Drivers of declining CO2 emissions in 18 developed economies

Global emissions of carbon dioxide (CO 2 ) from fossil fuels and industry increased by 2.2% per year on average between 2005 and 2015 1 . Global emissions need to peak and decline rapidly to limit climate change to well below 2 °C of warming 2,3 , which is one of the goals of the Paris Agreement 4 . Untangling the reasons underlying recent changes in emissions trajectories is critical to guide efforts to attain those goals. Here we analyse the drivers of decreasing CO 2 emissions in a group of 18 developed economies that have decarbonized over the period 2005–2015. We show that within this group, the displacement of fossil fuels by renewable energy and decreases in energy use explain decreasing CO 2 emissions. However, the decrease in energy use can be explained at least in part by a lower growth in gross domestic product. Correlation analysis suggests that policies on renewable energy are supporting emissions reductions and displacing fossil fuels in these 18 countries, but not elsewhere, and that policies on energy efficiency are supporting lower energy use in these 18 countries, as well as more widely. Overall, the evidence shows that efforts to reduce emissions are underway in many countries, but these efforts need to be maintained and enhanced by more stringent policy actions to support a global peak in emissions followed by global emissions reductions in line with the goals of the Paris Agreement 3

To what extent can behaviour change techniques be identified within an adaptable implementation package for primary care? A prospective directed content analysis

Interpreting evaluations of complex interventions can be difficult without sufficient description of key intervention content. We aimed to develop an implementation package for primary care which could be delivered using typically available resources and could be adapted to target determinants of behaviour for each of four quality indicators: diabetes control, blood pressure control, anticoagulation for atrial fibrillation and risky prescribing. We describe the development and prospective verification of behaviour change techniques (BCTs) embedded within the adaptable implementation packages

The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2018

Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), which is well in line with the national inventories. Over 2011–2015, the CO2 land sources and sinks from NGHGI estimates report −90 Tg C yr−1 ±  30 Tg C yr−1 while all other BU approaches report a mean sink of −98 Tg C yr−1 (± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 Tg C yr−1). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of “CO2 flux” obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a).publishedVersio

AD51B in Familial Breast Cancer

Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737 and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer predisposition, particularly in the context of familial breast cancer in Finland. We sequenced the coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for identification of possible recurrent founder mutations. In addition, we studied the known rs999737, rs2588809, and rs1314913 SNPs and RAD51B haplotypes in 44,791 breast cancer cases and 43,583 controls from 40 studies participating in the Breast Cancer Association Consortium (BCAC) that were genotyped on a custom chip (iCOGS). We identified one putatively pathogenic missense mutation c.541C>T among the Finnish cancer patients and subsequently genotyped the mutation in additional breast cancer cases (n = 5259) and population controls (n = 3586) from Finland and Belarus. No significant association with breast cancer risk was seen in the meta-analysis of the Finnish datasets or in the large BCAC dataset. The association with previously identified risk variants rs999737, rs2588809, and rs1314913 was replicated among all breast cancer cases and also among familial cases in the BCAC dataset. The most significant association was observed for the haplotype carrying the risk-alleles of all the three SNPs both among all cases (odds ratio (OR): 1.15, 95% confidence interval (CI): 1.11–1.19, P = 8.88 x 10−16) and among familial cases (OR: 1.24, 95% CI: 1.16–1.32, P = 6.19 x 10−11), compared to the haplotype with the respective protective alleles. Our results suggest that loss-of-function mutations in RAD51B are rare, but common variation at the RAD51B region is significantly associated with familial breast cancer risk

Reconstructing Global Daily CO2 Emissions via Machine Learning

High temporal resolution CO2 emission data are crucial for understanding the drivers of emission changes, however, current emission dataset is only available on a yearly basis. Here, we extended a global daily CO2 emissions dataset backwards in time to 1970 using machine learning algorithm, which was trained to predict historical daily emissions on national scales based on relationships between daily emission variations and predictors established for the period since 2019. Variation in daily CO2 emissions far exceeded the smoothed seasonal variations. For example, the range of daily CO2 emissions equivalent to 31% of the year average daily emissions in China and 46% of that in India in 2022, respectively. We identified the critical emission-climate temperature (Tc) is 16.5 degree celsius for global average (18.7 degree celsius for China, 14.9 degree celsius for U.S., and 18.4 degree celsius for Japan), in which negative correlation observed between daily CO2 emission and ambient temperature below Tc and a positive correlation above it, demonstrating increased emissions associated with higher ambient temperature. The long-term time series spanning over fifty years of global daily CO2 emissions reveals an increasing trend in emissions due to extreme temperature events, driven by the rising frequency of these occurrences. This work suggests that, due to climate change, greater efforts may be needed to reduce CO2 emissions

Fossil CO2 emissions in the post-COVID-19 era

Five years after the adoption of the Paris Climate Agreement, growth in global CO2 emissions has begun to falter. The pervasive disruptions from the COVID-19 pandemic have radically altered the trajectory of global CO2 emissions. Contradictory effects of the post-COVID-19 investments in fossil fuel-based infrastructure and the recent strengthening of climate targets must be addressed with new policy choices to sustain a decline in global emissions in the post-COVID-19 era

