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Quantitative understanding of the sources and sinks of greenhouse gases is essential for predicting greenhouse-gas-climate feedback processes and their impacts on climate variability and change. Australia plays a significant role in driving variability in global carbon cycling, but the budgets of carbon gases in Australia remain highly uncertain. Here, shipborne Fourier transform infrared spectrometer measurements collected around Australia are used together with a global chemical transport model (GEOS-Chem) to analyse the variability of three direct and indirect carbon greenhouse gases: carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO). Using these measurements, we provide an updated distribution of these gases. From the model, we quantify their sources and sinks, and we exploit the benefits of multi-species analysis to explore co-variations to constrain relevant processes. We find that for all three gases, the eastern Australian coast is largely influenced by local anthropogenic sources, while the southern, western and northern coasts are characterised by a mixture of anthropogenic and natural sources. Comparing coincident and co-located enhancements in the three carbon gases highlighted several common sources from the Australian continent. We found evidence for 17 events with similar enhancement patterns indicative of co-emission and calculated enhancement ratios and modelled source contributions for each event. We found that anthropogenic co-enhancement events are common along the eastern coast, while co-enhancement events in the tropics primarily derive from biomass burning sources. While the GEOS-Chem model generally reproduced the timing of co-enhancement events, it was less able to reproduce the magnitude of enhancements. We used these differences to identify underestimated, overestimated and missing processes in the model. We found model overestimates of CH4 from coal burning and underestimates of all three gases from biomass burning. We identifi

A field aerosol measurement campaign as part of the Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign was conducted between 16 January 2013 and 15 February 2013 in the coastal city of Wollongong, Australia. The objectives of this research were to study the occurrence frequency, characteristics and factors that influence new particle formation processes. Particle formation and growth events were observed from particle number size distribution data in the range of 14 nm-660 nm measured using a scanning particle mobility sizer (SMPS). Four weak Class I particle formation and growth event days were observed, which is equivalent to 13% of the total observation days. The events occurred during the day, starting after 8:30 Australian Eastern Standard time with an average duration of five hours. The events also appeared to be positively linked to the prevailing easterly to north easterly sea breezes that carry pollutants from sources in and around Sydney. This suggests that photochemical reactions and a combination of oceanic and anthropogenic air masses are among the factors that influenced these events.

A field aerosol measurement campaign as part of the Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign was conducted between 16 January 2013 and 15 February 2013 in the coastal city of Wollongong, Australia. The objectives of this research were to study the occurrence frequency, characteristics and factors that influence new particle formation processes. Particle formation and growth events were observed from particle number size distribution data in the range of 14 nm-660 nm measured using a scanning particle mobility sizer (SMPS). Four weak Class I particle formation and growth event days were observed, which is equivalent to 13% of the total observation days. The events occurred during the day, starting after 8:30 Australian Eastern Standard time with an average duration of five hours. The events also appeared to be positively linked to the prevailing easterly to north easterly sea breezes that carry pollutants from sources in and around Sydney. This suggests that photochemical reactions and a combination of oceanic and anthropogenic air masses are among the factors that influenced these events.

Quantitative understanding of the sources and sinks of greenhouse gases is essential for predicting greenhouse-gas-climate feedback processes and their impacts on climate variability and change. Australia plays a significant role in driving variability in global carbon cycling, but the budgets of carbon gases in Australia remain highly uncertain. Here, shipborne Fourier transform infrared spectrometer measurements collected around Australia are used together with a global chemical transport model (GEOS-Chem) to analyse the variability of three direct and indirect carbon greenhouse gases: carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO). Using these measurements, we provide an updated distribution of these gases. From the model, we quantify their sources and sinks, and we exploit the benefits of multi-species analysis to explore co-variations to constrain relevant processes. We find that for all three gases, the eastern Australian coast is largely influenced by local anthropogenic sources, while the southern, western and northern coasts are characterised by a mixture of anthropogenic and natural sources. Comparing coincident and co-located enhancements in the three carbon gases highlighted several common sources from the Australian continent. We found evidence for 17 events with similar enhancement patterns indicative of co-emission and calculated enhancement ratios and modelled source contributions for each event. We found that anthropogenic co-enhancement events are common along the eastern coast, while co-enhancement events in the tropics primarily derive from biomass burning sources. While the GEOS-Chem model generally reproduced the timing of co-enhancement events, it was less able to reproduce the magnitude of enhancements. We used these differences to identify underestimated, overestimated and missing processes in the model. We found model overestimates of CH4 from coal burning and underestimates of all three gases from biomass burning. We identifi

