Regional Air Quality Simulations Research Articles

Pollutant emission reductions deliver decreased PM2.5-caused mortality across China during 2015–2017

Abstract. Air pollution is a serious environmental issue and leading contributor to disease burden in China. Rapid reductions in fine particulate matter (PM2.5) concentrations and increased ozone concentrations occurred across China during 2015 to 2017. We used measurements of particulate matter with a diameter <2.5 µm (PM2.5) and ozone (O3) from more than 1000 stations across China along with Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) regional air quality simulations, to explore the drivers and impacts of observed trends. The measured nationwide median PM2.5 trend of -3.4µgm-3yr-1 was well simulated by the model (-3.5µgm-3yr-1). With anthropogenic emissions fixed at 2015 levels, the simulated trend was much weaker (-0.6µgm-3yr-1), demonstrating that interannual variability in meteorology played a minor role in the observed PM2.5 trend. The model simulated increased ozone concentrations in line with the measurements but underestimated the magnitude of the observed absolute trend by a factor of 2. We combined simulated trends in PM2.5 concentrations with an exposure–response function to estimate that reductions in PM2.5 concentrations over this period have reduced PM2.5-attributable premature mortality across China by 150 000 deaths yr−1.

Urban-Scale NO2 Prediction with Sensors Aboard Bicycles: A Comparison of Statistical Methods Using Synthetic Observations

Mobile devices for city-scale air quality monitoring is receiving increasing attention due to the advent of low-cost and miniaturized sensors. Mobility and crowdsensing have emerged as a new means to investigate the ambient air quality in urban areas. However, the design of the network (e.g., number of sensors per unit area) and the scientific interpretation of collected data with an ad hoc method are still challenging. In this paper, we focus on the use of a fleet of private bicycles to monitor NO2 concentrations in the city of Marseille, France. The study is based on synthetic observations generated by means of a regional air quality simulation system at a spatial resolution of 25 m × 25 m and simulated bike trips that are randomly generated in the city. The bike trips correspond to a maximum of 4500 bike commuters and are generated using a web-based navigation service. Simulated bike tracks are validated using available statistics on bike counts. Each bike track is associated with the along-track corresponding NO2 concentrations collected from the air quality simulations and physical features on the ground collected from Open Street Map. Spatialization of the information collected aboard the bikes is tested by using three different algorithms: kriging, land-use regression (LUR) and neural network (NN). LUR and NN show that the fleet can be limited to below 100 bikes while the performance of kriging is steadily increasing with the number of bikes. Increasing the sample distance above 200 m also impairs the citywide prediction of simulated NO2 concentrations.

Refined assessment of size-fractioned particulate matter (PM2.5/PM10/PMtotal) emissions from coal-fired power plants in China

Chinese coal-fired power plants (CFPPs) are experiencing large-scale and rapid retrofitting of ultralow emission (ULE), causing significant changes in emission level of particulate matter (PM) from CFPPs. In this study, based on coal ash mass balance over the whole process, an integrated emission factors (EFs) database of three size-fractioned particulate matters (PM2.5, PM10, and PMtotal) for CFPPs is constructed, which covers almost all typical ULE technical routes installed in CFPPs. To verify the reliability of PM EFs established in this study, we compare those with related results based on field tests. Overall, the gaps in the EFs of PM2.5, PM10, and PMtotal obtained by the two methods are not outrageous within a reasonable range. By combined with the refined size-fractioned PM EFs and unit-based activity level database, a detailed high-resolution emission inventory of PM2.5, PM10, and PMtotal from Chinese CFPPs in 2017 is established, with the corresponding total emissions of 143, 207, and 267 kt, respectively. Our estimation of PMtotal emission is comparable to the official statistics announced by China Electricity Council (CEC), which further demonstrates the reliability of PM EFs constructed in this study. Moreover, potential reductions of PM from CFPPs at two stages before and after 2017 are assessed under three application scenarios of major ULE technical routes. We forecast the final annual emissions of PM2.5, PM10, and PMtotal until 2020 will be reduced further, which fall within the range of 86–111 kt, 120–157 kt, and 142–184 kt, respectively, if all CFPPs achieve ULE requirements under the three scenarios. We believe our integrated database of PM EFs of CFPPs has good universality, and the forecast results will be helpful for policy guidance of ULE technologies, emissions inventory compilation, and regional air quality simulation and management.

