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507 records · Page 29

A comprehensive and synthetic dataset for global, regional, and national greenhouse gas emissions by sector 1970–2018 with an extension to 2019

To track progress towards keeping global warming well below 2 °C or even 1.5 °C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO 2 emissions, CH 4 emissions, N 2 O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF 6 , NF 3 ) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO 2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (~ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO 2 eq. consisting of CO 2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO 2 , CO 2 -LULUCF 5.7 ± 4.0 GtCO 2 , CH 4 10 ± 3.1 GtCO 2 eq., N2O 2.6 ± 1.6 GtCO 2 eq., and F-gases 1.3 ± 0.40 GtCO 2 eq. Initial estimates suggest further growth of 1.3 GtCO 2 eq. in GHG emissions to reach 59 ± 6.6 GtCO 2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr –1 ) compared to 2000–2009 (2.4 % yr –1 ), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

54 ENVIRONMENTAL SCIENCES↗

Dynamic projection of anthropogenic emissions in China: methodology and 2015–2050 emission pathways under a range of socio-economic, climate policy, and pollution control scenarios

Abstract. Future trends in air pollution and greenhouse gas (GHG)emissions for China are of great concern to the community. A set of globalscenarios regarding future socio-economic and climate developments, combiningshared socio-economic pathways (SSPs) with climate forcing outcomes asdescribed by the Representative Concentration Pathways (RCPs), was createdby the Intergovernmental Panel on Climate Change (IPCC). Chinese researchers have also developed various emission scenarios by considering detailed local environmental and climate policies. However, a comprehensive scenario set connecting SSP–RCP scenarios with local policies and representing dynamic emission changes under local policies is still missing. In this work, to fill this gap, we developed a dynamic projection model, the Dynamic Projection model for Emissions in China (DPEC), to explore China'sfuture anthropogenic emission pathways. The DPEC is designed tointegrate the energy system model, emission inventory model, dynamicprojection model, and parameterized scheme of Chinese policies. The modelcontains two main modules, an energy-model-driven activity rate projectionmodule and a sector-based emission projection module. The activity rateprojection module provides the standardized and unified future energyscenarios after reorganizing and refining the outputs from the energy systemmodel. Here we use a new China-focused version of the Global ChangeAssessment Model (GCAM-China) to project future energy demand and supply inChina under different SSP–RCP scenarios at the provincial level. Theemission projection module links a bottom-up emission inventory model, theMulti-resolution Emission Inventory for China (MEIC), to GCAM-China andaccurately tracks the evolution of future combustion and production technologiesand control measures under different environmental policies. We developedtechnology-based turnover models for several key emitting sectors (e.g.coal-fired power plants, key industries, and on-road transportationsectors), which can simulate the dynamic changes in the unit/vehicle fleetturnover process by tracking the lifespan of each unit/vehicle on an annualbasis. With the integrated modelling framework, we connected five SSP scenarios(SSP1–5), five RCP scenarios (RCP8.5, 7.0, 6.0, 4.5, and 2.6), and threepollution control scenarios (business as usual, BAU; enhanced controlpolicy, ECP; and best health effect, BHE) to produce six combined emissionscenarios. With those scenarios, we presented a wide range of China's futureemissions to 2050 under different development and policy pathways. We foundthat, with a combination of strong low-carbon policy and air pollutioncontrol policy (i.e. SSP1-26-BHE scenario), emissions of major airpollutants (i.e. SO 2 , NO x , PM 2.5 , and non-methane volatile organic compounds – NMVOCs) in China willbe reduced by 34%–66% in 2030 and 58%–87% in 2050 compared to 2015. End-of-pipe control measures are more effective for reducing air pollutant emissions before 2030, while low-carbon policy will play a more important rolein continuous emission reduction until 2050. In contrast, China's emissionswill remain at a high level until 2050 under a reference scenario without activeactions (i.e. SSP3-70-BAU). Compared to similar scenarios set from theCMIP6 (Coupled Model Intercomparison Project Phase 6), our estimates ofemission ranges are much lower than the estimates from the harmonized CMIP6 emissions dataset in2020–2030, but their emission ranges become similar in the year 2050.

54 ENVIRONMENTAL SCIENCES↗

Northern peatland microbial communities exhibit resistance to warming and acquire electron acceptors from soil organic matter

The response of microbial communities that regulate belowground carbon turnover to climate change drivers in peatlands is poorly understood. Here, we leverage a whole ecosystem warming experiment to elucidate the key processes of terminal carbon decomposition and community responses to temperature rise. Our dataset of 697 metagenome-assembled genomes (MAGs) represents the microbial community from the surface (10 cm) to 2 m deep into the peat column, with only 3.7% of genomes overlapping with other well-studied peatlands. Community composition has yet to show a significant response to warming after 3 years, suggesting that metabolically diverse soil microbial communities are resistant to climate change. Surprisingly, abundant and active methanogens in the genus Candidatus Methanoflorens, Methanobacterium , and Methanoregula show the potential for both acetoclastic and hydrogenotrophic methanogenesis. Nonetheless, the predominant pathways for anaerobic carbon decomposition include sulfate/sulfite reduction, denitrification, and acetogenesis, rather than methanogenesis based on gene abundances. Multi-omics data suggest that organic matter cleavage provides terminal electron acceptors, which together with methanogen metabolic flexibility, may explain peat microbiome composition resistance to warming.

54 ENVIRONMENTAL SCIENCES↗