Volatile organic compounds (VOCs) are important precursors to the formation of ozone and fine particulate matter, the two pollutants of most concern in Sydney, Australia. Despite this importance, there are very few published measurements of ambient VOC concentrations in Australia. In this paper, we present mole fractions of several important VOCs measured during the campaign known as MUMBA (Measurements of Urban, Marine and Biogenic Air) in the Australian city of Wollongong (34°S). We particularly focus on measurements made during periods when clean marine air impacted the measurement site and on VOCs of biogenic origin. Typical unpolluted marine air mole fractions during austral summer 2012-2013 at latitude 34°S were established for CO2 (391.0 ± 0.6 ppm), CH4 (1760.1 ± 0.4 ppb), N2O (325.04 ± 0.08 ppb), CO (52.4 ± 1.7 ppb), O3 (20.5 ± 1.1 ppb), acetaldehyde (190 ± 40 ppt), acetone (260 ± 30 ppt), dimethyl sulphide (50 ± 10 ppt), benzene (20 ± 10 ppt), toluene (30 ± 20 ppt), C8H10 aromatics (23 ± 6 ppt) and C9H12 aromatics (36 ± 7 ppt). The MUMBA site was frequently influenced by VOCs of biogenic origin from a nearby strip of forested parkland to the east due to the dominant north-easterly afternoon sea breeze. VOCs from the more distant densely forested escarpment to the west also impacted the site, especially during two days of extreme heat and strong westerly winds. The relative amounts of different biogenic VOCs observed for these two biomes differed, with much larger increases of isoprene than of monoterpenes or methanol during the hot westerly winds from the escarpment than with cooler winds from the east. However, whether this was due to different vegetation types or was solely the result of the extreme temperatures is not entirely clear. We conclude that the clean marine air and biogenic signatures measured during the MUMBA campaign provide useful information about the typical abundance of several key VOCs and can be used to constrain chemical transport mode

Volatile organic compounds (VOCs) are important precursors to the formation of ozone and fine particulate matter, the two pollutants of most concern in Sydney, Australia. Despite this importance, there are very few published measurements of ambient VOC concentrations in Australia. In this paper, we present mole fractions of several important VOCs measured during the campaign known as MUMBA (Measurements of Urban, Marine and Biogenic Air) in the Australian city of Wollongong (34°S). We particularly focus on measurements made during periods when clean marine air impacted the measurement site and on VOCs of biogenic origin. Typical unpolluted marine air mole fractions during austral summer 2012-2013 at latitude 34°S were established for CO2 (391.0 ± 0.6 ppm), CH4 (1760.1 ± 0.4 ppb), N2O (325.04 ± 0.08 ppb), CO (52.4 ± 1.7 ppb), O3 (20.5 ± 1.1 ppb), acetaldehyde (190 ± 40 ppt), acetone (260 ± 30 ppt), dimethyl sulphide (50 ± 10 ppt), benzene (20 ± 10 ppt), toluene (30 ± 20 ppt), C8H10 aromatics (23 ± 6 ppt) and C9H12 aromatics (36 ± 7 ppt). The MUMBA site was frequently influenced by VOCs of biogenic origin from a nearby strip of forested parkland to the east due to the dominant north-easterly afternoon sea breeze. VOCs from the more distant densely forested escarpment to the west also impacted the site, especially during two days of extreme heat and strong westerly winds. The relative amounts of different biogenic VOCs observed for these two biomes differed, with much larger increases of isoprene than of monoterpenes or methanol during the hot westerly winds from the escarpment than with cooler winds from the east. However, whether this was due to different vegetation types or was solely the result of the extreme temperatures is not entirely clear. We conclude that the clean marine air and biogenic signatures measured during the MUMBA campaign provide useful information about the typical abundance of several key VOCs and can be used to constrain chemical transport mode