Uncertainties Caused by Major Meteorological Analysis Data Sets in Simulating Air Quality Over India

AbstractMany places in India suffer from severe air pollution. Regional air quality simulations are essential to develop effective strategies for improving air quality, considering the nonlinear relationships between ambient pollutants and their precursor emissions. Meteorological fields used in simulations are derived from regional meteorological models with analysis data sets as inputs. This study reveals that two major analysis data sets provided by the National Centers for Environmental Prediction and the European Centre for Medium‐Range Weather Forecasts (ECMWF) cause significant differences in simulated meteorological fields over India. Especially, relative humidity values simulated using the ECMWF data set are much higher and closer to the observed values than those simulated using the National Centers for Environmental Prediction data set. Results simulated using the ECMWF data set show better model performance for most meteorological parameters over India. Differences in relative humidity originate in the data contained in the analysis data sets through grid nudging. It is not possible to avoid this underestimation by simply turning off grid nudging. The meteorological fields simulated with two major analysis data sets also lead to differences in pollutant concentrations simulated by regional chemical transport models through various physical and chemical processes. Differences originating in the two analysis data sets could be comparable with the uncertainties originating in various emission inventories in some regions and seasons in India. However, discrepancies between observed and simulated pollutant concentrations cannot be explained only by differences of the meteorological fields. Other aspects need to be explored for better performance required to develop effective strategies for India, based on accurate regional air quality simulations.

Effects of a Detailed Vegetation Database on Simulated Meteorological Fields, Biogenic VOC Emissions, and Ambient Pollutant Concentrations over Japan

Regional air quality simulations provide powerful tools for clarifying mechanisms of heavy air pollution and for considering effective strategies for better air quality. This study introduces a new vegetation database for Japan, which could provide inputs for regional meteorological modeling, and estimating emissions of biogenic volatile organic compounds (BVOCs), both of which are essential components of simulations. It includes newly developed emission factors (EFs) of BVOCs for major vegetation types in Japan, based on existing literature. The new database contributes to improved modeling of meteorological fields due to its updated representation of larger urban areas. Using the new vegetation and EF database, lower isoprene and monoterpene, and higher sesquiterpene emissions are estimated for Japan than those derived from previously available default datasets. These slightly reduce the overestimation of ozone concentrations obtained by a regional chemical transport model, whereas their effects on underestimated secondary organic aerosol (SOA) concentrations are marginal. Further work is necessary, not only on BVOC emissions but also the other simulation components, to further improve the modeling of ozone and SOA concentrations in Japan.

Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory

Abstract. The impact of regional emissions (e.g., domestic and international) on surface particulate matter (PM) concentrations in the Seoul metropolitan area (SMA), South Korea, and its sensitivities to meteorology and emissions inventories are quantitatively estimated for 2014 using regional air quality modeling systems. Located on the downwind side of strong sources of anthropogenic emissions, South Korea bears the full impact of the regional transport of pollutants and their precursors. However, the impact of foreign emissions sources has not yet been fully documented. We utilized two regional air quality simulation systems: (1) a Weather Research and Forecasting and Community Multi-Scale Air Quality (CMAQ) system and (2) a United Kingdom Met Office Unified Model and CMAQ system. The following combinations of emissions inventories are used: the Intercontinental Chemical Transport Experiment-Phase B, the Inter-comparison Study for Asia 2010, and the National Institute of Environment Research Clean Air Policy Support System. Partial contributions of domestic and foreign emissions are estimated using a brute force approach, adjusting South Korean emissions to 50 %. Results show that foreign emissions contributed ∼ 60 % of SMA surface PM concentration in 2014. Estimated contributions display clear seasonal variation, with foreign emissions having a higher impact during the cold season (fall to spring), reaching ∼ 70 % in March, and making lower contributions in the summer, ∼ 45 % in September. We also found that simulated surface PM concentration is sensitive to meteorology, but estimated contributions are mostly consistent. Regional contributions are also found to be sensitive to the choice of emissions inventories.

