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    Effect of Urbanization on the Urban Meteorology and Air Pollution in Hangzhou

    2015-12-12 12:56:55LIUHongnian1劉紅年MAWanli2馬萬(wàn)里QIANJjunlong1錢(qián)俊龍CAIJuzhen3蔡菊珍YEXianman4葉賢滿LIJiahui1李佳慧andWANGXueyuan1王學(xué)遠(yuǎn)
    Journal of Meteorological Research 2015年6期
    關(guān)鍵詞:劉紅

    LIU Hongnian1*(劉紅年),MA Wanli2(馬萬(wàn)里),QIAN Jjunlong1(錢(qián)俊龍), CAI Juzhen3(蔡菊珍), YE Xianman4(葉賢滿),LI Jiahui1(李佳慧), and WANG Xueyuan1(王學(xué)遠(yuǎn))

    1 School of Atmospheric Sciences,Nanjing University,Nanjing 210023

    2 Hangzhou Environmental Meteorological Center,Hangzhou 310008

    3 Zhejiang Climate Center,Hangzhou 310017

    4 Hangzhou Environmental Monitoring Central Station,Hangzhou 310007

    Effect of Urbanization on the Urban Meteorology and Air Pollution in Hangzhou

    LIU Hongnian1*(劉紅年),MA Wanli2(馬萬(wàn)里),QIAN Jjunlong1(錢(qián)俊龍), CAI Juzhen3(蔡菊珍), YE Xianman4(葉賢滿),LI Jiahui1(李佳慧), and WANG Xueyuan1(王學(xué)遠(yuǎn))

    1 School of Atmospheric Sciences,Nanjing University,Nanjing 210023

    2 Hangzhou Environmental Meteorological Center,Hangzhou 310008

    3 Zhejiang Climate Center,Hangzhou 310017

    4 Hangzhou Environmental Monitoring Central Station,Hangzhou 310007

    Urbanization has a substantial effect on urban meteorology. It can alter the atmospheric diffusion capability in urban areas and therefore affect pollutant concentrations.To study the effects of Hangzhou's urban development in most recent decade on its urban meteorological characteristics and pollutant diffusion, 90 weather cases were simulated,covering 9 weather types,with the Nanjing University City Air Quality Prediction System and high-resolution surface-type data and urban construction data for 2000 and 2010.The results show that the most recent decade of urban development in Hangzhou substantially affected its urban meteorology.Specifically,the average urban wind speed decreased by 1.1 m s?1;the average intensity of the heat island increased by 0.5℃;and the average urban relative humidity decreased by 9.7%.Based on one case for each of the nine weather types,the impact of urbanization on air pollution diffusion was investigated, revealing that the changes in the meteorological environment decreased the urban atmosphere's diffusion capability,and therefore increased urban pollutant concentrations.For instance,the urban nitrogen oxides concentration increased by 2.1μg m?3on average;the fine particulate matter(diameter of 2.5μm or less; PM2.5)pollution concentration increased by 2.3μg m?3on average;in highly urbanized areas,the PM2.5concentration increased by 30μg m?3and average visibility decreased by 0.2 km,with a maximum decrease of 1 km;the average number of daily hours of haze increased by 0.46 h;and the haze height lifted by 100–300 m.The“self-cleaning time”of pollutants increased by an average of 1.5 h.

    Hangzhou,urbanization,atmospheric environment,haze

    1.Introduction

    In recent years,urbanization in China has continuously accelerated.Although urbanization can apparently enhance mankind's standard of living,it creates numerous environmental problems that cannot be ignored.For example,the heat island effect becomes increasingly serious;urban visibility decreases dramatically;urban air quality continuously worsens;and the frequency of urban haze weather increases.

    The main cause of the increasing problems with respect to air quality in China's urban atmosphere is the growing energy consumption required to satisfy the country's rapidly growing economy of the past few decades.Another undeniable fact is that urbanization itself contributes to increased urban haze weather, which can decrease urban wind speed,decrease pollutant diffusion capability,and therefore,result in pollutant accumulation.Thus,pollutant concentrations increase,and consequently,visibility decreases.

    Xu(2002)and Xu et al.(2005)studied the spatial structure characteristics of urban atmospheric polluta-

    nts on multiple scales using samples from rapidly growing urban communities in Beijing and its surrounding areas.They concluded that on a heat island,mesoscale heat circulation characteristics and the interaction between dynamics and heat on the urban and urban-local scales have substantial effects on the transport,transformation,and diffusion of urban atmospheric pollutants.

