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Isoprene is a chemical compound emitted naturally by soil, microorganisms, plants, and animals into the atmosphere. But plants are the largest emission source, and the amount of emission depends on plant species, weather conditions, and environmental conditions, including exposure to environmental stresses such as heat and drought. Isoprene is very reactive in the atmosphere and is involved in atmospheric physicochemical processes that can impact atmospheric chemistry, air quality, and regional climate. Quantification and understanding of the atmospheric processes influenced by isoprene result from a combination of observational experiments and estimates obtained from computational models. However, only a few long-term observational experiments have been conducted in the largest source of isoprene to the global atmosphere – the Amazon rainforest, and there are still uncertainties in the model estimates. Recent experiments have also shown that the models have greater uncertainty when estimating intra- and inter-annual variations in isoprene. This study aimed to improve our understanding of isoprene emission from a central Amazonian site by considering biological and environmental factors influencing emission on intra- and interannual time scales. By combining observational datasets, we adapted a widely used computational model of isoprene emission to observed conditions in the field. Our observations indicated that isoprene emission was not as high as the model estimated when the forest experienced environmental stress, such as heat and drought, in the 2015 El-niño year. In addition, observations revealed that the model performed well when diurnal variations were analyzed but not when long-term variations occurred. The performance for estimating intra- and inter-annual isoprene emission improved when the model was modified on two biological factors – (i) the amount of different leaf ages throughout the year and (ii) the emission rates of these different leaf ages. This shows that isoprene emission estimates can be improved when biological processes are mechanistically incorporated into the model.

Secondary organic aerosol (SOA) makes a sizable contribution to fine-particulate-matter (PM2.5) pollution, especially during high-PM episodes. Past studies of SOA evolution at the episode scale mainly rely on measurements of bulk SOA mass, with few studies probing individual SOA molecular tracers. In this study, we continuously monitored (at a bi-hourly resolution) SOA tracers specific to a few common volatile organic compound (VOC) precursors at a suburban site in Hong Kong for a 4-month period from the end of August to December 2020. The SOA molecules include tracers for SOA derived from biomass burning (BB) emissions, monoaromatics, naphthalene/methylnaphthalenes, and three biogenic VOCs (isoprene, monoterpene, and sesquiterpene). Generally, the SOA tracers showed regional characteristics for both anthropogenic and biogenic SOA as well as for the BB-derived SOA. This work focused on the seasonal variation and evolution characteristics of SOA tracers during 11 city-wide PM2.5 episodes, which are defined as periods with PM2.5 concentrations exceeding 35 µg m−3 at 3 or more of the 15 general air quality monitoring stations cross the city. Mass increment ratios (MIR), calculated as the ratio of the mass concentration prior to an episode to that during an episode, were examined for individual species during each episode. During most episodes, the SOA tracer concentrations were enhanced (i.e. MIR >1), and the maximum MIR values were in the range of 5.5–11.0 for SOA tracers of different precursors. Episodes on summer and fall days showed notably larger MIR values than those falling on winter days, indicating the higher importance of SOA to the formation of summer/fall PM2.5 episodes. Simultaneous monitoring of six tracers for isoprene SOA revealed the dominance of the low-NOx pathway in forming isoprene SOA in our study region. The multiple monoterpene SOA products suggested fresher SOA in winter, evidenced by the increased presence of the early-generation products. Thus, the current study has shown by example the precursor-specific SOA chemical evolution characteristics during PM2.5 episodes in different seasons. This study also suggests the necessity to apply high-time-resolution organic marker measurement at multiple sites in order to fully capture the spatial heterogeneity of haze pollution at the city scale.

Halocarbons have been recognized for their role as major ozone-depleting substances (ODSs) since the 1970s, and some also function as greenhouse gases (GHGs). International agreements, such as the Montreal Protocol, Kyoto Protocol, and Paris Agreement, were established for worldwide cooperation to gradually reduce the production and use of halocarbons. Initial success was achieved in phasing out global chlorofluorocarbon (CFC) production, but recent studies found an unexpected decrease in the rate of decline in the atmospheric concentration of trichlorofluoromethane (CFC-11) after 2012.Historically, halocarbons have been emitted from various anthropogenic sources (e.g., the dry cleaning industry, electronic industry, and refrigeration) in Hong Kong. Emission sources in the Pearl River Delta (PRD) region, such as chemical manufacturing, also have remarkable impacts on the ambient halocarbons in Hong Kong. The ambient mixing ratios of major CFCs were declining in Hong Kong and the PRD region before 2010. However, no continuous measurements of ambient halocarbons were conducted in Hong Kong after 2010. Given that CFC emissions from the PRD region account for up to 25% of their total emissions in China, any unexpected CFC emissions in recent years will have significant impacts on the atmospheric abundance of halocarbons worldwide.We have been continuously monitoring ambient halocarbons in Hong Kong since Fall 2020. The temporal variability of major halocarbons and their source origins have been extensively investigated using multiple approaches. Our results indicate lower enhancements beyond the background values for major regulated CFCs and CCl4 than later controlled HCFCs and HFCs, suggesting the greater progress of Montreal Protocol implementation for the former species. The notable high enhancement values of non-regulated halocarbons from the north direction indicate their widespread usage in China. This work provides insight into the progress made in implementing the Montreal Protocol in Hong Kong and the surrounding region and the importance of continuous emission control.

