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Valuing Air Pollution Mortality in China's Cities

Valuing Air Pollution Mortality in China's Cities
Valuing Air Pollution Mortality in China's Cities

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Urban Studies

https://www.doczj.com/doc/9014864456.html,/content/41/8/1567The online version of this article can be found at:

DOI: 10.1080/0042098042000227019

2004 41: 1567

Urban Stud Victor Brajer and Robert W. Mead

Valuing Air Pollution Mortality in China's Cities

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Urban Studies,Vol.41,No.8,1567–1585,July2004

Valuing Air Pollution Mortality in China’s Cities

Victor Brajer and Robert W.Mead

[Paper first received,August2004;in final form,November2004]

Summary.Although China has made tremendous economic progress in recent years,air pollution continues to exact signi?cant health and economic https://www.doczj.com/doc/9014864456.html,ing pollution data from38 Chinese cities and China-based epidemiological functions,this paper estimates some of the economic bene?ts of reducing urban air pollution.It calculates the averted mortality which would result from the clean-up of particulates,sulphur dioxide and nitrogen dioxide—a pollutant not included in most previous China studies.The paper expands on earlier studies by examining the impact of seasonal variations in pollution levels.Finally,the monetary valuation of pollution-related averted mortality is developed using a China-based valuation study and,for a number of cities,the valuation is compared with city-level GDP.

Introduction

China’s urban air pollution problems are im-mediately apparent to any casual observer or visitor.The air is often dirty or grimy and is even gritty during dust and sandstorms.Fac-tories,power plants and industrial complexes are often observed belching smoke,while roads are clogged with ever-increasing num-bers of various motor vehicles.Construction projects,which often generate a fair amount of dust,are everywhere.In spite of the obvi-ous aspects of the problem and increasing activities by Chinese of?cials,urban air qual-ity in China continues to be poor.In1997, the World Bank,while noting improvement, observed that

ambient concentrations of particulates and sulfur dioxide in many Chinese cities are among the highest in the world and are signi?cantly above WHO(World Health Organization)guidelines and Chinese air quality standards(World Bank,1997,p.9).Four years later,the World Bank(2001) again noted that air pollution is the most prominent urban environmental problem in China.

Although there is a fairly extensive litera-ture trying to assess the health consequences of urban air pollution,there remain a number of shortcomings when it comes to looking at these consequences in China.First,previous studies are now either dated or limited in terms of their coverage.The most prominent study to date is the World Bank’s1997pub-lication,which assumes that Beijing’s1995 sulphur dioxide and particulate levels are representative of all of urban China.Given the economic growth and regional changes underway in China,this work needs to be updated with a more diverse sampling of Chinese cities.Two other studies are much more recent,but either focus only on Beijing (Brajer and Mead,2003a)or Shijiazhuang

Victor Brajer and Robert W.Mead are in the Department of Economics,California State University—Fullerton,Fullerton, California92834,USA.Fax:7142783097.E-mail:vbrajer@https://www.doczj.com/doc/9014864456.html, and rmead@https://www.doczj.com/doc/9014864456.html,.Portions of this paper were presented at the2003Annual Meeting of the Western Economics Association.The authors are grateful to Marion Jones and Nick Farnum for key technical assistance and useful suggestions.

0042-0980Print/1360-063X On-line/04/081567–19 2004The Editors of Urban Studies

DOI:10.1080/0042098042000227019

VICTOR BRAJER AND ROBERT W.MEAD 1568

(Peng et al.,2002).Given the scope of the issue,there is a need for an updated and broader path of investigation. Secondly,pollution in China has a sea-sonal pattern.Coal is a traditional source of heating and power,so cooler winter tempera-tures,especially in the northern cities,lead to higher consumption of coal and greater pol-lution levels.Because of these differences, annual averages tend to obscure the intersea-sonal variations in pollution which in turn can trigger a variety of different health ef-fects.By utilising the seasonal variations in-cluded in some China-based epidemiological functions,we are better able to establish the magnitude of the health risks and precisely delineate the speci?c pollution types con-tributing to various health consequences. These seasonal variations are not utilised in most previous studies(World Bank,1997; Peng et al.,2002).

Lastly,in addition to the seasonal changes in pollution levels,China’s urban air pol-lution is undergoing a signi?cant composi-tional change.Historically,the two major pollutants in China have been sulphur diox-ide(SO2)and particulates(TSP or PM10), with relatively little nitrogen dioxide(NO2) generated.However,even as China focuses its clean-up efforts on these historical pollu-tants,a rapid increase in the number of mo-torised vehicles in China is generating increasing levels of NO2almost simul-taneously with the medical literature’s recent development of the links between health problems and NO2.Other than Brajer and Mead’s(2003a)Beijing work,previous stud-ies of China’s air pollution and its health effects have ignored this aspect and miss a potentially signi?cant source of air-pollution-induced mortality.

In order to improve the overall under-standing of the health consequences of urban air pollution in China—in particular,TSP, SO2and NO2—this paper takes on four tasks. First,it updates and expands the scope of previous studies on the health impacts of China’s air pollution.Speci?cally,it esti-mates the number of mortality cases which could be averted by bringing current air pol-lution levels down to the Chinese and the pre-1999WHO standards(both of which are described in the scenario construction section below).Secondly,the paper utilises the sea-sonal aspects of urban air pollution to ident-ify more fully,and account for,the sources of pollution-related health effects.Thirdly, utilising recent literature linking NO2to health problems,it estimates the potential bene?ts associated with reductions in NO2 levels,a heretofore unexplored aspect of air pollution control efforts in urban China.Fi-nally,in an effort to value more accurately the monetary bene?ts of pollution clean-up, the paper uses recent China-based valuation studies in determining the value of a statisti-cal life.

The rest of the paper proceeds in the fol-lowing manner.The data and its collection are developed in the next section followed by the creation of various scenarios for each pollutant.Next,the methodology and results sections explain how China-based epidemio-logical studies and valuation studies are used to derive the health consequences and the accompanying dollar values for each clean-up effort.Final comments and a summary appear in the conclusion.

