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Background Uncomplicated hyperglycaemia is a common presentation in the emergency department (ED). Rapid glucose control is associated with the risk of iatrogenic hypoglycaemia. We sought to determine the safety of a rapid glucose control protocol delivered in a 24-h emergency department observation unit (OU). Methods This is a retrospective chart review of patients admitted to the OU for hyperglycaemia where the assessing clinician deemed there was no other reason for medical admission apart from hyperglycaemia; and that the patient could be safely discharged provided their hyperglycaemia was adequately treated. The rapid glucose control protocol consists of 4–6 hourly glucose monitoring and insulin injections according to a sliding scale. We report the demographics, reduction in glucose values and the incidence of hypoglycaemia in the OU. We also determine the rate of discharge from OU and the rate of hospital admission at 30 days. Results We included 101 patients. The mean age was 53.5 years (95% CI 50.4–56.6) and 64% of patients were male. The mean HbA1c value was 12.8% (95% CI 12.3–13.3). The mean admission and discharge glucose values were 27.2 (95% CI 26.3–28.1) and 13.9 (95% CI 13.2–14.6) mmols/l respectively. There was no incidence of hypoglycaemia in the OU. We successfully discharged 90.1% of the patients from the OU, of which 3 (3.3%) patients were admitted to the hospital within 30 days of discharge. Conclusion ED OU is a safe location to deliver effective management for patients presented with uncomplicated severe hyperglycaemia.

Background: Biogenic Volatile Organic Compounds (BVOCs) such as isoprene (C5H8) are ozone (O3) precursors that can be emitted at significant concentrations from the oil palm tree (Elaeis guineensis). Reactions involving BVOCs can lead to increased levels of surface O3 which can significantly impair air quality and cause crop damage. This study focuses on the link between isoprene, surface O3 and carbon dioxide (CO2) over an oil palm plantation and the effects of meteorological factors such as temperature and irradiance on the gas concentrations. The mixing ratios of isoprene, surface O3 and CO2 were measured using a portable gas chromatograph with a photoionization detector called ‘iDirac’, an EcoTech O3 analyser, and LI-COR, respectively. Atmospheric models were used for measured selected gases estimation and validation purposes.Results: Results showed that isoprene and surface O3 had maximum daytime mixing ratios of ~25 ppb and ~57 ppb, respectively. CO2 mixing ratios were high during the night compared to the day, with a maximum night-time ratio of ~883 ppm. It is also showed that suppression of isoprene emissions from plants by high CO2 concentrations during the night was due to the reduction of dimethylallyl diphosphate (DMADP) in the leaf cells. The meteorological parameters temperature and light intensity were significantly correlated with isoprene and surface O3, with r2=0.91 and p2=0.87 and p-2 h-1 which are higher than previous studies on pristine forest. This information together with the the in-situ measurement information on isoprene emission flux is then fed into the WRF-CMAQ atmospheric chemistry model to study the effect of oil palm plantation expansion over the years (2000 – 2016) on the local atmospheric chemistry.Conclusions: The in-situ of isoprene measurement in oil palm plantation has provided the variations of atmospheric concentration at different time scale which is important in giving information of surface O3 production. The relationship between isoprene-surface O3 and CO2-isoprene were interconnected at different time and influenced by meteorological factors. The model has discovered regions that are converted into oil palm plantation has experienced rise in isoprene concentration in region that are converted into oil palm plantation, and it even can be carried downwind up to 100 km inland of the emission source.

Ionization in Earth's troposphere is mainly due to Galactic cosmic rays. Occasionally, solar storms produce intense relativistic ion beams that significantly increase such ionization. One of the largest recorded solar radiation storms, on 20 January 2005, resulted in up to 55-fold increases in the count rates of ground-based particle detectors in polar regions. We use McMurdo and Inuvik neutron monitor data to estimate accurate time profiles of ion energy spectra above the atmosphere at each location. Using data-driven atmospheric models, we perform Monte Carlo simulations of particle-air interactions and calculate atmospheric ionization and potential biological dosage versus altitude and time for each location. We found that if airplane passengers had traversed the south polar region, they could have been exposed to the typical annual cosmic radiation dosage at sea level within 1 h. These techniques can help evaluate possible influences of solar activity on atmospheric properties.

Urbanized mountain valleys are usually prone to episodes of high concentrations of air pollutants due to the strong interplay between mountain meteorology and synoptic weather conditions. The mountain valley of Chiang Mai is engulfed by air pollutants with particulate matter (PM) concentration remaining above 50 µg m-3 (PM2.5, 24-hour average) during approximately 13 % days every year (mostly during February to April). This study presents the first time continuous measurements of mini- micro pulse LiDAR (MiniMPL) installed on the valley floor of Chiang Mai, providing vertical backscatter profile of aerosols and clouds from April 2017 onwards. This paper analyzes unique dataset of mixing layer (ML) height measurements made during April 2017 to June 2018 with a temporal resolution of 15 minutes. The ML height derived from the backscatter profile measurements are analyzed to understand the annual, monthly and diurnal variations. The ML height depicts distinct diurnal variations for all months of the year, evolving up to < 3.0 km during April to September. From October onwards the ML evolution is gradually inhibited, reducing to < 2.0 km during October to December and < 1.5 km during January to March. The variations in the concentration of PM were found to be partly modulated by the ML variations (Pearson coefficient ≈ −0.50) during dry season (February, March and April), possibly triggering the aerosol-boundary layer feedback mechanism for high concentrations (100 µg m-3) of PM and low ventilation in the valley. The inhibition of ML evolution due to feedback mechanism further escalates the high concentrations of PM, resulting in severe haze conditions on many days during the dry season.