The volatile organic compounds emitted by plants significantly impact the atmospheric environment. The impacts of drought stress on the biogenic volatile organic compound (BVOC) emissions of plants are still under debate. In this study, the effects of two drought–rehydration cycle groups with different durations on isoprene emissions from Populus nigra (black poplar) seedlings were studied. The P. nigra seedlings were placed in a chamber that controlled the soil water content, radiation, and temperature. The daily emissions of isoprene and physiological parameters were measured. The emission rates of isoprene (Fiso) reached the maximum on the third day (D3), increasing by 58.0% and 64.2% compared with the controlled groups, respectively, and then Fiso significantly decreased. Photosynthesis decreased by 34.2% and 21.6% in D3 in the first and second groups, respectively. After rehydration, Fiso and photosynthesis recovered fully in two groups. However, Fiso showed distinct inconsistencies in two groups, and the recovery rates of Fiso in the second drought group were slower than the recovery rates of Fiso in the first groups. The response of BVOC emissions during the drought-rehydration cycle was classified into three phases, including stimulated, inhibited, and restored after rehydration. The emission pattern of isoprene indicated that isoprene played an important role in the response of plants to drought stress. A drought–rehydration model was constructed, which indicated the regularity of BVOC emissions in the drought–rehydration cycle. BVOC emissions were extremely sensitive to drought, especially during droughts of short duration. Parameters in computational models related to BVOC emissions of plants under drought stress should be continuously improved.

Despite being regulated globally for almost three decades, halocarbon continues to play a vital role in climate change and ozone layer because of its long lifetime in the ambient air. In recent years, unexpected halocarbon emissions have been found in Asia, raising concerns about ozone recovery. As a number of studies focused on halocarbon variations and source profiles, there is an increasing need to identify halocarbon source origins. In this study, an eight-month regular air sampling was conducted at a coastal site in Hong Kong from November 2020 to June 2021, and seventeen halocarbon species were selected for extensive investigation after advanced sample analysis in our laboratory. The temporal variations of halocarbon mixing ratio enhancements were analyzed, and the spatial variations of source origins were investigated by wind sectors and backward trajectory statistics. Our results indicate lower enhancements beyond the background values for major regulated CFCs and CCl

Biogenic volatile organic compounds (BVOCs) are important drivers of atmospheric chemical composition and accurate model simulations require characterization of the emissions associated with specific vegetation types which is typically determined using enclosure measurements. Static enclosure techniques were used for past BVOC emission measurement studies, especially in the 1960s–1980s, but are no longer widely used because of concerns that the resulting emission rates are not representative. The main advantages of the static approach are the capability for rapid measurements and a lower detection limit that enables the use of less sensitive analytical techniques. We evaluate a version of the static approach which we call the semi-static approach. In order to evaluate the performance of the semi-static approach for BVOCs emission measurements, multiple replicate measurements for different plants were conducted in a laboratory growth chamber using both semi-static and dynamic enclosure techniques. Variability of replicate measurements was calculated and the results from the two techniques were compared. The semi-static technique provided consistent measurements for isoprene but not for α-pinene, β-pinene and other compounds that are stored in leaves. The measured isoprene emission factors were much higher than dynamic measurements. There were a large number of compounds to be detected by dynamic technique that could not be detected by the semi-static technique. But the semi-static technique could still provide qualitative information on categorization of non, low and high emitters for some compounds.

We present trace gas vertical profiles observed by instruments on the NASA DC-8 and at a ground site during the Korea-US air quality study (KORUS) field campaign in May to June 2016. We focus on the region near the Seoul metropolitan area and its surroundings where both anthropogenic and natural emission sources play an important role in local photochemistry. Integrating ground and airborne observations is the major research goal of many atmospheric chemistry field campaigns. Although airborne platforms typically aim to sample from near surface to the free troposphere, it is difficult to fly very close to the surface especially in environments with complex terrain or a populated area. A detailed analysis integrating ground and airborne observations associated with specific concentration footprints indicates that reactive trace gases are quickly oxidized below an altitude of 700 m. The total OH reactivity profile has a rapid decay in the lower part of troposphere from surface to the lowest altitude (700 m) sampled by the NASA DC-8. The decay rate is close to that of very reactive biogenic volatile organic compounds such as monoterpenes. Therefore, we argue that photochemical processes in the bottom of the boundary layer, below the typical altitude of aircraft sampling, should be thoroughly investigated to properly assess ozone and secondary aerosol formation.