Recent increase of surface particulate matter concentrations in the Seoul Metropolitan Area, Korea

Recent changes of surface particulate matter (PM) concentration in the Seoul Metropolitan Area (SMA), South Korea, are puzzling. The long-term trend of surface PM concentration in the SMA declined in the 2000s, but since 2012 its concentrations have tended to incline, which is coincident with frequent severe hazes in South Korea. This increase puts the Korean government’s emission reduction efforts in jeopardy. This study reports that interannual variation of surface PM concentration in South Korea is closely linked with the interannual variations of wind speed. A 12-year (2004–2015) regional air quality simulation was conducted over East Asia (27-km) and over South Korea (9-km) to assess the impact of meteorology under constant anthropogenic emissions. Simulated PM concentrations show a strong negative correlation (i.e. R = −0.86) with regional wind speed, implying that reduced regional ventilation is likely associated with more stagnant conditions that cause severe pollutant episodes in South Korea. We conclude that the current PM concentration trend in South Korea is a combination of long-term decline by emission control efforts and short-term fluctuation of regional wind speed interannual variability. When the meteorology-driven variations are removed, PM concentrations in South Korea have declined continuously even after 2012.

How healthy will be the air quality in 2050?

The air quality standards defined by the World Health Organization (WHO), and updated in 2005, continue to be much more exigent than current EU legislation, namely regarding the most critical pollutants over Europe: ozone (O3) and particulate matter (PM10 and PM2.5). This work intends to evaluate the fulfilment of these WHO standards in the present and in the future, including climate change effects. This study will be focused on Portugal, where each year, the O3 and PM10 concentrations exceed the legislated limit values. For this, regional air quality simulations for present and future periods were conducted, with CAMx version 6.0, to investigate the impacts of climate change and anthropogenic emission projections on air quality over Portugal in 2050. The climate and emission projections for 2050 were derived from the Representative Concentrations Pathway 8.5 scenario. Modelling results show that, over Portugal, the WHO standards are already not being fulfilled and will continue to be surpassed in the future. When considering climate change and projected anthropogenic emissions and comparing them to the actual scenario, a reduction in the maximum 8-h daily O3 concentration is expected. For PM, the results indicate serious problems regarding the health impact expected for both long-term and short-term exposure. The annual averages for both PM10 and PM2.5 exceed the AQG over the country. The PM short-term exposure is already very high for current conditions and higher impacts are expected for future scenario, in particular regarding the PM10 values. This air quality degradation is caused by the warmer and dryer conditions and the increase of background concentrations of pollutants expected for the 2050 climate. The results evidence that human health protection will be even more critical in the future, particularly for particulate matter. Furthermore, urgent air quality management strategies need to be designed, with transboundary cooperation and implementation.

Climate change and pollutant emissions impacts on air quality in 2050 over Portugal

Changes in climate and air pollutant emissions will affect future air quality from global to urban scale. In this study, regional air quality simulations for historical and future periods are conducted, with CAMx version 6.0, to investigate the impacts of future climate and anthropogenic emission projections on air quality over Portugal and the Porto metropolitan area in 2050. The climate and the emission projections were derived from the Representative Concentrations Pathways (RCP8.5) scenario. Modelling results show that climate change will impact NO2, PM10 and O3 concentrations over Portugal. The NO2 and PM10 annual means will increase in Portugal and in the Porto municipality, and the maximum 8-hr daily O3 value will increase in the Porto suburban areas (approximately 5%) and decrease in the urban area (approximately 2%). When considering climate change and projected anthropogenic emissions, the NO2 annual mean decreases (approximately 50%); PM10 annual mean will increase in Portugal and decrease in Porto municipality (approximately 13%); however PM10 and O3 levels increase and extremes occur more often, surpassing the currently legislated annual limits and displaying a higher frequency of daily exceedances. This air quality degradation is likely to be related with the trends found for the 2046–2065 climate, which implies warmer and dryer conditions, and with the increase of background concentrations of ozone and particulate matter. The results demonstrate the need for Portuguese authorities and policy-makers to design and implement air quality management strategies that take climate change impacts into account.

