Regional Emission Inventory In Asia Research Articles

Modification of Hybrid Receptor Model for Atmospheric Fine Particles (PM2.5) in 2020 Daejeon, Korea, Using an ACERWT Model

Hybrid receptor models overestimate the contribution of background areas (no specific emission sources), like the Yellow Sea in Korea. This study aimed to improve model performances using Advanced Concentration Emission and Retention Time Weighted Trajectory (ACERWT). ACERWT was combined with a positive matrix factorization (PMF), back trajectory, and Regional Emission Inventory in Asia (REAS). The PMF receptor model used one year of data from Korea’s Central Air Environment Research Center. In the PMF receptor model, eight sources (dust/soil, secondary nitrate, biomass burning, vehicles, secondary sulfate, industry, coal combustion and sea salt) influenced PM2.5 pollution at the receptor site (Daejeon, Korea). Secondary sulfate was the most dominant source, followed by secondary nitrate and vehicle sources. ACERWT results showed high contributions from China, Japan, and Korean regions, while the contribution from the Yellow Sea was significantly lower. Several regions, such as the eastern and south-eastern areas of China, the southern area of Taiwan, the western area of Tokyo, and the central area of Korea, showed high contributions due to large-scale emission facilities and industrial complexes. In this study, the ACERWT model significantly improved its performance regarding regional contributions to PM2.5 pollution at the receptor site.

Combining the Emission Preprocessor HERMES with the Chemical Transport Model TM5-MP

Emission inventories (EIs) are vital for air quality modeling. Specific research goals often require modifying EIs from diverse data sources, demanding significant code development. In this study, we utilized and further developed the High Elective Resolution Modeling Emission System version three for Global and Regional domains (HERMESv3_gr). This user-friendly processing system was adapted for generating EIs compatible with the Chemistry Transport Model Tracel Model 5 Massive Parallel (TM5-MP). The results indicate that HERMESv3_gr is capable of generating EIs with negligible biases (10−7 relative differences) for TM5-MP, showcasing its effectiveness. We applied HERMESv3_gr to integrate the EI Regional Emission inventory in Asia (REAS) into the global EI Community Emission Data System (CEDS). Comparison of model results using CEDS alone and the integrated EI against measurement data for various pollutants globally revealed small improvements for carbon monoxide (1%) ethane (1–2%), and nitrogen oxide (2%) and larger for propane (5–7%). Ozone in the northern hemisphere improved by about 2% while in the southern hemisphere improvements of 5% could be observed. Our findings highlight the importance of carefully considering the effects of EI integration for accurate air quality modeling.

Evaluation of a highly condensed SAPRC chemical mechanism and two emission inventories for ozone source apportionment and emission control strategy assessments in China

The response of summertime O3 to changes in the nitrogen oxides (NOx) and volatile organic compounds (VOC) emissions, and contributions of different NOx and VOC sources to O3 in China are studied using a highly condensed photochemical mechanism in the Statewide Air Pollution Research Center (SAPRC) family (CS07A) and two popular anthropogenic emission inventories, the Multi-resolution Emission Inventory for China (MEIC) and Regional Emission inventory in ASia (REAS). Although CS07A predicts slightly lower O3 concentrations than the standard fix-parameter version of the SAPRC-11 mechanism, the two mechanisms predict almost identical relative responses to daily maximum 8-hour O3 (O3-8h) due to NOx and VOC emission reductions. A source-oriented version of the CS07A is applied to determine source contributions of NOx and VOCs to O3 using MEIC and REAS. The two inventories lead to similar model performance of O3, with MEIC predicting higher O3 in Beijing and Shanghai, especially on high O3 days. Source apportionment results show that industry and transportation are the top two contributors to non-background O3 for both inventories, followed by power and biogenic emissions. In general, the two inventories lead to similar source contribution estimations to O3 attributable to NOx. However, their estimations of relative contributions to VOC-related O3 differ for the industrial and transportation sectors. Differences in the source apportionment results are more significant in some urban areas, although both emissions capture the spatial variations in the source contributions. Our results suggest that future emission control policies should be assessed using multiple emission inventories, and the condensed CS07A is suitable for policy applications when a large number of simulations are needed.

