Z. Wang? & H. Terada*€¦ · of the acid rain. During the last decade, comprehensive air quality...

A numerical study on acid rain and

neutralization by yellow-sand in East Asia

H. Ueda\ Z. Wang? & H. Terada*

Disaster Prevention Research Institute, Kyoto University, Japan

*FRSGC, Institute for Global Change Research, Japan

Abstract

An Air Quality Prediction Modeling System (AQPMS) was used to investigatethe neutralization of acid rain by yellow-sand in East Asia. A new deflationmodule of the yellow sand was designed to provide explicit information on thedust loading. Different from the previous ones for Sahara and Australian deserts,it included three major predictors, i.e., the friction velocity; the surface humidityand the predominant weather system. It was linked to AQPMS, which consistedof the advection, diffusion, dry and wet deposition, gas-phase chemistry and theliquid-phase chemistry. The predicted pH values and sulfate- and nitrate-ionlevels of precipitation, together with the surface concentrations of gaseouspollutants, were compared with measured values and a reasonable agreementwas obtained. The simulation results of April 1995 exhibited a strongneutralization of the precipitation by the yellow-sand. The monthly mean pHvalues in the northern China, Korea and Japan showed a remarkable increase of0.4-1.2, while the increase in the southern China was less than 0.1.

1 Introduction

Acid rain has been one of the serious environmental problems in East Asia forthe rapid industrialization in the last two decades. High-sulfur fossil fuels widelyused in the area results in the high-level sulfur in rainwater. The contour line ofpH value less than 5 has come up to the Yellow River region (35°N) from thesouthern China bounded by the Yangtze River (25°N) during these ten years.However, in spite of the SC>2 concentrations being almost at the same level as thesouthern China, acid rain in the northern China occurs seldom. Purpose of thisresearch is to make clear this reason quantitatively, supposing that alkaline soil

Air Pollution VIII, C.A. Brebbia, H. Power & J.W.S Longhurst (Editors) © 2000 WIT Press, www.witpress.com, ISBN 1-85312-822-8

120 Air Pollution VIII

dust, i.e., the so-called yellow sand soaring up from Asian deserts and Loessplateau and prevailing over the northern China, is responsible for neutralizationof the acid rain.

During the last decade, comprehensive air quality models have been used toassess air pollution and acid deposition and to develop effective emission controlstrategies for North America and Europe. These models attempt to implement adetailed, updated treatment of the transport, chemical transformation, cloudeffects, emission and dry and wet deposition. The Air Quality Prediction Model-ing System (AQPMS) is designed to simulate the chemistry and meteorology ofthe entire depth of the troposphere and to study the development and movementof the yellow-sand and its effects on the formation of acid rain in East Asia [4]. Anew deflation module of the yellow sand was designed to provide explicitinformation on the dust loading. The structure of AQPMS is briefly described insection 2 and model validation is shown in section 3. Simulations results of pHvalue in rain conducted for the yellow-sand (the so-called Kosa) in April 1995are provided in section 4. Major conclusions are summarized in section 5.

2 Model description

The model system outlined here is an Eulerian transport, transformation andremoval model which includes all the major processes such as emission, advec-tion, diffusion, chemistry, dry deposition, wet deposition and micro-physicalprocesses. It simulates time-varying three-dimensional distributions of tracegases and yellow-sand particles, as well as temporal and special distribution ofdry and wet deposition of atmospheric tracer species. In a spherical andteirain-following coordinate, the model solves a set of chemical species con-servation equations which can be described mathematically by

where C is the species concentration, t is the time, 0 and cp are the latitude andlongitude, R is the Earth radius, K& K^ and K& are the diffusion coefficients indifferent directions, u, v are the horizontal wind velocities, W is the equivalentvertical velocity, E is the emission intensity, Pchm and Lchm are the production andloss rates due to gas-phase and aqueous chemical interactions. (6C45%et is thetime rate of change of concentration due to scavenging process such as rainoutand washout, and (dC/dt) represents the changes in concentration due to drydeposition. The terrain-following height coordinate a reads


Air Pollution VIII 121

where H(6,cp) is the height of the tropopause layer, h(9,cp) the height of relief,and z the geopotential height.

The removal term is usually divided into dry removal due to sedimentationand deposition at surface and wet removal due to precipitation. The dry removalmechanism reconstructed by Zhang et al. [6] is adopted here to estimate drydeposition. The efficiency of wet removal by rain is usually described by thescavenging ratio A [4] ,

A = 10.8'E /D (3)

where E is the coagulation kernel (set as 0.83), R is the rainfall intensity (mm/hour), and Dp is the depth of cloud or model layer .