Assessment of the MACC reanalysis and its influence as chemical boundary conditions for regional air quality modeling in AQMEII-2

The Air Quality Model Evaluation International Initiative (AQMEII) has now reached its second phase which is dedicated to the evaluation of online coupled chemistry-meteorology models. Sixteen modeling groups from Europe and five from North America have run regional air quality models to simulate the year 2010 over one European and one North American domain. The MACC re-analysis has been used as chemical initial (IC) and boundary conditions (BC) by all participating regional models in AQMEII-2. The aim of the present work is to evaluate the MACC re-analysis along with the participating regional models against a set of ground-based measurements (O3, CO, NO, NO2, SO2, SO42−) and vertical profiles (O3 and CO). Results indicate different degrees of agreement between the measurements and the MACC re-analysis, with an overall better performance over the North American domain. The influence of BC on regional air quality simulations is analyzed in a qualitative way by contrasting model performance for the MACC re-analysis with that for the regional models. This approach complements more quantitative approaches documented in the literature that often have involved sensitivity simulations but typically were limited to only one or only a few regional scale models. Results suggest an important influence of the BC on ozone for which the underestimation in winter in the MACC re-analysis is mimicked by the regional models. For CO, it is found that background concentrations near the domain boundaries are rather close to observations while those over the interior of the two continents are underpredicted by both MACC and the regional models over Europe but only by MACC over North America. This indicates that emission differences between the MACC re-analysis and the regional models can have a profound impact on model performance and points to the need for harmonization of inputs in future linked global/regional modeling studies.

Contribution of Three-Dimensional Regional Air Quality Simulation for Mitigating Loads on Atmospheric Environment

Contribution of Three-Dimensional Regional Air Quality Simulation for Mitigating Loads on Atmospheric Environment

Effect of dramatic land use change on gaseous pollutant emissions from biomass burning in Northeastern China

Biomass burning contributes a substantial amount of gas and particle emissions to the atmosphere. As China's breadbasket, northeast China has experienced dramatic land use change in the past century, converting approximately 55×104ha of wetland into farmland to feed a rapidly growing population. This study combines measured emission factors of dominant crops (rice and soybean) and wetland plants (Calamagrostis angu-stifolia, Carex lasiocarpa, Carex pseudo-curaica) and remote sensing land use data to estimate the effect of the unprecedented land use change on gaseous pollutants emissions from biomass burning. Our biomass burning emission estimates resulting from land use changes have increased because of increased post-harvest crop residue burning and decreased burning of wetland plants. From 1986 to 2005, the total emissions of CO2, CO, CXHY, SO2 and NO have increased by 18.6%, 35.7%, 26.8%, 66.2% and 33.2%, respectively. We have found two trends in agricultural burning: increased dryland crop residue burning and decreased wetland (rice paddy) burning. Our results revealed that the large scale land use change in northeastern China has induced more active biomass-burning emissions. The regional emission inventory of gaseous pollutants derived from this work may be used to support further examination of the subsequent effects on regional climate and air quality simulations with numerical atmospheric models.

Photochemical roles of rapid economic growth and potential abatement strategies on tropospheric ozone over South and East Asia in 2030

