Carbon Dioxide Information Analysis Center Research Articles

Extreme weather events and death based on temperature and CO2 emission – A global retrospective study in 77 low-, middle- and high-income countries from 1999 to 2018

Due to rising temperatures and CO2 emissions, climate change has become one of the most important global issues. We described the relationship between extreme weather-related events and death, globally, from 1999 through 2018. We used data from the emergency events database of the Université Catholique de Louvain. We also categorized the countries’ income according to the World Bank GDP and we used the CO2 emission levels data from the Carbon Dioxide Information Analysis Center to link the GDP and CO2 emissions to years of extreme weather conditions in each country. We conducted descriptive and Poisson Regression analysis to analyze the data. A total of 77 countries reported 425 extreme weather-related events from1999 through 2018. Mortality related events were highest in middle-income countries due to severe winter conditions (N = 2,020) and cold-waves (N = 70,972). The total number of recorded deaths due to heat waves was highest in high-income countries (N = 84,344). Furthermore, the number of deaths in high-income countries, compared to low-income countries, was five-fold higher (IRR 5.18; 95%CI 4.58; 5.85, p < 0.001). The mortality rate in heat season was almost seven-fold higher than that in cold/severe winter (IRR 33.43; 95%CI 32.85; 34.02, p < 0.001). The number of deaths increased significantly with the repetition of extreme events (IRR 6.82; 95%CI 6.68; 6.96, p < 0.001). We found the number of deaths increased in high-income countries, and this was associated with an increase in the number of times extreme events occurred per year and with heat wave.

Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios

Increases in atmospheric carbon dioxide (CO2) concentrations is the main driver of global warming due to fossil fuel combustion. Satellite observations provide continuous global CO2 retrieval products, that reveal the nonuniform distributions of atmospheric CO2 concentrations. However, climate simulation studies are almost based on a globally uniform mean or latitudinally resolved CO2 concentrations assumption. In this study, we reconstructed the historical global monthly distributions of atmospheric CO2 concentrations with 1° resolution from 1850 to 2013 which are based on the historical monthly and latitudinally resolved CO2 concentrations accounting longitudinal features retrieved from fossil-fuel CO2 emissions from Carbon Dioxide Information Analysis Center. And the spatial distributions of nonuniform CO2 under Shared Socio-economic Pathways and Representative Concentration Pathways scenarios were generated based on the spatial, seasonal and interannual scales of the current CO2 concentrations from 2015 to 2150. Including the heterogenous CO2 distributions could enhance the realism of global climate modeling, to better anticipate the potential socio-economic implications, adaptation practices, and mitigation of climate change.

An analysis of the spatial and temporal changes on the Jakobshavn Glacier (Greenland) using remote sensing data

This article presents the problem of climate warming and the effect of melting ice caps. The problem of climate warming is discussed in two stages. In the first stage, the factors affecting global warming are discussed in detail and the effects and risks of ablation extensively described. Analyses were conducted on data available online from NASA and Carbon Dioxide Information Analysis Center. The Greenland area (Jakobshavn Glacier) was selected to visualize glacier calving front changes. The analysis of changes was performed on the selected satellite images covering the summer period (June to September) provided by the Landsat program. Then, the changes in the position of the calving front of the Jakobshavn Glacier were visualized for the period 1985–2020,with a repeatability of every 5 years. Thus, our results addressed the challenges of environmental changes to remote sensing data processing. In addition to the visualization, a surface summary of these changes was presented in the study. The results were discussed in the context of climate change data processed by means of the GIS method. Furthermore, an analysis of the effects of greenhouse gases on glacier surface changes was performed.In summary, the results reveal that satellite imagery is an excellent source of data on which to visualize glacier calving rates, comparing individual layers showing the position of the glacier calving front and calculating the area of calved ice.

