We have updated the Regional Emission inventory in ASia (REAS) as version 2.1. REAS 2.1 includes most major air pollutants and greenhouse gases from each year during 2000 and 2008 and following areas ...of Asia: East, Southeast, South, and Central Asia and the Asian part of Russia. Emissions are estimated for each country and region using updated activity data and parameters. Monthly gridded data with a 0.25° × 0.25° resolution are also provided. Asian emissions for each species in 2008 are as follows (with their growth rate from 2000 to 2008): 56.9 Tg (+34%) for SO2, 53.9 Tg (+54%) for NOx, 359.5 Tg (+34%) for CO, 68.5 Tg (+46%) for non-methane volatile organic compounds, 32.8 Tg (+17%) for NH3, 36.4 Tg (+45%) for PM10, 24.7 Tg (+42%) for PM2.5, 3.03 Tg (+35%) for black carbon, 7.72 Tg (+21%) for organic carbon, 182.2 Tg (+32%) for CH4, 5.80 Tg (+18%) for N2O, and 16.0 Pg (+57%) for CO2. By country, China and India were respectively the largest and second largest contributors to Asian emissions. Both countries also had higher growth rates in emissions than others because of their continuous increases in energy consumption, industrial activities, and infrastructure development. In China, emission mitigation measures have been implemented gradually. Emissions of SO2 in China increased from 2000 to 2006 and then began to decrease as flue-gas desulphurization was installed to large power plants. On the other hand, emissions of air pollutants in total East Asia except for China decreased from 2000 to 2008 owing to lower economic growth rates and more effective emission regulations in Japan, South Korea, and Taiwan. Emissions from other regions generally increased from 2000 to 2008, although their relative shares of total Asian emissions are smaller than those of China and India. Tables of annual emissions by country and region broken down by sub-sector and fuel type, and monthly gridded emission data with a resolution of 0.25° × 0.25° for the major sectors are available from the following URL: http://www.nies.go.jp/REAS/.
The mandate of the Task Force Hemispheric Transport of Air Pollution (TF HTAP) under the Convention on Long-Range Transboundary Air Pollution (CLRTAP) is to improve the scientific understanding of ...the intercontinental air pollution transport, to quantify impacts on human health, vegetation and climate, to identify emission mitigation options across the regions of the Northern Hemisphere, and to guide future policies on these aspects. The harmonization and improvement of regional emission inventories is imperative to obtain consolidated estimates on the formation of global-scale air pollution. An emissions data set has been constructed using regional emission grid maps (annual and monthly) for SO2, NOx, CO, NMVOC, NH3, PM10, PM2.5, BC and OC for the years 2008 and 2010, with the purpose of providing consistent information to global and regional scale modelling efforts. This compilation of different regional gridded inventories - including that of the Environmental Protection Agency (EPA) for USA, the EPA and Environment Canada (for Canada), the European Monitoring and Evaluation Programme (EMEP) and Netherlands Organisation for Applied Scientific Research (TNO) for Europe, and the Model Inter-comparison Study for Asia (MICS-Asia III) for China, India and other Asian countries - was gap-filled with the emission grid maps of the Emissions Database for Global Atmospheric Research (EDGARv4.3) for the rest of the world (mainly South America, Africa, Russia and Oceania). Emissions from seven main categories of human activities (power, industry, residential, agriculture, ground transport, aviation and shipping) were estimated and spatially distributed on a common grid of 0.1 degree 0.1 degree longitude-latitude, to yield monthly, global, sector-specific grid maps for each substance and year. The HTAP_v2.2 air pollutant grid maps are considered to combine latest available regional information within a complete global data set. The disaggregation by sectors, high spatial and temporal resolution and detailed information on the data sources and references used will provide the user the required transparency. Because HTAP_v2.2 contains primarily official and/or widely used regional emission grid maps, it can be recommended as a global baseline emission inventory, which is regionally accepted as a reference and from which different scenarios assessing emission reduction policies at a global scale could start. An analysis of country-specific implied emission factors shows a large difference between industrialised countries and developing countries for acidifying gaseous air pollutant emissions (SO2 and NOx) from the energy and industry sectors. This is not observed for the particulate matter emissions (PM10, PM2.5), which show large differences between countries in the residential sector instead. The per capita emissions of all world countries, classified from low to high income, reveal an increase in level and in variation for gaseous acidifying pollutants, but not for aerosols. For aerosols, an opposite trend is apparent with higher per capita emissions of particulate matter for low income countries.
