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  • Copernicus  (25)
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  • 1
    Publication Date: 2020-06-25
    Description: This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to −20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s−1 differences over inland regions).
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  • 2
    Publication Date: 2020-01-06
    Description: Despite the significant progress in improving chemical transport models (CTMs), applications of these modeling endeavors are still subject to large and complex model uncertainty. The Model Inter-Comparison Study for Asia III (MICS-Asia III) has provided the opportunity to assess the capability and uncertainty of current CTMs in East Asian applications. In this study, we have evaluated the multi-model simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia (NH3) over China under the framework of MICS-Asia III. A total of 13 modeling results, provided by several independent groups from different countries and regions, were used in this study. Most of these models used the same modeling domain with a horizontal resolution of 45 km and were driven by common emission inventories and meteorological inputs. New observations over the North China Plain (NCP) and Pearl River Delta (PRD) regions were also available in MICS-Asia III, allowing the model evaluations over highly industrialized regions. The evaluation results show that most models captured the monthly and spatial patterns of NO2 concentrations in the NCP region well, though NO2 levels were slightly underestimated. Relatively poor performance in NO2 simulations was found in the PRD region, with larger root-mean-square error and lower spatial correlation coefficients, which may be related to the coarse resolution or inappropriate spatial allocations of the emission inventories in the PRD region. All models significantly underpredicted CO concentrations in both the NCP and PRD regions, with annual mean concentrations that were 65.4 % and 61.4 % underestimated by the ensemble mean. Such large underestimations suggest that CO emissions might be underestimated in the current emission inventory. In contrast to the good skills for simulating the monthly variations in NO2 and CO concentrations, all models failed to reproduce the observed monthly variations in NH3 concentrations in the NCP region. Most models mismatched the observed peak in July and showed negative correlation coefficients with the observations, which may be closely related to the uncertainty in the monthly variations in NH3 emissions and the NH3 gas–aerosol partitioning. Finally, model intercomparisons have been conducted to quantify the impacts of model uncertainty on the simulations of these gases, which are shown to increase with the reactivity of species. Models contained more uncertainty in the NH3 simulations. This suggests that for some highly active and/or short-lived primary pollutants, like NH3, model uncertainty can also take a great part in the forecast uncertainty in addition to the emission uncertainty. Based on these results, some recommendations are made for future studies.
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  • 3
    Publication Date: 2020-09-10
    Description: Atmospheric nitrogen deposition in China has attracted public attention in recent years due to the increasing anthropogenic emission of reactive nitrogen (Nr) and its impacts on the terrestrial and aquatic ecosystems. However, limited long-term and multisite measurements have restrained the understanding of the mechanism of the Nr deposition and the chemical transport model (CTM) improvement. In this study, the performance of the simulated wet and dry deposition for different Nr species, i.e., particulate NO3- and NH4+, gaseous NOx, HNO3 and NH3 have been conducted using the framework of Model Inter-Comparison Study for Asia (MICS-Asia) phase III. A total of nine models, including five Weather Research and Forecasting models coupled with the Community Multiscale Air Quality (WRF-CMAQ) models, two self-developed regional models, a global model and a Regional Atmospheric Modeling System coupled with the Community Multiscale Air Quality (RAMS-CMAQ) model have been selected for the comparison. For wet deposition, observation data from 83 measurement sites from the East Asia Acid Deposition Monitoring Network (EANET), Chinese Ecosystem Research Network (CERN), China Agricultural University Deposition Network (CAUDN), National Acid Deposition Monitoring Network (NADMN) and Department of Ecological Environment (DEE) of China have been collected and normalized for comparison with model results. In general, most models show the consistent spatial and temporal variation of both oxidized N (Nox) and reduced N (Nrd) wet deposition in China, with the normalized mean error (NME) at around 50 %, which is lower than the value of 70 % based on EANET observation over Asia. Both the ratio of wet or dry deposition to the total inorganic N (TIN) deposition and the ratios of TIN to their emissions have shown consistent results with the Nationwide Nitrogen Deposition Monitoring Network (NNDMN) estimates. The performance of ensemble results (ENMs) was further assessed with satellite measurements. In different regions of China, the results show that the simulated Nox wet deposition was overestimated in northeastern China (NE) but underestimated in the south of China, namely southeastern (SE) and southwestern (SW) China, while the Nrd wet deposition was underestimated in all regions by all models. The deposition of Nox has larger uncertainties than the Nrd, especially in northern China (NC), indicating the chemical reaction process is one of the most important factors affecting the model performance. Compared to the critical load (CL) value, the Nr deposition in NC, SE and SW reached or exceeded reported CL values and resulted in serious ecological impacts. The control of Nrd in NC and SW and Nox in SE would be an effective mitigation measure for TIN deposition in these regions. The Nr deposition in the Tibetan Plateau (TP) with a high ratio of TIN ∕ emission (∼3.0), indicates a significant transmission from outside. Efforts to reduce these transmissions ought to be paramount due the climatic importance of the Tibetan region to the sensitive ecosystems throughout China.
