scholarly journals Numerical analysis of agricultural emissions impacts on PM<sub>2.5</sub> in China using a high-resolution ammonia emission inventory

2020 ◽  
Vol 20 (16) ◽  
pp. 9979-9996
Author(s):  
Xiao Han ◽  
Lingyun Zhu ◽  
Mingxu Liu ◽  
Yu Song ◽  
Meigen Zhang
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Source Apportionment ◽  
Mass Concentration ◽  
Emission Inventory ◽  
Atmospheric Modeling ◽  
Central China ◽  
High Mass ◽  
Nh3 Emission ◽  
The Impact

Abstract. China is one of the largest agricultural countries in the world. Thus, NH3 emission from agricultural activities in China considerably affects the country's regional air quality and visibility. In this study, a high-resolution agricultural NH3 emission inventory compiled on 1 km × 1 km horizontal resolution was applied to calculate the NH3 mass burden in China and reliably estimate the influence of NH3 on agriculture. The key parameter emission factors of this inventory were enhanced by considering many experiment results, and the dynamic data of spatial and temporal information were updated using statistical data of 2015. In addition to fertilizers and husbandry, farmland ecosystems, livestock waste, crop residue burning, wood-based fuel combustion, and other NH3 emission sources were included in this inventory. Furthermore, a source apportionment tool, namely, the Integrated Source Apportionment Method (ISAM) coupled with the air quality modeling system Regional Atmospheric Modeling System and Community Multiscale Air Quality, was applied to capture the contribution of NH3 emitted from total agriculture (Tagr) in China. The aerosol mass concentration in 2015 was simulated, and results showed that the high mass concentration of NH3 exceeded 10 µg m−3 and mainly appeared in the North China Plain, Central China, the Yangtze River Delta, and the Sichuan Basin. Moreover, the annual average contribution of Tagr NH3 to PM2.5 mass burden was 14 %–22 % in China. Specific to the PM2.5 components, Tagr NH3 contributed dominantly to ammonium formation (87.6 %) but trivially to sulfate formation (2.2 %). In addition, several brute-force sensitivity tests were conducted to estimate the impact of Tagr NH3 emission reduction on PM2.5 mass burden. In contrast to the result of ISAM, even though the Tagr NH3 only provided 10.1 % contribution to nitrate under the current emission scenario, the reduction of nitrate could reach 95.8 % upon removal of the Tagr NH3 emission. This deviation occurred because the contribution of NH3 to nitrate should be small under a “rich NH3”environment and large under a “poor NH3” environment. Thus, the influence of NH3 on nitrate formation would be enhanced with the decrease in ambient NH3 mass concentration.

scholarly journals Numerical analysis of the impact of agricultural emissions on PM<sub>2.5</sub> in China using a high-resolution ammonia emissions inventory

2020 ◽  
Author(s):  
Xiao Han ◽  
Lingyun Zhu ◽  
Mingxu Liu ◽  
Yu Song ◽  
Meigen Zhang
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Source Apportionment ◽  
Mass Concentration ◽  
Atmospheric Modeling ◽  
Central China ◽  
High Mass ◽  
Emissions Inventory ◽  
Aerosol Mass Concentration ◽  
The Impact