First Concurrent Observations of NO2 and CO2 From Power Plant Plumes by Airborne Remote Sensing

AbstractCombined NO2 and CO2 observations have the potential to constrain the identification of the locations and strength of urban CO2 emissions, in particular, point sources such as power plants. We report the first results of airborne spectroscopic NO2 and CO2 observations over an urban area in Japan in February 2018. Inversed emission rates of two stacks of the coal‐fired power plant for CO2 showed relatively good agreement with those estimated by a bottom‐up inventory—the Regional Emission inventory in ASia (REAS) v3.1—within −7% to 40% because the plume shapes were well identified due to constraint by NO2 measurements. The estimated NOx emission rates showed discrepancies more than 80% with those estimated by the REAS v3.1, mainly due to the uncertainties in activity data and emission factors, or in the greatly varying NO/NO2 ratios in fresh plumes, which warrant further investigations when estimating NOx emissions from satellite NO2 observations on km‐scales.

Long-term historical trends in air pollutant emissions in Asia: Regional Emission inventory in ASia (REAS) version 3

Abstract. A long-term historical emission inventory of air and climate pollutants in East, Southeast, and South Asia during 1950–2015 was developed as the Regional Emission inventory in ASia version 3 (REASv3). REASv3 provides details of emissions from major anthropogenic sources for each country and its sub-regions and also provides monthly gridded data with 0.25∘ × 0.25∘ resolution. The average total emissions in Asia during 1950–1955 and during 2010–2015 (growth rates in these 60 years estimated from the two averages) are as follows: SO2: 3.2 Tg, 42.4 Tg (13.1); NOx: 1.6 Tg, 47.3 Tg (29.1); CO: 56.1 Tg, 303 Tg (5.4); non-methane volatile organic compounds: 7.0 Tg, 57.8 Tg (8.3); NH3: 8.0 Tg, 31.3 Tg (3.9); CO2: 1.1 Pg, 18.6 Pg (16.5) (CO2 excluding biofuel combustion 0.3 Pg, 16.8 Pg (48.6)); PM10: 5.9 Tg, 30.2 Tg (5.1); PM2.5: 4.6 Tg, 21.3 Tg (4.6); black carbon: 0.69 Tg, 3.2 Tg (4.7); and organic carbon: 2.5 Tg, 6.6 Tg (2.7). Clearly, all the air pollutant emissions in Asia increased significantly during these 6 decades, but situations were different among countries and regions. Due to China's rapid economic growth in recent years, its relative contribution to emissions in Asia has been the largest. However, most pollutant species reached their peaks by 2015, and the growth rates of other species were found to be reduced or almost zero. On the other hand, air pollutant emissions from India showed an almost continuous increasing trend. As a result, the relative ratio of emissions of India to that of Asia has increased recently. The trend observed in Japan was different from the rest of Asia. In Japan, emissions increased rapidly during the 1950s–1970s, which reflected the economic situation of the period; however, most emissions decreased from their peak values, which were approximately 40 years ago, due to the introduction of control measures for air pollution. Similar features were found in the Republic of Korea and Taiwan. In the case of other Asian countries, air pollutant emissions generally showed an increase along with economic growth and motorization. Trends and spatial distribution of air pollutants in Asia are becoming complicated. Data sets of REASv3, including table of emissions by countries and sub-regions for major sectors and fuel types, and monthly gridded data with 0.25∘ × 0.25∘ resolution for major source categories are available through the following URL: https://www.nies.go.jp/REAS/index.html (last access: 31 October 2020).

Development of the CREATE Inventory in Support of Integrated Climate and Air Quality Modeling for Asia

A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: (1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and (2) a base-year, natural emissions inventory for biogenic and biomass burning. For (1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO2, NOx, CO, non-methane volatile organic compounds (NMVOC), NH3, OC, BC, PM10, PM2.5, CO2, CH4, N2O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.