GANDALF (Gas Analyzer for Nitrogen Dioxide Applying Laser-induced Fluorescence), a new instrument for the detection of nitrogen dioxide based on the laserinduced fluorescence (LIF) technique, is presented in this paper. GANDALF is designed for ground-based and airborne deployment with a robust calibration system. In the current set-up, it uses a multi-mode diode laser (447-450 nm) and performs in situ, continuous, and autonomous measurements with a laser pulse repetition rate of 5 MHz. The performance of GANDALF was tested during the summer of year 2011 (15 August-10 September) in a field experiment at Kleiner Feldberg, Germany. The location is within a forested region with an urban influence, where NOx levels were between 0.12 and 22 parts per billion by volume (ppb). Based on the field results, the limit of detection is estimated at 5- 10 parts per trillion by volume (ppt) in 60 s at a signal-tonoise ratio (SNR) of 2. The overall accuracy and precision of the instrument are better than 5% (1) and 0:5%C3 ppt (1 min-1), respectively. A comparison of nitrogen dioxide measurements based on several techniques during the field campaign PARADE 2011 is presented to explore methodic differences.

We present findings from the Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign, which took place in the coastal city of Wollongong in New SouthWales, Australia. We focus on a few key air quality indicators, along with a comparison to regional scale chemical transport model predictions at a spatial resolution of 1 km by 1 km. We find that the CSIRO chemical transport model provides accurate simulations of ozone concentrations at most times, but underestimates the ozone enhancements that occur during extreme temperature events. Themodel alsomeets previously published performance standards for fine particulate matter less than 2.5 microns in diameter (PM2.5), and the larger aerosol fraction (PM10). We explore the observed composition of the atmosphere within this urban air-shed during the MUMBA campaign and discuss the different influences on air quality in the city. Our findings suggest that further improvements to our ability to simulate air quality in this coastal city can be made through more accurate anthropogenic and biogenic emissions inventories and better understanding of the impact of extreme temperatures on air quality. The challenges in modelling air quality within the urban air-shed ofWollongong, including difficulties in accurate simulation of the local meteorology, are likely to be replicated in many other coastal cities in the Southern Hemisphere.

Particle number size distributions are among the most important parameters in trying to understand the characteristics of particle population. Atmospheric particles were measured in an interaction of mixed environments in the Southeastern coastal city of Wollongong, Australia, during a comprehensive field campaign known as Measurements of Urban, Marine and Biogenic Air (MUMBA). MUMBA ran in summer season between 21 st December 2012 and 15 th February 2013. Particle number concentrations measured during this campaign were indicative of the interplay between marine environments and urban air which met the objective of this campaign. Particle number size distributions ranging from 14 nm to 660 nm in diameter, as measured by Scanning Mobility Particle Sizer (SMPS) in this study, were grouped using Principal Component Analysis. Based on strong component loadings (value ≥ 0.75), three different factors were identified (i) Small Factor (N S ): 15 nm < Dp < 50 nm, (ii) Medium Factor (N M ): 60 nm < Dp < 150 nm and (iii) Large Factor (N L ): 210 nm < Dp < 450 nm. The three factors describe 89% of the dataset cumulative variance. Particles in this region are dependent upon the interaction between the sources, and cannot be viewed as a simple mixture of biogenic and anthropogenic sources associated with various mechanical processes. The particles observed in the morning were found to be influenced by combustion emissions, presumably primarily from traffic, which is most obvious in N L . The particle population during the day was found to be influenced by a mixture of marine sources and secondary aerosols production initiated by photochemical oxidation. The local steel works and the urban environment were the major contributors of particles at night. Secondary organic aerosols were identified in this study by the mass ratio of organic carbon to elemental carbon (OC/EC). Biogenic sources influenced secondary organic aerosols formation as a moderate correlation (R 2 = 0.6) was ob

We present findings from the Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign, which took place in the coastal city of Wollongong in New SouthWales, Australia. We focus on a few key air quality indicators, along with a comparison to regional scale chemical transport model predictions at a spatial resolution of 1 km by 1 km. We find that the CSIRO chemical transport model provides accurate simulations of ozone concentrations at most times, but underestimates the ozone enhancements that occur during extreme temperature events. Themodel alsomeets previously published performance standards for fine particulate matter less than 2.5 microns in diameter (PM2.5), and the larger aerosol fraction (PM10). We explore the observed composition of the atmosphere within this urban air-shed during the MUMBA campaign and discuss the different influences on air quality in the city. Our findings suggest that further improvements to our ability to simulate air quality in this coastal city can be made through more accurate anthropogenic and biogenic emissions inventories and better understanding of the impact of extreme temperatures on air quality. The challenges in modelling air quality within the urban air-shed ofWollongong, including difficulties in accurate simulation of the local meteorology, are likely to be replicated in many other coastal cities in the Southern Hemisphere.