Abstract. China is one of the largest agricultural countries in the world. The NH3 emissions from agricultural activities in China significantly affect regional air quality and horizontal visibility. To reliably estimate the influence of NH3 on agriculture, a high-resolution agricultural NH3 emissions inventory, compiled with a 1 km × 1 km horizontal resolution, was applied to calculate the NH3 mass burden in China. The key emission factors of this inventory were enhanced by considering the results of many native experiments, and the activity data of spatial and temporal information were updated using statistical data from 2015. Fertilizer and husbandry, as well as farmland ecosystems, livestock waste, crop residue burning, fuel wood combustion, and other NH3 emission sources were included in the inventory. Furthermore, a source apportionment tool, ISAM (Integrated Source Apportionment Method), coupled with the air quality modeling system RAMS-CMAQ (Regional Atmospheric Modeling System and Community Multiscale Air Quality), was applied to capture the contribution of NH3 emitted from total agriculture (Tagr) in China. The aerosol mass concentration in 2015 was simulated, and the results showed that a high mass concentration of NH3, which exceeded 10 μg m−3, appeared mainly in the North China Plain (NCP), Central China (CNC), the Yangtz River Delta (YRD), and the Sichan Basin (SCB), and the annual average contribution of Tagr NH3 to PM2.5 mass burden in China was 14–18 %. Specific to the PM2.5 components, Tagr NH3 provided a major contribution to ammonium formation (87.6 %) but a tiny contribution to sulfate (2.2 %). In addition, several brute-force sensitivity tests were conducted to estimate the impact of Tagr NH3 emissions reduction on the PM2.5 mass burden. Compared with the results of ISAM, it was found that even though the Tagr NH3 only contributed 10.1 % of nitrate under current emissions scenarios, the reduction of nitrate could reach 98.8 % upon removal of the Tagr NH3 emissions. The main reason for this deviation could be that the NH3 contribution to nitrate is small under rich NH3 conditions and large in poor NH3 environments. Thus, the influence of NH3 on nitrate formation could be enhanced with the decrease of ambient NH3 mass concentration.

scholarly journals Are contributions of emissions to ozone a matter of scale? – a study using MECO(n) (MESSy v2.50)

2020 ◽  
Vol 13 (1) ◽  
pp. 363-383 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Volker Grewe ◽  
Patrick Jöckel ◽  
Robert Sausen
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Emission Inventory ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Model Resolution ◽  
Regional Models ◽  
Continental Scale ◽  
The Impact ◽  
Apportionment Methods

Abstract. Anthropogenic and natural emissions influence the tropospheric ozone budget, thereby affecting air quality and climate. To study the influence of different emission sources on the ozone budget, often source apportionment studies with a tagged tracer approach are performed. Studies investigating air quality issues usually rely on regional models with a fine spatial resolution, while studies focusing on climate-related questions often use coarsely resolved global models. It is well known that simulated ozone mixing ratios depend on the resolution of the model and the resolution of the emission inventory. Whether the contributions simulated using source apportionment approaches also depend on the model resolution, however, is still unclear. Therefore, this study attempts for the first time to analyse the impact of the model, the model resolution, and the emission inventory resolution on simulated ozone contributions using a diagnostic tagging method. The differences in the ozone contributions caused by these factors are compared with differences that arise from the usage of different emission inventories. To do so, we apply the MECO(n) (MESSy-fied ECHAM and COSMO models nested n times) model system which couples online a global chemistry-climate model with a regional chemistry-climate model equipped with a tagging scheme for source apportionment. The results of the global model (at 300 km horizontal resolution) are compared with the results of the regional model at 50 km (Europe) and 12 km (Germany) resolutions. Besides model-specific differences and biases that are discussed in detail, our results have important implications for other modelling studies and modellers applying source apportionment methods. First, contributions from anthropogenic emissions averaged over the continental scale are quite robust with respect to the model, model resolution, and emission inventory resolution. Second, differences on the regional scale caused by different models and model resolutions can be quite large, and regional models are indispensable for source apportionment studies on the subcontinental scale. Third, contributions from stratospheric ozone transported to the surface differ strongly between the models, mainly caused by differences in the efficiency of the vertical mixing. As stratospheric ozone plays an important role for ground level ozone, but the models show large differences in the amount of downward transported ozone, source apportionment methods should account for this source explicitly to better understand inter-model differences.

scholarly journals TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling

2014 ◽  
Vol 14 (20) ◽  
pp. 10963-10976 ◽  
Author(s):  
J. J. P. Kuenen ◽  
A. J. H. Visschedijk ◽  
M. Jozwicka ◽  
H. A. C. Denier van der Gon
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
High Resolution ◽  
Emission Inventory ◽  
Point Sources ◽  
Air Quality Modelling ◽  
Emission Data ◽  
Data Set ◽  
Spatially Distributed ◽  
Reported Data