Data

In order to obtain a fairly broad grasp of China’s urban air pollution problem and the subsequent health effects,we collect pol-lution and population?gures for38Chinese cities and metropolitan areas(see Table1) using a number of different sources.For the pollution levels,our preferred source of in-formation is the most recent annual environ-mental report posted on the Internet by the various municipal environmental protection bureaus.For most cities,these reports are for the2001calendar year.When2001reports are not available,we use reports from either 1999or2000.In several cases,the annual reports are not directly available from the municipal environmental protection bureaus, so we use pollution numbers from posted news articles,provincial-level reports and China Social Statistics(2000).1

1569

AIR POLLUTION MORTALITY IN CHINA

T a b l e 1.P o l l u t i o n a n d p o p u l a t i o n l e v e l s b y c i t y

P o p u l a t i o n C i t y S O 2( g /m 3)

(m i l l i o n s )

T S P ( g /m 3

)

N O x ( g /m 3)P M 10( g /m 3

)

N O 2( g /m 3

)

Y e a r B e i j i n g

2001–02157.911.2230

65.679.0W i n t e r /s u m m e r 182.0/124.596.3/23.186.2/69.2G u a n g z h o u

2001–0271.547.1260

57.4674.97W i n t e r /s u m m e r 72.4/70.4

57.4/57.583.1/63.7H a n d a n

2000540.831.36

10354.3W i n t e r /s u m m e r 496.7/585.099.5/106.549.8/58.8H e n g s h u i

20012644.07

3430W i n t e r /s u m m e r 282.5/246.556.5/1334/26

1.105590

S a n m i n g

20012192431W i n t e r /s u m m e r 239/199

27.5/20.533.5/27.5

13.2714

S h a n g h a i

2001–02111.038.360.7W i n t e r /s u m m e r 130.2/83.4

44.2/30.069.0/49.2W e n z h o u

20011007.3881

1128W i n t e r /s u m m e r 120/80

14/1034/26W u h a n

7.5823

2001–02141.042.152.5W i n t e r /s u m m e r 158.8/116.3

50.5/30.4259.9/42.30.95

X i n y i

2001–022341120W i n t e r /s u m m e r 258/213

13/1019/21Z i b o

20011112.7048

5328W i n t e r /s u m m e r 126/96.5

65/40.530/25.5

A n s h a n 19994151.4569875C h a n g s h a 19992035.870911652C h e n g d u 1999231

10.1995541

11.3095C h o n g q i n g 200115010050D a l i a n 2001795.54613124F u s h u n 20013472.3103232F u z h o u 200179

5.94142445G u i y a n g 2000180

3.358113227H a n g z h o u 20011246.29145253H a r b i n 2001135

9.41103949

J i l i n C i t y

1999

563

2.0

85

68

1570

VICTOR BRAJER AND ROBERT W .MEAD

T a b l e 1.—C o n t i n u e d .

P o p u l a t i o n Y e a r S O 2( g /m 3)C i t y N O x ( g /m 3)P M 10( g /m 3)N O 2( g /m 3)T S P ( g /m 3)

(m i l l i o n s )

199935891J i n i n g 463.40342001800

65282.9651L a n z h o u 2001122

M a a n s h a n 1926

1.205N a n j i n g 2000187

2948

5.5304200164

52N a n n i n g 282.94562001329

P i n g x i a n g 22291.780Q i n g d a o 200198

52237.105Q i n g h u a n g d a o 200124431382.6441200110762

S h a n t o u 2843

4.6156S h e n y a n g 1999304

7265

6.8934S h e n z h e n 200163

2758

4.68761999198S h i j i a z h u a n g 129758.95941999416

272101

T a i y u a n 3.135********

T i a n j i n 5448

9.1398W u l u m u q i 1999463

14692

1.6903X i a m e n 20016124221.34362001

54

34Z h u h a i 36

1.2528

AIR POLLUTION MORTALITY IN CHINA1571

In addition,for10cities we obtain or derive seasonal variations in pollution levels as well.For5cities(Handan,Hengshui, Sanming,Wenzhou and Zibo),the seasonal levels are reported monthly or quarterly for the calendar year.We use the numbers re-ported and identify the1st and4th quarters as winter and the2nd and3rd quarters as summer.For Xinyi(in Jiangsu Province),the pollution?gures are reported on a weekly basis;and for Beijing,Shanghai,Guangzhou and Wuhan,daily index numbers are avail-able.For these cities we identify the period1 October2001to30April2002as the winter season and the period1May2002to30 September2002as summer.For those cities with daily pollution index numbers,we draw a random sample for each pollutant and con-vert the index numbers into pollution levels using the index guidelines established by the Chinese authorities(China Environmental Protection).2

For most of the cities,especially the larger ones and provincial capitals,the2001popu-lation numbers come from the2002China Statistical Yearbook.For those cities not listed in the statistical yearbook,the popu-lation numbers are either provided in the annual pollution report or obtained from the information given on the websites of the individual municipal governments. Because the choice of cities included is driven by our ability to access and obtain relatively recent pollution-level data,the sample is not truly random nor is it necess-arily representative.In fact,several sizeable cities of over6million(Xi’an,Changchun and Zhengzhou)are left out of the analysis because we do not have adequate pollution data.Nonetheless,the analysed cities com-prise a wide cross-section of Chinese cities and involve a substantial population-base. The analysed population exceeds189million people,which is approximately40per cent of the total urban population and nearly15 per cent of China’s total population. Having developed the pollution and popu-lation?gures,we next turn to baseline mor-tality?https://www.doczj.com/doc/9014864456.html,ing the same basic methodology of Brajer and Mead(2003a),we develop baseline?gures for death rates in order to apply the concentration–response health functions(described in the health ef-fect functions section below).The China Statistical Yearbook stopped breaking down the national death rate by city and county after1999,but city death rates make up a consistently lower proportion of the national averages in every year where the breakdown was published.To derive a2001urban death rate,we use the1999city death rate as a percentage of the national death rate and apply it to the reported2001national death rate(China Statistical Yearbook,2001and 2002).For the urban death rates of10major diseases,we use the2001numbers from the Statistical Yearbook(2002).For the seasonal breakdowns,we rely on Xu et al.(1994), whose analysis allows us to divide the death rates into‘summer’and‘winter’compo-nents.

Scenario Construction

Identifying and quantifying the links between air quality and the health-related economic bene?ts of successful pollution clean-up ef-forts involves a series of steps.Having col-lected local area pollution and population data,we?rst project pollution and population levels10years into the future for each metropolitan area.For the10-city subset where we have seasonal data,we also ac-count for seasonal variations in pollution lev-els.Secondly,information from the Chinese health literature is used to derive concen-tration-response functions that can determine the reductions in mortality.Thirdly,econ-omic values are attached to the estimated health improvements.These values are de-rived in part from a recent contingent valu-ation(CV)study(Zhou and Hammitt,2003) conducted in three locations in China and also from a large set of predominantly US-based studies.The adjustments we make to these US studies generate corresponding Chi-nese values consistent with other published Chinese valuation literature.