The gas-phase chemical reaction scheme used in the present work is aslightly modified version of the CBM-IV. Values of the reaction rate coefficientare updated with recent kinetic data and more detailed chemistry of SOx isincorporated [5]. The modified mechanism includes 34 species and 86photochemical, inorganic and organic reactions. 11 active species are predictedfrom the full equation of mass conservation including advection and diffusion,while reactive agents like radicals are calculated by the pseudo equilibriumassumption.

Changes in trace species concentrations due to chemical reactions ofsoluble and reactive gases in in-cloud and below-cloud droplets are computedusing a box aqueous chemical model. Cloud and rainwater composition iscomputed using a hybrid equilibrium and kinetic chemical model that isdescribed by Chang et al. [1]. The following balance is assumed to be main-tained at all times:

(4)Concentration of each of these ions are determined from Henry's law,dissociation equilibrium and liquid phase reactions [2,3]. Since those processesare strongly dependent on H* ion concentration [H*], concentrations of these ionsmust be calculated by an iteration method. SO] is oxidized by f O:, 63,hydrogen peroxide and tracer metals (Mn and Fe ). Tracer metal emissions areobtained from the deflation model.

The model uses emissions of SO], sulfate, NO, NO:, N%, CO and VOC,which are derived from GEIA datasets and RAINS-ASIA emission datasets. Allemissions were spatially aggregated into the appropriate model grids

Yellow-sand particles are divided into nine bins from 0.5pm to 90p.m in themodel. In each of the size bins we distinguish three types of aerosols. The firsttype is not allowed to grow by depleting vapors, but can grow by coagulation.Examples of this type include yellow-sand, sea salt and carbon particles. Thesecond type such as water droplets and sulfuric acid aerosols undergoes con-densation growth. The third type is the mixture of the first two kinds. The sizespectrum of yellow-sand depends on the deflation, gravitational settling, in-cloudand under-cloud micro-physical processes and washout by precipitation. A new



parameterization for the dust uptake is designed to estimate the dust loading byanalyzing in detail the meteorological condition, landform and climatebackground on the bases of the daily weather reports at about 300 local weatherstations in the northern China. Most of dust deflation occurs in the area from 35°to 50°N and 90° to 110°E, which is coincided with the arid regions and the LoessPlateau. The potential source areas are divided into several distinctive typesincluding desert, the Loess plateau, grassland, cultivated land and deciduousforest. The size distribution and weight factor of the dust load are considered tochange with latitude and season for each land type. Three major predictors,characterizing the mobilization process, are used in the module. (I) the frictionvelocity threshold, (II) the surface humidity threshold and (III) the predominantweather condition. The comparison of module results, using these 3 parametersaltogether or separately, with observed data of dust deflation, showed that thebest estimate can be obtained by considering the three predictors altogether whenwe accept the criteria as the minimum of the total error ratio. A good per-formance is obtained by the numerical model coupled with the deflation modulefor the main features of the yellow-sand life cycle. The emission intensity Qwhich depends on kinematics condition at the lowest model level, is calculatedby

a =C,CXj/(l-u ,/<,,). ,,,. ,,,, (5)

where the unit of (?,,;,/is kg.nf\s"\ C;is the weight factor for different landtype(Wang, et al. 2000), Cj is a constant depending on experiments and set as 2.9x10"**, ii*jjj is the kinematic friction velocity, %*%/,/ is the threshold value of %*,•/,,and Ryj is the fraction of /-th bin of deflating yellow-sand and is obtained fromthe spectrum distribution of dust in source areas. The humidity factor W i isdefined as

{ (\-RHIRHt) for RH<RH,W — J (f>\'-'''[ 0 for RH>RH, ^ '

where RH ,RHo are the surface relative humidity and its critical value.In the tracer code, a time splitting algorithm is used to calculate separately

the effects on species concentrations of advective and diffusive transport,chemistry and micro-physics. A simplified but very accurate, mass conservativeadvection algorithm is used to solve the three-dimensional mass conservationequation (1) with a time-splitting technique. Time step was chosen as 10 minutesby the CFL condition, i.e., the Courant number (uAt/Ax) being less than 1. Theboundary conditions used to solve equation (1) are set as these: yellow-sand cantransport out of but not into the boundary. The bottom surface is assumed as anabsorbing boundary while the top boundary as a closed one.

