We compile a large number of measurements of biomass consumption per unit area for important fire types and summarize several recent estimates of global biomass consumption by the major types of biomass burning. Biomass burning terminology is defined to promote consistency. Post emission processes are discussed to provide a context for the emission factor concept within overall atmospheric chemistry and also highlight the potential for rapid changes relative to the scale of some models or remote sensing products. Recent work shows that individual biomass fires emit significantly more gas-phase NMOC than previously thought and that including additional NMOC can improve photochemical model performance. A detailed global estimate suggests that BB emits at least 400 Tg yr−1 of gas-phase NMOC, which is about 4 times larger than most previous estimates. Selected recent results (e.g. measurements of HONO and the BB tracers HCN and CH3CN) are highlighted and key areas requiring future research are briefly discussed.

scholarly journals Using GOME NO<sub>2</sub> satellite data to examine regional differences in TOMCAT model performance

2004 ◽  
Vol 4 (3) ◽  
pp. 2569-2613
Author(s):  
N. H. Savage ◽  
K. S. Law ◽  
J. A. Pyle ◽  
A. Richter ◽  
H. Nüß ◽  
...  
Keyword(s):  
North America ◽  
Case Studies ◽  
Biomass Burning ◽  
Satellite Data ◽  
Atmospheric Chemistry ◽  
Regional Differences ◽  
Model Development ◽  
Vertical Mixing ◽  
Model Performance ◽  
Model Treatment

Abstract. This paper compares column measurements of NO2 made by the GOME instrument on ERS-2 to model results from the TOMCAT global CTM. The overall correlation between the model and observations is good (0.79 for the whole world, and 0.89 for north America) but the modelled columns are too large over polluted areas (gradient of 1.4 for North America and 1.9 for Europe). NO2 columns in the region of outflow from North America into the Atlantic seem too high in winter in the model compared to the GOME results, whereas the modelled columns are too small off the coast of Africa where there appear to be biomass burning plumes in the satellite data. Several hypotheses are presented to explain these discrepancies. Weaknesses in the model treatment of vertical mixing and chemistry appear to be the most likely explanations. It is shown that GOME and other satellite data will be of great value in furthering our understanding of atmospheric chemistry and in targeting and testing future model development and case studies.

scholarly journals Atmospheric Chemistry in a Box or a Bag

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 401 ◽  
Author(s):  
G. M. Hidy
Keyword(s):  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Reaction Mechanisms ◽  
Reaction Times ◽  
Atmospheric Models ◽  
Aerosol Chemistry ◽  
Surface Exchange ◽  
Volatile Organic ◽  
Smog Chambers ◽  
Chamber Studies

Environmental chambers have proven to be essential for atmospheric photochemistry research. This historical perspective summarizes chamber research characterizing smog. Experiments with volatile organic compounds (VOCs)-nitrogen oxides (NOx) have characterized O3 and aerosol chemistry. These led to the creation and evaluation of complex reaction mechanisms adopted for various applications. Gas-phase photochemistry was initiated and developed using chamber studies. Post-1950s study of photochemical aerosols began using smog chambers. Much of the knowledge about the chemistry of secondary organic aerosols (SOA) derives from chamber studies complemented with specially designed atmospheric studies. Two major findings emerge from post-1990s SOA experiments: (1) photochemical SOAs hypothetically involve hydrocarbons and oxygenates with carbon numbers of 2, and (2) SOA evolves via more than one generation of reactions as condensed material exchanges with the vapor phase during “aging”. These elements combine with multiphase chemistry to yield mechanisms for aerosols. Smog chambers, like all simulators, are limited representations of the atmosphere. Translation to the atmosphere is complicated by constraints in reaction times, container interactions, influence of precursor injections, and background species. Interpretation of kinetics requires integration into atmospheric models addressing the combined effects of precursor emissions, surface exchange, hydrometeor interactions, air motion and sunlight.

scholarly journals Description and evaluation of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH) version 1.0: gas-phase chemistry at global scale

