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Wildfires are becoming more frequent due to the global climate change. Large amounts of greenhouse gases emitted by wildfires can lead to increases in extreme climate events. Accurately estimating the greenhouse gas carbon dioxide (CO2) emissions from wildfires is important for mitigation of climate change. In this paper, we develop a novel method to estimate wildfire CO2 emissions from the relationship between local CO2 emissions and XCO2 anomalies. Our method uses the WRF-Chem assimilation system from OCO-2 XCO2 retrievals which coupled with Data Assimilation Research Testbed (DART). To validate our results, we conducted three experiments evaluating the wildfire CO2 emissions over the conterminous United States. The four-month average wildfire emissions from July to October in 2015∼2018 were estimated at 4.408 Tg C, 1.784 Tg C, 1.514 Tg C and 2.873 Tg C, respectively. Compared to the average of established inventories CT2019B, FINNv1.5 and GFASv1.2 fire emissions, our estimates fall within one standard deviation, except for 2017 due to lacking of OCO-2 XCO2 retrievals. These results suggest that the regional carbon assimilation system, such as WRF-Chem/DART, using OCO-2 XCO2 retrievals has a great potential for accurately tracking regional wildfire emissions. [ABSTRACT FROM AUTHOR]

Efforts to enhance greenhouse gas (GHG) emission reduction in East Asia play a pivotal role on both global and regional scales in advancing climate mitigation strategies. This study aimed to better constrain anthropogenic CO 2 emission estimates by expanding the network of near-surface in-situ stations for CO 2 observations across South Korea. To achieve an optimal CO 2 network design, we conducted an Observing System Simulation Experiment (OSSE) coupled with the Stochastic Lagrangian Transport model (STILT), utilizing meteorological data from the Korean Integrated Model (KIM). Our inversion setup incorporated two CO 2 emission datasets with a 0.1o resolution: EDGAR v6 for prior emissions and GRACED for truth emissions. A uniform model-mismatch error of 3 ppm was introduced across sites. The effectiveness of the existing five in-situ stations, termed the base network, in South Korea was evaluated to gauge their ability to constrain CO 2 surface flux estimates. However, the findings revealed a reduction in flux uncertainty of only 29.2%, which fell short of the desired uncertainty reduction goal. In this base network, the Lotte World Tower (LWT: 37.5126°E, 127.1025°E) in Seoul and the Anmyeondo (AMY: 36.538576° N, 126.330071° E) site in Taean county stood as major contributors, with estimated reductions of 17.48% and 6.35%, respectively. Consequently, we proposed and developed an extended network, identifying seven candidate sites based on consideration of logistical factors, existing infrastructures, and proximity to the emission source regions. An incremental optimization scheme ranked their contributions, resulting in an additional 25% reduction, bringing the total to 54.13%. However, it is noteworthy that diminishing returns (ranging from 13% to less than 0.1%) were observed with an increase in station count mainly due to the possibility that adding a station earlier in the sequence might render subsequent stations redundant. Despite this, the proposed CO 2 network successfully reduced uncertainty in emissions, narrowing the gap with the objectives of the Global Greenhouse Gas Watch (G3W). • Designing CO 2 near-surface observation network over South Korea. • New stations selected considering logistic factors, existing infrastructures, and proximity to emission sources. • The base network was able to reduce 29.18% of the uncertainty in CO 2 emissions. • Extending network, by adding new seven candidate sites, led to a total uncertainty reduction of 54.13%. [ABSTRACT FROM AUTHOR]

In this paper we evaluate whether the US states have been able to achieve convergence in their carbon emission cycles which may be a key factor in taking a leap as regards the development of a US climate change policy. The use of a dynamic unobserved component approach and a time-varying parameter model enable estimation of the short run dynamics of energy convergence over the extended period 1960–2017. To date, this type of analysis has not received enough attention in the literature. The results reveal the existence of cross-state links in the fluctuations of CO 2 emissions, although the degree to which a good part of the states are co-moving is weak. We also find that cyclical convergence patterns differ considerably in both the level and trajectories across the US states. The difficulties in increasing synchronization of the US CO 2 emissions highlight the importance of the states to lead climate change mitigation actions. The present study presents valuable information of interest regarding the short-run characteristics in carbon dioxide emissions, for better understanding of factors affecting CO 2 mitigation policies. Image 1 • Short run characteristics of CO2 emissions convergence at state-level are studied. • We rank US states by the level of cross-state links in CO2 fluctuations. • Cyclical convergence patterns are distinctively different across states. • National environmental initiatives only have transitory effects on CO2 emissions. • Dataset of CO2 emissions covering 1960–2017 at state level is provided. [ABSTRACT FROM AUTHOR]