We used a Weather Research and Forecasting Model with Chemistry (WRF-CHEM) model that includes anthropogenic emissions from EDGAR-HTAP, biomass burning from FINN, and biogenic emissions from MEGAN to investigate the main volatile organic compound (VOC) ozone precursors during high levels of biomass burning emissions in March 2014 over upper Southeast Asia. A comparison between the model and ground-based measurement data shows that the WRF-CHEM model simulates the precipitation and 2 m temperature reasonably well, with index of agreement (IOA) values ranging from 0.76 to 0.78. Further, the model predicts O3, NO2, and CO fairly well, with IOA values ranging from 0.50 to 0.57. However, the magnitude of the simulated NO2 concentration was generally underestimated compared to OMI satellite observations. The model result shows that CO and VOCs such as BIGENE play an important role in atmospheric oxidation to surface O3. In addition, biomass burning emissions are responsible for increasing surface O3 by ∼1 ppmv and increasing the reaction rate of CO and BIGENE by approximately 0.5 × 106 and 1 × 106 molecules/cm3/s, respectively, in upper Southeast Asia., Environmental science; Atmospheric science; Climatology; Environmental chemistry; Environmental pollution; Earth-surface processes; Volatile organic compounds; Surface ozone; WRF-CHEM model; Southeast Asia

Within our solar system, space weather is influenced by the solar wind and the interplanetary magnetic field carried by the solar wind plasma. Severe solar storms can expose people to increased radiation levels, shut down electrical systems, and interfere with radio signals. Space weather probably affects the weather and climate on our planet, but we do not yet have a precise understanding of the influence. Some aspects of space weather can be monitored at ground level with a detector, such as a “neutron monitor,” that measures cosmic rays from outer space. We have developed a portable “Changvan” neutron monitor to investigate the energy spectrum of cosmic rays and its solar modulation, i.e., variations over the typically 11-year sunspot cycle. The Changvan monitor located inside the insulated shipping container comprises three proportional counters in the standard-design neutron monitors, but the central counter is deficient in the lead producer. This monitor records counting rates during passage through a range of geomagnetic latitudes, which this technique is called “latitude survey.” The ultimate goal of the latitude surveys is to help accurately interpret data from every neutron monitor in a space environment that is always changing. In this work, we show a preliminary analysis of Changvan monitor data collected from two latitude surveys during 2019-2020 on the Chinese icebreaker MV Xue Long from Shanghai, China to Zhongshan station, Antarctica and back. A strong anti-correlation can be observed between the Changvan monitor count rate and barometric pressure.

A neutron monitor (NM) is a ground- (or sea-) based detector of the flux of cosmic ray particles in space. The high-energy cosmic rays in the GeV primary range interact in the upper atmosphere, producing a cascade of subatomic particles, some of which reach Earth’s surface. A neutron monitor is mostly sensitive to the neutron component of the atmospheric cascade. The standard-design neutron monitor (NM64) contains lead, the nuclei of which fragment when struck by a high-energy particle. Some of the fragments are neutrons which are moderated and trapped by polyethylene acting as a reflector and moderator. These neutrons can then be detected by induced nuclear fission of 10B in a 10BF3 gas proportional counter. The Changvan neutron monitor is a portable neutron monitor assembled in Thailand and housed in a standard insulated shipping container to conduct long-term research in polar regions. There are three proportional counters in the Changvan, but the central counter lacks the lead producer. Since the detector has a non-standard semi-leaded design, we examine the detection efficiency of the Changvan for neutrons and other atmospheric secondary particles. We are also developing an electronic board and a highly sensitive control module to reduce dead time to a minimum, for monitoring neutrons in the GeV energy range. Simulation results accounting for the dead time will also be reported.

The name “Changvan” is given to a transportable neutron monitor, modernized by researchers in Thailand and housed inside a standard-size shipping container. It contains three neutron-sensitive proportional counters, which contain enriched10BF3gas, to detect cosmic ray showers. Primary cosmic rays are high-energy particles arriving from outer space. By colliding with atoms in the atmosphere, they produce a shower of sub-atomic particles, called secondary particles. Some particles can reach the Earth’s surface, including neutrons. The Changvan is designed to measure atmospheric neutrons during a latitude survey. The side counter tubes are ringed with lead producer to produce evaporation neutrons when secondary particles collide with it. The center counter lacks the lead producer but can receive neutrons from nearby counters. The reflector and moderator made from polyethylene thermalize the evaporation neutrons and protect against disturbance by external low-energy neutrons. In this work, we pursue methods to determine spectral changes in Galactic cosmic rays using data from the Changvan, avoiding the systematic inconsistencies of cross-station comparisons. We examine neutron time delay histograms from the three counter tubes, as recorded by specially designed readout electronics, where the time delay refers to the time interval between consecutive neutron detections in one counter. We perform a preliminary analysis of such histograms to measure the leader fraction (L) of neutrons that do not follow a previous neutron from the same primary cosmic ray. The electronic dead time will be considered in theLcalculation.