Having compiled the base pollution,popu-lation and mortality data,we next construct

VICTOR BRAJER AND ROBERT W.MEAD 1572

several alternative scenarios in order to as-

sess the health effects of potential clean-up.

These projected scenarios require several as-

sumptions about future pollution and popu-

lation levels.Beginning with population,we

use2001data and assume an annual urban

population increase of0.7875per cent for the

period2001to2011,based on United Na-

tions(UN)projections reported by Heilig

(1999).This growth rate is much lower than

the World Bank’s projected urban growth

rate of3.4per cent(World Bank,2001).We

use the more conservative UN?gure because

the World Bank’s growth?gure includes

population growth,rural–urban migration

and the reclassi?cation of some rural areas as

urban.While we are focused upon urban

residents in our analysis,some of the city

population levels we use may include rural

residents within the metropolitan area.

Hence,any rural–urban migration or urban

boundary reclassi?cation would not necess-

arily re?ect a net population increase within

our identi?ed city.

For each of the three pollutants,we con-

struct three scenarios.The?rst scenario,or

the‘business as usual’(BAU)case,consti-

tutes a baseline based upon current pollution

levels.Two additional scenarios then look at

the bene?ts of successful pollution abatement

efforts.In the?rst of these two abatement

scenarios,we examine expected mortality re-

ductions resulting from clean-up efforts that

lower pollution levels to the Chinese clean

air standards:200micrograms per cubic me-

tre( g/m3)for TSP,60 g/m3for SO2and80 g/m3for NO2.Then,because the pre-1999 World Health Organization(WHO)standards

are even more stringent,we also calculate the

averted mortality bene?ts of meeting these

WHO standards:90 g/m3for TSP,50 g/m3

for SO2and40 g/m3for NO2.3For TSP and

SO2,we project a linear decline in the pollu-

tants from their2001levels to the targeted

standards in the year2011.If a city’s2001

pollution level is below the relevant standard,

no health bene?t is calculated.In the case of

NO2,the projected clean-up begins when the

BAU NO2levels exceed the targeted stan-

dards.

For SO2and TSP,we project the BAU scenario as keeping the2001levels constant. While China has publicly promoted in-creased efforts to decrease pollution and has highlighted localised successes,we feel that there is suf?cient reason to doubt the appear-ance of sudden,permanent decreases in pol-lution levels.First,the World Bank(2001) notes that the pollution levels in smaller cit-ies appear to have actually increased in the period1990–98and goes on to suggest that the clean-up successes that have been noted in some cities may only apply to inner-city areas and not to the overall metropolitan areas.There is also some feeling that there has been some relaxation or backsliding fol-lowing the efforts to meet the National Ninth Five-year Plan in2000(Betts,2002).In ad-dition,the National Tenth Five-year Plan for Environmental Protection,which covers the period2001–2005,appears to have set very modest clean-up goals(China Environmental Protection,2002).With respect to speci?ed urban standards,the plan mandates that over half of the cities will attain the second grade in national pollution standards.4However, this goal has already been met technically because most of the cities in our sample meet this standard even though they still have harmful levels of pollution.Finally,even the city of Beijing,which is something of a standard-bearer in terms of pollution abate-ment because of the2008Summer Olympics, has not been totally successful in its clean-up efforts.In spite of notable improvements in Beijing’s overall air quality since1998,2002 levels for SO2,NO2,PM10and TSP were all higher than their2001levels(Beijing EPB, 2003).

Because NO2pollution in China is a nascent yet growing problem,constructing our scenarios for this pollutant is a bit more involved.Automobile emissions,which were essentially unforeseen as an environmental issue at the beginning of the1990s(World Bank,2001),are now a major source of NO2 pollution in China’s urban areas(He et al., 2002;Hao et al.,2001;and World Bank, 2001).This change is a result of rapid growth in the Chinese motor vehicle?eet.Between

AIR POLLUTION MORTALITY IN CHINA1573

the years1990and2000,China’s motor ve-hicle?eet(excluding tractors and motorcy-cles)has increased from5.5million vehicles to over16million vehicles,with much of the increase consisting of privately owned vehi-cles,which have grown from800000vehi-cles in1990to over6million in2000(China Statistical Yearbook,2001).

While the increase in the automobile?eet is substantial,the impact in terms of automo-bile emissions and pollution is even larger. As the number of automobiles has increased, the urban road system has been unable to keep pace,leading to slower traf?c?ows and increased vehicle operational times(He et al.,2002;Fu et al.,2001;Zhou,1995).In addition,Chinese emissions are also much higher than in many other countries(Fu et al.,2001;World Bank,2001;WRI,1998) and many vehicles in China—potentially ex-ceeding50per cent in some cities—are not compliant with existing pollution standards (Fu et al.,2001;WRI,1998).Consequently, a smaller number of vehicles in China creates a relatively larger pollution problem than larger numbers of vehicles elsewhere. Noting these existing pollution problems and adding that automobile use in China is increasing rapidly and that the Tenth Five-year Plan does not speci?cally address NO2, we cautiously project a BAU annual growth of7.6per cent for NO2levels.We obtain this ?gure by?rst acknowledging that announced plans for nation-wide implementation of the Euro II auto emissions standards by2004or 2005(China Daily,2001;People’s Daily, 2003a)should lower the combined NO x and hydrocarbon emissions from new passenger vehicles by approximately half.We addition-ally assume that all these vehicles will stay compliant with established emissions stan-dards and that Chinese fuel quality will im-prove suf?ciently to allow Euro II compliance(see Walsh,2003,for details on fuel quality issues).Then,ignoring the prob-lems presented by increased congestion and inadequate traf?c management,we estimate that NO2pollution increases at half of the projected growth rate of automobiles in China.In our calculations,we use an annual growth rate of15.2per cent from the Devel-opment Research Centre in China for our calculations(Asia Times,2002),which we believe is a conservative growth estimate. Other annual forecasts are much higher, ranging from a15–20per cent increase for the next7years(China Daily,2003)to a29 per cent growth rate through to2010(Dor-gan,2003)to a linear58per cent growth rate to2006(Shirouzu and Hawkins,2003).As high as these forecasts are,they are still below the increase in sales of around70–80 per cent observed earlier this year(People’s Daily,2003b;Shirouzu and Hawkins,2003). Since we are not convinced that these recent explosive growth rates can be sustained,we refrain from constructing alternative scenar-ios with higher growth rates.