Relation between CO2 emissions and crude oil combustion in Iraq

Fossil fuel is the main source for CO2 emissions that causes global warming. This fact is the starting point for this paper, that consider on three different sources of data: crude oil used to calculate CO2 emissions for Iraq for the period from 1980 to 2018; annual data of total CO2 emissions available from the Carbon Dioxide Information Analysis Center (CDIAC) for Iraq and the world for the period from 1980 to 2014; and CO2 concentrations for Iraq for the period from 2002 to 2006 and for the world for the period from 1980 to 2018. The result is a multifaceted according to the dataset sources. Carbon dioxide emissions calculated from Iraqi crude oil was increased from 1.29 Mt in 2012 to 1.97 Mt in 2018. The world and Iraq CO2 emissions with different slop of average line that was 0.5 for world, 0.003 for Iraq, while increased exponential function from 2008 to 2014 to reach 36 and 0.17 Mt, respectively. The highest value of Iraqi CO2 concentration was 403 ppm in 2016, while the global CO2 concentrations slowly increased with slop line equal to 1.75 ppm per year, from minimum value of 338.6 ppm was in 1980, while maximum value of 407.05 ppm was in 2018, that’s mean no decreased in CO2 concentration unless emissions addressed.

Analysis The Intensity of CO2 Emissions from Fossil Fuel Combustion in Iraq

Carbon dioxide intensity (CI) refers to carbon dioxide emissions from fossil fuel combustion that mainly used for electricity, heat, transport, and other life requirements. The objective of this paper is better to understand CI as an indicator of Global Warming, and compared its behavior with two other variables (total CO2 emissions, and CO2 emissions per capita). The main data sources an available and activity data from Carbon Dioxide Information Analysis Center (CDIAC). Three annual variables used in this study; CI, total CO2 emissions, and CO2 per capita for fossil fuel emissions during long time series from (1971 to 2018).The results of CI shown that the highest value found out at the beginning of the study in 1971 was (7.188 kg/kg oil equivalent), and then decreased till reach to lower value was (1.707 kg/kg oil equivalent) in 1997, after that slowly increased in the last decade near to (3.63 kg/kg oil equivalent). The total CO2 emissions were strongly related to oil prediction. The highest value for total CO2 emissions was (188.1 Mt) in 2018, with Iraqi oil production more than (4.78 million barrel/day). The total CO2 emissions increased by (65. 176%) during the study period.  The total CO2 emissions were inversely proportional to CI.  The level of CO2 emission per capita rate fluctuated around average (3.49 metric tons per capita); the maximum rate was (4.99 metric tons per capita) in 2013.         

Assessment CO2 Emission Intensity of Crude Oil Production in Iraq

Carbon Dioxide Emissions Intensity (CDEI) in Iraq correlated between carbon dioxide emission (kg CO2) and crude oil production (COP) (kg oil equivalent). This relationship is important for industry and energy sectors to the achievement of their economic and environmental goal, then to know a common pattern of emissions intensity. The sources of data set from Carbon Dioxide Information analysis center (CDIAC), contain: total CO2 emission, COP from Iraqi Ministry of oil and Iraqi crude oil production increased over time and about (more than 80%) from Basra city. Environmental Kuznets Curve (EKC) was calculated.CDEI was nonlinear behavior that high level in the 1970s then decreased to reach 1.707 kg co2 / kgoil equivalent in 1997, and CDEI was more sensitive to COP than total CO2 emissions. EKC maximum values present in early 1970s and in 2004 present highest value was (0.082 metric ton / current US$ person). COP was unstable level, fluctuation between (1-3) mb/d, till reach 4.29 mb/d as average in 2019.

Research on the applicability of international databases to fossil fuel emission in China

ABSTRACTThe accuracy of carbon emissions statistics is a prerequisite for low-carbon development research. There are nearly 10 institutions in the world that have conducted in-depth studies on the carbon emissions of various countries; however, the accounting results of different databases are not the same and the analyses mainly focus on qualitative comparison. In order to clarify the source of databases’ difference in practical application, a quantitative applicability evaluation methodology has been built, which takes the data's scope, consistency and authority as the criterion, and combines the analytic hierarchy process and fuzzy integrated evaluation, enabling an applicability analysis of different databases on parameter level. Based on the emission characteristics of fossil fuel in China, the evaluation system has been applied to four core databases. The corresponding applicability to China, in descending order, is the International Energy Agency (IEA), Emissions Database for Global Atmospheric Research (EDGAR), Energy Information Administration (EIA) and Carbon Dioxide Information Analysis Center (CDIAC). Furthermore, by identifying the advantages/disadvantages of databases’ accounting of China's emissions, several suggestions on activity data, emission coefficients and supporting evaluation are proposed, aiming to provide references for the construction of a comprehensive database on carbon emissions in China.

