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Methane is the second largest greenhouse gas after carbon dioxide in its impact on climate change. Atmospheric methane has stagnated from 2000 to 2006, and then began to increase again in 2007, showing the largest increase since observation in 2021(19.94 ppb/yr).As part of UNFCCC’s goals for carbon neutrality, it is necessary to verify each country's GHG’s emissions sources and the verifications using satellite observations and atmospheric models are one of the important approaches.Currently, satellite data have been useful for methane monitoring, particularly the retrievals measured by TROPOMI with a high resolution(~7km) and good spatial coverage.Here we investigated the spatio-temporal characteristics of national methane distribution and the spatial correlation between satellite concentrations and the national emission sources over South Korea to identify the characteristics of high-level methane distributions from August 2018 to July 2019 . During the period, the average concentration of XCH4 in Korea was ~1858 ppb and the monthly mean concentrations of methane in Korea were higher from June to October, which in fact reflected the characteristics of rice paddy and wetlands in monsoon season. The spatial correlation analysis (SDM) found that there are some areas showing specific contributing emissions sources with higher methane levels. There are areas with high correlations with livestock production, fossil fuel uses(gas & oils), wastes(& landfill), and rice paddies, while there are areas with high correlations with complex effects of the four fields or with no clear correlations. Based on our analysis, the spatial correlation analysis with various emission sources and satellite data can provide the information to evaluate the CH4 emissions inventory and give some ideas to manage regional greenhouse gases reduction policies

Objectives : This study aims to discuss air quality policy improvement that reflect regional characteristics through analyzing recent PM2.5 concentration, air pollutant emission sources and those contributions to annual PM2.5 concentration in Chungcheong region (Daejeon Metropolitan City, Sejong Metropolitan Autonomous City, the Province of Chungcheongnam-do, and Chungcheongbuk-do) in South Korea. In addition, we identified the characteristics of the PM2.5 pollution at the level of fundamental local government, and demonstrated the number of vulnerable population exposed to high level of PM2.5 concentration in order to propose policy implications in Chungcheong region.Methods : Based on the national emissions estimates (CAPSS: Clean Air Policy Support System) and air quality modelling system, major sectors/sources of air pollutants emission and national contributions of PM2.5 concentrations in Chungcheong region were analyzed. Furthermore, the study identified the number of people exposed to the higher PM2.5 concentrations (>25 µg/m3) by the measurement data and demographics available in 2019.Results and Discussion : The national air pollutants emissions in Chungcheong region were emitted from Chungnam (about 59% of NOx emission volume, 89% of SOx, 70% of NH3, 54% of VOCs, 79% of PM2.5, and 68% of TSP respectively), mainly from industry, domestic, energy, and road sector. According to the results of the air quality modelling, Chungcheong region also had the largest contribution on the average annual PM2.5 concentration in South Korea (27%). Chungnam emitted the largest emission volume of air pollutants, mainly from industry and power generation sectors (especially in Dangjin, Seosan, and Boryeong), while Asan, Yesan, Hongseong, and Cheongyang were classified as the areas with higher PM2.5 concentrations (>25 µg/m3), showing a gap between the areas with large emission volume and high concentration. Chungbuk and Sejong had higher annual PM2.5 concentration due to the influence of external sources and their geographical characteristics. The largest vulnerable population (over 65 years old and under 18 years old) exposed to high PM2.5 concentrations annually lived in Cheongju. Chungbuk had about 40% more air pollutant emission volume than Chungnam, but about 17% more vulnerable population.Conclusions : At the current stage of “master plan” in Chungcheong region, it is important to mitigate air pollutants emissions on the basis of the local emissions characteristic at the level of fundamental local government (such as industry sector in Dangjin, Seosan, and Danyang/ Domestic buring in Cheongju, Cheonan, and Daejeon/power generation in Boryeong, Taean and Dangjin/ road in Daejeon, Cheongju, and Cheoan). In addition, Chungbuk requires management of the areas with higher PM2.5 concentration such as Goesan, Boeun, Okcheon, and Yeongdong located outside “air control zone”. To reduce high level of PM2.5 concentration in Chungcheong region, cooperation with neighboring local governments such as Gyeonggi Province is crucial, and policy solutions are needed between the stakeholders to resolve the disparity issues between areas with larger emission volume and higher PM2.5 concentration.

