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Economics Student Publications Economics
1995
Economic- Air Pollution Models: An Econometrics Regression Approach
Muhammed R. Yunus Wright State University - Main Campus
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This Master's Culminating Experience is brought to you for free and open access by the Economics at CORE Scholar. It has been accepted for inclusion in Economics Student Publications by an authorized administrator of CORE Scholar. For more information, please contact [email protected]. ECONOMIC - AIR POLLUTION MODELS:
AN ECONOMETRICS REGRESSION APPROACH
A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science
By
Muhammad R. Yunus B.S., Hasanuddin University, 1985
1995 Wright State University August 30. 1995
I HEREBY RECOMENDED THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Muhammad R.Yunus ENTITLED Economic- Air Pollution Models; An Econometrics Regression Approach BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science,
Dr, Thomas Traynor Faculty Reader
D and Applied Economics August 30. 1995
I HEREBY RECOMENDED THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Muhammad R.Yunus ENTITLED Economic- Air Pollution Models: An Econometrics Regression Approach BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Sciencec
Dr. James A. Swaney Faculty Supervisor
Dr. Thomas Traynor Faculty Reader
Roger Sylvester Director M.S., in Social and Applied Economics ABSTRACT
Yunuse Muhammad R. M.S., Department of Social and Applied Economics, Wright State University, 1995. Economic- Air Pollution Models: An Econometrics Regression Approach.
Economic- air pollution models have been developed using an
econometrics regression approach for the ambient air
concentration levels of total particulate matter (TPM) ,, I960-
1990, sulfur oxide (SOx), 1962-1992, and carbon monoxide (CO),
1970-1992. There are some difficulties in determining the
explanatory variables because many variables which affect
ambient air levels may also be related to others explanatory variables. Furthermore, the lack of available ambient air
concentration level data is another constraint in developing
the models. Yet, this study suggests that while gross domestic product per capita has increased over time, ambient air levels
of TPM and SOx pollutants have fallen significantly. Ambient
air levels of CO pollutant have fallen as well, but not
significantly. This may be due to the very limited number of
observations available in this model. The Clean Air Acts have
significantly improved ambient air quality of those three pollutants through reducing emission rates, emission per
quantity of the total output (i.e. GDP). On the other hand
increase in population has significantly increased pollution. Page
I. INTRODUCTION ...... 1
Background ...... 1
Earlier Study ...... 2
Objective . 5
Data ...... 4
II. AIR POLLUTION:SOURCES, TRENDS, AND RESPONSE . . 7
Sources of Air Pollution . 7
Clean Air Act ...... 9
Trends ..... 10
Public Opinion ..... 15
III. EMPIRICAL MODEL ..... 17
IV. EMPIRICAL FINDING .... 20
Results ...... 20
Discussion...... 22
V. CONCLUSION ...... 28
BIBLIOGRAPHY ...... 37 Table Page
1. Air Pollution Sources .... 8
2. Uncontrolled Emission from Different Types
Of FUelS c „ . c , o , „ ~ o . . . o , . a ...... a . o o o o « o . c . .„ 11
3. National Ambient Air Quality Standards 13
4. Public Opinions Economic Growth vs
Environmental Protection ...... 16
5. Public Opinion; Percentage Very Concerned
About National Environmenta1 Problems ...... 16
6. Sample Characteristics ...... 20
7. Estimates of TPM Ambient Air Concentration
Level Model, 1960-1990 25
8. Estimates of SOx Ambient Air Concentration
Level Model, 1962-1992 ... 26
9. Estimates of CO Ambient Air Concentration
Level Model, 1970-1992 ...... 27 Figure Page la. U.S. Trends in Ambient Air Quality for
TPM, SOx, and ozone pollutants, 1970-1992 ... 30 lb. U.S. Trends in Ambient Air Quality for
N02, CO, and lead pollutants, 1970-1992 ..... 31
2. Number of Areas Not Attaining Air
Pollution Standards ...... 32
3. Air Pollution Abatement Expenditures by
Source, 1972-1991 ...... 33
4. U.S. Trends in Energy Consumption per GDP,
1960- 1992 ...... 36
5. Energy Conservation in Industrial Sector,
1960- 1985 ...... 35
6. Motor Vehicle Efficiency, 1960- 1990 ...... 36 INTRODUCTION
BACKGROUND
Over the years various concepts of economic system - environment relations have been proposed. Some of them have dealt with input - output analysis, material balances, stock flow models and the use of super models. Though there is still lack of agreement either in the common understanding, or in the method used, or in the results of the models in explaining and predicting the human activity effects on the environment, study of this issue has never decreased (Hafkamp, 1991). The difficulties in formulating the models probably lie in the properties of the environment itself. The biological, chemical and physical processes in the ecosystem are too complex to be understood in sufficient detail at present (Jorgensen, 1989).
