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Although most countries have submitted their Nationally Determined Contributions (NDC), there is a lack of understanding what policies are effective in terms of carbon emission reduction under the announced pledges. We use East Asia as a case study to estimate the importance of national environmental policies in terms of reduction in fossil fuel carbon emissions (FFCO2). We show that the flagship policies of China, Japan, South Korea and Mongolia in the 2010s were generally beneficial in terms of slowing down FFCO2 growth rates. When flagship polices were enacted, annual FFCO2 growth rate has either slowed down by 1% (South Korea), 5% (Mongolia), 8% (China) or even resulted in a decline (Japan) comparing to prior periods. We find that the 12th Five-Year Plan (12th FYP) of China had the strongest footprint in FFCO2 emission dynamics across East Asia in 2010s. The recent slowest rate of FFCO2 growth across East Asia (2011–2015) temporally corresponds to the 12th FYP. This regional pattern of FFCO2 dynamics is driven by decrements in annual growth of FFCO2, coal use and cement production of China (all ˜8% per yer decrease) during the 12th FYP. Using compound periodical growth of FFCO2 emissions, we provide two baseline projections of emission distribution in East Asia, by assuming that all policies are enacted (policy-on) or not (policy-off) in the future. The projections show that policies were beneficial since policy-on scenario results in 24%, 80%, 166% less FFCO2 emissions than in policy-off scenario in East Asia by 2020, 2025 and 2030 respectively. This progress is yet insufficient for reaching NDC goals by 2030. Even in policy-on scenario in 2030, East Asian countries would either experience insufficient decline of FFCO2 like Japan (-13% of FFCO2 comparing to pledged -17%) or increase of FFCO2 like South Korea (11%) and Mongolia (4%) comparing to 2010 level. For China, due to lack of economy-independent goals, we were unable to assess NDC target compliance. We demonstrate that China will remain as the major FFCO2 emitter of EA in near future in any projection. For China, the highest emission cluster will remain at the Eastern Provinces with the strongest power generation demand. These provinces would be responsible for 43% and 52% of FFCO2 emissions in East Asia in policy-off and policy-on scenarios. We concluded that the current efforts of national flagship environmental policies are beneficial but not sufficient for reaching ambitious carbon reduction goals like Paris Agreement. This study once again underlined the necessity in the supranational framework that may control the carbon abatement goals in East Asia. Without the supranational framework, achievements in carbon emission reductions are strongly hindered by the socioeconomic environment and the regional (or sectoral) emphasis of carbon reduction activities within a national economy.

The CarbonTracker (CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model’s performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within −0.3 and 1.3 ppm, except for inland stations (7.7 ppm).

It is evident that evaluating the measurement of greenhouse gases (GHGs) obtained from multi-platform instruments against accurate and precise instrument such as aircraft in-situ is very essential when using remote sensing GHGs results for source/sink estimations with inverse modeling. The results of the inverse models are very sensitive even to small biases in the data (Rayner and O’Brien 2001). In this work, we have evaluated ground-based high resolution Fourier Transform Spectrometer (g-b FTS) and the Greenhouse gases Observing SATellite (GOSAT) column-averaged dry air mole fraction of methane (XCH4) through aircraft in-situ observations over Anmyeondo station (36.538o N, 126.331o E, 30 m above sea level). The impact of the spatial coincidence criteria was assessed by comparing GOSAT data against g-b FTS. We noticed there was no any systematic difference based on the given coincidence criteria. GOSAT exhibited a bias ranging from 0.10 to 3.37 ppb, with the standard deviation from 4.92 to 12.54 ppb, against g-b FTS with the spatial coincidence criteria of ±1, ±3, ±5 degrees of latitude and longitude and ± 1 h time window. Data observed during ascent and descent of the aircraft is considered as vertical profiles within an altitude range of 0.2 to a maximum of 9.0 km so that some assumptions were applied for the construction of the profiles below 0.2 and above 9.0 km. In addition, the suitability of aircraft data for evaluation of remote sensing instruments was confirmed based on the assessment of uncertainties. The spatial coincidence criteria is ±1o latitude and ± 2o longitude and for temporal difference is ±1 h of the satellite observation overpass time were applied, whereas g-b FTS data are the mean values measured within ±30 min of the aircraft observation time. Furthermore, the sensitivity differences of the instruments were taken into account. With respect to aircraft, the g-b FTS data were biased by −0.19 ± 0.69%, while GOSAT data were biased by −0.42 ± 0.84%. These results confirm that both g-b FTS and GOSAT are consistent aircraft observations and assure the reliability of the datasets for inverse estimate of CH4.

In this study, we propose a meshless scheme, GC-LSM (Geometric Conservation Least Squares Method), satisfying the geometric conservation and 1st order consistency. These constraints are introduced in order to overcome the non-conservativeness of the original meshless scheme and imposed by Lagrange multiplier on the least squares method which determines weighting coefficients of the derivative terms. Improvements on the meshless scheme are confirmed through computations with randomly distributed grid points for a sine wave, nozzle flow, and hypersonic flow around blunt body. Combined with AUSMPW + and MUSCL scheme, GC-LSM of the second order accuracy gives non-oscillating solution around a strong shockwave, even for hypersonic flow, and shows its capability comparable to the finite volume method in views of accuracy, robustness, and convergence.

Since the late 1990s, the meteorological observatory established in Anmyeondo (36.5382˚ N, 126.3311˚ E, and 30 m above mean sea level), has been monitoring several greenhouse gases such as CO2, CH4, N2O, CFCs, and SF6, as part of the Global Atmosphere Watch (GAW) Program. A high resolution ground-based (g-b) Fourier Transform Spectrometer (FTS, IFS-125HR model) was installed at such observation site in 2013, and has been fully operated within the frame work of the Total Carbon Column Observing Network (TCCON) since August, 2014. The solar spectra recorded by the g-b FTS are covered in the range between 3,800 and 16,000 cm−1 at the spectral resolution of 0.02 cm−1 during the measurement period between 2013 and 2016. In this work, the GGG2014 version of the TCCON standard retrieval algorithm was used to retrieve XCO2 concentrations from the FTS spectra. Two spectral bands (at 6220.0 and 6339.5 cm−1 center wavenumbers) were used to derive the XCO2 concentration within the spectral residual of +0.01 %. All sources of errors were thoroughly analyzed. In this paper, we introduced a new home made OASIS (Operational Automatic System for Intensity of Sunray) system to our g-b FTS instrument and that allows reducing the solar intensity variations (SIV) below 2 %. A comparison of the XCO2 concentration in g-b FTS and OCO-2 (Orbiting Carbon Observatory) satellite observations were presented only for the measurement period between 2014 and 2015. Nine coincident observations were selected on a daily mean basis. It was obtained that OCO-2 exhibited low bias with respect to the g-b FTS, which is about −0.065 ppm with the standard deviation of 1.66 ppm, and revealed a strong correlation (R = 0.85). Based on seasonal cycle comparisons, both instruments were generally agreed in capturing seasonal variations of the target species with its maximum and minimum levels in spring and late summer respectively. In the future, it is planned to exert further works in utilizing the FTS measurements for the evaluation of satellite observations such as Greenhouse Gases Observing Satellite (GOSAT) at observation sites. This is the first report of the g-b FTS observations of XCO2 species over the Anmyeondo station.