We analyzed the multi-year relationship between particulate matter (PM10 and PM2.5) concentrations and possible precursors including NO2, SO2, and NH3 based on local observations over the Seoul Metropolitan Area (SMA) from 2015 to 2017. Surface NH3 concentrations were obtained from Cross-track Infrared Sounder (CrIS) retrievals, while other pollutants were observed at 142 ground sites. We found that NH3 had the highest correlation with PM2.5 (R = 0.51) compared to other precursors such as NO2 and SO2 (R of 0.16 and 0.14, respectively). The correlations indicate that NH3 emissions are likely a limiting factor in controlling PM2.5 over the SMA in a high-NOx environment. This implies that the current Korean policy urgently requires tools for controlling local NH3 emissions from the livestock industry (for example, from hog manure). These findings provide the first satellite-based trace gas evidence that implementing an NH3 control strategy could play a key role in improving air quality in the SMA.

We investigated regional climate changes in South Korea over the last 40 years (1980 ~ 2019). The country was divided into 10 areas of Seoul, Gyeonggi, Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, and Jeju. We used the regional climate data (daily temperature and precipitation) measured by Korea Meteorological Administration (KMA) at 61 sites. There has been an annual average temperature increase of 1.4℃ for the last 40 years in Korea, with a range of +1.0℃ (Jeonnam) ~ +1.8℃ (Gangwon). The increases in annual minimum and maximum temperatures were even larger; the increase in annual maximum temperature was as high as 2.2℃ over a broad range of trends (+0.2℃ (Jeonnam) ~ +5.6℃ (Gyeonggi)). The change of annual total precipitation was not clear, but the southern part of Korea showed an increasing trend (Jeju(+206.4 mm/40years)), and the central part of Korea showed a decreasing trend (Chungnam (-119.6mm/40years)). The trend of annual temperature variability was negative in central Korea (Gyeonggi (-4.2℃/40 years)) and positive in southern Korea (Gyeongnam (+1.0℃ /40years)). The changes in the trends of monthly temperature variabilitiy differed by season; March (Gangwon (+0.1℃/40years) ~ Seoul (+3.6℃/40years)) and August (Jeju (-0.9℃/40 years) ~ Chungbuk (+2.9℃/40 years)) showed increasing trends due to the greater increase in maximum monthly temperatures. In comparison, September (Gyeongnam (-0.6℃/40 years) ~ Jeju (-3.5℃/40years)) and December (Seoul (+0.2℃/40 years) ~ Jeonbuk (-4.4℃/40 years)) showed decreasing trends due to the greater increase in minimum monthly temperatures. Those changes might cause different seasonal health impacts. Warming trends were noted in climate extreme indices over the last 40 years. For example, there was an almost one-month increase in the number of summer days (Tmax ≥ 25℃) in Seoul and 15-day increase in the number of tropical nights (Tmin ≥ 25℃) in Jeju. There was a similar decrease (14 days) in cold days (Tmin ≤ -12℃) in Gangwon. Our results show that regional differences in climate change over the last 40 years should be considered for establishing and implementing regional climate change adaptation policies.

SO2 column densities from Ozone Monitoring Instrument provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three Ozone Monitoring Instrument SO2 retrieval products (National Aeronautics and Space Administration (NASA) standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO2 emissions. SO2 column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4D‐Var/mass balance emission inversion to derive monthly SO2 emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in United States, India, and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO2 emissions increase from 2005 to 2016 by 35% (NASA)–48% (BIRA) in India, but decrease in China by 23% (NASA)–33% (BIRA) since 2008. Compared to in situ measurements, the posterior GEOS‐Chem surface SO2 concentrations have reduced NMB in China, the United States, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO2 measurement in China and spatial variability of SO2 concentration in China, South Korea, and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO2 emissions using Ozone Monitoring Instrument observations., Key Points SO2 retrievals are most consistent when VZA and SZA are small; treatment of cloud and radiative transfer can cause differences up to 4 DUTop‐down SO2 emissions are more robust between NASA and BIRA retrievals in China and India where SO2 concentrations are highSO2 emissions continuously increase in India from 2005 to 2017 but start to decrease in China from 2008

Growing concern about particulate matter (PM2.5) pressures Korea to reduce the health risks associated with its high dependency on fossil fuels. The Korean economy relies heavily on large thermal power plants&mdash, a major source of PM2.5 emissions. Although air quality regulations can negatively impact local economies, the Korean government announced two strict air quality mitigation policies in 2019. We develop a regional static computable general equilibrium model to simulate the economic and environmental impacts of these polices under alternative hypothetical scenarios. We separate two regions, Chungcheongnam-do, the most polluted region, and the rest of the country, in our model. As policy options, we introduce a regional development tax and a tradable market for PM emission permits, similar to an air pollution tax and a carbon permits market, respectively. The results show that allowing higher tax rates and a tradable permits market gives the optimal combination, with the PM2.5 emissions reduced by 2.35% without sacrificing economic growth. Since alternative options present, for example, a 0.04% loss of gross domestic product to reduce PM emissions by the same amount, our results here may present a new policy paradigm for managing air pollutants such as PM2.5.