Finally,we make several observations to place our own estimate in some context. Walsh(2000)provides?gures for Beijing that amount to9per cent annual increases in nitrogen oxide levels,which is a higher growth rate than his earlier projections for Beijing and urban China(Walsh,1995).Sim-ilarly,Shao and Zhang(2001)give Guangzhou?gures suggesting annual ambi-ent NO x growth of between6.4per cent and 7.9per cent.Finally,in spite of its2008 Olympic clean-up efforts and the adoption of auto emission standards which are even more stringent than the national counterparts,we note that Beijing observed a7per cent in-crease in NO2pollution between2001and 2002(Beijing EPB,2003).

Developing Health Effect Functions

In this section,we describe the derivation of the China-speci?c,concentration–response health https://www.doczj.com/doc/9014864456.html,ing China-based studies is important because even though there is an extensive literature in the US and other de-veloped countries linking air pollution(SO2, TSP and more recently NO2)to mortality, relatively few studies have been conducted in developing countries.Although some re-searchers have relied on extrapolations from US studies(for example,Krupnick et al., 1993;and Ostro,1994),the appropriateness

VICTOR BRAJER AND ROBERT W.MEAD

1574

Table2.Deriving concentration–response mortality‘slope’factors

Pollutant Relative risk factor

Exponential b Shenyang based values

(Xu et al.,2000)

SO2all year0.0188 1.0190.000186 TSP all year 1.013

0.01300.000129

Beijing based values

(Xu et al.,1994)

SO2winter0.2010.000767

1.1393

0.00344 SO2summer 1.0672

0.097

TSP summer 1.0901

0.1300.00032

0.0010157 SO2all year 1.1095

0.158

of such concentration–response function transfers has been called into question.Al-berini and Krupnick(1997)—for example, state that the validity of such transfers may be inadequate for a number of reasons(in-cluding basic cultural factors and differing perceptions of illness).Cropper et al.(1997) go so far as to state that extrapolations from US studies to developing countries“are likely to be misleading”.Hence,for this study,we rely completely on peer-reviewed, epidemiological studies conducted in China. Not only do we use China-based health studies,but in the second part of our analysis we also make full use of the seasonal varia-tions contained within these studies.Previous valuation work(see World Bank,1997,for example)focuses on all-year estimations, which obscure interseasonal variability by averaging high seasonal pollutant levels into annual averages.It is precisely the occur-rence of these high seasonal levels,however, that can trigger a variety of health effects.In our discussion of the results,we speci?cally examine the difference that using seasonal epidemiological functions can make.For a 10-city subset of the main data-set,we use separate health equations that are derived for the winter and summer seasons,and contrast the results with health outcomes predicted from an all-year epidemiological function. All-year Averted Mortality:SO2and TSP To develop all-year SO2and TSP health equations for the38-city data-set,we turn to

Xu et al.’s(2000)study on air pollution and

daily mortality in Shenyang,https://www.doczj.com/doc/9014864456.html,ing

Poisson regressions,they regress daily death

counts against pollution and weather vari-

ables,along with indicators for Sundays and

the previous day’s mortality.Speci?cally,

their model takes the form

1n E(y t)? x t? 1n z t?? y t?j where,t?1,2,…,365(day of the year);

j?1,2,…,5(lag day for mortality);y t is the

number of deaths on day t;x t is a vector of

weather conditions;z t is a vector of air pol-

lution variables on day t;and , and are

coef?cients to be estimated.It is the esti-

mated terms that allow the authors to cal-

culate relative risk(RR)factors for the two

pollutants’various health outcomes.For ex-

ample,for the case of particulates,Xu et al.’s

estimated RR factor?1.013,implying that

the risk of all-cause mortality increases by

1.3per cent with a100- g/m3increase in

TSP.The corresponding RR factor for a100- g/m3increase in SO2is equal to1.0188. These all-year relative risk factors for SO2

and TSP appear in Table2.

The next step in calculating expected

changes in pollution-related deaths is the

derivation of a concentration–response func-

tion.Here,we adopt the basic natural expo-

nential functional form developed in the US

EPA retrospective analysis(US EPA,1997),

which evaluates the bene?ts of emissions

controls imposed by the Clean Air Act.

AIR POLLUTION MORTALITY IN CHINA1575

Speci?cally,the following exponential func-tional form is used in all of our health effect calculations

C?C(e b P?1)

where,C is the number of baseline cases (here,the baseline death rate); P is the change in ambient pollutant concentration; and b is an exponential‘slope’factor derived from the health literature.In most of the recent health literature,relative risk factors are reported which relate changes in pol-lution levels to the increased odds of devel-oping various health effects.These risk factors are related to the‘b’in the EPA concentration–response functions in the fol-lowing manner

b?1n[(1?increased odds)]/

(change in pollutant)

Thus,for the case of all-year TSP,the expo-nential‘b’value is derived as follows

1.013?e b(100)

1n(1.013)?100b

b?0.000129

The exponential‘slope’factors for all-year SO2and TSP-related mortality appear in Table2.

Seasonal Averted Mortality:SO2and TSP For seasonal SO2and TSP mortality,we rely upon Xu et al.’s(1994)examination of the relationship between air pollution and daily mortality in two residential areas in Beijing. Here,the authors regress daily Beijing death counts against pollution and weather vari-ables,along with the previous day’s mor-tality.Once again,their model takes the form 1n E(y t)? x t? 1n z t?? y t?j where,all of the variables are de?ned as before.Here,the estimated terms permit us to calculate relative risk(RR)factors for averted morality.For example,in the winter SO2case,Xu et al.’s estimated for a doub-ling of SO2is0.201,implying an SO2mor-tality relative risk factor(RR)of0.1393.5Signi?cant associations are also found for summer SO2and summer TSP.