Furthermore, what economic variables contribute to the states of the environment or to the emission levels and how strong they interact with each other (related to the multicollinearity problem in regression models) are not easily determined. Another constraint is the lack of environmental data, perhaps because environmental monitoring is relatively recent and expensive.
However, we may say that the root of every case of pollution released to the environment is human decision behavior (Hafkamp, 1991). Decisions of producers to manufacture cars, decisions of consumers to drive those vehicles, and decisions of farmers to apply fertilisers and pesticides, for example, all produce pollution.
The idea of idiscommodityi, as introduced by Coddington
(1970) refers to anything that people would choose not to have or which renders a disservice. Noise, pollution of the air by gaseous waste, and of water and land by industrial waste, may be categorized as discommodities. According to Coddington, processes of consumption may be considered as transformation of commodities into discommodities.
The mid-19609 s of economic growth theory poses a compelling analogy between the laws of thermodynamics and that of economics. The first law, the matter can not be destroyed but only transformed from one state to others, is translated that pollutant or waste generated from production and consumption activities must be present somewhere in the physical system. Consequently, the capacity of that system to absorb waste or pollutants must be taken into account when planning economic activity. If we reduce pollutant or waste by recycling, however, according to the second law no process can achieve 100 percent efficiency. This is translated that complete recycling is impossible (Markandya and Richardson,
1995).
EARLIER STUDY
Janssen and Rotmans (1995) offer a theoretical model for allocating fossil C02 emissions in response to the global green-house effect = The model supposes that such international policy targets for €02 emission levels are to foe met. For this, global C02 emissions level during a fixed period are restricted under "the global €02 emission budget", Allocation of a (restricted) fossil C02 emissions budget to regions is based on indicators: GDP (economic affluence), population size, and primary energy use, because those are the main underlying factors associated with €02 emissions. Allocation of regional emission rights, regional permissible amounts of
€02 emitted in the future, is defined as the fractions for regions of the global €02 budget minus the historical regional
CO2 emission.
Another study using regression analysis was done by
Ringquist (1993), using state cross sectional data for the
United States. Ringquist models changes in state ambient concentration levels for the periods 1973-75 and 1985-87 for sulfur dioxide and nitrous oxides. Fossil fuel consumption is an explanatory variable in his model as well. Ringquist uses value added approach to model the seven industrial categories most responsible for air pollution, along with some other explanatory variables. Those other variables are regulatory program strength, state expenditures for pollution controls, the U.S. Environmental Protection Agency (EPA) abatement and state abatement activities. For each state, Ringquist ranks the state air pollution control programs from weakest to strongest. The stronger pollution control programs are associated with greater reductions in pollution. SPA and state abatement activities reflect the number of federal and state activities (i.e. enforcements) undertaken in each state„ An earlier regression analysis was performed by MacAvoy (1979) .
This model analyzes emissions per industrial output GNP by six industrial categories: mineral, automobile, chemical, primary metal, electric utility, and petrol refining. Observation involves the U.S. 1968-76 annual data. As explanatory variables he uses time trends to measure progress in technology, industrial rate of capacity utilization to measure cyclical production conditions, and regulation given in dummy variables. The study concludes that in those six industrial categories, regulation had a significant effect in reducing pollution only in the automobile and electric utility industries. MacAvoy concludes that regulations have no significant impact in reducing pollution (MacAvoy, 1979, p.
102-103).
Despite the use of different explanatory variables and different dependent variables (except for sulfur oxides), this study generally supports Ringguist's finding that regulations significantly improve ambient air quality, while it contradicts MacAvoy's finding. A rise in industrial activity in Ringquist1s study significantly increases pollution. Our study finds a statistically significant relationship between increase in per capita gross domestic product and increase in total particulate matter (TPM) and sulfur oxide (Sox) pollutants = The use of population as explanatory variable in our models accords with Janssen and Rotmans9 theoretical model.
OBJECTIVE
The objective of this study is to model the U.S. economic activity- air pollution relations using econometrics regression methods. The models are then analyzed. In those models, one variable, called dependent variable, is given as a linear function of one or more variables, called explanatory or independent variables. The basic assumption is that there is a relation between economic activity (i.e. GDP) and ambient air concentration levels. The study is focused on ambient air concentration levels of three regulated emission: total particulate matter (TPM), sulfur oxide (SOx), and carbon monoxide (CO). The data of the three other ambient air levels, nitrogen dioxide (N02) , ozone (03) and lead (Pb) may not be sufficient for regression analysis since the data starts from
1974-1975.