The Open-source Data Inventory for Anthropogenic Carbon dioxide (CO2), version 2016 (ODIAC2016): A global, monthly fossil-fuel CO2 gridded emission data product for tracer transport simulations and surface flux inversions.

The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial resolution gridded emission data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emission spatial distributions are estimated at a 1×1 km spatial resolution over land using power plant profiles (emission intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emission data product (ODIAC2016) and presents analyses that help guiding data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emission modeling framework in order to deliver a comprehensive global gridded emission data product. Major changes from the 2011 publication are 1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring and international aviation and marine bunkers), 2) the use of multiple spatial emission proxies by fuel type such as nightlight data specific to gas flaring and ship/aircraft fleet tracks and 3) the inclusion of emission temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emission data product that covers 2000-2015. Our emission data can be viewed as an extended version of CDIAC gridded emission data product, which should allow data users to impose global fossil fuel emissions in more comprehensive manner than original CDIAC product. Our new emission modeling framework allows us to produce future versions of ODIAC emission data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. ODIAC data product could play an important role to support carbon cycle science, especially modeling studies with space-based CO2 data collected near real time by ongoing carbon observing missions such as Japanese Greenhouse Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory 2 (OCO-2) and upcoming future missions. The ODIAC emission data product including the latest version of the ODIAC emission data (ODIAC2017, 2000-2016), is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI.

Assessment of atmospheric CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; concentration enhancement from anthropogenic emissions based on satellite observations

Anthropogenic CO2 emissions are the dominant factor driving atmospheric CO2 concentration enhancement. However, the magnitude of the increase of CO2 concentration due to regional anthropogenic emissions remains unclear. Satellite-derived observations of atmospheric CO2 concentration provide a promising and effective means by which to monitor and evaluate regional anthropogenic CO2 emissions. This study used the column-averaged dry air mole fraction of CO2 (XCO2) derived from the observations of the greenhouse gases observation satellite (GOSAT) to assess quantitatively the effect of anthropogenic emissions on CO2 enhancement in two study areas located within the same latitudinal zone (35°–50°N): one in northern China and the other in the eastern USA. The study collected original XCO2 data (v02.xx) from a five-year period (2010–2014), released by the GOSAT project of the National Institute for Environmental Studies in Japan. Two high-density urban areas were selected as anthropogenic emission regions (emission-regions). These areas comprised the Beijing-Tianjin-Hebei area centered on Beijing (43 million square kilometers) in northern China and the urban agglomeration that includes New York City (55 million square kilometers) in the eastern USA, for which the magnitudes of anthropogenic CO2 emissions were about 950 and 1312 Tg CO2/a, respectively, according to the CO2 emission inventory in 2010 released by the Carbon Dioxide Information Analysis Center (CDIAC). Two regions with lower emissions, considered as background-regions for comparison with the emission-regions, were prepared according to the distribution of potential temperature and CO2 emission data from CDIAC, where anthropogenic CO2 emissions in 2010 were about 127 and 123 Tg CO2/a, respectively. The yearly averaged XCO2 data were calculated based on the seasonally averaged XCO2 data using the original GOSAT XCO2 retrievals from the four regions. In comparison with the background-regions, the results showed the enhancements of CO2 concentration in the emission-regions were, on average, 1.8 and 2.0 ppm in the Beijing-Tianjin-Hebei area and urban agglomeration in the USA, respectively. The maximum and minimum enhancements in China were 2.4 ppm in 2010 and 1.3 ppm in 2014, respectively. The maximum and minimum enhancements in the USA were 2.6 ppm in 2012 and 1.6 ppm in 2010, respectively. Moreover, the enhancements were highest in winter (2.4±0.6 and 2.8±0.8 ppm in China and the USA, respectively). Intriguingly, analysis of the monthly variations revealed that CO2 concentration in the Beijing-Tianjin-Hebei area decreased anomalously by 3.2 ppm during the Asia-Pacific Economic Cooperation (APEC) summit in November 2014 compared with the period before the summit. This anomalous drop probably reflects the effects of the artificial control of CO2 emissions implemented by the government during the APEC summit in order to improve air quality. The above enhancements of CO2 concentration prefer to be slightly less than the actual enhancements of CO2 concentration induced by anthropogenic emissions due to bio-ecological flux in the emission-regions. Based on an investigation of bio-ecological flux in the Beijing-Tianjin-Hebei area in earlier researches, the actual CO2 enhancement induced by anthropogenic emissions should be added an increment of less than 0.6 ppm absorbed by the bio-ecological system to the above-mentioned 1.8 ppm enhancement. The study results demonstrate the efficacy of using satellite-derived observations for evaluating the impact of anthropogenic emissions on the enhancement of atmospheric CO2 by analyzing changes in regional CO2 concentration. This provides a promising method with which to verify regional anthropogenic emissions and to support governmental oversight, control, and decision making regarding CO2 emission reduction.