Wollongong, Australia is an urban site at the intersection of anthropogenic, biomass burning, biogenic and marine sources of atmospheric trace gases. The location offers a valuable opportunity to study drivers of atmospheric composition in the Southern Hemisphere. Here, a record of surface carbon monoxide (CO), methane (CH4) and carbon dioxide (CO2) was measured with an in situ Fourier transform infrared trace gas analyser between April 2011 and August 2014. Clean air was found to arrive at Wollongong in approximately 10% of air masses. Biomass burning influence was evident in the average annual cycle of clean air CO during austral spring. A significant negative short-term trend was found in clean air CO (−1.5 nmol mol−1 a−1), driven by a reduction in northern Australian biomass burning. Significant short-term positive trends in clean air CH4 (5.4 nmol mol−1 a−1) and CO2 (1.9 μmol mol−1 a−1) were consistent with the long-term global average trends. Polluted Wollongong air was investigated using wind-direction/wind-speed clustering, which revealed major influence from local urban and industrial sources from the south. High values of CH4, with anthropogenic ΔCH4/ΔCO2 enhancement ratio signatures, originated from the northwest, in the direction of local coal mining. A pollution climatology was developed for the region using back trajectory analysis and ΔO3/ΔCO enhancement ratios. Ozone production environments in austral spring and summer were associated with anticyclonic meteorology on the east coast of Australia, while ozone depletion environments in autumn and winter were associated with continental transport, or fast moving trajectories from southern latitudes. This implies the need to consider meteorological conditions when developing policies for controlling air quality.

Two elevated fine particulate mass concentration events were observed in a span of a week in northern Philippines on March of 2017. Results from chemical characterization, lidar observation, and model simulations of particulate matter show the high aerosol concentration events to be caused by long range transport (LRT) of anthropogenic pollutants from northern East Asia at the surface and biomass burning emission from Indochina aloft. In this study, we investigated the transport path of these LRT aerosols and estimated their direct radiative forcing. A strong Siberian high and a confluent flow induced by a continental high over the main Asian continent and a cyclonic circulation over the south of Japan produced a strong northerly wind that carried pollutants from northern East Asia to northern Philippines. At the same time, strong westerlies 2–4 km aloft carried biomass burning emissions from Indochina, which also had an impact on ground concentration. Mass extinction efficiency of LRT aerosols was estimated to be in the range of 2.06–6.44 m2g-1 with a mean value of 4.32 ± 1.32 m2g−1. In addition, we calculated the direct radiative forcing effect under clear sky condition and found that the transported aerosols had a mean net negative forcing (cooling) effect of −50.80 ± 12.38 Wm−2 and −11.98 ± 3.96 Wm−2 on surface and at the top of the atmosphere, respectively. Such pollutant transport during wintertime cold surges had been shown to reduce local surface pollutants in northern China. Consequently, its impacts shift to downwind regions as far as the Philippines. As winter cold surge frequency increases due to the warming arctic, more LRT events may be expected as a result of climate change.

This chapter gives an overview of Project MANTRA (Multi-platform Analysis of Trace gases and Aerosols) focusing on atmospheric carbon dioxide. Specifically, this chapter addresses how surface CO2 data can be measured in a cost-effective manner. Applications are shown for measurements at Lampang Rajabhat University (LPRU), Thailand, at the University of the Philippines Institute of Environmental Science and Meteorology (UP-IESM) and at Binan, Laguna, Philippines. The measured data were also compared with simulations using the Regional Emissions Inventory in Asia (REAS ver. 2.1) and the Stochastic Time-Inverted Lagrangian Transport (STILT) model. Mobile measurements taken from the Lampang-Tak route in Thailand and from Quezon City-Baguio route in the Philippines are also shown. Broadening to the regional scale, measurements from the Ship of Opportunity (SOOP), from the High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observation (HIPPO) and from the Greenhouse gases Observing SATellite (GOSAT) over the Southeast Asian region are presented. New initiatives such as the Total Carbon Column Observing Network (TCCON) Southeast Asia are also introduced.