We developed a new emission inventory for Asia (Regional Emission inventory in ASia (REAS) Version 1.1) for the period 1980–2020. REAS is the first inventory to integrate historical, present, and ...future emissions in Asia on the basis of a consistent methodology. We present here emissions in 2000, historical emissions for 1980–2003, and projected emissions for 2010 and 2020 of SO2, NOx, CO, NMVOC, black carbon (BC), and organic carbon (OC) from fuel combustion and industrial sources. Total energy consumption in Asia more than doubled between 1980 and 2003, causing a rapid growth in Asian emissions, by 28% for BC, 30% for OC, 64% for CO, 108% for NMVOC, 119% for SO2, and 176% for NOx. In particular, Chinese NOx emissions showed a marked increase of 280% over 1980 levels, and growth in emissions since 2000 has been extremely high. These increases in China were mainly caused by increases in coal combustion in the power plants and industrial sectors. NMVOC emissions also rapidly increased because of growth in the use of automobiles, solvents, and paints. By contrast, BC, OC, and CO emissions in China showed decreasing trends from 1996 to 2000 because of a reduction in the use of biofuels and coal in the domestic and industry sectors. However, since 2000, Chinese emissions of these species have begun to increase. Thus, the emissions of air pollutants in Asian countries (especially China) showed large temporal variations from 1980–2003. Future emissions in 2010 and 2020 in Asian countries were projected by emission scenarios and from emissions in 2000. For China, we developed three emission scenarios: PSC (policy success case), REF (reference case), and PFC (policy failure case). In the 2020 REF scenario, Asian total emissions of SO2, NOx, and NMVOC were projected to increase substantially by 22%, 44%, and 99%, respectively, over 2000 levels. The 2020 REF scenario showed a modest increase in CO (12%), a lesser increase in BC (1%), and a slight decrease in OC (−5%) compared with 2000 levels. However, it should be noted that Asian total emissions are strongly influenced by the emission scenarios for China.
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.
This study compares recent CO, NOx, NMVOC, SO2, BC, and OC anthropogenic emissions from several state‐of‐the‐art top‐down estimates to global and regional bottom‐up inventories and projections from ...five Shared Socioeconomic Pathways (SSPs) in several regions. Results show that top‐down emissions derived in several recent studies exhibit similar uncertainty as bottom‐up inventories in some regions for certain species and even less in the case of Chinese CO emissions. In general, the largest discrepancies are found outside of regions such as the United States, Europe, and Japan where the most accurate and detailed information on emissions is available. In some regions such as China, which has recently undergone dynamical economic growth and changes in air quality regulations, the top‐down estimates better capture recent emission trends than global bottom‐up inventories. These results show the potential of top‐down estimates to complement bottom‐up inventories and to aide in the development of emission scenarios, particularly in regions where global inventories lack the necessary up‐to‐date and accurate information regarding regional activity data and emission factors such as Africa and India. Areas of future work aimed at quantifying and reducing uncertainty are also highlighted. A regional comparison of recent CO and NOx trends in the five SSPs indicate that SSP126, a strong pollution control scenario, best represents the trends from the top‐down and regional bottom‐up inventories in the United States, Europe, and China, while SSP460, a low‐pollution control scenario, lies closest to actual trends in West Africa. This analysis can be useful for air quality forecasting and near‐future pollution control/mitigation policy studies.
Key Points
Top‐down emissions from several recent studies are within the range of bottom‐up inventories and exhibit a similar level of uncertainty for some regions and species
In China, the United States, and Europe emission trends in the last decade from SSP126 match most closely actual trends from bottom‐up and top‐down estimates
In Western Africa and India recent emission trends from low pollution control scenarios (SSP460 and SSP370, respectively) match most closely actual trends
Triggered by recent developments from laboratory and field studies regarding major NOx sink pathways in the troposphere, this study evaluates the influence of chemical uncertainties in NOx sinks for ...global NOx distributions calculated by the IMAGESv2 chemistry-transport model, and quantifies their significance for top-down NOx emission estimates. Our study focuses on five key chemical parameters believed to be of primary importance, more specifically, the rate of the reaction of NO2 with OH radicals, the newly identified HNO3-forming channel in the reaction of NO with HO2, the reactive uptake of N2O5 and HO2 by aerosols, and the regeneration of OH in the oxidation of isoprene. Sensitivity simulations are performed to estimate the impact of each source of uncertainty. The model calculations show that, although the NO2+OH reaction is the largest NOx sink globally accounting for ca. 60% of the total sink, the reactions contributing the most to the overall uncertainty are the formation of HNO3 in NO+HO2, leading to NOx column changes exceeding a factor of two over tropical regions, and the uptake of HO2 by aqueous aerosols, in particular over East and South Asia. Emission inversion experiments are carried out using model settings which either minimise (MINLOSS) or maximise (MAXLOSS) the total NOx sink, both constrained by one year of OMI NO2 column data from the DOMINO v2 KNMI algorithm. The choice of the model setup is found to have a major impact on the top-down flux estimates, with 75% higher emissions for MAXLOSS compared to the MINLOSS inversion globally. Even larger departures are found for soil NO (factor of 2) and lightning (1.8). The global anthropogenic source is better constrained (factor of 1.57) than the natural sources, except over South Asia where the combined uncertainty primarily associated to the NO+HO2 reaction in summer and HO2 uptake by aerosol in winter lead to top-down emission differences exceeding a factor of 2. Evaluation of the emission optimisation is performed against independent satellite observations from the SCIAMACHY sensor, with airborne NO2 measurements of the INTEX-A and INTEX-B campaigns, as well as with two new bottom-up inventories of anthropogenic emissions in Asia (REASv2) and China (MEIC). Neither the MINLOSS nor the MAXLOSS setup succeeds in providing the best possible match with all independent datasets. Whereas the minimum sink assumption leads to better agreement with aircraft NO2 profile measurements, consistent with the results of a previous analysis (Henderson et al., 2012), the same assumption leads to unrealistic features in the inferred distribution of emissions over China. Clearly, although our study addresses an important issue which was largely overlooked in previous inversion exercises, and demonstrates the strong influence of NOx loss uncertainties on top-down emission fluxes, additional processes need to be considered which could also influence the inferred source.