    Miao et al.(2010)studied the effect of Beijing's urbanization on urban meteorology and heavy rain and found that Beijing's urbanization can cause a clear decay in wind speed.Peng and Hu(2006)performed a statistical analysis of the average field observational data collected at Beijing's 325-m meteorological tower in the summers of 1994 and 1997–2003.They found that at the near land surface level–most strongly affected by the underlying surface–the wind direction gradually became disordered and the wind speed decreased from 1.23 m s?1in 1994 to 0.71 m s?1in 2003. Ma and Zhang(2015)studied the impacts of urban expansion on Meiyu precipitation over eastern China and found that urban expansion in the Yangtze River Delta region has led to changes in the surface energy balance and a warming(cooling)of the tropospheric(stratospheric)air temperature over eastern China.In their study of multi-year speed data in Shanghai,Zhou and Yu(1988)showed that rapid urbanization resulted in increased architectural complexity with increased density and height,leading to increased roughness of the underlying surface,and consequently decreased urban surface wind speed.

    Surface wind speed is the key factor in determining urban pollutant concentrations because decayed wind speed can lead to decreased atmospheric diffusion capability,resulting in increased pollutant concentrations.Dacre et al.(2007)found that even with no synoptic system influence,the removal rate of pollutants at the atmospheric boundary itself could reach 50%. The ventilation process of the atmospheric boundary can be affected by many factors(Agust′?-Panareda et al.,2005;Angevine et al.,2006;Verma et al.,2006;Esler et al.,2007;Zhang et al.,2015),of which the mean wind flow and turbulence processes are especially important(Nehrkorn et al.,2013;Skvortsov et al.,2013).

    Civerolo et al.(2007)numerically simulated variations in New York City's surface meteorological field and ozone concentration caused by urbanization for the next 50 years and found that a change in surface type could increase both the average daily ozone concentration by 1–5 ppb in New York City's urban area,and the average daily maximum 8-h ozone concentration by 6 ppb.Wang et al.(2007,2009)studied the effects of climate-characteristic variations caused by urban expansion in the Pearl River Delta region on the formation of secondary organic aerosols and ozone.They concluded that the urban expansion increased the concentrations of urban ozone and secondary organic aerosols by affecting urban temperature,wind speed,and mixing layer height.Wang et al.(2008)found that urban buildings can affect both the surrounding meteorological environment and the transport and diffusion capabilities of urban pollutants in the Beijing area.As the towns surrounding Beijing continued to expand,the particulate matter of 10μm in diameter or less(PM10)changed from moving mainly in the outgoing direction to the incoming direction in the primary urban area.The existence of small towns and cities contributed 0.192 t day?1to the PM10budget of the main urban area.

    Hangzhou is one of the most popular tourist destinations in China and a highly developed area.Over the past 20 years,its economy has developed rapidly and urbanization has accelerated.The quality of the urban-atmosphere environment,however,has been decreasing,and the frequency of haze weather has been continuously increasing.Based on the compiled haze weather data in Hangzhou from 2003 to 2008,it appears that every year had more than 150 haze weather days,with that number reaching 176 days in 2004(Jin et al.,2010).

    Many studies have been carried out on the air quality of Hangzhou;however,investigations on the influence of urbanization on air quality have been relatively few in number,and focused mainly on the impact of urbanization on the meteorology field and the evolution of air quality with the urbanization process.Using a regional boundary layer model,Chen and Jiang(2006)studied the influence of urban build-

    ings on the urban wind field and found that buildings tended to decrease the wind speed of the urban area(maximum reduction:1.6 m s?1)and trigger the convergence of low-level air flow.Mao et al. (2013)analyzed the evolution of annual average haze days in Hangzhou City and Zhejiang Province during 1960–2009 using the nighttime light distribution from a satellite product.The increase in air pollution emissions during the urbanization process is plausibly the major reason for the air quality deterioration of Hangzhou.Urbanization has greatly altered the surface characteristics and building height and density of the city,but how the air quality is affected by these changes remains unclear and will be investigated in this paper.