We used multiyear Greenhouse Gases Observing Satellite (GOSAT) dry air, column-integrated CO2 (XCO2) retrievals (2010–2013) to evaluate urban and local-scale CO2 emissions over East Asia and examin...

Statistical change-point analysis was applied to a spring time series of the Palmer Drought Severity Index (PDSI) in Korea, and this showed that the total analysis period can be divided into two periods: a wet period (1975–1990) and a dry period (1991–2014). To investigate the deepening of the spring drought in Korea, a difference in the spring means between the 1991–2014 and 1975–1990 periods was analyzed with respect to large-scale environments. In the recent spring, a typical pressure system pattern in winter, which was an anomalous west-high east-low pressure system pattern, was strengthened throughout the troposphere around Korea. Due to the anomalous pressure system pattern, Korea was affected by relatively cold and dry anomalous northerlies. Furthermore, the western North Pacific subtropical high (WNPSH) was not intensified, and thus the supply of warm and moist airs into Korea was further reduced due to the upper-level jet moving further to the south. In order to determine the reason for the development of the anomalous west-high east-low pressure system pattern in East Asia, the difference in spring snow depth between the two periods was analyzed, and the analysis results showed that positive anomalies were predominant throughout most regions in East Eurasia. As a result, in the analysis of the ground heat net flux, negative anomalies were strengthened in most regions in East Eurasia. The cooling effect in the surrounding regions due to the high snow depth in East Eurasia strengthened the anomalous pressure system pattern as a west-high east-low type.

Enforcement of an air quality standard for PM2.5 in the Seoul metropolitan area (SMA) was enacted in 2015. From May to June of 2016, an international airborne and surface measurement campaign took place to investigate air pollution mechanisms in the SMA. The total and speciated PM2.5 concentrations since 2008 have been measured at an intensive monitoring site for the SMA operated by the National Institute of Environmental Research (NIER). To gain insight on the trends and sources of PM2.5 in the SMA in May, we analyze PM2.5 concentrations from 2009 to 2013 using the measurements and simulations from a 3-dimensional global chemical transport model, GEOS-Chem and its adjoint. The model is updated here with the latest regional emission inventory and diurnally varying NH3 emissions. Monthly average PM2.5 concentration measured by β-ray attenuation ranges from 28 (2010) to 45 (2013) μg/m3, decreased from 2009 to 2010, and then continuously increased until 2013. The model shows good agreement with the measurements for the daily average PM2.5 concentrations (R ≥ 0.5), and reproduces 10 out of 17 measured episodes exceeding the daily air quality standard (50 μg/m3). Using the GEOS-Chem adjoint model, we find that anthropogenic emissions from the Shandong region have the largest modeled influence on PM2.5 in Seoul in May. Average contributions to the high PM2.5 episodes simulated by the model are 39% from the Shandong region, 16% from the Shanghai region, 14% from the Beijing region, and 15% from South Korea. Anthropogenic SO2 emissions from South Korea are negligible with 90% of the total contribution originating from China. Findings from this study may guide interpretation of observations obtained in the KORUS-AQ measurement campaign.

South Korea has recently chosen coal as the major energy source for the future national electricity power supply, mainly due to economic reasons. This has raised concerns about national air quality, considering the serious air pollution associated with the long-range transport of Chinese air pollutants. In the present study, we simulated air pollution levels for 2027 considering the changes in electricity power plants of South Korea proposed by the sixth Basic Plan for Long-Term Electricity Supply and Demand (6th BPE, 2013–2027). Compared to the emissions in 2010, the emissions of CO, NO x , SO x , and PM 10 from electricity supply in the Incheon, Gyunggi, Gangwon, Chungnam, and Gyeongnam regions will increase by 20–50% in 2027. The resulting number of days on which pollution levels exceeded the national air quality standards for O 3 and PM 10 will increase by fewer than 6 days in all regions, which seems to be a minor increase. However, that of NO 2 over the Seoul metropolitan area (SMA, including Incheon, part of Gyunggi, and Seoul) showed a marked increase of more than 21 days. Therefore, an impact from secondary air pollution, such as acid rain and PM 2.5 formation, can be expected, although this requires quantification.