DATA
The U.S. data used for empirical analysis is the time series data, a set of period observation on the values that a variable takes at different year. The sample size varies and depends on the availability of data (i.e. ambient air concentration level data), but in the range 1960-1992. The ambient air concentration data is obtained from the
Environmental Protection Agency (EPA) data, where data prior to 1972 is based on the National Air Sampling Network (NASN) data. GDP is measured in 1987 U.S. billion of dollars, while population is in thousand of people. SOURCES OF AIR POLLUTION
Air pollution is the presence of one or more contaminants in the ambient air in quantities, qualities, and duration which cause injuries to humans, animals or plants, or interfere with the comfortable enjoyment of life and property
(CRCi 1989 and Salvato, 1992).
Processes that are sources of air pollution include chemical reactions, evaporation, burning, crushing and grinding, drying and baking, and combinations of those processes (Salvato, 1992), that we may find in many economic activities. Sources of air pollution have been identified and in many cases are well characterized. Table 1 summarizes the man-made air pollution sources with examples for each source category.
Many of the most pressing environmental concerns in the
U.S. are linked to the consumption of energy. In fact, nearly all the criteria pollutants are by products of combustion of fossil fuels, which continue to be the primary energy sources in the United States. Fossil fuels are the leading sources of oxides of sulfur, carbon and nitrogen, and particulate matter, four of the "criteria pollutants" targeted by the CAA (CEQ,
1990). Table 2 shows examples of the amounts of uncontrolled emission from different types of fuels in kilograms of pollutants per billion joules calory delivered by fossil fuels. Table 1 Air Pollution Sources
Category- Examples Pollutants
Chemical plants Petroleum refineries, Hydrogen sulfide, pulp mills, super oxides of fluorids phosphate, fertilizer organic vapors, plants, cement mills. odors, particles. Crop spraying Pest and weed control Organic phospl and dusting. lead, chlorinat - hydrocarbon, Crushing,grin Road-mix plants. Mineral and orga ding and particulate. screening. Demolition Urban renewal Field burning Stubble and slash Smoke, fly ash, burning soot. Frost- damage Smudge pots control Fuel burning Home heating and power Oxides of sulfur and plants. of nitrogen, carbc ■ monoxide, smoke, ode- Fuel fabrication Gaseous diffusion. Inks Photography and printing Fluoride. Metallurgical Smelters, steel mills, Metal flumes (lead plants aluminum refineries zinc, arsenic), fluoride, oxides of sulfur Milling Grain elevators Motor vehicles Autos, buses, trucks. Oxides of sulfur and of nitrogen, carbon monoxide,smoke,odor Nuclear- device Atmospheric explosions Radioactive fallout testing (strontium 90, ce sium 137,carbon-14) Nuclear fusion Nuclear reactors Argon 41. Ore preparation Crushing, grinding, and Uranium and screening. beryllium dust Refuse burning Community and apartment Oxides of sulfur, house incinerators,open smoke, fly ash, burning dumps. organic vapors, odoj. Solvent cleaning Dry cleaning, de Spent- fuel greasing . processing Chemical separations Iodine-131 Automobile assembly, Hydrocarbon, other Spray painting furniture, appliance oxides. finishing. Waste recovery Metal scrap yards, auto Smoke, soot, organic body burning, rendering vapors, odors. plants.
Source: Practical Handbook of Environmental Control, 1989, reprinted from Chemical Engineering, October 14,1968. CLEAN AIR ACT
The quality of ambient air is measured based on time- average pollutant concentrations in the air, usually at the ground level, where people, animal, plants and property are often exposed to the pollutants. Air pollutants range from completely colorless and odorless gases such as carbon monoxide to highly visible dense soot such as particulate matter„ Lead, asbestos, and beryllium pollutants are highly toxic in minute amounts, Others such as carbon monoxide can cause headaches, angina attacks, even death at a very high concentration (CEQ, 1981).