The current model domain covers the East Asia from 16°N to 60°N, andfrom 72°E to 146°E with horizontal grids at l°xl° resolution. It includes theHimalayas, Tibet to the west, Korea and Japan to the east, south Siberia to thenorth, Taiwan and Hong Kong to the south, and Gobi and Taklanakan deserts, theLoess plateau, Beijing and Chongqing at the center. The vertical extent consistsof eighteen layers from the surface to tropopause along a terrain-following height



coordinate.Numerical simulation was performed for two cases, that is, with and without

the neutralization effects of Kosa. When it is desolved in water droplets, Kosaneutralizes acid rain by such a reaction as

Here, Kosa is assumed to contain 10wt% of Ca and 2wt%

3 Results and discussion

3.1 Weather system

The present investigation was made for April, since the yellow sand stormsoccurred most frequently in that month and prevailed over the north-eastern Asia.Numerical simulation was performed for one month, from 1 April to 30 April1995. In that period moving high and low pressure systems passed through Asiafrom west to east and the cold fronts associated with the moving low pressuresystems blew up a large amount of yellow sand.

3.2 Model validation

For model validation, nine grids of l*xl° in Japan were selected, which werelocated in the continental outflow and spanned from 27°N to 43 °N as shown inFig.2. The observed gaseous surface concentrations in these grids werecalculated by the 1/r weighted interpolation from the data of 2000 atmosphericmonitoring stations, while the observed liquid phase concentrations were fromthose of the 3rd Acid Rain Monitoring made by Japan Environmental Agency.

As seen in Fig.l, the simulated results were compared fairly well with theobservations. The observed monthly mean surface concentrations of SO: andNO: ranged from 1 to 12ppb and from 3 to 38ppb, respectively. The presentmodel predicted well their locality and values. Overestimation was seen in theNO concentration. That was considered to be due to the rapid destruction of NOto NO2 and to MV within one horizontal grid size in the real atmosphere and tobe inherent in the present regional model.

Figure 2 presents the simulated monthly mean surface concentration ofKosa of which diameter is less than 10/z m. Even in Japan Kosa increased thespm concentration by 10 to 20 //g/m , which accorded with the observed in-crease, compared with other months.

Fairly good agreement was also obtained between the predicted and ob-served liquid phase concentrations of SO ~ and NOg and pH values in rainwater,although the model predicted a little smaller pH values. Thus, it can be con-cluded that the present model may reproduce the air pollution, Kosa event andacid rain in East Asia.



NO

40

30

20

10

0

9 8 7 6 543 2 1

NO,

9 8 7 6 5 4 3 2 1

SO, pH

54.54

3.53

2.52

9 8 7 6 5 4 3 2

(III I l l l^ % #• % %5 ^ % ^5 %# # #N ^l# # #l#

9 8 7 6 5 4 3 2 1

so.2-

60

40

20

0

in

9 8 7 6 5 4 3 2 1 9 8 7 6 5 4 3 2 1

Figure 1: Comparison of simulated results with observed values for the monthlymean concentrations of the gas-phase NO, NO], and SO: [ppb], the pHvalue, and concentrations of sulfate and nitrate [ M eq/0 in rainwater,respectively. The columns' number from the right to left represents thedifferent site shown in Fig. 2. The black column shows the observedvalue, while the shaded represents the simulated one.

3.3 Distributions of Kosa, pollutants and acid rain

As seen in Fig.2, Kosa was emitted from deserts and the Loess plateau and co-vered throughout the northern half of China. It was transported by the seasonalwesterly wind to Korea and Japan. Simulated monthly mean surface con-centrations of nitrate and sulfate and pH value in rainwater were presented in



Figs.3 and 4 in which values in the area with the monthly mean precipitationbeing less than 0.1 mm/h was not plotted. In contrast to the distributions of SO]and NOx which were concentrated locally to large emission areas such as megacities and industrial areas (not shown), long-lived species like Kosa, nitrate andsulfate spread several 1000km. High concentration zones of nitrate and sulfatewere created from the Chinese coastal area, via Korea to central Japan. Moreclear zonal distributions could be seen in Kosa storm events (not shown). It wasalso understood quantatively from the observed data in Japan. As seen in Fig.l,locality of SO] and NO] concentrations observed in grids 1,2,7 and 9 weresmoothed out in the concentration distributions of nitrate and sulfate.