Particle number size distributions are among the most important parameters in trying to understand the characteristics of particle population. Atmospheric particles were measured in an interaction of mixed environments in the Southeastern coastal city of Wollongong, Australia, during a comprehensive field campaign known as Measurements of Urban, Marine and Biogenic Air (MUMBA). MUMBA ran in summer season between 21 st December 2012 and 15 th February 2013. Particle number concentrations measured during this campaign were indicative of the interplay between marine environments and urban air which met the objective of this campaign. Particle number size distributions ranging from 14 nm to 660 nm in diameter, as measured by Scanning Mobility Particle Sizer (SMPS) in this study, were grouped using Principal Component Analysis. Based on strong component loadings (value ≥ 0.75), three different factors were identified (i) Small Factor (N S ): 15 nm < Dp < 50 nm, (ii) Medium Factor (N M ): 60 nm < Dp < 150 nm and (iii) Large Factor (N L ): 210 nm < Dp < 450 nm. The three factors describe 89% of the dataset cumulative variance. Particles in this region are dependent upon the interaction between the sources, and cannot be viewed as a simple mixture of biogenic and anthropogenic sources associated with various mechanical processes. The particles observed in the morning were found to be influenced by combustion emissions, presumably primarily from traffic, which is most obvious in N L . The particle population during the day was found to be influenced by a mixture of marine sources and secondary aerosols production initiated by photochemical oxidation. The local steel works and the urban environment were the major contributors of particles at night. Secondary organic aerosols were identified in this study by the mass ratio of organic carbon to elemental carbon (OC/EC). Biogenic sources influenced secondary organic aerosols formation as a moderate correlation (R 2 = 0.6) was ob

The Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign took place in Wollongong, New South Wales (a small coastal city approximately 80 km south of Sydney, Australia) from 21 December 2012 to 15 February 2013. Like many Australian cities, Wollongong is surrounded by dense eucalyptus forest, so the urban airshed is heavily influenced by biogenic emissions. Instruments were deployed during MUMBA to measure the gaseous and aerosol composition of the atmosphere with the aim of providing a detailed characterisation of the complex environment of the ocean-forest-urban interface that could be used to test the skill of atmospheric models. The gases measured included ozone, oxides of nitrogen, carbon monoxide, carbon dioxide, methane and many of the most abundant volatile organic compounds. The aerosol characterisation included total particle counts above 3 nm, total cloud condensation nuclei counts, mass concentration, number concentration size distribution, aerosol chemical analyses and elemental analysis. The campaign captured varied meteorological conditions, including two extreme heat events, providing a potentially valuable test for models of future air quality in a warmer climate. There was also an episode when the site sampled clean marine air for many hours, providing a useful additional measure of the background concentrations of these trace gases within this poorly sampled region of the globe. In this paper we describe the campaign, the meteorology and the resulting observations of atmospheric composition in general terms in order to equip the reader with a sufficient understanding of the Wollongong regional influences to use the MUMBA datasets as a case study for testing a chemical transport model. The data are available from PANGAEA (http: //doi.pangaea.de/10.1594/PANGAEA.871982).