The legislative framework for managing the ambient air environment is based on the Clean Air Act (CAA) , which was developed in response to the increasing environmental concern
(CF, 1987). For this the U.S. Environmental Protection Agency
(EPA) has established national ambient air quality standards
(NAAQS) for six common pollutants : total particulate matter, sulfur dioxides, nitrogen dioxides, carbon monoxide, the organic compounds that contribute to the formation of ozone in the lowest layer of the atmosphere, and lead. The NAAQS were promulgated in April 1971 following passage of the Clean Air
Act amendments (CAA) of 1970. The ambient air quality standards specify maximum allowable concentrations of those pollutants in the air (CF, 1987 and CEQ, 1989) . The acts primary standards are intended to protect public health, while the secondary standards are intended to protect public welfare including property, vegetation and aesthetic values from
damage. The CAA of 1970 required achievement of the NAAQS to
protect human health by 1975. The 1977 CAA extended the
deadline for attainment of all primary standards in most areas
to 1982 (CEQ, 1981), with further extension to 1987 possible
for ozone (03) and carbon monoxide (CO) (Tietenberg, 1994).
The 1977 CAA also codified prevention of serious deterioration
(PSD) standards to protect relatively unpolluted areas.
Moreover, the acts required the EPA to specify all areas not
meeting the 1970 CAA deadline as non-attaining regions
(Tietenberg, 1994). Among the many provisions of the CAA
amendments of 1990, the act attempts to reduce pollutants from
automobiles and other sources (HC, CO, NOx, and particulates)
and to require increased use of cleaner motor vehicle fuels
(CEQ, 1991). Title 3 of this act mandates the regulation of
189 toxins emitted from municipal incinerators and commercial
and industrial sources (Salvato, 1990). The 1990 CAA
amendments revised, expanded, and extended the national
ambient air quality standards (NAAQS).
TRENDS
To provide an rough view of recent ambient air quality
trends, Figures 1-a and 1-b plot the index values (1975=100)
of the ambient air concentration levels of TPM, SOx, ozone,
N02, CO, and lead in the during period 1970- 1992. Figure 2
compares the number of areas not attaining the ambient air quality standards in 1978 and in 1985. Despite population growth, economic development, and enormous increases in the use of vehicles, progress in improving the nation1s ambient air quality is evident at least for some pollutants. Levels of
Table 2 Uncontrolled Emission from Different Types of Fuels
Fuels Effic TPM SOx NOx HC CO iency Industrial boilers: Wood 0.70 500 53 400 400 450 Anthracite 0.80 2800 820 320 22 45 Bituminous coal 0.80 94 1310 240 4 20 Distillate oil 0.90 8 1120 83 4 19 Natural gas 0.90 7 a) 99 2 8
Residential heating stoves: 0.50 2700 30 100 6800 17000 Wood 0. 65 46 200 250 100 1000 Anthracite 0. 65 550 1100 270 530 5300 Bituminous coal 0.5 11 1170 71 4 20 Distillate oil 0.85 7 a) 38 4 10
Residential cooking stoves: Tropical wood 0.15 3800 250 300 3200 34000 Hawaiian cowdung 0.15 10000 3200 44000 Indian coal 0.20 280 2200 460 2200 27000 Coconut husks 0.15 17000 54000 Natural gas 0.80 0.5 a) 10 5 250
Source: Statistical Record of the Environment, 1992 from Environment December 1988. Note: a) negligible.
some pollutants seem to have dropped much more than levels of
others. Nationally, the level of TPM concentration in the ambient air decreased approximately 35 % between 1970 and 1980, and approximately 25 % between 1980 and 1992. The level of CO dropped approximately 40 % between 1970 and 1980, and approximately 25 % between 1980 and 1992. In the same periods, the concentration level of SOx fell approximately 60 % and
15 II02 level decreased approximately 25 % during 1974-=
1980, and approximately 20 % during 1980- 1992. The ambient air concentration level of ozone dropped approximately 5 % between 1970 and 1980, and approximately 20 % between 1980 and
1992. The lead concentration level decreased by approximately
42 % from 1970 to 1980, and dropped sharply by about 90 % between 1980 and 1992.
A non-attaining area is an area that fails to accomplish an EPA ambient air quality standard (CEQ, 1978). The number of counties or portions of counties that failed to attain the primary or secondary standards for particulate matter dropped from 421 in 1978 to 290 in 1985. At the same time the number of areas not attaining the S02 standards fell from 101 in 1978 to 60 counties or portions of counties in 1985. Moreover, for
C02 the number of non-attaining areas dropped from 190 counties or portions of counties in 1978 to 152 in 1985. The number of non-attaining areas for ozone levels decreased from
607 counties or portions of counties in 1978 to 368 in 1985.