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  • 4
    Publication Date: 2019-12-19
    Description: Wet scavenging is one of the most efficient processes for removing aerosols from the atmosphere. This process is not well constrained in chemical transport models (CTMs) due to a paucity of localized parameterization regarding the below-cloud wet scavenging coefficient (BWSC). Here we conducted field measurements of the BWSC during the Atmospheric Pollution and Human Health Beijing (APHH-Beijing) campaign of 2016. Notably, the observed BWSC values based on the updated aerosol mass balance agree well with another estimation technique, and they fall in a range of 10−5 s−1. The measurement in this winter campaign, combined with that in summer of 2014, supported an exponential power distribution of BWSCs with rainfall intensity. The observed parameters were also compared with both the theoretical calculations and modeling results. We found that the theoretical estimations can effectively characterize the observed BWSCs of aerosols with sizes smaller than 0.2 µm and larger than 2.5 µm. However, the theoretical estimations were an order of magnitude lower than observed BWSCs within 0.2–2.5 µm, a domain size range of urban aerosols. Such an underestimation of BWSC through a theoretical method has been confirmed not only in APHH-Beijing campaign but also in all the rainfall events in summer of 2014. Since the model calculations usually originated from the theoretical estimations with simplified scheme, the significantly lower BWSC could well explain the underprediction of wet depositions in polluted regions as reported by the Model Inter-Comparison Study for Asia (MICS-Asia) and the global assessment of the Task Force on Hemispheric Transport of Atmospheric Pollutants (TF-HTAP). The findings highlighted that the wet deposition module in the CTMs requires improvement based on field measurement estimation to construct a more reasonable simulation scheme for BWSC, especially in polluted regions.
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  • 5
    Publication Date: 2018-04-10
    Description: Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-Asia III Topic 3 study design, including descriptions of participating models and model inputs, the experimental designs, and results of model evaluation, are presented. Six modeling groups from China, Korea and the United States submitted results from seven applications of online coupled chemistry–meteorology models. Results are compared to meteorology and air quality measurements, including data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) and the Acid Deposition Monitoring Network in East Asia (EANET). The correlation coefficients between the multi-model ensemble mean and the CARE-China observed near-surface air pollutants range from 0.51 to 0.94 (0.51 for ozone and 0.94 for PM2.5) for January 2010. However, large discrepancies exist between simulated aerosol chemical compositions from different models. The coefficient of variation (SD divided by the mean) can reach above 1.3 for sulfate in Beijing and above 1.6 for nitrate and organic aerosols in coastal regions, indicating that these compositions are less consistent from different models. During clean periods, simulated aerosol optical depths (AODs) from different models are similar, but peak values differ during severe haze events, which can be explained by the differences in simulated inorganic aerosol concentrations and the hygroscopic growth efficiency (affected by varied relative humidity). These differences in composition and AOD suggest that future models can be improved by including new heterogeneous or aqueous pathways for sulfate and nitrate formation under hazy conditions, a secondary organic aerosol (SOA) formation chemical mechanism with new volatile organic compound (VOCs) precursors, yield data and approaches, and a more detailed evaluation of the dependence of aerosol optical properties on size distribution and mixing state. It was also found that using the ensemble mean of the models produced the best prediction skill. While this has been shown for other conditions (for example, the prediction of high-ozone events in the US (McKeen et al., 2005)), this is to our knowledge the first time it has been shown for heavy haze events.