Rapid reduction in black carbon emissions from China: evidence from 2009–2019 observations on Fukue Island, Japan

Abstract. A long-term, robust observational record of atmospheric black carbon (BC) concentrations at Fukue Island for 2009–2019 was produced by unifying the data from a continuous soot monitoring system (COSMOS) and a Multi-Angle Absorption Photometer (MAAP). This record was then used to analyze emission trends from China. We identified a rapid reduction in BC concentrations of (-5.8±1.5) % yr−1 or −48 % from 2010 to 2018. We concluded that an emission change of (-5.3±0.7) % yr−1, related to changes in China of as much as −4.6 % yr−1, was the main underlying driver. This evaluation was made after correcting for the interannual meteorological variability (IAV) by using the regional atmospheric chemistry model simulations from the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models (collectively WRF/CMAQ) with the constant emissions. This resolves the current fundamental disagreements about the sign of the BC emissions trend from China over the past decade as assessed from bottom-up emission inventories. Our analysis supports inventories reflecting the governmental clean air actions after 2010 (e.g., MEIC1.3, ECLIPSE versions 5a and 6b, and the Regional Emission inventory in ASia (REAS) version 3.1) and recommends revisions to those that do not (e.g., Community Emissions Data System – CEDS). Our estimated emission trends were fairly uniform across seasons but diverse among air mass origins. Stronger BC reductions, accompanied by a reduction in carbon monoxide (CO) emissions, occurred in regions of south-central East China, while weaker BC reductions occurred in north-central East China and northeastern China. Prior to 2017, the BC and CO emissions trends were both unexpectedly positive in northeastern China during winter months, which possibly influenced the climate at higher latitudes. The pace of the estimated emissions reduction over China surpasses the Shared Socioeconomic Pathways (SSPs with reference to SSP1, specifically) scenarios for 2015–2030, which suggests highly successful emission control policies. At Fukue Island, the BC fraction of fine particulate matter (PM2.5) also steadily decreased over the last decade. This suggests that reductions in BC emissions started without significant delay when compared to other pollutants such as NOx and SO2, which are among the key precursors of scattering PM2.5.

Regional variability in black carbon and carbon monoxide ratio from long-term observations over East Asia: assessment of representativeness for black carbon (BC) and carbon monoxide (CO) emission inventories

Abstract. The black carbon (BC) and carbon monoxide (CO) emission ratios were estimated and compiled from long-term, harmonized observations of the ΔBC∕ΔCO ratios under conditions unaffected by wet deposition at four sites in East Asia, including two sites in South Korea (Baengnyeong and Gosan) and two sites in Japan (Noto and Fukuoka). Extended spatio-temporal coverage enabled estimation of the full seasonality and elucidation of the emission ratio in North Korea for the first time. The estimated ratios were used to validate the Regional Emission inventory in ASia (REAS) version 2.1 based on six study domains (“East China”, “North China”, “Northeast China”, South Korea, North Korea, and Japan). We found that the ΔBC∕ΔCO ratios from four sites converged into a narrow range (6.2–7.9 ng m−3 ppb−1), suggesting consistency in the results from independent observations and similarity in source profiles over the regions. The BC∕CO ratios from the REAS emission inventory (7.7 ng m−3 ppb−1 for East China – 23.2 ng m−3 ppb−1 for South Korea) were overestimated by factors of 1.1 for East China to 3.0 for South Korea, whereas the ratio for North Korea (3.7 ng m−3 ppb−1 from REAS) was underestimated by a factor of 2.0, most likely due to inaccurate emissions from the road transportation sector. Seasonal variation in the BC∕CO ratio from REAS was found to be the highest in winter (China and North Korea) or summer (South Korea and Japan), whereas the measured ΔBC∕ΔCO ratio was the highest in spring in all source regions, indicating the need for further characterization of the seasonality when creating a bottom-up emission inventory. At levels of administrative districts, overestimation in Seoul, the southwestern regions of South Korea, and Northeast China was noticeable, and underestimation was mainly observed in the western regions in North Korea, including Pyongyang. These diagnoses are useful for identifying regions where revisions in the inventory are necessary, providing guidance for the refinement of BC and CO emission rate estimates over East Asia.

Intercomparison of NO<sub><i>x</i></sub> emission inventories over East Asia

Abstract. 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.