We have been continuously observing the daily Be-7 concentrations at Bangkok in Thailand ($13.765^\circ$ N, $100.526^\circ$ E) since June 2014 to investigate the relationship between solar activities and the variation of cosmogenic nuclides in low latitude. The Be-7 concentrations show a clear seasonal variation with the high and low concentrations during January to May and June to December, respectively, for each year. In order to understand the seasonal variations, we calculated back trajectories of air mass by HYSPLIT. The calculation indicates that the back trajectories are distinguished three patterns in a year, which are "Indian Ocean trajectories", "Continental trajectories", and "Pacific Ocean trajectories". Moreover, we estimated monthly amount of Be-7 coming to Bangkok for each trajectories by EXPACS. From these findings, the amount of Be-7 is high during Continental and Pacific Ocean trajectories. On the other hand, one is low during Indian Ocean trajectories. This phase of calculated Be-7 can explain the seasonal variation. Comparing this phase and the phase of observed Be-7 concentrations, there is a time lag of one or two months.

Weather forecasts dictate our daily activities and allow us to respond properly during extreme weather events. However, weather forecasts are never perfect, but differences with model output and with observations can be minimized. Discrepancies between meteorological observations and weather model outputs are often caused by resolution differences (point vs. grid comparisons) and by the parameterizations used in the model. Atmospheric model parameterization refers to substituting small-scale and complicated atmospheric processes by simplified ones. In order to make weather forecasts more accurate, one can either increase the model resolution or improve the parameterizations used. Increasing model resolution can simulate small-scale atmospheric processes better, but takes a longer simulation time. On the other hand, improving model parameterization schemes involve in-depth measurements, analysis and research on numerous atmospheric processes. However, one can find a combination of existing parameterization schemes that would minimize observation-model differences. It is therefore essential to ask the question, “What model resolution and parameterization scheme combinations at a particular location and at particular seasons produce model output that has the smallest difference with observations simulated at a reasonable amount of time?” Northern Thailand is a meteorologically active and unstable region especially during the summer and monsoon months (e.g. intense thunderstorms, hail storms, etc). It is also where high concentrations of air pollutants occur during the dry months (e.g. haze). It is therefore essential to have model forecasts close to observations for this region to reduce risk from weather and from air quality degradation. This study aims to find the optimum model resolution and parameterization scheme combinations at particular provinces in northern Thailand with available data during the wet and dry seasons that produces minimum differences with observations. Nested model simulations were performed using the Weather Research and Forecasting (WRF) model (v. 3.6) ran in the High-Performance Computer (HPC) cluster of the National Astronomical Research Institute of Thailand (NARIT) for northern Thailand (2 km spatial resolution and hourly output), for the whole of Thailand (10 km spatial resolution and hourly output), and for the entire Southeast Asia (50 km spatial resolution and 3-hourly output). Combinations of the WRF Single-Moment 3-class, the WRF Single-Moment 5-class, the Lin et al. (Purdue), the WRF Single-Moment 6-class and the WRF Double-Moment 6-class microphysics parameterization schemes, as well as the Betts-Miller-Janjic, the Kain-Fritsch scheme, the Grell-Freitas (GF) ensemble and the Grell 3D cumulus parameterization schemes were utilized to determine the optimum resolution and parameterization of the model when compared to observations. Measured data came from the Thai Meteorological Department (TMD) weather stations in Chiang Mai, Chiang Rai and Lampang in northern Thailand from December 1-15, 2014 (cool dry season), from May 1-12 (hot dry season) and from August 1-7, 2015 (wet season). Results showed a seasonal dependence on the optimum microphysics and convective parameterization combination scheme. It was also found out that cloud resolving model grid sizes still failed to capture convective process as indicated by the derived optimum resolution for the hot-dry and wet seasons.

GOSAT is a joint effort of the Japan Aerospace Exploration Agency (JAXA), the National Institute for Environmental Studies (NIES), and the Ministry of the Environment (MOE), Japan. Part of this work on ACOS B2.9 was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. GOSAT spectra were kindly provided to the California Institute of Technology through a memorandum of understanding between JAXA and NASA. U. S. funding for TCCON is provided by NASA’s Terrestrial Ecology Program (grant number NNX11AG01G), the Orbiting Carbon Observatory Program, the Atmospheric CO2 Observations from Space (ACOS) Program, and the Department of Energy/Atmospheric Radiation Measurement (DOE/ARM) Program. The Darwin TCCON site was built at Caltech with funding from the OCO project and is operated by the University of Wollongong, with travel funds for maintenance and equipment costs funded by the OCO-2 project. We acknowledge funding to support Darwin and Wollongong from the Australian Research Council, Projects LE0668470, DP0879468, DP110103118, and LP0562346. Lauder TCCON measurements are funded by New Zealand Foundation of Research Science and Technology contracts C01X0204 and CO1X0406. We acknowledge financial support of the Bia- lystok and Orleans TCCON sites from the Senate of Bremen and EU projects IMECC, GEOMON and InGOS as well as maintenance and logistical work provided by AeroMeteo Service (Bialystok) and the RAMCES team at LSCE (Gif-sur-Yvette, France) and additional operational funding from the NIES GOSAT project. The Garmisch TCCON team acknowledges funding by the EC-INGOS project. Development of RemoTeC was partly funded by ESA through the GHG-CCI project (S. Guerlet) and by Deutsche Forschungsgemeinschaft (DFG) through grant BU2599/1-1 (A. Butz). The JRA-25/JCDAS data sets used for atmospheric transport modeling were provided by the cooperative, long-term reanalysis project by the Japan Meteorological Agency (JMA) and Central Research Institute of Electric Power Industry (CRIEPI). The authors thank Dr. Sasano, Director of the Center for Global Environmental Research at the NIES, the members of the NIES GOSAT and NASA ACOS projects.

