Air Quality Prediction Modeling Research Articles

Simulation on different response characteristics of aerosol particle number concentration and mass concentration to emission changes over mainland China

In this study, Nested Air Quality Prediction Modeling System with Advance Particle Microphysics module (NAQPMS+APM) is applied to simulate the response characteristics of aerosol particle number concentration and mass concentration to emission changes over mainland China. It is the first attempt to investigate the response of both aerosol mass concentration and number concentration to emission changes using a chemical transport model with detailed aerosol microphysics over mainland China. Results indicate that the response characteristics are obviously different between aerosol particle number concentration and mass concentration. Generally, the response of number concentration shows a more heterogeneous spatial distribution than that of mass concentration. Furthermore, number concentration has a higher sensitivity not only to primary particles emission but also to precursor gases than that of mass concentration. Aerosol particle mass concentration exhibits a consistent trend with the emission change and yet aerosol number concentration does not. Due to the nonlinearity of aerosol microphysical processes, reduction of primary particles emission does not necessarily lead to an obvious decrease of aerosol number concentration and it even increases the aerosol number concentration. Over Central-Eastern China (CEC), the most polluted regions in China, reducing primary particles emission rather than precursor gas emissions is more effective in reducing particles number concentration. By contrast, the opposite is true over the northwestern China. The features of fine particles pollution revealed in this study are associated with the spatial differences in China's population, geography, climate and economy. Considering the more adverse effects of ultrafine particles on human health and the spatial distribution of population, making different measures in controlling particles number concentration from that controlling mass concentration in different regions over mainland China is indicated. Main findingsFPN concentration responds more heterogeneously to emission than FPM. Spatial difference of response of FPN to emission is distinguished by a boundary line.

Time Series Forecasting of Air Quality Based On Regional Numerical Modeling in Hong Kong

AbstractBased on prevailing numerical forecasting models (Community Multiscale Air Quality [CMAQ] model , Comprehensive Air Quality Model with Extensions, and Nested Air Quality Prediction Modeling System) and observations from monitoring stations in Hong Kong, we employ a set of autoregressive integrated moving average (ARIMA) models with numerical forecasts (ARIMAX) to improve the forecast of air pollutants including PM2.5, NO2, and O3. The results show significant improvements in multiple evaluation metrics for daily (1–3 days) and hourly (1–72 hr) forecast. Forecasts on daily 1‐hr and 8‐hr maximum O3are also improved. For instance, compared with CMAQ, applying CMAQ‐ARIMA reduces average root‐mean‐square errors (RMSEs) at all stations for daily average PM2.5, NO2, and O3in the next 3 days by 14.3–21.0%, 41.2–46.3%, and 47.8–49.7%, respectively. For hourly forecasts in the next 72 hr, reductions in RMSEs brought by ARIMAX using CMAQ are 18.2% for PM2.5, 32.1% for NO2, and 36.7% for O3. Large improvements in RMSEs are achieved for nonrural PM2.5and rural NO2using ARIMAX with three numerical models. Dynamic hourly forecast shows that ARIMAX can be applied for forecast of 7‐ to 72‐hr PM2.5, 4‐ to 72‐hr NO2, and 4‐ to 6‐hr O3. Besides applying ARIMAX for NO2, we recommend a mixed forecast strategy to ARIMAX for normal values of PM2.5and O3and employ numerical models for outputs above 75th percentile of historical observations. Our hybrid ARIMAX method can combine the advantage of ARIMA and numerical modeling to assist real‐time air quality forecasting efficiently and consistently.