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  • 6
    Publication Date: 2019-06-05
    Description: The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) programme is an international collaborative project focusing on understanding the sources, processes and health effects of air pollution in the Beijing megacity. APHH-Beijing brings together leading China and UK research groups, state-of-the-art infrastructure and air quality models to work on four research themes: (1) sources and emissions of air pollutants; (2) atmospheric processes affecting urban air pollution; (3) air pollution exposure and health impacts; and (4) interventions and solutions. Themes 1 and 2 are closely integrated and support Theme 3, while Themes 1–3 provide scientific data for Theme 4 to develop cost-effective air pollution mitigation solutions. This paper provides an introduction to (i) the rationale of the APHH-Beijing programme and (ii) the measurement and modelling activities performed as part of it. In addition, this paper introduces the meteorology and air quality conditions during two joint intensive field campaigns – a core integration activity in APHH-Beijing. The coordinated campaigns provided observations of the atmospheric chemistry and physics at two sites: (i) the Institute of Atmospheric Physics in central Beijing and (ii) Pinggu in rural Beijing during 10 November–10 December 2016 (winter) and 21 May–22 June 2017 (summer). The campaigns were complemented by numerical modelling and automatic air quality and low-cost sensor observations in the Beijing megacity. In summary, the paper provides background information on the APHH-Beijing programme and sets the scene for more focused papers addressing specific aspects, processes and effects of air pollution in Beijing.
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  • 7
    Publication Date: 2019-01-07
    Description: Depolarization ratio (δ) of backscattered light is an applicable parameter for distinguishing the sphericity of particles in real time, which has been widely adopted by ground-based lidar observation systems. In this study, δ values of particles and chemical compositions in both PM2.5 (aerodynamic diameter less than 2.5 µm) and PM10 (aerodynamic diameter less than 10 µm) were concurrently measured on the basis of a bench-top optical particle counter with a polarization detection module (POPC) and a continuous dichotomous aerosol chemical speciation analyzer (ACSA-14) from November 2016 to February 2017 at an urban site in Beijing megacity. In general, measured δ values depended on both size and sphericity of the particles. During the observation period, mass concentrations of NO3- in PM2.5 (fNO3) were about an order of magnitude higher than that in PM2.5−10 (cNO3) with a mean fNO3∕cNO3 ratio of 14±10. A relatively low fNO3∕cNO3 ratio (∼5) was also observed under higher relative humidity conditions, mostly due to heterogeneous processes and particles in the coarse mode. We found that δ values of ambient particles in both PM2.5 and PM2.5−10 obviously decreased as mass concentration of water-soluble species increased at unfavorable meteorological conditions. This indicated that the morphology of particles was changed as a result of water-absorbing processes. The particles with optical size (Dp) of Dp = 5 µm were used to represent mineral dust particles, and its δ values (δDp=5) decreased by 50 % as the mass fraction of cNO3 increased from 2 % to 8 % and ambient relative humidity increased up to 80 %, suggesting that mineral dust particles were likely to be spherical during humid pollution episodes. During the observation, relative humidity inside the POPC measuring chamber was stable at 34±2 %, lower than the ambient condition. Its influence on the morphology was estimated to be limited and did not change our major conclusion. This study highlights the evident alteration of non-sphericity of mineral dust particles during their transport owing to a synergistic effect of both pollutant coatings and hygroscopic processes, which plays an important role in the evaluation of its environmental effect.
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  • 8
    Publication Date: 2018-01-08
    Description: The real-time measurements of NH3 and trace gases were conducted, in conjunction with semi-continuous measurements of water-soluble ions in PM2.5 at a rural site in the North China Plain (NCP) from May to September 2013 in order to better understand chemical characteristics of ammonia and the impact of secondary ammonium aerosols on formation in the NCP. Extremely high NH3 and NH4+ concentrations were observed after a precipitation event within 7–10 days following urea application. Elevated NH3 levels coincided with elevated NH4+, indicating that NH3 likely influenced particulate ammonium mass. For the sampling period, the average conversion ∕ oxidation ratios for NH4+ (NHR), SO42- (SOR), and NO3- (NOR) were estimated to be 0.30, 0.64, and 0.24, respectively. The increased NH3 concentrations, mainly from agricultural activities and regional transport, coincided with the prevailing meteorological conditions. The high NH3 level with NHR of about 0.30 indicates that the emission of NH3 in the NCP is much higher than needed for aerosol acid neutralisation, and NH3 plays an important role in the formation of secondary aerosols as a key neutraliser. The hourly data obtained were used to investigate gas–aerosol partitioning characteristics using the thermodynamic equilibrium model ISORROPIA-II. Modelled SO42-, NO3-, and NH3 values agree well with the measurements, while the modelled NH4+ values largely underestimate the measurements. Our observation and modelling results indicate that strong acids in aerosol are completely neutralised. Additional NH4+ exists in aerosol, probably a result of the presence of a substantial amount of oxalic and other diacids.