Abstract. A regional air quality simulation framework including the Weather Research and Forecasting modeling system (WRF), the Community Multi-scale Air Quality modeling system (CMAQ), and precursor emissions to simulate tropospheric ozone over South and East Asia is introduced. Concentrations of tropospheric ozone and related species simulated by the framework are validated by comparing with observation data of surface monitoring, ozonesondes, and satellites obtained in 2010. The simulation demonstrates acceptable performance on tropospheric ozone over South and East Asia at regional scale. Future energy consumption, carbon dioxide (CO2), nitrogen oxides (NOx), and volatile organic compound (VOC) emissions in 2030 under three future scenarios are estimated. One of the scenarios assumes a business-as-usual (BAU) pathway, and other two scenarios consider implementation of additional energy and environmental strategies to reduce energy consumption, CO2, NOx, and VOC emissions in China and India. Future surface ozone under these three scenarios is predicted by the simulation. The simulation indicates future surface ozone significantly increases around India for a whole year and around northeastern China in summer. NOx is a main driver on significant seasonal increase of surface ozone, whereas VOC as well as increasing background ozone and methane is also an important factor on annual average of surface ozone in East Asia. Warmer weather around India is also preferable for significant increase of surface ozone. Additional energy and environmental strategies assumed in future scenarios are expected to be effective to reduce future surface ozone over South and East Asia.

Improving the representation of secondary organic aerosol (SOA) in the MOZART-4 global chemical transport model

Abstract. The secondary organic aerosol (SOA) module in the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) was updated by replacing existing two-product (2p) parameters with those obtained from two-product volatility basis set (2p-VBS) fits (MZ4-C1), and by treating SOA formation from the following additional volatile organic compounds (VOCs): isoprene, propene and lumped alkenes (MZ4-C2). Strong seasonal and spatial variations in global SOA distributions were demonstrated, with significant differences in the predicted concentrations between the base case and updated model simulations. Updates to the model resulted in significant increases in annual average SOA mass concentrations, particularly for the MZ4-C2 simulation in which the additional SOA precursor VOCs were treated. Annual average SOA concentrations predicted by the MZ4-C2 simulation were 1.00 ± 1.04 μg m−3 in South America, 1.57 ± 1.88 μg m−3 in Indonesia, 0.37 ± 0.27 μg m−3 in the USA, and 0.47 ± 0.29 μg m−3 in Europe with corresponding increases of 178, 406, 311 and 292% over the base-case simulation, respectively, primarily due to inclusion of isoprene. The increases in predicted SOA mass concentrations resulted in corresponding increases in SOA contributions to annual average total aerosol optical depth (AOD) by ~ 1–6%. Estimated global SOA production was 5.8, 6.6 and 19.1 Tg yr−1 with corresponding burdens of 0.22, 0.24 and 0.59 Tg for the base-case, MZ4-C1 and MZ4-C2 simulations, respectively. The predicted SOA budgets fell well within reported ranges for comparable modeling studies, 6.7 to 96 Tg yr−1, but were lower than recently reported observationally constrained values, 50 to 380 Tg yr−1. For MZ4-C2, simulated SOA concentrations at the surface also were in reasonable agreement with comparable modeling studies and observations. Total organic aerosol (OA) mass concentrations at the surface, however, were slightly over-predicted in Europe, Amazonian regions and Malaysian Borneo (Southeast Asia) during certain months of the year, and under-predicted in most sites in Asia; relative to those regions, the model performed better for sites in North America. Overall, with the inclusion of additional SOA precursors (MZ4-C2), namely isoprene, MOZART-4 showed consistently better skill (NMB (normalized mean bias) of −11 vs. −26%) in predicting total OA levels and spatial distributions of SOA as compared with unmodified MOZART-4. Treatment of SOA formation by these known precursors (isoprene, propene and lumped alkenes) may be particularly important when MOZART-4 output is used to generate boundary conditions for regional air quality simulations that require more accurate representation of SOA concentrations and distributions.

Simulating near-road reactive dispersion of gaseous air pollutants using a three-dimensional Eulerian model