Here we demonstrate the sharp seasonal and latitudinal gradient of atmospheric CO 2 over East Asia, where there are relatively few ground-based observations. The Greenhouse gases Observing SATellite (GOSAT) column-averaged dry air CO 2 mole fraction (xCO 2 ) retrieved by NASA's Atmospheric CO 2 Observations from Space (ACOS) (2009–2011) program and GEOS-Chem nested-grid CO 2 results are used. The strong anthropogenic emissions mainly from China and intensive vegetation uptake from northeastern Asia lead to a clear seasonal change of the xCO 2 between spring maximum and summer minimum (>10 ppm). In particular, the steep latitudinal gradient of summer time xCO 2 by 3–5 ppm in the vicinity of the Korean Peninsula (32°N-44°N) is likely attributed to the large difference in CO 2 fluxes among industry/cities, northeastern forests and the northwest Pacific region. This study represents the current progress to understand sub-continental scale atmospheric CO 2 variabilities with recent satellite retrievals and nested-grid modeling.

Enforcement of an air quality standard for PM

Global aerosol direct radiative forcing (DRF) is an important metric for assessing potential climate impacts of future emissions changes. However, the radiative consequences of emissions perturbations are not readily quantified nor well understood at the level of detail necessary to assess realistic policy options. To address this challenge, here we show how adjoint model sensitivities can be used to provide highly spatially resolved estimates of the DRF from emissions of black carbon (BC), primary organic carbon (OC), sulfur dioxide (SO(2)), and ammonia (NH(3)), using the example of emissions from each sector and country following multiple Representative Concentration Pathway (RCPs). The radiative forcing efficiencies of many individual emissions are found to differ considerably from regional or sectoral averages for NH(3), SO(2) from the power sector, and BC from domestic, industrial, transportation and biomass burning sources. Consequently, the amount of emissions controls required to attain a specific DRF varies at intracontinental scales by up to a factor of 4. These results thus demonstrate both a need and means for incorporating spatially refined aerosol DRF into analysis of future emissions scenario and design of air quality and climate change mitigation policies.

Global atmospheric CO2 distributions were simulated with a chemical transport model (GEOS-Chem) and compared with space-borne observations of CO2 column density by GOSAT from April 2009 to January 2010. The GEOS-Chem model simulated 3-D global atmospheric CO2 at 2°×2.5° horizontal resolution using global CO2 surface sources/sinks as well as 3-D emissions from aviation and the atmospheric oxidation of other carbon species. The seasonal cycle and spatial distribution of GEOS-Chem CO2 columns were generally comparable with GOSAT columns over each continent with a systematic positive bias of ~1.0%. Data from the World Data Center for Greenhouse Gases (WDCGG) from twelve ground stations spanning 90°S-82°N were also compared with the modeled data for the period of 2004-2009 inclusive. The ground-based data show high correlations with the GEOS-Chem simulation (0.66≤R2≤0.99) but the model data have a negative bias of ~1.0%, which is primarily due to the model initial conditions. Together these two comparisons can be used to infer that GOSAT CO2 retrievals underestimate CO2 column concentration by ~2.0%, as demonstrated in recent validation work using other methods. We further estimated individual source/sink contributions to the global atmospheric CO2 budget and trends through 7 tagged CO2 tracers (fossil fuels, ocean exchanges, biomass burning, biofuel burning, net terrestrial exchange, shipping, aviation, and CO oxidation) over 2004-2009. The global CO2 trend over this period (2.1 ppmv/year) has been mainly driven by fossil fuel combustion and cement production (3.2 ppmv/year), reinforcing the fact that rigorous CO2 reductions from human activities are necessary in order to stabilize atmospheric CO2 levels.