The global methane budget 2000–2012

Abstract. The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003–2012 decade, global methane emissions are estimated by top-down inversions at 558 Tg CH4 yr−1, range 540–568. About 60 % of global emissions are anthropogenic (range 50–65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 Tg CH4 yr−1, range 596–884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (∼ 64 % of the global budget, &lt; 30° N) as compared to mid (∼ 32 %, 30–60° N) and high northern latitudes (∼ 4 %, 60–90° N). Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH4 yr−1, range 51–72, −14 %) and higher emissions in Africa (86 Tg CH4 yr−1, range 73–108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30–40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_METHANE_BUDGET_2016_V1.1) and the Global Carbon Project.

Gridded uncertainty in fossil fuel carbon dioxide emission maps, a CDIAC example

Abstract. Due to a current lack of physical measurements at appropriate spatial and temporal scales, all current global maps and distributions of fossil fuel carbon dioxide (FFCO2) emissions use one or more proxies to distribute those emissions. These proxies and distribution schemes introduce additional uncertainty into these maps. This paper examines the uncertainty associated with the magnitude of gridded FFCO2 emissions. This uncertainty is gridded at the same spatial and temporal scales as the mass magnitude maps. This gridded uncertainty includes uncertainty contributions from the spatial, temporal, proxy, and magnitude components used to create the magnitude map of FFCO2 emissions. Throughout this process, when assumptions had to be made or expert judgment employed, the general tendency in most cases was toward overestimating or increasing the magnitude of uncertainty. The results of the uncertainty analysis reveal a range of 4–190 %, with an average of 120 % (2σ) for populated and FFCO2-emitting grid spaces over annual timescales. This paper also describes a methodological change specific to the creation of the Carbon Dioxide Information Analysis Center (CDIAC) FFCO2 emission maps: the change from a temporally fixed population proxy to a temporally varying population proxy.

Global Carbon Budget 2016

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – 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 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 CO2 concentration 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 SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) 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 ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 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 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −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 EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from 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 Quéré 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).

An internally consistent dataset of &amp;lt;i&amp;gt;δ&amp;lt;/i&amp;gt;&amp;lt;sup&amp;gt;13&amp;lt;/sup&amp;gt;C-DIC in the North Atlantic Ocean – NAC13v1

Abstract. The stable carbon isotope composition of dissolved inorganic carbon (δ13C-DIC) can be used to quantify fluxes within the carbon system. For example, knowing the δ13C signature of the inorganic carbon pool can help in describing the amount of anthropogenic carbon in the water column. The measurements can also be used for evaluating modeled carbon fluxes, for making basin-wide estimates of anthropogenic carbon, and for studying seasonal and interannual variability or decadal trends in interior ocean biogeochemistry. For all these purposes, it is not only important to have a sufficient amount of data, but these data must also be internally consistent and of high quality. In this study, we present a δ13C-DIC dataset for the North Atlantic which has undergone secondary quality control. The data originate from oceanographic research cruises between 1981 and 2014. During a primary quality control step based on simple range tests, obviously bad data were flagged. In a second quality control step, biases between measurements from different cruises were quantified through a crossover analysis using nearby data of the respective cruises, and values of biased cruises were adjusted in the data product. The crossover analysis was possible for 24 of the 32 cruises in our dataset, and adjustments were applied to 11 cruises. The internal accuracy of this dataset is 0.017 ‰. The dataset is available via the Carbon Dioxide Information Analysis Center (CDIAC) at http://cdiac.ornl.gov/oceans/ndp_096/NAC13v1.html, doi:10.3334/CDIAC/OTG.NAC13v1.