We analysed the extensive dataset from the HUMPPA-COPEC 2010 and the HOPE 2012 field campaigns in the boreal forest and rural environments of Finland and Germany, respectively, and estimated the abundance of stabilised Criegee intermediates (SCIs) in the lower troposphere. Based on laboratory tests, we propose that the background OH signal observed in our IPI-LIF-FAGE instrument during the aforementioned campaigns is caused at least partially by SCIs. This hypothesis is based on observed correlations with temperature and with concentrations of unsaturated volatile organic compounds and ozone. Just like SCIs, the background OH concentration can be removed through the addition of sulfur dioxide. SCIs also add to the previously underestimated production rate of sulfuric acid. An average estimate of the SCI concentration of ∼ 5.0 x 104 molecules cm−3 (with an order of magnitude uncertainty) is calculated for the two environments. This implies a very low ambient concentration of SCIs, though, over the boreal forest, significant for the conversion of SO2 into H2SO4. The large uncertainties in these calculations, owing to the many unknowns in the chemistry of Criegee intermediates, emphasise the need to better understand these processes and their potential effect on the self-cleaning capacity of the atmosphere.

The Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign took place in Wollongong, New South Wales (a small coastal city approximately 80 km south of Sydney, Australia) from 21 December 2012 to 15 February 2013. Like many Australian cities, Wollongong is surrounded by dense eucalyptus forest, so the urban airshed is heavily influenced by biogenic emissions. Instruments were deployed during MUMBA to measure the gaseous and aerosol composition of the atmosphere with the aim of providing a detailed characterisation of the complex environment of the ocean-forest-urban interface that could be used to test the skill of atmospheric models. The gases measured included ozone, oxides of nitrogen, carbon monoxide, carbon dioxide, methane and many of the most abundant volatile organic compounds. The aerosol characterisation included total particle counts above 3 nm, total cloud condensation nuclei counts, mass concentration, number concentration size distribution, aerosol chemical analyses and elemental analysis. The campaign captured varied meteorological conditions, including two extreme heat events, providing a potentially valuable test for models of future air quality in a warmer climate. There was also an episode when the site sampled clean marine air for many hours, providing a useful additional measure of the background concentrations of these trace gases within this poorly sampled region of the globe. In this paper we describe the campaign, the meteorology and the resulting observations of atmospheric composition in general terms in order to equip the reader with a sufficient understanding of the Wollongong regional influences to use the MUMBA datasets as a case study for testing a chemical transport model. The data are available from PANGAEA (http: //doi.pangaea.de/10.1594/PANGAEA.871982).

We analysed the extensive dataset from the HUMPPA-COPEC 2010 and the HOPE 2012 field campaigns in the boreal forest and rural environments of Finland and Germany, respectively, and estimated the abundance of stabilised Criegee intermediates (SCIs) in the lower troposphere. Based on laboratory tests, we propose that the background OH signal observed in our IPI-LIF-FAGE instrument during the aforementioned campaigns is caused at least partially by SCIs. This hypothesis is based on observed correlations with temperature and with concentrations of unsaturated volatile organic compounds and ozone. Just like SCIs, the background OH concentration can be removed through the addition of sulfur dioxide. SCIs also add to the previously underestimated production rate of sulfuric acid. An average estimate of the SCI concentration of ∼ 5.0 x 104 molecules cm−3 (with an order of magnitude uncertainty) is calculated for the two environments. This implies a very low ambient concentration of SCIs, though, over the boreal forest, significant for the conversion of SO2 into H2SO4. The large uncertainties in these calculations, owing to the many unknowns in the chemistry of Criegee intermediates, emphasise the need to better understand these processes and their potential effect on the self-cleaning capacity of the atmosphere.

The Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign took place in Wollongong, New South Wales (a small coastal city approximately 80 km south of Sydney, Australia) from 21 December 2012 to 15 February 2013. Like many Australian cities, Wollongong is surrounded by dense eucalyptus forest, so the urban airshed is heavily influenced by biogenic emissions. Instruments were deployed during MUMBA to measure the gaseous and aerosol composition of the atmosphere with the aim of providing a detailed characterisation of the complex environment of the ocean-forest-urban interface that could be used to test the skill of atmospheric models. The gases measured included ozone, oxides of nitrogen, carbon monoxide, carbon dioxide, methane and many of the most abundant volatile organic compounds. The aerosol characterisation included total particle counts above 3 nm, total cloud condensation nuclei counts, mass concentration, number concentration size distribution, aerosol chemical analyses and elemental analysis. The campaign captured varied meteorological conditions, including two extreme heat events, providing a potentially valuable test for models of future air quality in a warmer climate. There was also an episode when the site sampled clean marine air for many hours, providing a useful additional measure of the background concentrations of these trace gases within this poorly sampled region of the globe. In this paper we describe the campaign, the meteorology and the resulting observations of atmospheric composition in general terms in order to equip the reader with a sufficient understanding of the Wollongong regional influences to use the MUMBA datasets as a case study for testing a chemical transport model. The data are available from PANGAEA (http: //doi.pangaea.de/10.1594/PANGAEA.871982).

