Do emissions and income have a common trend? A country-specific, time-series, global analysis, 1970-2008

This paper uses Vector Autoregressions that allow for nonstationarity and cointegration to investigate the dynamic relation between income and emissions in the period 1970-2008, for all world countries. We consider three emissions compounds, namely CO2, SO2 and a composite global warming index (GWP100). These emissions include energy-related activities with a share varying from 60% (GWP100) to almost 90% (SO2). For all chemical compounds, it is found that for over two thirds of cases income and emissions are driven by unrelated random walks with drift, at 5% significance level. For one quarter of the cases the variables are found to be driven by a common random walk with drift. Finally, for the remaining 4.5% of cases the variables are trend-stationary. Tests of Granger-causality show evidence of both directions of causality. For the case of unrelated stochastic trends, one finds a predominance of emissions causing income (in growth rates), which accords with a production-function rather than with a consumption-function interpretation of the emissions-income relation. The evidence challenges the main implications of the Environmental Kuznets Curve hypothesis, namely that the dominant direction of causality should be from income to emissions, and that for increasing levels of income, emissions should tend to decrease.Environmental Kuznets Curve; Emissions; Income; Cointegration; Common trends JEL Classification: Q53, Q54

Trends in global CO2 emissions: 2012 report

Global emissions of carbon dioxide (CO2) – the main cause of global warming – increased by 3% in 2011, reaching an all-time high of 34 billion tonnes in 2011. In 2011, China’s average per capita carbon dioxide (CO2) emissions increased by 9% to 7.2 tonnes CO2¬, whereas these emissions in the European Union declined by 4 % to 7.5 tonnes CO2, bringing for the first time Europe’s and China’s CO2 emissions on similar levels. China, the world’s most populous country, is now well within the 6 to 19 tonnes/person range spanned by the major industrialised countries. In comparison, in 2011, the United States was still one of the largest emitters of CO2, with 16.5 tonnes in per capita emissions, after a steep decline mainly caused by the recession in 2008-2009, high oil prices compared to low fuel taxes and an increased share of natural gas. This is one of the main findings of the annual report ‘Trends in global CO2 emissions’, released today by PBL Netherlands Environmental Assessment Agency and the European Commission’s Joint Research Centre (JRC).JRC.H.2-Air and Climat

Do emissions and income have a common trend? A country-specific, time-series, global analysis, 1970-2008

This paper analyzes the relation between income and emissions in the period 1970-2008, for all world countries. We consider time-series of CO2, SO2 and GWP100, and use Vector Autoregressive models that allow for nonstationarity and cointegration. At 5\% significance level, income and emissions are found to be driven by unrelated random walks with drift (respectively by a common random walk with drift) in about 70% (respectively 25%) of cases; in the remaining cases the variables are trend-stationary. Tests of Granger-causality show evidence of both directions of causality. For the case of unrelated stochastic trends, we almost never find income driving emissions, as predicted by a consumption-function interpretation. These causality results and the absence of a common trend challenge the main implications of the Environmental Kuznets Curve, namely that the dominant direction of causality should be from income to emissions, and that for increasing levels of income, emissions should tend to decrease.JRC.DDG.01-Econometrics and applied statistic

Do Emissions and Income Have a Common Trend? A Country-Specific, Time-Series, Global Analysis, 1970-2008

This paper uses Vector Autoregressions that allow for nonstationarity and cointegration to investigate the dynamic relation between income and emissions in the period 1970-2008, for all world countries. We consider three emission variables over the years 1970-2008 taken from the EDGARv4.2 database, namely CO2, SO2 and a composite global warming index (denoted GWP100) in which all Kyoto-protocol greenhouse chemical compounds are converted to units of tonnes CO2-equivalent with the standard UNFCCC 100-year weighting factors. EDGAR-v4.2 is the greenhouse gas and air pollutant emissions database that provides consistent global estimates and covers the full IPCC emissions category set. These emissions include energy-related activities with a share varying from 60% (GWP100) to almost 90% (SO2). For all chemical compounds, it is found that for over two thirds of cases income and emissions are driven by unrelated random walks with drift, at 5% significance level. For one quarter of the cases the variables are found to be driven by a common random walk with drift. Finally, for the remaining 4.5% of cases the variables are trend-stationary. Tests of Granger-causality show evidence of both directions of causality. For the case of unrelated stochastic trends, one finds a predominance of emissions causing income (in growth rates), which accords with a production-function rather than with a consumption-function interpretation of the emissions-income relation. The evidence challenges the main implications of the Environmental Kuznets Curve hypothesis, namely that the dominant direction of causality should be from income to emissions, and that for increasing levels of income, emissions should tend to decrease.JRC.H.2-Air and Climat