National contributions to climate change due to historical emissions of carbon dioxide, methane, and nitrous oxide since 1850

Anthropogenic emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) have made significant contributions to global warming since the pre-industrial period and are therefore targeted in international climate policy. There is substantial interest in tracking and apportioning national contributions to climate change and informing equitable commitments to decarbonisation. Here, we introduce a new dataset of national contributions to global warming caused by historical emissions of carbon dioxide, methane, and nitrous oxide during the years 1851–2021, which are consistent with the latest findings of the IPCC. We calculate the global mean surface temperature response to historical emissions of the three gases, including recent refinements which account for the short atmospheric lifetime of CH4. We report national contributions to global warming resulting from emissions of each gas, including a disaggregation to fossil and land use sectors. This dataset will be updated annually as national emissions datasets are updated

European anthropogenic AFOLU emissions and their uncertainties: a review and benchmark data

Emission of greenhouse gases (GHG) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, along with estimates of their inherent uncertainties, in order to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in Europe. The data integrates recent AFOLU emission inventories with ecosystem data and land carbon models, covering the European Union (EU28) and summarizes GHG emissions and removals over the period 1990–2016, of relevance for UNFCCC. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGI) with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Particular effort is devoted to the estimation of uncertainty, its propagation and role in the comparison of different estimates. While NGHGI data for EU28 provides consistent quantification of uncertainty following the established IPCC guidelines, uncertainty in the estimates produced with other methods will need to account for both within model uncertainty and the spread from different model results. At EU28 level, the largest inconsistencies between estimates are mainly due to different sources of data related to human activity which result in emissions or removals taking place during a given period of time (IPCC 2006) referred here as activity data (AD) and methodologies (Tiers) used for calculating emissions/removals from AFOLU sectors. The referenced datasets related to figures are visualised at https://doi.org/10.5281/zenodo.3460311, Petrescu et al., 2019

Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories 1959-2018

Quantification of CO2 fluxes at the Earth’s surface is required to evaluate the causes and drivers of observed increases in atmospheric CO2 concentrations. Atmospheric inversion models disaggregate observed variations in atmospheric CO2 concentration to variability in CO2 emissions and sinks. They require prior constraints fossil CO2 emissions. Here we describe GCP-GridFED (version 2019.1), a gridded fossil emissions dataset that is consistent with the national CO2 emissions reported by the Global Carbon Project (GCP). GCP-GridFEDv2019.1 provides monthly fossil CO2 emissions estimates for the period 1959-2018 at a spatial resolution of 0.1°. Estimates are provided separately for oil, coal and natural gas, for mixed international bunker fuels, and for the calcination of limestone during cement production. GCP-GridFED also includes gridded estimates of O2 uptake based on oxidative ratios for oil, coal and natural gas. It will be updated annually and made available for atmospheric inversions contributing to GCP global carbon budget assessments, thus aligning the prior constraints on top-down fossil CO2 emissions with the bottom-up estimates compiled by the GCP

Global Carbon Budget 2016

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere &ndash; the &ldquo;global carbon budget&rdquo; &ndash; is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2&nbsp;emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in&nbsp;SOCEAN&nbsp;is evaluated with data products based on surveys of ocean CO2&nbsp;measurements. The global residual terrestrial CO2&nbsp;sink (SLAND) &nbsp;is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as &plusmn;1&sigma;, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006&ndash;2015),&nbsp;EFF was 9.3 &plusmn; 0.5 GtC yr-1,&nbsp;ELUC 1.0 &plusmn; 0.5 GtC yr-1,&nbsp;GATM 4.5 &plusmn; 0.1 GtC yr-1,&nbsp;SOCEAN&nbsp;2.6 &plusmn; 0.5 GtC yr-1, and&nbsp;SLAND 3.1 &plusmn; 0.9 GtC yr-1. For year 2015 alone, the growth in&nbsp;EFF was approximately zero and emissions remained at 9.9 &plusmn; 0.5 GtC yr-1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr-1 that took place during 2006&ndash;2015. Also, for 2015,&nbsp;ELUC was 1.3 &plusmn; 0.5 GtC yr-1,&nbsp;GATM&nbsp;was 6.3 &plusmn; 0.2 GtC yr-1,&nbsp;SOCEAN&nbsp;was 3.0 &plusmn; 0.5 GtC yr-1, and&nbsp;SLAND was 1.9 &plusmn; 0.9 GtC yr-1.&nbsp;GATM&nbsp;was higher in 2015 compared to the past decade (2006&ndash;2015), reflecting a smaller&nbsp;SLAND for that year. The global atmospheric CO2&nbsp;concentration reached 399.4 &plusmn; 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in&nbsp;EFF with +0.2 % (range of &minus;1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of&nbsp;EFF in 2016, the growth rate in atmospheric CO2&nbsp;concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Ni&ntilde;o conditions of 2015&ndash;2016. From this projection of&nbsp;EFF and assumed constant&nbsp;ELUC for 2016, cumulative emissions of CO2&nbsp;will reach 565 &plusmn; 55 GtC (2075 &plusmn; 205 GtCO2) for 1870&ndash;2016, about 75 % from&nbsp;EFF and 25 % from&nbsp;ELUC . This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Qu&eacute;r&eacute; et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).</p