The practical usefulness of a desktop optical spectrum analyzer (OSA) for measuring atmospheric CO2 and CH4 column densities at surface sites was examined in two separate measurement campaigns. The first comparison involved operating the OSA in parallel with a high resolution Fourier transform spectroscopy (FTS) situated at the University of Wollongong in Australia. Scale factors for the OSA were assigned for the column average volume mixing ratios of xCO2 and xCH4 by comparing with the well-studied FTS. The second method is a calibration against aircraft CO2 profiles in situ over Tsukuba in Japan obtained during a GOSAT validation campaign carried out from 28 January to 7 February 2011. The xCO2 values in the campaign, deduced by use of a derived OSA scale factor, were in excellent agreement with the integrated aircraft profiles.

We present a comparison of an atmospheric general circulation model (AGCM)-based chemistry-transport model (ACTM) simulation with total column measurements of CO2, CH4 and N2O from the Total Carbon Column Observing Network (TCCON). The model is able to capture observed trends, seasonal cycles and inter hemispheric gradients at most sampled locations for all three species. The model-observation agreements are best for CO2, because the simulation uses fossil fuel inventories and an inverse model estimate of non-fossil fuel fluxes. The ACTM captures much of the observed seasonal variability in CO2 and N2O total columns (~81 % variance, R>0.9 between ACTM and TCCON for 19 out of 22 cases). These results suggest that the transport processes in troposphere and stratosphere are well represented in ACTM. Thus the poor correlation between simulated and observed CH4 total columns, particularly at tropical and extra-tropical sites, have been attributed to the uncertainties in surface emissions and loss by hydroxyl radicals. While the upward-looking total column measurements of CO2 contains surface flux signals at various spatial and temporal scales, the N2O measurements are strongly affected by the concentration variations in the upper troposphere and stratosphere.

This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common a priori CO2 fluxes and initial concentrations. Forward simulations of column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over the oceans. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 PgC/yr per 106 km2 over land and 0.03 PgC/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 PgC/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. A variable, but overall encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen, although systematic differences are found exceeding the 0.5 ppm level. Because of this, our estimate of the impact of transport model uncerainty is likely to be conservative. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Improving the accuracy of these models should receive high priority, which calls for a closer collaboration between experts in atmospheric dynamics and tracer transport.

The Weather Research and Forecasting (WRF v. 3.7) model was applied to model PM10 data in Chiang Mai city for 10-days during a high haze event utilizing updated land use categories from the Moderate Resolution Imaging Spectroradiometer (MODIS). A higher resolution meteorological lateral boundary condition (from 1 degree to 0.25 degree) was also used from the NCEP GDAS/FNL Global Tropospheric Analyses and Forecast Grid system. A 3-category urban canopy model was also added and the Thompson aerosol-aware microphysics parameterization scheme was used to model the aerosol number concentrations that were later converted to PM10 concentrations. Aerosol number concentration monthly climatology was firstly used as initial and lateral boundary conditions to model PM10 concentrations. These were compared to surface data obtained from two stations of the Pollution Control Department (PCD) of Thailand. The results from the modeled PM10 concentrations could not capture the variability (r = 0.29; 0.27 for each site) and underestimated a high PM10 spike during the period studied. The authors then added satellite data to the aerosol climatology that improved the comparison with observations (r = 0.45; 43). However, both model runs still were not able to capture the high PM10 concentration event. This requires further investigation.

Surface carbon dioxide concentrations were measured using a non-dispersive infrared carbon dioxide sensor at Lampang Rajabhat University from April to May 2013 and at the University of the Philippines-Diliman campus starting September 2013. Factors influencing the variations in these measurements were determined using multiple linear regression and a Lagrangian transport model. Air temperature and sea level pressure were the dominant meteorological factors that affect the CO2 variations. However, these factors are not enough. Surface CO2 flux and transboundary transport needs to be considered as well.

We investigate factors that drive the variability in total column CO2 at the Total Carbon Column Observing Network sites in the Southern Hemisphere using CarbonTracker analysed fluxes tagged by process and by source region. We show that the terrestrial biosphere is the largest driver of variability in the Southern Hemisphere column CO2, however, it does not dominate in the same fashion as in the Northern Hemisphere. Local and hemispheric scale biomass burning can also play an important role, particularly at the tropical site, Darwin. The magnitude of seasonal variability in the column-average dry-air mole fraction of CO2, XCO2, is also much smaller in the Southern Hemisphere and comparable in magnitude to the annual increase. Comparison of measurements to the model simulations highlights that there is some discrepancy between the two timeseries, especially in the early part of the Darwin data record. We show that this mismatch is most likely due to erroneously estimated local fluxes in the Australian tropical region, which are associated with enhanced photosynthesis caused by early rainfall during the tropical monsoon season.