    The impacts of urbanization mainly fall into two aspects.Firstly,the city area,the characteristics of the buildings,and the variation of the surface can significantly affect the urban atmospheric environment. Secondly,human activities such as anthropogenic heat and pollutant emissions also have a direct influence. To study the effect of urbanization on Hangzhou's urban meteorological characteristics and pollutant diffusion over the past decade,numerical simulations were conducted by using the Nanjing University-City Air Quality Prediction System(NJU-CAQPS),highresolution surface-type data,and urban construction data in 2000 and 2010. In addition,variations in the urban meteorological environment resulting from Hangzhou's urbanization were analyzed,including not only the variations in urban heat island and city wind characteristics but also the concentration distribution differences caused by variations in urban meteorological conditions.

    The simulations for 2000 and 2010 used different surface types,building heights,building densities,and anthropogenic heat caused by urbanization in Hangzhou.The same pollution emission inventory and NCEP-NCAR reanalysis data of 2010 were used in the simulations.Thus,by comparing the simulation results for these two periods,we were able to obtain the effect of Hangzhou's urbanization on the urban meteorological environment and pollutant diffusion.In fact,the work presented in this paper comprised a sensitivity study about the effect of surface type,building height and density,and anthropogenic heat on the atmospheric environment.

    2.Model and design

    2.1Model

    The NJU-CAQPS model is composed of four modules:the WRF(Weather Research and Forecasting)model,UBLM(Urban Boundary Layer Model), ACTDM(Atmosphere Contaminant Transport and Diffusion Model),and CSTM(Contamination Source Treatment Model)(Liu et al.,2009).

    The WRF model system is a new-generation, mesoscale prediction model and assimilation system established in 1997 by the meso-and small-scale meteorological station at NCAR,the Environment Simulation Center at NCEP,the Forecast Study Station of the Forecast Systems Laboratory,and the Center for Analysis and Prediction of Storms at the University of Oklahoma.The system remains in wide use today.

    UBLM is a 3D,fine-scale,urban atmospheric boundary modeland non-hydrostatic and highresolution turbulence closure model(Fang et al., 2004).In this model,urban anthropogenic heat is added to the surface energy balance equation,and the urban building drag term is added to the momentum and turbulence energy equations,which can therefore accurately simulate urban meteorological characteristics and better reflect urban-local heat and dynamic forcing effects. ACTDM,which is online-coupled with UBLM,includes concentration prediction models for transport,diffusion,chemical conversion,and dry and wet deposition of multiple substances(Liu et al.,2009),calculates 3D concentration variations of multiple pollutants[i.e.,sulfur dioxide(SO2),nitrogen oxides(NOX),total suspended particles,PM10, PM2.5(particulate matter of 2.5μm or less),ozone (O3),carbon monoxide(CO),and the main components of aerosols–including sulfates,nitrates,ammonium salts,black carbon,and organic carbon],and calculates the atmospheric light extinction coefficient and visibility based on aerosol concentration to discriminate haze.The gaseous chemical reaction mech-

    anism is CBM4(Carbon Bond Mechanism IV),and secondary inorganic aerosols(e.g.,sulfates,nitrates, and ammonium salts)are computed with the aerosol thermodynamic balance model.Based on the mass concentrations of aerosol chemical components,the extinction coefficients and visibility were calculated.

    UBLM employs the initial condition and boundary condition provided by WRF.ACTDM uses the inverse square interpolation method to compute the initial condition from observational data,and takes the real observational value of the reference observation sites as the boundary value.

    Describing the impact of urban buildings on the wind field is crucial in the simulation of urban meteorology and air pollution diffusion.Due to the damping and disturbance effects of buildings on the urban lower-layer wind field,when airflow passes through urban areas,wind speed is decreased and turbulence energy is increased.UBLM introduces drag force into the momentum equation to represent the impact of urban buildings on the wind field,based on the studies of Sorbjan and Uliasz(1982),Uno et al.(1989), and Urano et al.(1999).The surface area index of urban buildings A(z)is calculated as follows:

    where Sgis the total surface perpendicular to wind speed in a grid,and Vgis the grid volume.In the control function set,the urban building damping terms Fbuand Fbvare added to the u and v component equations,respectively,and a building disturbance term of turbulence energy(PEb)and dissipation rate(Pεb)are added to the turbulence energy and dissipation rate functions in UBLM,respectively:

    The parameter η is the building area ratio in each grid. According to the wind tunnel test results reported by Raupach(1992),the drag coefficient Cdwas set to 0.4.