Spatial and temporal variabilities of NPP(Net Primary Production) retrieved from two satellite instruments, AVHRR(Advanced Very High Resolution Radiometer, 1981-2000) and MODIS(MODerate-resolution Imaging Spectroradiometer, 2000-2006), were investigated. The range of mean NPP from AVHRR and MODIS were estimated to be 894-1068 ghC/m 2 /yr and 610-694.90 ghC/m 2 /yr, respectively. The discrepancy of NPP between the two instruments is about 325 gh C/m 2 /yr, and MODIS product is generally closer to the ground measurement than AVHRR despite the limitation in direct comparison such as spatial resolution and vegetation classification. The higher NPP values over South Korea are related to the regions with higher biomass (e.g., mountains) and higher annual temperature. The interannual NPP trends from the two satellite products were computed, and both mean annual trends show continuous NPP increase; 2.14 ghC/m 2 /yr from AVHRR (1981-2000) and 6.08 ghC/m 2 /yr from MODIS (2000-2006) over South Korea. Specifically, the higher increasing trends over the Southwestern region are likely due to the increasing productivity of crop fields from sufficient irrigation and fertilizer use. The retrieved NPP shows a closer relationship between monthly temperature and precipitation, which results in maximum correlation during summer monsoons. The difference in the detection wavelength and model schemes during the retrieval can make a significant difference in the satellite products, and a better accuracy in the meterological and land use data and modeling applications will be necessary to improve the satellite-based NPP data.

Concurrent tropospheric O3 and CO vertical profiles from the Tropospheric Emission Spectrometer (TES) during the MILAGRO/INTEX-B aircraft campaigns over the Mexico City Metropolitan Area (MCMA) and its surrounding regions were used to examine Mexico City pollution outflow on a regional scale. The pollution outflow from the MCMA occurred predominantly at 600–800 hPa as evident in O3, CO, and NOx enhancements in the in situ aircraft observations. TES O3 and CO are sensitive to the MCMA pollution outflow due to their relatively high sensitivities at 600–800 hPa. We examined O3, CO, and their correlation at 600–800 hPa from TES retrievals, aircraft measurements, and GEOS-Chem model results. TES captures much of the spatial and day-to-day variability of O3 seen in the in situ data. TES CO, however, shows much less spatial and day-to-day variability compared with the in situ observations. The DO3/DCO slope is significantly higher in the TES data (0.43) than the in situ data (0.28) due partly to the lack of variability in TES CO. Extraordinarily high DO3/DCO slope (0.81) from TES observations at 618 hPa over the Eastern U.S. was previously reported by Zhang et al. [Zhang, L., Jacob, D.J., Bowman, K.W., et al., 2006. Ozone–CO correlations determined by the TES satellite instrument in continental outflow regions. Geophys. Res. Lett. 33, L18804. 10.1029/2006GL026399.]. Thus the application of TES CO–O3 correlation to map continental pollution outflow needs further examination. Published by Elsevier Ltd.

A major aircraft experiment Transport and Chemical Evolution over the Pacific (TRACE-P) mission over the NW Pacific in March-April 2001 was conducted to better understand how outflow from the Asian continent affects the composition of the global atmosphere. In this paper, a global climate model, GEOS-Chem is used to investigate possible black carbon aerosol contributions from TRACE-P region. Our result depicts that absorbing black carbon ("soot") significantly outflow during lifting to the free troposphere through warm conveyor belt and convection associated with this lifting. The GEOS-Chem simulation results show significant transport of black carbon aerosols from Asian regions to the Western Pacific region during the spring season. As estimated by GEOS-Chem simulations, approximately 25% of the black carbon concentrations over the western pacific originate from SE Asia in the spring.

Trace gas measurements of TOPSE and TRACE-P experiments and corresponding global GEOS-Chem model simulations are analyzed with the Positive Matrix Factorization (PMF) method for model evaluation purposes. Specially, we evaluate the model simulated contributions to O3 variability from stratospheric transport, intercontinental transport, and production from urban/industry and biomass burning/biogenic sources. We select a suite of relatively long-lived tracers, including 7 chemicals (O3, NOy, PAN, CO, C3H8, CH3Cl, and 7Be) and 1 dynamic tracer (potential temperature). The largest discrepancy is found in the stratospheric contribution to 7Be. The model underestimates this contribution by a factor of 2–3, corresponding well to a reduction of 7Be source by the same magnitude in the default setup of the standard GEOS-Chem model. In contrast, we find that the simulated O3 contributions from stratospheric transport are in reasonable agreement with those derived from the measurements. However, the springtime increasing trend over North America derived from the measurements are largely underestimated in the model, indicating that the magnitude of simulated stratospheric O3 source is reasonable but the temporal distribution needs improvement. The simulated O3 contributions from long-range transport and production from urban/industry and biomass burning/biogenic emissions are also in reasonable agreement with those derived from the measurements, although significant discrepancies are found for some regions.

