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Atmospheric CH4 and CO2 enhancements and biomass burning emission ratios derived from satellite observations of the 2015 Indonesian fire plumes

The 2015–2016 strong El Niño event has had a dramatic impact on the amount of Indonesian biomass burning, with the El Niño-driven drought further desiccating the already-drier-than-normal landscapes that are the result of decades of peatland draining, widespread deforestation, anthropogenically driven forest degradation and previous large fire events. It is expected that the 2015–2016 Indonesian fires will have emitted globally significant quantities of greenhouse gases (GHGs) to the atmosphere, as did previous El Niño-driven fires in the region. The form which the carbon released from the combustion of the vegetation and peat soils takes has a strong bearing on its atmospheric chemistry and climatological impacts. Typically, burning in tropical forests and especially in peatlands is expected to involve a much higher proportion of smouldering combustion than the more flaming-characterised fires that occur in fine-fuel-dominated environments such as grasslands, consequently producing significantly more CH4 (and CO) per unit of fuel burned. However, currently there have been no aircraft campaigns sampling Indonesian fire plumes, and very few ground-based field campaigns (none during El Niño), so our understanding of the large-scale chemical composition of these extremely significant fire plumes is surprisingly poor compared to, for example, those of southern Africa or the Amazon. Here, for the first time, we use satellite observations of CH4 and CO2 from the Greenhouse gases Observing SATellite (GOSAT) made in large-scale plumes from the 2015 El Niño-driven Indonesian fires to probe aspects of their chemical composition. We demonstrate significant modifications in the concentration of these species in the regional atmosphere around Indonesia, due to the fire emissions. Using CO and fire radiative power (FRP) data from the Copernicus Atmosphere Service, we identify fire-affected GOSAT soundings and show that peaks in fire activity are followed by subsequent large increases in regional greenhouse gas concentrations. CH4 is particularly enhanced, due to the dominance of smouldering combustion in peatland fires, with CH4 total column values typically exceeding 35 ppb above those of background “clean air” soundings. By examining the CH4 and CO2 excess concentrations in the fire-affected GOSAT observations, we determine the CH4 to CO2 (CH4 ∕ CO2) fire emission ratio for the entire 2-month period of the most extreme burning (September–October 2015), and also for individual shorter periods where the fire activity temporarily peaks. We demonstrate that the overall CH4 to CO2 emission ratio (ER) for fires occurring in Indonesia over this time is 6.2 ppb ppm−1. This is higher than that found over both the Amazon (5.1 ppb ppm−1) and southern Africa (4.4 ppb ppm−1), consistent with the Indonesian fires being characterised by an increased amount of smouldering combustion due to the large amount of organic soil (peat) burning involved. We find the range of our satellite-derived Indonesian ERs (6.18–13.6 ppb ppm−1) to be relatively closely matched to that of a series of close-to-source, ground-based sampling measurements made on Kalimantan at the height of the fire event (7.53–19.67 ppb ppm−1), although typically the satellite-derived quantities are slightly lower on average. This seems likely because our field sampling mostly intersected smaller-scale peat-burning plumes, whereas the large-scale plumes intersected by the GOSAT Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) footprints would very likely come from burning that was occurring in a mixture of fuels that included peat, tropical forest and already-cleared areas of forest characterised by more fire-prone vegetation types than the natural rainforest biome (e.g. post-fire areas of ferns and scrubland, along with agricultural vegetation). The ability to determine large-scale ERs from satellite data allows the combustion behaviour of very large regions of burning to be characterised and understood in a way not possible with ground-based studies, and which can be logistically difficult and very costly to consider using aircraft observations. We therefore believe the method demonstrated here provides a further important tool for characterising biomass burning emissions, and that the GHG ERs derived for the first time for these large-scale Indonesian fire plumes during an El Niño event point to more routinely assessing spatiotemporal variations in biomass burning ERs using future satellite missions. These will have more complete spatial sampling than GOSAT and will enable the contributions of these fires to the regional atmospheric chemistry and climate to be better understood.
Nine years of global hydrocarbon emissions based on source inversion of OMI formaldehyde observations

