Coal combustion for power generation made up 30% of global CO2 emissions in 2018. To achieve the goal of the Paris Agreement to keep global average temperatures below 2°C, power generation must be decarbonized globally by mid-century. This requires a rapid phase-out of coal-fired power generation. However, global coal power expansion continues, mostly in developing countries where electricity demand continues to increase. Since the early 2010s, Southeast Asia's coal power capacity expansion has been among the fastest in the world, following China and India, but its implications for the global climate and regional energy transition remain understudied. Here we examine Southeast Asia's power generation pipeline as of mid-2020 and evaluate its implications for the region's CO2 emissions over the plant lifetime as well as projected electricity generation between 2020-2030 in Indonesia, Vietnam, and the Philippines. We find that power plants under construction and planned in Southeast Asia as of 2020 will more than double the region's fossil fuel power generation capacity. If all fossil fuel plants under development are built, Southeast Asia's power sector CO2 emissions will increase by 72% from 2020 to 2030 and long-term committed emissions will double. Moreover, in Indonesia, Vietnam, and the Philippines, projected electricity generation from fossil fuel plants under development, combined with generation from renewable capacity targets and existing power capacity, will exceed future national electricity demand. As a result, fossil fuel plants will likely be underutilized and/or become stranded assets while also potentially crowding out renewable energy deployment.
Power sector decarbonization requires a fundamental redirection of global finance from fossil fuel infrastructure towards low carbon technologies. Bilateral finance plays an important role in the global energy transition to non-fossil energy, but an understanding of its impact is limited. Here, for the first time, we compare the influence of overseas finance from the three largest economies – United States, China, and Japan – on power generation development beyond their borders and evaluate the associated long-term CO2 emissions. We construct a new dataset of Japanese and U.S. overseas power generation finance between 2000 and 2018 by analyzing their national development finance institutions’ press releases and annual reports and tracking their foreign direct investment at the power plant level. Synthesizing this new data with previously developed datasets for China, we find that the three countries’ overseas financing concentrated in fossil fuel power technologies over the studied period. Financing commitments from China, Japan, and the United States facilitated 101 GW, 95 GW, and 47 GW overseas power capacity additions, respectively. The majority of facilitated capacity additions are fossil fuel plants (64% for China, 87% for Japan, and 66% for the United States). Each of the countries’ contributions to non-hydro renewable generation was less than 15% of their facilitated capacity additions. Together, we estimate that overseas fossil fuel power financing through 2018 from these three countries will lock in 24 Gt CO2 emissions by 2060. If climate targets are to be met, replacing bilateral fossil fuel financing with financing of renewable technologies is crucial.
Large-scale carbon capture, utilization, and storage (CCUS) requires development of critical infrastructure to connect capture locations to geological storage sites. Here, we investigate what government policies would be required to make the development of CO2 pipelines and large-scale CCUS in the power sector economically viable. We focus on the transition from conventional coal to non-CO2-emitting natural gas-fired Allam-cycle power with CCUS and study a system in which 156 Allam-cycle power generators representing 100 GW of capacity send their captured CO2 emissions to three geological storage locations in the central United States through 7500 miles of new pipeline. Enabling policies for this system include low-interest government loans of approximately $20 billion for pipeline construction and an extended 20-year Section 45Q tax credit, or similar longer-term carbon price incentive. Additional policy support will be needed to enable initial construction of pipelines and early mover power generators, such as cost-sharing, governments assuming future demand risk, or increased subsidies to early movers. The proposed system will provide reliable, dispatchable, flexible zero-emission power generation, complementing the intermittent generation by renewables in a decarbonized U.S. power sector. The proposed pipeline network could also connect into future regional infrastructure networks and facilitate large-scale carbon management.
Recent studies have reported methane (CH4) emissions from abandoned oil and gas wells across the United States and the United Kingdom. These emissions can reach hundreds of kg CH4 per year per well and are important to include in greenhouse gas emission inventories and mitigation strategies. Emission estimates are generally based on single, short-term measurements that assume constant emission rates over both short (hours) and longer (months/years) time periods. To investigate this assumption, we measure CH4 missions from 18 abandoned oil and gas wells in the USA and the UK continuously over 24 h and then make repeat 24 -h measurements at a single site over 12 months. While the lack of historical records for these wells makes it impossible to determine the underlying leakage-pathways, we observed that CH4 emissions at all wells varied over 24 h (range 0.2-81,000 mg CH4 hr−1) with average emissions varying by a factor of 18 and ranging from factors of 1.1–142. We did not find a statistically significant relationship between the magnitude of emissions and variability or that variability is correlated with temperature, relative humidity or atmospheric pressure. The results presented here suggest high CH4 emission events tend to be short-lived, so short-term (< 1 h) sampling is likely to miss them. Our findings present the dynamic nature of CH4 emissions from abandoned oil and gas wells which should be considered when planning measurement methodologies and developing greenhouse gas inventories/mitigation strategies. Incorporation of these temporal dynamics could improve national greenhouse gas emissions inventories.