SO2 trajectories in a complex terrain environment using CALPUFF dispersion model, OMI and MODIS data

Latest improvements in the resolution of atmospheric satellite sensors that measure chemical constituents from space have led to enhanced detection of trace gases. This paper explores the use of sulfur dioxide (SO2) level 2 dataset from OMI instrument, in conjunction with aerosol optical depth and Ångström exponent data from MODIS spectroradiometer, to estimate SO2 loads under clear and turbid atmospheres. The spatial patterns of SO2 loads in polluted atmospheric conditions are compared with a regional pollutant dispersion model (CALPUFF) and field observations near the Andes Peruvian city La Oroya, which is one of the most polluted places in the world. The efficacy of this methodology is further examined incorporating synchronous wind vectors. Results show that the spatial-temporal dynamics of OMI SO2 is in agreement with field measurements and CALPUFF. The SO2 satellite data obtained under optimal viewing conditions and clear skies are also compared with field observations. A correlation is found between in-situ measurements and OMI estimations. The correlation increases for days with predominantly fine aerosols when Ångström exponents are between 0.7 and 1. Moreover, pixel averaging techniques and low and high spatial frequency filtration, applied to OMI SO2 data, results in a more reliable representation of the mean SO2 plume. The paper concludes that anthropogenic SO2 can be monitored from space, even for turbid sky conditions. This demonstrates the potential for the use of satellite products to improve the air quality prediction models.

Source tagging modeling study of regional contributions to acid rain in summer over Liaoning Province, Northeastern China.

Strong acid rain was recently observed over Northeastern China, particularly in summer in Liaoning Province where alkaline dust largely neutralized acids in the past. This seems to be related to the regional transboundary pollution and poses new challenges in acid rain control scheme in China. In order to delve into the regional transport impact, and quantify its potential contributions to such an "eruption" of acid rain over Liaoning, this paper employs an online source tagging model in coupling with the Nested Air Quality Prediction Modeling System (NAQPMS). Validation of predictions shows the model capability in reproducing key meteorological and chemical features. Acid concentration over Liaoning is more pronounced in August (average of 0.087 mg/m3) with strong pollutant import from regional sources against significant depletion of basic species. Seasonal mean contributions from regional sources are assessed at both lower and upper boundary layers to elucidate the main pathways of the impact of regional sources on acid concentration over Liaoning. At the upper layer (1.2 km), regional sources contribute to acid concentration over Liaoning by 67%, mainly from Shandong (16%), Hebei (13%), Tianjin (11%) and Korean Peninsula (9%). Identified main city-receptors in Liaoning are Dandong, Dalian, Chaohu, Yingkou, Liaoyang, Jinfu, Shengyang, Panjin, Tieling, Benxi, Anshan and Fushun. At lower layer (120 m) where Liaoning local contribution is dominant (58%), regional sources account for 39% in acid concentration. However, inter-municipal acid exchanges are prominent at this layer and many cities in Liaoning are revealed as important sources of local acid production. Seasonal acid contribution average within 1.2 km-120 m attains 55%, suggesting dominance of vertical pollutant transport from regional sources towards lower boundary layer in Liaoning. As direct environmental implication, this study provides policy makers with a perspective of regulating the regional transboundary environmental impact assessment in China with application to acid rain control.

A state of the art regarding urban air quality prediction models

Urban pollution represents an increasing risk to residents of urban regions, particularly in large, over-industrialized cities knowing that the traffic is responsible for more than 25% of air gaseous pollutants and dust particles. Air quality modelling plays an important role in addressing air pollution control and management approaches by providing guidelines for better and more efficient air quality forecasting, along with smart monitoring sensor networks. The advances in technology regarding simulations, forecasting and monitoring are part of the new smart cities which offers a healthy environment for their occupants.