We note that Xu et al.also estimate‘all-year’health functions for SO2and TSP. When both pollutants are included in the regressions together,however,only SO2is statistically signi?cant.As a result,we do not include an all-year TSP epidemiological equation in this set of estimations.The value and corresponding RR factor for all-year SO2,along with the remainder of the sea-sonal s and RR factors estimated in Xu et al.’s(1994)multipollutant summer/winter re-gressions,appear in Table2.6

Averted Mortality:NO2

While the health literature linking SO2and TSP exposures to premature mortality is rather well established,the linkages between NO2exposures and mortality are much more recent.Increasingly,however,the health literature is?nding more and more signi?cant associations between NO2and a variety of health outcomes,including prema-ture mortality.Such associations are being found in single-pollutant mortality models (Bremner et al.,1999;Cadum et al.,1999; Galan Labaca et al.,1999;Hong et al.,2002; Kan et al.,2003;Michelozzi et al.,1998;and Sunyer et al.,1996and2002),in multipollu-tant morbidity models(Michelozzi et al., 2000;Tsai et al.,2003;and C.-M.Wong et al.,2002)and,most importantly for our study,in multipollutant mortality models (Fischer et al.,2003;Hoek et al.,2000; Vedal et al.,2003;C.-M.Wong et al.,2001; and T.W.Wong et al.,2002).This latter ?nding is an important result because con-centrations of NO2and particulates are often highly correlated,making the use of multi-pollutant models essential for disentangling the relative impacts of the pollutants.Typi-cally,NO2coef?cient estimates taken from multipollutant equations can be as much as one-third(see Stieb et al.,2002)the size of their single pollutant equation counterparts. We therefore have only used multipollutant equations in generating all of our bene?t

VICTOR BRAJER AND ROBERT W.MEAD 1576

estimations(not only for NO2,but also for SO2and TSP).

For NO2mortality,we rely on the study by C.-M.Wong et al.(2001)that assessed the effects of NO2in both cool and warm sea-sons in Hong Kong,which as an autonomous region of China has the closest geographical and cultural ties to the cities in our study. Using Poisson regression,these authors ob-served a positive relationship during the cool season between NO2and cardiovascular mor-tality.In a multipollutant regression adjusted for the effects of SO2,a relative risk factor of 1.08was derived.Converting this factor into our exponential–concentration response function yields a slope estimate(‘b’)of 0.001828.

It is important to emphasise that six of the recent studies from various parts of the world (Bremner et al.,1999;Cadum et al.,1999; Kan et al.,2003;Roemer and van Wijnen, 2001;T.W.Wong et al.,2002;and Zegh-noun et al.,2001)generate a range of‘b’values from0.0006to0.0022665,with an average value of0.001727.For the three studies that focused on cardiovascular mortality(Bremner et al.,Cadum et al., and Zeghnoun et al.),the average b value is0.001818.Thus,the C.-M.Wong et al.(2001)results from which we calculate our‘b’value is in line with the evolving health literature for NO2-related mortality effects.

Developing Economic Values

A number of economic studies have been published in the US to value the health ef-fects of air pollution,but relatively few stud-ies have taken place in countries with signi?cantly lower incomes.Transferring economic values to other countries typically relies on a simple‘scaling’based on national per capita output(or income)ratios between the country of interest and the US.Such a procedure contains many drawbacks;the most obvious is the implicit assumption that preferences for health are similar between the country of interest and the US and are determined largely by income(which ignores the potential importance of cultural factors in in?uencing these preferences).This pro-cedure also assumes that the income elastic-ity of willingness to pay( -WTP)for improved health is equal to1.0(or that treat-ing it as1.0captures all other factors that may in?uence the WTP).7

Some recent valuation studies have begun to address the issue of income and prefer-ences in developing countries.In a Bangkok study,Chestnut et al.?nd that the WTP for avoiding a respiratory illness day actually exceeds what would be predicted following a simple national income adjustment,suggest-ing that health may be viewed as a basic necessity and“that those with lower incomes may be willing to pay a higher share of that income to protect their health”(Chestnut et al.,1997,p.1634).Alberini and Krupnick (1998;2000)reach a similar conclusion in a comprehensive health valuation study of three urban areas in Taiwan.More recently, Bowland and Beghin(2001)derive a predic-tion function for developing countries which accounts for differences in income,estimat-ing an income elasticity of WTP range of 1.52–2.27for averted mortality.In contrast, in a World Bank study(2002)calculating the health bene?ts of reducing ozone and partic-ulates for Mexico City,an -WTP of0.40is assumed for central value calculations and Quah and Boon(2003)use an -WTP of 0.32in assessing the economic costs of par-ticulate air pollution in Singapore.Finally,in the?rst major valuation study conducted in China,Zhou and Hammitt(2003)employ contingent valuation to value adverse health effects in three locations in the country. Given the scarcity of quantitative evidence in this area,we partially rely on the tra-ditional approach of converting US values using national per capita output(or income) ratios,implicitly assuming an -WTP of1.0, to produce what becomes our high-range es-timate for VSL.To generate our low-range and mid-range values,we then use quantitat-ive results from Zhou and Hammitt(2003), Bowland and Beghin(2001)and the World Bank(2003),as described below.

AIR POLLUTION MORTALITY IN CHINA1577

Valuing Averted Mortality

Increased risk of premature mortality is one effect long associated with exposure to SO2, TSP and,more recently,NO2.Early attempts to value averted mortality relying on human capital accounting measures provided an in-complete estimate of the loss to the individ-ual and to society of reduced life expectancy. Economists therefore have moved towards the more comprehensive willingness-to-pay (WTP)and willingness-to-accept(WTA) measures.These measures more completely capture the overall value of life by assessing the value that groups of individuals place on reducing the probability of giving up life earlier than would otherwise be expected. The value of averted death,or reduced an-nual risk of death,is a more accurate term for what is being measured,but the common expression used is value of a statistical life (VSL).

A comprehensive assessment of virtually all available US estimates from published WTP and WTA studies(including wage-risk, consumer behaviour and CV studies)places most reported values of statistical life in the range of$3.5–8million(Viscusi,1993),but the overall range extends from about$1mil-lion to over$15million in1997dollars.The US EPA is currently using$5.7million as their mid-range estimate for a VSL.

China Value of Life

We noted above that the traditional approach for bene?t transfer assumes -WTP of1.0.In producing a VSL for China,two previous valuation studies(Feng,1999;World Bank, 1997)implicitly follow this approach by be-ginning with mid-range WTP estimates from the US and then scaling them by the ratio of average per capita national output(or in-comes)in the two countries.The World Bank’s comparison is based on of?cial ex-change rates,but this comparison does not capture the relative domestic purchasing power of different currencies.Instead,many researchers(for example,Brajer and Mead, 2003a;and Quah and Boon,2003)prefer to compare relative incomes by using purchas-ing power parities(PPPs)as conversion fac-tors.For China,while the2001GDP per capita is only2.58per cent of that of the US using exchange rate conversion,this?gure increases to11.71per cent when using PPP (World Bank,2003).In converting from the US-based value of life estimates,we use the PPP-based national output ratio between the US and China.The resulting economic value for averted mortality is equal to($5.7mil-lion)*(11.71per cent)or$667000.We call this our high-range estimate.To generate a low-range estimate,we use the average of Zhou and Hammitt’s(2003)mean VSL, which ranges from$15000to$178000. This gives us a WTP estimate to avoid premature mortality of$96500.Finally,to generate a mid-range VSL,we compute the average of our high and low estimates.This produces a value of$382000,which we note is consistent with an -WTP of1.26.Since the mean of Bowland and Beghin’s(2001) highest -WTP(2.27)and the World Bank’s (2002)lowest -WTP of0.40is equal to 1.33,we feel that our mid-range value for VSL is a reasonable one.It should again be noted that these values are not being ascribed to the life of any individual,but to reducing the annual probability of death by a small amount.