We report OH reactivity observations by a chemical ionization mass spectrometer – comparative reactivity method (CIMS-CRM) instrument in a suburban forest of the Seoul Metropolitan Area (SMA) during Korea US Air Quality Study (KORUS-AQ 2016) from mid-May to mid-June of 2016. A comprehensive observational suite was deployed to quantify reactive trace gases inside of the forest canopy including a high-resolution proton transfer reaction time of flight mass spectrometer (PTR-ToF-MS). An average OH reactivity of 30.7 ± 5.1 s−1 was observed, while the OH reactivity calculated from CO, NO + NO2 (NOx), ozone (O3), sulfur dioxide (SO2), and 14 volatile organic compounds (VOCs) was 11.8 ± 1.0 s−1. An analysis of 346 peaks from the PTR-ToF-MS accounted for an additional 6.0 ± 2.2 s−1 of the total measured OH reactivity, leaving 42.0 % missing OH reactivity. The missing OH reactivity most likely comes from VOC oxidation products of both biogenic and anthropogenic origin.

Isoprene regulates large-scale biogeochemical cycles by influencing atmospheric chemical and physical processes, and its dominant sources to the global atmosphere are the tropical forests. Although global and regional model estimates of isoprene emission have been optimized in the last decades, modeled emissions from tropical vegetation still carry high uncertainty due to a poor understanding of the biological and environmental controls on emissions. It is already known that isoprene emission quantities may vary significantly with plant traits, such as leaf phenology, and with the environment; however, current models still lack of good representation for tropical plant species due to the very few observations available. In order to create a predictive framework for the isoprene emission capacity of tropical forests, it is necessary an improved mechanistic understanding on how the magnitude of emissions varies with plant traits and the environment in such ecosystems. In this light, we aimed to quantify the isoprene emission capacity of different tree species across leaf ages, and combine these leaf measurements with long-term canopy measurements of isoprene and its biological and environmental drivers; then, use these results to better parameterize isoprene emissions estimated by MEGAN. We measured at the Amazon Tall Tower Observatory (ATTO) site, central Amazonia: (1) isoprene emission capacity at different leaf ages of 21 trees species; (2) isoprene canopy mixing ratios during six campaigns from 2013 to 2015; (3) isoprene tower flux during the dry season of 2015 (El-Niño year); (3) environmental factors – air temperature and photosynthetic active radiation (PAR) - from 2013 to 2018; and (4) biological factors – leaf demography and phenology (tower based measurements) from 2013 to 2018. We then parameterized the leaf age algorithm of MEGAN with the measurements of isoprene emission capacity at different leaf ages and the tower-based measurements of leaf demography and phenology. Modeling estimates were later compared with measurements (canopy level) and five years of satellite-derived isoprene emission (OMI) from the ATTO domain (2013-2017). Leaf level of isoprene emission capacity showed lower values for old leaves (> 6 months) and young leaves (< 2 months), compared to mature leaves (2-6 months); and our model results suggested that this affects seasonal ecosystem isoprene emission capacity, since the demography of the different leaf age classes varied a long of the year. We will present more results on how changes in leaf demography and phenology and in temperature and PAR affect seasonal ecosystem isoprene emission, and how modeling can be improved with the optimization of the leaf age algorithm. In addition, we will present a comparison of ecosystem isoprene emission of normal years (2013, 2014, 2017 years) and anomalous years (2015 - El-Niño; and 2016 - post El-Niño), and discuss how a strong El-Niño year can influence plant functional strategies that can be carried over to the consecutive year and potentially affect isoprene emission.

Isoprene fluxes vary seasonally with changes in environmental factors (e.g., solar radiation and temperature) and biological factors (e.g., leaf phenology). However, our understanding of the seasonal patterns of isoprene fluxes and the associated mechanistic controls is still limited, especially in Amazonian evergreen forests. In this paper, we aim to connect intensive, field-based measurements of canopy isoprene flux over a central Amazonian evergreen forest site with meteorological observations and with tower-mounted camera leaf phenology to improve our understanding of patterns and causes of isoprene flux seasonality. Our results demonstrate that the highest isoprene emissions are observed during the dry and dry-to-wet transition seasons, whereas the lowest emissions were found during the wet-to-dry transition season. Our results also indicate that light and temperature cannot totally explain isoprene flux seasonality. Instead, the camera-derived leaf area index (LAI) of recently mature leaf age class (e.g., leaf ages of 3–5 months) exhibits the highest correlation with observed isoprene flux seasonality (R2=0.59, p). Attempting to better represent leaf phenology in the Model of Emissions of Gases and Aerosols from Nature (MEGAN 2.1), we improved the leaf age algorithm by utilizing results from the camera-derived leaf phenology that provided LAI categorized into three different leaf ages. The model results show that the observations of age-dependent isoprene emission capacity, in conjunction with camera-derived leaf age demography, significantly improved simulations in terms of seasonal variations in isoprene fluxes (R2=0.52, p). This study highlights the importance of accounting for differences in isoprene emission capacity across canopy leaf age classes and identifying forest adaptive mechanisms that underlie seasonal variation in isoprene emissions in Amazonia.