Model-Integration of Anthropogenic Heat for Improving Air Quality Forecasts over the Beijing Megacity

In air quality forecasting systems, failure to consider the considerably large anthropogenic heat emissions generated daily in the Beijing megacity by intensive human activities is one of the major causes of model failure. In this paper, we employ the nested air quality prediction model system coupled with the weather research and forecasting model and an urban canopy model to integrate anthropogenic heat emissions over Beijing into the modeling system and exhaustively evaluate their potential effects on air quality forecast by analyzing the wind field, boundary layer structure (height and atmospheric circulation), and surface and vertical distribution of pollutants. Consequently, the effects of anthropogenic heat on the boundary layer structure, greatly pronounced in urban areas, exhibited substantial variability at different levels depending on the time. The effects were evident during both daytime and night, but played a more prominent singular role in the night in the absence of solar short-wave radiation. Basically, anthropogenic heat acts not only by directly inducing the ascent of a warm air mass from the low parts of the atmosphere over urban areas to the top of the boundary layer, but also by indirectly driving wind convergence and inducing the descent of a cooled air mass from a high altitude to the boundary layer through a complex atmospheric circulation process. Incorporating anthropogenic heat emissions into the modeling system was effective in improving predictions by reducing the normalized mean bias by 20%–30% (for wind speed) and root mean square error by 361–558 m (for boundary layer height) and by 10–23 µg m–3 (for surface PM10), with a significant reduction in the underestimation of ozone concentration by approximately 20 ppb at urban sites. This paper is expected to provide new insights into the improvement of model accuracy for air quality forecasts over megacities.

Importance of mineral dust and anthropogenic pollutants mixing during a long-lasting high PM event over East Asia.

A long-lasting high particulate matter (PM) concentration episode persisted over East Asia from May 24 to June 3, 2014. The Nested Air Quality Prediction Model System (NAQPMS) was used to investigate the mixing of dust and anthropogenic pollutants during this episode. Comparison of observations revealed that the NAQPMS successfully reproduced the time series PM2.5 and PM10 concentrations, as well as the nitrate and sulfate concentrations in fine (aerodynamic diameter≤2.5μm) and coarse mode (2.5μm<aerodynamic diameter≤10μm). This episode originated from two dust events that occurred in the inland desert areas of Mongolia and China, and then the long-range transported dust and anthropogenic pollutants were trapped over the downwind region of East Asia for more than one week due to the blocked north Pacific subtropical high-pressure system over the east of Japan. The model results showed that mineral dust accounted for 53-83% of PM10, and 39-67% of PM2.5 over five cities in East Asia during this episode. Sensitivity analysis indicated that the Qingdao and Seoul regions experienced dust and pollution twice, by direct transport from the dust source region and from dust detoured over the Shanghai area. The results of the NAQPMS model confirmed the importance of dust heterogeneous reactions (HRs) over East Asia. Simulated dust NO3- concentrations accounted for 75% and 84% of total NO3- in fine and coarse mode, respectively, in Fukuoka, Japan. The horizontal distribution of model results revealed that the ratio of dust NO3-/dust concentration increased from about 1% over the Chinese land mass to a maximum of 8% and 6% respectively in fine and coarse mode over the ocean to the southeast of Japan, indicating that dust NO3- was mainly formed over the Yellow Sea and the East China Sea before reaching Japan.

Radiative and heterogeneous chemical effects of aerosols on ozone and inorganic aerosols over East Asia

Currently, many challenges are faced in simulating ozone(O3), sulfate(SO42−), and nitrate(NO3−) concentrations over East Asia, particularly the overestimation of surface O3 and NO3− concentrations and underestimation of the SO42− concentration during haze episodes. In this study, we examined the radiative and heterogeneous chemical effects of aerosols by incorporating recently reported mechanisms, including self-amplifying SO42− formation, dinitrogen pentoxide (N2O5) hydrolysis, and a heterogeneous reaction converting gaseous nitric acid (HNO3) to nitric oxide (NOx), into a Nested Air Quality Prediction Modeling System. Uptakes by aerosols can be computed through a simple parameterization that is dependent on the aerosol core and shell species, shell thickness, and amount of aerosol liquid water. In this study, a 1-year simulation was conducted for 2013. The updated model successfully reproduced the seasonal and daily observations of O3, fine particulate matter, SO42−, and NO3− concentrations in East Asia. Our results revealed that heterogeneous reactions reduced more surface O3 concentrations (10–20 ppbv) in the polluted regions of East China than did perturbations in photolysis frequencies from aerosols, effectively again improving the comparison between simulations and observations. Oxidation of SO2 by NO2 on wet aerosols significantly enhanced SO42− formation, with sulfate covering approximately ~30–60% of total sulfate concentrations in North China Plain during haze days in winter. The uptake of reactive nitrogen species on aerosols effectively reduced NO3− concentrations and successfully balanced the NOx/HNO3 chemistry in the models. We recommended that larger reductions of gaseous precursors should be considered in China to achieve the national air quality objective. The results show that surface O3 concentrations over East China will increase if the emission of aerosols is reduced without corresponding reductions in O3 precursors.