The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean

Abstract. Version 2 of the Global Ocean Data Analysis Project (GLODAPv2) data product is composed of data from 724 scientific cruises covering the global ocean. It includes data assembled during the previous efforts GLODAPv1.1 (Global Ocean Data Analysis Project version 1.1) in 2004, CARINA (CARbon IN the Atlantic) in 2009/2010, and PACIFICA (PACIFic ocean Interior CArbon) in 2013, as well as data from an additional 168 cruises. Data for 12 core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4) have been subjected to extensive quality control, including systematic evaluation of bias. The data are available in two formats: (i) as submitted but updated to WOCE exchange format and (ii) as a merged and internally consistent data product. In the latter, adjustments have been applied to remove significant biases, respecting occurrences of any known or likely time trends or variations. Adjustments applied by previous efforts were re-evaluated. Hence, GLODAPv2 is not a simple merging of previous products with some new data added but a unique, internally consistent data product. This compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg−1 in dissolved inorganic carbon, 6 µmol kg−1 in total alkalinity, 0.005 in pH, and 5 % for the halogenated transient tracers.The original data and their documentation and doi codes are available at the Carbon Dioxide Information Analysis Center (http://cdiac.ornl.gov/oceans/GLODAPv2/). This site also provides access to the calibrated data product, which is provided as a single global file or four regional ones – the Arctic, Atlantic, Indian, and Pacific oceans – under the doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2. The product files also include significant ancillary and approximated data. These were obtained by interpolation of, or calculation from, measured data. This paper documents the GLODAPv2 methods and products and includes a broad overview of the secondary quality control results. The magnitude of and reasoning behind each adjustment is available on a per-cruise and per-variable basis in the online Adjustment Table.

A new global interior ocean mapped climatology: the 1° ×  1° GLODAP version 2

Abstract. We present a mapped climatology (GLODAPv2.2016b) of ocean biogeochemical variables based on the new GLODAP version 2 data product (Olsen et al., 2016; Key et al., 2015), which covers all ocean basins over the years 1972 to 2013. The quality-controlled and internally consistent GLODAPv2 was used to create global 1°  ×  1° mapped climatologies of salinity, temperature, oxygen, nitrate, phosphate, silicate, total dissolved inorganic carbon (TCO2), total alkalinity (TAlk), pH, and CaCO3 saturation states using the Data-Interpolating Variational Analysis (DIVA) mapping method. Improving on maps based on an earlier but similar dataset, GLODAPv1.1, this climatology also covers the Arctic Ocean. Climatologies were created for 33 standard depth surfaces. The conceivably confounding temporal trends in TCO2 and pH due to anthropogenic influence were removed prior to mapping by normalizing these data to the year 2002 using first-order calculations of anthropogenic carbon accumulation rates. We additionally provide maps of accumulated anthropogenic carbon in the year 2002 and of preindustrial TCO2. For all parameters, all data from the full 1972–2013 period were used, including data that did not receive full secondary quality control. The GLODAPv2.2016b global 1°  ×  1° mapped climatologies, including error fields and ancillary information, are available at the GLODAPv2 web page at the Carbon Dioxide Information Analysis Center (CDIAC; doi:10.3334/CDIAC/OTG.NDP093_GLODAPv2).

Global Carbon Budget 2015

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere 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 a 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 as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, 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 CO2 concentration 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 SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). 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 ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from 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 Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015).