Isoprene, a dominant biogenic volatile organic compound that is mainly emitted by trees, has a significant impact on the atmospheric chemistry. Regional to global changes in biogenic isoprene emission associated with vegetation variations between 2000 and 2015 were estimated using the MEGAN model with satellite land cover data for inputs in this study. The satellite data estimates of land cover changes were compared to results from previous investigators that have either conducted regional studies or have used lower resolution land cover data. The analysis indicates that tree coverage increases of >5% occurred in 13% of locations including in central China and Europe. In contrast, a decrease of >5% was observed in about 5% of locations, especially in tropical regions. The trends in global tree coverage from 2000 to 2015 resulted in a global isoprene emission decrease of only 1.5%, but there were significant regional variations. Obvious decreases in tree coverage in some tropical areas (e.g., Amazon Basin, Western Africa, Southeast Asia) resulted in a similar to 10% reduction of regional isoprene emission due to agricultural expansion. Distinct increments of isoprene emission (5-10%) were mainly found in Northeast China and India and were associated with afforestation efforts. Deforestation and afforestation associated with managed plantations does not only affect the total forest coverage but also impacts average isoprene emission capacity, which can result in accelerated isoprene emission variations. Consequently, isoprene variation assessments are needed that not only account for changes in vegetation fractions but also consider the changes in plant species compositions of forests and other landscapes.

One of the least understood aspects in atmospheric chemistry is how urban emissions influence the formation of natural organic aerosols, which affect Earth’s energy budget. The Amazon rainforest, during its wet season, is one of the few remaining places on Earth where atmospheric chemistry transitions between preindustrial and urban-influenced conditions. Here, we integrate insights from several laboratory measurements and simulate the formation of secondary organic aerosols (SOA) in the Amazon using a high-resolution chemical transport model. Simulations show that emissions of nitrogen-oxides from Manaus, a city of ~2 million people, greatly enhance production of biogenic SOA by 60–200% on average with peak enhancements of 400%, through the increased oxidation of gas-phase organic carbon emitted by the forests. Simulated enhancements agree with aircraft measurements, and are much larger than those reported over other locations. The implication is that increasing anthropogenic emissions in the future might substantially enhance biogenic SOA in pristine locations like the Amazon., It remains unclear how urban emissions influence the formation of secondary organic aerosols (SOA), including in the Amazon forest. Here, the authors simulate the formation of SOAs in the Amazon using a high-resolution regional chemical transport model. They find that urban emissions of NOx from Manaus enhance the production of biogenic SOA by 60–200%.

Satellite observations of nitrogen dioxide (NO2) have often been used to derive nitrogen oxides (NOx = NO + NO2) emissions. A widely used inversion method was developed by Martin et al. (2003). Refinements of this method were subsequently developed. In the context of this inversion method, we show that the local derivative (of a first-order Taylor expansion) is more appropriate than the “bulk ratio” (ratio of emission to column) used in the original formulation for polluted regions. Using the bulk ratio can lead to biases in regions of high NOx emissions such as eastern China due to chemical non-linearity. Inverse modelling using the local derivative method is applied to both GOME-2 and OMI satellite measurements to estimate anthropogenic NOx emissions over eastern China. Compared with the traditional method using bulk ratio, the local derivative method produces more consistent NOx emission estimates between the inversion results using GOME-2 and OMI measurements. The results also show significant changes in the spatial distribution of NOx emissions, especially over high emission regions of eastern China. We further discuss a potential pitfall of using the difference of two satellite measurements to derive NOx emissions. Our analysis suggests that chemical non-linearity needs to be accounted for and that a careful bias analysis is required in order to use the satellite differential method in inverse modelling of NOx emissions.

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface scheme CLM4 (Community Land Model version 4.0) in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a stand-alone vegetation map that differs from what is used by land surface schemes. This improved modeling framework is used to investigate the impact of two land surface schemes, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provided an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface schemes do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry and, consequently, secondary organic aerosol formation.