2017 ◽  
Vol 10 (2) ◽  
pp. 609-638 ◽  
Author(s):  
Alba Badia ◽  
Oriol Jorba ◽  
Apostolos Voulgarakis ◽  
Donald Dabdub ◽  
Carlos Pérez García-Pando ◽  
...  
Keyword(s):  
Gas Phase ◽  
Southern Hemisphere ◽  
Biomass Burning ◽  
Atmospheric Chemistry ◽  
State Of The Art ◽  
Seasonal Trends ◽  
Gas Phase Chemistry ◽  
Cycle Simulation ◽  
Extensive Evaluation ◽  
Phase Chemistry

Abstract. This paper presents a comprehensive description and benchmark evaluation of the tropospheric gas-phase chemistry component of the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (NMMB-MONARCH), formerly known as NMMB/BSC-CTM, that can be run on both regional and global domains. Here, we provide an extensive evaluation of a global annual cycle simulation using a variety of background surface stations (EMEP, WDCGG and CASTNET), ozonesondes (WOUDC, CMD and SHADOZ), aircraft data (MOZAIC and several campaigns), and satellite observations (SCIAMACHY and MOPITT). We also include an extensive discussion of our results in comparison to other state-of-the-art models. We note that in this study, we omitted aerosol processes and some natural emissions (lightning and volcano emissions). The model shows a realistic oxidative capacity across the globe. The seasonal cycle for CO is fairly well represented at different locations (correlations around 0.3–0.7 in surface concentrations), although concentrations are underestimated in spring and winter in the Northern Hemisphere, and are overestimated throughout the year at 800 and 500 hPa in the Southern Hemisphere. Nitrogen species are well represented in almost all locations, particularly NO2 in Europe (root mean square error – RMSE – below 5 ppb). The modeled vertical distributions of NOx and HNO3 are in excellent agreement with the observed values and the spatial and seasonal trends of tropospheric NO2 columns correspond well to observations from SCIAMACHY, capturing the highly polluted areas and the biomass burning cycle throughout the year. Over Asia, the model underestimates NOx from March to August, probably due to an underestimation of NOx emissions in the region. Overall, the comparison of the modeled CO and NO2 with MOPITT and SCIAMACHY observations emphasizes the need for more accurate emission rates from anthropogenic and biomass burning sources (i.e., specification of temporal variability). The resulting ozone (O3) burden (348 Tg) lies within the range of other state-of-the-art global atmospheric chemistry models. The model generally captures the spatial and seasonal trends of background surface O3 and its vertical distribution. However, the model tends to overestimate O3 throughout the troposphere in several stations. This may be attributed to an overestimation of CO concentration over the Southern Hemisphere leading to an excessive production of O3 or to the lack of specific chemistry (e.g., halogen chemistry, aerosol chemistry). Overall, O3 correlations range between 0.6 and 0.8 for daily mean values. The overall performance of the NMMB-MONARCH is comparable to that of other state-of-the-art global chemistry models.

Developing high-resolution simulations of tropospheric NO2 over Flanders using WRF-Chem

2021 ◽  
Author(s):  
Catalina Poraicu ◽  
Jean-François Müller ◽  
Trissevgeni Stavrakou ◽  
Dominique Fonteyn ◽  
Frederik Tack ◽  
...  
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Atmospheric Chemistry ◽  
Model Performance ◽  
Wrf Model ◽  
Chemical Mechanism ◽  
Atmospheric Models ◽  
Atmospheric Measurements ◽  
Measured Concentration ◽  
Atmospheric Species