In this study, the TAMNROM-3D model, a 3D Eulerian near-road air quality model with vehicle induced turbulence parameterization and a MOVES based emission preprocessor, is tested using near-road gaseous pollutants data collected near a rural freeway with 34% heavy duty vehicle traffic. Exhaust emissions of gasses from the vehicles are estimated using a lumped vehicle classification scheme based on the number of vehicle axles and the default county-level MOVES vehicle fleet database. The predicted dilution of CO and NOx in the downwind direction agrees well with observation, although the total NOx emission has to be scaled to 85% of its original emission rate estimated by the MOVES model. Using the atmospheric turbulent diffusion coefficient parameterization of Degrazia et al. (2000) with variable horizontal turbulent diffusion coefficient (Kxx) leads to slightly better predictions than a traditional non-height-dependent Kxx parameterization. The NO2 concentrations can be better predicted when emission of total NOx is split into NO and NO2 using the NO2 to NOx ratio of 29% measured near the road. Simulations using the SAPRC99 photochemical mechanism do not show significant changes in the predicted NO and NO2 concentrations near the road compared to simulations using a simple three-reaction mechanism that involves only NOx and O3. A regional air quality simulation in Houston, Texas during a high O3 episode in August 2000 shows that using the NO2 to NOx ratio of 29% instead of the traditional 5% leads to as much as 6ppb increase in 8-h O3 predictions.

Comparison of exposure estimation methods for air pollutants: Ambient monitoring data and regional air quality simulation

Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5μm (PM2.5) and ozone (O3) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM2.5 and O3, respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O3 (annual normalized mean bias=4.30%), while modeled PM2.5 had an annual normalized mean bias of −2.09%, although bias varied seasonally, from 32% in November to –27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors.

Simulation of urban and regional air pollution in Bangladesh

We have developed a regional scale air quality simulation using the Weather Research and Forecasting (WRF) – Community Multiscale Air Quality Model (CMAQ) to assess the suitability of such an advanced modeling system for predicting the air quality of Bangladesh and its surrounding region. The Regional Emission Inventory in Asia (REAS) was used as the emission input in this modeling approach. Both meteorological and chemical model performance were evaluated with observations including satellite data. Comparison between simulated and observed meteorological parameters revealed that the WRF can generate the necessary meteorological inputs for CMAQ. Comparison of observed and simulated concentrations of different air pollutants revealed that CMAQ greatly underestimates the concentrations of key pollutants. Comparison with satellite observations revealed that CMAQ reproduces the spatial distribution of NO2with some underestimation in Bangladesh and India. The simulated AOD and satellite‐retrieved AOD showed good temporal and spatial agreement mutually, with a correlation coefficient of 0.58. Sensitivity simulation using higher horizontal resolution emission data made by re‐gridding the REAS inventory with the population distribution improved the CMAQ performance. Nevertheless, CMAQ underestimated the pollutant concentrations in Dhaka. Uncertainties in the emission inventory and in the lack of time variation in emissions input mainly contributed to the model underestimation. Model predictions show that 36–72% PM10 and 15–60% PM2.5 in Dhaka might be contributed from brick kiln emissions in monthly average of January 2004. The chemical composition of PM2.5showed that the considerable amounts of secondary aerosols in Dhaka and carbonaceous components (particularly organic carbon) are most responsible for the model underestimation. Results suggest that improvements of emission inputs and more detailed sensitivity analysis of CMAQ model are important to assess the reliability and applicability of WRF‐CMAQ modeling system in this region.

A high-resolution emission inventory of crop burning in fields in China based on MODIS Thermal Anomalies/Fire products

Abstract Agricultural field burning plays an important role in atmospheric pollution and climate change. This work aims to develop a detailed emission inventory for agricultural burning in China with a high spatial and temporal resolution. Province-specific statistical data, distributed by the Chinese national government, and results from scientific literature were utilized to estimate the total emissions for the base year 2006. Emissions were allocated to a 1 km grid and a 10-day interval by using the Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies/Fire product (MOD/MYD14A1). The estimated annual emission ranges, with a 90% confidence interval, are 68 (51–85) Tg CO2 yr−1, 4 (2–7) Tg CO yr−1, 0.25 (0.08–0.46) Tg CH4 yr−1, 2.2 (1.08–3.46) Tg NMOCs yr−1, 0.23 (0.08–0.41) Tg NOx yr−1, 0.09 (0.03–0.17) Tg NH3 yr−1, 0.02 (0.01–0.03) Tg SO2 yr−1, 0.03 (0.01–0.05) Tg BC yr−1, 0.1 (0.04–0.17) Tg OC yr−1, 0.27 (0.13–0.42) Tg PM2.5 yr−1, 0.31 (0.12–0.53) Tg PM10 yr−1. Provinces with the highest emissions are Anhui, Guizhou and Hunan. Spatially, agricultural fires are mostly located in the North China Plain, where the occurrence of fires is concentrated in early and late June (over 75% of the whole year) with another smaller peak in early October. This pattern corresponds with sowing and harvesting times for the main crops: wheat and maize. The temporal fire variation of two other agricultural zones in northeast China and south China are also detailed in our study. Our inventory, with a relatively high spatiotemporal resolution (1 km grid and 10 days), could meet the need of global and regional air quality simulations.