Since 1850 the atmospheric mixing ratio of methane (CH4), a potent greenhouse gas, has doubled. This increase is directly linked to an escalation in emissions from anthropogenic sources. An inexpensive means to identify and monitor CH4 emission sources and evaluate the efficacy of mitigation strategies is essential. However, sourcing reliable, low-cost, easy-to-calibrate sensors that are fit for purpose is challenging. A recent study showed that CH4 mixing ratio data from a low-power, low-cost CH4 sensor (Figaro TGS2600) agreed well with CH4 mixing ratios measured by a high precision sensor at mixing ratios between 1.85 ppm and 2 ppm. To investigate, as a proof of concept, if this low-cost sensor could be used to measure typical ambient CH4 mixing ratios, we operated a TGS2600 in conjunction with a Los Gatos Ultra-portable Greenhouse Gas Analyzer (UGGA) in controlled laboratory conditions. We then explored the sensor's long-term reliability by deploying the TGS2600 near an onshore gas terminal to calculate emissions from May to July 2018. Our initial studies showed that previously published linear algorithms could not convert TGS2600 output to CH4 mixing ratios measured by the UGGA. However, we derived a non-linear empirical relationship that could be used to reliably convert the output of a TGS2600 unit to CH4 mixing ratios over a range of 1.85–5.85 ppm that agree to a high-precision instrument output to ±0.01 ppm. Our study showed that the TGS2600 could be used to continuously measure variability in CH4 mixing ratios from 1.82 to 5.40 ppm for three months downwind of the gas terminal. Using a simplified Gaussian Plume approach, these mixing ratios correspond to an emission flux range of 0–238 g CH4 s−1, with average emission of 9.6 g CH4 s−1 from the currently active North Terminal and 1.6 g CH4 s−1 from the decommissioned South Terminal. Our work here demonstrates the feasibility of utilizing a low-cost sensor to detect methane leakage at concentrations close to ambient background levels, as long as the device is routinely calibrated with an accurate reference instrument. Having a widely deployed network of such low-cost CH4 sensors would allow improved identification, monitoring and mitigation of a variety of CH4 emissions.
This study evaluates the ability of the Community Multiscale Air Quality (CMAQ) model to simulate the spatial variability of summertime ozone (O3) at the surface and in the free troposphere over the continental United States. Simulated surface O3 concentrations are compared with 987 Air Quality System (AQS) sites and 123 Clean Air Status and Trends Network (CASTNet) sites. CMAQ’s ability to reproduce surface observations varies with O3 concentration. The model best simulates observed O3 for intermediate concentrations (40–60 ppbv), while over-(under-) predicting at lower (higher) levels. CMAQ reproduces surface O3 for a wide range of conditions (30–80 ppbv) with a normalized mean error (NME) less than 35% and normalized mean bias (NMB) lying between 715% for the whole domain. Although systematically over-predicting O3 in the east and under-predicting it in the western United States, CMAQ is able to reproduce 1- and 8-h daily maxima with a cross-domain mean bias (MB) of 1 and 8 ppbv, or NMB of 8% and 25%, respectively. The model underestimates observed O3 at rural sites (MB ¼ 5 ppbv, NMB ¼ 5% and NME ¼ 23% with a 40 ppbv cut-off value) and over-predicts it at urban and suburban sites by a similar magnitude (MB ¼ 6 ppbv, NMB ¼ 7% and NME ¼ 25%). Apparent errors and biases decrease when data is averaged over longer periods, suggesting that most evaluation statistics are dependent on the time scale of data aggregation. Therefore, performance criteria should specify an averaging period (e.g., 1- or 8- h) and not be independent of averaging period as some current model evaluation studies imply. Comparisons of vertical profiles of simulated O3 with ozonesonde data show both overestimation and underestimation by 10–20 ppbv in the lower troposphere and a consistent under-prediction in the upper troposphere. Vertical O3 distributions are better simulated when lateral boundary conditions obtained from the global Model of Ozone and Related Tracers version 2 (MOZART-2) are used, but under-prediction remains. The assumption of zero-flux at the top boundary and the resulting exclusion of the contribution of stratosphere–troposphere exchange to tropospheric O3 concentrations limit the ability of CMAQ to reproduce O3 concentrations in the upper troposphere. r 2006 Elsevier Ltd. All rights reserved.