&lt;p&gt;Atmospheric chemistry is critical in determining air quality and thus impacts climate change. Anthropogenic species are released into the atmosphere, and undergo complex photochemical transformations leading to the production of secondary pollutants, among which ozone and particulate matter. This can induce adverse effects on human health, visibility, ecosystems and local meteorology. &amp;#160;The combination of state-of-the-art atmospheric models with accurate atmospheric measurements of atmospheric species abundances is needed to evaluate whether atmospheric models can successfully simulate the chemical and physical processes occurring, and hopefully monitor the emissions of anthropogenic compounds and help in the implementation and verification of abatement policies.&lt;/p&gt;&lt;p&gt;In this work, ground-based, airborne and spaceborne measuring techniques are used to evaluate the performance of the full chemistry on-line WRF-Chem model over Antwerp in Flanders, Belgium, one of the areas with the highest NO2 pollution in the world. The model is configured to allow two nested domains with spatial resolution changing from 5 to 1km, so as to pinpoint the most pollutant sources in the region, and applied to simulate the urban air quality over the Antwerp agglomeration.&lt;/p&gt;&lt;p&gt;We will briefly discuss the choices and adaptations made regarding the physical parameterizations, emission inventories and chemical mechanism. The model performance is evaluated through comparison with various observation types. The physics parameterizations in WRF model &amp;#160;are evaluated through comparison against ground-based data from two meteorological stations in the Antwerp region. The WRF-Chem NO2 distributions are evaluated against (1) hourly measured concentration values from monitoring stations in Flanders, (2) vertical columns measured by an airborne hyperspectral imager APEX, providing a 2-dimensional spatial mapping, on 27 and 29 June 2019, and (3) spaceborne NO2 columns over Belgium obtained from the high-resolution TROPOMI instrument aboard S5p. The consistency of the model biases across the three datasets will be discussed, and recommendations will be made for improving model performance in this region.&lt;/p&gt;

scholarly journals Application of random forest regression to the calculation of gas-phase chemistry within the GEOS-Chem chemistry model v10

2019 ◽  
Vol 12 (3) ◽  
pp. 1209-1225 ◽  
Author(s):  
Christoph A. Keller ◽  
Mat J. Evans
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Random Forest Regression ◽  
Data Set ◽  
Gas Phase Chemistry ◽  
Chemical Conditions ◽  
Phase Chemistry ◽  
The Impact

Abstract. Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models are numerically intense, and previous attempts to reduce the numerical cost of chemistry solvers have not delivered transformative change. We show here the potential of a machine learning (in this case random forest regression) replacement for the gas-phase chemistry in atmospheric chemistry transport models. Our training data consist of 1 month (July 2013) of output of chemical conditions together with the model physical state, produced from the GEOS-Chem chemistry model v10. From this data set we train random forest regression models to predict the concentration of each transported species after the integrator, based on the physical and chemical conditions before the integrator. The choice of prediction type has a strong impact on the skill of the regression model. We find best results from predicting the change in concentration for long-lived species and the absolute concentration for short-lived species. We also find improvements from a simple implementation of chemical families (NOx = NO + NO2). We then implement the trained random forest predictors back into GEOS-Chem to replace the numerical integrator. The machine-learning-driven GEOS-Chem model compares well to the standard simulation. For ozone (O3), errors from using the random forests (compared to the reference simulation) grow slowly and after 5 days the normalized mean bias (NMB), root mean square error (RMSE) and R2 are 4.2 %, 35 % and 0.9, respectively; after 30 days the errors increase to 13 %, 67 % and 0.75, respectively. The biases become largest in remote areas such as the tropical Pacific where errors in the chemistry can accumulate with little balancing influence from emissions or deposition. Over polluted regions the model error is less than 10 % and has significant fidelity in following the time series of the full model. Modelled NOx shows similar features, with the most significant errors occurring in remote locations far from recent emissions. For other species such as inorganic bromine species and short-lived nitrogen species, errors become large, with NMB, RMSE and R2 reaching >2100 % >400 % and <0.1, respectively. This proof-of-concept implementation takes 1.8 times more time than the direct integration of the differential equations, but optimization and software engineering should allow substantial increases in speed. We discuss potential improvements in the implementation, some of its advantages from both a software and hardware perspective, its limitations, and its applicability to operational air quality activities.

scholarly journals Economic value of protected areas via visitor mental health

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Ralf Buckley ◽  
Paula Brough ◽  
Leah Hague ◽  
Alienor Chauvenet ◽  
Chris Fleming ◽  
...  
Keyword(s):  
Mental Health ◽  
Protected Areas ◽  
Protected Area ◽  
Economic Value ◽  
Future Research ◽  
Global Estimate ◽  
Conservation Policies ◽  
Life Years ◽  
Order Of Magnitude ◽  
Individual Scale