We retrieved column-averaged dry air mole fractions of atmospheric carbon dioxide (X_CO_2) from backscattered short-wave infrared (SWIR) sunlight measured by the Japanese Greenhouse gases Observing SATellite (GOSAT). Over two years of X_CO_2 retrieved from GOSAT is compared with X_CO_2 inferred from collocated SWIR measurements by seven ground-based Total Carbon Column Observing Network (TCCON) stations. The average difference between GOSAT and TCCON X_CO_2 for individual TCCON sites ranges from −0.87 ppm to 0.77 ppm with a mean value of 0.1 ppm and standard deviation of 0.56 ppm. We find an average bias between all GOSAT and TCCON X_CO_2 retrievals of −0.20 ppm with a standard deviation of 2.26 ppm and a correlation coefficient of 0.75. One year of XCO2 was retrieved from GOSAT globally, which was compared to global 3-D GEOS-Chem chemistry transport model calculations. We find that the latitudinal gradient, seasonal cycles, and spatial variability of GOSAT and GEOS-Chem agree well in general with a correlation coefficient of 0.61. Regional differences between GEOS-Chem model calculations and GOSAT observations are typically less than 1 ppm except for the Sahara and central Asia where a mean difference between 2 to 3 ppm is observed, indicating regional biases in the GOSAT X_CO_2 retrievals unobserved by the current TCCON network. Using a bias correction scheme based on linear regression these regional biases are significantly reduced, approaching the required accuracy for surface flux inversions.

[1] This report describes a validation study of Greenhouse gases Observing Satellite (GOSAT) data processing using ground-based measurements of the Total Carbon Column Observing Network (TCCON) as reference data for column-averaged dry air mole fractions of atmospheric carbon dioxide (XCO2). We applied the photon path length probability density function method to validate XCO2retrievals from GOSAT data obtained during 22 months starting from June 2009. This method permitted direct evaluation of optical path modifications due to atmospheric light scattering that would have a negligible impact on ground-based TCCON measurements but could significantly affect gas retrievals when observing reflected sunlight from space. Our results reveal effects of optical path lengthening over Northern Hemispheric stations, essentially from May–September of each year, and of optical path shortening for sun-glint observations in tropical regions. These effects are supported by seasonal trends in aerosol optical depth derived from an offline three-dimensional aerosol transport model and by cirrus optical depth derived from space-based measurements of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. Removal of observations that were highly contaminated by aerosol and cloud from the GOSAT data set resulted in acceptable agreement in the seasonal variability of XCO2 over each station as compared with TCCON measurements. Statistical comparisons between GOSAT and TCCON coincident measurements of CO2column abundance show a correlation coefficient of 0.85, standard deviation of 1.80 ppm, and a sub-ppm negative bias of −0.43 ppm for all TCCON stations. Global distributions of monthly mean retrieved XCO2 with a spatial resolution of 2.5° latitude × 2.5° longitude show agreement within ∼2.5 ppm with those predicted by the atmospheric tracer transport model.

The practical usefulness of a desktop optical spectrum analyzer (OSA) for measuring atmospheric CO2 and CH4 column densities at surface sites was examined in two separate measurement campaigns. The first involved a long term measurement in parallel with a high resolution Fourier transform spectroscopy (FTS) studies at the University of Wollongong in Australia. Scale factors of the OSA were assigned for the column average volume mixing ratios of xCO2 and xCH4 by comparing with the well-studied FTS. The second method is a calibration against aircraft CO2 profiles in situ over Tsukuba in Japan obtained during a GOSAT validation campaign carried out from 28 January to 7 February 2011. The xCO2 values in the campaign, deduced by use of a derived OSA scale factor, were in excellent agreement with the integrated aircraft profiles.

We present a comparison of an atmospheric general circulation model (AGCM)-based chemistry-transport model (ACTM) simulation with total column measurements of CO2, CH4 and N2O from the Total Carbon Column Observing Network (TCCON). The model is able to capture observed trends, seasonal cycles and inter hemispheric gradients at most sampled locations for all three species. The model-observation agreements are best for CO2, because the simulation uses fossil fuel inventories and an inverse model estimate of non-fossil fuel fluxes. The ACTM captures much of the observed seasonal variability in CO2 and N2O total columns (~81% variance, R>0. 9 between ACTM and TCCON for 19 out of 22 cases). These results suggest that the transport processes in troposphere and stratosphere are well represented in ACTM. Thus the poor correlation between simulated and observed CH4 total columns, particularly at tropical and extra-tropical sites,have been attributed to the uncertainties in surface emissions and loss by hydroxyl radicals. While the upward-looking total column measurements of CO2 contains surface flux signals at various spatial and temporal scales, the N2O measurements are strongly affected by the concentration variations in the upper troposphere and stratosphere.

We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO2 (XCO2) from space, and we illustrate the method by applying the method to the Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) v2.8 data. The approach exploits the lack of large gradients in XCO2 south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the correlation between free-tropospheric temperature and XCO2 in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors.