Nitryl chloride (ClNO2) is a radical reservoir species that releases chlorine radicals upon photolysis. An integrated analysis of the impact of ClNO2 on regional photochemistry in the Seoul metropolitan area (SMA) during the Korea–United States Air Quality Study (KORUS-AQ) 2016 field campaign is presented. Comprehensive multiplatform observations were conducted aboard the NASA DC-8 and at two ground sites (Olympic Park, OP; Taehwa Research Forest, TRF), representing an urbanized area and a forested suburban region, respectively. Positive correlations between daytime Cl2 and ClNO2 were observed at both sites, the slope of which was dependent on O3 levels. The possible mechanisms are explored through box model simulations constrained with observations. The overall diurnal variations in ClNO2 at both sites appeared similar but the nighttime variations were systematically different. For about half of the observation days at the OP site the level of ClNO2 increased at sunset but rapidly decreased at around midnight. On the other hand, high levels were observed throughout the night at the TRF site. Significant levels of ClNO2 were observed at both sites for 4–5 h after sunrise. Airborne observations, box model calculations, and back-trajectory analysis consistently show that these high levels of ClNO2 in the morning are likely from vertical or horizontal transport of air masses from the west. Box model results show that chlorine-radical-initiated chemistry can impact the regional photochemistry by elevating net chemical production rates of ozone by ∼25 % in the morning.

We present a characterization of the chemical composition of the atmosphere of the Brazilian Amazon rainforest based on trace gases measurements carried out during the South American Biomass Burning Analysis (SAMBBA) airborne experiment in September 2012. We analyzed the observations of primary biomass burning emission tracers, i.e., carbon monoxide (CO) and nitrogen oxides (NOx), ozone (O3), isoprene, and its main oxidation products, methyl vinyl ketone (MVK), methacrolein (MACR), and hydroxyhydroperoxides (ISOPOOH). The focus of SAMBBA was primarily on biomass burning emissions, but there were also several flights in areas of the Amazon forest not directly affected by biomass burning, revealing a background with a signature of biomass burning in the chemical composition due to long-range transport of biomass burning tracers from both Africa and the eastern part of Amazonia. We used the [MVK + MACR + ISOPOOH] / [Isoprene] ratio and the hydroxyl radical (OH) indirect calculation to assess the oxidative capacity of the Amazon forest atmosphere. We compared the background regions (CO

Isoprene and monoterpene emission rates are essential inputs for atmospheric chemistry models that simulate atmospheric oxidant and particle distributions. Process studies of the biochemical and physiological mechanisms controlling these emissions are advancing our understanding and the accuracy of model predictions but efforts to quantify regional emissions have been limited by a lack of constraints on regional distributions of ecosystem emission capacities. We used an airborne wavelet-based eddy covariance measurement technique to characterize isoprene and monoterpene fluxes with high spatial resolution during the 2013 SAS (Southeast Atmosphere Study) in the southeastern United States. The fluxes measured by direct eddy covariance were comparable to emissions independently estimated using an indirect inverse modeling approach. Isoprene emission factors based on the aircraft wavelet flux estimates for high isoprene chemotypes (e.g., oaks) were similar to the MEGAN2.1 biogenic emission model estimates for landscapes dominated by oaks. Aircraft flux measurement estimates for landscapes with fewer isoprene emitting trees (e.g., pine plantations), were about a factor of two lower than MEGAN2.1 model estimates. The tendency for high isoprene emitters in these landscapes to occur in the shaded understory, where light dependent isoprene emissions are diminished, may explain the lower than expected emissions. This result demonstrates the importance of accurately representing the vertical profile of isoprene emitting biomass in biogenic emission models. Airborne measurement-based emission factors for high monoterpene chemotypes agreed with MEGAN2.1 in landscapes dominated by pine (high monoterpene chemotype) trees but were more than a factor of three higher than model estimates for landscapes dominated by oak (relatively low monoterpene emitting) trees. This results suggests that unaccounted processes, such as floral emissions or light dependent monoterpene emissions, or vegetation other than high monoterpene emitting trees may be an important source of monoterpene emissions in those landscapes and should be identified and included in biogenic emission models.

Isoprene dominates global non-methane volatile organic compound emissions, and impacts tropospheric chemistry by influencing oxidants and aerosols. Isoprene emission rates vary over several orders of magnitude for different plants, and characterizing this immense biological chemodiversity is a challenge for estimating isoprene emission from tropical forests. Here we present the isoprene emission estimates from aircraft eddy covariance measurements over the Amazonian forest. We report isoprene emission rates that are three times higher than satellite top-down estimates and 35% higher than model predictions. The results reveal strong correlations between observed isoprene emission rates and terrain elevations, which are confirmed by similar correlations between satellite-derived isoprene emissions and terrain elevations. We propose that the elevational gradient in the Amazonian forest isoprene emission capacity is determined by plant species distributions and can substantially explain isoprene emission variability in tropical forests, and use a model to demonstrate the resulting impacts on regional air quality., Isoprene emissions are commonly estimated using satellite measurements and model simulations. Here, using eddy covariance, the authors report higher emission rates over the Amazon forest than those estimated with these techniques and a relationship between terrain elevation and isoprene emissions.