[1] We assess the impact of transport of pollution from midlatitudes on the abundance of ozone in the Arctic in summer 2006 using the GEOS-Chem global chemical transport model and its adjoint. We find that although the impact of midlatitude emissions on ozone abundances in the Arctic is at a maximum in fall and winter, in July transport from North America, Asia, and Europe together contributed about 25% of surface ozone abundances in the Arctic. Throughout the summer, the dominant source of ozone in the Arctic troposphere was photochemical production within the Arctic, which accounted for more than 50% of the ozone in the Arctic boundary layer and as much as 30%–40% of the ozone in the middle troposphere. An adjoint sensitivity analysis of the impact of NOx emissions on ozone at Alert shows that on synoptic time scales in both the lower and middle troposphere, ozone abundances are more sensitive to emissions between 50°N and 70°N, with important influences from anthropogenic, biomass burning, soil, and lightning sources. Although local surface NOx emissions contribute to ozone formation, transport of NOx in the form of peroxyacetyl nitrate (PAN) from outside the Arctic and from the upper troposphere also contributed to ozone production in the lower troposphere. We find that in late May and June the release of NOx from PAN decomposition accounted for 93% and 55% of ozone production at the Arctic surface, respectively.

The total column densities of acetylene (C(2)H(2)), carbon monoxide (CO), hydrogen cyanide (HCN) and ethane (C(2)H(6)) measured in Bremen (Germany, 53.107 degrees N, 8.854 degrees E) were compared with data from Mace Head/Ireland (MHD) and GEOS-Chem model simulations. The data were obtained between August 2002 and October 2006 with the ground based high resolution Fourier Transform Infra-Red (FTIR) Spectrometry, using the sun as the light source. The analysis showed good agreements between all the three data sets for the seasonal cycle of CO. Enhancements in summer 2003 and summer 2004 due to influence of biomass burning were identified in all three data sets. The high correlations between C(2)H(6) and C(2)H(2), C(2)H(2) and CO, and for C(2)H(6) and CO support the similarities in their sources and sinks. The results suggest that the background air in Bremen is mainly influenced by long-ranged transport of biomass burning products. Local pollution plays a minor role for the measurements performed in Bremen.

The first seasonal and interannual validation of OH measurements from the Aura Microwave Limb Sounder (MLS) has been conducted using ground-based OH column measurements from the Fourier Transform Ultra-Violet Spectrometer (FTUVS) over the Jet Propulsion Laboratory's Table Mountain Facility (TMF) during 2004–2007. To compare with FTUVS total column measurements, MLS OH vertical profiles over TMF are integrated to obtain partial OH columns above 21.5 hPa, which covers nearly 90% of the total column. The tropospheric OH and the lower stratopheric OH not measured by MLS are estimated using GEOS (Goddard Earth Observing System)-Chem and a Harvard 2-D model implemented within GEOS-Chem, respectively. A number of field observations and calculations from a photochemical box model are compared to OH profiles from these models to estimate the variability in the lower atmospheric OH and thus the uncertainty in the combined total OH columns from MLS and models. In general, the combined total OH columns agree extremely well with TMF total OH columns, especially during seasons with high OH. In winter with low OH, the combined columns are often higher than TMF measurements. A slightly weaker seasonal variation is observed by MLS relative to TMF. OH columns from TMF and the combined total columns from MLS and models are highly correlated, resulting in a mean slope of 0.969 with a statistically insignificant intercept. This study therefore suggests that column abundances derived from MLS vertical profiles have been validated to within the mutual systematic uncertainties of the MLS and FTUVS measurements.

Concurrent tropospheric O 3 and CO vertical profiles from the Tropospheric Emission Spectrometer (TES) during the MILAGRO/INTEX-B aircraft campaigns over the Mexico City Metropolitan Area (MCMA) allow us to characterize mega-city pollution. Outflow from the MCMA occurred predominantly at 600–800 hPa, evident in O 3 , CO, and NO x enhancements in the in situ observations. We examined O 3 , CO, and their correlation at 600–800 hPa from TES retrievals, aircraft measurements, and GEOS-Chem model results over the aircraft coverage (within a radius of ~700 km around MCMA). The enhancements in O 3 and CO seen in the in situ measurements are not apparent in TES data, due to the lack of TES coverage during several strong pollution events. However, TES O 3 and CO data are consistent with the aircraft observations on a daily mean basis (50–60 ppbv and 100–130 ppbv for O 3 and CO respectively). The O 3 -CO correlation coefficients and enhancement ratios (ΔO 3 /ΔCO) derived from TES data are in good agreements with those derived from the aircraft observations and GEOS-Chem model results ( r : 0.5–0.9; ΔO 3 /ΔCO: 0.3–0.4), reflecting significant springtime photochemical production over MCMA and the surrounding region.