Singular value decomposition analysis of spatial relationships between monthly weather and air pollution index in China

Spatial patterns are important features for understanding regional air quality variability. Statistical analysis tools, such as empirical orthogonal function (EOF), have been extensively used to identify and classify spatial patterns. These tools, however, do not directly reveal the related weather conditions. This study used singular value decomposition (SVD) to identify spatial air pollution index (API) patterns related to meteorological conditions in China, one of world’s regions facing catastrophic air pollution. The monthly API and four meteorological variables (precipitation, surface air temperature, humidity, and wind speed) during 2001–2012 in 42 cities in China were used. The two leading SVD spatial patterns display the API anomalies with the same sign across China and opposite signs between northern and southern China, respectively. The meteorological variables have different relationships with these patterns. For the first pattern, wind speed is the most important. The key regions, where the correlations between the API field and the wind speed’s SVD time series are significant at the 99% confidence level, are found nationwide. Precipitation and air temperature are also important in the southern and northern portions of eastern China, respectively. For the second pattern, the key regions occur mainly in northern China for temperature and humidity and southern China for wind speed. Air humidity has the largest contribution to this pattern. The weather-API relationships characterized by these spatial patterns are useful for selecting factors for statistical air quality prediction models and determining the geographic regions with high prediction skills.

Source tagging modeling study of heavy haze episodes under complex regional transport processes over Wuhan megacity, Central China

Wuhan as a megacity of Central China was suffering from severe particulate matter pollution according to previous observation studies, however, the mechanism behind the pollution formation especially the impact of regional chemical transport is still unclear. This study, carried out on the Nested Air Quality Prediction Modeling System (NAQPMS) coupled with an on-line source-tagging module, explores different roles regional transport had in two strong haze episodes over Wuhan in October 2014 and quantitatively assesses the contributions from local and regional sources to PM2.5 concentration. Validation of predictions based on observations shows modeling system good skills in reproducing key meteorological and chemical features. The first short-time haze episode occurred on 12 October under strong northerly winds, with a hourly PM2.5 peak of 180 μg m−3, and was found to be caused primarily by the long-range transport from the northern regions, which contributed 60.6% of the episode's PM2.5 concentration (versus a total of 32.7% from sources in and near Wuhan). The second episode lasted from the 15–20 October under stable regional large-scale synoptic conditions and weak winds, and had an hourly PM2.5 peak of 231.0 μg m−3. In this episode, both the long-distance transport from far regions and short-range transport from the Wuhan-cluster were the primary causes of the haze episode and account for 24.8% and 29.2% of the PM2.5 concentration respectively. Therefore, regional transport acts as a crucial driver of haze pollution over Wuhan through not only long-range transfer of pollutants, but also short-range aerosol movement under specific meteorological conditions. The present findings highlight the important role of regional transport in urban haze formation and indicate that the joint control of multi city-clusters are needed to reduce the particulate pollution level in Wuhan.

GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

Abstract. The Global Nested Air Quality Prediction Modeling System (GNAQPMS) is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL). Compared with the first-generation Xeon Phi coprocessor (codenamed Knights Corner, KNC), KNL has many new hardware features such as a bootable processor, high-performance in-package memory and ISA compatibility with Intel Xeon processors. In particular, we describe the five optimisations we applied to the key modules of GNAQPMS, including the CBM-Z gas-phase chemistry, advection, convection and wet deposition modules. These optimisations work well on both the KNL 7250 processor and the Intel Xeon E5-2697 V4 processor. They include (1) updating the pure Message Passing Interface (MPI) parallel mode to the hybrid parallel mode with MPI and OpenMP in the emission, advection, convection and gas-phase chemistry modules; (2) fully employing the 512 bit wide vector processing units (VPUs) on the KNL platform; (3) reducing unnecessary memory access to improve cache efficiency; (4) reducing the thread local storage (TLS) in the CBM-Z gas-phase chemistry module to improve its OpenMP performance; and (5) changing the global communication from writing/reading interface files to MPI functions to improve the performance and the parallel scalability. These optimisations greatly improved the GNAQPMS performance. The same optimisations also work well for the Intel Xeon Broadwell processor, specifically E5-2697 v4. Compared with the baseline version of GNAQPMS, the optimised version was 3.51 × faster on KNL and 2.77 × faster on the CPU. Moreover, the optimised version ran at 26 % lower average power on KNL than on the CPU. With the combined performance and energy improvement, the KNL platform was 37.5 % more efficient on power consumption compared with the CPU platform. The optimisations also enabled much further parallel scalability on both the CPU cluster and the KNL cluster scaled to 40 CPU nodes and 30 KNL nodes, with a parallel efficiency of 70.4 and 42.2 %, respectively.

Model elucidating the sources and formation mechanisms of severe haze pollution over Northeast mega-city cluster in China

Recent studies on regional haze pollution over China come up in general with strong variability of main causes of heavy polluted episodes, in linkage with local specificities, sources and pollution characteristics. This paper therefore aims at elucidating the main specific sources and formation mechanisms of observed strong haze pollution episodes over 1–15 November 2015 in Northeast region considered as one of biggest megacity clusters in China. The Northeast China mega-city cluster, including Heilong Jiang, Jilin and Liaoning provinces, is adjacent to Russia in the north, Mongolian at the west, North Korea at east, and representing key geographical location in the regional and transnational air pollution issues in China due to the presence of heavy industries and intense economic activities. The present study, based on air quality monitoring, remote sensing satellite data and sensitivity experiments carried on the Nested Air Quality Prediction Modeling System (NAQPMS), quantitatively assesses the impact of meteorological conditions and potential contributions from regional chemical transport, intensive energy combustion, illegal emission and biomass burning emissions to PM2.5 concentration variation. The results indicate strong inversion occurrence at lower atmosphere with weak near-surface wind speed and high relative humidity, leading to PM2.5 concentration increase of about 30–50%. Intensive energy combustion (plausibly for heating activities) and illegal emission also significantly enhance the overall PM2.5 accumulation by 100–200 μg m−3 (60–70% increase), against 75–100 μg m−3 from the biomass burning under the northeast-southwest transport pathway, corresponding to a contribution of 10–20% to PM2.5 concentration increase. Obviously, stagnant meteorological conditions, energy combustion, illegal emission and biomass burning are main drivers of strong haze formation and spatial distribution over Northeast China megacity cluster. In clear, much effort on emission abatement at both local and regional scales is still an urgent imperative to overcome current critical haze pollution.

A nonnegativity preserved efficient chemical solver applied to the air pollution forecast

Air pollution forecast is becoming more and more important nowadays. The numerically sticky chemical ordinary differential equations (ODEs) is a critical component of air pollution models. Various solvers have been designed for the chemical ODEs in the past. However, they are either slow or imprecise. In our previous work, we have designed a nonnegativity preserved efficient chemical solver MBE, which is an acronym for Modified-Backward-Euler. In this paper, we review MBE method and prove its convergence and stability mathematically, which guarantee that MBE results converge to the exact solutions as the step-size becomes smaller and MBE results with relatively small step-size can be used as the standard. Then we apply MBE to the Nested Air Quality Prediction Modeling System (NAQPMS). Comparison between MBE and the most popular solver LSODE is also made. Considering the speed and precision, MBE is a better choice for the air pollution forecast.