The production of sulfate aerosols through sulfur chemistry in marine environments is critical to the tropical climate system. However, not all sulfur compounds have been studied in detail. One such compound is methanesulfonic acid (MSA). In this study, we use a one-dimensional chemical transport model to analyze the observed vertical profiles of gas phase MSA during the Pacific Atmospheric Sulfur Experiment. The observed sharp decrease in MSA from the surface to 600 m implies a surface source of 4.0 × 107 molecules/cm2/s. Evidence suggests that this source is photolytically enhanced in daytime. We also find that the observed large increase of MSA from the boundary layer into the lower free troposphere (1000–2000 m) results mainly from the degassing of MSA from dehydrated aerosols. We estimate a source of 1.2 × 107 molecules/cm2/s to the free troposphere through this pathway. This source of soluble MSA could potentially provide an important precursor for new particle formation in the free troposphere over the tropics, affecting the climate system through aerosol-cloud interactions.

Inverse modeling using satellite observations of nitrogen dioxide (NO2) columns has been extensively used to estimate nitrogen oxides (NOx) emissions in China. Recently, the Global Ozone Monitoring Experiment-2 (GOME-2) and Ozone Monitoring Instrument (OMI) provide independent global NO2 column measurements on a nearly daily basis at around 9:30 and 13:30 local time across the equator, respectively. Anthropogenic NOx emission estimates by applying previously developed monthly inversion (MI) or daily inversion (DI) methods to these two sets of measurements show substantial differences. We improve the DI method by conducting model simulation, satellite retrieval, and inverse modeling sequentially on a daily basis. After each inversion, we update anthropogenic NOx emissions in the model simulation with the newly obtained a posteriori results. Consequently, the inversion-optimized emissions are used to compute the a priori NO2 profiles for satellite retrievals. As such, the a priori profiles used in satellite retrievals are now coupled to inverse modeling results. The improved procedure was applied to GOME-2 and OMI NO2 measurements in 2011. The new daily retrieval-inversion (DRI) method estimates an average NOx emission of 6.9 Tg N/yr over China, and the difference between using GOME-2 and OMI measurements is 0.4 Tg N/yr, which is significantly smaller than the difference of 1.3 Tg N/yr using the previous DI method. Using the more consistent DRI inversion results, we find that anthropogenic NOx emissions tend to be higher in winter and summer than spring (and possibly fall) and the weekday-to-weekend emission ratio tends to increase with NOx emission in China.

Satellite observations of nitrogen dioxide (NO2) have often been used to derive nitrogen oxides (NOx = NO + NO2) emissions. A widely used inversion method was developed by Martin et al. (2003). Refinements of this method were subsequently developed. In the context of this inversion method, we show that the local derivative (of a first-order Taylor expansion) is more appropriate than the “bulk ratio” (ratio of emission to column) used in the original formulation for polluted regions. Using the bulk ratio can lead to biases in regions of high NOx emissions such as eastern China due to chemical nonlinearity. Inverse modeling using the local derivative method is applied to both GOME-2 and OMI satellite measurements to estimate anthropogenic NOx emissions over eastern China. Compared with the traditional method using bulk ratio, the local derivative method produces more consistent NOx emission estimates between the inversion results using GOME-2 and OMI measurements. The results also show significant changes in the spatial distribution of NOx emissions especially over high emission regions of eastern China. We further discuss a potential pitfall of using the difference of two satellite measurements to derive NOx emissions. Our analysis suggests that chemical nonlinearity needs to be accounted for and that a careful bias analysis is required in order to use the satellite differential method in inverse modeling of NOx emissions.

Current climate models still have large uncertainties in estimating biogenic trace gases, which can significantly affect atmospheric chemistry and secondary aerosol formation that ultimately influences air quality and aerosol radiative forcing. These uncertainties result from many factors, including uncertainties in land-surface processes and specification of vegetation types, both of which can affect the simulated near-surface fluxes of biogenic volatile organic compounds (BVOCs). In this study, the latest version of Model of Emissions of Gases and Aerosols from Nature (MEGAN v2.1) is coupled within the land surface parameterization CLM4 in the Weather Research and Forecasting model with chemistry (WRF-Chem). In this implementation, MEGAN v2.1 shares a consistent vegetation map with CLM4 for estimating BVOC emissions. This is unlike MEGAN v2.0 in the public version of WRF-Chem that uses a standalone vegetation map that differs from what is used by land surface parameterizations. This improved modeling framework is used to investigate the impact of two land surface parameterizations, CLM4 and Noah, on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. The measurements collected during the Carbonaceous Aerosol and Radiative Effects Study (CARES) and the California Nexus of Air Quality and Climate Experiment (CalNex) conducted in June of 2010 provide an opportunity to evaluate the simulated BVOCs. Sensitivity experiments show that land surface parameterizations do influence the simulated BVOCs, but the impact is much smaller than that of vegetation distributions. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover datasets for climate and air quality models in terms of simulating BVOCs, oxidant chemistry, and consequently secondary organic aerosol formation.

