Search

We present a new data set of annual historical (1750–2014) anthropogenic chemically reactive gases (CO, CH4, NH3, NOx, SO2, NMVOCs), carbonaceous aerosols (black carbon – BC, and organic carbon – OC), and CO2 developed with the Community Emissions Data System (CEDS). We improve upon existing inventories with a more consistent and reproducible methodology applied to all emission species, updated emission factors, and recent estimates through 2014. The data system relies on existing energy consumption data sets and regional and country-specific inventories to produce trends over recent decades. All emission species are consistently estimated using the same activity data over all time periods. Emissions are provided on an annual basis at the level of country and sector and gridded with monthly seasonality. These estimates are comparable to, but generally slightly higher than, existing global inventories. Emissions over the most recent years are more uncertain, particularly in low- and middle-income regions where country-specific emission inventories are less available. Future work will involve refining and updating these emission estimates, estimating emissions' uncertainty, and publication of the system as open-source software.

We compare nine emission inventories of nitrogen oxides including four satellite-derived NOx inventories and the following bottom-up inventories for East Asia: REAS (Regional Emission inventory in ASia), MEIC (Multi-resolution Emission Inventory for China), CAPSS (Clean Air Policy Support System) and EDGAR (Emissions Database for Global Atmospheric Research). Two of the satellite-derived inventories are estimated by using the DECSO (Daily Emission derived Constrained by Satellite Observations) algorithm, which is based on an extended Kalman filter applied to observations from OMI or from GOME-2. The other two are derived with the EnKF algorithm, which is based on an ensemble Kalman filter applied to observations of multiple species using either the chemical transport model CHASER and MIROC-chem. The temporal behaviour and spatial distribution of the inventories are compared on a national and regional scale. A distinction is also made between urban and rural areas. The intercomparison of all inventories shows good agreement in total NOx emissions over mainland China, especially for trends, with an average bias of about 20 % for yearly emissions. All the inventories show the typical emission reduction of 10 % during the Chinese New Year and a peak in December. Satellite-derived approaches using OMI show a summer peak due to strong emissions from soil and biomass burning in this season. Biases in NOx emissions and uncertainties in temporal variability increase quickly when the spatial scale decreases. The analyses of the differences show the importance of using observations from multiple instruments and a high spatial resolution model for the satellite-derived inventories, while for bottom-up inventories, accurate emission factors and activity information are required. The advantage of the satellite-derived approach is that the emissions are soon available after observation, while the strength of the bottom-up inventories is that they include detailed information of emissions for each source category.

Anthropogenic air pollutant emissions have been increasing rapidly in China, leading to worsening air quality. Modelers use emissions inventories to represent the temporal and spatial distribution of these emissions needed to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates. Thus, assessing differences in these inventories is essential for the better understanding of air pollution over China. We compare five different emissions inventories estimating emissions of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter of 10 µm or less (PM10) from China. The emissions inventories analyzed in this paper include the Regional Emission inventory in ASia v2.1 (REAS), the Multi-resolution Emission Inventory for China (MEIC), the Emission Database for Global Atmospheric Research v4.2 (EDGAR), the inventory by Yu Zhao (ZHAO), and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008, during which Chinese economic activities more than doubled. In addition to national totals, we also analyzed emissions from four source sectors (industry, transport, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements exist among the five inventories at disaggregated levels. These disagreements lead to differences of 67 µg m−3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modeled regional concentrations in China. We also find that all the inventory emissions estimates create a volatile organic compound (VOC)-limited environment and MEIC emissions lead to much lower O3 mixing ratio in East and Central China compared to the simulations using REAS and EDGAR estimates, due to their low VOC emissions. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding effective mitigation measures for reducing national and regional air pollution in China.

The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO2. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.1 % for SO2, +19.2 % for NOx, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH3, −3.4 % for PM10, −1.6 % for PM2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO2. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.

Satellite observations of the tropospheric NO2 vertical column density (VCD) are closely correlated to, and thus can be used to estimate, surface NOx emissions. In this study, the NO2 VCD simulated by a regional chemical transport model with emissions data from the updated Regional Emission inventory in ASia (REAS) version 2.1 were validated through comparison with multisatellite observations during the period 2000–2010. Rapid growth in NO2 VCD (~11% year−1) driven by the expansion of anthropogenic NOx emissions was identified above the central eastern China (CEC) region, except for the period during the economic downturn. In contrast, slightly decreasing trends (~2% year−1) were identified above Japan accompanied by a decline in anthropogenic emissions. To systematically compare the modeled NO2 VCD, we estimated sampling bias and the effect of applying the averaging kernel information, with particular focus on the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. Using the updated REAS, the modeled NO2 VCD reasonably reproduced annual trends observed by multisatellites, suggesting that the rate of increase of NOx emissions estimated by the updated REAS inventory would be robust. Province-scale revision of emissions above CEC is needed to further refine emission inventories. Based on the close linear relationship between modeled and observed NO2 VCD and anthropogenic NOx emissions, NOx emissions in 2009 and 2010, which were not covered by the updated REAS inventory, were estimated. NOx emissions from anthropogenic sources in China in 2009 and 2010 were determined to be 26.4 and 28.5 Tg year−1, respectively, indicating that NOx emissions increased more than twofold between 2000 and 2010. This increase reflected the strong growth of anthropogenic emissions in China following the rapid recovery from the economic downturn from late 2008 until mid-2009. Our method consists of simple estimations from satellite observations and provides results that are consistent with the most recent inventory of emissions data for China.

Systematic analyses of interannual and seasonal variations of tropospheric NO2 vertical column densities (VCDs) based on GOME satellite data and the regional scale chemical transport model (CTM), Community Multi-scale Air Quality (CMAQ), are presented for the atmosphere over eastern Asia between 1996 and June 2003. A newly developed year-by-year emission inventory (REAS) was used in CMAQ. The horizontal distribution of annual averaged GOME NO2 VCDs generally agrees well with the CMAQ results. However, CMAQ/REAS results underestimate the GOME retrievals with factors of 2–4 over polluted industrial regions such as Central East China (CEC), a major part of Korea, Hong Kong, and central and western Japan. The most probable reasons for the underestimation typically over the CEC are accuracy of the basic energy statistic data, emission factors, and socio-economic data used for construction of emission inventory. For the Japan region, GOME and CMAQ NO2 data show reasonable agreement with respect to interannual variation and show no clear increasing trend. For CEC, GOME and CMAQ NO2 data indicate a very rapid increasing trend from 2000. Analyses of the seasonal cycle of NO2 VCDs show that GOME data have larger dips than CMAQ NO2 during February–April and September–November. Sensitivity experiments with fixed emission intensity reveal that the detection of emission trends from satellite in fall or winter has a larger error caused by the variability of meteorology. Examination during summer time and annual averaged NO2 VCDs are robust with respect to variability of meteorology and are therefore more suitable for analyses of emission trends. Analysis of recent trends of annual emissions in China shows that the increasing trends of 1996–1998 and 2000–2002 for GOME and CMAQ/REAS show good agreement, but the rate of increase by GOME is approximately 10–11% yr−1 after 2000; it is slightly steeper than CMAQ/REAS (8–9% yr−1). The greatest difference was apparent between the years 1998 and 2000: CMAQ/REAS only shows a few percentage points of increase, whereas GOME gives a greater than 8% yr−1 increase. The exact reason remains unclear, but the most likely explanation is that the emission trend based on the Chinese emission related statistics underestimates the rapid growth of emissions.