Even though on average the national ambient air levels of some pollutants have met the primary NAAQS (since around 1970 for Table 3
National Ambient Air Quality Standards (NAAQS)
Pollutants Averaging time Primary Secondary standard standard Particulate Annual 75 pg/m3 60 pg/m3 matter (TPM) (geometric mean) a) 24- hour 260 jag/m3 150 p.g/m3
Sulfur Oxide Annual 80 ytg/m3 (Sox) (arithmetic (0,03 ppm) mean) 365 pg/m3 24-hour (0.14 ppm)
3-hour 1300 pg/m3 (0,5 ppm)
Carbon 8-hour 10 mg/m3 No secondary monoxide (9 ppm) standard (CO) 1-hour 40 mg/m3 (35 ppm)
Nitrogen Annual 100 yig/m3 Same as dioxide (arithmetic (0.05 ppm) primary (N02) mean)
Ozone (03) Maximum daily 235 pg/m3 Same as 1 hour average (0.12 ppm) primary
Lead (Pb) b) Maximum 1.5 pg/m3 Same as quarterly primary average
Source :Environmental Trends, 1989, from National Air Quality and Emission Trend Report, 1988, Office of Air Quality Planning and Standards Technique Support Division, EPA. Notes: a) PM-10 standards, 50 pg/m3 (annual arithmetic mean) and 150pg/m3 (24-hour), were promulgated in 1987 to replace TPM standards, b) Lead standards were proposed in December 1977.
TPM and SOx, since around 1980 for CO, since around 1990 for ozone, and before 1975 for N02 and lead), many metropolitan areas still continue to exceed the standards at least for one pollutant. In fact, over 100 urban areas in the U.S. have yet to meet the primary standards for at least one of the six
"criteria" pollutants (CQ, 1991).
During the 20 years from 1972 trough 1991, the U.S. spent approximately a total of $ 500 billion in constant 1937 dollars for air pollution control. This included abatement expenditures for mobile sources (cars, trucks, and buses) and stationary sources (industry, and power stations) by both private and government sectors. The expenditure share for mobile sources in the total air pollution control expenditures gradually increased by 1990 and fell somewhat in 1991. That share was only approximately 30 % in 1970, and increased to approximately 55 % in 1990.
As mentioned earlier, the role of U.S. energy consumption on the quality of ambient air is undeniable. The following figures illustrate how this country consumes energy. A primary indicator of the intensity of energy use is the relationship between total energy consumption and real gross domestic product. Figure 4 shows, however, that energy consumption per dollar of GDP has declined persistently over the period 1960- 1992. It fell from 22,000 Btu per 1987 dollar of GDP in 1960 to 16,500 in 1992, a drop of 25 %. Two other indicators of energy use are energy conservation in the industrial sector and fuel efficiency in the transportation sector exhibited in Figures 5 and 6. Energy conservation (the use of wore energy- efficient processes) and fuel efficiency
(the increase of fuel rate) evidently seem to have occurred in both the industrial and transportation sectors. Consumption of energy has fallen from approximately 12,000 Btu per 1982 dollar of industrial output in 1960, to approximately 8,700 in
1985, a drop of 12.25 %., On average, the fuel rate of all vehicles including passenger cars, motorcycles, buses, and trucks has increased from approximately 12.40 miles of travel per gallon of fuel in 1960, to approximately 16.30 in 1990, an increase of 31.40 %. The fuel rate of passenger cars alone has increased from approximately 14.30 miles per gallon in 1960, to approximately 20.90 in 1990, an increase of 46.50 %.
PUBLIC OPINION
The two following tables present public opinion surveys carried out in the US from Gallup Polls in 1984 and in 1990 with a coordinated framework suggested by OECD. Table 4 compares the public opinion concerning environmental protection versus economic growth, while Table 5 compares the percentage of persons highly concerned about national environmental problems for both two year surveys. As shown by the 1984 and 1990 polls the percentage of people who thought that the environmental protection problem should be given more priority have increased. In fact, in general more people have been very concerned about pollution problem. The degree of concern appears to be correlated with the increase of economic well-being* This shift in public opinion has increased the government environmental protection efforts (CF,
1984) through monitoring, regulations, enforcement, and abatement expenditures.