    The NJU-CAQPS model is in operational use at the meteorological bureaus of Suzhou,Hangzhou,and Ningbo,The model has also been used to study the formation mechanisms and factors influencing haze weather(Lu et al.,2011;Qian et al.,2013,2015).

    2.2Design

    Consistent with the analysis of the characteristics of Hangzhou's weather between 1995 and 2000, its weather was divided into nine types by Hangzhou Meteorological Bureau,i.e.,high-pressure front,highpressure bottom,high-pressure control,high-pressure rear,cyclone system,east wind belt system,inverted trough,cold-front rear,and cold-front front.The classification of synoptic types took place as follows:On the surface weather map or 500-hPa weather map at 0600 UTC,the synoptic system that occurred in the predetermined region with Hangzhou at the center was defined as the synoptic type.If there were two synoptic types occurring at the same time,the one that went on to affect Hangzhou was chosen.Categorizing each day's weather according to the above nine types is a standard task of Hangzhou Meteorological Bureau.The data of synoptic types were therefore obtained from Hangzhou Meteorological Bureau.

    Ninety individual cases under the nine different weather types were selected to simulate the effect of urbanization on the meteorological field from 2010 to 2012 and the effect of urbanization on pollutant diffusion for each typical case of each weather type.Each synoptic type had 10 cases and the selection process used a rule that there needed to be a case in each of the seasons.All case dates are listed in Table 1.

    The design of the grid in the model was as follows: a quadruple nested grid was used in WRF,the center at 30.238°N,120.205°E.All four grids of the quadruple nested grid had 82×61 grid points,and the spatial resolutions were 27,9,3,and 1 km,respectively.The extended hydrostatic pressure-following vertical coordinate was used in the vertical direction,which had 78 vertical layers and a top level at 100 hPa.The boundary condition used 1°×1°NCEP data,updated every 6 hours. The microphysics process used the WSM3 simple ice scheme;the longwave and shortwave radiation schemes were the RRTM and Dudhia schemes,respectively;the land process used the Noah scheme; the boundary layer scheme was the Monin-Obukhov scheme;and the cumulus convection parameterization only took the Kain-Fritsch scheme at one and two vertical layers.The simulation of each case started at 1200 UTC on the day before the simulation day.Thus, each case ran for 36 h,and the first 12 hours was the model spin-up period.The horizontal grid distance in the boundary layer model and chemical model was 500 m,and the horizontal grid points were 99×71.The vertical distance was divided into 13 layers;the top height in the model was 3 km;and the lowest layer height was 5 m.

    Table 1.Case dates of each synoptic type

    The numerical simulation region in the NJUCAQPS model covered a 49×35-km2area centered on the junction of Fuchun Road and Shimin Street in Hangzhou(30.27859°N,120.1842°E).According to Hangzhou's underlying surface characteristics,the study region can be classified as city,water area,grassland,woodland,and soil. Figure 1 shows the distribution of land-use types in 2000 and 2010 based on a 10-m resolution and surface-type data,in which the purple region represents“city”.Hangzhou Urban Planning Bureau provided the urban area gridded data of urban building height,water area,grassland,and other surface types,with a spatial resolution of 10 m. The suburban area surface type data were provided by the MODIS surface type database in WRF.Following 10 yr of urbanization,the size of Hangzhou's urban area has greatly increased from 133 km2in 2000 to 378 km2in 2010.In 2000,the area was limited to the north of Qiantang River,while Hangzhou City was developed around the south of Qiantang River and the main urban area expanded to the north,northeast, and west.

    There are eight districts in Hangzhou City,i.e., Yuhang(YH),Xihu(XH),Shangcheng(SC),Xiacheng (XC),Jianggan(JG),Gongshu(GS),Binjiang(BJ), and Xiaoshan(XS).According to traditional classifications,SC,XC,XH,GS,and JG were considered as Hangzhou's main urban areas.In the model domain, the terrain of Hangzhou's urban area was flat,and the hills in the southwest were generally less than 300 m.

    Each case(Table 1)was simulated twice.In the first run,the land-use types and building data of 2010 were used,and the results compared with observations.In the second run,the data were replaced by those of 2000.In the simulation of each case,the NCEP data and emissions data remained unchanged, so the differences between the results of 2010 and 2000 could be attributed to the development of urbanization.

    Fig.1.Hangzhou's land-use types in(a)2000 and(b)2010.