Temporal characteristics of atmospheric ammonia and nitrogen dioxide over China based on emission data, satellite observations and atmospheric transport modeling since 1980

Abstract. China is experiencing intense air pollution caused in large part by anthropogenic emissions of reactive nitrogen (Nr). Atmospheric ammonia (NH3) and nitrogen dioxide (NO2) are the most important precursors for Nr compounds (including N2O5, HNO3, HONO and particulate NO3− and NH4+) in the atmosphere. Understanding the changes in NH3 and NO2 has important implications for the regulation of anthropogenic Nr emissions and is a requirement for assessing the consequence of environmental impacts. We conducted the temporal trend analysis of atmospheric NH3 and NO2 on a national scale since 1980 based on emission data (during 1980–2010), satellite observation (for NH3 since 2008 and for NO2 since 2005) and atmospheric chemistry transport modeling (during 2008–2015).Based on the emission data, during 1980–2010, significant continuous increasing trends in both NH3 and NOx were observed in REAS (Regional Emission inventory in Asia, for NH3 0.17 and for NOx 0.16 kg N ha−1 yr−2) and EDGAR (Emissions Database for Global Atmospheric Research, for NH3 0.24 and for NOx 0.17 kg N ha−1 yr−2) over China. Based on the satellite data and atmospheric chemistry transport model (CTM) MOZART-4 (Model for Ozone and Related chemical Tracers, version 4), the NO2 columns over China increased significantly from 2005 to 2011 and then decreased significantly from 2011 to 2015; the satellite-retrieved NH3 columns from 2008 to 2014 increased at a rate of 2.37 % yr−1. The decrease in NO2 columns since 2011 may result from more stringent strategies taken to control NOx emissions during the 12th Five Year Plan, while no control policy has focused on NH3 emissions. Our findings provided an overall insight into the temporal trends of both NO2 and NH3 since 1980 based on emission data, satellite observations and atmospheric transport modeling. These findings can provide a scientific background for policy makers that are attempting to control atmospheric pollution in China. Moreover, the multiple datasets used in this study have implications for estimating long-term Nr deposition datasets to assess its impact on soil, forest, water and greenhouse balance.

Long-term observations of black carbon mass concentrations at Fukue Island, western Japan, during 2009–2015: constraining wet removal rates and emission strengths from East Asia

Abstract. Long-term (2009–2015) observations of atmospheric black carbon (BC) mass concentrations were performed using a continuous soot-monitoring system (COSMOS) at Fukue Island, western Japan, to provide information on wet removal rate constraints and the emission strengths of important source regions in East Asia (China and others). The annual average mass concentration was 0.36 µg m−3, with distinct seasonality; high concentrations were recorded during autumn, winter, and spring and were caused by Asian continental outflows, which reached Fukue Island in 6–46 h. The observed data were categorized into two classes, i.e., with and without a wet removal effect, using the accumulated precipitation along a backward trajectory (APT) for the last 3 days as an index. Statistical analysis of the observed ΔBC ∕ ΔCO ratios was performed to obtain information on the emission ratios (from data with zero APT only) and wet removal rates (including data with nonzero APTs). The estimated emission ratios (5.2–6.9 ng m−3 ppb−1) varied over the six air mass origin areas; the higher ratios for south-central East China (30–35° N) than for north-central East China (35–40° N) indicated the relative importance of domestic emissions and/or biomass burning sectors. The significantly higher BC ∕ CO emission ratios adopted in the bottom-up Regional Emission inventory in Asia (REAS) version 2 (8.3–23 ng m−3 ppb−1) over central East China and Korea needed to be reduced at least by factors of 1.3 and 2.8 for central East China and Korea, respectively, but the ratio for Japan was reasonable. The wintertime enhancement of the BC emission from China, predicted by REAS2, was verified for air masses from south-central East China but not for those from north-central East China. Wet removal of BC was clearly identified as a decrease in the ΔBC ∕ ΔCO ratio against APT. The transport efficiency (TE), defined as the ratio of the ΔBC ∕ ΔCO ratio with precipitation to that without precipitation, was fitted reasonably well by a stretched exponential decay curve against APT; a single set of fitting parameters was sufficient to represent the results for air masses originating from different areas. An accumulated precipitation of 25.5 ± 6.1 mm reduced the TE to 1∕e. BC-containing particles traveling to Fukue must have already been converted from hydrophobic to hydrophilic particles, because the behavior of TE against APT was similar to that of PM2.5, the major components of which are hydrophilic. Wet loss of BC greatly influenced interannual variations in the ΔBC ∕ ΔCO ratios and BC mass concentrations. This long-term data set will provide a benchmark for testing chemical transport/climate model simulations covering East Asia.