Table 4 Public Opinion : Economic growth vs environmental protection
Year Number of Priority to Priority Donr t ‘total envi to know (%) (%) inter ronmental economic views protection growth (%) (%) 1984 1590 62 28 10 i.OO 1990 1223 71 19 10 100
Source : OECD Environmental Data Compendiurns 1987 and 1990
Table 5 Public Opinion : Percentage Very Concerned About National Environmental Problems
Year Number Industrial Air Water Accidental Nuclear of waste pollution pollution damage to waste inter disposal marine en disposal views vironment 1984 1590 64 46 52 54 69
1990 1223 n. a. 58 64 52 48
Source : OECD Environmental Data Compendiums 1987 and 1990. Note : n.a. = not available The pollution (E) generated from economic activity in the production and consumption context may be determined by the quantity of the total output (H), the quantity of pollution good p (Xp) in the total output, and emission rate (e) , emission per quantity of the pollution goods p. Furthermore, we assume that emission rate (e) is a function of regulations since the role of regulations is actually to reduce emission rate (e),
E = f (H, Xp, e(REG)) ...... (1)
Equation (1) describes this process. If the quantity of the total output (H) increase due to the increase of quantity of the pollution goods p, pollution will increase, and vice verse. Next, if the increase of the total output (H) is caused by the decrease of quantity of the pollution goods p (Xp) and an increase of quantity of the non-pollution goods c (Xc) , where H= Xp + Xc, then pollution may fall. Moreover, a decrease in the emission rate (e) (due to regulation stimulations) obviously will reduce pollution, and vice verse.
Since production and consumption of all goods and related products potentially cause pollution (they differ only in the pollution intensity), we may say that most of the part of the total output (H) comes from production and consumption of the pollution goods p (Xp),
One of the assumptions of the classical linear regression model is that there is no multicollinearity among the explanatory variables. Many of the explanatory variables that effect the state of the environment (e.i. ambient air levels), however, may causally be related to the other explanatory variables as well. Therefore,, caution must be given in choosing those explanatory variables. For example, since most heavily polluting industries are also energy intensive, the dependence upon fossil fuel may be affected by change in industrial activity (Ringquist, 1992). Similarly, the strength of regulations may increase abatement expenditures spent by both business and government sectors. Furthermore, progress in technology, particularly in acquiring a cleaner technology, may be related to the regulation stimulation.
The econometrics model of air pollution relation in this study is developed based on the equation:
(A/POP)=a1+bn CAAn+ c2 CHLN(GDP/POP) + c2CHLNPOP+ u2 . (2)
where CAAn are dummy variables controlling the effects of the regulations. There are two assumptions regarding the Control
Air Act (CAA). First, for simplification the model assumes that regulations are in place the year following the passage year of that acts. Second, CAAn have a value of zero before and including the passage year of the acts, and one after ISthafco By this the effect of each CAA is separated in the estimates. GDP is U.S. gross domestic product, and POP is the
U.S. population. A is the ambient air concentration levels of pollutants, ui is the disturbance or error term to capture other exogenous factors, but are not taken into account explicitly, such as climate. CH and LN denote change and logarithm, respectively. RESULTS
The means and standard deviations of the ambient air concentration levels of total particulate mattert sulfur oxides, and carbon monoxide used in estimation are provided in
Table 6. The results of the regression estimates are presented
in Tables 7, 8 and 9.
Table 6 Sample characteristics
Variables Mean Standard deviation
Total 62 o 20 (jug/m3) 14.15 particulate matter (TPM)
Sulfur oxide 47.67 (m g/m3) 28.14 (Sox)
Carbon monoxide 101.16 (mg/m3) 31.74 (CO)
Estimates of the parameters are typically different from
zero (except for the CHLN (GDP/POP) parameters in the CO ambient air level model), and many of them at high levels of significance. The R squared 0.956 in the TPM ambient air level model indicates that 95.6 % of the variation in the TPM air concentration per capita is explained by variation in the
CAAs , change in the log of GDP per capita, and change in the log of population. In the two other models, Sox and CO ambient air level models, 97.0 % variation in Sox air concentration per capita, and 90.80 % variation in CO air concentration per capita are explained by variations in the independent variables. The null hypothesis that there is no relation between the change in gross domestic product per capita and ambient air concentration levels per capita observed for total particulate matter and sulfur oxide is rejected. However, we fail to reject this null hypothesis in the CO ambient air concentration model. The estimated parameters of the CAAs are negative and statistically significant, implying that those regulations played a positive influence on ambient air quality. Moreover, as expected, the estimated parameter of change in log of population are positive and statistically significant for the three models.
Increase in population is associated with increase in pollution. The Durbin- Watson statistic for autocorrelation in the SOx and CO ambient air concentration level models fall in the rejection of positive or negative regions. Therefore, for these two models autocorrelation, the correlation between members of series of observations ordered in the series data, is not a problem. In the TPM ambient air concentration level model the Durbin- Watson statistics fall in the indeterminate regions. The Breush- Pagan test is used to detect heteroscedasticity. Heteroscedasticity is present if the variance of each disturbance term u*, conditional on the chosen values of explanatory variables, is not some constant number. The 5 % critical Chi-square values for 4 df (4 independent variables) is 9,487, and for 5 df (5 independent variables) is 11,070, Since the Chi-square statistics in the
TPM and CO air concentration level models are less than the critical Chi square values for 4 df, we fail to reject that there is heteroscedasticity in the error variances in the two models. However, in the SOx ambient air concentration model the Chi square value exceeds the critical Chi-square value for
5 df, indicating that heteroscedasticity is present in this model. This model may require more observations. The positive sign of the estimated parameters of CHLN (GDP/POP) in the three models are as expected. However, the estimated parameter for
CO ambient air level model is in question since it is statistically not significant.