    3.Urbanization of Hangzhou

    Figure 2 shows the distribution of building height and density variation in 2000 and 2010 based on 10-m resolution urban-building height and distribution data for Hangzhou.After 10 yr of urbanization in Hangzhou,the building height and density variation in 2010 were clearly larger than in 2000.In the main urban area and parts of the new urban area,the number of large and tall buildings increased rapidly,as did the building density.The average building height and density were 9.8 m and 0.15,respectively,in 2000,and the corresponding values in 2010 were 9.5 m and 0.16, respectively.The amount of buildings in 2010 was far greater than in 2000,and most of the buildings in the newly developed urban areas were lower than 10 m; this was why the average building height in 2010 was slightly less than that in 2000.

    With the increasing urban population and development of industry and transport,the effect of urban anthropogenic heat on the urban environment and climate has become increasingly important,making anthropogenic heat a key factor in the simulation of urban meteorology.In this study,urban anthropogenic heat was classified as the sensible heat flux from industry,transport,living and human body heat.

    Based on data for industrial energy consumption, vehicle possession,main road traffic-flow,domestic energy consumption,human population,and standard coal calorific values,recorded in the 2010 Hangzhou Statistical Annual Book,Hangzhou's anthropogenic heat in 2010 was estimated.Industry,transport,domestic,and human body-heat radiation in Hangzhou were calculated to be 39.1,10.8,5.57,and 1.57 W m?2,respectively,and the total anthropogenic heat was 57.04 W m?2. Similarly,Hangzhou's anthropogenic heat in 2000 was estimated to be 47.84 W m?2,based on statistical data from 2000 for its economy.Thus,compared to 2000,anthropogenic heat in 2010 increased by 9.2 W m?2,which was a relatively small increase considering Hangzhou's energy consumption of unit GDP(in ten thousand RMB)decreased during the past 10 years.UBLM introduces anthropogenic heat into the sensible heat term in the surface energy balance,and the anthropogenic heat is homogeneously distributed over the urban area,taking no account of the spatial distribution of anthropogenic heat.The estimation of anthropogenic heat and its daily variation is based on the work of Wang and Wang(2011).

    Based on the 2010 emission data from Hangzhou Environmental Protection Agency,a 500-m resolution emission inventory was produced. The emission species included SO2,NOX,CO,HC(hydrocarbon),PM10,and PM2.5.For brevity,only the emissions of four species from transport are shown(Fig. 3). The emission sources were industry(including power plants),domestic,and transport.In the simulated area,total annual emissions of SO2amounted to 55931.5 t,with 49154.8 t emanating from industry.The total annual emissions of NOXamounted to 73536.5 t,with 35242.0 and 37654.5 t emanating

    from transport and industry,respectively.The total annual emissions of PM10were 68158 t,with 41849.9 t emanating from transport and 21606.1 t emanating from industry.Finally,total annual CO emissions were 813831 t,with 657528 t emanating from industry and 154169 t from transport.

    Fig.2.Urban(a,c)building height(m)and(b,d)density in(a,b)2000 and(c,d)2010,and(e,f)their differences.

    4.Simulation results and analysis

    4.1 Validation of simulation results

    The simulated daily average results were compared with observationalresultsobtained from Hangzhou Meteorological Station (30°13′33′′N(xiāo), 120°09′53′′).The simulated values of the observation sites were computed from values of the four nearby grid points using inverse square interpolation.Figure 4 shows scatter distributions comparing the 90 individual simulation case results with observational values.According to the statistical results,the average temperature of the 90 simulated days was 17℃and the corresponding observational value was 17.5℃, with a correlation coefficient of 0.97;the average value of the simulated wind speed was 1.9 m s?1and the corresponding observed value was 2.3 m s?1,with a correlation coefficient of 0.703;and the average value of the simulated relative humidity was 68.7%and the

    corresponding observed value was 73%,with a correlation coefficient of 0.89.The RMSEs of wind,temperature,and relative humidity were 0.74 m s?1,2.22℃, and 7.86%,respectively.

    Fig.3.Distribution of emissions from transport(t yr?1km?2).

    Fig.4.Comparison of simulated(a)wind speed(m s?1)at 10-m height,(b)daily average surface temperature(℃), and(c)relative humidity(%)with observational values.