We analyze summertime photochemistry near the surface in Beijing, China, using a 1-D photochemical model (Regional chEmical and trAnsport Model, REAM-1D) constrained by in situ observations, focusing on the budgets of ROx (OH + HO2 + RO2) radicals and O3 formation. While the modeling analysis focuses on near-surface photochemical budgets, the implications for the budget of O3 in the planetary boundary layer are also discussed. In terms of daytime average, the total ROx primary production rate near the surface in Beijing is 6.6 ppbv per hour (ppbv h−1, among the highest found in urban atmospheres. The largest primary ROx source in Beijing is photolysis of oxygenated volatile organic compounds (OVOCs), which produces HO2 and RO2 at 2.5 ppbv h−1 and 1.7 ppbv h−1, respectively. Photolysis of excess HONO from an unknown heterogeneous source is the predominant primary OH source at 2.2 ppbv h−1, much larger than that of O1D+H2O (0.4 ppbv h−1). The largest ROx sink is via OH + NO2 reaction (1.6 ppbv h−1), followed by formation of RO2NO2 (1.0 ppbv h−1) and RONO2 (0.7 ppbv h−1). Due to the large aerosol surface area, aerosol uptake of HO2 appears to be another important radical sink, although the estimate of its magnitude is highly variable depending on the uptake coefficient value used. The daytime average O3 production and loss rates near the surface are 32 ppbv h−1 and 6.2 ppbv h−1, respectively. Assuming NO2 to be the source of excess HONO, the NO2 to HONO transformation leads to considerable O3 loss and reduction of its lifetime. Our observation-constrained modeling analysis suggests that oxidation of VOCs (especially aromatics) and heterogeneous reactions (e.g. HONO formation and aerosol uptake HO2) play potentially critical roles in the primary radical budget and O3 formation in Beijing. One important ramification is that O3 production is neither NOx nor VOC limited, but in a transition regime where reduction of either NOx or VOCs could result in reduction of O3 production. The transition regime implies more flexibility in the O3 control strategies than a binary system of either NOx or VOC limited regime. The co-benefit of concurrent reduction of both NOx and VOCs in reducing column O3 production integrated in the planetary boundary layer is significant. Further research on the spatial extent of the transition regime over the polluted eastern China is critically important for controlling regional O3 pollution.

Using a GC/FID/MS system, we analyzed the mixing ratio of 16 halocarbon species in more than 100 air samples collected in 2004 from the Pearl River Delta (PRD) region of southern China. The results revealed that there are elevated mixing ratios for most of halocarbons, especially for HClC = CCl2 (trichloroethylene, TCE), CH2Cl2 (dichloromethane, DCM), CH3 Br (bromomethane), HCFC-22, CHCl3 (trichloromethane), CCl4 (tetrachloromethane), Cl2C = CCl2 (perchloroethylene, PCE), CH3CCl3 (methyl chloroform, MCF), and CFC-12. Comparisons were done with the data from TRACE-P and ALE/GAGE/AGAGE experiments, we found that the large variability in mixing ratios (relative standard deviation ranged from 9.31 % to 96.55 %) of the halocarbons suggested substantial local emissions from the PRD region in 2004. Correlations between the mixing ratio of each species and carbon monoxide (CO) was examined, and then the emission of each halocarbon was quantified based on scaling the optimized CO emission inventory with the slope of the regression line fitted to each species relative to CO. The calculated results revealed that mass of CH2Cl2 (7.0 Gg), CH3CCl3 (6.7 Gg), and Cl2C = CCl2 (2.3 Gg) accounted for about 62.9 % of total halocarbon emissions, it suggested a significant contribution from solvent use in the PRD region. Emissions of HCFC-22 (3.5 Gg), an alternative refrigerant to chlorofluorocarbons (CFCs), were about 2.3 times greater than those of CFC-12 (1.6 Gg). CFC-12 and HCFC-22 accounted for 21.5 % of total emissions of halocarbons, so that the refrigerant would be the second largest source of halocarbons. However, the ratio approach found only minor emissions of CFCs, such as CFC-11, and the emission of CFC-114 and CFC-113 were close to zero. Emissions of other anthropogenic halocarbons, such as CCl4, CHCl3, CH3Br, and CH3Cl, were also estimated. Where possible, the emissions estimated from the measured ratios were compared with results from source inventory techniques, we found that both approaches gave emissions at similar magnitude for most of the halocarbons, except CFC-11. The comparison suggested that the ratio method may be a useful tool for assessing regional halocarbon emissions, and emission uncertainty could be further reduced by incorporating both longer-term and higher-frequency observations, as well as improving the accuracy of the CO inventory.