[1] The column-average dry air mole fractions of atmospheric carbon dioxide and methane and are inferred from observations of backscattered sunlight conducted by the Greenhouse gases Observing SATellite (GOSAT). Comparing the first year of GOSAT retrievals over land with colocated ground-based observations of the Total Carbon Column Observing Network (TCCON), we find an average difference (bias) of −0.05% and −0.30% for and with a station-to-station variability (standard deviation of the bias) of 0.37% and 0.26% among the 6 considered TCCON sites. The root-mean square deviation of the bias-corrected satellite retrievals from colocated TCCON observations amounts to 2.8 ppm for and 0.015 ppm for Without any data averaging, the GOSAT records reproduce general source/sink patterns such as the seasonal cycle of suggesting the use of the satellite retrievals for constraining surface fluxes.

This study presents a synthetic model intercomparison to investigate the importance of transport model errors for estimating the sources and sinks of CO2 using satellite measurements. The experiments were designed for testing the potential performance of the proposed CO2 lidar A-SCOPE, but also apply to other space borne missions that monitor total column CO2. The participating transport models IFS, LMDZ, TM3, and TM5 were run in forward and inverse mode using common CO2 fluxes and initial concentrations. Simulated column averaged CO2 (xCO2) mixing ratios vary between the models by σ=0.5 ppm over the continents and σ=0.27 ppm over sea. A variable, but overall quite encouraging agreement is found in comparison with FTS measurements at Park Falls, Darwin, Spitsbergen, and Bremen. Despite the fact that the models agree on average on the sub-ppm level, these modest differences nevertheless lead to significant discrepancies in the inverted fluxes of 0.1 Pg C/yr per 106 km2 over land and 0.03 Pg C/yr per 106 km2 over the ocean. These transport model induced flux uncertainties exceed the target requirement that was formulated for the A-SCOPE mission of 0.02 Pg C/yr per 106 km2, and could also limit the overall performance of other CO2 missions such as GOSAT. It is concluded that to make use of the remote sensing technique for quantifying the sources and sinks of CO2 not only requires highly accurate satellite instruments, but also puts stringent requirements on the performance of atmospheric transport models. Further development of these models should receive high priority.

The first ground-based remote sensing measurements of the column averaged volume mixing ratio of CO2 (XCO2) in tropical South America have been obtained at Paramaribo, Suriname (5.8° N, 55.2° W). The remote sensing observations are complemented by surface air-samples collected at the site, analyzed for CO2 and 13CO2. The surface in-situ measurements are strongly influenced by local sources. From the isotopic composition of the air samples the local source component is suggested to be dominated by the terrestrial biosphere. Using δ13C from the NOAA/ESRL stations Ascension Is. (ASC), 7.9° S, 14.4° W, and Ragged Point (RPB), 13.2° N, 59.4° W, the data has been corrected for the local source component. Due to the migration of the Intertropical Convergence Zone (ITCZ) over the measurement site the sampled air masses belong to the Northern or Southern Hemisphere depending on the time of the year. Comparison to analyzed CO2 fields based on TM3 model simulations using optimized fluxes indicate agreement for the seasonality in XCO2 as well as for the corrected CO2 mixing ratios at the surface for the long dry season, when Paramaribo belongs to the Southern Hemisphere. A slightly worse agreement during the short dry season is attributed to a larger representation error during this time of the year. Overall the comparison indicates that the TM3 model is capable to simulate the seasonal variation of surface concentrations as well as column densities of CO2 correctly at Paramaribo. It has been also shown that the column measurements currently performed at Paramaribo have a limited precision and lack the link to the in situ measurements. Solutions for future improvements have been suggested.

The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO2, CO, CH4, N2O and H2O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Organization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale instrumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. The aircraft campaigns are the Stratosphere-Troposphere Analyses of Regional Transport 2008 (START-08), which included a profile over the Park Falls site, the HIAPER Pole-to-Pole Observations (HIPPO-1) campaign, which included profiles over the Lamont and Lauder sites, a series of Learjet profiles over the Lamont site, and a Beechcraft King Air profile over the Tsukuba site. These calibrations are compared with similar observations made during the INTEX-NA (2004), COBRA-ME (2004) and TWP-ICE (2006) campaigns. A single, global calibration factor for each gas accurately captures the TCCON total column data within error.