    Figure 5 compares some of the air quality simulations with their observed counterparts–the av-

    erage of values observed by Environment Monitoring Stations of Hangzhou Environmental Protection Agency:Hemu(HM;Wolongqiao(WLQ;;Xiasha (XS;ChengxiangzhenLinping (LP;and Xixi(XX;.In general,the simulated SO2concentration was higher than the observed value because the averaged simulation to observation ratio was 1.21.Meanwhile,the averaged simulation to observation ratio for nitrogen dioxide(NO2)was 1.03, and that for PM10was 1.15.Thus,the simulation results agreed well with the observational data.

    4.2 Effects of urbanization on the meteorological field

    Figure 6 shows the distribution variations of the mean flow field and temperature field for 90 cases of 9 weather types.The average wind direction in the simulated area was northeasterly,and when the dominant wind was northeasterly,the air corridor was primarily located in ShiqiaozhenPengfuzhenand Jianggan districts.The coastal wind speed along the Qiantang River was relatively higher and the minimum-value regions were Shangcheng,Xiacheng,and northern Xihu districts,in which the flow field showed apparent convergence.The low wind speed areas were expanded compared to 2000,and the wind speed in Xiaoshan district had clearly decreased.The only value that was preserved in 2010 was the 2000 high wind speed belt along the Qiantang River in the areas downstream from the estuary.

    Table 2 shows the mean statistical results for the individual cases over 90 days.It indicates that the average urban temperature was 16.2℃,which increased by 0.9℃;the maximum temperature was 24.6℃,which increased by 0.6℃;and the minimum temperature was 3.4℃,which increased by 1.1℃.Thus,urbanization greatly increased the nighttime temperature;the heat island intensity was 0.6℃,which increased by 0.5℃; the average relative humidity was 69.0%,which decreased by 9.3%;and the average urban wind speed was 1.9 m s?1,which decreased by 1.1 m s?1.Table 2 shows that urbanization reduced the turbulence energy over the urban area,which was the results of a combination of two opposite impacts of urbanization

    on turbulence.On the one hand,urbanization increased turbulence energy by increasing the surface roughness.On the other hand,urbanization reduced the average wind speed and then lowered the turbulence energy.The model results illustrate that the reduction of turbulence energy due to average wind speed was more significant.

    Fig.5.Comparison of simulated(a)SO2,(b)NOx,and(c)PM10concentrations(μg m?3)with their corresponding observed values.

    Fig.6.Averaged distribution variation of the flow fields and temperature fields of 90 cases:(a)surface flow field(m s?1)in 2000,(b)surface flow field in(m s?1)2010,(c)wind speed and flow field variation caused by urbanization(m s?1),and(d)surface temperature variation caused by urbanization(K).

    Table 2.Averaged statistical results of meteorological factors over 90 days

    4.3 Effects of urbanization on pollutant diffusion capability

    In addition to the“heat island effect”,urbanization can cause a“turbid island effect”.The heat island effect can decrease the frequency of inversion layer and increase air-convection transport in the vertical direction.In addition,the relatively low relative humidity and average wind speed of urban areas can inhibit the horizontal transport of air.Under such conditions,it is very difficult for urban emitted particle pollutants to diffuse.

    The air quality for nine cases was simulated,each representing one of the nine weather types(bold dates in Table 1).The average results in the simulated ur-

    ban area are listed in Table 3(values in parentheses are extreme values).The numbers of haze hours in the table were estimated based on average hourly visibility,relative humidity,and particle concentration using the Observation and Forecast Grades of Haze provided by the Chinese Meteorological Administration(CMA, 2010).Table 3 shows that for different weather types, urbanization increased the averaged daily urban NO2concentration by 1.0–3.3μg m?3(increased by an average of 2.1μg m?3)and the maximum local effect reached 12.44μg m?3;the averaged daily urban PM2.5increased by an average of 2.3μg m?3and the maximum local effect reached 15.3μg m?3;on average,visibility decreased by 0.2 km and the local effect reached 1.3 km;the averaged daily number of haze hours increased by 0.1–1.2 h,increasing by an average of 0.46 h,and the local effect reached 3.3 h.

    Figure 7 shows the distributions of averaged PM2.5concentration and visibility for the nine individual cases.The results show that the maximum PM2.5concentration was located at the boundary of Shangcheng,Xiacheng,and Jianggan districts,which increased by 40μg m?3due to urbanization.The corresponding visibility also decreased by approximately 1 km.In addition,in another high PM2.5concentration area within Xiaoshan district,the corresponding visibility clearly decreased.