Meo/n,

55-

50-

45-

40

35-

30-

25-

20-

80 85 90 95 100 105 110 115 120 125 130 135 140 145

Figure 2: Simulated mean surface Kosa concentration (/z g/m3) in April 1995.The numbers (1-9) represent the locations of 9 observed sites in Japanfor the model validation.

The concentration of sulfate was much larger than that of nitrate. It indicatesthat acidity of rainwater was mainly controlled by sulfate. In Fig.4, the mean pHshowed remarkably similar distribution to sulfate. Again low pH zone wascreated from the Chinese coastal area, via Korea to central Japan. In contrast,high pH values were surrounding the arid area in the northern China (blank inFig.4). Those values were much larger than that of pure rainwater saturated bycarbon dioxide, i.e., 5.4. Moreover, rainwater suffered by Kosa storms some-times showed alkaline pH values, i.e., more than 7. It suggests that theconcentrated Kosa works to neutralize acid rain. These neutralization effects ofKosa are examined in the next section.



#03- in, rain, /or ^prif,

55-

50

45

40-

35-

30-

25-

20-

55-

50-

45-

40-

35-

30-

25-

20-

/A ' x>

80 85 90 95 100 105 110 115 120 125 130 135 140 145

Mean S04= in rain(fj,eq/l) for April,1995

80 85 90 95 100 105 110 115 120 125 130 135 140 145

Figure 3: Simulated mean nitrate and sulfate concentrations (// eq/0 rainwaterin April 1995, respectively.



55-

50-

45-

40-

35-

30-

25-

20-

o \Ci'/\.4.5 * •;-

/A

flO 85 90 95 100 105 110 115 120 125 130 135 140 145

Figure 4: Simulated mean pH in rainwater in April 1995.

80 85 90 95 1WJ05 110 115JW 125 130 135 140 1450.1 0.2 0.5

Figure 5: Difference of pH values in rainwater with and without neutralizationreactions by Kosa in April 1995.


128 /Wr fo//w OM K///

3.4 Effects of Kosa neutralization on rainwater

A numerical experiment was performed by neglecting the neutralizationreactions by Kosa and remaining others under the same conditions in the presentmodel. Comparison of the simulated results with and without neutralizationreactions was made in Fig. 5 which represented the difference of pH values inrainwater with and without neutralization reactions. Around Taklamakan andGobi deserts and the Loess plateau which were Kosa emission areas, the dif-ference in the monthly mean pH values attained 1.8 to 2.0. When compared withKosa concentration distribution (Fig.2), similarity between these distributions isclear. It indicates that neutralization effects of Kosa is significant on the acidityof rainwater. Even in Japan Kosa caused increase of the pH value by 0.1 to 0.2.In contrast, the increase in the southern China was less than 0.1.

4 Conclusion

An Air Quality Prediction Modeling System (AQPMS) was used to investigatethe neutralization of acid rain by yellow-sand in East Asia. The predicted pHvalues and sulfate- and nitrate-ion levels of precipitation, together with the sur-face concentrations of gaseous pollutants, were compared with measured valuesand a reasonable agreement was obtained. The simulation results of April 1995exhibited a strong neutralization of the precipitation by the yellow-sand. Themonthly mean pH values in the northern China, Korea and Japan showed aremarkable increase of 0.4-1.2, while the increase in the southern China was lessthan 0.1.

References

[1] Chang, J. S., Brost, R. A., Isaksen, I S. A., Madronich, S., Middleton, P.,Stockwell, W.R. & Walcek, C.J. A three-dimensional Eulerian acid depositionmodel: Physical concepts and formulation. J. Geophys. Res., 92, 14681-14700, 1987.

[2] Seinfeld, J. H and S. N. Pandis, 1998: Atmospheric chemistry and physics,John Wiley & Sons, 1326pp.

[3] Ueda, H, T Takemoto, Y-P Kim and W Sha, 2000: Behaviors of volatileinorganic components in urban aerosols. Atmos. Environment, 34, 353-361.

[4] Wang, Z, W Sha and H Ueda, 2000: Numerical modeling of pollutanttransport and chemistry during a high-ozone event in northern Taiwan. Tellus,528,411-428.

[51 Wang, Z, Huang, M, He, D, Xu, H & Zhou, L Sulfur distribution andtransport studies in East Asia using Eulerian model. Adv. Atmos. Set., 13, pp.399-409, 1996.

[6] Zhang X. Y, Akimoto, R, Zhu, G.H., Chen, T. & Zhang, GY Concentration,size-distribution and deposition of mineral aerosol over Chinese desertregions. Tellus, SOB, 317-330, 1998.


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