Anthropogenic emissions and space-borne observations of carbon monoxide over South Asia

The focus of this study is to understand anthropogenic emissions, spatiotemporal variability and trends of carbon monoxide (CO) over South Asia by using datasets from MACCity (Monitoring Atmospheric Composition and Climate, MACC and megaCITY – Zoom for the Environment, CityZEN), REAS (Regional Emission inventory in Asia), AIRS (Atmospheric Infrared Sounder) and SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY). MACCity anthropogenic emissions show an overall increase of 16.5% during 2000–2010. Elevated levels of MACCity CO are found in Indo-Gangetic Basin (IGB), eastern mining region of India, Bangladesh and large urban areas. Some of the major contributors of these emissions have been identified as agricultural waste burning, land transport, industrial production, and energy generation and distribution. An area averaged mean value of AIRS CO at 600hPa is found to be 114±2ppbv (slope −0.48±0.2ppbvyr−1, y-intercept 117±1ppbv and r=0.68) with a minor declining trend at −0.41±0.18%yr−1 over the region during 2003–2015. A strong seasonality in AIRS CO concentration is observed with spring season peak in March 129±1.9ppbv, whereas low values have been observed in summer monsoon with sturdy dip in July 99.6±1.94ppbv. AIRS CO and SCIAMACHY CO Total Column (CO TC) over the study region show spatial patterns similar to MACCity and REAS emissions. An analysis of SCIAMACHY CO TC tendencies has been performed which indicates minor rising trends over some parts of the region. Background CO, Recent Emissions (RE), and spatial anomalies in RE over high anthropogenic activity zones of Indus Basin, Ganges Basin and Eastern Region were analyzed using AIRS and SCIAMACHY CO data.

Inter-comparison of different NOX emission inventories and associated variation in simulated surface ozone in Indian region

In this work, we compare for the first time different anthropogenic NOX emission inventories and examine the associate variation in simulated surface ozone (O3) in India. Six anthropogenic NOX emission inventories namely Emission Database for Global Atmospheric Research (EDGAR), Intercontinental Chemical Transport Experiment-Phase B (INTEX-B), Regional Emission Inventory in Asia (REAS), MACCity, Indian National Emission Inventory (India_NOx), and Top-Down NOX emission inventory for India (Top-Down) are included in the comparison. We include these emission inventories in regional chemical transport model WRF-Chem to simulate tropospheric column NO2 and surface O3 mixing ratios for the month of summer (15-March to 15-April) and winter (December) in 2005. Predicted tropospheric column NO2 using different NOX emission inventory are evaluated with the OMI satellite observations. All emission inventories show similar spatial features, however uncertainty in NOX emissions distribution is about 20–50% over rural regions and about 60–160% over the major point sources. Compared to OMI, the largest bias in simulated tropospheric NO2 columns is seen in the REAS (−243.0 ± 338.8 × 1013 molecules cm−2) emission inventory, followed by EDGAR (−199.1 ± 272.2 × 1013 molecules cm−2), MACCity (−150.5 ± 236.3 × 1013 molecules cm−2), INTEX-B (−96.8 ± 199.5 × 1013 molecules cm−2), India_NOx (−87.7 ± 159.9 × 1013 molecules cm−2) and Top-Down (−30.8 ± 69.6 × 1013 molecules cm−2) inventories during winter. Simulations using different NOX emission inventories produces maximum deviation in daytime 8-h averaged O3 of the order of 9–17 ppb (15–40%) in summer and 3–12 ppb (5–25%) in winter over most of the land area. The simulation suggests that choice of NOX emission inventories have significant effect on surface O3 concentration for air quality studies over India.

Regional modeling of tropospheric NO<sub>2</sub> vertical column density over East Asia during the period 2000–2010: comparison with multisatellite observations

Abstract. 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.