Estimation of atmospheric aging time of black carbon particles in the polluted atmosphere over central-eastern China using microphysical process analysis in regional chemical transport model

Mixing state of black carbon (BC) particles has significant impacts on their radiative forcing, visibility impairment and the ability in modifying cloud formation. In this study, an aging scheme of BC particles using prognostic variables based on aerosol microphysics was incorporated into a regional atmospheric chemistry model, Nested Air Quality Prediction Modeling System with Advanced Particle Microphysics (NAQPMS + APM), to investigate the temporal and spatial variations in aging time scale of BC particles in polluted atmosphere over central-eastern China. The model results show that the aging time scale has a clear diurnal variation with a lower value in the daytime and a higher value in the nighttime. The shorter aging time scale in the daytime is due to condensation aging associated with intense photochemical reaction while the longer aging time scale in the nighttime is due to coagulation aging, which is much slower than that due to condensation. In Beijing, the aging time scale is 2 h or less in the surface layer in daytime, which is far below the fixed 1.2 days used in many models. As a result, the fraction of hydrophilic BC particles by the new scheme is larger than that by the scheme with fixed aging time scale though the mean aging time scale by the new scheme is much larger than 1.2 days. Hydrophilic fraction of BC particles increases with the increase of height. Over central-eastern China, the averaged aging time scale calculated by the new scheme is in the range from 12 h to 7 days, with higher values in regions far from the source areas. Hydrophilic fraction of BC particles is more than 90% at the higher levels in polluted atmosphere. Difference of simulated BC concentration with internal mixing and microphysical aging is within 5%, indicating that the assumption of internal mixing for BC particles to respond to in-cloud scavenging is more appropriate than the external mixing assumption in polluted atmosphere over central-eastern China.

Significant impacts of heterogeneous reactions on the chemical composition and mixing state of dust particles: A case study during dust events over northern China

The impact of heterogeneous reactions on the chemical components and mixing state of dust particles are investigated by observations and an air quality model over northern China between March 27, 2015 and April 2, 2015. Synergetic observations were conducted using a polarization optical particle counter (POPC), a depolarized two-wavelength Lidar and filter samples in Beijing. During this period, dust plume passed through Beijing on March 28, and flew back on March 29 because of synoptic weather changes. Mineral dust mixed with anthropogenic pollutants was simulated using the Nested Air Quality Prediction Modeling System (NAQPMS) to examine the role of heterogeneous processes on the dust. A comparison of observations shows that the NAQPMS successfully reproduces the time series of the vertical profile, particulate matter concentration, and chemical components of fine mode (diameter ≤ 2.5 μm) and coarse mode (2.5 μm < diameter ≤ 10 μm) particles. After considering the heterogeneous reactions, the simulated nitrate, ammonium, and sulfate are in better agreement with the observed values during this period. The modeling results with observations show that heterogeneous reactions are the major mechanisms producing nitrate reaching 19 μg/m3, and sulfate reaching 7 μg/m3, on coarse mode dust particles, which were almost 100% of the coarse mode nitrate and sulfate. The heterogeneous reactions are also important for fine mode secondary aerosols, for producing 17% of nitrate and 11% of sulfate on fine mode dust particles, with maximum mass concentrations of 6 μg/m3 and 4 μg/m3. In contrast, due to uptake of acid gases (e.g. HNO3 and SO2) by dust particles, the fine mode anthropogenic ammonium nitrate and ammonium sulfate decreased. As a result, the total fine mode nitrate decreased with a maximum of 14 μg/m3, while the total fine mode sulfate increased with a maximum of 2 μg/m3. Because of heterogeneous reactions, 15% of fine mode secondary inorganic aerosols and the entire coarse mode nitrate and sulfate were internally mixed with dust particles. The significant alterations of the chemical composition and mixing state of particles due to heterogeneous reactions are important for the direct and indirect climate effects of dust and anthropogenic aerosols.