As formaldehyde (HCHO) is a high-yield product in the oxidation of most volatile organic compounds (VOCs) emitted by fires, vegetation, and anthropogenic activities, satellite observations of HCHO are well-suited to inform us on the spatial and temporal variability of the underlying VOC sources. The long record of space-based HCHO column observations from the Ozone Monitoring Instrument (OMI) is used to infer emission flux estimates from pyrogenic and biogenic volatile organic compounds (VOCs) on the global scale over 2005–2013. This is realized through the method of source inverse modeling, which consists in the optimization of emissions in a chemistry-transport model (CTM) in order to minimize the discrepancy between the observed and modeled HCHO columns. The top–down fluxes are derived in the global CTM IMAGESv2 by an iterative minimization algorithm based on the full adjoint of IMAGESv2, starting from a priori emission estimates provided by the newly released GFED4s (Global Fire Emission Database, version 4s) inventory for fires, and by the MEGAN-MOHYCAN inventory for isoprene emissions. The top–down fluxes are compared to two independent inventories for fire (GFAS and FINNv1.5) and isoprene emissions (MEGAN-MACC and GUESS-ES). The inversion indicates a moderate decrease (ca. 20 %) in the average annual global fire and isoprene emissions, from 2028 Tg C in the a priori to 1653 Tg C for burned biomass, and from 343 to 272 Tg for isoprene fluxes. Those estimates are acknowledged to depend on the accuracy of formaldehyde data, as well as on the assumed fire emission factors and the oxidation mechanisms leading to HCHO production. Strongly decreased top–down fire fluxes (30–50 %) are inferred in the peak fire season in Africa and during years with strong a priori fluxes associated with forest fires in Amazonia (in 2005, 2007, and 2010), bushfires in Australia (in 2006 and 2011), and peat burning in Indonesia (in 2006 and 2009), whereas generally increased fluxes are suggested in Indochina and during the 2007 fires in southern Europe. Moreover, changes in fire seasonal patterns are suggested; e.g., the seasonal amplitude is reduced over southeast Asia. In Africa, the inversion indicates increased fluxes due to agricultural fires and decreased maxima when natural fires are dominant. The top–down fire emissions are much better correlated with MODIS fire counts than the a priori inventory in regions with small and agricultural fires, indicating that the OMI-based inversion is well-suited to assess the associated emissions. Regarding biogenic sources, significant reductions in isoprene fluxes are inferred in tropical ecosystems (30–40 %), suggesting overestimated basal emission rates in those areas in the bottom–up inventory, whereas strongly positive isoprene emission updates are derived over semiarid and desert areas, especially in southern Africa and Australia. This finding suggests that the parameterization of the soil moisture stress used in MEGAN greatly exaggerates the flux reduction due to drought in those regions. The isoprene emission trends over 2005–2013 are often enhanced after optimization, with positive top–down trends in Siberia (4.2 % year−1) and eastern Europe (3.9 % year−1), likely reflecting forest expansion and warming temperatures, and negative trends in Amazonia (−2.1 % year−1), south China (−1 % year−1), the United States (−3.7 % year−1), and western Europe (−3.3 % year−1), which are generally corroborated by independent studies, yet their interpretation warrants further investigation.
Characteristics of vertical air motion in isolated convective clouds

The vertical velocity and air mass flux in isolated convective clouds are statistically analyzed using aircraft in situ data collected from three field campaigns: High-Plains Cumulus (HiCu) conducted over the midlatitude High Plains, COnvective Precipitation Experiment (COPE) conducted in a midlatitude coastal area, and Ice in Clouds Experiment-Tropical (ICE-T) conducted over a tropical ocean. The results show that small-scale updrafts and downdrafts (<  500 m in diameter) are frequently observed in the three field campaigns, and they make important contributions to the total air mass flux. The probability density functions (PDFs) and profiles of the observed vertical velocity are provided. The PDFs are exponentially distributed. The updrafts generally strengthen with height. Relatively strong updrafts (>  20 m s−1) were sampled in COPE and ICE-T. The observed downdrafts are stronger in HiCu and COPE than in ICE-T. The PDFs of the air mass flux are exponentially distributed as well. The observed maximum air mass flux in updrafts is of the order 104 kg m−1 s−1. The observed air mass flux in the downdrafts is typically a few times smaller in magnitude than that in the updrafts. Since this study only deals with isolated convective clouds, and there are many limitations and sampling issues in aircraft in situ measurements, more observations are needed to better explore the vertical air motion in convective clouds.
Characteristics of total gaseous mercury (TGM) concentrations in an industrial complex in South Korea: impacts from local sources