Using Bayesian optimization method and FLEXPART tracer model to evaluate CO emission in East China in springtime

Carbon monoxide (CO) is of great interest as a restriction factor for pollutants related to incomplete combustions. This study attempted to evaluate CO emission in East China using the analytical Bayesian inverse method and observations at Mount Hua in springtime. The mixing ratio of CO at the receptor was calculated using 5-day source-receptor relationship (SRR) simulated by a Lagrangian Particle Dispersion Model (FLEXPART) and CO emission flux. The stability of the inversion solution was evaluated on the basis of repeated random sampling simulations. The inversion results demonstrated that there were two city cluster regions (the Beijing-Tianjin-Hebei region and the low reaches of the Yangtze River Delta) where the difference between a priori (Intercontinental Chemical Transport Experiment-Phase B, INTEX-B) and a posteriori was statistically significant and the a priori might underestimate the CO emission flux by 37 %. A correction factor (a posteriori/a priori) of 1.26 was suggested for CO emission in China in spring. The spatial distribution and magnitude of the CO emission flux were comparable to the latest regional emission inventory in Asia (REAS2.0). Nevertheless, further evaluation is still necessary in view of the larger uncertainties for both the analytical inversion and the bottom-up statistical approaches.

Emissions of air pollutants and greenhouse gases over Asian regions during 2000–2008: Regional Emission inventory in ASia (REAS) version 2

Abstract. 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/.

Premature mortality in Japan due to ozone

In Japan, all 47 prefectures conduct routine air quality monitoring at 1145 stations throughout the country to assess environmental effects. This study aims to provide a better understanding of possible estimations of premature mortality in Japan caused by exposure to monitored and modeled concentrations of tropospheric ozone during the period from January to December, 2005. The spatial distribution and temporal variation of ozone concentrations were modeled using the Models-3 Community Multiscale Air Quality modeling system coupled with the Regional Emission Inventory in Asia (CMAQ/REAS). Premature mortality caused by exposure to ozone was calculated assuming a relative risk (RR) value of 1.003 [95% Confidence Interval (CI): 1.001–1.004] for concentrations above 35 ppb according to the SOMO35 index (annual Sum of daily maximum 8-h Ozone Means Over 35 ppb) recommended by WHO (2008). Based on CMAQ/REAS simulations, the estimated all-cause premature mortality in 2005 is about 13,000 (95% CI: 4320–17,300) cases. This value is 2.5 times greater than the estimated premature mortality based on monitored ozone concentrations, which is 5220 (95% CI: 1740–6960) cases.

Multiannual changes of CO<sub>2</sub> emissions in China: indirect estimates derived from satellite measurements of tropospheric NO<sub>2</sub> columns

Abstract. Multiannual satellite measurements of tropospheric NO2 columns are used for evaluation of CO2 emission changes in China in the period from 1996 to 2008. Indirect top-down annual estimates of CO2 emissions are derived from the satellite NO2 column measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistry–transport model and the CO2-to-NOx emission ratios from the Emission Database for Global Atmospheric Research (EDGAR) global anthropogenic emission inventory and Regional Emission Inventory in Asia (REAS). Exponential trends in the normalized time series of annual emissions are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO2 emissions, and that the trend in the second period was significantly larger than the trend in the first period. Specifically, the trends in the first and second periods are best estimated to be in the range from 3.7 to 8.3 and from 11.0 to 13.2% per year, respectively, taking into account statistical uncertainties and differences between the CO2-to-NOx emission ratios from the EDGAR and REAS inventories. Comparison of our indirect top-down estimates of the CO2 emission changes with the corresponding bottom-up estimates provided by the EDGAR (version 4.2) and Global Carbon Project (GCP) glomal emission inventories reveals that while acceleration of the CO2 emission growth in the considered period is a common feature of both kinds of estimates, nonlinearity in the CO2 emission changes may be strongly exaggerated in the global emission inventories. Specifically, the atmospheric NO2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and indirect top-down estimates of the CO2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the global emission inventories, but is strongly positive in our estimates). These results confirm the findings of earlier studies that indicated probable large uncertainties in the energy production and other activity data for China from international energy statistics used as the input information in the global emission inventories. For the period from 2001 to 2008, some quantitative differences between the different kinds of estimates are found to be in the range of possible systematic uncertainties associated with our estimation method. In general, satellite measurements of tropospheric NO2 are shown to be a useful source of information on CO2 sources collocated with sources of nitrogen oxides; the corresponding potential of these measurements should be exploited further in future studies.

