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Severe spatiotemporal heterogeneity of emissions sources and limited measurement networks have been hampering the monitoring and understanding of CO2 fluxes in large cities, a great concern in climate research as big cities are among the major sources of anthropogenic CO2 in the climate system. To understand the CO2 fluxes in Seoul, Korea, CO2 fluxes at eight surface energy balance sites, six urban (vegetation-area fraction < 15%) and two suburban (vegetation-area fraction > 60%), for 2017–2018 are analyzed and attributed to the local land-use and business types. The analyses show that the CO2 flux variations at the suburban sites are mainly driven by vegetation and that the CO2 flux differences between the urban and suburban sites originate from the differences in the vegetation-area fraction and anthropogenic CO2 emissions. For the CO2 fluxes at the urban sites; (1) vehicle traffic (traffic) and heating-fuel consumption (heating) contribute > 80% to the total, (2) vegetation effects are minimal, (3) the seasonal cycle is driven mainly by heating, (4) the contribution of heating is positively related to the building-area fraction, (5) the annual total is positively (negatively) correlated with the commercial-area (residential-area) fraction, and (6) the traffic at the commercial sites depend further on the main business types to induce distinct CO2 flux weekly cycles. This study shows that understanding and estimation of CO2 fluxes in large urban areas require careful site selections and analyses based on detailed consideration of the land-use and business types refined beyond the single representative land-use type widely-used in contemporary studies. [ABSTRACT FROM AUTHOR]

The so-called Green Sahara (GS), which was a wet and vegetative Sahara region in the early to mid-Holocene, provides useful information on our climate simulation because it is a consequence of complex interaction between biophysical and climatic processes. It is still a challenge to simulate the GS in terms of vegetative extent and precipitation using current climate models. This study attempts to simulate the Green Sahara 8000 years ago by using the state-of-the-art Earth system model CESM that incorporates the nitrogen cycle and the soil–precipitation feedbacks. Our study puts more emphasis on the impact of soil biophysical properties (e.g., bare-soil albedo, porosity, heat capacity, and hydraulic conductivity) and soil nitrogen influenced by soil organic matter on the simulation of the GS. In this coupled simulation, vegetation interacts with changes in soil properties and soil organic matter by phenology, decomposition, and allocation of carbon and nitrogen. With changes in the Earth's orbit and dust in the early to mid-Holocene, the model simulates increased precipitation in North Africa but does not capture the extent of the GS. Our analysis shows that the Holocene greening is simulated better if the amount of soil nitrogen and soil texture is properly modified for the humid and vegetative GS period. Soil biochemical and physical properties increase precipitation and vegetation cover in North Africa through their influence on photosynthesis and surface albedo as well as their consequent enhanced albedo–precipitation and evapotranspiration–precipitation feedbacks. Our findings suggest that future climate simulation needs to consider consequent changes in soil nitrogen and texture with changes in vegetation cover and density for proper climate simulations. [ABSTRACT FROM AUTHOR]

Based on multiple linear regression (MLR) models, we estimated the PM2.5 at Seoul using a number of aerosol optical depth (AOD) values obtained from ground-based and satellite remote sensing observations. To construct the MLR model, we consider various parameters related to the ambient meteorology and air quality. In general, all AOD values resulted in the high quality of PM2.5 estimation through the MLR method: mostly correlation coefficients >~0.8. Among various polar-orbit satellite AODs, AOD values from the MODIS measurement contribute to better PM2.5 estimation. We also found that the quality of estimated PM2.5 shows some seasonal variation; the estimated PM2.5 values consistently have the highest correlation with in situ PM2.5 in autumn, but are not well established in winter, probably due to the difficulty of AOD retrieval in the winter condition. MLR modeling using spectral AOD values from the ground-based measurements revealed that the accuracy of PM2.5 estimation does not depend on the selected wavelength. Although all AOD values used in this study resulted in a reasonable accuracy range of PM2.5 estimation, our analyses of the difference in estimated PM2.5 reveal the importance of utilizing the proper AOD for the best quality of PM2.5 estimation. [ABSTRACT FROM AUTHOR]

