Reconciling China’s economic development with global and local environmental protection Mun Ho (Harvard U. & Resources for the Future) Dale Jorgenson (Harvard University) Mitigation of air pollution and climate Change in China Workshop Oslo, October 17-19 2004 A research project of Institute of Environmental Science & Engr, Tsinghua University Harvard University Center for the Environment Hao Jiming, Wang Shuxiao, Liu Bingjiang, Lu Yongqi Sue Greco, James Hammitt, Mun HO, Dale Jorgenson, Jon Levy, Chris Nielsen, ZHOU Ying http://www.ksg.harvard.edu/cbg/ptep/ http://environment.harvard.edu/activities/sponsored/chinaproject/ Topics • Intake Fraction method to estimate health damages from air pollution • Contrast with World Bank (1997) Clear Water Blue Skies method of Lvovsky et. al. (1997,2000) • Estimate of damages by industry; by health effects; etc. • Use of ‘green tax’ policies to reduce damages and promote tax reform and economic efficiency Methodology Goal: Efficient national policies to reduce local health damages, also calculate coincident CO2 reductions Step 1: Estimate marginal damages by industry (in terms of yuan of damages per yuan of output). Step 2: Estimate marginal damages by type of fuel Step 3: Construct an economic model that traces output and inter-industry transactions, including fuel use; traces consumption and investment. Use model to simulate ‘green tax’ policy effects. Table 1 Sector emissions in 1997 Sector 1 2 7 8 11 12 13 14 15 17 23 25 26 32 Agriculture Coal mining and processing Food products, tobacco Textile goods Paper products, printing Petroleum refining & coking Chemical Nonmetal mineral products Metals smelting & pressing Machinery and equipment Electricity, steam, hot water Construction Transport & warehousing Health, Educ., other services Households Total TSP (kton) Combustion 160 181 310 166 201 72 672 2549 632 125 3953 121 361 416 462 11369 Process 0 65 16 3 92 76 200 10756 1244 24 72 0 0 0 0 12974 SO2 (kton) Combustion Process 367 163 467 332 254 112 1216 1525 739 185 7846 414 609 714 778 17452 0 29 11 2 8 51 214 654 925 4 49 0 0 0 0 2089 Table 2 Emissions, fuel use and output 1997 1 2 7 8 11 12 13 14 15 17 23 25 26 32 Sector Agriculture Coal mining and processing Food products, tobacco Textile goods Paper products, printing Petroleum refining & coking Chemical Nonmetal mineral products Metals smelting & pressing Machinery and equipment Electricity, steam, hot water Construction Transport & warehousing Health, educ., other services Households Totals TSP Gross Coal Oil (combus) Output use use (kton) (bil. yuan) (mil tons) (mil tons) 159.7 2467.7 12.7 9.61 180.7 238.0 40.8 2.72 310.4 1371.3 33.2 1.74 166.1 913.0 21.8 1.06 200.5 445.5 18.1 1.34 71.6 308.5 20.0 8.75 671.8 1488.8 148.5 32.08 2548.8 874.9 206.7 10.34 632.0 750.2 183.2 8.81 125.4 882.1 36.2 3.81 3953.0 380.8 384.9 14.80 120.8 1738.6 9.4 20.63 361.0 506.6 17.5 23.07 416.0 658.5 33.5 1.15 461.7 37.1 2.11 20067 11369.1 1350.3 189.8 Concentration in major cities in China 400 350 micro gram/m3 300 250 TSP SO2 200 150 100 50 0 1988 1990 1992 1994 1996 1998 2000 2002 2004 GDP and energy use 3.5 3 2.5 2 GDP Coal Oil 1.5 1 0.5 0 1990 1992 1994 1996 1998 2000 2002 2004 THE PROBLEM • Have