[1] Airborne trace gas measurements from Transport and Chemical Evolution over the Pacific (TRACE-P), Pacific Exploratory Mission (PEM)-Tropics B, and Intercontinental Chemical Transport Experiment-North America (INTEX-NA) experiments are analyzed to examine the major source factors contributing to the observed variabilities of oxygenated volatile organic compounds and cyanides. The positive matrix factorization method is applied to coincident measurements of 11 chemicals including CH3OH, CH3COCH3, CH3CHO, C2H2, C2H6, i-C5H12, CO, CH3Cl, and CHBr3. Measurements of HCN and CH3CN are available for TRACE-P and INTEX-NA. We identify major source contributions from the terrestrial biosphere, biomass burning, industry/urban regions, and oceans. Spatial and back trajectory characteristics of these factors are examined. On the basis of TRACE-P and PEM-Tropics B data, we find a factor that explains 80–88% of the CH3OH variability, 20–40% of CH3COCH3, 7–35% of CH3CHO, and 41% of HCN, most likely representing the emissions from terrestrial biosphere. Our analysis suggested that biogenic emissions of HCN may be significant. Cyanogenesis in plants is likely a major emission process for HCN, which was not fully accounted for previously. Larger contributions than previous global estimations to CH3COCH3 and CH3CHO by biomass burning and industry/urban sources likely reflect significant secondary production from volatile organic compound oxidation. No evidence was found for large emissions of CH3COCH3 from the ocean. The oceanic CH3CHO contribution implies large regional variations.

[1] Inverse modeling using the Bayesian least squares method is applied to better constrain the sources and sinks of atmospheric methyl chloride (CH3Cl) using observations from seven surface stations and eight aircraft field experiments. We use a three-dimensional global chemical transport model, the GEOS-Chem, as the forward model. Up to 39 parameters describing the continental/hemispheric and seasonal dependence of the major sources of CH3Cl are used in the inversion. We find that the available surface and aircraft observations cannot constrain all the parameters, resulting in relatively large uncertainties in the inversion results. By examining the degrees of freedom in the inversion Jacobian matrix, we choose a reduced set of parameters that can be constrained by the observations while providing valuable information on the sources and sinks. In particular, we resolve the seasonal dependence of the biogenic and biomassburning sources for each hemisphere. The in situ aircraft measurements are found to provide better constraints on the emission sources than surface measurements. The a posteriori emissions result in better agreement with the observations, particularly at southern high latitudes. The a posteriori biogenic and biomass-burning sources decrease by 13 and 11% to 2500 and 545 Gg yr � 1 , respectively, while the a posteriori net ocean source increases by about a factor of 2 to 761 Gg yr � 1 . The decrease in biomass-burning emissions is largely due to the reduction in the emissions in seasons other than spring in the Northern Hemisphere. The inversion results indicate that the biogenic source has a clear winter minimum in both hemispheres, likely reflecting the decrease of biogenic activity during that season.

[1] Biogenic isoprene plays an important role in tropospheric chemistry. Current isoprene emission estimates are highly uncertain because of a lack of direct observations. Formaldehyde (HCHO) is a high-yield product of isoprene oxidation. The short photochemical lifetime of HCHO allows the observation of this trace gas to help constrain isoprene emissions. We use HCHO column observations from the Global Ozone Monitoring Experiment (GOME). These global data are particularly useful for studying large isoprene emissions from the tropics, where in situ observations are sparse. Using the global Goddard Earth Observing System–Chemistry (GEOS-CHEM) chemical transport model as the forward model, a Bayesian inversion of GOME HCHO observations from September 1996 to August 1997 is conducted to calculate global isoprene emissions. Column contributions to HCHO from 10 biogenic sources, in addition to biomass-burning and industrial sources, are considered. The inversion of these 12 HCHO sources is conducted separately for eight geographical regions (North America, Europe, east Asia, India, Southeast Asia, South America, Africa, and Australia). GOME measurements with high signal-to-noise ratios are used. The a priori simulation greatly underestimates global HCHO columns over the eight geographical regions (bias, −14 to −46%; R = 0.52–0.84). The a posteriori solution shows generally higher isoprene and biomass-burning emissions, and these emissions reduce the model biases for all regions (bias, −3.6 to −25%; R = 0.56–0.84). The negative bias in the a posteriori estimate reflects in part the uncertainty in GOME measurements. The a posteriori estimate of the annual global isoprene emissions of 566 Tg C yr−1 is ∼50% larger than the a priori estimate. This increase of global isoprene emissions significantly affects tropospheric chemistry, decreasing the global mean OH concentration by 10.8% to 0.95 × 106 molecules/cm3. The atmospheric lifetime of CH3CCl3 increases from 5.2 to 5.7 years.