Abstract We evaluate methods to calculate the economic value of protected areas derived from the improved mental health of visitors. A conservative global estimate using quality-adjusted life years, a standard measure in health economics, is US$6 trillion p.a. This is an order of magnitude greater than the global value of protected area tourism, and two to three orders greater than global aggregate protected area management agency budgets. Future research should: refine this estimate using more precise methods; consider interactions between health and conservation policies and budgets at national scales; and examine links between personalities and protected area experiences at individual scale.

scholarly journals The composition and variability of atmospheric aerosol over Southeast Asia during 2008

2012 ◽  
Vol 12 (2) ◽  
pp. 1083-1100 ◽  
Author(s):  
W. Trivitayanurak ◽  
P. I. Palmer ◽  
M. P. Barkley ◽  
N. H. Robinson ◽  
H. Coe ◽  
...  
Keyword(s):  
Southeast Asia ◽  
Gas Phase ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Sea Salt ◽  
Dust Aerosol ◽  
Small Scale ◽  
Formation Mechanisms ◽  
Sulphate Aerosol ◽  
Phase Oxidation

Abstract. We use a nested version of the GEOS-Chem global 3-D chemistry transport model to better understand the composition and variation of aerosol over Borneo and the broader Southeast Asian region in conjunction with aircraft and satellite observations. Our focus on Southeast Asia reflects the importance of this region as a source of reactive organic gases and aerosols from natural forests, biomass burning, and food and fuel crops. We particularly focus on July 2008 when the UK BAe-146 research aircraft was deployed over northern Malaysian Borneo as part of the ACES/OP3 measurement campaign. During July 2008 we find using the model that Borneo (defined as Borneo Island and the surrounding Indonesian islands) was a net exporter of primary organic aerosol (42 kT) and black carbon aerosol (11 kT). We find only 13% of volatile organic compound oxidation products partition to secondary organic aerosol (SOA), with Borneo being a net exporter of SOA (15 kT). SOA represents approximately 19% of the total organic aerosol over the region. Sulphate is mainly from aqueous-phase oxidation (68%), with smaller contributions from gas-phase oxidation (15%) and advection into the regions (14%). We find that there is a large source of sea salt, as expected, but this largely deposits within the region; we find that dust aerosol plays only a relatively small role in the aerosol burden. In contrast to coincident surface measurements over Northern Borneo that find a pristine environment with evidence for substantial biogenic SOA formation we find that the free troposphere is influenced by biomass burning aerosol transported from the northwest of the Island and further afield. We find several transport events during July 2008 over Borneo associated with elevated aerosol concentrations, none of which coincide with the aircraft flights. We use MODIS aerosol optical depths (AOD) data and the model to put the July campaign into a longer temporal perspective. We find that Borneo is where the model has the least skill at reproducing the data, where the model has a negative bias of 76% and only captures 14% of the observed variability. This model performance reflects the small-scale island-marine environment and the mix of aerosol species, with the model showing more skill at reproducing observed AOD over larger continental regions such as China where AOD is dominated by one aerosol type. The model shows that AOD over Borneo is approximately evenly split between organic and sulphate aerosol with sea salt representing 10–20% during May–September; we find a similar breakdown over continental Southeast Asia but with less sea salt aerosol and more dust aerosol. In contrast, East China AOD is determined mainly by sulphate aerosol and a seasonal source of dust aerosol, as expected. Realistic sensitivity runs, designed to test our underlying assumptions about emissions and chemistry over Borneo, show that model AOD is most sensitive to isoprene emissions and organic gas-phase partitioning but all fail to improve significantly upon the control model calculation. This emphasises the multi-faceted dimension of the problem and the need for concurrent and coordinated development of BVOC emissions, and BVOC chemistry and organic aerosol formation mechanisms.

Atmospheric chemistry of trans-CF3CHCHCl: Kinetics of the gas-phase reactions with Cl atoms, OH radicals, and O3

2008 ◽  
Vol 199 (1) ◽  
pp. 92-97 ◽  
Author(s):  
M.P. Sulbaek Andersen ◽  
E.J.K. Nilsson ◽  
O.J. Nielsen ◽  
M.S. Johnson ◽  
M.D. Hurley ◽  
...  
Keyword(s):  
Gas Phase ◽  
Atmospheric Chemistry ◽  
Oh Radicals ◽  
Gas Phase Reactions ◽  
Kinetics Of ◽  
Cl Atoms
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