Total gaseous mercury (TGM) concentrations were measured every 5 min in Pohang, Gyeongsangbuk-do, Korea, during summer (17–23 August 2012), fall (9–17 October 2012), winter (22–29 January 2013), and spring (26 March–3 April 2013) to (1) characterize the hourly and seasonal variations of atmospheric TGM concentrations; (2) identify the relationships between TGM and co-pollutants; and (3) identify likely source directions and locations of TGM using the conditional probability function (CPF), conditional bivariate probability function (CBPF) and total potential source contribution function (TPSCF). The TGM concentration was statistically significantly highest in fall (6.7 ± 6.4 ng m−3), followed by spring (4.8 ± 4.0 ng m−3), winter (4.5 ± 3.2 ng m−3) and summer (3.8 ± 3.9 ng m−3). There was a weak but statistically significant negative correlation between the TGM concentration and ambient air temperature (r = −0.08, p<0.05). Although the daytime temperature (14.7 ± 10.0 °C) was statistically significantly higher than that in the nighttime (13.0 ± 9.8 °C) (p<0.05), the daytime TGM concentration (5.3 ± 4.7 ng m−3) was statistically significantly higher than that in the nighttime (4.7 ± 4.7 ng m−3) (p<0.01), possibly due to local emissions related to industrial activities and activation of local surface emission sources. The observed ΔTGM ∕ ΔCO was significantly lower than that of Asian long-range transport, but similar to that of local sources in Korea and in US industrial events, suggesting that local sources are more important than those of long-range transport. CPF, CBPF and TPSCF indicated that the main sources of TGM were iron and manufacturing facilities, the hazardous waste incinerators and the coastal areas.
Carbon monoxide climatology derived from the trajectory mapping of global MOZAIC-IAGOS data

A three-dimensional gridded climatology of carbon monoxide (CO) has been developed by trajectory mapping of global MOZAIC-IAGOS in situ measurements from commercial aircraft data. CO measurements made during aircraft ascent and descent, comprising nearly 41 200 profiles at 148 airports worldwide from December 2001 to December 2012, are used. Forward and backward trajectories are calculated from meteorological reanalysis data in order to map the CO measurements to other locations and so to fill in the spatial domain. This domain-filling technique employs 15 800 000 calculated trajectories to map otherwise sparse MOZAIC-IAGOS data into a quasi-global field. The resulting trajectory-mapped CO data set is archived monthly from 2001 to 2012 on a grid of 5° longitude  ×  5° latitude  ×  1 km altitude, from the surface to 14 km altitude. The mapping product has been carefully evaluated, firstly by comparing maps constructed using only forward trajectories and using only backward trajectories. The two methods show similar global CO distribution patterns. The magnitude of their differences is most commonly 10 % or less and found to be less than 30 % for almost all cases. Secondly, the method has been validated by comparing profiles for individual airports with those produced by the mapping method when data from that site are excluded. While there are larger differences below 2 km, the two methods agree very well between 2 and 10 km with the magnitude of biases within 20 %. Finally, the mapping product is compared with global MOZAIC-IAGOS cruise-level data, which were not included in the trajectory-mapped data set, and with independent data from the NOAA aircraft flask sampling program. The trajectory-mapped MOZAIC-IAGOS CO values show generally good agreement with both independent data sets. Maps are also compared with version 6 data from the Measurements Of Pollution In The Troposphere (MOPITT) satellite instrument. Both data sets clearly show major regional CO sources such as biomass burning in Central and southern Africa and anthropogenic emissions in eastern China. While the maps show similar features and patterns, and relative biases are small in the lowermost troposphere, we find differences of ∼  20 % in CO volume mixing ratios between 500 and 300 hPa. These upper-tropospheric biases are not related to the mapping procedure, as almost identical differences are found with the original in situ MOZAIC-IAGOS data. The total CO trajectory-mapped MOZAIC-IAGOS column is also higher than the MOPITT CO total column by 12–16 %. The data set shows the seasonal CO cycle over different latitude bands and altitude ranges as well as long-term trends over different latitude bands. We observe a decline in CO over the northern hemispheric extratropics and the tropics consistent with that reported by previous studies using other data sources. We anticipate use of the trajectory-mapped MOZAIC-IAGOS CO data set as an a priori climatology for satellite retrieval and for air quality model validation and initialization.
Atmospheric salt deposition in a tropical mountain rainforest at the eastern Andean slopes of south Ecuador – Pacific or Atlantic origin?