[1] Observations (0–8 km) from the Tropospheric Ozone Production about the Spring Equinox (TOPSE) experiment are analyzed to examine air masses contributing to the observed variability of springtime O3 and its seasonal increase at 40°–85°N over North America. Factor analysis using the positive matrix factorization and principal component analysis methods is applied to the data set with 14 chemical tracers (O3, NOy, PAN, CO, CH4, C2H2, C3H8, CH3Cl, CH3Br, C2Cl4, CFC-11, HCFC-141B, Halon-1211, and 7Be) and one dynamic tracer (potential temperature). Our analysis results are biased by the measurements at 5–8 km (70% of the data) due to the availability of 7Be measurements. The identified tracer characteristics for seven factors are generally consistent with the geographical origins derived from their 10 day back trajectories. Stratospherically influenced air accounts for 14 ppbv (35–40%) of the observed O3 variability for data with O3 concentrations

Moderate Resolution Imaging Radiometer (MODIS) gross primary productivity (GPP) has been used widely to study the global carbon cycle associated with terrestrial ecosystems. The retrieval of the current MODIS productivity with a 1 × 1 km 2 resolution has limitations when presenting subgrid scale processes in terrestrial ecosystems, specifically when forests are located in mountainous areas, and shows heterogeneity in vegetation type due to intensive land use. Here, we evaluate MODIS GPP (MOD17) at Gwangneung deciduous forest KoFlux tower (deciduous forest; GDK) for 2006–2010 in Korea, where the forests comprise heterogeneous vegetation cover over complex terrain. The monthly MODIS GPP data overestimated the GDK measurements in a range of +15% to +34% and was fairly well correlated ( R = 0.88) with the monthly variability at GDK during the growing season. In addition, the MODIS data partly represented the sharp GPP reduction during the Asian summer monsoon (June–September) when intensive precipitation considerably reduces solar radiation and disturbs the forest ecosystem. To examine the influence of subgrid scale heterogeneity on GPP estimates over the MODIS scale, the individual vegetation type and its area within a corresponding MODIS pixel were identified using a national forest type map (∼71-m spatial resolution), and the annual GPP in the same area as the MODIS pixel was estimated. This resulted in a slight reduction in the positive MODIS bias by ∼10%, with a high degree of uncertainty in the estimation. The MODIS discrepancy for GDK suggests further investigation is necessary to determine the MODIS errors associated with the site-specific aerodynamic and hydrological characteristics that are closely related to the mountainous topography. The accuracy of meteorological variables and the impact of the very cloudy conditions in East Asia also need to be assessed.

The Boreal black spruce forest is highly susceptible to wildfire, and postfire changes in soil temperature and substrates have the potential to shift large areas of such an ecosystem from a net sink to a net source of carbon. In this paper, we examine CO 2 exchange rates (e.g., NPP and Re) in juniper haircap moss ( Polytrichum juniperinum ) and microbial respiration in no-vegetation conditions using an automated chamber system in a five-year burned black spruce forest in interior Alaska during the fall season of 2009. Mean ± standard deviation microbial respiration and NEP (net ecosystem productivity) of juniper haircap moss were 0.27 ± 0.13 and 0.28 ± 0.38 gCO 2 /m 2 /hr, respectively. CO 2 exchange rates and microbial respiration showed temporal variations following fluctuation in air temperature during the fall season, suggesting the temperature sensitivity of juniper haircap moss and soil microbes after fire. During the 45-day fall period, mean NEP of P. juniperinum moss was 0.49 ± 0.28 MgC/ha following the five-year-old forest fire. On the other hand, simulated microbial respiration normalized to a 10 °C temperature might be stimulated by as much as 0.40 ± 0.23 MgC/ha. These findings demonstrate that the fire-pioneer species juniper haircap moss is a net C sink in the burned black spruce forest of interior Alaska.