Towards a global EDGAR‐inventory of particulate matter with focus on elemental carbon

The Emissions Database for Global Atmospheric Research (EDGAR) provides technology based global anthropogenic emissions data of greenhouse gases and air pollutants by country and sector on a 0.1° x 0.1° spatial grid, on a timeline that ranges from 1970 to present days. As part of the constantly ongoing amendment and improvement of the database, a review of the available literature and emission inventory data has been conducted focusing on particulate emissions, with the aim of acquiring a comprehensive array of primary particle matter and carbonaceous particle emission factors (EF). It was found, that emission factor data from different studies show large variation for a given fuel and technology. Furthermore it is plausible that a certain literature or measurement describes emission factors better in the region where it is originating from. With this in mind, a comparison has been made between the available emission factor datasets in a number of different regions, focusing on the power generation sector. The aim of this experiment is to select the most appropriate EF dataset for a given region.JRC.H.2-Air and Climat

The Ultrasonic Densitometer Time Domain Response

Experiments were undertaken to investigate the feasibility of using propagating ultrasonic waves to find the speed of sound and density of solutions contained in opaque, sealed containers. A portable design is proposed which consists of 3 ultrasonic transducers aligned on a single plane along the surface of a tank. The content is then examined by measuring the time it takes for a signal to reflect off the back wall of the tank and return to another transducer. This time domain response approach delivered a very accurate analysis, with a low spread of results. This report demonstrates that by using this technique, very small changes in density can be observed. The final error in the density has been found to be less than 2%, which is adequate to reliably tell the difference between salt and fresh water.JRC.DG.E.9-Nuclear security (Ispra

On the CH4 and N2O emission inventory compiled by EDGAR and improved with the EPRTR data for the INGOS project

This report documents the EDGAR INGOS emission inventory for CH4 and N2O, as publicly made available on: http://edgar.jrc.ec.europa.eu/ingos/index.php?SECURE=123. The EDGAR INGOS CH4 and N2O emission inventory provides bottom‐up estimates of global anthropogenic CH4 and N2O emissions for the period 2000‐2010. The EDGAR InGOS product is an update of the EDGARv4.2FT2010 inventory, taking into account emissions reported as point sources by facilities under the European Pollutant Release and Transfer Register (EPRTR) for (1) power plants (N2O), (2) oil refineries (CH4 and N2O), (3) coal mining (CH4), (4) production of oil and gas (CH4), (5) chemicals production (inorganic, nitro‐fertilizers and other bulk chemicals) (N2O), industrial process and product use (N2O), (6) solid waste ‐ landfills (CH4), (7) industrial wastewater treatment (CH4 and N2O). In a first step gridmaps have been improved for the European region taking into account the geospatial data of the E‐PRTR database. In addition, for the last 4 years an option is given to select inventories solely based on officially reported emission data (for the categories covered by E‐PRTR), gapfilled with EDGARv4.2FT2010 for non‐reporting countries.JRC.H.2-Air and Climat

An approach with a Business-as-Usual scenario projection to 2020 for the Covenant of Mayors from the Eastern Partnership

The methodology for the Covenant of Mayors – East needed to be extended with a business-as-usual projection of the emissions for 2020, from which national coefficients for the previous years are derived. In this way, signatories will be able to do their emission inventories of the present situation, and estimate which their emissions in 2020 will be. Then they will commit to an emission reduction target based on their projections of emissions for 2020 following the business-as-usual scenario. The factors are country-specific, calculated both for CO2 and CO2eq (CO2, CH4, N2O using the GWP100metric) in order to allow signatories to choose the approach they prefer. Moreover an urban dimension is provided, providing a margin on the projections.JRC.H.2-Air and Climat