To place these?gures in some perspective, we note that even our high-range value is not that much greater than the1999projected central value estimate of$445000developed by Feng(1999).It is also similar to a1990 value of$413000made by Liu et al.(1997) using compensating wage differentials for work-related fatalities in Taiwan.Our low-range value is60per cent of the$160000?gure used by Peng et al.(2002)in their Shijiazhuang study.We concede that our mid-range value is markedly lower than that used in Brajer and Mead’s(2003a)recent study of air-pollution-related health effects in Beijing.The consideration,for the?rst time, of a China-based CV study,and its lower estimated VSL,has led us to shift the range of China’s VSL down somewhat.8Finally, we again point out that when estimating

VICTOR BRAJER AND ROBERT W.MEAD 1578

bene?ts in any developing country,details of local culture and conditions are important (see Mendelsohn and Shaw,1996,for exam-ple)and that it may be misleading to simply transfer methods or conclusions from West-ern countries.In China,combining the poss-ibly large number of adverse health impacts on children and the elderly with the nation’s one-child policy and respect for the elderly points to a potentially higher VSL than that implied even by the direct(PPP)ratio con-version.Obviously,more China-based, health valuation studies are important for more re?ned and precise analysis.

Results

Applying the Chinese epidemiological func-tions to our projected levels of pollution in the38cities,we are able to quantify the expected number of statistical lives saved. Clearly,the bene?ts of pollution clean-up are substantial.In the WHO Scenario projections made for2002–11,rising population levels, combined with reductions in pollution,result in a steadily increasing number of averted mortality cases.Over the10-year period, these total nearly250000deaths avoided (Table3).While nearly half are attributable to NO2,TSP and SO2related reductions also generate a large bene?t on their own.The mid-range dollar value of these health im-provements approaches$100billion in2001 US dollars(Table5),with low-range and high-range estimates of nearly$25billion and$168billion respectively.Although the China scenario projections are only about two-?fths as large as those of the WHO scenario,due to the assumed lower level of clean-up success,the overall results are still sizeable.Here,about96000cases of averted mortality(Table4)are projected over the decade,with a mid-range economic value of approximately$37.2billion(Table5).

To put these numbers in context,we look at a24-city subset of our data-set.For these cities,China’s National Bureau of Statistics also publishes2001city GDP?gures(China Statistical Yearbook,2003).Using the mid-range value for mortality,we?nd that the average estimated annual gains from effec-tive pollution control to the WHO standard equal approximately 2.6per cent of city https://www.doczj.com/doc/9014864456.html,ing mid-range values for the China standard,the estimated annual gains still av-erage about1.2per cent.Overall,the average estimated annual mid-value gains range from zero in a relatively clean city like Xiamen, which already meets the China standards,to as high as9.4per cent,as a relatively pol-luted city like Taiyuan cleans up to the WHO standard.

The Seasonal Factor

In this section,we estimate averted mortality cases for a10-city subsample of the data-set for which we have seasonal SO2and TSP data.Here,our approach represents a depar-ture from some of the earlier studies(such as World Bank,1997)that used Chinese all-year epidemiological results to estimate pol-lution-related health improvements.The Xu et al.(1994)study,on which these World Bank valuations were based,estimated all-year,multipollutant regressions that showed no statistical association between TSP and mortality.Apparently,the relatively high correlation with SO2(R?0.60)contributed to some masking of possible TSP effects,for in the season-speci?c analyses done for the same data-set,Xu et al.(1994)found both pollutants to be signi?cant predictors of mor-tality in the summer months,with SO2re-maining signi?cant in the winter season.The use of these seasonal regressions allows us to capture some previously unrecognised(or at least,unaccounted for)signi?cant effects of TSP.The results appear in Table6. Breaking down the pollutants into their seasonal levels and speci?cally identifying each pollutant’s seasonal effects triples the number of averted mortality cases.In those cities with initial SO2levels above the WHO standards(Beijing,Guangzhou,Handan and Zibo),use of the seasonal data produces dra-matic differences in the numbers of averted mortality cases estimated,with summer TSP cases accounting for much of the increase. The summer/winter health equations gener-

AIR POLLUTION MORTALITY IN CHINA1579 Table3.Averted deaths:pollution down to WHO standard

City SO2TSP NO2Total Anshan38218163271

1073

Beijing27548

95619180

7412

Changsha212325246411

1764

Chengdu27954769466701 Chongqing18182

30708270

6842

Dalian244

01119

875

Fushun022********* Fuzhou4556

03616

940

Guangzhou29079012702

11622

Guiyang151011482982956 Handan3072

392331

2349

Hangzhou5125

687984

2791

Harbin04835669211527 Hengshui3771

01062

2709

Jilin City1234

3825272

3656

Jining757346521406362 Lanzhou8822

242352

8228

Maanshan93

0611

518

Nanjing0203611063142 Nanning566

32348

186

236

Pingxiang1862

01626

Qingdao2243

77188

1978

Qinghuangdao015535052058 Sanming054224566 Shanghai21208

016450

4758

Shantou029********* Shenyang8285636390310367 Shenzhen4702

04435

267

Shijiazhuang6603

388118706

8222

Taiyuan38723949376911590 Tianjin13033

1996266

6568

Wenzhou028********* Wuhan04186754511731 Wulumuqi5063

8901747

2426

Xiamen18

077

59

Xinyi01270127 Zhuhai411

0411

Zibo1191

413816

2584

Total249946

20271123749

105926

ate totals that are from131.77per cent to 492.8per cent higher than the all-year,SO2 equation.More dramatically,in5of the re-maining6cities(Hengshui,Sanming,Shang-hai,Wuhan and Xinyi),signi?cant numbers of averted deaths are estimated using the season-speci?c epidemiological functions, whereas no averted death cases are detected using only the all-year SO2function(an in?nite increase in percentage terms).More-over,in Hengshui and Wuhan,winter in-creases in SO2produce cases of averted SO2 mortality which are masked by annual aver-ages.