A framework has been developed that allows validating CO2 column averaged volume mixing ratios (VMRs) retrieved from ground-based solar absorption measurements using Fourier transform infrared spectrometry (FTS) against measurements made in-situ (such as from aircrafts and tall towers). Since in-situ measurements are done frequently and at high accuracy on the global calibration scale, linking this scale with FTS total column retrievals ultimately provides a calibration scale for remote sensing. FTS, tower and aircraft data were analyzed from measurements during the CarboEurope Regional Experiment Strategy (CERES) from May to June 2005 in Biscarrosse, France. Carbon dioxide VMRs from the MetAir Dimona aircraft, the TM3 global transport model and Observations of the Middle Stratosphere (OMS) balloon based experiments were combined and integrated to compare with the FTS measurements. The comparison allows for calibrating the retrieved carbon dioxide VMRs from the FTS. The Stochastic Time Inverted Lagrangian Transport (STILT) model was then utilized to identify differences in surface influence regions or footprints between the FTS and the aircraft CO2 concentrations. Additionally, the STILT model was used to compare carbon dioxide concentrations from a tall tower situated in close proximity to the FTS station. The STILT model was then modified to produce column concentrations of CO2 to facilitate comparison with the FTS data. These comparisons were additionally verified by using the Weather Research and Forecasting – Vegetation Photosynthesis and Respiration Model (WRF-VPRM). The differences between the model-tower and the model-FTS were then used to calculate an effective bias of approximately −2.5 ppm between the FTS and the tower. This bias is attributed to the scaling factor used in the FTS CO2 data, which was to a large extent derived from the aircraft measurements made within a 50 km distance from the FTS station: spatial heterogeneity of carbon dioxide in the coastal area caused a low bias in the FTS calibration. Using STILT for comparing remotely sensed CO2 data with tower measurements of carbon dioxide and quantifying this comparison by means of an effective bias, provided a framework or a "transfer standard" that allowed validating the FTS retrievals versus measurements made in-situ.

This study aims to determine the variability and trends of tropical biomass burning, tropospheric ozone levels from 2005–2012 in Thailand and the ozone transport from the surrounding regions. Intense biomass burning and tropospheric ozone in this area have a seasonal variability with the maximum generally occurring during the dry season. The northern part of Thailand was observed to have high tropospheric ozone during the dry peak season in April. Forward trajectory analysis determined that ozone sources due to biomass burning in the northern and western surrounding regions (Myanmar, Laos and India) enhance the tropospheric ozone column in northern Thailand. Seasonal variations were also seen for the middle and northeastern regions of Thailand. During August, most biomass burning occurs in Indonesia and Malaysia. However, forward trajectory analysis showed that the effect in the tropospheric ozone column level in the southern part of Thailand is minimal from these regions. Eight-year trends of tropospheric ozone column were also calculated for the different regions of Thailand. However, statistical analysis showed that these trends were not significant. The interannual variability of the tropospheric ozone column concentrations due to El Nino Southern Oscillation were also investigated. It was observed that the best correlation of the tropospheric ozone column with the Oceanic Nino Index (ONI) occured when ONI was advanced 3 months for the north, northeast and south regions of Thailand and 4 months for the middle region of Thailand.

Quantification of sources and sinks of carbon at global and regional scales requires not only a good description of the land sources and sinks of carbon, but also of the synoptic and mesoscale meteorology. An experiment was performed in Les Landes, southwest France, during May¿June 2005, to determine the variability in concentration gradients and fluxes of CO2. The CarboEurope Regional Experiment Strategy (CERES; see also http://carboregional.mediasfrance.org/index) aimed to produce aggregated estimates of the carbon balance of a region that can be meaningfully compared to those obtained from the smallest downscaled information of atmospheric measurements and continental-scale inversions. We deployed several aircraft to concentration sample the CO2 and fluxes over the whole area, while fixed stations observed the fluxes and concentrations at high accuracy. Several (mesoscale) meteorological modeling tools were used to plan the experiment and flight patterns. Results show that at regional scale the relation between profiles and fluxes is not obvious, and is strongly influenced by airmass history and mesoscale flow patterns. In particular, we show from an analysis of data for a single day that taking either the concentration at several locations as representative of local fluxes or taking the flux measurements at those sites as representative of larger regions would lead to incorrect conclusions about the distribution of sources and sinks of carbon. Joint consideration of the synoptic and regional flow, fluxes, and land surface is required for a correct interpretation. This calls for an experimental and modeling strategy that takes into account the large spatial gradients in concentrations and the variability in sources and sinks that arise from different land use types. We briefly describe how such an analysis can be performed and evaluate the usefulness of the data for planning of future networks or longer campaigns with reduced experimental efforts.

High resolution solar absorption Fourier transform spectrometry (FTS) is the most precise ground-based remote sensing technique to measure the total column of atmospheric carbon dioxide. For carbon cycle studies as well as for the calibration and validation of spaceborne sensors the instrumental comparability of FTS systems is of critical importance. Retrievals from colocated measurements by two identically constructed FTS systems have been compared for the first time. Under clear sky conditions a precision for the retrieved x CO 2 better than ∼0.1% is demonstrated and the instruments agree within ∼0.07%. An important factor in achieving such good comparability of the x CO 2 is an accurate sampling of the internal reference laser. A periodic laser mis-sampling leads to ghosts (artificial spectral lines), which are mirrored images from original spectral lines. These ghosts can interfere with the spectral range of interest. The influence of the laser mis-sampling on the retrieved x CO 2 and xO2 in the near-IR has been quantified. For a typical misalignment, the ratio of the ghost intensity compared to the intensity of the original spectral line is about 0.18% and in this case the retrieved x CO 2 is wrong by 0.26% (1 ppm) and the retrieved xO2 is wrong by 0.2%. DOI: 10.1111/j.1600-0889.2010.00491.x