Abstract. Emissions to air are reported by countries to EMEP. The emissions data are used for country compliance checking with EU emission ceilings and associated emission reductions. The emissions data are also necessary as input for air quality modelling. The quality of these "official" emissions varies across Europe. As alternative to these official emissions, a spatially explicit high-resolution emission inventory (7 × 7 km) for UNECE-Europe for all years between 2003 and 2009 for the main air pollutants was made. The primary goal was to supply air quality modellers with the input they need. The inventory was constructed by using the reported emission national totals by sector where the quality is sufficient. The reported data were analysed by sector in detail, and completed with alternative emission estimates as needed. This resulted in a complete emission inventory for all countries. For particulate matter, for each source emissions have been split in coarse and fine particulate matter, and further disaggregated to EC, OC, SO4, Na and other minerals using fractions based on the literature. Doing this at the most detailed sectoral level in the database implies that a consistent set was obtained across Europe. This allows better comparisons with observational data which can, through feedback, help to further identify uncertain sources and/or support emission inventory improvements for this highly uncertain pollutant. The resulting emission data set was spatially distributed consistently across all countries by using proxy parameters. Point sources were spatially distributed using the specific location of the point source. The spatial distribution for the point sources was made year-specific. The TNO-MACC_II is an update of the TNO-MACC emission data set. Major updates included the time extension towards 2009, use of the latest available reported data (including updates and corrections made until early 2012) and updates in distribution maps.

scholarly journals Development of PM<sub>2.5</sub> source impact spatial fields using a hybrid source apportionment air quality model

2015 ◽  
Vol 8 (7) ◽  
pp. 2153-2165 ◽  
Author(s):  
C. E. Ivey ◽  
H. A. Holmes ◽  
Y. T. Hu ◽  
J. A. Mulholland ◽  
A. G. Russell
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Large Scale ◽  
Major Ions ◽  
Current Knowledge ◽  
Direct Method ◽  
Hybrid Approach ◽  
Sensitivity Analyses ◽  
Adjustment Factors ◽  
The Impact

Abstract. An integral part of air quality management is knowledge of the impact of pollutant sources on ambient concentrations of particulate matter (PM). There is also a growing desire to directly use source impact estimates in health studies; however, source impacts cannot be directly measured. Several limitations are inherent in most source apportionment methods motivating the development of a novel hybrid approach that is used to estimate source impacts by combining the capabilities of receptor models (RMs) and chemical transport models (CTMs). The hybrid CTM–RM method calculates adjustment factors to refine the CTM-estimated impact of sources at monitoring sites using pollutant species observations and the results of CTM sensitivity analyses, though it does not directly generate spatial source impact fields. The CTM used here is the Community Multiscale Air Quality (CMAQ) model, and the RM approach is based on the chemical mass balance (CMB) model. This work presents a method that utilizes kriging to spatially interpolate source-specific impact adjustment factors to generate revised CTM source impact fields from the CTM–RM method results, and is applied for January 2004 over the continental United States. The kriging step is evaluated using data withholding and by comparing results to data from alternative networks. Data withholding also provides an estimate of method uncertainty. Directly applied (hybrid, HYB) and spatially interpolated (spatial hybrid, SH) hybrid adjustment factors at withheld observation sites had a correlation coefficient of 0.89, a linear regression slope of 0.83 ± 0.02, and an intercept of 0.14 ± 0.02. Refined source contributions reflect current knowledge of PM emissions (e.g., significant differences in biomass burning impact fields). Concentrations of 19 species and total PM2.5 mass were reconstructed for withheld observation sites using HYB and SH adjustment factors. The mean concentrations of total PM2.5 at withheld observation sites were 11.7 (± 8.3), 16.3 (± 11), 8.59 (± 4.7), and 9.2 (± 5.7) μg m−3 for the observations, CTM, HYB, and SH predictions, respectively. Correlations improved for concentrations of major ions, including nitrate (CMAQ–DDM (decoupled direct method): 0.404, SH: 0.449), ammonium (CMAQ–DDM: 0.454, SH: 0.492), and sulfate (CMAQ–DDM: 0.706, SH: 0.730). Errors in simulated concentrations of metals were reduced considerably: 295 % (CMAQ–DDM) to 139 % (SH) for vanadium; and 1340 % (CMAQ–DDM) to 326 % (SH) for manganese. Errors in simulated concentrations of some metals are expected to remain given the uncertainties in source profiles. Species concentrations were reconstructed using SH results, and the error relative to observed concentrations was greatly reduced as compared to CTM-simulated concentrations. Results demonstrate that the hybrid method along with a spatial extension can be used for large-scale, spatially resolved source apportionment studies where observational data are spatially and temporally limited.