DISCUSSION
Perhaps the most interesting finding here is that while gross domestic product per capita (GDP/POP) increased over the period, the quality of ambient air per capita for two observed pollutants, total particulate matter (TPM), and sulfur oxide
(Sox) has significantly improved.
Since the processes of production and consumption of goods may cause pollution (different only in their pollutant intensity) „ reducing the share of higher pollution goods in the total output, or reducing emission rate may have the effect in improving air quality, which is given in equation
(1). As shown by Figures 4, 5 and 6, conservation of energy, the use of more efficient energy processes and techniques in the economic activity, and the fuel efficiency of motor vehicles seem to have occurred approximately after 1970, The marginal product, that is, the change in output (i.e. GDP) for the change in energy consumed, has increased. This may have caused the falling emission rate (emission per total output).
The EPA reported that since 1970 total emissions of sulfur oxide, carbon monoxide, nitrogen oxide, volatile organic compound, particulate matter, and lead have declined due to the use of cleaner fuels with lower sulfur content, improvement in processes and emission control devices, and regulation (EPA, 1991).
While changes in fossil fuel prices may have affected energy consumption, these changes may also have had impact on the total output. With lower energy prices, people tend to consume more energy, and thus increase the total output, and vice verse. A study by John Tatom (1979) suggests this causality. He estimates the production function model for the
U.S. private business sector for the quarterly period 1948-1 to 1978-11, by including energy price and capital and labor resource formations in the model. One of his finding in this study is that a rise in the real price of energy leads to a significant decline in the real output per the flow of capital services. Therefore, energy price may not belong in our model since it may be causally be related to the explanatory variable change in gross domestic product. In fact, we added real energy price to our models, but it did not improve the results.
The three models suggest that the later CAA amendments have not contributed as much to cleaner air as the earlier
CAAs, as shown in the estimates. This is probably because national average ambient air concentration levels for TPM and
SOx have met the standards since around 1970, and CO levels have met the standards since around 1980, even though many metropolitan cities still continue to exceed ambient air quality standards for at least one pollutant. Table 7 Estimates of TPM Ambient Air Level Model, 1960-1990
Dependent variable: TPM ambient air concentration (/xg/m3/cap) x 10~5
Independent Estimated parameters
variables Original mode C.O. model
Intercept 16,453 ***) 16.661 ***) (4,356) (4.197)
CAA 70 -7,007 ***) -7.487 ***) (-5.561) (-4.989)
CAA 77 -6.396 ***) -5.636 ***) (-6.226) (-4.129)
CAA 90 --
CHLN(GDP/POP) 28.004 36.354 **) (1,456) (2.196)
CHLNPOP 1978.032 ***) 1939.072 ***) (7.915) (6.525)
R square 0.956 0.969
N 31 31 II a D 0.848 1.375
Chi square 4.064
Notes: C.O. = Cochrane Orcut t- statistics are in parenthesis ***) significant at the .01 level **) significant at the .05 level *) Significant at the .10 level Table 8
Estimates of Sox Ambient Air Level Model, 1962-1992
Dependent variable: Sox Ambient Air Concentration per capita (/Ltg/m3-cap) xl0'5
Independent Estimated parameters
variables Original model C.O. model
Intercept 20.243 ***) (3,902) (3.892)
CAA 70 -20.554 *-'*) -20.572 ***) (-12.067) (-12.082)
CAA 77 -3.149 ***) -8.147 ***) (-5.868) (-5.899)
CAA 90 -4.933 **) -4.977 **) (-2.123) (-2.128)
CHLN(GDP/POP) 44.832 *) 44.729 *) (1.741) (1.712)
CHLNPOP 1940.594 ***) 1942.047 ***) (4.709) (4.698)
R squared 0.970 0.970
N 31 31
DW = d 2.046 2.010
Chi squared 16.193
Notes: C.O. Cochrane Orcut t-statistics are in parenthesis ***) significant at the .01 level **) significant at the .05 level *) significant at the .10 level Table 9
Estimates of CO Ambient Air Level Model, 1970-1992
Dependent variables CO ambient air concentration per capita (mg/m3-cap)x 10~5
Independent Estimated parameters
variables Original model C.O. model
Intercept 19.05' 21.995 (1.321) (1.356)
CAA 70 _ -
CAA 77 -26.734 ***) -26.075 ***) (-9.544) (-7.332)
CAA 90 -17,644 ***) -15„764 ***) (-3.671) (-3.006)
CHLN(GDP/POP) 27.319 30,676 (0.467) (0.518)
CHLNPOP 4435.617 ***) 4083.277 ***) (3.295) (2.693)
R square 0.902 0.908
N 22 22 »d o £ ii 1.544 1.779
Chi square 1.780
Notes: C.O. = Cochrane Orcut t-statistics are in parenthesis ***) significant at the .01 level **) significant at the .05 level *) significant at the .10 level CONCLUSION
This study developed economic- air pollution models using the least squared econometrics regression approach. U.S. data over the 1960- 1992 period is used in the models. For this, the three states of the environment, namely the ambient air concentration levels of total particulate matter (TPM), sulfur oxide (Sox) , and carbon monoxide (CO) have been treated as dependent variables. There are some difficulties in determining the explanatory variables since many of the variables, which influence the ambient air levels, may be casually related to other explanatory variables. There is no doubt that increasing the number of observations could significantly improve the models, but of course this will take time.