Rapid formation of a severe regional winter haze episode over a mega-city cluster on the North China Plain

The Nested Air Quality Prediction Model System (NAQPMS) was used to investigate an extreme regional haze episode persisting over the Beijing-Tianjin-Hebei megacity cluster from November 26 to December 1, 2015. During this extreme haze event, the regional daily mean PM2.5 exceeded 500 μg/m3. We found that local emissions were the main source of haze over Beijing and Hebei in the early formational stage of this episode. The accumulation of regionally transported, highly aged secondary inorganic aerosols (SIA) along the foot of the mountains was responsible (60%) for the rapid increase of surface PM2.5 in Beijing between November 30 and December 1, although PM2.5 concentrations in the source regions of Hebei province were lower. The height of regional transport ranged from 200 to 700 m above ground level, with a slow increase with increasing distance of the source regions from Beijing. This indicates that more attention should be given to point sources at heights of 200–500 m in order to reduce the contribution of transport. The contribution of local emissions to haze in Beijing was mostly concentrated below 300 m above ground level, and was more significant for black carbon (BC) and organic matter (OM) than SIA. Tagging of pollutants by emission time showed that PM2.5 had been aged before it arrived at Beijing, and PM2.5 formed one or more days prior to arrival was twice that formed on the arrival day. This suggests that control measures would be more effective if they were implemented two days prior to haze episodes. In contrast to Beijing, haze in Tianjin was governed by transport from outside sources, whereas in cities located in Hebei province this episode resulted from local emissions.

PM2.5 in the Yangtze River Delta, China: Chemical compositions, seasonal variations, and regional pollution events

Fine particle (PM2.5) samples were collected simultaneously at three urban sites (Shanghai, Nanjing, and Hangzhou) and one rural site near Ningbo in the Yangtze River Delta (YRD) region, China, on a weekly basis from September 2013 to August 2014. In addition, high-frequency daily sampling was conducted in Shanghai and Nanjing for one month during each season. Severe regional PM2.5 pollution episodes were frequently observed in the YRD, with annual mean concentrations of 94.6 ± 55.9, 97.8 ± 40.5, 134 ± 54.3, and 94.0 ± 57.6 μg m−3 in Shanghai, Nanjing, Hangzhou, and Ningbo, respectively. The concentrations of PM2.5 and ambient trace metals at the four sites showed clear seasonal trends, with higher concentrations in winter and lower concentrations in summer. In Shanghai, similar seasonal patterns were found for organic carbon (OC), elemental carbon (EC), and water-soluble inorganic ions (K+, NH4+, Cl−, NO3−, and SO42-). Air mass backward trajectory and potential source contribution function (PSCF) analyses implied that areas of central and northern China contributed significantly to the concentration and chemical compositions of PM2.5 in Shanghai during winter. Three heavy pollution events in Shanghai were observed during autumn and winter. The modelling results of the Nested Air Quality Prediction Modeling System (NAQPMS) showed the sources and transport of PM2.5 in the YRD during the three pollution processes. The contribution of secondary species (SOC, NH4+, NO3−, and SO42-) in pollution event (PE) periods was much higher than in BPE (before pollution event) and APE (after pollution event) periods, suggesting the importance of secondary aerosol formation during the three pollution events. Furthermore, the bioavailability of Cu, and Zn in the wintertime PM2.5 samples from Shanghai was much higher during the pollution days than during the non-pollution days.