The Pacific Atmospheric Sulfur Experiment (PASE) is the first sulfur-budget field experiment to feature simultaneous flux measurements of DMS marine emissions and SO2 deposition to the ocean surface. We make use of these data to constrain a 1-D chemical transport model to study the production and loss pathways for DMS and SO2 over the equatorial Pacific. Model results suggest that OH is the main sink for DMS in the boundary layer (BL), and the average DMS-to-SO2 conversion efficiency is ~73%. In an exploratory run involving the addition of 1 pptv of BrO as a second oxidant, a 14% increase in the DMS flux is needed beyond that based on OH oxidation alone. This BrO addition also reduces the DMS-to-SO2 conversion efficiency from 73% to 60%. The possibility of non-DMS sources of marine sulfur influencing the estimated conversion efficiency was explored and found to be unconvincing. For BL conditions, SO2 losses consist of 48% dry deposition, while transport loss to the BuL and aerosol scavenging each account for another 19%. The conversion of SO2 to H2SO4 consumes the final 14%. In the BuL, cloud scavenging removes 85% of the SO2, thus resulting in a decreasing vertical profile for SO2. The average SO2 dry deposition velocity from direct measurements (i.e., 0.36 cm sec−1) is approximately 50% of what is calculated from the 1-D model and the global GEOS-Chem model. This suggests that the current generation of global models may be significantly overestimating SO2 deposition rates over some tropical marine areas. Although the specific mechanism cannot be determined, speculation here is that the dry deposition anomalous results may point to the presence of a micro-surface chemical phenomenon involving partial saturation with either S(IV) and/or S(VI) DMS oxidation products. This could also appear as a pH drop in the ocean’s surface microfilm layer in this region. Finally, we propose that the enhanced SO2 level observed in the lower free troposphere versus that in the upper BuL during PASE is most likely the result of transported DMS/SO2-rich free-tropospheric air parcels from the east of the PASE sampling area, rather than an inadequate representation in the model of local convection.

We analyzed satellite observations of nitrogen dioxide (NO2) columns by the Ozone Monitoring Instrument (OMI) over China from 2005 to 2010 in order to estimate the top-down anthropogenic nitrogen oxides (NOx) emission trends. Since NOx emissions were affected by the economic slowdown in 2009, we removed one year of abnormal data in the analysis. The estimated average emission trend is 4.01 ± 1.39% yr(-1), which is slower than the trend of 5.8-10.8% yr(-1) reported for previous years. We find large regional, seasonal, and urban-rural variations in emission trends. The average NOx emission trend of 3.47 ± 1.07% yr(-1) in warm season (June-September) is less than the trend of 5.03 ± 1.92% yr(-1) in cool season (October-May). The regional annual emission trends decrease from 4.76 ± 1.61% yr(-1) in North China Plain to 3.11 ± 0.98% yr(-1) in Yangtze River Delta and further down to -4.39 ± 1.81% yr(-1) in Pearl River Delta. The annual emission trends of the four largest megacities, Shanghai, Beijing, Guangzhou, and Shenzhen are -0.76 ± 0.29%, 0.69 ± 0.27%, -4.46 ± 1.22%, and -7.18 ± 2.88% yr(-1), considerably lower than the regional averages or surrounding rural regions. These results appear to suggest that a number of factors, including emission control measures of thermal power plants, increased hydro-power usage, vehicle emission regulations, and closure or migration of high-emission industries, have significantly reduced or even reversed the increasing trend of NOx emissions in more economically developed megacities and southern coastal regions, but their effects are not as significant in other major cities or less economically developed regions.

We analyze the observations of near-surface peroxy acetyl nitrate (PAN) and its precursors in Beijing, China in August of 2007. The levels of PAN are remarkably high (up to 14 ppbv), surpassing those measured over other urban regions in recent years. Analyses employing a 1-D version of a chemical transport model (Regional chEmical and trAnsport Model, REAM) indicate that aromatic non-methane hydrocarbons (NMHCs) are the dominant (55-75%) PAN source. The major oxidation product of aromatics that produces acetyl peroxy radicals is methylglyoxal (MGLY). PAN and O(3) in the observations are correlated at daytime; aromatic NMHCs appear to play an important role in O(3) photochemistry. Previous NMHC measurements indicate the presence of reactive aromatics at high levels over broad polluted regions of China. Aromatics are often ignored in global and (to a lesser degree) regional 3D photochemical transport models; their emissions over China as well as photochemistry are quite uncertain. Our findings suggest that critical assessments of aromatics emissions and chemistry (such as the yields of MGLY) are necessary to understand and assess ozone photochemistry and regional pollution export in China.