The seasonal factors continue to make a difference in half of the cities even when the much less stringent China standard is used as the threshold for pollution-related health ef-fects.The percentage increase in averted mortality cases is still over240per cent.For

VICTOR BRAJER AND ROBERT W.MEAD

1580

Table4.Averted deaths:pollution down to China standard

City SO2TSP NO2Total Anshan30111971655

157

Beijing15904

34312869

2692

Changsha1800661866

Chengdu0119801198 Chongqing5789

24541208

2127

Dalian0

00

Fushun0129301293 Fuzhou273

0273

Guangzhou007644

7644

Guiyang1325001325 Handan2085

3170

1768

Hangzhou1054

01212

158

Harbin0890******* Hengshui998

00

998

Jilin City97

2733161

2791

Jining57320341802787 Lanzhou6996

800

6916

Maanshan0

016

16

Nanjing0000 Nanning0

00

Pingxiang872

0872

Qingdao0

00

Qinghuangdao04400440 Sanming080080 Shanghai7309

07309

Shantou00100100 Shenyang45127251603336 Shenzhen1258

01258

Shijiazhuang965

33898785

4431

Taiyuan3696260216377935 Tianjin3528

0809

2719

Wenzhou0000 Wuhan0100425553559 Wulumuqi3108

797610

1701

Xiamen0

00

Xinyi01270127 Zhuhai0

00

Zibo0

00

Total96452

1579939808

40845

Beijing and Zibo,the higher levels of winter SO2produce additional cases which are masked by annual averages.In Handan,the higher pollution levels in the summer ac-count for the increased mortality.In addition, for Beijing,the percentage increase of the seasonal estimate over the all-year case(at nearly200per cent)is even larger than it was in the WHO standard comparisons.Overall, using our mid-range value of life,these sea-sonal variations identify an additional$3billion in gains from a clean-up to the China standard.With a clean-up to the WHO stan-dard,the mid-range valuation represents an additional gain of$9.9billion.

Summary and Conclusions

This paper explores the potential economic bene?ts to China’s urban areas should exten-sive air pollution clean-up efforts be under-taken.By projecting decreases in the levels

AIR POLLUTION MORTALITY IN CHINA

1581

Table 5.Valuation of averted mortality (billions of 2001US$)

Averted NO 2Averted TSP Averted SO 2mortality

mortality

Scenario mortality

Total

Averted mortality:China standard 9.308Low value 3.8411.525 3.942Mid value 6.03515.20715.60336.845High value

10.53827.24426.55264.333Averted mortality:WHO standard Low value 1.95611.94210.22224.120Mid value 95.4797.74447.27240.46482.541

166.714

High value

13.521

70.653

Table 6.The seasonal factor

Percentage

increase over

Seasonal City Summer TSP

all-year SO 2Summer SO 2Winter SO 2totals All-year SO 2Averted mortality cases:China standard Beijing 190.03

1875543850810357Guangzhou 000000Handan 1756240.66

66559823021

2296Hengshui 000804804?Sanming 000000Shanghai 000000Wenzhou 000000Wuhan 000000Xinyi 0005555?Zibo 016800168?Total 3631242.8059141244730213512Averted mortality cases:WHO standard Beijing 131.77524412154649905655Guangzhou 15886562448828147.63932Handan 21708353719

29907544247.65

Hengshui 0?326306902743Sanming 005170?517Shanghai 0?027*******

Wenzhou 000000Wuhan 0510********?Xinyi 0?050205021322Zibo 492.82235050817Total 9225281.92

8872

35232

6167

20193

pollution levels from a wider spectrum of different cities in China than has been used in previous work and demonstrate the ex-tremely high health costs generated by air pollution in urban China.Secondly,we ex-ploit the seasonal variations in selected cities in order to capture some previously unrecog-nised (or at least,unaccounted for)

of several speci?c pollutants under two dif-ferent clean-up targets,we are able to esti-mate the number of statistical deaths averted.We then assign dollar values to these cases and ?nd that the identi?ed direct bene?ts are substantial.

We depart from previous studies in several important ways.First,we use contemporary

VICTOR BRAJER AND ROBERT W.MEAD 1582

signi?cant effects of TSP.Here,we?nd that the seasonal effect is indeed substantial.Fi-nally,we include the health effects of NO2 pollution which is becoming increasingly problematic as China’s automobile?eet un-dergoes rapid expansion.The potential ef-fects of this pollutant are also quite large. Finally,we close with several observa-tions.First,given the transition underway in China’s economy,we note that markets for risk are“still in their infancy”(World Bank, 1997).Therefore,to develop meaningful, China-based economic mortality and morbid-ity values,additional valuation studies need to be conducted.Secondly,our focus on mortality omits a number of other air pol-lution consequences or clean-up bene?ts. Some of these omissions include non-fatal, pollution-induced morbidity bene?ts(see Brajer and Mead,2003b)as well as a host of non-health,pollution-related impacts,includ-ing reductions in damage to ecosystems and materials as well as improvements in visi-bility.Thirdly,these bene?ts and valuations are based solely upon a10-year projection subject to multiple uncertainties.Clean-up efforts involving long-term projects or per-manent changes to lower pollution fuels will produce additional bene?ts for China’s urban areas well beyond2011.Finally,we note that the values estimated here must be viewed as just that,estimates of the mortality-related health bene?ts resulting from improved air quality.Recent advances in health research have narrowed the bounds of uncertainty and there is some emerging consensus on key economic values,but there are still many questions about where,within a range of probable effects or dollar measures,the‘real’values lie.

Notes

1.The Chongqing numbers come from a news

release publicising the new,lower pollution levels reached by the city.Actual levels are not reported,so we use the lowest levels of pollution within the reported categories.

Consequently,the pollution levels used are probably a lower https://www.doczj.com/doc/9014864456.html,nzhou SO2and TSP?gures are derived from a?gure in the

Gansu Province annual report.The NO2 number is the provincial average which is probably lower than the actual levels in Lanzhou.

https://www.doczj.com/doc/9014864456.html,ing the method of determining sample size

described in Madsen and Moeschberger (1983),random samples are drawn from the daily pollution indexes until the margin of error for the sample mean is within10per cent at the95per cent con?dence interval.