Sea salt (NaCl) has recently been proven to be of the utmost importance for ecosystem functioning in Amazon lowland forests because of its impact on herbivory, litter decomposition and, thus, carbon cycling. Sea salt deposition should generally decline as distance from its marine source increases. For the Amazon, a negative east–west gradient of sea salt availability is assumed as a consequence of the barrier effect of the Andes Mountains for Pacific air masses. However, this generalized pattern may not hold for the tropical mountain rainforest in the Andes of southern Ecuador. To analyse sea salt availability, we investigated the deposition of sodium (Na+) and chloride (Cl−), which are good proxies of sea spray aerosol. Because of the complexity of the terrain and related cloud and rain formation processes, sea salt deposition was analysed from both, rain and occult precipitation (OP) along an altitudinal gradient over a period between 2004 and 2009. To assess the influence of easterly and westerly air masses on the deposition of sodium and chloride over southern Ecuador, sea salt aerosol concentration data from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis data set and back-trajectory statistical methods were combined. Our results, based on deposition time series, show a clear difference in the temporal variation of sodium and chloride concentration and Na+ ∕ Cl− ratio in relation to height and exposure to winds. At higher elevations, sodium and chloride present a higher seasonality and the Na+ ∕ Cl− ratio is closer to that of sea salt. Medium- to long-range sea salt transport exhibited a similar seasonality, which shows the link between our measurements at high elevations and the sea salt synoptic transport. Although the influence of the easterlies was predominant regarding the atmospheric circulation, the statistical analysis of trajectories and hybrid receptor models revealed a stronger impact of the north equatorial Atlantic, Caribbean, and Pacific sea salt sources on the atmospheric sea salt concentration in southern Ecuador. The highest concentration in rain and cloud water was found between September and February when air masses originated from the north equatorial Atlantic, the Caribbean Sea and the equatorial Pacific. Together, these sources accounted for around 82.4 % of the sea salt budget over southern Ecuador.
Uptake of gaseous formaldehyde by soil surfaces: a combination of adsorption/desorption equilibrium and chemical reactions

Gaseous formaldehyde (HCHO) is an important precursor of OH radicals and a key intermediate molecule in the oxidation of atmospheric volatile organic compounds (VOCs). Budget analyses reveal large discrepancies between modeled and observed HCHO concentrations in the atmosphere. Here, we investigate the interactions of gaseous HCHO with soil surfaces through coated-wall flow tube experiments applying atmospherically relevant HCHO concentrations of ∼  10 to 40 ppbv. For the determination of uptake coefficients (γ), we provide a Matlab code to account for the diffusion correction under laminar flow conditions. Under dry conditions (relative humidity  =  0 %), an initial γ of (1.1 ± 0.05)  ×  10−4 is determined, which gradually drops to (5.5 ± 0.4)  ×  10−5 after 8 h experiments. Experiments under wet conditions show a smaller γ that drops faster over time until reaching a plateau. The drop of γ with increasing relative humidity as well as the drop over time can be explained by the adsorption theory in which high surface coverage leads to a reduced uptake rate. The fact that γ stabilizes at a non-zero plateau suggests the involvement of irreversible chemical reactions. Further back-flushing experiments show that two-thirds of the adsorbed HCHO can be re-emitted into the gas phase while the residual is retained by the soil. This partial reversibility confirms that HCHO uptake by soil is a complex process involving both adsorption/desorption and chemical reactions which must be considered in trace gas exchange (emission or deposition) at the atmosphere–soil interface. Our results suggest that soil and soil-derived airborne particles can either act as a source or a sink for HCHO, depending on ambient conditions and HCHO concentrations.
Impacts of historical climate and land cover changes on fine particulate matter (PM2.5) air quality in East Asia between 1980 and 2010

To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981–1985 and 2007–2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0–12.0 µg m−3 in northern China, but to an increase in summertime PM2.5 by 6.0–8.0 µg m−3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2–0.8 µg m−3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (−2.1 to +1.3 µg m−3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (−0.4 to +1.2 µg m−3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by −12.0 to +12.0 µg m−3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.
An evaluation of IASI-NH3 with ground-based Fourier transform infrared spectroscopy measurements

Global distributions of atmospheric ammonia (NH3) measured with satellite instruments such as the Infrared Atmospheric Sounding Interferometer (IASI) contain valuable information on NH3 concentrations and variability in regions not yet covered by ground-based instruments. Due to their large spatial coverage and (bi-)daily overpasses, the satellite observations have the potential to increase our knowledge of the distribution of NH3 emissions and associated seasonal cycles. However the observations remain poorly validated, with only a handful of available studies often using only surface measurements without any vertical information. In this study, we present the first validation of the IASI-NH3 product using ground-based Fourier transform infrared spectroscopy (FTIR) observations. Using a recently developed consistent retrieval strategy, NH3 concentration profiles have been retrieved using observations from nine Network for the Detection of Atmospheric Composition Change (NDACC) stations around the world between 2008 and 2015. We demonstrate the importance of strict spatio-temporal collocation criteria for the comparison. Large differences in the regression results are observed for changing intervals of spatial criteria, mostly due to terrain characteristics and the short lifetime of NH3 in the atmosphere. The seasonal variations of both datasets are consistent for most sites. Correlations are found to be high at sites in areas with considerable NH3 levels, whereas correlations are lower at sites with low atmospheric NH3 levels close to the detection limit of the IASI instrument. A combination of the observations from all sites (Nobs = 547) give a mean relative difference of −32.4 ± (56.3) %, a correlation r of 0.8 with a slope of 0.73. These results give an improved estimate of the IASI-NH3 product performance compared to the previous upper-bound estimates (−50 to +100 %).
One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.