Atmospheric concentrations of nitrous acid (HONO), one of the major precursors of the hydroxyl radical (OH) in the troposphere, significantly exceed the values predicted by the assumption of a photostationary state (PSS) during daytime. Therefore, additional sources of HONO were intensively investigated in the last decades. This study presents budget calculations of HONO based on simultaneous measurements of all relevant species, including HONO and OH at two different measurement heights, i.e. 1 m above the ground and about 2 to 3 m above the canopy (24 m above the ground), conducted in a boreal forest environment. We observed mean HONO concentrations of about 6.5 x 108 molecules cm−3 (26 ppt) during daytime, more than 20 times higher than expected from the PSS of 0.2 x 108 molecules cm−3 (1 ppt). To close the budgets at both heights, a strong additional source term during daytime is required. This unidentified source is at its maximum at noon (up to 1.1 x 106 molecules cm−3 s−1, 160 ppt h−1) and in general up to 2.3 times stronger above the canopy than close to the ground. The insignificance of known gas phase reactions and other processes like dry deposition or advection compared to the photolytic decomposition of HONO at this measurement site was an ideal prerequisite to study possible correlations of this unknown term to proposed HONO sources. But neither the proposed emissions from soils nor the proposed photolysis of adsorbed HNO3 contributed substantially to the unknown source. However, the unknown source was found to be perfectly correlated to the unbalanced photolytic loss of HONO.

Atmospheric concentrations of nitrous acid (HONO), one of the major precursors of the hydroxyl radical (OH) in the troposphere, significantly exceed the values predicted by the assumption of a photostationary state (PSS) during daytime. Therefore, additional sources of HONO were intensively investigated in the last decades. This study presents budget calculations of HONO based on simultaneous measurements of all relevant species, including HONO and OH at two different measurement heights, i.e. 1 m above the ground and about 2 to 3 m above the canopy (24 m above the ground), conducted in a boreal forest environment. We observed mean HONO concentrations of about 6.5 x 108 molecules cm−3 (26 ppt) during daytime, more than 20 times higher than expected from the PSS of 0.2 x 108 molecules cm−3 (1 ppt). To close the budgets at both heights, a strong additional source term during daytime is required. This unidentified source is at its maximum at noon (up to 1.1 x 106 molecules cm−3 s−1, 160 ppt h−1) and in general up to 2.3 times stronger above the canopy than close to the ground. The insignificance of known gas phase reactions and other processes like dry deposition or advection compared to the photolytic decomposition of HONO at this measurement site was an ideal prerequisite to study possible correlations of this unknown term to proposed HONO sources. But neither the proposed emissions from soils nor the proposed photolysis of adsorbed HNO3 contributed substantially to the unknown source. However, the unknown source was found to be perfectly correlated to the unbalanced photolytic loss of HONO.

A photochemical box model constrained by ancillary observations was used to simulate OH and HO 2 concentrations for three days of ambient observations during the HOxComp field campaign held in Jülich, Germany in July 2005. Daytime OH levels observed by four instruments were fairly well reproduced to within 33% by a base model run (Regional Atmospheric Chemistry Mechanism with updated isoprene chemistry adapted from Master Chemical Mechanism ver. 3.1) with high R 2 values (0.72-0.97) over a range of isoprene (0.3-2 ppb) and NO (0.1-10 ppb) mixing ratios. Daytime HO 2(*) levels, reconstructed from the base model results taking into account the sensitivity toward speciated RO 2 (organic peroxy) radicals, as recently reported from one of the participating instruments in the HO 2 measurement mode, were 93% higher than the observations made by the single instrument. This also indicates an overprediction of the HO 2 to OH recycling. Together with the good model-measurement agreement for OH, it implies a missing OH source in the model. Modeled OH and HO 2(*) could only be matched to the observations by addition of a strong unknown loss process for HO 2(*) that recycles OH at a high yield. Adding to the base model, instead, the recently proposed isomerization mechanism of isoprene peroxy radicals (Peeters and Müller, 2010) increased OH and HO 2(*) by 28% and 13% on average. Although these were still only 4% higher than the OH observations made by one of the instruments, larger overestimations (42-70%) occurred with respect to the OH observations made by the other three instruments. The overestimation in OH could be diminished only when reactive alkanes (HC8) were solely introduced to the model to explain the missing fraction of observed OH reactivity. Moreover, the overprediction of HO 2(*) became even larger than in the base case. These analyses imply that the rates of the isomerization are not readily supported by the ensemble of radical observations. One of the measuremen