3.We use the pre-1999WHO standards to

indicate that the Chinese standards are merely a?rst step and to note that there are signi?cant gains to meeting even more strin-gent standards.The WHO has since discon-tinued a standard for TSP because adverse health effects were being found at even lower levels of pollution and because a re-search switchover to PM2.5has yet to yield enough information to establish a new WHO standard.While we continue to use TSP because our studies are based upon TSP pollution,the lack of a standard does not imply a lack of health effects.In fact,op-posite is true:there is no standard because there is no currently identi?ed‘safe’level of particulate pollution.

4.The class2standard is a pollution index

level between50and100.For SO2,PM10 and NO2this range consists of pollution levels of50–150,50–150and80–120 g/m3, respectively.For TSP,the range is120–300 g/m3.

5.This is calculated using the following rela-

tionship: lnE(y t)? lnSO2.For a doub-ling of SO2, lnSO2?0.693.It follows that lnE(y t)?(0.201)(0.693)?0.1393.The risk of winter mortality is thus estimated to in-crease by13.93per cent with each doubling in SO2concentrations.In the same re-gression,the coef?cient on the ln TSP vari-able is not statistically signi?cant;therefore, we assume that in this case no TSP-related mortality effect exists,separate from the SO2-related effect.

6.Since SO2and TSP,the only two pollutants

analysed,were fairly highly correlated (R?0.6),we were careful to base our derivations on Xu et al.’s‘two-pollutant models’,models in which the estimated coef?cients for both pollutants were statisti-cally signi?cant.This minimises the possibil-ity of‘double counting’avoided deaths;

obviously,estimating RR factors from the single pollutant equations would impart an upward bias on any results obtained.

7.This point is made in Alberini et al.(1996).

However,in a theoretical investigation be-tween income and the WTP for environmen-tal goods,Flores and Carson(1997)show

AIR POLLUTION MORTALITY IN CHINA1583

that,despite being related,knowledge of the ordinary income elasticity of demand is “insuf?cient to determine the magnitude or even the sign”of the income elasticity of WTP.

8.Despite the fact that Zhou and Hammitt’s

(2003)CV work was conducted completely in China,we hesitate to adopt the average of their mean VSL range as our mid-level value.By their own admission,some form of hypothetical bias(or respondent bias)may exist in their study.When respondents were offered risk reductions of different sizes as part of the CV questioning,there was no signi?cant difference in their WTP re-sponses.

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(生产管理知识)制剂生产过程中常见问题和处理方法

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度小,流动性差,可压性差,重新制粒。 ⑤颗粒的流动性差,填入模孔的颗粒不均匀。 ⑥有较大块或颗粒、碎片堵塞刮粒器及下料口,影响填充量。 ⑦压片机械的因素。压力过小,多冲压片机冲头长短不齐,车速过快或加料斗中颗粒时多时少。可调节压力、检查冲模是否配套完整、调整车速、勤加颗粒使料斗内保持一定的存量等方法克服。 2.裂片 片剂受到震动或经放置时,有从腰间裂开的称为腰裂;从顶部裂开的称为顶裂,腰裂和顶裂总称为裂片,原因分析及解决方法: ①药物本身弹性较强、纤维性药物或因含油类成分较多。可加入糖粉以减少纤维弹性,加强黏合作用或增加油类药物的吸收剂,充分混匀后压片。 ②黏合剂或润湿剂不当或用量不够,颗粒在压片时粘着力差。 ③颗粒太干、含结晶水药物失去过多造成裂片,解决方法与松片相同。 ④有些结晶型药物,未经过充分的粉碎。可将此类药物充分粉碎后制粒。 ⑤细粉过多、润滑剂过量引起的裂片,粉末中部分空气不能及时逸出而被压在片剂内,当解除压力后,片剂内部空气膨胀造成裂片,可筛去部分细粉与适当减少润滑剂用量加以克服。 ⑥压片机压力过大,反弹力大而裂片;车速过快或冲模不符合要求,冲头有长短,中部磨损,其中部大于上下部或冲头向内卷边,

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关于环保的英语好句子 没有地球的健康就没有人类的健康与自然重建和谐,与地球重修旧好垃圾混置是垃圾,垃圾分类是资源。 关于环保的英语好句子(一) 1、But save square inch ground, stay with descendant Geng. 但存方寸地,留与子孙耕。 2、Protection of the environment is everyones responsibility. 保护环境,人人有责。 3、Rescue the Earth is to rescue future. 拯救地球就是拯救未来。 4、The amount of water which is suitable to drink is less and less. 水的量是适宜的饮料是越来越少了。 5、But some people dont care about it. 但有些人不关心它。 6、It is very important to take care of our environment. 这是非常重要,我们要保护我们的环境。 7、Now p eople pay more attention to how to pretend our environment .With the development of science and technology,it

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片剂及其生产过程中常见问题和处理方法

片剂及其生产过程中常见问题和处理方法

片剂及其生产过程中常见问题和处理方法 于亮1 马飞2 (1.山东聊城建设学校,山东聊城252000;2.聊城万合工业制造有限公司,山东聊城252022) 摘要:通过对片剂及片剂生产过程中可能出现的问题和处理方法简单介绍,阐述了片剂生产过程中造成质量问题的诸多因素,为保证片剂质量提供了一些解决和预防的办法和经验。 关键词:片剂;片重超差;问题;处理方法 1 片剂 片剂可定义为用压制或模制的方法制成的含药物的固体制剂,可用稀释剂,也可不用。从19世纪后期开始片剂已经广泛使用并一直深受欢迎,到19世纪末随着压片设备的出现和不断改进,片剂的生产和应用得到了迅速的发展。近十几年来,片剂生产技术与机械设备方面也有较大的发展,如沸腾制粒、全粉末直接压片、半薄膜包衣、新辅料、新工艺等。总之,目前片剂已成为品种多、产量大、用途广,使用和贮运方便,质量稳定的剂型之一,片剂在中国以及其他许多国家的药典所收载的制剂总量中,均占1/3以上,可见应用之广。 1.1 片剂的特点 1.1.1 片剂的优点 (1)一般情况下片剂的溶出速率及生物利用度较丸剂好; (2)剂量准确,片剂内药物含量差异较小; (3)质量稳定,片剂为干燥固体,且某些易氧化变质及潮解的药物可借包衣加以保护,所以光线、空气、水分等对其影响较小; (4)携带、运输、服用较为方便; (5)可实现机械化生产,产量大,成本低,卫生标准也容易达到。 1.1.2 片剂的缺点 (1)片剂中药物的溶出速率较散剂及胶囊剂慢,其生物利用度稍差些; (2)儿童和昏迷病人不易吞服; (3)含挥发性成分的片剂贮存较久时含量下降。

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