one number for pollutant concentration which is believed to be the determinant of health effects and other environmental damage • Have emissions for each industry • Need to assign each industry’s contribution to the ambient concentration of PM and SO2 • Not feasible to model each emission source • Lvovsky et. al. (1997,2000) method • Intake Fraction (iF) method Lvovsky et. al. (1997,2000) innovation: C x = γ x ,low EM x ,low + γ x ,med EM x ,med + γ x ,high EM x ,high 3 γ’s derived from air dispersion models Each industry assigned to low, medium or high stack height Strength: simple to implement, comprehensive Weakness: x=TSP, EM(TSP) is only primary TSP, ignoring secondary TSP; not all Cx due to human activity; not all Cx due to local emissions; Intake fractions for Electricity, Iron&Steel, Cement, Chemicals, Transportation (Wang Shuxiao, Liu Bingjiang, Zhou Ying et.al. ) - fraction of emissions from a source that is eventually ingested - samples of plants from 5 cities - used short range air dispersion model (ISCLT) to calculate concentration due to primary PM and SO2 - used Calpuff model to long range effects, secondary SO4,NO3 - used detailed population location data to estimate exposures - scaled up to national intake fractions using national samples n iFix = ∑ ( POPj × Concijx × BR) / EM ix j =1 iF calculation in Jinan city: Population, concentration, pop*conc Estimated intake fractions for China industries iF (50km domain) TSP SO2 Coal mining Food products Chemical Cement Metals smelting Electricity Transportation Transp (NO3/NOx) Health,Educ,Service 3.28E-06 3.46E-06 3.75E-06 2.16E-06 7.72E-05 6.61E-06 3.99E-06 6.03E-06 2.38E-06 Secondary iF (whole domain) TSP SO2 iF(SO4/SO2) 1.05E-05 1.66E-05 4.40E-06 1.05E-05 1.66E-05 4.40E-06 9.84E-06 1.98E-05 4.40E-06 1.04E-05 1.20E-05 4.40E-06 1.13E-05 1.81E-05 4.40E-06 4.32E-06 4.76E-06 4.40E-06 7.72E-05 1.66E-05 4.40E-06 3.10E-06 3.86E-05 1.66E-05 4.40E-06 Dose-response and valuations of health effects, base parameters Health Effect Due to PM Mortality Respiratory hospital admissions Emergency room visits Restricted activity days LRI/child(astmatic) Asthma attacks Chronic bronchitis Respiratory symptoms Due to SO2 Mortality Chest discomfort Respir. systems/child Dose-response per million/ g/m 3 Valuation yuan 1997 1.95 12 235 57500 23 2608 61 183000 370000 1751 142 14 80 25 48000 3.7 1.95 10000 5.0 370000 6.2 6.2 Health damages due to outdoor air pollution, 1997 iF method LH method Base param High param Base param Damage (mil yuan) 137000 349500 230800 (% of GDP) (1.84%) (4.69%) (3.10%) Due to PM 116700 - primary PM 56100 - secondary PM 60600 Due to SO2 20300 218400 12400 Marginal damages, total damages by industry Food products Chemical cement Metals smelting Electricity Construction Transportation Health,Educ,Service Households MD Value yuan/yuan mil. Yuan 0.00262 3594 0.00607 9041 0.01960 17148 0.00875 6563 0.09362 35654 0.00275 4786 0.02668 13519 0.01492 9824 8035 Share % 2.6 6.6 12.5 4.8 26.0 3.5 9.9 7.2 5.9 Marginal damages from fuels, averaged over all industries Coal Oil Gas per unit fuel 93.84 yuan/ton 54.28 yuan/ton 0.08 yuan/1000m3 per yuan of fuel 0.5751 yuan/yuan 0.0249 yuan/yuan 0.0002 yuan/yuan National policies