A toolbox for secondary quality control on ocean chemistry and hydrographic data

High quality, reference measurements of chemical and physical properties of seawater are of great importance for a wide research community, including the need to validate models and attempts to quantify spatial and temporal variability. Whereas data precision has been improved by technological advances, the data accuracy has improved mainly by the use of certified reference materials (CRMs). However, since CRMs are not available for all variables, and use of CRMs does not guarantee bias-free data, we here present a recently developed Matlab toolbox for performing so-called secondary quality control on oceanographic data by the use of crossover analysis. This method and how it has been implemented in this toolbox is described in detail. This toolbox is developed mainly for use by sea-going scientists as a tool for quickly assessing possible bias in the measurements that can—hopefully—be remedied during the expedition, but also for possible post-cruise adjustment of data to be consistent with previous measurements in the region. The toolbox, and reference data, can be downloaded from the Carbon Dioxide Information Analysis Center (CDIAC): http://cdiac.ornl.gov/ftp/oceans/2nd_QC_Tool_V2/.

Global carbon budget 2014

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere 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 a 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, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (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 CO2 concentration 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 SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover-change (some including nitrogen–carbon interactions). 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 ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004–2013), EFF was 8.9 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 2.9 ± 0.8 GtC yr−1. For year 2013 alone, EFF grew to 9.9 ± 0.5 GtC yr−1, 2.3% above 2012, continuing the growth trend in these emissions, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 5.4 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 2.5 ± 0.9 GtC yr−1. GATM was high in 2013, reflecting a steady increase in EFF and smaller and opposite changes between SOCEAN and SLAND compared to the past decade (2004–2013). The global atmospheric CO2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that EFF will increase by 2.5% (1.3–3.5%) to 10.1 ± 0.6 GtC in 2014 (37.0 ± 2.2 GtCO2 yr−1), 65% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of EFF and assumed constant ELUC for 2014, cumulative emissions of CO2 will reach about 545 ± 55 GtC (2000 ± 200 GtCO2) for 1870–2014, about 75% from EFF and 25% from ELUC. This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Quéré et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014).

Climate change and respiratory health.

To discuss the nature of climate change and both its immediate and long-term effects on human respiratory health. This review is based on information from a presentation of the American College of Chest Physicians course on Occupational and Environmental Lung Disease held in Toronto, Canada, June 2013. It is supplemented by a PubMed search for climate change, global warming, respiratory tract diseases, and respiratory health. It is also supplemented by a search of Web sites including the Environmental Protection Agency, National Oceanic and Atmospheric Administration, World Meteorological Association, National Snow and Ice Data Center, Carbon Dioxide Information Analysis Center, Inter-Governmental Panel on Climate Change, and the World Health Organization. Health effects of climate change include an increase in the prevalence of certain respiratory diseases, exacerbations of chronic lung disease, premature mortality, allergic responses, and declines in lung function. Climate change, mediated by greenhouse gases, causes adverse health effects to the most vulnerable patient populations-the elderly, children, and those in distressed socioeconomic strata.

Global carbon budget 2013

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere 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 a 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, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, 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 CO2 concentration 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 SOCEAN is evaluated for the first time in this budget with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2 and land cover change (some including nitrogen–carbon interactions). All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2003–2012), EFF was 8.6 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.5 ± 0.5 GtC yr−1, and SLAND 2.8 ± 0.8 GtC yr−1. For year 2012 alone, EFF grew to 9.7 ± 0.5 GtC yr−1, 2.2% above 2011, reflecting a continued growing trend in these emissions, GATM was 5.1 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and assuming an ELUC of 1.0 ± 0.5 GtC yr−1 (based on the 2001–2010 average), SLAND was 2.7 ± 0.9 GtC yr−1. GATM was high in 2012 compared to the 2003–2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52 ± 0.10 ppm averaged over 2012. We estimate that EFF will increase by 2.1% (1.1–3.1%) to 9.9 ± 0.5 GtC in 2013, 61% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the economy. With this projection, cumulative emissions of CO2 will reach about 535 ± 55 GtC for 1870–2013, about 70% from EFF (390 ± 20 GtC) and 30% from ELUC (145 ± 50 GtC). This paper also documents any changes in the methods and data sets used in this new carbon budget from previous budgets (Le Quéré et al., 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2013_V2.3).