Carbon footprint of global natural gas supplies to China

China's energy landscape has long been dominated by coal, but concerns over air pollution prompted a significant shift towards natural gas. The coal-to-gas switching policy accelerated natural gas's growth, making it the fastest-growing fossil fuel in the country. By 2017, China's gas supply reached a record 235 billion standard cubic meters (bscm), a 17% increase from 2016. This trend is projected to continue, with gas's share in the energy mix anticipated to rise from 6% in 2016 to 15% by 2030. However, China's limited domestic conventional gas production necessitates significant imports via pipelines and liquefied natural gas (LNG). The country is actively developing its shale gas resources, boasting the world's largest technically recoverable shale gas reserves. While replacing coal with natural gas aims to reduce emissions and align with China's commitment to a 60-65% carbon intensity reduction from 2005 levels by 2030, the effectiveness depends on the lifecycle emissions of natural gas. Upstream emissions (extraction, processing, transmission for pipeline gas, and additional liquefaction, shipping, storage, and regasification for LNG) account for 20-50% of these lifecycle emissions. Combustion emissions remain relatively constant. Variations in well-to-city-gate emissions among different sources, influenced by geological conditions, gas composition, and distances to market, underscore the need for a field-specific analysis to assess GHG emissions. This study undertakes this analysis for the first time, offering crucial insights for emission reduction strategies and energy policy development.

Previous research has examined the potential climate benefits of switching from coal to natural gas in China, but with varying conclusions due to uncertainties surrounding natural gas lifecycle emissions. Studies like Qin et al. (2017) investigated the net carbon reductions achievable through shale gas adoption, finding mixed results depending on specific scenarios and assumptions. Other works have focused on regional differences in air pollution and carbon-water synergies resulting from China's natural gas industry (Qin et al., 2018). However, these studies often lack the granular level of analysis necessary to account for the heterogeneity of individual gas fields. The present study addresses this gap by examining the specific GHG intensities of gas supplies to China from 104 fields across multiple countries.

This research employed a well-to-city-gate life-cycle assessment (LCA) model to estimate GHG intensities. The model integrated existing methodologies for natural gas extraction, processing, and transmission (Skone et al., 2016; Littlefield et al., 2014) with Argonne National Laboratory's GREET model (Wang, 2018) for LNG-related processes. The model incorporates field-specific data, including gas field location, production characteristics, raw gas composition, pipeline transmission distances, liquefaction plant data, shipping distances, and more. This field-specific approach accounts for the heterogeneity across different gas sources and offers a more accurate assessment than broader regional or national averages. A detailed estimation of pipeline transmission distances involved identifying target consumers for each gas field and calculating weighted average transmission distances based on pipeline system information from major oil and gas companies. Provincial-level aggregation of supply destinations was used due to data limitations. The LCA model accounts for the electricity generation mix of each gas-producing country using data from the International Energy Agency's World Energy Statistics (IEA, 2016). The model considers various processes such as gas extraction, processing, transmission, liquefaction, shipping, storage, and regasification. Uncertainties in parameters were addressed using Monte Carlo simulations to calculate confidence intervals for the results. The study analyzed 104 gas fields accounting for approximately 96% of China's gas supply in 2016, providing a comprehensive representation of the nation’s gas supply sources.

The study revealed substantial variation in well-to-city-gate GHG intensities across the 104 gas fields, ranging from 6.2 to 43.3 g CO₂eq MJ⁻¹. Domestic conventional gas exhibited the lowest average GHG intensity (15.5 g CO₂eq MJ⁻¹), while international pipeline gas showed the highest (35.9 g CO₂eq MJ⁻¹). Analysis of domestic conventional gas fields (34 fields) revealed that transmission distances significantly influence transmission emissions, with fields farthest from consumption centers displaying the highest emissions. High raw gas impurity levels (e.g., CO₂, H₂S) result in increased gas processing emissions due to intensive energy requirements for separation. Furthermore, fields with high gas processing emissions also tended to have higher extraction emissions due to the increased raw gas extraction needed to compensate for feedstock loss during processing. Domestic unconventional gas (25 fields) showed an average GHG intensity of 21.4 g CO₂eq MJ⁻¹, varying across coal bed methane, tight gas, and shale gas. The 37 overseas LNG sources had a range of 17.2 to 43.3 g CO₂eq MJ⁻¹, influenced by extraction techniques, production characteristics, gas composition, transmission, and shipping distances. The GHG intensity supply curve for 2016 shows a supply-energy-weighted average GHG intensity of 21.7 g CO₂eq MJ⁻¹. Key contributors to the 2016 supply included Sulige (domestic tight gas), Galkynysh and Bagtiyarlyk (Turkmenistan), Anyue-longwangmiao (domestic conventional gas), Puguang (domestic conventional gas), Jingbian (domestic tight gas), Kela (domestic conventional gas), Fuling (domestic shale gas), Australia Pacific LNG, and Qatargas LNG. The 2030 projections indicate an increase in the supply-energy-weighted average GHG intensity to 23.3 g CO₂eq MJ⁻¹, driven by increased shares of GHG-intensive sources from Russia, Central Asia, and China's domestic shale gas fields. The analysis suggests that high GHG intensities from gas supply could significantly offset the climate benefits of coal-to-gas switching. Different scenarios with varying GHG intensities illustrate potential ranges of climate benefits, ranging from significant reductions to minimal gains, depending on the gas source’s GHG intensity.

The findings highlight the critical need to consider the GHG intensity of gas supplies in China's energy policy. While the coal-to-gas switch offers potential climate benefits, the considerable variation in GHG intensities among different sources underscores the importance of strategic gas resource management. The results emphasize the necessity to reduce GHG intensity to maximize the climate benefits of the coal-to-gas switch. Optimizations of pipeline networks to reduce transmission distances, methane leakage mitigation, and the application of carbon capture and storage (CCS) in high-CO₂ gas fields are crucial for emissions reduction. Importantly, the study demonstrates how different import strategies carry different implications for global warming. The geographical distance between gas fields in Western Russia and Central Asia and China's demand centers necessitates longer pipelines and higher GHG intensities compared to utilizing less-GHG-intensive LNG sources from closer regions. This suggests opportunities for optimizing regional distribution of gas supplies within China to enhance emission reduction benefits. While the study's projections reflect current plans, uncertainties remain due to evolving energy policies and the uncertain production status of individual gas fields. The high GHG intensity of domestic shale gas, compared to overseas LNG, raises concerns about the climate benefits of its aggressive development.

This study provides crucial insights into the carbon footprint of China's natural gas supplies, revealing significant variability in GHG intensities across different sources. The analysis underscores the need for a strategic approach to gas supply diversification, focusing on lower-emission sources to maximize the climate benefits of the coal-to-gas switch. Future research should explore more detailed economic analyses encompassing the cost of various natural gas sources, along with further investigation into the potential for emission reductions through technological advancements and policy interventions. Continued monitoring and refinement of the GHG intensity supply curves will be essential to inform effective clean energy policymaking in China.

The study's projections for 2030 are based on existing plans and might not fully capture the dynamic nature of energy policy and unforeseen changes in gas production. The aggregation of supply destinations at the provincial level, due to data limitations, could introduce some uncertainty in the transmission distance estimates. Also, the economic analysis is preliminary and requires further data for more in-depth assessments.