to reduce local and global pollution Efficient general policy is tax on emissions but not feasible - analyze 2 policies: i) tax on output proportional to health damage caused ii) tax on fuels proportional to health damage caused - model calculates both costs and benefits of pollution control : - estimate reduction in health damages - estimate change in output of each sector, change in Consumption, change in GDP growth (some cost, e.g. pollution control equipment, not explicitly considered) Methodology for cost-benefit analysis - estimate a base case growth path of the economy where pollution taxes = 0 - estimate alternative case where tax(j) = MD(j); new revenues used to cut other pre-existing taxes - compare the time paths of both cases 40000 4 35000 3.5 30000 3 25000 2.5 20000 2 15000 1.5 10000 1 5000 0 1997 0.5 0 2002 2007 GDP 2012 TSP 2017 SO2 Energy 2022 Energy (Bil. tons coal equiv.) GDP (Bil. Yuan); Emissions (ktons) Figure 1: GDP, Energy and Emissions Projected in Base Case Base case projection of the economy (30 year growth) Urban population (million) GDP (billion 1997 yuan) Coal Use (million tons) Oil Use (million tons) Carbon Emissions (million tons) Primary particulate emissions (m tons) Combustion TSP emissions Noncombustion TSP emissions Low height sources SO2 emissions (million tons) NOx (transportation) (million tons) Premature Deaths (1,000) Health Damage/GDP 1997 368 7,630 1,390 210 900 24.23 11.59 12.64 2.04 19.98 3.24 97 1.9% 2006 432 15,000 2,090 440 1,460 17.00 8.63 8.37 2.24 25.76 6.26 137 2.4% 2026 568 33,500 2,750 960 2,260 15.69 8.54 7.16 3.05 34.59 11.60 232 3.6% growth rate 1.46% 5.06% 2.30% 5.16% 3.12% -1.44% -1.01% -1.88% 1.35% 1.85% 4.34% 2.96% Effects of an output tax based on pollution damages Variable GDP Consumption Investment Coal use Carbon emissions Primary particulate emissions Combustion TSP Noncombustion TSP High height source (Electricity) Low height sources SO2 Emissions NOx (transportation) Premature Deaths Value of Health Damages Change in other tax rates Pollution tax/Total tax revenue Effect in 1st Year -0.04% -0.06% 0.06% -3.95% -3.41% -3.08% -4.25% -2.01% -9.21% -1.84% -4.56% -3.80% -3.21% -3.53% -8.5% 9.1% Effect in 20th Year +0.18% -0.01% +0.55% -3.36% -2.41% -2.30% -4.00% -1.05% -7.42% -0.92% -4.00% -2.93% -2.88% -3.01% -6.1% 6.0% Effects of an output tax based on pollution damages Sector Agriculture Coal mining Crude petroleum mining Food products, tobacco Petroleum refining Chemical Nonmetal mineral prod Metals smelting Electricity, steam, Construction Transport & warehousing Post & telecommunication Commerce & Restaurants Social services Health, Educ., services Price 0.00 0.19 -0.58 -0.40 -0.44 0.25 1.63 0.80 5.76 0.65 2.24 -0.11 -0.98 0.71 1.54 Quantity 0.06 -3.85 -0.83 0.48 -1.20 -0.86 -2.10 -1.68 -6.69 -0.28 -3.10 -0.26 0.57 -1.03 -1.05 Effects of a fuel tax based on damages Variable GDP Consumption Investment Coal use Carbon emissions Primary particulate emissions Combustion TSP Noncombustion TSP High height source (Elect.) Low height sources SO2 emissions NOx (transportation) Premature Deaths Value of Health Damages Change in other tax rates Pollution tax/Total tax revenue 1st year -0.04% -0.06% +0.07% -13.2% -10.7% -6.0% -11.8% -0.6% -12.4% -11.0% -10.2% -1.0% -10.7% -10.7% -2.8% 2.72% 20th year +0.05% -0.02% +0.20% -18.2% -12.5% -9.0% -16.3% -0.7% -16.3% -15.3% -14.0% -1.6% -14.3% -14.0% -2.1% 1.99% Effects of a fuel tax based on damages Sector Price Quantity Agriculture Coal mining Crude petroleum mining Food products, tobacco Petroleum refining Chemical Nonmetal mineral prod Metals smelting Electricity, steam, Construction Transport & warehousing Post & telecommunication Commerce & Restaurants Social services Health, Educ., services 0.08 14.11 -0.03 -0.05 1.08 0.34 0.77 0.49 2.39 0.29 0.15 0.07 -0.30 0.12 0.23 0.06 -13.25 -0.49 0.20 -1.28 -0.34 -0.57 -0.78 -2.69 -0.01 -0.21 -0.08 0.31 -0.09 -0.17 Figure 3: Change in PM Emissions and Concentrations due to a pollution tax on fuels 0 -2 -4 Percentage Change -6 -8 -10 -12 -14 -16 -18 -20 1997 2002 2007 2012 2017 Emissions Concentration Damages 2022 Conclusions - Magnitude of control costs of well designed policies is much smaller than the local benefits, even ignoring global benefits. - Local pollution reduction would very likely involve carbon emission reduction. -Green tax policies help tax reform goals - The short run adjustment costs may be higher than estimated here leading to less control efforts by China if unaided by outside world. Hence, rich countries may play a very important role in tipping the balance towards greater efforts and sooner. Reconciling China’s economic development with global and local environmental protection Mun Ho (Harvard U. & Resources for the Future) ho@rff.org Dale Jorgenson (Harvard University) djorgenson@harvard.edu Papers available at: www.ksg.harvard.edu/cbg/ptep/ http://environment.harvard.edu/uce/ Economic activity, pollution and health: A general equilibrium framework 1) Emissions = f( output, fuel use, control technology) 2) Concentration = f(Emissions, meteorology, geography) 3) Health effects = f(Concentration, population; DR) 4) Value of Damage = f( Health effects, valuation(income)) 5) Costs of control = f( level of reduction, control tech, ...) 6) f(output, prices, income, consumption, investment) = 0 7) Costs of control versus Value of Damage reduction Lvovsky-Hughes simple method for all sectors: ⎛ ⎜ ⎜ ⎝ 1) EM jxt = σ jxQI jt + ∑ f ψ jxf AF x=PM10,SO2 f=coal, oil, gas j = sector 1,2,... ⎞ ⎟ jft ⎟ ⎠ EM : emissions QI : sector output AF : fuel input 2) EM cx = ∑ EM jx j∈c c=high, medium, low height 3) CxN = γ high EM high, x + γ med EM med , x + γ low EM low, x C : concentration LH Method, continued: DR : dose-response ⎛ ⎞ ⎝ ⎠ 4) HEht = ∑ x ⎜⎜ DRhx (CxtN −α x )POPtu ⎟⎟ h=Mortality,CB,.... 5) Damageht =Vht HEht HE : health effect POP: population V : valuation in ¥ Damages by sector. Marginal damage per unit emissions in sector j: MD jx = ∑Vht DRhxγ j POPt u er h Marginal damage per yuan(1997) of output: ⎛ EM jx ,tb ⎞ ⎜ ⎟ MD = ∑ MD jx ⎜ QI j ,tb ⎟⎠ x ⎝ O j Marginal total damage of sector j: MTD jt = MD Ojt QI jt Sector j's share of total marginal damages: MTD jt / ∑ MTD jt j iF method to estimate sector damages: Health effects due to sector j: N ⎛ iF xj EM xj HE hjS = ∑ ⎜ DRhx ⎜ BR x ⎝ ⎞ ⎟ ⎟ ⎠ Marginal total damages due to j: ⎛ iFxjN EM xj MTD jt = ∑ Vht HE = ∑ Vht ∑ ⎜ DRhx ⎜ BR h h x ⎝ S hj ⎞ ⎟ ⎟ ⎠