Influence of model grid resolution on NO2 vertical column densities over East Asia

NO2 vertical column densities (VCDs) over East Asia in June and December 2007 were simulated by the Community Multi-scale Air Quality (CMAQ) version 4.7.1 using an updated and more elaborate version of the Regional Emission Inventory in Asia (REAS) version 2. The modeling system could reasonably capture observed spatiotemporal changes of NO2 VCDs by satellite sensors, the Global Ozone Monitoring Experiment-2 (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), and the Ozone Monitoring Instrument (OMI), even at the coarsest horizontal resolution of 80 km. The CMAQ simulations were performed in a sequence of three horizontal resolutions (80 km, 40 km, and 20 km) for June and December 2007 to investigate the influence of changes of horizontal resolution on the obtained NO2 VCDs. CMAQ-simulated NO2 VCDs generally increased with improvements in resolution from 80 km to 40 km and then to 20 km. Increases in the CMAQ-simulated NO2 VCDs were greater for the change from 80 km to 40 km than for those from 40 km and 20 km, in which the increases of NO2 VCDs due to the improvement of horizontal resolution were approached convergence at the horizontal resolution of approximately 20 km. Conversely, no clear convergences in NO2 VCDs changes were found at near Tokyo and over the East China Sea. The biases of the NO2 VCDs simulated at a resolution of 20 km against the satellite retrievals were ∼36% near Beijing (CHN1) and ∼78% near Shanghai (CHN2) in summer; these errors were found to be comparable to the horizontal resolution-dependent errors, which were 18–25% at CHN1 and 44–58% at CHN2 from 80 km to 40 km. Conversely, the influence of changes of horizontal resolution in winter was relatively less compared to that in summer.Implications: NO2 VCDs over East Asia in June and December 2007 were simulated using CMAQ version 4.7.1 and REAS version 2. The modeling system could reasonably capture observed spatiotemporal changes of NO2 VCDs by satellite sensors. The CMAQ simulations were performed in a sequence of three horizontal resolutions, 80, 40, and 20 km, to investigate the influence of changes of horizontal resolution on the obtained NO2 VCDs. The results suggested that the influence of changes of horizontal resolution was larger in summer compared to that in winter. The magnitude of the influence was comparable to the biases of the NO2 VCDs simulated at a resolution of 20 km against the satellite retrievals.

A projection of ozone‐induced wheat production loss in China and India for the years 2000 and 2020 with exposure‐based and flux‐based approaches

Using a high-resolution (40 × 40 km) chemical transport model coupled with the Regional Emission inventory in Asia (REAS), we simulated surface ozone concentrations ([O3 ]) and evaluated O3 -induced wheat production loss in China and India for the years 2000 and 2020 using dose-response functions based on AOT40 (accumulated [O3 ] above 40 ppb) and PODY (phytotoxic O3 dose, accumulated stomatal flux of O3 above a threshold of Y nmol m(-2) s(-1) ). Two O3 dose metrics (90 days AOT40 and POD6 ) were derived from European experiments, and the other two (75 days AOT40 and POD12 ) were adapted from Asian studies. Relative yield loss (RYL) of wheat in 2000 was estimated to be 6.4-14.9% for China and 8.2-22.3% for India. POD6 predicted greater RYL, especially for the warm regions of India, whereas the 90 days AOT40 gave the lowest estimates. For the future projection, all the O3 dose metrics gave comparable estimates of an increase in RYL from 2000 to 2020 in the range 8.1-9.4% and 5.4-7.7% for China and India, respectively. The lower projected increase in RYL for India may be due to conservative estimation of the emission increase in 2020. Sensitivity tests of the model showed that the PODY -based estimates of RYL are highly sensitive to perturbations in the meteorological inputs, but that the estimated increase in RYL from 2000 to 2020 is much more robust. The projected increase in wheat production loss in China and India in the near future is substantially larger than the uncertainties in the estimation and indicates an urgent need for curbing the rapid increase in surface [O3 ] in these regions.