    Figure 8 shows the vertical section contour lines of PM2.5concentration(75 and 100μg m?3)and visibility(10 and 7 km)in the east-west direction acrossthe center of the simulated area(30°16′43′′N(xiāo))in different years.Note that 75μg m?3is the maximum mean daily value for PM2.5,according to the Chinese Air Quality Standard,and 10-km visibility is the maximum value to determine haze(called“haze height”in this study),according to the Chinese Meteorological Administration.The haze height was very low in the suburbs,at approximately 300 m;whereas,its value in urban areas was much higher.This is because particle pollutants in urban areas are more severe than those in suburban areas,thus decreasing both the surface visibility and the upper layer visibility of the boundary layer.In 2010,the haze height was approximately 1300 m,which was about 200 m higher than that in 2000.This indicates that urbanization decreased urban diffusion capability and resulted in pollutant accumulation,which led to a lifted haze height.In summary,over the city and in the downwind direction,the PM2.5vertical diffusion range was higher and urbanization led to strengthened vertical diffusion of PM2.5, resulting in a higher“chaos island”.

    Table 3.Air-quality simulation results of individual cases for nine days

    Fig.7.Averaged(a,c)PM2.5(μg m?3)and(b,d)visibility(km)in(a,b)2000 and(c,d)2010,and(e,f)their differences(μg m?3;km).

    Fig.8.Vertical cross-sections of averaged(a)PM2.5(μg m?3)and(b)visibility(km).

    To further investigate the effect of urban ventilation capability on pollutant diffusion,diffusion tests were performed without an emission source,i.e.,by removing the emission source.The same initial field was established and the decreasing PM10concentration rate over time was compared.The results for individual cases on nine days were simulated.Figure 9 shows the PM10concentration decay curves over time for the underlying surface in both 2000 and 2010. The results show that the air pollution concentration kept decreasing to almost zero due to the lack of emissions and air pollution transport,and urbanization slowed down the decay process of air pollution concentration.Since the decay process can be represented bywhere C is the concentration,C0is the initial concentration,t is the time and TSCis the characteristic time,we defined TSCas the“selfcleaning time”,i.e.,the time for the PM10concentration to decay to 1/e of its initial concentration,where e is the Napierian base.As shown,urbanization resulted in decreased diffusion capability,and the average selfcleaning time increased by 1.5 h.

    Fig.9.PM10concentration variations over nine days for different underlying surfaces.

    Table 4 shows the PM10self-cleaning times for individual cases over nine days.As shown,the decreasing rates of PM10concentration were clearly different for different weather conditions.For the present underlying surface,the PM10concentration decayed faster during“inverted trough”weather and“coldfront rear”weather,with better diffusion capability, and its self-cleaning time was approximately 7 h.During“high-pressure front”and“high-pressure control”systems,the PM10concentration decayed slower,with worse diffusion capability,and its self-cleaning times were 13.6 and 19.3 h,respectively.The self-cleaning time varied greatly with the change of weather system. When a“high-pressure control”system dominated, Hangzhou lay under a high pressure center.Due to the domination of downdraft flow and low wind speed, urbanization had a considerable influence and the selfcleaning time increased by 4.8 h.When weather systems with high wind speed dominated,such as a cyclone system,or cold-front front,urbanization had a small influence and the self-cleaning time tended to

    be short.On average,the self-cleaning times for the 9-day individual cases in 2000 and 2010 were 8.5 and 10 h,respectively.

    Table 4.Self-cleaning times(h)of PM10concentrations for different types of weather

    5.Discussion

    With the great increase in its urban population, China has witnessed rapid urbanization,characterized by an expanding urban area,increased building height and density,rising anthropogenic heat,and worsening air pollution.The key impacts of urbanization on urban meteorology include the enhancement of the urban heat island effect,decreasing wind speed in the urban area,and change in the urban boundary layer height and surface energy balance.We conclude that the increased emissions of air pollutants during the urbanization process is the major reason for the deterioration in Hangzhou's air quality in the last decade. Urbanization also affects urban meteorology by changing the variation in air pollution concentrations,but this indirect effect is a secondary reason.