Modeling the Long-Range Transport of Particulate Matters for January in East Asia using NAQPMS and CMAQ

ABSTRACTTwo regional chemical transport models were applied to simulate high concentrations of particulate matters (PM) observed in East Asia in January 2015; the first model is the Nested Air Quality Prediction Modeling System (NAQPMS) and the second is the Community Multi-scale Air Quality Model (CMAQ). The variation of PM2.5 in both models showed well agreement with measurements over both eastern China and western Japan. Based on the model results and the aerosol compositions observed in Fukuoka in western Japan, three types of PM long-range transport (LRT) were identified: N-, S-, and D-type. The N episode showed higher fine-mode nitrate (fNO3–) concentrations than fine-mode sulfate (fSO42–), indicating the importance of NO3– LRT. The S episode showed the highest fSO42– concentrations (28.9 µg m–3), which were 3.4-fold higher than fNO3–, due to high relative humidity. During the D episode, dust stagnated in Fukuoka for three days, due to the influence of low- and high-pressure systems; thus, dust LRT is also important in winter besides spring. Both models reasonable explained variations in aerosol components during both N and S episodes; however, both underestimated fSO42– especially during D episode, suggesting that they may miss certain emissions or chemical mechanisms. High coarse-mode NO3– (cNO3–) concentrations (maximum: 6.3 µg m–3), and high cNO3–/fNO3– ratios (maximum: 1.2) were observed during D episode. NAQPMS successfully captured this cNO3– peak after including heterogeneous reactions on dust. Our results emphasize the importance of such heterogeneous processes for understanding the LRT of dust and anthropogenic pollutants over East Asia.

Regional Impact of Biomass Burning in Southeast Asia on Atmospheric Aerosols during the 2013 Seven South-East Asian Studies Project

ABSTRACTA nested air quality prediction modeling system (NAQPMS) with an online tracer-tagged module was utilized to investigate the regional impact of biomass burning (BB) on aerosols and source–receptor relationships in Southeast Asia during March–April 2013. NAQPMS could reproduce the three-dimensional spatial distribution of aerosols. Both monthly and episodic analyses indicated that BB significantly contributed to surface and column aerosol concentrations in Southeast Asia along two long-range transport pathways. In the first pathway, aerosols from BB were blown northward from the Indochina peninsula to southwestern provinces in China. The mean contributions of BB decreased from 70%–80% in the source regions to 10%–40% in southwestern China. Myanmar was the largest exporter. In the second pathway, PM2.5 emitted by BB was uplifted into the mid-altitudes (2000 m) in the Indochina peninsula and transported eastward to the western Pacific at altitudes of 2500–4000 m, passing the South China Sea, southern China and western Pacific. In downwind regions, BB contributed 30%–60% of aerosols at altitudes of 2000–4000 m and 10%–30% below 2000 m. A simple estimation based on source–receptor relationships showed that BB emissions were likely overestimated by 35%–50% in the Fire Inventory from National Center for Atmospheric Research (v1.5).

Development of an on-line source-tagged model for sulfate, nitrate and ammonium: A modeling study for highly polluted periods in Shanghai, China

An on-line source-tagged model coupled with an air quality model (Nested Air Quality Prediction Model System, NAQPMS) was applied to estimate source contributions of primary and secondary sulfate, nitrate and ammonium (SNA) during a representative winter period in Shanghai. This source-tagged model system could simultaneously track spatial and temporal sources of SNA, which were apportioned to their respective primary precursors in a simulation run. The results indicate that in the study period, local emissions in Shanghai accounted for over 20% of SNA contributions and that Jiangsu and Shandong were the two major non-local sources. In particular, non-local emissions had higher contributions during recorded pollution periods. This suggests that the transportation of pollutants plays a key role in air pollution in Shanghai. The temporal contributions show that the emissions from the “current day” (emission contribution from the current day during which the model was simulating) contributed 60%–70% of the sulfate and ammonium concentrations but only 10%–20% of the nitrate concentration, while the previous days’ contributions increased during the recorded pollution periods. Emissions that were released within three days contributed over 85% averagely for SNA in January 2013. To evaluate the source-tagged model system, the results were compared by sensitivity analysis (emission perturbation of −30%) and backward trajectory analysis. The consistency of the comparison results indicated that the source-tagged model system can track sources of SNA with reasonable accuracy.