A photochemical box model constrained by ancillary observations was used to simulate OH and HO 2 concentrations for three days of ambient observations during the HOxComp field campaign held in Jülich, Germany in July 2005. Daytime OH levels observed by four instruments were fairly well reproduced to within 33% by a base model run (Regional Atmospheric Chemistry Mechanism with updated isoprene chemistry adapted from Master Chemical Mechanism ver. 3.1) with high R 2 values (0.72-0.97) over a range of isoprene (0.3-2 ppb) and NO (0.1-10 ppb) mixing ratios. Daytime HO 2(*) levels, reconstructed from the base model results taking into account the sensitivity toward speciated RO 2 (organic peroxy) radicals, as recently reported from one of the participating instruments in the HO 2 measurement mode, were 93% higher than the observations made by the single instrument. This also indicates an overprediction of the HO 2 to OH recycling. Together with the good model-measurement agreement for OH, it implies a missing OH source in the model. Modeled OH and HO 2(*) could only be matched to the observations by addition of a strong unknown loss process for HO 2(*) that recycles OH at a high yield. Adding to the base model, instead, the recently proposed isomerization mechanism of isoprene peroxy radicals (Peeters and Müller, 2010) increased OH and HO 2(*) by 28% and 13% on average. Although these were still only 4% higher than the OH observations made by one of the instruments, larger overestimations (42-70%) occurred with respect to the OH observations made by the other three instruments. The overestimation in OH could be diminished only when reactive alkanes (HC8) were solely introduced to the model to explain the missing fraction of observed OH reactivity. Moreover, the overprediction of HO 2(*) became even larger than in the base case. These analyses imply that the rates of the isomerization are not readily supported by the ensemble of radical observations. One of the measuremen

A photochemical box model constrained by ancillary observations was used to simulate OH and HO 2 concentrations for three days of ambient observations during the HOxComp field campaign held in Jülich, Germany in July 2005. Daytime OH levels observed by four instruments were fairly well reproduced to within 33% by a base model run (Regional Atmospheric Chemistry Mechanism with updated isoprene chemistry adapted from Master Chemical Mechanism ver. 3.1) with high R 2 values (0.72-0.97) over a range of isoprene (0.3-2 ppb) and NO (0.1-10 ppb) mixing ratios. Daytime HO 2(*) levels, reconstructed from the base model results taking into account the sensitivity toward speciated RO 2 (organic peroxy) radicals, as recently reported from one of the participating instruments in the HO 2 measurement mode, were 93% higher than the observations made by the single instrument. This also indicates an overprediction of the HO 2 to OH recycling. Together with the good model-measurement agreement for OH, it implies a missing OH source in the model. Modeled OH and HO 2(*) could only be matched to the observations by addition of a strong unknown loss process for HO 2(*) that recycles OH at a high yield. Adding to the base model, instead, the recently proposed isomerization mechanism of isoprene peroxy radicals (Peeters and Müller, 2010) increased OH and HO 2(*) by 28% and 13% on average. Although these were still only 4% higher than the OH observations made by one of the instruments, larger overestimations (42-70%) occurred with respect to the OH observations made by the other three instruments. The overestimation in OH could be diminished only when reactive alkanes (HC8) were solely introduced to the model to explain the missing fraction of observed OH reactivity. Moreover, the overprediction of HO 2(*) became even larger than in the base case. These analyses imply that the rates of the isomerization are not readily supported by the ensemble of radical observations. One of the measuremen