Development of a framework for a high-resolution, three-dimensional regional air quality simulation and its application to predicting future air quality over Japan

Abstract We have developed a framework for a three-dimensional regional air quality simulation that is applicable to various air quality studies over Japan. The framework consists of the following simulation model systems: the Weather Research and Forecasting (WRF) model to simulate meteorological fields; the Community Multi-scale Air Quality (CMAQ) modeling system to simulate pollutant concentrations; emissions estimate models; and emission databases. Motor vehicle emissions in Japan are estimated using the Japan Auto-Oil Program (JATOP) vehicle emissions estimate model; anthropogenic emissions from sources other than motor vehicles in Japan are estimated using the Georeference-Based Emission Activity Modeling System (G-BEAMS); and biogenic emissions are estimated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN). The Regional Emission inventory in Asia (REAS) is used for emissions in Asian countries except for Japan. The most prominent feature of our framework is its ability to simulate multi-scale air quality. The framework allows for the simulation of emissions and the dynamic transport of pollutants in heavily polluted urban areas with a maximum resolution of 1 × 1 km, and the long-range transport of pollutants is also taken into account. This framework is used to analyze the impact of future emissions from anthropogenic sources on air quality over the Tokyo metropolitan area. NOx, NMVOC and primary PM2.5 emissions over the Tokyo metropolitan area are estimated to be reduced by 44.5%, 18.1% and 41.7%, respectively, from 2005 to 2020. The simulation predicts that concentrations of NO2 and PM2.5 over the Tokyo metropolitan area will decrease by approximately 30–40% and 15–20%, respectively, during the above period. O3 concentrations significantly increase in winter due to decreased titration by NO, whereas no significant variations are observed in spring and summer. In addition, we analyzed the impact of future long-range transport projected under three emission scenarios provided by REAS. The simulation indicates that future long-range transport will affect concentrations of O3 and PM2.5 over the Tokyo metropolitan area; however, its impact is small compared with that of future anthropogenic emissions in Japan.

Decadal regional air quality simulations over Europe in present climate: near surface ozone sensitivity to external meteorological forcing

Abstract. Regional climate-air quality decadal simulations over Europe were carried out with the RegCM3/CAMx modeling system for the time slice 1991–2000, in order to study the impact of different meteorological forcing on surface ozone. The RegCM3 regional climate model was firstly constrained by the ERA40 reanalysis dataset which is considered as an experiment with perfect meteorological boundary conditions and then it was constrained by the global circulation model ECHAM5. A number of meteorological parameters were examined including the 500 mb geopotential height, solar radiation, temperature, cloud liquid water path, planetary boundary layer height and surface wind. The different RegCM meteorological forcing resulted in changes of near surface ozone over Europe ranging between ± 4 ppb for winter and summer. The area showing the greatest sensitivity in O3 during winter is central and southern Europe while in summer central north continental Europe. The different meteorological forcing impacts on the atmospheric circulation, which in turn affects cloudiness and solar radiation, temperature, wind patterns and the meteorology depended biogenic emissions. For comparison reasons, the impact of chemical boundary conditions on surface ozone was additionally examined with a series of sensitivity studies, indicating that surface ozone changes are comparable to those caused by the different meteorological forcing. These findings suggest that, when it comes to regional climate-air quality simulations, the selection of external meteorological forcing can be as important as the selection of adequate chemical lateral boundary conditions.