To evaluate temporal variations in nitrogen wet deposition across Japan during 1989–2008, we analyzed results of a chemical transport model (the Models‐3 Community Multiscale Air Quality) and ...observational data. The model successfully reproduced the general patterns of spatial and temporal variations of observed NO3− wet deposition rates. Wet deposition rates of NO3− across Japan increased during 1989–2008, with rates of increase of 2–5%/yr. Sensitivity simulations indicated that the increase of NO3− wet deposition rates was mostly (61%–94%) explained by the increased emissions of atmospheric pollutants in China. Contributions of China's emissions increased from 29%–35% during 1989–1993 to 43%–61% during 2004–2008, suggesting that transboundary pollution had a large impact on NO3− wet deposition in Japan. The contribution of observed NO3− to total nitrogen wet deposition (i.e., NO3− + NH4+) increased in southwestern Japan, and currently, NO3− and NH4+ make similar contributions to nitrogen wet deposition across Japan. Interannual variation of NO3− wet deposition was further evaluated using a meteorological index, area‐weighted surface pressure anomaly (ASPA). When ASPA was negative, air masses from the Asian continent were more directly transported to Japan, and NO3− concentrations across Japan became high. Thus, anomalies of NO3− concentrations were negatively correlated with ASPA. Anomalies of NO3− wet deposition rates, however, showed a weak positive correlation with ASPA, reflecting a positive correlation between anomalies in precipitation rates and ASPA. This result strongly suggests that precipitation patterns have a large impact on the interannual variation of NO3− wet deposition across Japan.
Key Points
Evaluation of temporal variations in nitrogen wet deposition across Japan
The number of vehicles in China has been increasing rapidly. We evaluate the impact of current and possible future vehicle emissions from China on Asian air quality. We modify the Regional Emission ...Inventory in Asia (REAS) for China's road transport sector in 2000 using updated Chinese data for the number of vehicles, annual mileage, and emission factors. We develop two scenarios for 2020: a scenario where emission factors remain the same as they were in 2000 (No-Policy, NoPol), and a scenario where Euro 3 vehicle emission standards are applied to all vehicles (except motorcycles and rural vehicles). The Euro 3 scenario is an approximation of what may be the case in 2020 as, starting in 2008, all new vehicles in China (except motorcycles) were required to meet the Euro 3 emission standards. Using the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem), we examine the regional air quality response to China's vehicle emissions in 2000 and in 2020 for the NoPol and Euro 3 scenarios. We evaluate the 2000 model results with observations in Japan, China, Korea, and Russia. Under NoPol in 2020, emissions of carbon monoxide (CO), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs), black carbon (BC), and organic carbon (OC) from China's vehicles more than double compared to the 2000 baseline. If all vehicles meet the Euro 3 regulations in 2020, however, these emissions are reduced by more than 50% relative to NoPol. The implementation of stringent vehicle emission standards leads to a large, simultaneous reduction of the surface ozone (O3) mixing ratios and particulate matter (PM2.5) concentrations. In the Euro 3 scenario, surface O3 is reduced by more than 10 ppbv and surface PM2.5 is reduced by more than 10 μg m−3 relative to NoPol in Northeast China in all seasons. In spring, surface O3 mixing ratios and PM2.5 concentrations in neighboring countries are also reduced by more than 3 ppbv and 1 μg m−3, respectively. We find that effective regulation of China's road transport sector will be of significant benefit for air quality both within China and across East Asia as well.
We present a new global three‐dimensional chemical model for the troposphere, named chemical atmospheric general circulation model (AGCM) for study of atmospheric environment and radiative forcing ...(CHASER). This model, developed in the framework of the Center for Climate System Research/National Institute for Environment Studies (CCSR/NIES) AGCM, is aimed to study tropospheric photochemistry and its influences on climate. The chemical component of the model simulates the O3‐HOx‐NOx‐CH4‐CO photochemical system and oxidation of nonmethane hydrocarbons through 88 chemical and 25 photolytic reactions with 47 chemical species in its present configuration. The model includes emission sources, dry and wet deposition, as well as chemical transformations. Meteorological processes such as transport due to advection, convection, and other subgrid‐scale mixing are simulated “on‐line” by the dynamical component of the CCSR/NIES AGCM. A detailed evaluation of the model results is presented in a companion paper Sudo et al., 2002. An evaluation of the transport scheme adopted in the model suggests that the model is capable of simulating transport associated with convection and boundary layer mixing as well as large‐scale advection. The model capability to simulate dry and wet deposition was also evaluated by conducting a simulation of atmospheric lead. The simulated lead distributions are consistent with those observed at the surface, showing the validity of the deposition parameterization adopted in the model.
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.
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