Cities represent a key space for our sustainable trajectory in a changing environment, and our society is steadily embracing urban green space for its role in mitigating heatwaves and anthropogenic CO2 emissions. This study reports two-year surface fluxes of energy and CO2 measured via the eddy covariance method in an artificially constructed urban forest to examine the impact of urban forests on air temperature and net CO2 exchange. The urban forest site shows typical seasonal patterns of forest canopies with the seasonal march of the East Asian summer monsoon. Our analysis indicates that the urban forest reduces both the warming trend and urban heat island intensity compared to the adjacent high-rise urban areas and that photosynthetic carbon uptake is large despite relatively small tree density and leaf area index. During the significant drought period in the second year, gross primary production and evapotranspiration decreased, but their reduction was not as significant as those in natural forest canopies. We speculate that forest management practices, such as artificial irrigation and fertilization, enhance vegetation activity. We also stipulate that ecosystem respiration in urban forests is more pronounced than typical natural forests in a similar climate zone. This can be attributed to the substantial amount of soil organic carbon available due to intensive historical soil use and soil transplantation during forest construction, as well as relatively warmer temperatures in urban heat domes. Our observational study also indicates the need for caution in soil management for less CO2 emissions in urban areas. [ABSTRACT FROM AUTHOR]

Using the eddy covariance method, this study reports the one‐year turbulent fluxes of momentum, energy, and CO2, and their seasonal variations over a recently redeveloped high‐rise, high‐population, residential area in the metropolitan city of Seoul, Korea. The study area is affected by the Asian monsoon, which is accompanied by long rain spells and a related mid‐season depression of solar radiation in the summer. Our analysis shows that the urban surface energy balance and turbulence characteristics demonstrate typical urban properties. Unstable conditions dominate all day, and the storage heat flux (night‐time and morning) and sensible heat flux (afternoon) significantly affect the diurnal variations in the urban surface energy balance. Owing to the rough urban surface, the turbulence intensities are higher than those reported previously in other cities. The annual CO2 emission rate is approximately 13.1 kg CO2 m−2⋅year−1 with traffic, which is the major source of CO2 (+2.3 μmol⋅m−2⋅s−1 per 100 vehicles). Ecosystem respiration, including that by vegetation, soil, and humans, becomes dominant in the night‐time (00:00–05:00), thus contributing significantly to the annual CO2 budget. Further analysis indicates a unique coupling of urban surface energy partitioning and CO2 emission rates with the seasonal progression of the Asian monsoon: (a) surface albedo has annual minima in late summer when the sun elevation angle, is relatively higher and the urban surface condition is wetter than in other seasons; (b) the Bowen ratio ranges from 1.7 (summer) to 7.0 (winter); and (c) CO2 emission rates show seasonal variations with the progress of the summer monsoon. [ABSTRACT FROM AUTHOR]

Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9 km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3 ppmv for 16 and 9 km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16 km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of -19.2 (16 km), -16.7 (9 km), and -20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO = dCO2 = 9 ppbv ppmv-1) compared to theWest Sea (dCO=dCO2 = 28 ppbv ppmv-1). This "combustion signature contrast" is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8-12 ppbv ppmv-1, the West Sea: ~30 ppbv ppmv-1) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64-0.90, the West Sea: ~0:80) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO2 variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO2 concentrations at the surface with steeper vertical gradients (~0:4 ppmv hPa-1 for CO2 and 3.5 ppbv hPa-1 for CO) in the morning samples than observed (0:25 ppmv hPa-1 for CO2 and 1.7 ppbv hPa-1 for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9 km vs. 16 km) generally produces better forecasts. [ABSTRACT FROM AUTHOR]