scholarly journals Modeling analysis of the seasonal characteristics of haze formation in Beijing

2014 ◽  
Vol 14 (18) ◽  
pp. 10231-10248 ◽  
Author(s):  
X. Han ◽  
M. Zhang ◽  
J. Gao ◽  
S. Wang ◽  
F. Chai
Keyword(s):  
Air Quality ◽  
Relative Humidity ◽  
Formation Mechanism ◽  
Mass Concentration ◽  
Atmospheric Modeling ◽  
Aerosol Optical Property ◽  
The North ◽  
Seasonal Characteristics ◽  
Different Seasons ◽  
Haze Formation

Abstract. The air quality modeling system RAMS-CMAQ (Regional Atmospheric Modeling System–Community Multiscale Air Quality), coupled with an aerosol optical property scheme, was applied to simulate the meteorological field, major aerosol components (sulfate, nitrate, ammonium, black carbon, organic carbon, dust, and sea salt), and surface visibility over the North China Plain (NCP) in 2011. The modeled results in February and July 2011 were selected and analyzed to obtain an in-depth understanding of the haze formation mechanism in Beijing for different seasons. The simulation results showed that the visibility was below 10 km for most regions of the NCP, and dropped to less than 5 km over the megacities of Beijing and Tianjin, the whole of Hebei Province, and the northwest part of Shandong Province during pollution episodes in February and July. The heavy mass concentration of PM2.5 ranged from 120 to 300 μg m−3 and was concentrated in the areas with low visibility. The haze formation mechanism in Beijing in winter was different from that in summer. The mass concentration of PM2.5 was higher, and the components more complicated, in winter. While the mass concentration of PM2.5 in summer was lower than that in winter, the mass concentrations of hygroscopic inorganic salts were comparable with those in winter, and the relative humidity was, as expected, higher. Therefore, the water uptake of hygroscopic aerosols played a key role in summer. Moreover, the analysis showed that the influence of the PM2.5 mass burden on visibility was very weak when its value was larger than 100 μg m−3. Only when the mass burden of PM2.5 decreased to a certain threshold interval did the visibility increase rapidly. This indicates that, when emission reduction measures are taken to control haze occurrence, the mass burden of PM2.5 must be cut to below this threshold interval. The relationship between the threshold of haze occurrence and the relative humidity in Beijing was fitted by an exponential function, and the resulting fitting curves could provide a new theoretical basis to understand and control haze formation in Beijing.

scholarly journals High resolution modelling of aerosol dispersion regimes during the CAPITOUL field experiment: from regional to local scale interactions

2011 ◽  
Vol 11 (15) ◽  
pp. 7547-7560 ◽  
Author(s):  
B. Aouizerats ◽  
P. Tulet ◽  
G. Pigeon ◽  
V. Masson ◽  
L. Gomes
Keyword(s):  
Air Quality ◽  
High Resolution ◽  
Field Experiment ◽  
Aerosol Particle ◽  
Pollutant Dispersion ◽  
Local Scale ◽  
Plume Dispersion ◽  
Urban Dynamics ◽  
The Impact ◽  
Resolution Simulation

Abstract. High resolution simulation of complex aerosol particle evolution and gaseous chemistry over an atmospheric urban area is of great interest for understanding air quality and processes. In this context, the CAPITOUL (Canopy and Aerosol Particle Interactions in the Toulouse Urban Layer) field experiment aims at a better understanding of the interactions between the urban dynamics and the aerosol plumes. During a two-day Intensive Observational Period, a numerical model experiment was set up to reproduce the spatial distribution of specific particle pollutants, from the regional scales and the interactions between different cities, to the local scales with specific turbulent structures. Observations show that local dynamics depends on the day-regime, and may lead to different mesoscale dynamical structures. This study focuses on reproducing these fine scale dynamical structures, and investigate the impact on the aerosol plume dispersion. The 500-m resolution simulation manages to reproduce convective rolls at local scale, which concentrate most of the aerosol particles and can locally affect the pollutant dispersion and air quality.

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