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  • 9
    Publication Date: 2020-01-30
    Description: Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating wintertime haze events in the North China Plain region and evaluates the importance of aerosol radiative feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the participating models. Over the Beijing–Tianjin–Hebei (BTH) region, the ensemble mean of estimated aerosol direct radiative forcing (ADRF) at the top of atmosphere, inside the atmosphere, and at the surface are −1.1, 7.7, and −8.8 W m−2 during January 2010, respectively. Subdivisions of direct and indirect aerosol radiative forcing confirm the dominant role of direct forcing. During severe haze days (17–19 January 2010), the averaged reduction in near-surface temperature for the BTH region can reach 0.3–1.6 ∘C. The responses of wind speeds at 10 m (WS10) inferred from different models show consistent declines in eastern China. For the BTH region, aerosol–radiation feedback-induced daytime changes in PM2.5 concentrations during severe haze days range from 6.0 to 12.9 µg m−3 (
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  • 10
    Publication Date: 2019-09-25
    Description: A total of 14 chemical transport models (CTMs) participated in the first topic of the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. These model results are compared with each other and an extensive set of measurements, aiming to evaluate the current CTMs' ability in simulating aerosol concentrations, to document the similarities and differences among model performance, and to reveal the characteristics of aerosol components in large cities over East Asia. In general, these CTMs can well reproduce the spatial–temporal distributions of aerosols in East Asia during the year 2010. The multi-model ensemble mean (MMEM) shows better performance than most single-model predictions, with correlation coefficients (between MMEM and measurements) ranging from 0.65 (nitrate, NO3-) to 0.83 (PM2.5). The concentrations of black carbon (BC), sulfate (SO42-), and PM10 are underestimated by MMEM, with normalized mean biases (NMBs) of −17.0 %, −19.1 %, and −32.6 %, respectively. Positive biases are simulated for NO3- (NMB = 4.9 %), ammonium (NH4+) (NMB = 14.0 %), and PM2.5 (NMB = 4.4 %). In comparison with the statistics calculated from MICS-Asia phase II, frequent updates of chemical mechanisms in CTMs during recent years make the intermodel variability of simulated aerosol concentrations smaller, and better performance can be found in reproducing the temporal variations of observations. However, a large variation (about a factor of 2) in the ratios of SNA (sulfate, nitrate, and ammonium) to PM2.5 is calculated among participant models. A more intense secondary formation of SO42- is simulated by Community Multi-scale Air Quality (CMAQ) models, because of the higher SOR (sulfur oxidation ratio) than other models (0.51 versus 0.39). The NOR (nitric oxidation ratio) calculated by all CTMs has larger values (∼0.20) than the observations, indicating that overmuch NO3- is simulated by current models. NH3-limited condition (the mole ratio of ammonium to sulfate and nitrate is smaller than 1) can be successfully reproduced by all participant models, which indicates that a small reduction in ammonia may improve the air quality. A large coefficient of variation (CV 〉 1.0) is calculated for simulated coarse particles, especially over arid and semi-arid regions, which means that current CTMs have difficulty producing similar dust emissions by using different dust schemes. According to the simulation results of MMEM in six large Asian cities, different air-pollution control plans should be taken due to their different major air pollutants in different seasons. The MICS-Asia project gives an opportunity to discuss the similarities and differences of simulation results among CTMs in East Asian applications. In order to acquire a better understanding of aerosol properties and their impacts, more experiments should be designed to reduce the diversities among air quality models.
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