    The indirect effect of urbanization consists of thermodynamic and dynamic effects.The thermodynamic effect refers to the enhancement of the urban heat island.Chen et al.(2012)found that anthropogenic heat release in economically developed areas in northern,eastern,and southern China is much larger than that in other regions.The strengthened urban heat island circulation tends to boost the vertical diffusion of air pollution,and then reduces the pollution concentration.The dynamic effect refers to the drag effect of urban buildings on air flow,which slows down the urban wind speed,weakens the atmospheric diffusion capacity,and increases the air pollution concentration.The simulations considered both the thermodynamic and dynamic effects,and the results showed that the combined effect is to increase the pollution concentration,which means that the dynamic effect dominates.Nonetheless,further understanding of the two effects is required,by separating them and studying each of them individually.Increases in air pollution concentration as a result of urbanization occur not only in Hangzhou,but also in Nanjing and Suzhou–two regions that have also experienced rapid urbanization(Lu et al.,2011;Qian et al.,2015).

    The impact of urbanization on urban air pollution concentrations is complex.The influence of urbanization on the temperature and humidity fields can change the rate constant of chemical reactions and hygroscopic growth of aerosols,respectively.Further insight into these chemical and physical processes need to be further studied.

    6.Conclusions

    The effect of urbanization on the urban meteorological environment is a complicated issue.Numerous factors can affect the urban meteorological environment,such as increased emissions of anthropogenic pollutants and heat,and changes in building materials(effects on the surface energy balance).In this study,we considered variations in two characteristics to evaluate urbanization,including the underlying surface and building height(density),and simulated the meteorological field and pollutant diffusion process using different weather types for two different underlying surfaces and urban building distributions in Hangzhou in 2000 and 2010. Ninety cases belonging to nine weather types,and nine cases featuring air pollution diffusion,were simulated.The key conclusions can be summarized as follows:

    Owing to urbanization,the area of urban low wind speed clearly increased and the mean daily urban wind speed decreased by 1.1(0.1–2.9)m s?1.Also, the heat island intensity increased by an average of 0.5 (–0.1–1.3)℃and the mean daily urban relative humidity decreased by an average of 9.7%(3.6%–17.9%).

    For different weather types,urbanization increased the PM2.5concentration in Hangzhou and the maximum local effect reached 12.4μg m?3.The mean daily PM2.5concentration increased on average by 2.3 μg m?3and the maximum local effect reached 15.3μg m?3.Visibility decreased by an average of 0.2 km and the maximum local effect reached 1.3 km.And the mean daily number of haze hours increased by 0.1–1.2 h,with the haze height lifting by 100–300 m.

    Urbanization decreased the urban self-cleaning capability and the average PM10self-cleaning time increased from 8.5 h in 2000 to 10 h in 2010.However, the reductions in self-cleaning time were far less than

    the differences among the weather types,indicating urban pollution is strongly affected by the changes in weather and the effects of urbanization on pollution are secondary.

    Urbanization has a significant impact on urban meteorology and air quality,which has plausibly contributed to the air quality deterioration of the Yangtze River Delta region during recent decades.Urbanization development mainly manifests in the development of suburban areas,i.e.,farmland and other natural surfaces being transformed into urban surfaces.However, the effect on air pollution concentrations is not confined to suburban areas.The extreme values of temperature,wind speed,and air pollution concentration related to urbanization mainly occur in the central urban area.

    We conclude that the increases in air pollution emissions during urbanization were the major reason for the deterioration in Hangzhou's air quality in the last decade.Reductions in emissions are the main way to control urban pollution,but the effects of urbanization on urban meteorology cannot be ignored.

    The Chinese government has made plans to control the developing boundaries of 14 major cities including Beijing,Shanghai,Nanjing,Hangzhou, Suzhou,ect.,and thus the speed of urbanization in such cities should slow down.In these cities,the building characteristics of the main urban area are unlikely to change substantially,and an increase in the effect of urbanization should be inhibited.While for the middle or small cities,with their high speeds of development, it is important that city development plans consider the effect of urbanization on their urban meteorology and environments.

    Acknowledgments.WethanktheHigh-Performance Computing Center at Nanjing University for its technical support during our numerical calculations.

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    10.1007/s13351-015-5013-y.

    Supported by the National Key Basic Research and Development(973)Program of China(2014CB441203)and National Natural Science Foundation of China(41575141).

    ?Corresponding author:liuhn@nju.edu.cn.

    ?The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2015

    (Received April 13,2015;in final form September 17,2015)

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