It does seem appropriate, however, to offer three tentative conclusions. First, despite the increase in gross domestic product (GDP), there is a significant improvement in the national ambient air quality at least for two ambient air concentration levels observed: total particulate matter (TPM) and sulfur oxide (SOx). In the carbon monoxide (CO) model this improvement is not significant, perhaps because of the limited number of observation available in this model. Second, this improvement may have been related to the increase of marginal product, the ratio between the change in gross domestic per capita and the change in energy consumption input since 1970, and the improvement in techniques to prevent pollution
(processes, plant operations, and emission control devices).
This improvement may have lowered the emission rate. Third, the Clean Air Acts (CAA) have played a significant positive role in ambient air quality performance through reducing the emission rate (emission per quantity of the total output), at least for the three ambient air concentration levels observed in this study. Figure la U.S. Trends in Ambient Air Quality for TPM, SOx, and Ozone Pollutants, 1970-1992
Ambient Air Quality, 1970-1992 (TPM, SOx, Ozone) 200
§150
fes ^100 “B> 50
0 1970 75 80 85 90 92
------TPM Ozone ------SOx
Source: Environmetal Quality, 1972 and 1991, Statistical Abstract of the US, 1994 from the EPA. Notes:The available data for ozone starts in 1974, while for TPM finishs in 1990. Figure lb U.S. Trends in Ambient Air Quality for N02, CO, and Lead Pollutants, 1970-1992
Ambient Air Quality, 1970-1992 (N02, CO, Lead)
— _ ___ N02 CO ------Lead
Source: Environmental Quality, 1991, 1990 and 1972, Statistical Abstract of the US, from the EPA. Notes: The available data for N02 starts in 1974, while for lead starts in 1975. Figure 2 Number of Areas Not Attaining Air Pollution Standards, by Pollutant, 1978 and 1985
Areas Not Attaining Air Pollution Standards, 1978 and 1985 700 600 *500 |400 'o 1300 E 2200 100 0 Ozone TPMCO S02 N02
■ 1978 1985
Source: State of the Environment, 1987 from the EPA Figure 3
Air Pollution Abatement Expenditures by Sources
1972 - 1991
Air Pollution Abatement Expenditures 1972-1991
Total Mobile sources Stationary sources
Sources: Statistical Abstract of the U.S., 1994, Survey of Current Business, February 1984. Figure 4 U.S. Trends in Energy Consumption per Gross Domestic Product, 1960-1992
Energy Consumption per GDP, 1960-1992
Source: Calculated from Economic Report of the President, 1991 and 1994, Annual Energy Review, 1991 Figure 5 Energy Conservation in Industrial Sector , 1960-1985
Industrial Energy Consumed per Industrial Output, 1960-1985
Source : Annual Energy Review, 1989 Figure 6 Motor Vehicles Efficiency, 1960-1990
Motor Vehicle Efficiency, 1960-1990 25
0 20 m »• ■ •1 § hj1 5 ------^ <5 & „10
5
0 i i i i i i i i i i i i i i i i i i i i i i i i t ri ii 1960 65 70 75 80 85 90
...... Passenger Cars
------All Motor Vehicles
Source : Annual Energy Review, 1991 Note: In period 1960-1965 passenger cars included motor cycles All motor vehicles include passenger cars, motor cycles, buses, and trucks. BIBLIOGRAPHY
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